Volume 3B: 47th Design Automation Conference (DAC)最新文献_第3页

Uncertainty Quantification and Reduction Using Sensitivity Analysis and Hessian Derivatives 利用敏感性分析和Hessian导数的不确定度量化和降低

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-71037

Josefina Sánchez, K. Otto

{"title":"Uncertainty Quantification and Reduction Using Sensitivity Analysis and Hessian Derivatives","authors":"Josefina Sánchez, K. Otto","doi":"10.1115/detc2021-71037","DOIUrl":"https://doi.org/10.1115/detc2021-71037","url":null,"abstract":"\u0000 We study the use of Hessian interaction terms to quickly identify design variables that reduce variability of system performance. To start we quantify the uncertainty and compute the variance decomposition to determine noise variables that contribute most, all at an initial design. Minimizing the uncertainty is next sought, though probabilistic optimization becomes computationally difficult, whether by including distribution parameters as an objective function or through robust design of experiments. Instead, we consider determining the more easily computed Hessian interaction matrix terms of the variance-contributing noise variables and the variables of any proposed design change. We also relate the Hessian term coefficients to subtractions in Sobol indices and reduction in response variance. Design variable changes that can reduce variability are thereby identified quickly as those with large Hessian terms against noise variables. Furthermore, the Jacobian terms of these design changes can indicate which design variables can shift the mean response, to maintain a desired nominal performance target. Using a combination of easily computed Hessian and Jacobian terms, design changes can be proposed to reduce variability while maintaining a targeted nominal. Lastly, we then recompute the uncertainty and variance decomposition at the more robust design configuration to verify the reduction in variability. This workflow therefore makes use of UQ/SA methods and computes design changes that reduce uncertainty with a minimal 4 runs per design change. An example is shown on a Stirling engine design where the top four variance-contributing tolerances are matched with two design changes identified through Hessian terms, and a new design found with 20% less variance.","PeriodicalId":299235,"journal":{"name":"Volume 3B: 47th Design Automation Conference (DAC)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114246359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Identifying Computer-Aided Design Action Types From Professional User Analytics Data 从专业用户分析数据中识别计算机辅助设计动作类型

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-72102

K. Leonardo, A. Olechowski

{"title":"Identifying Computer-Aided Design Action Types From Professional User Analytics Data","authors":"K. Leonardo, A. Olechowski","doi":"10.1115/detc2021-72102","DOIUrl":"https://doi.org/10.1115/detc2021-72102","url":null,"abstract":"\u0000 Inspired by popular personality type indicators, we develop a framework for classifying individuals by their computer-aided design (CAD) behaviours. We are motivated by the trend of modern CAD software towards cloud platforms and expanded collaborative features. Cloud-CAD platforms enable collaboration by increasing access, and reducing conflicts and barriers to file-sharing.\u0000 In order to generate insight to support CAD collaboration, we analyze the real-world data from an industry partner’s product development project, consisting of eight professional designers working on a cloud-CAD platform. This data corresponds to more than 1,420,000 actions over a span of eight months. Via hierarchical clustering, we group 79 unique CAD activities into 14 categories of CAD action groups, such as Part Studio, Assembly, Comment, View/Scan and Export. Next, we identify the degree to which each of the eight designers performs activity in these CAD action groups. We demonstrate the usefulness of this framework by highlighting insights revealed by the CAD action group mapping, confirmed via discussion with the industry partner. This CAD-type behaviour framework provides a tool for assessment and reflection on the types of behavioural tendencies present or missing on a team of designers. It can assist CAD educators and trainees in understanding their comprehensive CAD learning trajectory. Future extensions of the framework could leverage artificial intelligence techniques to provide real-time feedback on designer roles.","PeriodicalId":299235,"journal":{"name":"Volume 3B: 47th Design Automation Conference (DAC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123733892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SDF-Based Inverse Process Design of Solar Cells Using Molecular Dynamics Simulations 基于sdf的太阳能电池反工艺设计的分子动力学模拟

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-71595

Umar Farooq Ghumman, Anton van Beek, Joydeep Munshi, T. Chien, G. Balasubramanian, Wei Chen

