Volume 2A: 44th Design Automation Conference最新文献

Reducing Evaluation Cost for Circuit Synthesis Using Active Learning 利用主动学习降低电路综合评估成本

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/detc2018-85654

Tinghao Guo, Daniel R. Herber, James T. Allison

{"title":"Reducing Evaluation Cost for Circuit Synthesis Using Active Learning","authors":"Tinghao Guo, Daniel R. Herber, James T. Allison","doi":"10.1115/detc2018-85654","DOIUrl":"https://doi.org/10.1115/detc2018-85654","url":null,"abstract":"In this article, an active learning strategy is introduced for reducing evaluation cost associated with system architecture design problems and is demonstrated using a circuit synthesis problem. While established circuit synthesis methods, such as efficient enumeration strategies and genetic algorithms (GAs), are available, evaluation of candidate architectures often requires computationally-expensive simulations, limiting the scale of solvable problems. Strategies are needed to explore architecture design spaces more efficiently, reducing the number of evaluations required to obtain good solutions. Active learning is a semi-supervised machine learning technique that constructs a predictive model. Here we use active learning to interactively query architecture data as a strategy to choose which candidate architectures to evaluate in a way that accelerates effective design search. Active learning is used to iteratively improve predictive model accuracy with strategically-selected training samples. The predictive model used here is an ensemble method, known as random forest. Several query strategies are compared. A circuit synthesis problem is used to test the active learning strategy; two complete data sets for this case study are available, aiding analysis. While active learning has been used for structured outputs, such as sequence labeling task, the interface between active learning and engineering design, particularly circuit synthesis, has not been well studied. The results indicate that active learning is a promising strategy in reducing the evaluation cost for the circuit synthesis problem, and provide insight into possible next steps for this general solution approach.","PeriodicalId":138856,"journal":{"name":"Volume 2A: 44th Design Automation Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116737987","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: 10

An Interactive Manufacturability Analysis and Tolerance Allocation Tool for Additive Manufacturing 一种面向增材制造的可制造性分析与公差分配工具

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-86344

Hannah D. Budinoff, Sara McMains, A. Rinaldi

引用次数: 4

Modeling Spatiotemporal Heterogeneity of Customer Preferences in Engineering Design 工程设计中客户偏好的时空异质性建模

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-86245

Youyi Bi, Jian Xie, Zhenghui Sha, Mingxian Wang, Yan Fu, Wei Chen

{"title":"Modeling Spatiotemporal Heterogeneity of Customer Preferences in Engineering Design","authors":"Youyi Bi, Jian Xie, Zhenghui Sha, Mingxian Wang, Yan Fu, Wei Chen","doi":"10.1115/DETC2018-86245","DOIUrl":"https://doi.org/10.1115/DETC2018-86245","url":null,"abstract":"Customer preferences are found to evolve over time and correlate with geographical locations. Studying spatiotemporal heterogeneity of customer preferences is crucial to engineering design as it provides a dynamic perspective for a thorough understanding of preference trend. However, existing analytical models for demand modeling do not take the spatiotemporal heterogeneity of customer preferences into consideration. To fill this research gap, a spatial panel modeling approach is developed in this study to investigate the spatiotemporal heterogeneity of customer preferences by introducing engineering attributes explicitly as model inputs in support of demand forecasting in engineering design. In addition, a step-by-step procedure is proposed to aid the implementation of the approach. To demonstrate this approach, a case study is conducted on small SUV in China’s automotive market. Our results show that small SUVs with lower prices, higher power, and lower fuel consumption tend to have a positive impact on their sales in each region. In understanding the spatial patterns of China’s small SUV market, we found that each province has a unique spatial specific effect influencing the small SUV demand, which suggests that even if changing the design attributes of a product to the same extent, the resulting effects on product demand might be different across different regions. In understanding the underlying social-economic factors that drive the regional differences, it is found that Gross Domestic Product (GDP) per capita, length of paved roads per capita and household consumption expenditure have significantly positive influence on small SUV sales. These results demonstrate the potential capability of our approach in handling spatial variations of customers for product design and marketing strategy development. The main contribution of this research is the development of an analytical approach integrating spatiotemporal heterogeneity into demand modeling to support engineering design.","PeriodicalId":138856,"journal":{"name":"Volume 2A: 44th Design Automation Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124023353","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: 7

