Offshore structure design, Sigve Hamilton Aspelund

1. Offshore Structure Design
Sigve Hamilton Aspelund

2. Day 1:
• Introduction to offshore structures
• Different types of offshore structure
• Loads effects on offshore structure
• Design Parameters Specifications
• General Design Considerations
• Basics design of offshore platforms

3. Rig Types/ Classifications/ Functions

4. Jack up
• Retractable legs that can be lowered to the sea bed.
• The legs support the drilling rig and keep the rig in position.

5. Jack up
• Unaffected by the weather during the drilling phase
• The safety valve is located on deck
• It does not need anchoring system
• It does not need heave compensator
• (permanent installation in the drilling phase)
• It has removable drill tower
• Depth limit is 150 meters
• It is unstable under the relocation
• It depends on the tug for moving

6. Semi submersible
• Portable device that consists of a deck placed on
columns attached to two or more pontoons.
• During operation tubes are filled with water and lowered beneath
the sea surface.

7. Semi submersible
• The vessel normally kept in position by anchors, but may also have
dynamic positioning equipment (DP).
• Usually have their own propulsion machinery (max. depth approx. 600
to 800 meters).
• The most common type is the "semi-submersible drilling rig".

8. Drilling ship
• In very deep water (2300m) drill ships are used for drilling the well.
• A drillship is easy to move and is therefore well suited for drilling in deep
waters, since it is well suited for dynamic positioning.
• It requires relatively little force to remain in position.

9. Condeep platform
• Condeep platform is the denomination of a series of oil platforms
that were developed in Norway to drill for oil and gas in the North Sea.
• The name comes from
the English“concrete deep water structure", or deep
structure of concrete.
• The platforms rest on thick concrete tanks that are on the ocean
floor and acts as an oil stock.
• From these sticks it as one, three or
four slender hollow columns, which is about 30 feet above the surface.

10. Condeep platform
• It was Stavanger company Norwegian Contractors who developed the
concept of Condeep platforms in 1973, after the success of the concrete
tank at the Ekofisk field.
• Condeep platforms are not produced anymore.
• The large concrete platforms are out competed by new,
cheaper floating rigs and remote-controlled underwater installations.

11. Jacket platform
• The most widely used platform in the North Sea bearing structure is
built as framed in steel
• Platform are poles fixed to the bottom
• The construction is susceptible to corrosion
Has no storage tank, but must be associated pipeline network.
• Edvard Grieg Project Update - May 2015

12. Tension leg platform
• A tension leg platform is a floating and vertically anchored platform
or buoy which is normally used for offshore production of oil or natural
gas, and is especially suitable for water depths exceeding
300 meters. We usually use rods or chains to keep the platform in place.

13. Tension leg platform
• Affordable solution
• Quick to install
• Can be equipped entirely by countries
• Can be used on very deep
• Can be moved when a field is empty
• Because of movement of water required
compensation equipment

14. Well head plattform
• Can be an alternative to production facilities on the seabed, especially
where water depth is small, as in the southern part of the north sea.
• The wellhead platform is an unmanned small platform, which
we can remotely control from a “mother platform".
Valve tree is dry.

15. FPSO
• What is FPSO (Floating Production Storage and Offloading) System?
• The FPSO (Floating Production Storage and Offloading) system is used
extensively by oil companies for the purpose of storing oil from the oil
rigs in the middle of the ocean and in the high seas.
• It is one of the best devised systems to have developed in the oil
exploration industry in the marine areas.

16. • The FPSO, as its name suggests, is a floating contraption that
allows oil rigs the freedom not just to store oil but also to produce or
refine it before finally offloading it to the desired industrial sectors,
either by way of cargo containers or with the help of pipelines built
underwater.
• The use of this system ensures that shipping companies do not have
to invest even more money by ferrying the raw and crude oil to an
onshore refinery before transferring it to the required industrial
areas.
• In simple terms, the FPSO saves time and money effectively.

17. • Understanding FPSO
• The following steps will elaborate on the different functions
performed by the FPSO as a system:

18. • Production: The ‘P’ in the FPSO stands for production.
• Production means evolving the crude oil obtained from the deeper
parts of the ocean.
• The FPSO is enabled and fitted with equipments that would act as a
refinery of sort to distil the oil obtained from the ocean along with
the gases that are emitted.
• This is the main feature of a FPSO as only with the help of this feature
can a FPSO attain the reliability that it enjoys in today’s times.

19. • Storage: This is the second most important feature
and the ‘S’ in the acronym FPSO.
• Second-most important because just as it is important
to filter the excavated oil from its oceanic reservoirs, it
is equally important to store it well.
• For this purpose, the FPSO is built in such a way that
the tubes and the pipes and the tanks are perfect for
storing the distilled product from the crude raw-
material.
• They are safe and sturdy so as to resist any chances of
unwanted oil spillage and thus contamination of the
marine life-forms.

20. • Offloading: This is ‘O’ in the concept of FPSO.
• The offloading aspect is important when the FPSO has
to transfer its contents into ships designed as oil
carriers or to pipelines that act as transfer agents.
• In simple terms, offloading refers to removing the
cargo in a FPSO and transferring it to another cargo-
carrying vessel or equipment.
• The offloading part is very tricky as the process is
carried out in the middle of the sea and thus requires
a lot of concentration and focus in order to avoid any
sort of spillage.

21. • Important Information
• It has to be noted that even while the entire working process of a
FPSO is very intriguing, the designing aspect is very amazing.
• This is because the system has to be constructed in such a way that it
remains invulnerable to the constant changes that take place in the
middle of the ocean or the seas.
• The various tubes and pipes have to be built in such a way that they
do not affect the pureness of the oil obtained and the same time do
not get broken because of heavy storms or tide-currents.

23. Conclusion
• The FPSO as a system has been in use from the seventies when
major-scale oil exploration began in the oceans and seas.
• In these past four decades, given the way oil exploration industry has
been on the rise, the use and relevance of a FPSO has increased even
more.
• The system is fool proof, enables cost efficiency and thus becomes a
very major asset when it comes to excavating oil in the marine areas.

24. Spar Platforms
• For drilling wells beyond 10,000 feet, naval architects have designed a
type of drilling and production platform which has a hollow cylindrical
hull that can descend up to a sea depth of 200 meters.
• This are called Spar Platforms.
• It is secured to the ocean floor by a complex network of cables and
tendons.
• The weight of the cylindrical hull stabilises the
drilling platform and caters for the drilling risers
to descend up to the drilling well on the sea floor.

25. Subsea Production System
• As the name suggests, this system is based on the idea where
wellheads are mounted on the sea floor after the wells have been
drilled by one of the many deep sea drilling platforms.
• Shell Ormen Lange - a journey in energy

26. • The wellheads are remotely controlled and their automated system is
so designed that it allows for transporting the oil or gas directly to the
production facilities using a network of undersea pipelines and risers.
• Apart from those mentioned above, shuttle tankers are also used in
offshore oil production systems.
• As technology advancements are progressively made, deep water
exploration possess superior challenges for all the operating parties.
• These massive structures are home to some highly improved and
advanced systems, machineries and equipments for carrying out the
coveted job of offshore drilling.

27. The Guyed Tower
• ABSTRACT
The guyed tower is an offshore platform that rests on a spud can or
bearing foundation and is held upright by multiple guylines.
• A simplified procedure for calculating the wave-induced dynamic
response of this compliant tower is presented.
• Also, the dynamic characteristics that allow the structure to safely
resist large ocean waves is discussed.
• A large scale test model of the tower has been installed in 300 feet of
water in the Gulf of Mexico to verify the validity of the conclusions
drawn.

28. • INTRODUCTION
A new compliant offshore structure, the guyed tower, has been proposed
as a deep water production and drilling platform.
• The concept as proposed has two major advantages over other proposed
schemes; first, the structure can be fabricated and installed using presently
available equipment and technology; second, this production platform is
anticipated to be less expensive to build, and maintain than present
alternatives proposed for water depths from 600 to 2000 feet.
• This paper describes the basic guyed tower concept and illustrates the
design procedures used to insure that the compliant structure will safely
withstand severe environmental forces and yet be slender, lightweight and
economical.

29. • Prototype Guyed Tower
The guyed tower is a trussed structure that rests on the ocean floor,
extends upward to a deck supported above the waves, and is held upright
by multiple guylines.
• The base of the tower is supported on a truss reinforced shell foundation
called a spud can.
• During installation the spud can is forced into the ocean bottom until the
desired load carrying capability is attained.
• The amount of design penetration is of course dependent on the load to be
carried and the site soil parameters.

30. • The main truss of the tower as currently proposed would have four equally
spaced legs connected primarily with x-bracing.
• However, other geometric configurations could be used.
• For a structure supporting 24 wells in 1500 feet of water, the legs would be
spaced 100 feet apart and range in size from 5 to 8 feet in diameter.
• Ideally the deck would be designed to support all the equipment to drill
and produce a large number (20 to 40) of wells.
• The deck for the 24 well 1500 ft structure would have two levels 150 feet
on a side and would support 7500 tons deck payload, which is adequate for
many areas of the world.
• To carry larger payloads, the support capacity of the tower truss, spud can,
and guying system would have to be increased proportionally.

