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Volume 3A: 49th Design Automation Conference (DAC)

Front Matter

IDETC-CIE2023 Front Matter

IDETC-CIE 2023; V03AT00A001https://doi.org/10.1115/DETC2023-FM3A

Abstract

View Articletitled, IDETC-CIE2023 Front Matter

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49th Design Automation Conference (DAC)

Control Co-Design

Control Co-Design With Approximate Explicit Model Predictive Controllers

Ying-Kuan Tsai, Richard J. Malak, Jr.

IDETC-CIE 2023; V03AT03A001https://doi.org/10.1115/DETC2023-109551

Abstract

View Articletitled, Control Co-Design With Approximate Explicit Model Predictive Controllers

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Topics: Control equipment , Design , Stability , Optimization , Probability , Approximation , Control systems , Decision making , Dynamic systems , Errors

Control Co-Design With Varying Available Information Applied to Vehicle Suspensions

Saeid Bayat, James T. Allison

IDETC-CIE 2023; V03AT03A002https://doi.org/10.1115/DETC2023-114690

Abstract

View Articletitled, Control Co-Design With Varying Available Information Applied to Vehicle Suspensions

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Topics: Design , Optimal control , Optimization , Predictive control , Suspension systems

A Two-Timescale Reinforcement Learning Approach for Control Co-Design Problems

Eddieb Sadat, Mostaan Lotfalian Saremi, Alparslan Emrah Bayrak

IDETC-CIE 2023; V03AT03A003https://doi.org/10.1115/DETC2023-116567

Abstract

View Articletitled, A Two-Timescale Reinforcement Learning Approach for Control Co-Design Problems

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Topics: Design , Reinforcement learning

Platform Hydrodynamic and Structural Control Co-Optimization for the Floating Offshore Wind Turbines

Jinbin Liang, Xianping Du, Jianbo Yi, Guowei Qian, Peng Xie, Hongyi Xu

IDETC-CIE 2023; V03AT03A004https://doi.org/10.1115/DETC2023-117541

Abstract

View Articletitled, Platform Hydrodynamic and Structural Control Co-Optimization for the Floating Offshore Wind Turbines

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Topics: Dampers , Design , Floating wind turbines , Hydrodynamics , Optimization

Artificial Intelligence and Machine Learning for Challenging Real-World Problems in Design Automation

A Heuristic Approach to Classify Geometrically Defective Bead Segments Based on Range of Curvature, Range of Sound Power and Maximum Height

Nowrin Akter Surovi, Gim Song Soh

IDETC-CIE 2023; V03AT03A005https://doi.org/10.1115/DETC2023-114741

Abstract

View Articletitled, A Heuristic Approach to Classify Geometrically Defective Bead Segments Based on Range of Curvature, Range of Sound Power and Maximum Height

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Topics: Additive manufacturing , Density , Errors , Optical quality control , Wire

Automating Style Analysis and Visualization With Explainable AI - Case Studies on Brand Recognition

Yu-Hsuan Chen, Levant Burak Kara, Jonathan Cagan

IDETC-CIE 2023; V03AT03A006https://doi.org/10.1115/DETC2023-115150

Abstract

View Articletitled, Automating Style Analysis and Visualization With Explainable AI - Case Studies on Brand Recognition

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Topics: Artificial neural networks , Automobiles , Data acquisition , Design , Design automation , Economics , Lenses (Optics) , Modeling , Robustness , Scalars

Characterizing Designs via Isometric Embeddings: Applications to Airfoil Inverse Design

Qiuyi Chen, Mark D. Fuge

IDETC-CIE 2023; V03AT03A007https://doi.org/10.1115/DETC2023-116743

Abstract

View Articletitled, Characterizing Designs via Isometric Embeddings: Applications to Airfoil Inverse Design

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Topics: Airfoils , Design , Ablation (Vaporization technology) , Manifolds , Shape optimization , Trains

Counterfactuals for Design: A Model-Agnostic Method for Design Recommendations

Lyle Regenwetter, Yazan Abu Obaideh, Faez Ahmed

IDETC-CIE 2023; V03AT03A008https://doi.org/10.1115/DETC2023-117216

Abstract

View Articletitled, Counterfactuals for Design: A Model-Agnostic Method for Design Recommendations