Experimentally-Infused Active System Optimization Framework: Theoretical Convergence Analysis and Airborne Wind Energy Case Study 实验注入主动系统优化框架:理论收敛分析与机载风能案例研究

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-85305

N. Deodhar, C. Vermillion

引用次数: 2

Approaches for Supporting Exploration for Analogical Inspiration With Behavior, Material and Component Based Structural Representations of Patent Databases 基于行为、材料和组件的专利数据库结构表示支持类比灵感探索的方法

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-85591

H. Song, Katherine K. Fu

{"title":"Approaches for Supporting Exploration for Analogical Inspiration With Behavior, Material and Component Based Structural Representations of Patent Databases","authors":"H. Song, Katherine K. Fu","doi":"10.1115/DETC2018-85591","DOIUrl":"https://doi.org/10.1115/DETC2018-85591","url":null,"abstract":"This paper presents an explorative-based computational methodology to aid the analogical retrieval process in design-by-analogy practice. The computational methodology, driven by Non-negative Matrix Factorization (NMF), iteratively builds a hierarchical repositories of design solutions within which clusters of design analogies can be explored by designers. In the work, the methodology has been applied on a large repository of mechanical design related patents, processed to contain only component-, behavior-, or material-based content, to demonstrate that unique and valuable attribute-based analogical inspiration can be discovered from different representations of patent data. For explorative purposes, the hierarchical repositories have been visualized with a three-dimensional hierarchical structure and two-dimensional bar graph structure, which can be used interchangeably for retrieving analogies. This paper demonstrates that the explorative-based computational methodology provides designers an enhanced control over design repositories, empowering them to retrieve analogical inspiration for design-by-analogy practice.","PeriodicalId":138856,"journal":{"name":"Volume 2A: 44th Design Automation Conference","volume":"435 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123198466","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

Online Estimation of Lithium-Ion Battery Capacity Using Deep Convolutional Neural Networks 基于深度卷积神经网络的锂离子电池容量在线估计

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-86347

Sheng Shen, Mohammadkazem Sadoughi, Xiangyi Chen, Mingyi Hong, Chao Hu

{"title":"Online Estimation of Lithium-Ion Battery Capacity Using Deep Convolutional Neural Networks","authors":"Sheng Shen, Mohammadkazem Sadoughi, Xiangyi Chen, Mingyi Hong, Chao Hu","doi":"10.1115/DETC2018-86347","DOIUrl":"https://doi.org/10.1115/DETC2018-86347","url":null,"abstract":"Over the past two decades, safety and reliability of lithium-ion (Li-ion) rechargeable batteries have been receiving a considerable amount of attention from both industry and academia. To guarantee safe and reliable operation of a Li-ion battery pack and build failure resilience in the pack, battery management systems (BMSs) should possess the capability to monitor, in real time, the state of health (SOH) of the individual cells in the pack. This paper presents a deep learning method, named deep convolutional neural networks, for cell-level SOH assessment based on the capacity, voltage, and current measurements during a charge cycle. The unique features of deep convolutional neural networks include the local connectivity and shared weights, which enable the model to estimate battery capacity accurately using the measurements during charge. To our knowledge, this is the first attempt to apply deep learning to online SOH assessment of Li-ion battery. 10-year daily cycling data from implantable Li-ion cells are used to verify the performance of the proposed method. Compared with traditional machine learning methods such as relevance vector machine and shallow neural networks, the proposed method is demonstrated to produce higher accuracy and robustness in capacity estimation.","PeriodicalId":138856,"journal":{"name":"Volume 2A: 44th Design Automation Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122236339","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: 12