31. Deep-water guyed tower concept

32. 1, 2) Conventional fixed platforms;
3) Compliant tower;
4, 5) Vertically moored tension leg and mini-tension leg platform;
6) Spar;
7,8) Semi-submersibles;
9) Floating production, storage, and offloading facility;
10) Sub-sea completion and tie-back to host facility.

33. Loads
Offshore structure shall be designed for following types of loads:
• Permanent (dead) loads
• Operating (live) loads
• Environmental loads
• Wind load
• Wave load
• Earthquake load
• Construction - installation loads
• Accidental loads
• The design of offshore structures is dominated by environmental loads, especially
wave load

34. Permanent Loads
• Weight of the structure in air, including the weight of ballast.
• Weights of equipment, and associated structures permanently
mounted on the platform.
• Hydrostatic forces on the members below the waterline.
• These forces include buoyancy and hydrostatic pressures.

35. Operating (Live) Loads
• Operating (Live) Loads:
• Operating loads include the weight of all non permanent equipment
or material, as well as forces permanent equipment or material,
generated during operation of equipment.
• The weight of drilling, production facilities, living quarters, furniture,
life support systems, heliport, consumable supplies, liquids, etc.
• Forces generated during operations, e.g. drilling, vessel mooring,
helicopter landing, helicopter landing, crane operations.

36. • Following Live load values are recommended in BS6235:
• Crew quarters and passage ways: 3.2 KN/m²
• Working areas: 8,5 KN/m²

37. Wind Loads:
• Wind load act on portion of platform above the water level as well as
on any equipment, the water level as well as on any equipment,
housing, derrick, etc.
• For combination with wave loads, codes recommend the most
unfavorable of the following two loadings:
• 1 minute sustained wind speeds combined with extreme waves
• 3 second gusts

38. • When, the ratio of height to the least horizontal dimension of
structure is greater than 5, then API-RP2A requires the dynamic
effects of the wind to be taken into account and the flow induced
cyclic wind loads due to vortex shedding must be investigated.

39. Wave load:
• The wave loading of an offshore structure is usually the most
important of all environmental loadings.
• The forces on the structure are caused by the motion of the water
due to the waves
• Determination of wave forces requires the solution of,
• a) Sea state using an idealization of the wave surface profile and the
wave kinematics by wave theory
• b) Computation of the wave forces on individual members and on the
total structure, from the fluid motion.

40. • Design wave concept is used, where a regular wave of given height
and period is defined and the forces due to this wave are calculated
using a high-order wave theory.
• Usually the maximum wave with a return period of 100 years, is
chosen.
• No dynamic behavior of the structure is considered.
• This static analysis is appropriate when the dominant wave periods
are well above the period of the structure.
• This is the case of extreme storm waves acting on shallow water
structures.

41. Wave theories
• Wave theories describe the kinematics of waves of water
• They serve to calculate the particle velocities and accelerations and
the dynamic pressure as functions of the surface elevation of the
waves.
• The waves are assumed to be long-crested,
i.e. they can be described by a two dimensional
flow field, and are characterized by the
parameters: wave height (H), period (T)
and water depth (d).

42. Wave forces on structural members
• Structures exposed to waves experience forces much higher than
wind loadings.
• The forces result from the dynamic pressure and the water particle
motions.
• Two different cases can be distinguished:
• Large volume bodies, termed hydrodynamic compact structures,
influence the wave field by diffraction and reflection. The forces on
these bodies have to be determined by calculations based on
diffraction theory.

43. • Slender, hydro-dynamically transparent structures have no significant
influence on the wave field. The forces can be calculated in a straight-
forward manner with Morison's equation. The steel jackets of
offshore structures can usually be regarded as hydro-dynamically
transparent.
• As a rule, Morison's equation may be applied when D/L < 0.2, where
D is the member diameter and L is the wave length.
• Morison's equation expresses the wave force as the sum of,
• An inertia force proportional to the particle acceleration
• A non-linear drag force proportional to the square of the particle velocity

44. Earthquake load:
• Offshore structures are designed for two
levels of earthquake intensity.
• Strength level: Earthquake, defined as
having a "reasonable likelihood of not
being exceeded during the platform's life"
(mean recurrence interval ~ 200 - 500
years), the structure is designed to
respond elastically.

45. • Ductility level:
• Earthquake, defined as close to the "maximum credible earthquake"
at the site, the structure is designed for inelastic response and to have
adequate reserve strength to avoid collapse. strength to avoid
collapse.

46. • Ice and Snow Loads:
• Ice is a primary problem for marine structures in the arctic and sub-
arctic zones.
• Ice formation and expansion can generate large pressures that give
rise to horizontal as well as vertical forces.
• In addition, large blocks of ice driven by current, winds and waves
with speeds up to 0,5 to 1,0 m/s, may hit the structure and produce
impact loads.

47. • Temperature Load:
• Temperature gradients produce thermal stresses.
• To cater such stresses, extreme values of sea and air temperatures
which are likely to occur during the life of the structure shall be
estimated.
• In addition to the environmental sources, accidental release of
cryogenic material can result in temperature increase, which must be
taken into account as accidental loads.
• The temperature of the oil and gas produced must also be
considered.

48. • Marine Growth:
• Marine growth is accumulated on submerged members. Its main
effect is to increase the wave forces on the members by increasing
exposed areas and drag coefficient due to higher surface roughness. It
is accounted for in design through appropriate increases in the
diameters and masses of the submerged members.

49. • Installation Load
• These are temporary loads and arise during
fabrication and installation of the platform or
its components.
• During fabrication, erection lifts of various
structural components generate lifting forces,
while in the installation phase forces are
generated during platform load out,
transportation to the site, launching and
upending, as well as during lifts related to
installation.

50. • All members and connections of a lifted component must be
designed for the forces resulting from static equilibrium of the lifted
weight and the sling tensions.
• Load out forces are generated when the jacket is loaded from the
fabrication yard onto the barge.
• Depends on friction co-efficient.

51. Accidental Load Accidental Load :
• According to the DNV rules , accidental loads are loads, which may
occur as a result of accident or exceptional circumstances.
• Examples of accidental loads are, collision with vessels, fire or
explosion, dropped objects, and unintended flooding of buoyancy
tanks.
• Special measures are normally taken to reduce the risk from
accidental loads.

52. Load Combinations Load Combinations:
• The load combinations depend upon the design method used, i.e.
whether limit state or allowable stress design is employed.
• The load combinations recommended for use with allowable stress
procedures are:
• Normal operations
• Dead loads plus operating environmental loads plus maximum live loads.
• Dead loads plus operating environmental loads plus minimum live loads.

53. • Extreme operations
• Dead loads plus extreme environmental loads plus maximum live loads.
• Dead loads plus extreme environmental loads plus minimum live loads
• Environmental loads, should be combined in a manner consistent
with their joint probability of occurrence.
• Earthquake loads, are to be imposed as a separate environmental
load, i.e., not to be combined with waves, wind, etc.

54. Design Parameters Specifications

60. General Design Considerations

62. Basics design of offshore platforms

63. Design of offshore fixed platforms
• The most commonly used offshore platforms in the Gulf of Mexico,
Nigeria, California shorelines and the Persian Gulf are template type
platforms made of steel, and used for oil/gas exploration and
production (Sadeghi 1989, 2001).
• The design and analyses of these offshore structures must be made in
accordance with recommendations published by the American
Petroleum Institute (API).

64. • The design and analysis of offshore platforms must be done taking into
consideration many factors, including the following important parameters:
• Environmental (initial transportation, and in-place 100-year storm
conditions)
• Soil characteristics
• Code requirements (e.g. American Institute of Steel Construction “AISC”
codes)
• Intensity level of consequences of failure
• The entire design, installation, and operation must be approved by the
client.

65. Different analyses needed for template
platforms
• Different main analyses required for design of a template (jacket) type
platform are as follows (Sadeghi 2001):
• In-place analysis
• Earthquake analysis
• Fatigue analysis
• Impact analysis
• Temporary analysis
• Loadout analysis
• Transportation analysis
• Transportation analysis
• Appurtenances analysis
• Lift/Launch analysis
• Upending analysis
• Uprighting analysis
• Unpiled stability analysis
• Pile and conductor pipe drivability analysis
• Cathodic protection analysis
• Installation analysis

66. Software used in the platforms design
• To perform a structural analysis of platforms, the following software
may be used (Sadeghi 2001):
Structural analysis:
• SACS
• FASTRUDL
• MARCS
• OSCAR
• StruCAD
• SESAM
Pile analysis:
• Maxsurf Hydromax
• Seamoor for hydrodynamics calculations
• GRLWEAP
• PDA
• CAPWAP

67. Day 2:
• Design methodology for floating structure
• Different types of floating structure
• Basic concept and dynamic analysis
• Structure optimum configuration
• Structure Reliability

68. Design methodology for floating structure

97. Different types of floating structure

109. Basic concept and dynamic analysis
• Basic Concepts of Analysis
• The software uses the Finite Element Method (FEM).
• FEM is a numerical technique for analyzing engineering designs.
• FEM is accepted as the standard analysis method due to its generality
and suitability for computer implementation.
• FEM divides the model into many small pieces of simple shapes called
elements effectively replacing a complex problem by many simple
problems that need to be solved simultaneously.

