ottimizzazione 2023 parte II RID.pdf

Structural Design and Optimization
Part II – V edition, 2023
Prof. Ing. Franco Bontempi
Docente di TEORIA E PROGETTO DI PONTI – GESTIONE DI PONTI E GRANDI STRUTTURE
Facoltà di Ingegneria Civile e Industriale
Università degli Studi di Roma La Sapienza
franco.bontempi@uniroma1.it
29-Jan-23 STRUCTURAL DESIGN AND OPTIMIZATION 2023 2
Abstract
• Structural engineering can nowadays make use of very remarkable computational
tools. This availability can lead to affirm that the entire process of designing and
verifying the quality of a structure can be automated.
• Paradoxically, the opposite is true: powerful tools require deep reflections on what
are the bases of structural design in order to consciously address the procedures
of representation and optimization available today.
• In this only in this way, that optimization can represent an effective fundamental
component of structural design, in order to try to maximize the performance of
the structures and their sustainability.
• In order to obtain a correct optimization, it is therefore necessary to examine the
roots of the design, to understand its meanings and evaluate the limits of the
different numerical implementations.
• The lessons of the course will develop the concepts underlying structural
optimization while presenting specific significant applications
• Monday 30 January
15.00-18.00 (3 hours)
• Prof. Franco Bontempi
• Basis of structural design
• The art of structural engineering. The
principles of design. The creative process.
Structural concept. Design context and
structural requirements. Structural values.
Design by evolution and innovation.
Integration and specialization. Path of
loads. Structural schemes and their limits.
Structural analysis.
DAY 1
• D. Billington, The Tower and the Bridge: The New Art of
Structural Engineering
• E. S. Ferguson, Engineering and the Mind’s Eye.
• H. Simon, The Science of Artificial.
• G. Madhavan, Come pensano gli ingegneri. Intelligenze
applicate.
• B. Munari, Da cosa nasce cosa. Appunti per una
metodologia progettuale.
• P. L. Nervi, Scienza o arte del costruire?
• E. Torroja, La concezione Strutturale.
• L.E. Robertson, The Structure of Design.
• W. Lidwell, K. Holden, J. Butler, Universal Principle of Design.
• U. Kirsch, Structural Optimization. Fundamentals and
Applications.
• S. Adriaenssens, P. Block, D. Veenendaal, C.Williams. Shell
Structures for Architecture: Form Finding and Optimization.
• M. Sarkisian, Designing Tall Buildings: Structure as
Architecture.
• Tuesday 31 January
10.00-13.00 (3 hours)
• Qualitative and quantitative aspects of
structural optimization
• Setting up the structural problem.
Uncertainties and undefinitions. Limited
rationality and partial knowledge.
Structural modeling. Solution of the
structural problem and its critical
judgment. Naïve setting of optimization
problems. Optimization algorithms.
Stochastic aspects. Heuristic approaches.
Discrete structural schemes.
DAY 2
15.00-18.00 (3 hours)
• Dr. Valentina Tomei
• Optimization strategies for the design of
gridshell type structures
• Notes on the types of structural optimization
and on the single-objective and multi-
objective optimization algorithms of an
evolutionary type. Notes on strategies for
finding the optimal shape: form-finding.
Gridshell type structures. The role of form in
gridshells. The role of structural optimization
in gridshell design: examples of design
strategies.
• Wednesday 1st February
15.00-18.00 (3 hours)
• Prof. Elena Mele
• Optimization of structures for tall
buildings
• Behavior of tall buildings, "premium for
height" and structural types. Notes on the
evolution of the structural design of tall
buildings and recent trends: the search for
efficiency and the role of robustness.
Diagrid structures and structural patterns:
sectional and topological optimization.
Patterns inspired by isostatic lines.
Generative design and shape grammar.
DAY 3
10.00-13.00 (3 hours)
• Prof. Francesco Petrini
• Optimization in the performance design of
buildings under wind action and seismic
action
• Application of optimization methods to real
problems. Performance-based design: general
aspects and specific characteristics.
Optimization of devices for the control of
vibrations of tall buildings under the action of
the wind. Risk-based design of reinforced
concrete frames in seismic zone with
development of an optimization procedure
based on the gradient method.
DAY 4
• Thursday 2nd February
10.00-13.00 (3 hours)
• Dr. Innocenzo Becci
• Seismic recovery of prefabricated buildings
with the use of dissipation systems and
decoupling systems
• With a technical practice setting, the
presentation concerns the seismic
improvement design approach on
prefabricated structures with the use of
mechanical connection and dissipation
devices. For the typological conception of the
mechanisms and for the materials used in the
systems, the selection criteria and the
experiences of experimental feedback which
have made it possible to validate the expected
operating principles will be exposed.
15.00-18.00 (3 hours)
• Prof. Arch. Patrizia Trovalusci
• The construction of form in architectural
works: critical issues and advantages of
the mathematical/numerical approach
• The lesson presents, explores and
discusses mainly qualitative aspects
concerning works of architecture and is
accompanied by some examples of study
addressed in some degree theses (which
are available at this link:
https://sites.google.com/a/uniroma1.it/pa
triziatrovalusci/tesi-di-laurea/tesi-di-
laurea-sdc)

