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Optimization of sealing casting by identifying solidification defect and improvement of strength by casting simulation
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Optimization of sealing casting by identifying solidification defect and improvement of strength by casting simulation
1.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 1247 Optimization of sealing casting by identifying solidification defect and improvement of strength by casting simulation Suhas M. More1, R. M. Chanmanwar2 1Student, Mechanical Engineering Department, Walchand College of Engineering, Sangli, Maharashtra, India 2Asst. Prof. Mechanical Engineering Department, Walchand College of Engineering, Sangli, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The casting industry employsavarietyof ways to address casting fault issues. A large number of casting rejections results in a waste of both money and effort. Single flaws in casting might have a single or several causes, thus it's critical to figure out what's causing the problem. This industry's productivity has risen to an all-time high. Modern technology has reduced resource use while simultaneously reducing faults. Adopting a more controlled approach to describing, recognizing, and regulating the underlying cause of an issue will be advantageous. The primary goal of this research is to identify solidification defect and minimize it by optimizing new design with help of casting simulation software. This research will aid in improving strength of material and hence quality. Key Words: Sand casting, Solidification defect, ProCAST, L-type Sealing casting, shrinkage porosity, Misrun 1. INTRODUCTION Casting is one of the main economical production processes used in industry and is a complex process that involves important metallurgical and mechanical aspects. The rate of solidification largely determines the microstructure, which in turn determines mechanical properties such as strength, hardness, machinability, etc. The location, size, and shape of risers in a casting depend on the shape, mold design, and heat of the casting, properties of the metal and other factors, process parameters. Improperly designed riser and gate systems will always result in defective moldswithshrinkage cavities or poor experimental results, which are always better for mold design and development and to achieve optimal process parameters. However, this can be expensive, time consuming, and in some cases impossible. Therefore, the casting simulation process is a convenient way to properly design a riser system and analyze the effect of various parameters. The number of foundry simulation programs in India is also increasing day by day, as it essentially replacesorminimizes shop floor testing to achieve the desired internal quality in the maximum possible time. It can greatly reduce iterations on the shop floor and is mainly used for proof-of-concept. Simulation programs generally increase the confidence of foundries when creating more complex castings (complex, large) with higher margins. It also provides a scientific and documented basis for quality assurance and certification. 1.1 Related Work Ravi (2008) have studiedatthebenefitsofcastingsimulation, bottlenecks and best practices for overcoming bottlenecks without burial testing, they provide quality assurance and significantly minimize lead times to cast the first good sample. Naveen (2014) has discussed the steps which is included in simulation the possible source of error and care to be has to be taken during the time of casting simulation process. According to him the designer should have confidence in casting simulation tool which are going to be used. The confidence level will come only by experience and usage of the tool to mimic effect of various process parameters. Prabhakara et al. (2006) have studied on the solidification mold filling simulation of green sand casting, ductile iron casting sand, and using casting simulation software such as PRO CAST, it was concluded that defects such as shrinkage, porosity, etc. could be eliminated. Itcan also improveyieldof the casting, optimize the gating system design & mold filling. Karl B. Rundman explained metal casting procedure, sand casting procedureand other casting procedure. He discusses the defects in casting. He also studies the solidification phenomena in casting procedure. C. W. Ammen [1979] He discussed the different elements required in sand castings. He also discussed the defects in sand casting. 1.2 Problem Definition: In order to remain competitive in today’s market, a modern foundry has to take full advantage of the benefits offered by casting simulation. These allow the foundry man toanalyses problems in detail, faster, and at an early stage in the design cycle, thus enabling decisionstobemadetowardsimproving design and quality. Therefore, the costs and the risk associated with the trial and error procedure of
