Design heuristics are traditionally used as qualitative principles to guide the design process, but they have also been used to improve the efficiency of design optimization. Using design heuristics as soft constraints or search operators has been shown for some problems to reduce the number of function evaluations needed to achieve a certain level of convergence. However, in other cases, enforcing heuristics can reduce diversity and slow down convergence. This paper studies the question of when and how a given set of design heuristics represented in different forms (soft constraints, repair operators, biased sampling) can be utilized in an automated way to improve efficiency for a given design problem. An approach is presented for identifying promising heuristics for a given problem by estimating the overall impact of a heuristic based on an exploratory screening study. Two impact indices are formulated: weighted influence index and hypervolume difference index. Using this approach, the promising heuristics for 4 design problems are identified and the efficacy of selectively enforcing only these promising heuristics over both enforcement of all available heuristics and not enforcing any heuristics is benchmarked. In all problems, it is found that enforcing only the promising heuristics as repair operators enables finding good designs faster than by enforcing all available heuristics or not enforcing any heuristics. Enforcing heuristics as soft constraints or biased sampling functions results in improvements in efficiency for some of the problems. Based on these results, guidelines for designers to leverage heuristics effectively in design optimization are presented.
{"title":"Identifying and Leveraging Promising Design Heuristics for Multiobjective Combinatorial Design Optimization","authors":"Roshan Suresh Kumar, Emilie Baker, Srikar Srivatsa, Meredith Silberstein, Daniel Selva","doi":"10.1115/1.4063238","DOIUrl":"https://doi.org/10.1115/1.4063238","url":null,"abstract":"\u0000 Design heuristics are traditionally used as qualitative principles to guide the design process, but they have also been used to improve the efficiency of design optimization. Using design heuristics as soft constraints or search operators has been shown for some problems to reduce the number of function evaluations needed to achieve a certain level of convergence. However, in other cases, enforcing heuristics can reduce diversity and slow down convergence. This paper studies the question of when and how a given set of design heuristics represented in different forms (soft constraints, repair operators, biased sampling) can be utilized in an automated way to improve efficiency for a given design problem. An approach is presented for identifying promising heuristics for a given problem by estimating the overall impact of a heuristic based on an exploratory screening study. Two impact indices are formulated: weighted influence index and hypervolume difference index. Using this approach, the promising heuristics for 4 design problems are identified and the efficacy of selectively enforcing only these promising heuristics over both enforcement of all available heuristics and not enforcing any heuristics is benchmarked. In all problems, it is found that enforcing only the promising heuristics as repair operators enables finding good designs faster than by enforcing all available heuristics or not enforcing any heuristics. Enforcing heuristics as soft constraints or biased sampling functions results in improvements in efficiency for some of the problems. Based on these results, guidelines for designers to leverage heuristics effectively in design optimization are presented.","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"54 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90901864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study proposes an inverse method for synthesizing shape-morphing structures in the lateral direction by integrating two-dimensional hexagonal unit-cell with curved beams. Analytical expressions are derived to formulate the effective Young's modulus and Poisson's ratio for the base unit cell as a function of its geometric parameters. The effective lateral Poisson's ratio can be controlled by manipulating a set of geometric parameters, resulting in a dataset of over 6000 data points with Poisson's ratio values ranging from -1.2 to 10.4. Furthermore, we utilize the established dataset to train an inverse design framework that utilizes a physics-guided neural network algorithm, and the framework can predict design parameters for a targeted shape-morphing structure. The proposed approach enables the generation of structures with tailored Poisson's ratio ranging from -1.2 to 3.4 while ensuring flexibility and reduced stress concentration within the predicted structure. The generated shape-morphing structures' performance is validated through numerical simulation and physical tensile testing. The FEA simulation results confirm agreement with the designed values for the shape-morphing structure, and the tensile testing results reveal the same trend in shape-morphing behavior. The proposed design automation framework demonstrates the feasibility of creating intricate and practical shape-morphing structures with high accuracy and computational efficiency.