111. • Elements share common points called nodes.
• The process of dividing the model into small pieces is called meshing.
• The behavior of each element is well-known under all possible support and load scenarios.
• The finite element method uses elements with different shapes.
• The response at any point in an element is interpolated from the response at the element nodes.
• Each node is fully described by a number of parameters depending on the analysis type and the
element used.
• For example, the temperature of a node fully describes its response in thermal analysis.
• For structural analyses, the response of a node is described, in general, by three translations and
three rotations.
• These are called degrees of freedom (DOFs).
• Analysis using FEM is called Finite Element Analysis (FEA).

113. • The software formulates the equations governing the behavior of
each element taking into consideration its connectivity to other
elements.
• These equations relate the response to known material properties,
restraints, and loads.
• Next, the program organizes the equations into a large set of
simultaneous algebraic equations and solves for the unknowns.
• In stress analysis, for example, the solver finds the displacements at
each node and then the program calculates strains and finally
stresses.

114. The software offers the following types of studies:
Static (or Stress) Studies.
• Static studies calculate displacements, reaction forces, strains, stresses, and
factor of safety distribution.
• Material fails at locations where stresses exceed a certain level.
• Factor of safety calculations are based on one of four failure criterion.
• Static studies can help you avoid failure due to high stresses.
• A factor of safety less than unity indicates material failure.
• Large factors of safety in a contiguous region indicate low stresses and that
you can probably remove some material from this region.

115. Frequency Studies.
• A body disturbed from its rest position tends to vibrate at certain
frequencies called natural, or resonant frequencies.
• The lowest natural frequency is called the fundamental frequency.
• For each natural frequency, the body takes a certain shape called mode
shape.
• Frequency analysis calculates the natural frequencies and the associated
mode shapes.
• In theory, a body has an infinite number of modes.
• In FEA, there are theoretically as many modes as degrees of freedom
(DOFs).
• In most cases, only a few modes are considered.

116. • Excessive response occurs if a body is subjected to a dynamic load vibrating
at one of its natural frequencies.
• This phenomenon is called resonance.
• For example, a car with an out-of-balance tire shakes violently at a certain
speed due to resonance.
• The shaking decreases or disappears at other speeds.
• Another example is that a strong sound, like the voice of an opera singer,
can cause a glass to break.
• Frequency analysis can help you avoid failure due to excessive stresses
caused by resonance.
• It also provides information to solve dynamic response problems.

117. Dynamic Studies.
• Dynamic studies calculate the response of a model due to loads that
are applied suddenly or change with time or frequency.
• Linear dynamic studies are based on frequency studies.
• The software calculates the response of the model by accumulating
the contribution of each mode to the loading environment.

118. • In most cases, only the lower modes contribute significantly to the
response.
• The contribution of a mode depends on the load’s frequency content,
magnitude, direction, duration, and location.
• The objectives of a dynamic analysis include:
• (a) the design of structural and mechanical systems to perform
without failure in dynamic environments, and
• (b) the reduction of vibration effects.

119. Buckling Studies.
• Buckling refers to sudden large displacements due to axial loads.
• Slender structures subject to axial loads can fail due to buckling at
load levels lower than those required to cause material failure.
• Buckling can occur in different modes under the effect of different
load levels.
• In many cases, only the lowest buckling load is of interest.
• Buckling studies can help you avoid failure due to buckling.

120. Thermal Studies.
• Thermal studies calculate temperatures, temperature gradients, and
heat flow based on heat generation, conduction, convection, and
radiation conditions.
• Thermal studies can help you avoid undesirable thermal conditions
like overheating and melting.

121. Design Studies.
• Optimization design studies automate the search for the optimum design based
on a geometric design.
• The software is equipped with a technology to quickly detect trends and identify
the optimum solution using the least number of runs.
• Optimization design studies require the definition of the following:
• Goals or Objectives. State the objective of the study. For example, minimum material to be
used.
• Design Variables. Select the dimensions that can change and set their ranges. For example,
the diameter of a hole can vary from 0.5” to 1.0” while the extrusion of a sketch can vary
from 2.0” to 3.0”.
• Constraints. Set the conditions that the optimum design must satisfy. For example, you can
require that a stress component does not exceed a certain value and the natural frequency to
be within a specified range.
• NOTE: For the non-optimization design study, do not define any goals.

122. Nonlinear Studies.
• When the assumptions of linear static analysis do not apply, you can
use nonlinear studies to solve the problem.
The main sources of nonlinearity are:
• Large displacements, nonlinear material properties, and contact.
• Nonlinear studies calculate displacements, reaction forces, strains,
and stresses at incrementally varying levels of loads and restraints.
• When inertia and damping forces can not be ignored, you can use
nonlinear dynamic analysis.

123. • Nonlinear studies refer to nonlinear structural studies.
• For thermal studies, the software automatically solves a linear or nonlinear
problem based on material properties and thermal restraints and loads.
• Solving a nonlinear problem requires much more time and resources than
solving a similar linear static study.
• The principle of superposition does not apply for nonlinear studies.
• For example, If applying force F1 causes stress S1 and applying force F2
causes stress S2 at a point, then applying the forces together does NOT
necessarily cause a stress (S1+S2) at the point as is the case for linear
studies.
• Nonlinear studies can help you assess the behavior of the design beyond
the limitations of static and buckling studies.

124. • Solving a nonlinear problem requires much more time and resources than
solving a similar linear static study.
• The principle of superposition does not apply for nonlinear studies.
• For example, If applying force F1 causes stress S1 and applying force F2
causes stress S2 at a point, then applying the forces together does NOT
necessarily cause a stress (S1+S2) at the point as is the case for linear
studies.
• Nonlinear studies can help you assess the behavior of the design beyond
the limitations of static and buckling studies.
• Static studies offer a nonlinear solution for contact problems when you
activate the large displacement option.

125. Drop Test Studies.
• Drop test studies evaluate the effect of dropping the design on a rigid floor.
• You can specify the dropping distance or the velocity at the time of impact
in addition to gravity.
• The program solves a dynamic problem as a function of time using explicit
integration methods.
• Explicit methods are fast but require the use of small time increments.
• Due to the large amount of information the analysis can generate, the
program saves results at certain instants and locations as instructed before
running the analysis.
• After the analysis is completed, you can plot and graph displacements,
velocities, accelerations, strains, and stresses.

126. Fatigue Studies.
• Repeated loading weakens objects over time even when the induced
stresses are considerably less than allowable stress limits.
• The number of cycles required for fatigue failure to occur at a location
depends on the material and the stress fluctuations.
• This information, for a certain material, is provided by a curve called the S-
N curve.
• The curve depicts the number of cycles that cause failure for different
stress levels.
• Fatigue studies evaluate the consumed life of an object based on fatigue
events and S-N curves.

127. Structure optimum configuration
• Reinforced Concrete walls, which include lift wells or shear walls, are usual requirements of Multistory
Buildings.
• Constructing the Shear wall in tall, medium and even short buildings will reinforce the significantly and
either more economic than the bending frames.
• By the Shear walls, we can control the side bending of the structure, much better than other elements like
closed frames and certainly the shear walls are more flexible than them.
• However, on many occasions the design has to be based on the off center position of the Lift and stair case
walls with respect to the centre of mass.
• The design in these cases results into an excessive stresses in most of the structural members, unwanted
torsional moments and sways.
• Design by coinciding Stiffness centre and mass of the building is the ideal for a structure.
• In this case there is no eccentricity, but as per IS 1893(1):2002 the minimum eccentricity is to be considered.
• The lateral force in a wall due to rotational moment is given by, Fir =
• ri = Radial distance of shear wall “i”
• F = Design Shear force ed = Design eccentricity

128. • From the above equation, it is observed that the distance of any shear
wall from the centre of stiffness increases, the Shear generated in the
Shear wall is decreased.
• The distance of Shear wall from the Centre of Stiffness is also an
important Criteria for the Stresses generated in the Structural
members and overall behavior of the whole structure.

129. • The nature of stresses generated in the Shear wall according to its
position is also different.
• The shear wall kept at very near to the Centre of stiffness act as a
Vertical bending element and the shear wall kept at corner of the
building are may be in axial compression or in axial tension according
to the direction of the Lateral Force.
• In the bending nature of the wall the drift generated is more compare
to shear walls kept at the corner of the building.
• So it is necessary and important to know, what should be the exact
location of the shear walls that can results in minimum stresses in all
the structural members of the multistoried building.

130. To locate shear wall at radial distance from the centre of mass for optimum
configuration of a multi storey building, by keeping the features of shear wall
constant.
1. To Study the operation of computer aided software “STRUD”
2. Validation of “STRUD” by designing a model building having existing
design data
3. Preparation of problem building drawing from the data
4. Model generation of problem building in “STRUD”
5. Comparison of analysis and design data of four different cases having
various radial position of shear wall generated in the “STRUD”

131. 1) To Study the operation of computer aided software STRUD
• When any type of high-rise structure is going to be design, it should
be analyze as the space frame rather than plain frame or plain grid.
• As the analysis of the high-rise structure as a space frame is very
difficult or it seems to be impossible manually, so we need computer
aided software which helps us to analyze the high-rise structure
• So we are going to use the computer aided software “STRUD”
• And for this we are first of all going to study the operation by the
tutorial of the software

132. 2) Whenever any structure is to be analyzing in any type of computer
aided software first of all validation should be done about the software
that the result given by the software are fair?
For this purpose we are going to take one identical problem whose
design have been done by manually or by any other means and we are
going to input the same data into the above software and compare the
result.

