BITS Faculty Publications
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Item A mold insert case study on topology optimized design for additive manufacturing(2019) Ranjan, RajitThe Additive Manufacturing (AM) of injection molding inserts has gained popularity during recent years primarily due to the reduced design-to-production time and form freedom offered by AM. In this paper, Topology Optimization (TO) is performed on a metallic mold insert which is to be produced by the Laser Powder Bed Fusion (LPBF) technique. First, a commercially available TO software is used, to minimize the mass of the component while ensuring adequate mechanical response under a prescribed loading condition. The commercial TO tool adopts geometry-based AM constraints and achieves a mass reduction of ~50 %. Furthermore, an in-house TO method has been developed which integrates a simplified AM process model within the standard TO algorithm for addressing the issue of local overheating during manufacturing. The two topology optimized designs are briefly compared, and the advantages of implemeItem A physics-based topology optimization method for enhancing precision in metal am parts(TU Delft, 2022) Ranjan, RajitA physics-based topology optimization method for enhancing precision in metal am parts | TU Delft Repository TU Delft Library search Press enter to search in title/abstract in title/abstract in authors local_library Repository Title Metadata Abstract Files A physics-based topology optimization method for enhancing precision in metal am parts Conference paper (2022) Authors R. Ranjan Computational Design and Mechanics - Mechanical, Maritime and Materials Engineering Zhuoer Chen Chalmers University of Technology C. Ayas Computational Design and Mechanics - Mechanical, Maritime and Materials Engineering M. Langelaar Computational Design and Mechanics - Mechanical, Maritime and Materials Engineering Matthijs Langelaar Computational Design and Mechanics - Mechanical, Maritime and Materials Engineering A. van Keulen Mechanical Engineering Research Group Computational DesignItem Overheating control in additive manufacturing using a 3D topology optimization method and experimental validation(Elsevier, 2023-01) Ranjan, RajitOverheating is a major issue especially in metal Additive Manufacturing (AM) processes, leading to poor surface quality, lack of dimensional precision, inferior performance and/or build failures. A 3D density-based topology optimization (TO) method is presented which addresses the issue of local overheating during metal AM. This is achieved by integrating a simplified AM thermal model and a thermal constraint within the optimization loop. The simplified model, recently presented in literature, offers significant computational gains while preserving the ability of overheating detection. The novel thermal constraint ensures that the overheating risk of optimized designs is reduced. This is fundamentally different from commonly used geometry-based TO methods which impose a geometric constraint on overhangs. Instead, the proposed approach takes the process physics into account. The proposed method is validated via an experimental comparative study. Optical tomography (OT) is used for in-situ monitoring of process conditions during fabrication and obtained data is used for evaluation of overheating tendencies. The novel TO method is compared with two other methods: standard TO and TO with geometric overhang control. The experimental data reveals that the novel physics-based TO design experienced less overheating during the build as compared to the two classical designs. A study further investigated the correlation between overheating observed by high OT values and the defect of porosity. It shows that overheated regions indeed show higher defect of porosity. This suggests that geometry-based guidelines, although enhance printability, may not be sufficient for eliminating overheating issues and related defects. Instead, the proposed physics-based method is able to deliver efficient designs with reduced risk of overheating.Item Integrated method for performance analysis of reliability-based topologically optimized components(Sage, 2019-08) Rout, Bijay KumarThe available robust and reliable topology optimization methods provide quick and efficient design output in an uncertain environment. However, the whole domain of performance function remains hidden during this design process. In the interest of the designer, it is required to know the overall behavior of performance functions in deterministic as well as uncertain/realistic environment. The current work achieves this by proposing an integrated methodology, which combines the design of experiments approach and reliability-based topology optimization. The proposed method enables the designer to simulate performance functions in a desired design-factors space, including uncertainties, via reliability value. For this analysis, compliance, maximum deflection, mechanical advantage, and von Mises stress values are selected as performance functions. Volume fraction, applied force, and dimensions or aspect ratio are chosen as design/control factors. The uncertainties of these design factors are captured using reliability-based topology optimization. The uncertainties due to noncontrollable factors such as material property, load direction, and magnitude are incorporated using the design of experiments approach. Under these uncertainties, the performance of topologically optimized problem is simulated for different experimental combinations of the design factors. The experimental combinations for uncertainties and design factors are generated using Taguchi's orthogonal array. Simulated results are analyzed using techniques such as analysis of mean and variance, signal-to-noise ratio, and response surface method. These analyses help in identifying statistical significance of factors and uncertainties, performance variations, and equivalence relation of performance vs. factor. The proposed methodology is illustrated by selecting monolithic structures such as, on MBB, cantilever beam, and force inverter mechanism.Item Tolerance range section of topologically optimized structure using combined array design of experiments approach(Sage, 2012-11) Rout, Bijay KumarTopology optimization is a popular method to optimize the material for structural components. For minimum compliance problem, the effectiveness of the obtained topology is characterized by its compliance value. Here, compliance value depends on many factors. Due to uncertainties in these factors, desired compliance value is difficult to achieve. The sensitivities of these factors have already been investigated by researchers. Present work focuses on the selection and the significance of tolerance of these factors. The tolerance of input factors like applied force, volume fraction, aspect ratio of material domain and modulus of elasticity are selected to investigate the effect on compliance. To select tolerance range, the concept of inner and outer orthogonal arrays proposed by Taguchi is employed along with solid isotropic microstructure with penalization method of topology optimization. Different tolerance ranges are selected for each factor and tolerance combinations are generated using inner array. Thereafter outer array is used to create replications of a particular combination. For each replicate, compliance value is simulated using solid isotropic microstructure with penalization method. Based on statistical analysis of obtained values, significant factors are identified and optimal tolerance ranges are selected. In similar way, maximum deflection values are also simulated for analysis. Proposed methodology is applied on four different benchmark problems. The presented approach provides the effect of each possible set of tolerance on performance functions, which are compliance and deflection values. This work will be helpful to designers to select optimum tolerance of factors to achieve desired compliance value and performance for a topologically optimized structure prior to manufacturing in the realistic environment.