• Tuesday 26 October 10.00-13.00 (3 hours)
• Tuesday 26 October 15.30-18.30 (2 hours)
laurea-sdc)
DAY 2
FORMULABILE
NON
FORMULABILE
Esprimibile in equazioni
HARD
RESTRICTED
Non esprimibile in equazioni
SOFT
WIDE
Prima
lezione
Seconda
lezione
NON
FORMULABILE
Non esprimibile in equazioni
SOFT
WIDE
Prima
lezione
8. Constructive approach
• Insight in a structural problem
• Simple observations
9. Algorithms
• Direct way: basic aspects
• Surrogate
• Not so basic aspects
• Heuristics
• In another (indirect) way:
optimality criteria
10.Levels in action
• Sizing
• Morphology
• Topology
• Generative
Index Part II
1983
CONSTRUCTIVE APPROACH
8
CONSTRUCTIVE APPROACH
STRUCTURAL DESIGN AND OPTIMIZATION 2023 16
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19
INSIGHT
IN A STRUCTURALPROBLEM

Load Path
21
1
Load Transfer Mechanism
2
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STRUCTURAL DESIGN AND OPTIMIZATION 2023
1 - Strutture resistenti per forma
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In tutta la struttura c'è solo o trazione o compressione
STRUCTURAL DESIGN AND OPTIMIZATION 2023 25 29-Jan-23 STRUCTURAL DESIGN AND OPTIMIZATION 2023 26
2 - Strutture resistenti per azione vettoriale
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Nella struttura ci sono elementi che lavorano uniformemente
a trazione o a compressione (tiranti o puntoni)
3 - Strutture resistenti per flessione
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Nelle sezioni della struttura c'è sia trazione sia compressione
(diagramma degli sforzi a farfalla)

4 - Strutture resistenti per superficie
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La struttura distribuisce ed equilibra i carichi con azione membranale
(distribuzione di sforzo uniforme sullo spessore)
Structural System
34
3
35
x
x
x
x
Fault
Fault
Fault
Fault
Overall plant
1st level
Plant item
2nd level
Control loop
3rd level
Element/Component
4th level
STRUTTURA
GLOBALE
SOTTO-STRUTTURA
2 livello
ELEMENTO STRUTURALE
3 livello
COMPONENTE
4 livello
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Es.