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Topics: Design , Design automation , Weight (Mass) , Bicycles , Collaboration , Optimization , Pareto optimization , Safety , Tradeoffs , Visualization

Novel AI or ML Frameworks for Design or Systems Science

Bayesian Mesh Optimization for Graph Neural Networks to Enhance Engineering Performance Prediction

Jangseop Park, Namwoo Kang

IDETC-CIE 2023; V03AT03A009https://doi.org/10.1115/DETC2023-113308

Abstract

View Articletitled, Bayesian Mesh Optimization for Graph Neural Networks to Enhance Engineering Performance Prediction

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Topics: Artificial neural networks , Computer-aided design , Computer-aided engineering , Design , Metamodeling , Optimization

On the Use of Geometric Deep Learning Towards the Evaluation of Graph-Centric Engineering Systems

Anthony Sirico, Jr., Daniel R. Herber

IDETC-CIE 2023; V03AT03A010https://doi.org/10.1115/DETC2023-114592

Abstract

View Articletitled, On the Use of Geometric Deep Learning Towards the Evaluation of Graph-Centric Engineering Systems

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Topics: Circuits , Design , Engineering systems and industry applications , Machine learning , Gas diffusion layers , Frequency response , Topology , Tradeoffs

AutoSurf: Automated Expert-Guided Meshing With Graph Neural Networks and Conformal Predictions

Amin Heyrani Nobari, Justin Rey, Suhas Kodali, Matthew Jones, Faez Ahmed

IDETC-CIE 2023; V03AT03A011https://doi.org/10.1115/DETC2023-115065

Abstract

View Articletitled, AutoSurf: Automated Expert-Guided Meshing With Graph Neural Networks and Conformal Predictions

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Topics: Artificial neural networks , Computational fluid dynamics , Image segmentation

Diffusing the Optimal Topology: A Generative Optimization Approach

Giorgio Giannone, Faez Ahmed

IDETC-CIE 2023; V03AT03A012https://doi.org/10.1115/DETC2023-116595

Abstract

View Articletitled, Diffusing the Optimal Topology: A Generative Optimization Approach

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Topics: Optimization , Topology , Diffusion (Physics) , Approximation , Design , Engineering design , Engineering systems and industry applications , Errors , Topology optimization

Document Understanding-Based Design Support: Language Model Based Design Knowledge Extraction

Yunjian Qiu, Yan Jin

IDETC-CIE 2023; V03AT03A013https://doi.org/10.1115/DETC2023-116746

Abstract

View Articletitled, Document Understanding-Based Design Support: Language Model Based Design Knowledge Extraction

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Topics: Design

Topology Optimization Using Neural Networks With Conditioning Field Initialization for Improved Efficiency

Hongrui Chen, Aditya Joglekar, Levent Burak Kara

IDETC-CIE 2023; V03AT03A014https://doi.org/10.1115/DETC2023-116937

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View Articletitled, Topology Optimization Using Neural Networks With Conditioning Field Initialization for Improved Efficiency

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Topics: Artificial neural networks , Topology optimization , Density , Topology , Design , Displacement , Finite element analysis , Geometry , Optimization

Data-Driven Design

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

Cyril Picard, Jürg Schiffmann, Faez Ahmed

IDETC-CIE 2023; V03AT03A015https://doi.org/10.1115/DETC2023-111609

Abstract

View Articletitled, Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

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Topics: Engineering design , Artificial intelligence , Compressors , Design , Sampling methods , Tradeoffs , Turbochargers

Deep Generative Model-Based Synthesis of Four-Bar Linkage Mechanisms Considering Both Kinematic and Dynamic Conditions

Sumin Lee, Jihoon Kim, Namwoo Kang

IDETC-CIE 2023; V03AT03A016https://doi.org/10.1115/DETC2023-114464

Abstract

View Articletitled, Deep Generative Model-Based Synthesis of Four-Bar Linkage Mechanisms Considering Both Kinematic and Dynamic Conditions

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Topics: Kinematics , Linkages , Design , Torque , Design methodology , Displacement , Generative design , Scalars