133. 3) We will develop an identical model by using Auto CA 2008 in the
computer. We have taken a structure having six bays in both the
horizontal direction.
From these drawing we have created four different cases by placing the
shear wall radically away from the centre of the stiffness in sequence.
Also we will generate the centerline plan in AutoCAD 2008.

134. 4) After generating the centerline plan in AutoCAD 2008, we will input
the above data in computer aided Structure Designing software.
• The input in the software is done in sequence from bottom to top.
• The design of structure is done in descending order from slab-beam-
column-footing sequence.

135. • 5) After inputting the data in software and after attaching all the
sections / after doing all the preliminary data the analysis is carried
out.
• With the help of this analysis of all the four different cases we will
find the bending moment, shear force, axial force and sway in various
elements of the structure.
• After obtaining the final results from all the above four cases we are
going to make the comparison of ……

136. • Beam moments.
• Column axial forces.
• Storey displacement & drift.
• Percentage of steel in beams.
• Percentage of steel in column.
• Percentage of steel in footings.
• Overall economy of each case.

137. • A typical building (G+8) having three various position of shear wall
and one without shear wall having following data Floor to Floor
height = 3000mm Height of Plinth = 450mm above ground level.
• Depth of Foundation = 2100mm below ground level.
• External Walls =230 mm Internal Walls =115 mm

138. • Roof: Roof Finish = 1.5 KN/m2
• Live Load = Variable parameter
• Floor : Floor Finish = 1.0 KN/m2
• Live Load = Variable parameter
• EQ load generation method = Response Spectrum Method
• Seismic Zone = Zone 3
• Soil Type = Medium Soil
• Percentage Damping = 5 %
• Modal Combination method = SRSS

139. • Concrete = M20
• Steel: Main & Secondary = Fe 415
• Unit Weight of Concrete = 25 KN/m2
• Unit Weight of Bricks Masonry = 19 KN/m2
• Design Basis: =Limit State Method based on IS: 456-2000
• Live Load = 2 KN/m2
• Preliminary Beam Size = 230 x 450 mm

141. • When live load 2 KN/m² and beam size is 230 x 450mm, quantity of
steel is increase (approx 17%) at location of shear wall near to the
center of building, compare to shear wall at corner of building.
• When the shear wall kept near to the center with live load is 2KN/m²
and preliminary dimension of beam is 230 x 300mm, quantity of steel
in beam increase (approx 15%), while quantity of steel in column is
decrease (approx 8.77%) as compare to shear wall at corner of
building.

142. • When live load 3 KN/m² and beam size is 230X300mm, quantity of
steel is increase (approx 13%) at location of shear wall near to the
center of building, compare to shear wall at corner of building.
• When live load 3 KN/m² and beam size is 230 x 300mm, quantity of
steel is decrease (approx 22%) at location of shear wall near to the
center of building, compare to building without shear wall.

143. • The location of shear wall at corners of building is much effective
while increasing live load 3 KN/m² with preliminary dimension of
beam 230 x 300mm.
• The shear wall gives beneficial effect of more clear head way in case
of providing it at corners of building or away from the center of
building.
• Quantity of steel and concrete is less in case of without shear wall so
it is said that for G+8 building with 2 KN/m² live load and preliminary
beam size is 230 x 450 mm or 250 x 300mm, there is no economical
beneficial effect of shear wall.

144. • Here the G+8 building is taken one can take higher no. of floor as
G+15 or G+20 more than that, it may be given.
• More effective beneficial effect of shear wall.
• The problem building is only symmetric square building; one can take
rectangle, L-shape, C-shape building with eccentricity.
• Identical building of (6 bay x 6 bay) is taken in problem for simplicity,
but commercial and residential building irregular shape in plan can
also take for further work for implementation to this project.
• Shape of shear wall is taken in this building is “L shape”; one can take
different shape for further work.

145. Structure Reliability

148. Reliability engineering
• Reliability engineering is engineering that emphasizes dependability in
the lifecycle management of a product.
• Dependability, or reliability, describes the ability of a system or component
to function under stated conditions for a specified period of time.
• Reliability engineering represents a sub-discipline within systems
engineering.
• Reliability is theoretically defined as the probability of success
(Reliability=1-Probability of Failure), as the frequency of failures, or in
terms of availability, as a probability derived from reliability and
maintainability.
• Maintainability and maintenance is often defined as a part of "reliability
engineering" in Reliability Programs.
• Reliability plays a key role in the cost-effectiveness of systems.

149. • Reliability engineering deals with the estimation and management of
high levels of "lifetime" engineering uncertainty and risks of failure.
• Although stochastic parameters define and affect reliability, according
to some expert authors on Reliability Engineering, e.g. P. O'Conner, J.
Moubray and A. Barnard, reliability is not (solely) achieved by
mathematics and statistics.
• "Nearly all teaching and literature on the subject emphasize these
aspects, and ignore the reality that the ranges of uncertainty involved
largely invalidate quantitative methods for prediction and
measurement"

150. • Reliability engineering relates closely to safety engineering and to system
safety, in that they use common methods for their analysis and may require
input from each other.
• Reliability engineering focuses on costs of failure caused by system
downtime, cost of spares, repair equipment, personnel and cost of
warranty claims.
• Safety engineering normally emphasizes not cost, but preserving life and
nature, and therefore deals only with particular dangerous system-failure
modes.
• High reliability (safety factor) levels also result from good engineering, from
attention to detail and almost never from only re-active failure
management (reliability accounting / statistics).

151. Scope and techniques to be used within Reliability Engineering
• Reliability engineering for complex systems requires a different, more
elaborate systems approach than for non-complex systems.
Reliability engineering may in that case involve:
• System availability and mission readiness analysis and related
reliability and maintenance requirement allocation
• Functional System Failure analysis and derived requirements
specification
• Inherent (system) Design Reliability Analysis and derived
requirements specification: for both Hardware- and Software design
• System Diagnostics design
• Predictive and Preventive maintenance (e.g. Reliability Centered
Maintenance)
• Human Factors / Human Interaction / Human Errors

152. • Manufacturing and Assembly induced failures (non 0-hour Quality)
• Maintenance induced failures
• Transport induced failures
• Storage induced failures
• Use (load) studies, component stress analysis and derived requirements specification
• Software(systematic) failures
• Failure / reliability testing
• Field failure monitoring and corrective actions
• Spare-parts stocking (Availability control)
• Technical documentation, caution and warning analysis
• Data and information acquisition/organisation (Creation of a general reliability
development Hazard Log and FRACAS system)

153. Effective reliability engineering requires understanding of the basics
of failure mechanisms for which experience, broad engineering skills and
good knowledge from many different special fields of engineering,like:
• Tribology
• Stress (mechanics)
• Fracture mechanics / Fatigue (material)
• Thermal engineering
• Fluid mechanics / shock loading engineering
• Electrical engineering
• Chemical engineering (e.g. Corrosion)
• Material science

154. Definitions
Reliability may be defined in the following ways:
• The idea that an item is fit for a purpose with respect to time
• The capacity of a designed, produced or maintained item to perform as
required over time
• The capacity of a population of designed, produced or maintained items to
perform as required over specified time
• The resistance to failure of an item over time
• The probability of an item to perform a required function under stated
conditions for a specified period of time
• The durability of an object.

155. Basics of a Reliability Assessment
Many engineering techniques are used in reliability risk assessments,
such as reliability hazard analysis, failure mode and effects
analysis (FMEA), fault tree analysis (FTA), Reliability Centered
Maintenance, material stress and wear calculations, fatigue and creep
analysis, human error analysis, reliability testing, etc.
Because of the large number of reliability techniques, their expense,
and the varying degrees of reliability required for different situations,
most projects develop a reliability program plan to specify the
reliability tasks that will be performed for that specific system.

156. Consistent with the creation of a safety cases, for example ARP4761, the goal of
reliability assessments is to provide a robust set of qualitative and quantitative
evidence that use of a component or system will not be associated with
unacceptable risk.
The basic steps to take are to:
• First thoroughly identify relevant unreliability "hazards", e.g. potential conditions,
events, human errors, failure modes, interactions, failure mechanisms and root
causes, by specific analysis or tests
• Assess the associated system risk, by specific analysis or testing
• Propose mitigation, e.g. requirements, design changes, detection
logic, maintenance, training, by which the risks may be lowered and controlled
for at an acceptable level.
• Determine the best mitigation and get agreement on final, acceptable risk levels,
possibly based on cost-benefit analysis

157. • Risk is here the combination of probability and severity of the failure incident (scenario)
occurring.
• In a deminimus definition, severity of failures include the cost of spare parts, man hours,
logistics, damage (secondary failures) and downtime of machines which may cause
production loss.
• A more complete definition of failure also can mean injury, dismemberment and death of
people within the system (witness mine accidents, industrial accidents, space shuttle
failures) and the same to innocent bystanders (witness the citizenry of cities like Bhopal,
Love Canal, Chernobyl or Sendai and other victims of the 2011 Tōhoku earthquake and
tsunami) - in this case, Reliability Engineering becomes System Safety.
• What is acceptable is determined by the managing authority or customers or the
effected communities.
• Residual risk is the risk that is left over after all reliability activities have finished and
includes the un-identified risk and is therefore not completely quantifiable.