MAIN
STRUCTURAL
SYSTEM
AUXILIARY
STRUCTURAL
SYSTEM
SECONDARY
STRUCTURAL
SYSTEM
SPECIAL
DECK ZONES
BRIDGE
DECK
HIGHWAY SYSTEM
RAILWAY SYSTEM
OPERATION
MAINTENANCE
EMERGENCY
FOUNDATION OF TOWERS
TOWERS
ANCHORAGES
SUPPORTING
CONDITION
HIGHWAY BOX-GIRDER
CROSS BOX-GIRDER
RAILWAY BOX-GIRDER
INNER
OUTER
BRIDGE
SUPERSTRUCTURE
MACRO-LEVELS
MESO-LEVELS
MAIN CABLES
HANGERS
SUSPENSION
SYSTEM
SADDLES
OUTER
HIGHWAY BOX-GIRDER
CROSS BOX-GIRDER
RA
R
R ILWAY BOX-GIRDER
FOUN
U
U DATION OF TOWERS
TOWERS
AN
A
A CHORA
R
R GES
MAIN CABLES
SADDLES
Structures Essentials
• Micro-level:
local size of the sections, i.e., thickness, area, inertia, … (Detailed
Geometry)
• Meso-level:
form of the structural element or structural part (substructure), i.e.
main longitudinal axis, curvature, profile, … (Global Geometry)
• Macro-level:
connections of the different structural parts (Load Path)
42
local size of the sections, i.e., thickness, area, inertia, … (Detailed
4
http://carat.st.bv.tum.de/caratuserswiki/index.php/Users:Structural_Optimization/General_Formulation
Optimization Levels (1)
43
Optimization Levels (2)
Micro-level:
local size of the sections,
i.e. thickness, area,
inertia, … (Detailed
Geometry)
Meso-level:
form of the structural
element or structural part
(substructure), i.e. main
longitudinal axis, curvature,
profile, … (Global Geometry)
Macro-level:
connections of the
different structural
parts (Load Path)
44
SIMPLE OBSERVATIONS
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47
47
The nature of optimum (1)
48
Example (1)
49
Example (2)
50

51
Robustness of the formulation
The nature of optimum (2)
A sub-optimal solution
to a problem is one
that is less than perfect.
Slack situation: loose and not pulled tight.
53
Limiti approssimativi abbastanza larghi
ALGORITHMS
9
DIRECT WAY: BASIC ASPECTS
57
Direct
Approach
for
Optimization
1D
function
–
Line
Optimization
(1
direction)
Bracketing of the minimum
59
1° step
Δ1
βΔ1
a1 b1
c1
f(x)
x
60

2° step
Δ2
βΔ2
a2
b2
c2
f(x)
x
61
3° step
Δ3
βΔ3
a3
b3
c3
f(x)
x
β=0.61803
62
Quadratic Fitting
63
65
Bracketing with parabolic interpolation
66
Cubic Fitting
67
69
Convergence
Criteria

71
73
75
Searching in the good direction
77
Scaling of Design Variables
• It is often desirable to eliminate wide variations in the magnitudes
of design variables and the value of constraints by normalization.
• Design variables may be normalized to order 1 by scaling.
• This operation may enhance the efficiency and reliability of the
numerical optimization process.
78
79

81
SURROGATE
83
Design of Experiments (DOE)
84
• In general usage, design of experiments (DOE) or experimental design is the
design of any information-gathering exercises where variation is present,
whether under the full control of the experimenter or not. However, in
statistics, these terms are usually used for controlled experiments.
• Formal planned experimentation is often used in evaluating physical objects,
chemical formulations, structures, components, and materials.
• Other types of study, and their design, are discussed in the articles on
computer experiments, opinion polls and statistical surveys (which are types
of observational study), natural experiments and quasi-experiments (for
example, quasi-experimental design).
Sampling Points (1)
85
Sampling Points (2)
86
Simulation & Approximation of the Response
87
The Function: y(x1,x2)
88
The Sensibility of the Function
89
STRATEGY #1: SENSITIVITY - Governance of Priorities
90

The Bounding of the Function
91
STRATEGY #2: BOUNDING - Behavior Governance
p
l(p)
l
p
l(p)
l
92
NOT SO BASIC ASPECTS
Relative
Gain
1
95
96
97
97
98
A decision point in the development of the solution
100
100

101
101
Multilevel Optimal Design
102
2
Decomposition
103
Multilevel Structures
104
105
107
1997
HEURISTICS