{"title":"Inverse Design of 2D Shape-Morphing Structures","authors":"Mohammad Abu-Mualla, Victor Jiron, Jida Huang","doi":"10.1115/1.4063191","DOIUrl":"https://doi.org/10.1115/1.4063191","url":null,"abstract":"\u0000 This study proposes an inverse method for synthesizing shape-morphing structures in the lateral direction by integrating two-dimensional hexagonal unit-cell with curved beams. Analytical expressions are derived to formulate the effective Young's modulus and Poisson's ratio for the base unit cell as a function of its geometric parameters. The effective lateral Poisson's ratio can be controlled by manipulating a set of geometric parameters, resulting in a dataset of over 6000 data points with Poisson's ratio values ranging from -1.2 to 10.4. Furthermore, we utilize the established dataset to train an inverse design framework that utilizes a physics-guided neural network algorithm, and the framework can predict design parameters for a targeted shape-morphing structure. The proposed approach enables the generation of structures with tailored Poisson's ratio ranging from -1.2 to 3.4 while ensuring flexibility and reduced stress concentration within the predicted structure. The generated shape-morphing structures' performance is validated through numerical simulation and physical tensile testing. The FEA simulation results confirm agreement with the designed values for the shape-morphing structure, and the tensile testing results reveal the same trend in shape-morphing behavior. The proposed design automation framework demonstrates the feasibility of creating intricate and practical shape-morphing structures with high accuracy and computational efficiency.","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"80 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74433601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Design knowledge in the vast amount of design reports and documents can be a great resource for designers in their practice. However, capturing such domain-specific information embedded in long-length unstructured texts is always time-consuming and sometimes difficult. Therefore, it is highly desirable for a computer system to automatically extract the main knowledge points and their corresponding inner structures from given documents. In this study of document understanding for design support (DocUDS), a design-perspective knowledge extraction approach is proposed that uses phrase-level domain-specific labeled datasets to finetune a Bidirectional Encoder Representation from Transformers (BERT) model so that it can extract design knowledge from documents. The BERT model finetuning attempts to blend in the domain-specific knowledge of well-recognized domain concepts and is based on the datasets generated from design reports. The model is utilized to map the captured sentences to the main design entities , , and . In addition, this approach uncovers inner relationships among the sentences and constructs overall structures of documents to enhance understanding. The definitions of design perspectives, inter-perspective relations, and intra-perspective relations are introduced, which together capture the main design knowledge points and their relations and constitute an understanding of the design domain knowledge of a text. The case study results have demonstrated the proposed approach's effectiveness in understanding and extracting relevant design knowledge points
{"title":"Document Understanding-based Design Support: Application of Language Model for Design Knowledge Extraction","authors":"Y. Qiu, Yang Jin","doi":"10.1115/1.4063161","DOIUrl":"https://doi.org/10.1115/1.4063161","url":null,"abstract":"\u0000 Design knowledge in the vast amount of design reports and documents can be a great resource for designers in their practice. However, capturing such domain-specific information embedded in long-length unstructured texts is always time-consuming and sometimes difficult. Therefore, it is highly desirable for a computer system to automatically extract the main knowledge points and their corresponding inner structures from given documents. In this study of document understanding for design support (DocUDS), a design-perspective knowledge extraction approach is proposed that uses phrase-level domain-specific labeled datasets to finetune a Bidirectional Encoder Representation from Transformers (BERT) model so that it can extract design knowledge from documents. The BERT model finetuning attempts to blend in the domain-specific knowledge of well-recognized domain concepts and is based on the datasets generated from design reports. The model is utilized to map the captured sentences to the main design entities <requirement>, <function>, and <solution>. In addition, this approach uncovers inner relationships among the sentences and constructs overall structures of documents to enhance understanding. The definitions of design perspectives, inter-perspective relations, and intra-perspective relations are introduced, which together capture the main design knowledge points and their relations and constitute an understanding of the design domain knowledge of a text. The case study results have demonstrated the proposed approach's effectiveness in understanding and extracting relevant design knowledge points","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"129 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85748023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anastasia M. K. Schauer, Ritesh Bhatt, Christopher Saldaña, Katherine Fu
The goal of this work is to study the way student designers use heuristics to effectively design for laser-cut manufacturing methods. With the recent advent of academic makerspaces, digital fabrication tools like laser cutters are a relatively new addition to the classroom. Therefore, there is a gap in formal education or training on these tools, and students can find it challenging to design effectively for them. A study was performed to investigate the way students apply heuristics to redesign laser cut assemblies when received in different modalities. All participants were given an identical lecture on laser cutter heuristics. Then, a redesign problem was presented, and three experimental groups were given the heuristics in different modalities: Text-Only, text with Visual aids, and text with Tactile aids. The novelty and quality of each of the resulting redesigns was evaluated. It was hypothesized that participants would have more difficulty interpreting and applying the Text-Only heuristics, lowering the quality of redesigned solutions relative to the other two conditions. It was also hypothesized that participants would experience fixation caused by interacting with tactile aids, leading to lower novelty of their redesigned solutions relative to the other two conditions. Results showed that modality played a significant role in participants' feelings of self-efficacy after the intervention, as well as in their understanding of laser cutter design skills when responding to quiz-style questions. However, analysis of novelty and quality showed no significant impact of the intervention and varying modalities on participants' designs.