{"title":"SDF-Based Inverse Process Design of Solar Cells Using Molecular Dynamics Simulations","authors":"Umar Farooq Ghumman, Anton van Beek, Joydeep Munshi, T. Chien, G. Balasubramanian, Wei Chen","doi":"10.1115/detc2021-71595","DOIUrl":"https://doi.org/10.1115/detc2021-71595","url":null,"abstract":"\u0000 Despite their lower weight, cheaper production cost, and diminished demand of metals, Organic Photovoltaic Cells (OPVCs) have not replaced conventional solar cells. The reason for this is their relatively low power conversion efficiency that could be a consequence of a lack in understanding of the underlying physics. More specifically, the influence of processing conditions and microstructure morphology on OPVC performance is still an open research area. In a previous study, we presented a spectral density function (SDF)-based design framework to optimize material performance with respect to its quasi-random microstructure (such as an OPVC). However, to guarantee manufacturability, the influence of processing conditions to material performance needs to be considered. In this study we present a two-step inverse design scheme which first identifies the optimal key microstructure descriptor(s) and then the optimal processing conditions. Dividing the design problem in two steps greatly benefits tractability as it allows the use of SDF reconstruction to reduce the dimensionality of the processing conditions. Subsequently, fewer costly high fidelity coarse-grained molecular dynamics simulations (or physical experiments) are required to identify the optimal processing conditions. We apply the introduced framework to optimize the performance of an OPVC with respect to volume fraction (i.e., chemical compositions) and annealing temperature. The inverse design approach results in a potential ten-fold decrease in the computational cost compared to direct process-performance optimization.","PeriodicalId":299235,"journal":{"name":"Volume 3B: 47th Design Automation Conference (DAC)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124393987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Probabilistic Approach for Estimating the Environmental Impact of Novel Product Concepts 估算新产品概念对环境影响的概率方法

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-70990

Vincenzo Ferrero, C. Hoyle, Bryony DuPont

{"title":"A Probabilistic Approach for Estimating the Environmental Impact of Novel Product Concepts","authors":"Vincenzo Ferrero, C. Hoyle, Bryony DuPont","doi":"10.1115/detc2021-70990","DOIUrl":"https://doi.org/10.1115/detc2021-70990","url":null,"abstract":"\u0000 Global concerns about climate change and resource management have escalated the need for sustainable consumer products. In light of this, sustainable design methodologies that supplement the product design process are needed. Current research focuses on developing sustainable design curricula, adapting classical design methods to accommodate environmental sustainability, and sustainability tools that are applicable during the early design phase. However, concurrent work suggests that sustainability-marketed and innovative products still lack a reduction of environmental impact compared to conventional products. Life cycle assessment (LCA) has proven to be an exceptional tool used to assess the environmental impact of a realized product. However, LCA is a reactive tool that does not proactively reduce the environmental impact of novel product concepts. Here we develop a novel methodology, the PeeP method, using historical product LCA data with kernel density estimation to provide an estimated environmental impact range for a given product design. The PeeP method is tested using a series of case studies exploring four different products. Results suggest that probability density estimations developed through this method reflect the environmental impact of the product at both the product and component level. In the context of sustainable design research, the PeeP method is a viable methodology for assessing product design environmental impact prior to product realization. Our methodology can allow designers to identify high-impact components and reduce the cost of product redesign in practice.","PeriodicalId":299235,"journal":{"name":"Volume 3B: 47th Design Automation Conference (DAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134511361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Allocation of Design Margins in Additive Remanufacturing 增材再制造中设计余量的优化分配

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-69378

K. Al Handawi, M. Panarotto, Petter Andersson, O. Isaksson, M. Kokkolaras

引用次数: 0

FMEA-Inspired Analysis for Social Impact of Engineered Products 基于fmea的工程产品社会影响分析

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-70595

Andrew Armstrong, C. Mattson, Jon Salmon, E. Dahlin

引用次数: 0

Multi-Material and Multi-Joint Topology Optimization for Lightweight and Cost-Effective Design 面向轻量化和高性价比设计的多材料和多关节拓扑优化

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-67317

Luke Crispo, S. W. K. Roper, R. Bohrer, Rosalie Morin, I. Kim

{"title":"Multi-Material and Multi-Joint Topology Optimization for Lightweight and Cost-Effective Design","authors":"Luke Crispo, S. W. K. Roper, R. Bohrer, Rosalie Morin, I. Kim","doi":"10.1115/detc2021-67317","DOIUrl":"https://doi.org/10.1115/detc2021-67317","url":null,"abstract":"\u0000 Lightweighting and cost reduction are overarching research themes in aerospace and automotive industries, leading to the exploration of new materials, advanced manufacturing methods, and design optimization algorithms. Multi-material topology optimization is an important tool that can generate unconventional designs leveraging the differing mechanical properties of multiple material types to increase performance. However, these approaches do not consider joining design during optimization, which can ultimately result in higher cost, worse performance, and unrealistic designs that must be altered in the interpretation stage. This work presents a multi-material and multi-joint topology optimization methodology that models joints at the interfaces between dissimilar materials, controls the joining pattern using joint design variables, and reduces cost through the addition of a joining cost constraint. Design variable interpolation schemes, interface detection for unstructured meshes, and sensitivity analysis are outlined in detail in this paper. The approach is applied to a real-world rocker arm geometry to demonstrate the importance of considering joints during multi-material topology optimization. The results of the numerical example indicate that the methodology can successfully detect interfaces in unstructured meshes and strategically place joints to maximize stiffness of the structure. A parameter study of various joining cost constraint levels illustrates how the optimizer alters part topology and joining design to reduce cost.","PeriodicalId":299235,"journal":{"name":"Volume 3B: 47th Design Automation Conference (DAC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117100054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Conformal Topology Optimization of Heat Conduction Problems on Manifolds Using an Extended Level Set Method (X-LSM) 基于扩展水平集方法(X-LSM)的流形热传导问题共形拓扑优化