Heuristics
• A heuristic technique (/hjᵿˈrɪstᵻk/; Ancient Greek: εὑρίσκω, "find"
or "discover"), often called simply a heuristic, is any approach to
problem solving, learning, or discovery that employs a practical
method not guaranteed to be optimal or perfect, but sufficient for
the immediate goals.
• Where finding an optimal solution is impossible or impractical,
heuristic methods can be used to speed up the process of finding a
satisfactory solution.
• Heuristics can be mental shortcuts that ease the cognitive load of
making a decision.
111
εὑρίσκω
• Heuristic (/hjʉˈrɪstɨk/; Greek: "Εὑρίσκω", "find" or "discover")
refers to experience-based techniques for problem solving,
learning, and discovery that give a solution which is not
guaranteed to be optimal. Where the exhaustive search is
impractical, heuristic methods are used to speed up the process of
finding a satisfactory solution via mental shortcuts to ease the
cognitive load of making a decision. Examples of this method
include using a rule of thumb, an educated guess, an intuitive
judgment, stereotyping, or common sense.
• In more precise terms, heuristics are strategies using readily
accessible, though loosely applicable, information to control
problem solving in human beings and machines.
112
εὑρίσκω
• L'euristica (dalla lingua greca εὑρίσκω, letteralmente "scopro" o
"trovo") è una parte dell'epistemologia e del metodo scientifico.
• Si definisce procedimento euristico, un metodo di approccio alla
soluzione dei problemi che non segue un chiaro percorso, ma che
si affida all'intuito e allo stato temporaneo delle circostanze, al fine
di generare nuova conoscenza. È opposto al procedimento
algoritmico. In particolare, l'euristica di una teoria dovrebbe
indicare le strade e le possibilità da approfondire nel tentativo di
rendere una teoria progressiva.
113
Bounded Rationality
• Bounded rationality is the idea that in decision-making, rationality of
individuals is limited by the information they have, the cognitive limitations
of their minds, and the finite amount of time they have to make a decision.
• It was proposed by H. A. Simon as an alternative basis for the mathematical
modeling of decision making, as used in economics, …; it complements
rationality as optimization, which views decision-making as a fully rational
process of finding an optimal choice given the information available.
• Another way to look at bounded rationality is that, because decision-makers
lack the ability and resources to arrive at the optimal solution, they instead
apply their rationality only after having greatly simplified the choices
available. Thus, the decision-maker is a satisfier, one seeking a satisfactory
solution rather than the optimal one.
114
1
119
Simulated Annealing (Metropolis)
• Simulated annealing (SA) is a generic probabilistic heuristic for the global
optimization problem of locating a good approximation to the global optimum of a
given function in a large search space.
• The name and inspiration come from annealing in metallurgy, a technique
involving heating and controlled cooling of a material to increase the size of its
crystals and reduce their defects.
• This notion of slow cooling is implemented in the Simulated Annealing algorithm
as a slow decrease in the probability of accepting worse solutions as it explores the
solution space. Accepting worse solutions is a fundamental property of heuristics
because it allows for a more extensive search for the optimum.
• The method is an adaptation of the Metropolis-Hastings algorithm, a Monte Carlo
method to generate sample states of a thermodynamic system, invented by M.N.
Rosenbluth and published in a paper by N. Metropolis et al. in 1953.

121
Basic version (1)
122
Basic version (2)
123
125
Points for SA
• Diameter of the search graph
• Transition probabilities
• Acceptance probabilities
• Efficient candidate generation
• Barrier avoidance
• Cooling schedule
126
127
129
2
130

Nelder-Mead Method (Amoeba)
• The Nelder–Mead method or downhill simplex method or amoeba
method is a commonly used nonlinear optimization technique,
which is a well-defined numerical method for problems for which
derivatives may not be known.
• The Nelder–Mead technique is a heuristic search method that was
proposed by John Nelder & Roger Mead (1965) for minimizing an
objective function in a many-dimensional space.
131
133
135
Basic movements
National Vegetable Research Station
136
;-)
137
2
139
Genetic Algorithm (GA)
• The original motivation for the GA approach was a biological analogy. In the
selective breeding of plants or animals, for example, offspring are sought
that have certain desirable characteristics, characteristics that are
determined at the genetic level by the way the parents’ chromosomes
combine. In the case of GAs, a population of strings is used, i.e.
chromosomes.
• The recombination of strings is carried out using analogies of genetic
crossover and mutation, and the search is guided by the results of evaluating
the objective function f for each string in the population.
• Based on this evaluation, strings that have higher fitness (i.e., represent
better solutions) can be identified, and these are given more opportunity to
breed.
140