158. Reliability and availability program plan
• A reliability program plan is used to document exactly what "best
practices" (tasks, methods, tools, analysis and tests) are required for a
particular (sub)system, as well as clarify customer requirements for
reliability assessment.
• For large scale, complex systems, the reliability program plan should be a
separate document.
• Resource determination for manpower and budgets for testing and other
tasks is critical for a successful program.
• In general, the amount of work required for an effective program for
complex systems is large.

159. • A reliability program plan is essential for achieving high levels of
reliability, testability, maintainability and the resulting
system Availability and is developed early during system development
and refined over the systems life-cycle.
• It specifies not only what the reliability engineer does, but also the
tasks performed by other stakeholders.
• A reliability program plan is approved by top program management,
which is responsible for allocation of sufficient resources for its
implementation.

160. • A reliability program plan may also be used to evaluate and improve
availability of a system by the strategy on focusing on increasing testability
& maintainability and not on reliability.
• Improving maintainability is generally easier than reliability.
• Maintainability estimates (Repair rates) are also generally more accurate.
• However, because the uncertainties in the reliability estimates are in most
cases very large, it is likely to dominate the availability (prediction
uncertainty) problem; even in the case maintainability levels are very high.
• When reliability is not under control more complicated issues may arise,
like manpower (maintainers / customer service capability) shortage, spare
part availability, logistic delays, lack of repair facilities, extensive retro-fit
and complex configuration management costs and others.

161. • The problem of unreliability may be increased also due to the "domino effect" of
maintenance induced failures after repairs.
• Only focusing on maintainability is therefore not enough.
• If failures are prevented, none of the others are of any importance and therefore
reliability is generally regarded as the most important part of availability.
• Reliability needs to be evaluated and improved related to both
availability and the cost of ownership (due to cost of spare parts, maintenance
man-hours, transport costs, storage cost, part obsolete risks, etc.).
• But, as GM and Toyota have belatedly discovered, TCO also includes the down-
stream liability costs when reliability calculations do not sufficiently or accurately
address customers' personal bodily risks.
• Often a trade-off is needed between the two.
• There might be a maximum ratio between availability and cost of ownership.

162. • Testability of a system should also be addressed in the plan as this is
the link between reliability and maintainability.
• The maintenance strategy can influence the reliability of a system
(e.g. by preventive and/or predictive maintenance), although it can
never bring it above the inherent reliability.
• The reliability plan should clearly provide a strategy for availability
control.
• Whether only availability or also cost of ownership is more important
depends on the use of the system.

163. • For example, a system that is a critical link in a production system –
e.g. a big oil platform – is normally allowed to have a very high cost of
ownership if this translates to even a minor increase in availability, as
the unavailability of the platform results in a massive loss of revenue
which can easily exceed the high cost of ownership.
• A proper reliability plan should always address RAMT analysis in its
total context.
• RAMT stands in this case for reliability, availability,
maintainability/maintenance and testability in context to the
customer needs.

164. Reliability requirements
• For any system, one of the first tasks of reliability engineering is to adequately specify the
reliability and maintainability requirements derived from the overall availability needs and more
importantly, from proper design failure analysis or preliminary prototype test results.
• Clear (able to design to) Requirements should constrain the designers from designing particular
unreliable items / constructions / interfaces / systems.
• Setting only availability (reliability, testability and maintainability) allocated targets (e.g. max.
Failure rates) is not appropriate.
• This is a broad misunderstanding about Reliability Requirements Engineering.
• Reliability requirements address the system itself, including test and assessment requirements,
and associated tasks and documentation.
• Reliability requirements are included in the appropriate system or subsystem requirements
specifications, test plans and contract statements.
• Creation of proper lower level requirements is critical.

165. • Provision of only quantitative minimum targets (e.g. MTBF values/ Failure rates) is
not sufficient for different reasons.
• One reason is that a full validation (related to correctness and verifiability in
time) of an quantitative reliability allocation (requirement spec) on lower levels
for complex systems can (often) not be made as a consequence of
• 1) The fact that the requirements are probabalistic
• 2) The extremely high level of uncertainties involved for showing compliance with
all these probabalistic requirements
• 3) Reliability is a function of time and accurate estimates of a (probabalistic)
reliability number per item are available only very late in the project, sometimes
even only many years after in-service use.
• Compare this problem with the continues (re-)balancing of for example lower
level system mass requirements in the development of an aircraft, which is
already often a big undertaking.

166. • Notice that in this case masses do only differ in terms of only some %, are not a function of time,
the data is non-probabalistic and available already in CAD models.
• In case of reliability, the levels of unreliability (failure rates) may change with factors of decades
(1000's of %) as result of very minor deviations in design, process or anything else.
• The information is often not available without huge uncertainties within the development phase.
• This makes this allocation problem almost impossible to do in a useful, practical, valid manner,
which does not result in massive over- or under specification.
• A pragmatic approach is therefore needed.
• For example; the use of general levels/ classes of quantitative requirements only depending on
severity of failure effects.
• Also the validation of results is a far more subjective task than for any other type of requirement.
• (Quantitative) Reliability parameters -in terms of MTBF - are by far the most uncertain design
parameters in any design.

167. • Furthermore, reliability design requirements should drive a (system or
part) design to incorporate features that prevent failures from occurring or
limit consequences from failure in the first place!
• Not only to make some predictions, this could potentially distract the
engineering effort to a kind of accounting work.
• A design requirement should be so precise enough so that a designer can
"design to" it and can also prove -through analysis or testing- that the
requirement has been achieved, and if possible within some a stated
confidence.
• Any type of reliability requirement should be detailed and could be derived
from failure analysis (Finite Element Stress and Fatigue analysis, Reliability
Hazard Analysis, FTA, FMEA, Human Factor analysis, Functional Hazard
Analysis, etc.) or any type of reliability testing.

168. • Also, requirements are needed for verification tests e.g. required overload loads (or
stresses) and test time needed.
• To derive these requirements in an effective manner, a systems engineering based risk
assessment and mitigation logic should be used.
• Robust hazard log systems are to be created that contain detailed information on why
and how systems could or have failed.
• Requirements are to be derived and tracked in this way.
• These practical design requirements shall drive the design and not only be used for
verification purposes.
• These requirements (often design constraints) are in this way derived from failure
analysis or preliminary tests.
• Understanding of this difference with only pure quantitative (logistic) requirement
specification (e.g. Failure Rate/ MTBF setting) is paramount in the development of
successful (complex) systems.

169. • The maintainability requirements address the costs of repairs as well as
repair time.
• Testability (not to be confused with test requirements) requirements
provide the link between reliability and maintainability and should address
detectability of failure modes (on a particular system level), isolation levels
and the creation of diagnostics (procedures).
• As indicated above, reliability engineers should also address requirements
for various reliability tasks and documentation during system development,
test, production, and operation.
• These requirements are generally specified in the contract statement of
work and depend on how much leeway the customer wishes to provide to
the contractor.

170. • Reliability tasks include various analyses, planning, and failure
reporting.
• Task selection depends on the criticality of the system as well as cost.
• A safety critical system may require a formal failure reporting and
review process throughout development, whereas a non-critical
system may rely on final test reports.
• The most common reliability program tasks are documented in
reliability program standards, such as MIL-STD-785 and IEEE 1332.
• Failure reporting analysis and corrective action systems are a
common approach for product/process reliability monitoring.

171. Reliability culture / Human Errors / Human Factors
Practically, most failures can in the end be traced back to a root causes of the type
of human error of any kind.
For example, human errors in:
• Management decisions on for example budgeting, timing and required tasks
• Systems Engineering: Use studies (load cases)
• Systems Engineering: Requirement analysis / setting
• Systems Engineering: Configuration control
• Assumptions
• Calculations / simulations / FEM analysis
• Design

172. • However, humans are also very good in detection of (the same) failures,
correction of failures and improvising when abnormal situations occur.
• The policy that human actions should be completely ruled out of any design and
production process to improve reliability may not be effective therefore.
• Some tasks are better performed by humans and some are better performed by
machines.
• Furthermore, human errors in management and the organization of data and
information or the misuse or abuse of items may also contribute to unreliability.
• This is the core reason why high levels of reliability for complex systems can only
be achieved by following a robust systems engineering process with proper
planning and execution of the validation and verification tasks.
• This also includes careful organization of data and information sharing and
creating a "reliability culture" in the same sense as having a "safety culture" is
paramount in the development of safety critical systems.

173. Reliability prediction and improvement
• Reliability prediction is the combination of the creation of a proper
reliability model (see further on this page) together with estimating
(and justifying) the input parameters for this model (like failure rates
for a particular failure mode or event and the mean time to repair the
system for a particular failure) and finally to provide a system (or part)
level estimate for the output reliability parameters (system availability
or a particular functional failure frequency).

174. • Some recognized reliability engineering specialists – e.g. Patrick O'Connor, R. Barnard –
have argued that too much emphasis is often given to the prediction of reliability
parameters and more effort should be devoted to the prevention of failure (reliability
improvement).
• Failures can and should be prevented in the first place for most cases.
• The emphasis on quantification and target setting in terms of (e.g.) MTBF might provide
the idea that there is a limit to the amount of reliability that can be achieved.
• In theory there is no inherent limit and higher reliability does not need to be more costly
in development.
• Another of their arguments is that prediction of reliability based on historic data can be
very misleading, as a comparison is only valid for exactly the same designs, products,
manufacturing processes and maintenance under exactly the same loads and
environmental context.
• Even a minor change in detail in any of these could have major effects on reliability.