{"title":"THE EFFECT OF LASER CUTTING HEURISTIC PRESENTATION MODALITY ON DESIGN LEARNING","authors":"Anastasia M. K. Schauer, Ritesh Bhatt, Christopher Saldaña, Katherine Fu","doi":"10.1115/1.4063156","DOIUrl":"https://doi.org/10.1115/1.4063156","url":null,"abstract":"\u0000 The goal of this work is to study the way student designers use heuristics to effectively design for laser-cut manufacturing methods. With the recent advent of academic makerspaces, digital fabrication tools like laser cutters are a relatively new addition to the classroom. Therefore, there is a gap in formal education or training on these tools, and students can find it challenging to design effectively for them. A study was performed to investigate the way students apply heuristics to redesign laser cut assemblies when received in different modalities. All participants were given an identical lecture on laser cutter heuristics. Then, a redesign problem was presented, and three experimental groups were given the heuristics in different modalities: Text-Only, text with Visual aids, and text with Tactile aids. The novelty and quality of each of the resulting redesigns was evaluated. It was hypothesized that participants would have more difficulty interpreting and applying the Text-Only heuristics, lowering the quality of redesigned solutions relative to the other two conditions. It was also hypothesized that participants would experience fixation caused by interacting with tactile aids, leading to lower novelty of their redesigned solutions relative to the other two conditions. Results showed that modality played a significant role in participants' feelings of self-efficacy after the intervention, as well as in their understanding of laser cutter design skills when responding to quiz-style questions. However, analysis of novelty and quality showed no significant impact of the intervention and varying modalities on participants' designs.","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"45 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79337569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A large-range-of-motion compliant transmission mechanism is introduced that uses the screw degree-of-freedom (DOF) of a multi-DOF compliant module, sandwiched between two other single-DOF compliant modules, to convert a rotational input to a collinear translational output and vice versa. The geometric advantages (i.e., transmission ratios) of the mechanism when driven with a rotation to a translation or with a translation to a rotation can be tuned as desired. The freedom and constraint topologies (FACT) approach is used to design the mechanism, and stiffness matrices are used to explain why the transmission ratio of the mechanism is different depending on whether the mechanism is driven with its rotational or translational inputs. A version of the mechanism is fabricated and its transmission ratio is measured to be ~1.36 mm/° when the mechanism is driven with a rotation, and is measured to be the inverse of ~1.89 mm/° when the mechanism is driven with a translation. The transmission ratios both remain impressively constant over the mechanism's full range of motion and only vary slightly when they are actuated in different directions (i.e., counterclockwise or clockwise if the mechanism is driven with a rotation, or pushing or pulling if the mechanism is driven with a translation).