Terminology
141
143
Coding
• One of the distinctive features of the GA approach is to allow the
separation of the representation of the problem from the actual
variables in which it was originally formulated.
• In line with biological usage of the terms, it has become customary
to distinguish the ‘genotype’—the encoded representation of the
variables, from the ‘phenotype’—the set of variables themselves.
144
Translation
Genotype space = {0,1}L
(mappa)
Phenotype space
(territorio)
Encoding
(representation)
Decoding
(inverse representation)
01101001
01001001
10010010
10010001
145
Esempio: numero intero fra -7 e +7
Example
147
Mating, Mutation, Selection
149
One or Two
150

IN ANOTHER (INDIRECT) WAY:
OPTIMALITY CRITERIA
Optimality Criteria
152
153
155
9. Algorithms
• Surrogate
• Heuristics
• In another (Indirect) way:
optimality criteria
10.Levels in action
• Sizing
• Morphology
• Topology
• Generative
Index Part II
9. Algorithms
• Surrogate
• Heuristics
• In another (Indirect) way:
optimality criteria
LEVELS IN ACTION
10
LEVELS IN ACTION
Optimization Levels
Micro-level:
local size of the sections,
i.e. thickness, area,
inertia, … (Detailed
Geometry)
Meso-level:
form of the structural
element or structural part
(substructure), i.e. main
longitudinal axis, curvature,
profile, … (Global Geometry)
Macro-level:
connections of the
different structural
parts (Load Path)
159
SIZING

161
Fully Stressed Design (FSD)
162
163
Strutture isostatiche / iperstatiche
• Nelle strutture isostatiche il regime statico ovvero lo stato di sforzo
è determinato unicamente dalle condizioni di equilibrio (tra l’altro,
considerando piccoli spostamenti, il regime statico non è
influenzato dalle non linearità di materiale eventualmente
presenti).
• Nelle strutture iperstatiche, il regime statico ovvero la distribuzione
delle sollecitazioni e degli sforzi dipende dalla distribuzione delle
rigidezze, considerando che parti strutturali più rigide attirano
maggiori sollecitazioni e sforzi.
FSD in action
165
167
169
Solution that satisfies everything
[ ]
i
i
Design a
a max
4
,...
1
=
=
170

Industrial α - sections
171
A / W for HEB for α = h
A = 9E-13x6
- 3E-09x5
+ 5E-06x4
- 0,0036x3
+ 1,2509x2
- 139x + 7185,3
W = 1E-11x6
- 9E-08x5
+ 0,0002x4
- 0,2162x3
+ 113,67x2
- 17128x + 881393
0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
0 200 400 600 800 1000 1200
A
W
Poly. (A)
Poly. (W)
172
IPE HEB
173
Nota
• Con tale tecnica, si ottiene un dimensionamento che sfrutta a
pieno la capacità portante della sezione.
• Il progetto è basato quindi sul raggiungimento del requisito di
resistenza: un elemento strutturale e la struttura nel complesso
devono però soddisfare a differenti altri requisiti.
• È possibile considerare indirettamente questi altri aspetti anche
con il FSD: basta agire sui valori dei limiti tensionali o sui valori dei
moltiplicatori αmax ed αmin per dimensionare l’elemento con
riferimento ad altri aspetti che non siano la sola resistenza.
175
175
Taglio / Instabilità
Es.
177
179

181
183
185
187
MORPHOLOGY
189

191
193
195
Geometry Parameter Based Optimization
197
Non-Parametric Optimization
198
Hybrid optimization
199
200

Michell
201
203
205
207
TOPOLOGY
209
210

211
211
morfologica
topologica
Es.
215
a b
Es. a
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b
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STRUCTURAL DESIGN AND OPTIMIZATION
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Mesolivello
-
morfologico

2023
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237
2023
Fundamental steps of the BG evolutionary process
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2023
240
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Macrolivello
-
topologico
2023
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2023
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2023
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2023
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Maillart’s Bridges
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Maillart
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Ponti Maillart
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SHORTCUTS: DISCRETE MODELS
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Nb: vhange in topology
Morphology Optimization via OC
273
275
277
Es.