175. • Furthermore, normally the most unreliable and important items (most interesting
candidates for a reliability investigation) are most often subjected to many
modifications and changes.
• Engineering designs are in most industries updated frequently.
• This is the reason why the standard (re-active or pro-active) statistical methods
and processes as used in the medical industry or insurance branch are not as
effective for engineering.
• Another surprising but logical argument is that to be able to accurately predict
reliability by testing, the exact mechanisms of failure must have been known in
most cases and therefore – in most cases – can be prevented!
• Following the incorrect route by trying to quantify and solving a complex
reliability engineering problem in terms of MTBF or Probability and using the re-
active approach is referred to by Barnard as "Playing the Numbers Game" and is
regarded as bad practise.

176. • For existing systems, it is arguable that responsible programs would directly
analyse and try to correct the root cause of discovered failures and thereby may
render the initial MTBF estimate fully invalid as new assumptions (subject to high
error levels) of the effect of the patch/redesign must be made.
• Another practical issue concerns a general lack of availability of detailed failure
data and not consistent filtering of failure (feedback) data or ignoring statistical
errors, which are very high for rare events (like reliability related failures).
• Very clear guidelines must be present to be able to count and compare failures,
related to different type of root-causes (e.g. manufacturing-, maintenance-,
transport-, system-induced or inherent design failures).
• Comparing different type of causes may lead to incorrect estimations and
incorrect business decisions about the focus of improvement.

177. • To perform a proper quantitative reliability prediction for systems may be difficult and may be
very expensive if done by testing.
• On part level, results can be obtained often with higher confidence as many samples might be
used for the available testing financial budget, however unfortunately these tests might lack
validity on system level due to the assumptions that had to be made for part level testing.
• These authors argue that it can not be emphasized enough that testing for reliability should be
done to create failures in the first place, learn from them and to improve the system / part.
• The general conclusion is drawn that an accurate and an absolute prediction – by field data
comparison or testing – of reliability is in most cases not possible.
• An exception might be failures due to wear-out problems like fatigue failures.
• In the introduction of MIL-STD-785 it is written that reliability prediction should be used with
great caution if not only used for comparison in trade-off studies.
• See also: Risk Assessment#Quantitative risk assessment – Critics paragraph

178. Design for reliability
• Reliability design begins with the development of a (system) model.
• Reliability and availability models use block diagrams and Fault Tree
Analysis to provide a graphical means of evaluating the relationships
between different parts of the system.
• These models may incorporate predictions based on failure rates taken
from historical data.
• While the (input data) predictions are often not accurate in an absolute
sense, they are valuable to assess relative differences in design
alternatives.
• Maintainability parameters, for example MTTR, are other inputs for these
models.

179. • The most important fundamental initiating causes and failure
mechanisms are to be identified and analyzed with engineering tools.
• A diverse set of practical guidance and practical performance and
reliability requirements should be provided to designers so they can
generate low-stressed designs and products that protect or are
protected against damage and excessive wear.
• Proper Validation of input loads (requirements) may be needed and
verification for reliability "performance" by testing may be needed.

180. • One of the most important design techniques is redundancy.
• This means that if one part of the system fails, there is an alternate
success path, such as a backup system.
• The reason why this is the ultimate design choice is related to the fact
that high confidence reliability evidence for new parts / items is often
not available or extremely expensive to obtain.
• By creating redundancy, together with a high level of failure
monitoring and the avoidance of common cause failures, even a
system with relative bad single channel (part) reliability, can be made
highly reliable (mission reliability) on system level.

181. A Fault Tree Diagram

182. • No testing of reliability has to be required for this.
• Furthermore, by using redundancy and the use of dissimilar design
and manufacturing processes (different suppliers) for the single
independent channels, less sensitivity for quality issues (early
childhood failures) is created and very high levels of reliability can be
achieved at all moments of the development cycles (early life times
and long term).
• Redundancy can also be applied in systems engineering by double
checking requirements, data, designs, calculations, software and tests
to overcome systematic failures.

183. • Another design technique to prevent failures is called physics of failure.
• This technique relies on understanding the physical static and dynamic failure
mechanisms.
• It accounts for variation in load, strength and stress leading to failure at high level
of detail, possible with use of modern finite element method (FEM) software
programs that may handle complex geometries and mechanisms like creep, stress
relaxation, fatigue and probabilistic design (Monte Carlo simulations / DOE).
• The material or component can be re-designed to reduce the probability of
failure and to make it more robust against variation.
Another common design technique is component derating:
• Selecting components whose tolerance significantly exceeds the expected stress,
as using a heavier gauge wire that exceeds the normal specification for the
expected electrical current.

184. • Another effective way to deal with unreliability issues is to perform
analysis to be able to predict degradation and being able to prevent
unscheduled down events / failures from occurring.
• RCM (Reliability Centered Maintenance) programs can be used for
this.
• Many tasks, techniques and analyses are specific to particular
industries and applications.

185. Commonly these include:
• Built-in test (BIT) (testability analysis)
• Failure mode and effects analysis (FMEA)
• Reliability hazard analysis
• Reliability block-diagram analysis
• Dynamic Reliability block-diagram analysis
• Fault tree analysis
• Root cause analysis
• Statistical Engineering, Design of Experiments - e.g. on Simulations / FEM models or with
testing
• Sneak circuit analysis
• Accelerated testing

186. • Reliability growth analysis (re-active reliability)
• Weibull analysis (for testing or mainly "re-active" reliability)
• Thermal analysis by finite element analysis (FEA) and / or measurement
• Thermal induced, shock and vibration fatigue analysis by FEA and / or measurement
• Electromagnetic analysis
• Avoidance of single point of failure
• Functional analysis and functional failure analysis (e.g., function FMEA, FHA or FFA)
• Predictive and preventive maintenance: reliability centered maintenance (RCM)
analysis
• Testability analysis
• Failure diagnostics analysis (normally also incorporated in FMEA)
• Human error analysis
• Operational hazard analysis
• Manual screening
• Integrated logistics support

187. • Results are presented during the system design reviews and logistics
reviews.
• Reliability is just one requirement among many system requirements.
• Engineering trade studies are used to determine
the optimum balance between reliability and other requirements and
constraints.

188. Quantitative and Qualitative approaches and the importance of
language in reliability engineering
• Reliability engineers could concentrate more on "why and how" items
/ systems may fail or have failed, instead of mostly trying to predict
"when" or at what (changing) rate (failure rate (t)).
• Answers to the first questions will drive improvement in design and
processes.
• When failure mechanisms are really understood then solutions to
prevent failure are easily found.
• Only required Numbers (e.g. MTBF) will not drive good designs.

189. • The huge amount of (un)reliability hazards that are generally part of
complex systems need first to be classified and ordered (based on
qualitative and quantitative logic if possible) to get to efficient
assessment and improvement.
• This is partly done in pure language and proposition logic, but also
based on experience with similar items.
• This can for example be seen in descriptions of events in Fault Tree
Analysis, FMEA analysis and a hazard (tracking) log.

190. • In this sense language and proper grammar (part of qualitative analysis)
plays an important role in reliability engineering, just like it does in safety
engineering or in general within systems engineering.
• Engineers are likely to question why?
• Well, it is precisely needed because systems engineering is very much
about finding the correct words to describe the problem (and related risks)
to be solved by the engineering solutions we intend to create.
• In the words of Jack Ring, the systems engineer’s job is to “language the
project.” [Ring et al. 2000].
• Language in itself is about putting an order in a description of the reality of
a (failure of a) complex function/item/system in a complex surrounding.
• Reliability engineers use both quantitative and qualitative methods, which
extensively use language to pinpoint the risks to be solved.

191. • The importance of language also relates to the risks of human error,
which can be seen as the ultimate root cause of almost all failures -
see further on this site.
• As an example, proper instructions (often written by technical authors
in so called simplified English) in maintenance manuals, operation
manuals, emergency procedures and others are needed to prevent
systematic human errors in any maintenance or operational task that
may result in system failures.

192. Reliability modelling
• Reliability modelling is the process of predicting or understanding the reliability
of a component or system prior to its implementation.
• Two types of analysis that are often used to model a complete system availability
(including effects from logistics issues like spare part provisioning, transport and
manpower) behavior are Fault Tree Analysis and reliability block diagrams.
• On component level the same type of analysis can be used together with others.
• The input for the models can come from many sources: Testing, Earlier
operational experience field data or data handbooks from the same or mixed
industries can be used.
• In all cases, the data must be used with great caution as predictions are only valid
in case the same product in the same context is used.
• Often predictions are only made to compare alternatives.

193. For part level predictions, two separate fields of investigation are
common:
• The physics of failure approach uses an understanding of physical
failure mechanisms involved, such as mechanical crack propagation or
chemical corrosion degradation or failure.
• The parts stress modelling approach is an empirical method for
prediction based on counting the number and type of components of
the system, and the stress they undergo during operation.
• Software reliability is a more challenging area that must be
considered when it is a considerable component to system
functionality.