{"title":"Large-range Rotation-to-translation Compliant Transmission Mechanism","authors":"Nigel C. Archer, J. Hopkins","doi":"10.1115/1.4063160","DOIUrl":"https://doi.org/10.1115/1.4063160","url":null,"abstract":"\u0000 A large-range-of-motion compliant transmission mechanism is introduced that uses the screw degree-of-freedom (DOF) of a multi-DOF compliant module, sandwiched between two other single-DOF compliant modules, to convert a rotational input to a collinear translational output and vice versa. The geometric advantages (i.e., transmission ratios) of the mechanism when driven with a rotation to a translation or with a translation to a rotation can be tuned as desired. The freedom and constraint topologies (FACT) approach is used to design the mechanism, and stiffness matrices are used to explain why the transmission ratio of the mechanism is different depending on whether the mechanism is driven with its rotational or translational inputs. A version of the mechanism is fabricated and its transmission ratio is measured to be ~1.36 mm/° when the mechanism is driven with a rotation, and is measured to be the inverse of ~1.89 mm/° when the mechanism is driven with a translation. The transmission ratios both remain impressively constant over the mechanism's full range of motion and only vary slightly when they are actuated in different directions (i.e., counterclockwise or clockwise if the mechanism is driven with a rotation, or pushing or pulling if the mechanism is driven with a translation).","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"17 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85033301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tae-hyun Kim, Keon-Ik Jang, Dae-Young Lee, Jae-Hung Han
This paper proposes a novel thickness-accommodating method to design a void-free for flat-foldable origami pattern without self-intersection. Unlike existing methods, it enables uniform thickness distribution without any holes or voids at any location, and maximizes the effective area of the unfolded state. The proposed method is applicable not only to 2-D folding, but also to a generic flat-foldable Degree-4-Vertex (D4V) pattern. The pattern's thickness-accommodated configuration to avoid self-intersection is determined through kinematic analysis, and a pattern design flow is provided for the generic D4V systematically. Prototypes of the D4V pattern and a more complex Miura-ori-based tessellation model are fabricated to demonstrate the effectiveness of the proposed method. This method can be employed to the design of more complete and diverse foldable structures, such as a foldable space shield with thick materials.
{"title":"A Thickness-accommodating Method for Void-free Design in Uniformly Thick Origami","authors":"Tae-hyun Kim, Keon-Ik Jang, Dae-Young Lee, Jae-Hung Han","doi":"10.1115/1.4063159","DOIUrl":"https://doi.org/10.1115/1.4063159","url":null,"abstract":"\u0000 This paper proposes a novel thickness-accommodating method to design a void-free for flat-foldable origami pattern without self-intersection. Unlike existing methods, it enables uniform thickness distribution without any holes or voids at any location, and maximizes the effective area of the unfolded state. The proposed method is applicable not only to 2-D folding, but also to a generic flat-foldable Degree-4-Vertex (D4V) pattern. The pattern's thickness-accommodated configuration to avoid self-intersection is determined through kinematic analysis, and a pattern design flow is provided for the generic D4V systematically. Prototypes of the D4V pattern and a more complex Miura-ori-based tessellation model are fabricated to demonstrate the effectiveness of the proposed method. This method can be employed to the design of more complete and diverse foldable structures, such as a foldable space shield with thick materials.","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"43 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80224961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Engineered systems can be characterized by the inherent uncertainties and interactions in the system. To effectively design such engineered systems while improving the quality of design decisions, we contend that addressing the inherent interactions and uncertainties is critical. By addressing interactions, we incorporate the ability to account for the influence of one design decision over another in the decision-making process. Through uncertainty management, we design decisions that are relatively insensitive to uncertainty. In this paper, we identify the various elements required for designing engineered systems and address some key elements, that are, (i) decision identification and classification, (ii) modeling decisions and their interactions, (iii) managing the effect of uncertainties in decisions and, (iv) solution space exploration. We utilize these key elements in the formulation and exploration of design problems using 3 design examples, that are: (i) design of a fender, (ii) design of a gearbox, and (iii) design of a composite structure. As a contribution, we offer a generic method that enables designers to design engineered systems when interactions and uncertainties are prevalent in design decisions.
