CHS: Medium: Collaborative Research: Discovery and Exploration of Design Trade-Offs

CHS：媒介：协作研究：设计权衡的发现和探索

• 批准号: 1955697
• 负责人: Wojciech Matusik
• 金额: $ 37.5万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1955697&HistoricalAwards=false
• 关键词: CHS; Medium; Collaborative; Research; Discovery

To build functional, complex, and integrated products, we need tools that allow engineers to efficiently explore a design space that encompasses geometry, materials, electronics, software, and fabrication processes, and these computational tools must be able to simultaneously optimize conflicting objectives such as mechanical performance, weight, and cost. Currently, experts and novice users alike go through a long process of trial-and-error to identify top-performing designs, and a critical bottleneck then occurs when engineers convert concepts created by designers into high-performance products because design variations that improve one performance metric may worsen another, so that there is no single best possible design but rather a set of "Pareto optimal" designs that reflect different trade-offs. This research will create algorithms that can discover the Pareto front of trade-offs efficiently and can then present it to engineers and designers seeking to optimize the performance of a design along more than one axis. Project outcomes will make foundational contributions to computer-aided manufacturing, with demonstrations on a variety of pipelines for creating different types of objects. The resulting methods will both allow engineers to create high-performing products in less time while also dramatically improving the quality of the products themselves. The work will have additional broad impact through involvement of both undergraduate and high school students in the research activities.To achieve the project's goals, novel methods will be developed for capturing the full space of optimal design trade-offs whose shape is typically nonlinear and even disconnected. These methods will be driven by probabilistic analysis in the context of multi-objective stochastic optimization. Efficient representations and algorithms for exploring trade-offs with real-time feedback, showing which designs achieve desired performance characteristics, will also be defined. These techniques will then be used to implement a system that conveys an intuitive understanding of design trade-offs, allowing engineers to quickly discover desired solutions or find efficient ways to iterate on the design specifications. In addition, for complex designs requiring assembly-based approaches, tools will be created for iteratively constraining and refining the design space until the engineer feels confident with the assembled artifact. The workflow will allow engineers to find solutions that are better than what a human or a computer alone would find.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

为了构建功能，复杂和集成的产品，我们需要工具，使工程师能够有效探索一个包含几何，材料，电子，软件和制造过程的设计空间，并且这些计算工具必须能够同时优化冲突的目标，例如机械性能，重量，重量和成本。 Currently, experts and novice users alike go through a long process of trial-and-error to identify top-performing designs, and a critical bottleneck then occurs when engineers convert concepts created by designers into high-performance products because design variations that improve one performance metric may worsen another, so that there is no single best possible design but rather a set of "Pareto optimal" designs that reflect different trade-offs. 这项研究将创建算法，可以有效地发现权衡的帕累托前线，然后可以将其展示给寻求优化多个轴设计性能的工程师和设计师。 项目成果将为计算机辅助制造提供基本贡献，并在各种管道上进行了用于创建不同类型对象的管道的演示。 最终的方法都将使工程师能够在更少的时间内创建高性能的产品，同时也可以显着提高产品本身的质量。 这项工作将通过在研究活动中涉及本科生和高中生的参与，从而产生更大的影响。为了实现该项目的目标，将开发出新的方法来捕捉最佳设计权衡的整个空间，这些最佳设计权衡通常是非线性的，甚至是断开了连接的。 这些方法将由多目标随机优化的背景下的概率分析驱动。 还将定义有效的表示和算法，以实时反馈探索权衡取舍，显示哪些设计具有所需的性能特征。 然后，这些技术将用于实施一个系统，该系统传达了对设计权衡的直观理解，从而使工程师可以快速发现所需的解决方案或找到有效的方法来迭代设计规格。 此外，对于需要基于组装方法的复杂设计，将为迭代限制和完善设计空间创建工具，直到工程师对组装的工件感到充满信心。 该工作流程将使工程师能够找到比人类或计算机所能找到的要好的解决方案。该奖项反映了NSF的法定任务，并认为使用基金会的知识分子优点和更广泛的影响评估标准，认为值得通过评估来获得支持。

项目成果

Data-Free Learning of Reduced-Order Kinematics

• DOI: 10.1145/3588432.3591521
• 发表时间: 2023-05
• 期刊: ACM SIGGRAPH 2023 Conference Proceedings
• 作者: Nicholas Sharp;Cristian Romero;Alec Jacobson;E. Vouga;P. Kry;D. Levin;J. Solomon

Pareto gamuts: exploring optimal designs across varying contexts

帕累托域：探索不同环境下的最佳设计

• DOI: 10.1145/3450626.3459750
• 发表时间: 2021
• 期刊: ACM Transactions on Graphics
• 影响因子: 6.2
• 作者: Makatura, Liane;Guo, Minghao;Schulz, Adriana;Solomon, Justin;Matusik, Wojciech
• 通讯作者: Matusik, Wojciech

Learning Proximal Operators to Discover Multiple Optima

• 发表时间: 2022-01
• 期刊: ArXiv
• 作者: Lingxiao Li;Noam Aigerman;Vladimir G. Kim;Jiajin Li;K. Greenewald;M. Yurochkin;J. Solomon

MechSense: A Design and Fabrication Pipeline for Integrating Rotary Encoders into 3D Printed Mechanisms

MechSense：将旋转编码器集成到 3D 打印机构中的设计和制造流程

• DOI: 10.1145/3544548.3581361
• 发表时间: 2023
• 期刊: CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
• 作者: Alalawi, Marwa;Pacik-Nelson, Noah;Zhu, Junyi;Greenspan, Ben;Doan, Andrew;Wong, Brandon M;Owen-Block, Benjamin;Mickens, Shanti Kaylene;Schoeman, Wilhelm Jacobus;Wessely, Michael
• 通讯作者: Wessely, Michael