2.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 1248 experimental castings are minimized. In the present dissertation we use the casting simulation software to identify the solidifying defects present in the sealing casting and an attempt was made to optimize the sealing casting. 1.3 Objectives The main objective of present investigation is optimization of sealing casting by casting simulation process. 1. To study the casting procedure, application,problemsand defects in sealing casting. 2. To do solidification Analysis of the existingsealingcasting. 3. To give solution for the defects like shrinkage, Misrun and improve strength of sealing casting by using casting simulation process. 4. To carry out the results of analysis. 2. Methodology In this chapter, the approach employed in the present work is briefly discussed. In this research, a sealing casting model constructed of grey cast iron is examined. For sand casting, different circumstances are simulated numericallyusingthe commercial software pro-CAST. Various solidification performance metrics, including temperature, hotspot, total shrinkage porosity, voidscontour,andsolidificationcontour, etc. The existing technology utilized for simulation of solidification is investigated as the foundation of this work. At the conclusion of the chapter, the findings obtained using the existing gating system for the moulds are discussed. Typically, simulation software consists of three primary components: (1) Pre-processing (the programme reads the CAD geometry and generates the mesh),(2)Mainprocessing (addition of boundary conditions and material data, filling, and temperature calculations), and (3) Post processing (presentation and evaluation). Based on Finite Element technology, ProCAST offers a comprehensive simulation solution for a wide variety of applications. proCAST's objective is to construct a finiteelementmodel,configurethe calculation, execute the analysis, and evaluate the findings. The following actions (procedures) were carried out in ProCAST's simulation of the seal casting process. Computer-aided design (3D) of a seal casting featuring a gating systemutilizingtheANSYSDesign Modeler programme. Save the CAD file in IGES format and import it into the proCAST software using the geometry transformation tool. Mesh the mould and cast using a 2D and 3D surface mesh and volume mesh. Input data includingvolume manager,interfaceHTC manager, process condition manager, and simulation parameters, and initiate simulation by selecting ProCAST with a solver count of four. Analyze the results with the view cast, such as temperature, solidification time, and fraction of solid and total shrinkage porosity. The steps related to simulationareshowninFigure 1. Fig -1: Steps Involved In Numerical Simulation of Solidification Process 2.1 Pre-processing (the programme reads the CAD geometry and generates the mesh) Figure 2 shows the isometric wireframe view of the casting mold used for the study. The dimensions of the same are given as below, Length = 300 mm, Width = 300 mm, Height = 120 mm. The model is drawn and developed in the Ansys Design Modelers software. The developed model is then imported for the meshing purpose. The meshing of the model is carried out in two steps, first the surface meshing is carried out followed by the volume meshing of the model. Both the
3.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 1249 surface meshing and volume meshing of the model are shown in Figure 3 and Figure 4 respectively. Fig -2: Isometric Wire Frame Model of the Casting Mold Used For the Study Fig -3: Surface Meshing Of the Model Fig -4: Volume Meshing Of the Model 2.2 Main processing (addition of boundary conditions and material data, filling, and temperature calculations) After meshing the main processing stagecomesin picture.In main processing material assignment, boundary condition and heat transfer conditions from body to mold should be given. Material assignment is done in volume manager as shown in figure 5. Fig -5: Volume Manager Boundary conditions aregiveninprocessconditionmanager as shown in figure 6, in which we generated inlet boundary condition as BC_inlet_2. In BC_inlet_2 we added mass flow rate and pouring temperature and also velocity component. Heat transfer condition from body to mold is given in interface HTC manager as shown in figure 7.
4.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 1250 Fig -6: Process Condition Manager Fig -7: Interface HTC Manager 2.3 Post processing (presentation and evaluation). Post processing is the last and important step in the simulation process. In post processing we got various contours, graphs charts, etc. our focus in this research is mainly on the shrinkage porosity, hotspot and misrun sensitivity. Figure 8 shows total shrinkage porosity of the existing model which is about 6.67% at different locations. Fig -8: Total Shrinkage Porosity of Existing Model Figure 9 shows the contour of hotspot on the existingmodel, from the figure we may say that existing model has several hotspots on its top surface. Misrun sensitivity of existing model is shown in figure 10, from the figure we may conclude that existingmodel hashighrisk misrunsensitivity. Fig -9: Hotspot on Existing Model Fig -10: Misrun Sensitivity of Existing Model 3. Modified Design of L type sealing Casting In the previous chapter the existing model of L type sealing casting is simulated inProCASTsoftware. The existingmodel has several casting defects which needed to be rectified. In present chapter, a modified designisdeveloped basedonthe several design calculation and the same is simulated in the ProCAST software under variable conditions. At the end of this chapter the results obtained from the numerical simulation of the modified L type sealing casting are discussed. 3.1 Pouring time Pouring time, For less than 40 Kg Where,
5.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 1251 T = Average section thickness in mm W = Mass of casting So, 3.2 Choke area Choke area: Where, W= casting mass in kg d=mass density of molten metal t=pouring time C=efficiency factor g=acceleration due to gravity mm/ H=effective metal head in mm So, 3.3 Gating Ratio and Sprue well Gating ratio = 1:2:1 (sprue: runner: gate) Choke area A = 201 mm2 Runner area from gating ratio (1:2): mm2 Ingate area from gating ratio (1:1) = 201 mm2 Sprue well area: mm2 mm 3.4 Riser [Note: Constant Canies equation for Grey Cast Iron a = 0.3, b = 0.03, c = 1.00] Substituting above values in to Canies equation for grey cast iron By trial and error method, Height of the riser = diameter of the riser = 7cm.