1° Step
2° Step
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2023
298
Smoothing / Streamlining
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2023
299
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Design Process
300

Filters
301
303
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Engineering Design Phases
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Engineering …
• Minimum / maximum thicknesses
• Minimum / maximum lengths
•Symmetries
•Industrialized elements / components
•Manufacturing Procedures
(forging, bending, weldability, ...)
• Constructability
•Maintenability
•Inspectability
REFINED DESIGN
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PROBLEM
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Meccanismo a cursore: 1a fase, aperto
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Meccanismo a cursore: 2a fase, chiuso
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PORTATA MENSOLA
• La stragrande maggioranza dei tegoli (più dell’80% del
mercato USA) necessitano di una mensola con
capacità portante ULTIMA (UL) intorno ai 70 Kips.
• Dalle analisi siamo convinti che sarà possibile ridurre,
almeno in parte, il peso della mensola. In ogni caso il
peso complessivo della mensola non potrà superare i
7 Kg.
• Note:
• 70 Kips ULS = 70 x 4.45 kN = 312 kN = 31.2 t
• 70 / 2.5 = 28 Kips -> 312/2.5 = 125 kN = 12.5 t
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1.0 1.6 0.6
ANCHORAGEFORCE
SHEAR
(SUPPORTREACTION)
RIGHT END REACTION
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1.0 1.6 0.6
ANCHORAGEFORCE
SHEAR
(SUPPORTREACTION)
RIGHT END REACTION
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Classe di resistenza acciaio
• Si è deciso di adottare per la forgiatura della mensola, acciaio tipo
S460M (ASTM 913 Grade 65) il cui valore di snervamento è 460
N/mm2 ed è particolarmente tenace e resiliente anche a basse
temperature.
• Il forgiatore ha già confermato la disponibilità ad usare questo acciaio.
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1.0 1.6 0.6
ANCHORAGE FORCE
SHEAR
(SUPPORT REACTION)
RIGHT END REACTION
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12/20/2012 333
Limit
Stat
e
λ Shear
(slice 1.9685
inch)
Anchorage
(slice
1.9685
inch)
Right end
(slice
1.9685
inch)
Slice 0.3937
inch
(model)
Slice 3.1496
inch
(suggested)
kN Kips kN Kips kN Kips kN Kips kN Kips
SLS 1.0 120 26.98 190 42.71 72 16.19 24 5.40 192 43.16
ULS 1.5 180 40.47 285 64.07 108 24.28 36 8.09 288 64.74
SILS 1.9 230 51.71 365 82.06 139 31.25 45 10.12 365 82.06
1.0 1.6 0.6
ANCHORAGE FORCE
SHEAR
(SUPPORT REACTION)
RIGHT END REACTION
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BASIC ANALYSIS
29-Jan-23 334
29-Jan-23 335
Comportamento Stringer&Panel
29-Jan-23 336
Airframe Stringer & Panel
29-Jan-23 337
Stringer Panel Method (SPM)
29-Jan-23 338
STRINGERS
29-Jan-23 339
STRINGERS PROPERTIES
29-Jan-23 340

CONNECTION PROPERTIES
29-Jan-23 341
PANELS
29-Jan-23 342
PANELS PROPERTIES
29-Jan-23 343
29-Jan-23 345
SWL elastic behavior
29-Jan-23 347
SWL elastic behavior
29-Jan-23 348
USL elastic behavior
29-Jan-23 349
USL elastic behavior
29-Jan-23 350

USL elasto-plastic behavior
29-Jan-23 351
29-Jan-23 352
29-Jan-23 353
HOLES
29-Jan-23 355
correnti
fori
29-Jan-23 357
Forgiatura
29-Jan-23 358
COMPARISON
ANSYS - ABAQUS
29-Jan-23 359
Ansys
29-Jan-23 360

Ansys
Stato Limite di Esercizio Richiesto F = 120 KN
Total mechanical strain intensity
29-Jan-23 361
Ansys
Stato Limite Ultimo Richiesto F=180 KN
29-Jan-23 362
Ansys
Stato Limite di Collasso Richiesto F=230 KN
29-Jan-23 363
Ansys
Stato Limite di Collasso Effettivo F = 260 KN
29-Jan-23 364
Abaqus
29-Jan-23 365
Abaqus
29-Jan-23 366
Abaqus
Stato Limite di Esercizio Effettivo F = 170 KN
29-Jan-23 367
Abaqus
29-Jan-23 368
Abaqus
Stato Limite Ultimo Effettivo F = 195 KN
29-Jan-23 369
Abaqus
29-Jan-23 370