Kinematic Synthesis Using Reinforcement Learning 基于强化学习的运动学综合

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-85529

Kaz Vermeer, Reinier Kuppens, J. Herder

引用次数: 4

Design of Mechanical Metamaterials via Constrained Bayesian Optimization 基于约束贝叶斯优化的机械超材料设计

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-85270

Conner Sharpe, C. Seepersad, S. Watts, D. Tortorelli

引用次数: 14

An Electricity Grid As an Agent-Based Market System: Exploring the Effects of Policy on Sustainability 电网作为一个基于主体的市场系统:探讨政策对可持续性的影响

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-86031

Steven Hoffenson, M. Wiśniowski

{"title":"An Electricity Grid As an Agent-Based Market System: Exploring the Effects of Policy on Sustainability","authors":"Steven Hoffenson, M. Wiśniowski","doi":"10.1115/DETC2018-86031","DOIUrl":"https://doi.org/10.1115/DETC2018-86031","url":null,"abstract":"Electricity generation is a major source of air pollution, contributing to nearly one-third of the total greenhouse gas emissions in the United States. As with most goods, production must keep up with the projected consumer demand, and the industry is subject to government regulations at the federal, state, and local levels. This study models the New Jersey electric grid as a market system, using agent-based modeling to represent individual consumers and power companies making utility-maximizing decisions. Each consumer agent is prescribed a unique value function that includes factors such as income, energy intensity, and environmental sensitivity, and they are able to make decisions about how much energy they use and whether they opt into a renewable energy program. Power producers are modeled to keep up with demand and minimize their cost per unit of electricity produced, and they include options to prefer either on-demand or renewable energy sources. Using this model, different scenarios are examined with respect to producer strategy and government policy. The results provide a proof-of-concept for the modeling approach, and they reveal interesting trends about how the markets are expected to react under different scenarios.","PeriodicalId":138856,"journal":{"name":"Volume 2A: 44th Design Automation Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114166428","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: 3

Customization of a 3D Printed Prosthetic Finger Using Parametric Modeling 使用参数化建模的3D打印假肢手指定制

Volume 2A: 44th Design Automation Conference Pub Date : 2018-08-26 DOI: 10.1115/DETC2018-85645

Daniel Lim, T. Georgiou, Aashish Bhardwaj, G. O’Connell, A. Agogino

{"title":"Customization of a 3D Printed Prosthetic Finger Using Parametric Modeling","authors":"Daniel Lim, T. Georgiou, Aashish Bhardwaj, G. O’Connell, A. Agogino","doi":"10.1115/DETC2018-85645","DOIUrl":"https://doi.org/10.1115/DETC2018-85645","url":null,"abstract":"Prosthetic limbs and assistive devices require customization to effectively meet the needs of users. Despite the expense and hassle involved in procuring a prosthetic, 56% of people with limb loss end up abandoning their devices [1]. Acceptance of these devices is contingent on the comfort of the user, which depends heavily on the size, weight, and overall aesthetic of the device. As seen in numerous applications, parametric modeling can be utilized to produce medical devices that are specific to the patient’s needs. However, current 3D printed upper limb prosthetics use uniform scaling to fit the prostheses to different users.\u0000 In this paper, we propose a parametric modeling method for designing prosthetic fingers. We show that a prosthetic finger designed using parametric modeling has a range of motion (ROM) (path of the finger tip) that closely aligns with the digit’s natural path. We also show that the ROM produced by a uniformly scaled prosthetic poorly matches the natural ROM of the finger. To test this, finger width and length measurements were collected from 50 adults between the ages of 18–30. It was determined that there is negligible correlation between the length and width of the index (D2) digit among the participants.\u0000 Using both the highest and the lowest length to width ratio found among the participants, a prosthetic finger was designed using a parametric model and fabricated using additive manufacturing. The mechanical design of the prosthetic finger utilized a crossed four bar linkage mechanism and its ROM was determined by Freudenstein’s equations. By simulating the different paths of the fingers, we demonstrate that parametrically modeled fingers outperform uniformly scaled fingers at matching a natural digit’s path.","PeriodicalId":138856,"journal":{"name":"Volume 2A: 44th Design Automation Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121877105","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: 5