6.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 1252 3.5 Pre-processing (the programme reads the CAD geometry and generates the mesh) Figure 11 shows the isometric wireframe view of the modified casting mold used. The dimensions of the same are given as below, Length = 300 mm, Width = 300 mm, Height = 120 mm. The model is drawn and developed in the Ansys Design Modelers software. The modified model is thenimported for the meshing purpose. The meshing of the model is carried out in two steps, first the surface meshing is carried out followed by the volume meshing of the model. Both the surface meshing and volume meshing of the model are shown in Figure 12 and Figure 13 respectively. Fig -11: Isometric Wire Frame Modified Model of the Casting Mold Fig -12: Surface Meshing Of the Modified Model Fig -13: Volume Meshing Of the Modified Model 3.6 Main processing (addition of boundary conditions and material data, filling, and temperature calculations) After meshing the main processing stagecomesin picture.In main processing material assignment, boundary condition and heat transfer conditions from body to mold were given as per the existing model shown on figure 5, 6 and 7. 3.7 Post processing (presentation and evaluation). At post processing we got the contours of total shrinkage porosity, hotspot and misrun sensitivity. In figure 14 we can clearly see that total shrinkageporosityreducedandpresent at only few points. Fig -14: Total Shrinkage Porosity of Modified Model Figure 15 shows the contour of hotspot on the modified model, from the figure we may say that modified model has fewer hotspots on its top surface. Misrun sensitivity of
7.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 1253 modified model is shown in figure 16, from the figure we may conclude thatmodified model norisk misrunsensitivity. Fig -15: Hotspot on Existing Model Fig -16: Misrun Sensitivity of Existing Model 4. CONCLUSIONS In this research, it is proposed to examine a sealing casting model produced from grey cast iron. For sand casting, different circumstances are simulated numericallyusingthe commercial software pro-CAST. Various solidification performance metrics, including temperature, hotspot, total shrinkage porosity, and solidification contour, etc. 1. Casting simulation technology has sufficiently matured and has become an essential tool for casting defect troubleshooting and method optimization. It enables quality assurance and high yield without shop-floor trials, and considerably reduces the lead-time for the first good samplecast. 2. By moving the trial and error process into the virtual world and determine the cost of different design and process options. By minimizing real world trial and error (and surprises) making castings right the first time. 3. From above thesis work, we found that when riser is introduced the shrinkage porosity decreased. Also by modifying geometry as per the sizes of the gating system defects like hotspot, misrun and shrinkage porosity decreased. After all it reduces the casting rejection rate. REFERENCES [1] Dr. Ravi, “casting simulation & optimization, benefits, bottlenecks & best practices”, India Foundry Journal, 2008 [2] Naveen Hebsur, and Sunil Mangsheety, “Casting Simulation for Sand Casting of Flywheel”, ALUCAST, pp. 62-67, 2014 [3] P. Prabhakara Rao, G. Chakaraverthi, “Application of casting simulation”, International journal of thermal technologies, Vol.1 2011. [4] Karl B. Rundman, Metal Casting, Michigan Tech. University, Michiga [5] C.W. Ammen, The Complete Handbook of Sand Casting, Tab Books, United States of America, 1979. [6] A. Bermudez, M. V. O. (2006). "An existence result for a two-phase Stefan problem arising in metal casting in metal casting." Mathematical methods in applied sciences 29: 325-350. [7] A.V. Arasu, A. S. M. (2012). "Numerical study on melting of paraffin wax with Al2O3 in a square enclosure." International Communications in Heat and Mass Transfer 39: 8–16. [8] B. Rubinsky, E. G. C. (1981). "A finite elementmethodfor the solution of one-dimensional phase change problems." International journal of Heat Mass Transfer 24: 1987-1989. [9] Babak Kamkaria, H. J. A. (2017). "Numerical simulation and experimental verification of constrained melting of phase change material in inclined rectangular enclosures." International Communications in Heat and Mass Transfer 88: 211-219. [10] Feng Liu, “Optimized Design of Gating/Riser System in Casting Based on CAD and Simulation Technology” Worcester polytechnic institute, December 2008. [11] Hwang, K.-Y. (1997). "Effects of density change and natural convection onthesolidification processofa pure metal." Journal of Materials Processing Technology 71: 466-476. [12] Slota, D. (2011). "Restoring boundary conditions in the solidification of pure metals."ComputersandStructures 89: 48-54.
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