GradeS: An AI-Driven Graphic Design Support System for Design Style Analysis

Jinyu Song, Weitao You, Shuhui Shi, Ziwei Tu, Juntao Ji, Kaixin Han, Lingyun Sun

IDETC-CIE 2023; V03AT03A017https://doi.org/10.1115/DETC2023-114660

Abstract

View Articletitled, GradeS: An AI-Driven Graphic Design Support System for Design Style Analysis

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Topics: Data-driven design , Design

On-the-Fly Dual Reduction Method on Transient Fluid Topology Optimization

Tianye Wang, Xiaoping Qian

IDETC-CIE 2023; V03AT03A018https://doi.org/10.1115/DETC2023-114806

Abstract

View Articletitled, On-the-Fly Dual Reduction Method on Transient Fluid Topology Optimization

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Topics: Fluids , Modeling , Topology optimization , Transients (Dynamics)

Investigating the Effect of a Brand Factor in Product Design Based on a Data-Driven Approach Using Online Reviews

Seyoung Park, Harrison Kim

IDETC-CIE 2023; V03AT03A019https://doi.org/10.1115/DETC2023-114966

Abstract

View Articletitled, Investigating the Effect of a Brand Factor in Product Design Based on a Data-Driven Approach Using Online Reviews

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Topics: Bills of materials , Data-driven design , Equilibrium (Physics) , Product design

A Visual Representation of Engineering Catalogs Using Variational Autoencoders

Saketh Sridhara, Krishnan Suresh

IDETC-CIE 2023; V03AT03A020https://doi.org/10.1115/DETC2023-115029

Abstract

View Articletitled, A Visual Representation of Engineering Catalogs Using Variational Autoencoders

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Topics: Artificial neural networks , Bearings , Design , Dimensions , Engineering disciplines , Engineering systems and industry applications , Errors , Motors , Product development , Visualization

Interpretable Neural Network Analyses for Understanding Complex Physical Interactions in Engineering Design

Tuba Dolar, Doksoo Lee, Wei Chen

IDETC-CIE 2023; V03AT03A021https://doi.org/10.1115/DETC2023-115103

Abstract

View Articletitled, Interpretable Neural Network Analyses for Understanding Complex Physical Interactions in Engineering Design

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Topics: Artificial neural networks , Engineering design , Machine learning , Sensitivity analysis

Investigate Customer Preferences Using Online Video Reviews - Preliminary Results

Kangcheng Lin, Harrison Kim

IDETC-CIE 2023; V03AT03A022https://doi.org/10.1115/DETC2023-115206

Abstract

View Articletitled, Investigate Customer Preferences Using Online Video Reviews - Preliminary Results

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Topics: Preferences , Feedback , E-commerce , Engineering design , Product design

Heat Sink Design Optimization via GAN-CNN Combined Deep-Learning

Nathan Flynn, Xiaoping Qian

IDETC-CIE 2023; V03AT03A023https://doi.org/10.1115/DETC2023-116429

Abstract

View Articletitled, Heat Sink Design Optimization via GAN-CNN Combined Deep-Learning

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Topics: Design , Heat sinks , Optimization , Simulation , Temperature , Artificial neural networks , Computational fluid dynamics , Computer software , Errors , Fluid dynamics

On the Connectedness of the Topology Optimization Predictors

Mohammad Mahdi Behzadi, Horea T. Ilies

IDETC-CIE 2023; V03AT03A024https://doi.org/10.1115/DETC2023-116574

Abstract

View Articletitled, On the Connectedness of the Topology Optimization Predictors

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Topics: Topology , Topology optimization

When Is it Actually Worth Learning Inverse Design?

Milad Habibi, Jun Wang, Mark Fuge

IDETC-CIE 2023; V03AT03A025https://doi.org/10.1115/DETC2023-116678

Abstract

View Articletitled, When Is it Actually Worth Learning Inverse Design?