Abaqus
Stato Limite di Collasso Effettivo F = 275 KN
29-Jan-23 371
Ansys Vs Abaqus
29-Jan-23 372
Abaqus
Ansys
29-Jan-23 373
Abaqus
Ansys
29-Jan-23 374
Abaqus
Ansys
29-Jan-23 375
PUSHOVER
0
50
100
150
200
250
300
350
0 5 10 15
Force
[KN]
Vert_Displ [mm]
Abaqus_ottimizzata (3D model) Ansys_Ottimizzata (2D model)
29-Jan-23 376
REFINED DESIGN
29-Jan-23 377
REFINED DESIGN
29-Jan-23 378
Mesh
Str
Str
Str
Str
Str
o
Str
Str
Str
Str
Str
N
o
o N
N
GER
29-Jan-23 379
Mesh
Str
Str
Str
Str
Str
o
Str
Str
Str
Str
Str
N
o
o N
N
GER
29-Jan-23 380

λ=1.0
29-Jan-23 381
λ=1.5
29-Jan-23 382
λ=1.9
29-Jan-23 383
Mesh + Concrete Block
29-Jan-23 384
λ=1.0 – 120 kN – 28 Kips
29-Jan-23 385
λ=1.5 – 180 kN – 40 Kips
29-Jan-23 386
λ=1.9 – 230 kN – 52 Kips
29-Jan-23 387
Concrete Block - λ=1.0
388
29-Jan-23 388
389
29-Jan-23 389
390
29-Jan-23 390

Structural Response
λ=1.9 – 230 kN – 52 Kips
λ=1.5 – 180 kN – 40 Kips
λ=1.0 – 120 kN – 28 Kips
29-Jan-23 391
UNDER FIRE
(ISO Fire - Steel Temperature)
29-Jan-23 392
Steel mechanical properties degradation
T
<=100°C
200°C
400°C
600°C
800°C
500°C
2%
e
20%
0.2% 15%
s
fyk
29-Jan-23 393
0
200
400
600
800
1000
0 10 20 30 40 50 60
ISO 834
θ steel
ISO Fire - Steel Temperature
29-Jan-23 394
ANSYS
ABAQUS
PANEL STRESS, t= 0 sec, T= 20 °C, Yield stress 450 N/mm2
29-Jan-23 395
ANSYS
ABAQUS
29-Jan-23 396
ANSYS
ABAQUS
29-Jan-23 397
ANSYS
ABAQUS
29-Jan-23 398
ANSYS
ABAQUS
29-Jan-23 399
0
2
4
6
8
10
12
14
0 200 400 600 800
displ
[mm]
TEMP [°C]
Ansys
Abaqus
Structural Response (1)
29-Jan-23 400

0
2
4
6
8
10
12
0 5 10 15
displ
[mm]
Time [min]
Ansys
Abaqus
Structural Response (2)
29-Jan-23 401
0
200
400
600
800
1000
1200
0 20 40 60 80 100 120
ISO 834
Acciaio non protetto
pittura intumescente
schiuma PROMAFOAM d=7mm
Gesso
Time [min]
TEMP
[°C]
Protective Measures
29-Jan-23 402
EXPERIMENTAL RESULTS
29-Jan-23 403
29-Jan-23 405
29-Jan-23 407
Mensola ottimizzata peso ≈ 5.3 kg
Roma, 03 dicembre 2012
29-Jan-23 408
2D

411
3D
415
415
416
Vincoli funzionali

421
421
Es.
http://www.dezeen.com/2013/08/22/qatar-national-convention-centre-by-arata-isozaki/
425
425

433
GENERATIVE
437
Script

441
441
443
http://thecreatorsproject.vice.com/blog/cgi-crowd-simulation-battle
446
9. Algorithms
• Surrogate
• Heuristics
• In another (indirect) way:
optimality criteria
10.Levels I action
• Sizing
• Morphology
• Topology
• Generative
Index Part II