195. Reliability theory
• Main articles: Reliability theory, Failure rate and Survival analysis
• Reliability is defined as the probability that a device will perform its
intended function during a specified period of time under stated
conditions. Mathematically, this may be expressed as,
Where is the failure probability density function and is the length
of the period of time (which is assumed to start from time zero).

196. There are a few key elements of this definition:
1. Reliability is predicated on "intended function:"
• Generally, this is taken to mean operation without failure.
• However, even if no individual part of the system fails, but the system
as a whole does not do what was intended, then it is still charged
against the system reliability.
• The system requirements specification is the criterion against which
reliability is measured.

197. • 2. Reliability applies to a specified period of time. In practical terms,
this means that a system has a specified chance that it will operate
without failure before time Reliability engineering ensures that
components and materials will meet the requirements during the
specified time. Units other than time may sometimes be used.
• 3. Reliability is restricted to operation under stated (or explicitly
defined) conditions. This constraint is necessary because it is
impossible to design a system for unlimited conditions. A Mars
Rover will have different specified conditions than a family car. The
operating environment must be addressed during design and testing.
That same rover may be required to operate in varying conditions
requiring additional scrutiny.

198. Quantitative system reliability parameters – theory
• Quantitative Requirements are specified using reliability parameters.
• The most common reliability parameter is the mean time to failure (MTTF), which
can also be specified as the failure rate (this is expressed as a frequency or
conditional probability density function (PDF)) or the number of failures during a
given period.
• These parameters may be useful for higher system levels and systems that are
operated frequently, such as most vehicles, machinery, and electronic equipment.
Reliability increases as the MTTF increases.
• The MTTF is usually specified in hours, but can also be used with other units of
measurement, such as miles or cycles.
• Using MTTF values on lower system levels can be very misleading, specially if the
Failures Modes and Mechanisms it concerns (The F in MTTF) are not specified
with it.

199. • In other cases, reliability is specified as the probability of mission success.
• For example, reliability of a scheduled aircraft flight can be specified as a
dimensionless probability or a percentage, as in system safety engineering.
• A special case of mission success is the single-shot device or system. These are
devices or systems that remain relatively dormant and only operate once.
• Examples include automobile airbags, thermal batteries and missiles. Single-shot
reliability is specified as a probability of one-time success, or is subsumed into a
related parameter.
• Single-shot missile reliability may be specified as a requirement for the
probability of a hit.
• For such systems, the probability of failure on demand (PFD) is the reliability
measure – which actually is an unavailability number. This PFD is derived from
failure rate (a frequency of occurrence) and mission time for non-repairable
systems.

200. • For repairable systems, it is obtained from failure rate and mean-
time-to-repair (MTTR) and test interval.
• This measure may not be unique for a given system as this measure
depends on the kind of demand.
• In addition to system level requirements, reliability requirements may
be specified for critical subsystems.
• In most cases, reliability parameters are specified with appropriate
statistical confidence intervals.

201. Reliability testing
• The purpose of reliability testing is to discover potential problems
with the design as early as possible and, ultimately, provide
confidence that the system meets its reliability requirements.
• Reliability testing may be performed at several levels and there are
different types of testing.
• Complex systems may be tested at component, circuit board, unit,
assembly, subsystem and system levels [1]

202. • (The test level nomenclature varies among applications.) For example,
performing environmental stress screening tests at lower levels, such as
piece parts or small assemblies, catches problems before they cause
failures at higher levels.
• Testing proceeds during each level of integration through full-up system
testing, developmental testing, and operational testing, thereby reducing
program risk.
• However, testing does not mitigate unreliability risk.
• With each test both a statistical type 1 and type 2 error could be made and
depends on sample size, test time, assumptions and the needed
discrimination ratio.
• There is risk of incorrectly accepting a bad design (type 1 error) and the risk
of incorrectly rejecting a good design (type 2 error).

203. • It is not always feasible to test all system requirements.
• Some systems are prohibitively expensive to test; some failure modes
may take years to observe; some complex interactions result in a huge
number of possible test cases; and some tests require the use of
limited test ranges or other resources.
• In such cases, different approaches to testing can be used, such as
(highly) accelerated life testing, design of experiments,
and simulations.

204. A reliability sequential test plan

205. • The desired level of statistical confidence also plays an role in reliability
testing.
• Statistical confidence is increased by increasing either the test time or the
number of items tested.
• Reliability test plans are designed to achieve the specified reliability at the
specified confidence level with the minimum number of test units and test
time.
• Different test plans result in different levels of risk to the producer and
consumer.
• The desired reliability, statistical confidence, and risk levels for each side
influence the ultimate test plan.
• The customer and developer should agree in advance on how reliability
requirements will be tested.

206. • A key aspect of reliability testing is to define "failure".
• Although this may seem obvious, there are many situations where it is not clear
whether a failure is really the fault of the system.
• Variations in test conditions, operator differences, weather and unexpected
situations create differences between the customer and the system developer.
• One strategy to address this issue is to use a scoring conference process.
• A scoring conference includes representatives from the customer, the developer,
the test organization, the reliability organization, and sometimes independent
observers.
• The scoring conference process is defined in the statement of work.
• Each test case is considered by the group and "scored" as a success or failure.
• This scoring is the official result used by the reliability engineer.

207. • As part of the requirements phase, the reliability engineer develops a test
strategy with the customer.
• The test strategy makes trade-offs between the needs of the reliability
organization, which wants as much data as possible, and constraints such as cost,
schedule and available resources.
• Test plans and procedures are developed for each reliability test, and results are
documented.
• Reliability testing is common in the Photonics industry.
• Examples of reliability tests of lasers are life test and burn-in.
• These tests consist of the highly accelerated ageing, under controlled conditions,
of a group of lasers.
• The data collected from these life tests are used to predict laser life expectancy
under the intended operating characteristics.

208. • Reliability test requirements
• Reliability test requirements can follow from any analysis for which the first
estimate of failure probability, failure mode or effect needs to be justified.
• Evidence can be generated with some level of confidence by testing.
• With software-based systems, the probability is a mix of software and
hardware-based failures.
• Testing reliability requirements is problematic for several reasons.
• A single test is in most cases insufficient to generate enough statistical
data.
• Multiple tests or long-duration tests are usually very expensive.
• Some tests are simply impractical, and environmental conditions can be
hard to predict over a systems life-cycle.

209. • Reliability engineering is used to design a realistic and affordable test
program that provides empirical evidence that the system meets its
reliability requirements.
• Statistical confidence levels are used to address some of these concerns.
• A certain parameter is expressed along with a corresponding confidence
level: for example, an MTBF of 1000 hours at 90% confidence level.
• From this specification, the reliability engineer can, for example, design a
test with explicit criteria for the number of hours and number of failures
until the requirement is met or failed.
• Different sorts of tests are possible.

210. • The combination of required reliability level and required confidence level greatly
affects the development cost and the risk to both the customer and producer.
• Care is needed to select the best combination of requirements – e.g. cost-
effectiveness.
• Reliability testing may be performed at various levels, such as
component, subsystem and system.
• Also, many factors must be addressed during testing and operation, such as
extreme temperature and humidity, shock, vibration, or other environmental
factors (like loss of signal, cooling or power; or other catastrophes such as fire,
floods, excessive heat, physical or security violations or other myriad forms of
damage or degradation).
• For systems that must last many years, accelerated life tests may be needed.

211. Accelerated testing
The purpose of accelerated life testing (ALT test) is to induce field
failure in the laboratory at a much faster rate by providing a harsher,
but nonetheless representative, environment.
In such a test, the product is expected to fail in the lab just as it would
have failed in the field—but in much less time.
The main objective of an accelerated test is either of the following:
• To discover failure modes
• To predict the normal field life from the high stress lab life

212. An Accelerated testing program can be broken down into the following
steps:
• Define objective and scope of the test
• Collect required information about the product
• Identify the stress(es)
• Determine level of stress(es)
• Conduct the accelerated test and analyze the collected data.

213. Common way to determine a life stress relationship are
• Arrhenius model
• Eyring model
• Inverse power law model
• Temperature–humidity model
• Temperature non-thermal model

214. Software reliability
Further information: Software reliability
• Software reliability is a special aspect of reliability engineering.
• System reliability, by definition, includes all parts of the system, including
hardware, software, supporting infrastructure (including critical external
interfaces), operators and procedures.
• Traditionally, reliability engineering focuses on critical hardware parts of
the system.
• Since the widespread use of digital integrated circuit technology, software
has become an increasingly critical part of most electronics and, hence,
nearly all present day systems.

215. • There are significant differences, however, in how software and hardware behave.
• Most hardware unreliability is the result of a component or material failure that results in
the system not performing its intended function.
• Repairing or replacing the hardware component restores the system to its original
operating state.
• However, software does not fail in the same sense that hardware fails.
• Instead, software unreliability is the result of unanticipated results of software
operations.
• Even relatively small software programs can have astronomically large combinations of
inputs and states that are infeasible to exhaustively test.
• Restoring software to its original state only works until the same combination of inputs
and states results in the same unintended result.
• Software reliability engineering must take this into account.