{"title":"EXPLORING ROBUST DECISIONS IN THE DESIGN OF COUPLED ENGINEERED SYSTEMS","authors":"Gehendra Sharma, J. Allen, F. Mistree","doi":"10.1115/1.4063157","DOIUrl":"https://doi.org/10.1115/1.4063157","url":null,"abstract":"\u0000 Engineered systems can be characterized by the inherent uncertainties and interactions in the system. To effectively design such engineered systems while improving the quality of design decisions, we contend that addressing the inherent interactions and uncertainties is critical. By addressing interactions, we incorporate the ability to account for the influence of one design decision over another in the decision-making process. Through uncertainty management, we design decisions that are relatively insensitive to uncertainty. In this paper, we identify the various elements required for designing engineered systems and address some key elements, that are, (i) decision identification and classification, (ii) modeling decisions and their interactions, (iii) managing the effect of uncertainties in decisions and, (iv) solution space exploration. We utilize these key elements in the formulation and exploration of design problems using 3 design examples, that are: (i) design of a fender, (ii) design of a gearbox, and (iii) design of a composite structure. As a contribution, we offer a generic method that enables designers to design engineered systems when interactions and uncertainties are prevalent in design decisions.","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"76 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80942765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Continuous constraint satisfaction is prevalent in many science and engineering fields. When solving continuous constraint satisfaction problems, it is more advantageous for practitioners to derive all feasible regions (i.e., the solution space) rather than a limited number of solution points, since these feasible regions facilitate design concept generation and design tradeoff evaluation. Several CPU-based branch-and-prune methods and geometric approximation methods have been proposed to derive feasible regions for continuous constraint satisfaction problems. However, these methods have not been extensively adopted in practice, mainly because of their high computational expense. To overcome the computational bottleneck of extant CPU-based methods, this paper introduces a GPU-based parallel region classification method to derive feasible regions for continuous constraint satisfaction problems in a reasonable computational time. Using interval arithmetic, coupled with the computational power of GPU, this method iteratively partitions the design space into many subregions and classifies these subregions as feasible, infeasible, and indeterminate regions. To visualize these classified regions in the design space, a planar visualization approach that projects all classified regions into one figure is also proposed. The GPU-based parallel region classification method and the planar visualization approach are validated through two case studies about the bird function and the welded beam design. These case studies show that the method and the approach can solve the continuous constraint satisfaction problems and visualize the results effectively and efficiently. A four-step procedure for implementing the method and the approach in practice is also outlined.
{"title":"A GPU-Based Parallel Region Classification Method for Continuous Constraint Satisfaction Problems","authors":"Guanglu Zhang, Wangchuan Feng, J. Cagan","doi":"10.1115/1.4063158","DOIUrl":"https://doi.org/10.1115/1.4063158","url":null,"abstract":"\u0000 Continuous constraint satisfaction is prevalent in many science and engineering fields. When solving continuous constraint satisfaction problems, it is more advantageous for practitioners to derive all feasible regions (i.e., the solution space) rather than a limited number of solution points, since these feasible regions facilitate design concept generation and design tradeoff evaluation. Several CPU-based branch-and-prune methods and geometric approximation methods have been proposed to derive feasible regions for continuous constraint satisfaction problems. However, these methods have not been extensively adopted in practice, mainly because of their high computational expense. To overcome the computational bottleneck of extant CPU-based methods, this paper introduces a GPU-based parallel region classification method to derive feasible regions for continuous constraint satisfaction problems in a reasonable computational time. Using interval arithmetic, coupled with the computational power of GPU, this method iteratively partitions the design space into many subregions and classifies these subregions as feasible, infeasible, and indeterminate regions. To visualize these classified regions in the design space, a planar visualization approach that projects all classified regions into one figure is also proposed. The GPU-based parallel region classification method and the planar visualization approach are validated through two case studies about the bird function and the welded beam design. These case studies show that the method and the approach can solve the continuous constraint satisfaction problems and visualize the results effectively and efficiently. A four-step procedure for implementing the method and the approach in practice is also outlined.","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"49 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81467780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhuo Huang, Ye Tian, Kang Yang, Tielin Shi, Qi Xia
A shape and generalized topology optimization method based on the level set based density method is proposed for designing curved grid stiffeners. The overall layout of the stiffeners is described by combining many single stiffeners, and each single stiffener is described by a level set function parameterized by using the compactly supported radial basis functions (CS-RBFs). The curvilinear path of each stiffener is described by the zero iso-contour of each level set function, and the width of each stiffener is described by applying an interval projection to each level set function. The combination operation that is similar to the Boolean operation “union” is achieved by using the p-norm method. The expansion coefficients of CS-RBFs are taken as part of the design variables of the optimization, and they are responsible for changing the shape of curved stiffeners. A topology design variable is assigned to each single stiffener, and it is responsible for changing the existence of single stiffeners. The proposed method is validated through several numerical examples, and the results demonstrate that the shape and topology of stiffeners can be effectively changed during the optimization.