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-67819

Xiaoqiang Xu, Shikui Chen, X. Gu, M. Wang

{"title":"Conformal Topology Optimization of Heat Conduction Problems on Manifolds Using an Extended Level Set Method (X-LSM)","authors":"Xiaoqiang Xu, Shikui Chen, X. Gu, M. Wang","doi":"10.1115/detc2021-67819","DOIUrl":"https://doi.org/10.1115/detc2021-67819","url":null,"abstract":"\u0000 In this paper, the authors propose a new dimension reduction method for level-set-based topology optimization of conforming thermal structures on free-form surfaces. Both the Hamilton-Jacobi equation and the Laplace equation, which are the two governing PDEs for boundary evolution and thermal conduction, are transformed from the 3D manifold to the 2D rectangular domain using conformal parameterization. The new method can significantly simplify the computation of topology optimization on a manifold without loss of accuracy. This is achieved due to the fact that the covariant derivatives on the manifold can be represented by the Euclidean gradient operators multiplied by a scalar with the conformal mapping. The original governing equations defined on the 3D manifold can now be properly modified and solved on a 2D domain. The objective function, constraint, and velocity field are also equivalently computed with the FEA on the 2D parameter domain with the properly modified form. In this sense, we are solving a 3D topology optimization problem equivalently on the 2D parameter domain. This reduction in dimension can greatly reduce the computing cost and complexity of the algorithm. The proposed concept is proved through two examples of heat conduction on manifolds.","PeriodicalId":299235,"journal":{"name":"Volume 3B: 47th Design Automation Conference (DAC)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114875648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Impact of Asset Management in a Green Supply Chain 绿色供应链中资产管理的影响

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-70826

Sara Hajihashemi, R. Alizadeh, J. Allen, F. Mistree

{"title":"Impact of Asset Management in a Green Supply Chain","authors":"Sara Hajihashemi, R. Alizadeh, J. Allen, F. Mistree","doi":"10.1115/detc2021-70826","DOIUrl":"https://doi.org/10.1115/detc2021-70826","url":null,"abstract":"\u0000 With increasing concerns about global warming caused by greenhouse gasses (GHGs), organizations have become more responsible for their operations. According to the U.S. Environmental Protection Agency (EPA), companies with a supply chain (SC) generate about 42% of GHGs in their transportation (30%) and inventory systems (12%), which makes mitigating climate change through a green supply chain (GSC) management a reasonable solution.\u0000 To design a GSC, we model the SC as a customer and store network, with customers driving in cars to and from stores and the retailer resupplying the stores from a central warehouse. The number and location of stores are determined to find a low-cost and low emission configuration for the SC.\u0000 The key findings are (1) SCs with more small stores generate less emission than ones with fewer large stores; (2) when minimizing the operating cost is more important than mitigating GHG emissions, fewer large stores are preferred than having more small stores; (3) a SC with two warehouses reduces the number of open stores in a large area such as Puerto Rico.\u0000 Our contributions are (1) building a model of a GSC based on population data; (2) modeling a GSC in a two-echelon network which can be solved simultaneously using the k-median approach; (3) evaluating the effect of multiple warehouses on the overall GHGs emissions; (4) managing the incompleteness and inaccuracy of the data through implementing the compromise Decision Support Problem construct to identify satisficing solutions.\u0000 The model mentioned earlier highlights the important parameters that impact the green GHG emissions reduction from a SC that describe in this paper. We also discuss how this approach can be employed for other design problems, including manufacturing and healthcare.","PeriodicalId":299235,"journal":{"name":"Volume 3B: 47th Design Automation Conference (DAC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116734643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning Method for Forecasting Weather Needed For Crop Water Demand Estimations in Low-Resource Settings Using A Case Study in Morocco 低资源环境下作物需水量估算所需天气预测的机器学习方法——以摩洛哥为例

Volume 3B: 47th Design Automation Conference (DAC) Pub Date : 2021-08-17 DOI: 10.1115/detc2021-70571

Carolyn Sheline, A. Winter

引用次数: 0