216. • Despite this difference in the source of failure between software and hardware,
several software reliability models based on statistics have been proposed to quantify
what we experience with software: the longer software is run, the higher the probability
that it will eventually be used in an untested manner and exhibit a latent defect that
results in a failure (Shooman 1987), (Musa 2005), (Denney 2005).
• As with hardware, software reliability depends on good requirements, design and
implementation.
• Software reliability engineering relies heavily on a disciplined software
engineering process to anticipate and design against unintended consequences.
• There is more overlap between software quality engineering and software reliability
engineering than between hardware quality and reliability.
• A good software development plan is a key aspect of the software reliability program.
• The software development plan describes the design and coding standards, peer
reviews, unit tests, configuration management, software metrics and software models to
be used during software development.

217. • A common reliability metric is the number of software faults, usually expressed as
faults per thousand lines of code.
• This metric, along with software execution time, is key to most software reliability
models and estimates.
• The theory is that the software reliability increases as the number of faults (or
fault density) decreases or goes down.
• Establishing a direct connection between fault density and mean-time-between-
failure is difficult, however, because of the way software faults are distributed in
the code, their severity, and the probability of the combination of inputs
necessary to encounter the fault.
• Nevertheless, fault density serves as a useful indicator for the reliability engineer.
Other software metrics, such as complexity, are also used.
• This metric remains controversial, since changes in software development and
verification practices can have dramatic impact on overall defect rates.

218. • Testing is even more important for software than hardware.
• Even the best software development process results in some software
faults that are nearly undetectable until tested.
• As with hardware, software is tested at several levels, starting with
individual units, through integration and full-up system testing.
• Unlike hardware, it is inadvisable to skip levels of software testing.
• During all phases of testing, software faults are discovered, corrected,
and re-tested.
• Reliability estimates are updated based on the fault density and other
metrics.

219. • At a system level, mean-time-between-failure data can be collected and
used to estimate reliability.
• Unlike hardware, performing exactly the same test on exactly the same
software configuration does not provide increased statistical confidence.
• Instead, software reliability uses different metrics, such as code coverage.
• Eventually, the software is integrated with the hardware in the top-level
system, and software reliability is subsumed by system reliability.
• The Software Engineering Institute's capability maturity model is a
common means of assessing the overall software development process for
reliability and quality purposes.

220. Reliability engineering vs safety engineering
• Reliability engineering differs from safety engineering with respect to the
kind of hazards that are considered.
• Reliability engineering is in the end only concerned with cost.
• It relates to all Reliability hazards that could transform into incidents with a
particular level of loss of revenue for the company or the customer.
• These can be cost due to loss of production due to system unavailability,
unexpected high or low demands for spares, repair costs, man hours,
(multiple) re-designs, interruptions on normal production (e.g. due to high
repair times or due to unexpected demands for non-stocked spares) and
many other indirect costs

221. • Safety engineering, on the other hand, is more specific and regulated.
• It relates to only very specific and system safety hazards that could potentially
lead to severe accidents and is primarily concerned with loss of life, loss of
equipment, or environmental damage.
• The related system functional reliability requirements are sometimes extremely
high.
• It deals with unwanted dangerous events (for life, property, and environment) in
the same sense as reliability engineering, but does normally not directly look at
cost and is not concerned with repair actions after failure / accidents (on system
level).
• Another difference is the level of impact of failures on society and the control of
governments.
• Safety engineering is often strictly controlled by governments (e.g. nuclear,
aerospace, defense, rail and oil industries).

222. • Furthermore, safety engineering and reliability engineering may even have
contradicting requirements.
• This relates to system level architecture choices.
• For example, in train signal control systems it is common practice to use a
fail-safe system design concept.
• In this concept the Wrong-side failure need to be fully controlled to an
extreme low failure rate.
• These failures are related to possible severe effects, like frontal collisions
(2* GREEN lights).
• Systems are designed in a way that the far majority of failures will simply
result in a temporary or total loss of signals or open contacts of relays and
generate RED lights for all trains.

223. • This is the safe state.
• All trains are stopped immediately.
• This fail-safe logic might unfortunately lower the reliability of the
system.
• The reason for this is the higher risk of false tripping as any full or
temporary, intermittent failure is quickly latched in a shut-down
(safe)state.
• Different solutions are available for this issue.
• See chapter Fault Tolerance below.

224. Fault tolerance
• Reliability can be increased here by using a 2oo2 (2 out of 2) redundancy on part
or system level, but this does in turn lower the safety levels (more possibilities for
Wrong Side and undetected dangerous Failures).
• Fault tolerant voting systems (e.g. 2oo3 voting logic) can increase both reliability
and safety on a system level.
• In this case the so-called "operational" or "mission" reliability as well as the safety
of a system can be increased.
• This is also common practice in Aerospace systems that need continued
availability and do not have a fail safe mode (e.g. flight computers and related
electrical and/ or mechanical and/ or hydraulic steering functions need always to
be working.
• There are no safe fixed positions for rudder or other steering parts when the
aircraft is flying).

225. Basic reliability and mission (operational) reliability
• The above example of a 2oo3 fault tolerant system increases both mission
reliability as well as safety.
• However, the "basic" reliability of the system will in this case still be lower than a
non redundant (1oo1) or 2oo2 system!
• Basic reliability refers to all failures, including those that might not result in
system failure, but do result in maintenance repair actions, logistic cost, use of
spares, etc.
• For example, the replacement or repair of 1 channel in a 2oo3 voting system that
is still operating with one failed channel (which in this state actually has become a
1oo2 system) is contributing to basic unreliability but not mission unreliability.
• Also, for example, the failure of the taillight of an aircraft is not considered as a
mission loss failure, but does contribute to the basic unreliability.

226. Detectability and common cause failures
• When using fault tolerant (redundant architectures) systems or
systems that are equipped with protection functions, detectability of
failures and avoidance of common cause failures becomes paramount
for safe functioning and/or mission reliability.

227. Reliability versus Quality (Six Sigma)
• Six-Sigma has its roots in manufacturing and Reliability engineering is more
related to systems engineering.
• The systems engineering process is a discovery process that is quite unlike
a manufacturing process.
• A manufacturing process is focused on repetitive activities that achieve
high quality outputs with minimum cost and time.
• The systems engineering process must begin by discovering the real
(potential) problem that needs to be solved; the biggest failure that can be
made in systems engineering is finding an elegant solution to the wrong
problem (or in terms of reliability: "providing elegant solutions to the
wrong root causes of system failures").

228. • The everyday usage term "quality of a product" is loosely taken to
mean its inherent degree of excellence.
• In industry, this is made more precise by defining quality to be
"conformance to requirements at the start of use".
• Assuming the product specifications adequately capture customer (or
rest of system) needs, the quality level of these parts can now be
precisely measured by the fraction of units shipped that meet the
detailed product specifications.

229. • But are (derived, lower level) requirements and related product
specifications validated?
• Will it later result in worn items and systems, by general wear, fatigue
or corrosion mechanisms, debris accumulation or due to maintenance
induced failures?
• Are there interactions on any system level (as investigated by for
example Fault Tree Analysis)?
• How many of these systems still meet function and fulfill the needs
after a week of operation?

230. • What performance losses occurred?
• Did full system failure occur?
• What happens after the end of a one-year warranty period?
• And what happens after 50 years (a common lifetime for aircraft,
trains, nuclear systems, etc...)?
• That is where "reliability" comes in.

231. • Quality is a snapshot at the start of life and mainly related to control of
lower level product specifications and reliability is (as part of systems
engineering) more of a system level motion picture of the day-by-day
operation for many years.
• Time zero defects are manufacturing mistakes that escaped final test
(Quality Control).
• The additional defects that appear over time are "reliability defects" or
reliability fallout.
• These reliability issues may just as well occur due to Inherent design issues,
which may have nothing to do with non-conformance product
specifications.

232. • Items that are produced perfectly - according all product specifications -
may fail over time due to any single or combined failure mechanism (e.g.
mechanical-, electrical-, chemical- or human error related).
• All these parameters are also a function of all possible variances coming
from initial production.
• Theoretically, all items will functionally fail over infinite time.
• In theory the Quality level might be described by a single fraction defective.
• To describe reliability fallout a probability model that describes the fraction
fallout over time is needed. This is known as the life distribution model.

233. • Quality is therefore related to Manufacturing and Reliability is more related
to the validation of sub-system or lower item requirements, (System or
Part) inherent Design and life cycle solutions.
• Items that do not conform to (any) product specification in general will do
worse in terms of reliability (having a lower MTTF), but this does not
always have to be the case.
• The full mathematical Quantification (in statistical models) of this
combined relation is in general very difficult or even practical impossible.
• In case manufacturing variances can be effectively reduced, six sigma tools
may be used to find optimal process solutions and may thereby also
increase reliability.
• Six Sigma may also help to design more robust related to manufacturing
induced failures.

234. • In contrast with Six Sigma, Reliability Engineering Solutions are generally
found by having a focus into a (system) design and not on the
manufacturing process.
• Solutions are found in different ways, for example by simplifying a system
and therefore understanding more mechanisms of failure involved,
detailed calculation of material stress levels and required safety factors,
finding possible abnormal system load conditions and next to this also to
increase design robustness against variation from the manufacturing
variances and related failure mechanisms.
• Furthermore reliability engineering use system level solutions, like
designing redundancy and fault tolerant systems in case of high availability
needs (see chapter Reliability engineering vs Safety engineering above).