Abstract
• Structural engineering can nowadays make use of very remarkable computational
tools. This availability can lead to affirm that the entire process of designing and
verifying the quality of a structure can be automated.
• Paradoxically, the opposite is true: powerful tools require deep reflections on what
are the bases of structural design in order to consciously address the procedures
of representation and optimization available today.
• In this only in this way, that optimization can represent an effective fundamental
component of structural design, in order to try to maximize the performance of
the structures and their sustainability.
• In order to obtain a correct optimization, it is therefore necessary to examine the
roots of the design, to understand its meanings and evaluate the limits of the
different numerical implementations.
• The lessons of the course will develop the concepts underlying structural
optimization while presenting specific significant applications
• Monday 30 January
15.00-18.00 (3 hours)
• Basis of structural design
• The art of structural engineering. The
principles of design. The creative process.
Structural concept. Design context and
structural requirements. Structural values.
Design by evolution and innovation.
Integration and specialization. Path of
loads. Structural schemes and their limits.
Structural analysis.
DAY 1
• D. Billington, The Tower and the Bridge: The New Art of
Structural Engineering
• E. S. Ferguson, Engineering and the Mind’s Eye.
• H. Simon, The Science of Artificial.
• G. Madhavan, Come pensano gli ingegneri. Intelligenze
applicate.
• B. Munari, Da cosa nasce cosa. Appunti per una
metodologia progettuale.
• P. L. Nervi, Scienza o arte del costruire?
• E. Torroja, La concezione Strutturale.
• L.E. Robertson, The Structure of Design.
• W. Lidwell, K. Holden, J. Butler, Universal Principle of Design.
• U. Kirsch, Structural Optimization. Fundamentals and
Applications.
• S. Adriaenssens, P. Block, D. Veenendaal, C.Williams. Shell
Structures for Architecture: Form Finding and Optimization.
• M. Sarkisian, Designing Tall Buildings: Structure as
Architecture.
10.00-13.00 (3 hours)
DAY 2
15.00-18.00 (3 hours)
• Dr. Valentina Tomei
• Optimization strategies for the design of
gridshell type structures
• Notes on the types of structural optimization
and on the single-objective and multi-
objective optimization algorithms of an
evolutionary type. Notes on strategies for
finding the optimal shape: form-finding.
Gridshell type structures. The role of form in
gridshells. The role of structural optimization
in gridshell design: examples of design
strategies.
15.00-18.00 (3 hours)
• Prof. Elena Mele
• Optimization of structures for tall
buildings
• Behavior of tall buildings, "premium for
height" and structural types. Notes on the
evolution of the structural design of tall
buildings and recent trends: the search for
efficiency and the role of robustness.
Diagrid structures and structural patterns:
sectional and topological optimization.
Patterns inspired by isostatic lines.
Generative design and shape grammar.
DAY 3
10.00-13.00 (3 hours)
• Prof. Francesco Petrini
• Optimization in the performance design of
buildings under wind action and seismic
action
• Application of optimization methods to real
problems. Performance-based design: general
aspects and specific characteristics.
Optimization of devices for the control of
vibrations of tall buildings under the action of
the wind. Risk-based design of reinforced
concrete frames in seismic zone with
development of an optimization procedure
based on the gradient method.
DAY 4
10.00-13.00 (3 hours)
• Dr. Innocenzo Becci
• Seismic recovery of prefabricated buildings
with the use of dissipation systems and
decoupling systems
• With a technical practice setting, the
presentation concerns the seismic
improvement design approach on
prefabricated structures with the use of
mechanical connection and dissipation
devices. For the typological conception of the
mechanisms and for the materials used in the
systems, the selection criteria and the
experiences of experimental feedback which
have made it possible to validate the expected
operating principles will be exposed.
15.00-18.00 (3 hours)
laurea-sdc)
Structural Design and Optimization
Part II – V edition, 2023
Prof. Ing. Franco Bontempi
Docente di TEORIA E PROGETTO DI PONTI – GESTIONE DI PONTI E GRANDI STRUTTURE
Facoltà di Ingegneria Civile e Industriale
Università degli Studi di Roma La Sapienza
franco.bontempi@uniroma1.it

ottimizzazione 2023 parte II RID.pdf

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