{"title":"Shape and generalized topology optimization of curved grid stiffeners through the level set based density method","authors":"Zhuo Huang, Ye Tian, Kang Yang, Tielin Shi, Qi Xia","doi":"10.1115/1.4063093","DOIUrl":"https://doi.org/10.1115/1.4063093","url":null,"abstract":"\u0000 A shape and generalized topology optimization method based on the level set based density method is proposed for designing curved grid stiffeners. The overall layout of the stiffeners is described by combining many single stiffeners, and each single stiffener is described by a level set function parameterized by using the compactly supported radial basis functions (CS-RBFs). The curvilinear path of each stiffener is described by the zero iso-contour of each level set function, and the width of each stiffener is described by applying an interval projection to each level set function. The combination operation that is similar to the Boolean operation “union” is achieved by using the p-norm method. The expansion coefficients of CS-RBFs are taken as part of the design variables of the optimization, and they are responsible for changing the shape of curved stiffeners. A topology design variable is assigned to each single stiffener, and it is responsible for changing the existence of single stiffeners. The proposed method is validated through several numerical examples, and the results demonstrate that the shape and topology of stiffeners can be effectively changed during the optimization.","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"17 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83388471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eesh Kamrah, Fatemeh Ghoreishi, Zijian Ding, Joel Chan, M. Fuge
Design researchers have struggled to produce quantitative predictions for exactly why and when diversity might help or hinder design search efforts. This paper addresses that problem by studying one ubiquitously used search strategy -- Bayesian Optimization (BO) -- on a 2D test problem with modifiable difficulty. Specifically, we test how providing diverse versus non-diverse initial samples to BO affects its performance during search and introduce a fast DPP sampling method for computing diverse sets to detect sets of highly diverse or non-diverse initial samples. We initially found, to our surprise, that diversity did not affect BO, neither helping nor hurting its convergence. However, follow-on experiments illuminated a trade-off. Non-diverse initial samples hastened posterior convergence for the underlying model hyper-parameters -- a Model Building advantage. In contrast, diverse initial samples accelerated exploring the function itself -- a Space Exploration advantage. Both advantages help BO, but in different ways, and the initial sample diversity modulates how BO trades those advantages. We show that fixing the BO hyper-parameters removes the Model Building advantage, causing diverse initial samples to always outperform models trained with non-diverse samples. These findings shed light on why, at least for BO-type optimizers, the use of diversity has mixed effects and cautions against the ubiquitous use of space-filling initializations in BO. To the extent that humans use explore-exploit search strategies similar to BO, our results provide a testable conjecture for why and when diversity may affect human-subject or design team experiments.
{"title":"How Diverse Initial Samples Help and Hurt Bayesian Optimizers","authors":"Eesh Kamrah, Fatemeh Ghoreishi, Zijian Ding, Joel Chan, M. Fuge","doi":"10.1115/1.4063006","DOIUrl":"https://doi.org/10.1115/1.4063006","url":null,"abstract":"\u0000 Design researchers have struggled to produce quantitative predictions for exactly why and when diversity might help or hinder design search efforts. This paper addresses that problem by studying one ubiquitously used search strategy -- Bayesian Optimization (BO) -- on a 2D test problem with modifiable difficulty. Specifically, we test how providing diverse versus non-diverse initial samples to BO affects its performance during search and introduce a fast DPP sampling method for computing diverse sets to detect sets of highly diverse or non-diverse initial samples. We initially found, to our surprise, that diversity did not affect BO, neither helping nor hurting its convergence. However, follow-on experiments illuminated a trade-off. Non-diverse initial samples hastened posterior convergence for the underlying model hyper-parameters -- a Model Building advantage. In contrast, diverse initial samples accelerated exploring the function itself -- a Space Exploration advantage. Both advantages help BO, but in different ways, and the initial sample diversity modulates how BO trades those advantages. We show that fixing the BO hyper-parameters removes the Model Building advantage, causing diverse initial samples to always outperform models trained with non-diverse samples. These findings shed light on why, at least for BO-type optimizers, the use of diversity has mixed effects and cautions against the ubiquitous use of space-filling initializations in BO. To the extent that humans use explore-exploit search strategies similar to BO, our results provide a testable conjecture for why and when diversity may affect human-subject or design team experiments.","PeriodicalId":50137,"journal":{"name":"Journal of Mechanical Design","volume":"42 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80823882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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