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Topics: Design , Topology optimization , Optimization , Artificial neural networks , Design methodology , Machine learning , Physics , Shapes

Design of Self-Organizing Systems Using Multi-Agent Reinforcement Learning and the Compromise Decision Support Problem Construct

Mingfei Jiang, Zhenjun Ming, Chuanhao Li, Farrokh Mistree, Janet K. Allen

IDETC-CIE 2023; V03AT03A026https://doi.org/10.1115/DETC2023-116703

Abstract

View Articletitled, Design of Self-Organizing Systems Using Multi-Agent Reinforcement Learning and the Compromise Decision Support Problem Construct

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Topics: Design , Reinforcement learning , Self-organization

Using Machine Learning to Predict the Adoption of Building Electrification Technologies in US Households

Andrew Majowicz, Philip Odonkor

IDETC-CIE 2023; V03AT03A027https://doi.org/10.1115/DETC2023-116751

Abstract

View Articletitled, Using Machine Learning to Predict the Adoption of Building Electrification Technologies in US Households

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Topics: Electrification , Machine learning , Stress

Ship-D: Ship Hull Dataset for Design Optimization Using Machine Learning

Noah J. Bagazinski, Faez Ahmed

IDETC-CIE 2023; V03AT03A028https://doi.org/10.1115/DETC2023-117003

Abstract

View Articletitled, Ship-D: Ship Hull Dataset for Design Optimization Using Machine Learning

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Topics: Design , Hull , Machine learning , Optimization , Ships , Naval architecture , Drag (Fluid dynamics) , Cycles , Computational methods , Computer-aided design

Surrogate Modeling of Car Drag Coefficient With Depth and Normal Renderings

Binyang Song, Chenyang Yuan, Frank Permenter, Nikos Arechiga, Faez Ahmed

IDETC-CIE 2023; V03AT03A029https://doi.org/10.1115/DETC2023-117400

Abstract

View Articletitled, Surrogate Modeling of Car Drag Coefficient With Depth and Normal Renderings

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Topics: Design , Drag (Fluid dynamics) , Metamodeling

Decision Making in Engineering Design

Modeling the Dynamics of Customer Demand to Determine the Optimal Time to Release Product Updates: A Cognitive Approach

Ian Walter, Philip E. Paré, Jitesh H. Panchal

IDETC-CIE 2023; V03AT03A030https://doi.org/10.1115/DETC2023-115259

Abstract

View Articletitled, Modeling the Dynamics of Customer Demand to Determine the Optimal Time to Release Product Updates: A Cognitive Approach

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Topics: Dynamics (Mechanics) , Field theories (Physics) , Modeling

A Framework to Support Multilevel Robust Co-Design of Manufacturing Supply Networks

Mathew Baby, Akshay Guptan, Jacob Broussard, Janet K. Allen, Farrokh Mistree, Anand Balu Nellippallil

IDETC-CIE 2023; V03AT03A031https://doi.org/10.1115/DETC2023-117145

Abstract

View Articletitled, A Framework to Support Multilevel Robust Co-Design of Manufacturing Supply Networks

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Topics: Design , Manufacturing

Design and Optimization of Energy Systems

Improving Nonuniform Utilization of Li-Ion Pouch Cells Using Tapered Electrodes Through Calendering

Changik Cho, Seth Kelley, Joseph G. Tylka, Miao He, Naresh N. Nandola, Christopher D. Rahn

IDETC-CIE 2023; V03AT03A032https://doi.org/10.1115/DETC2023-111360

Abstract

View Articletitled, Improving Nonuniform Utilization of Li-Ion Pouch Cells Using Tapered Electrodes Through Calendering

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Topics: Electrodes

System Level Techno-Economic and Environmental Design Optimization for Ocean Wave Energy

Rebecca McCabe, Madison Dietrich, Alan Liu, Maha Haji

IDETC-CIE 2023; V03AT03A033https://doi.org/10.1115/DETC2023-114607

Abstract

View Articletitled, System Level Techno-Economic and Environmental Design Optimization for Ocean Wave Energy

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Topics: Design , Economics , Optimization , Wave energy , Architecture , Ocean waves , Renewable energy , Sustainability , Wave energy converters

A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation

Honglin Li, Cong Feng, Jie Zhang

IDETC-CIE 2023; V03AT03A034https://doi.org/10.1115/DETC2023-114762

Abstract

View Articletitled, A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation

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Topics: Density , Wind farms , Wind power , Energy generation , Wind resource assessments , Wind turbines , Wind velocity , China , Computer simulation , Energy management

Exploration of Building Clustering Potential With Energy Storage in New York City

Gregory Kaminski, Philip Odonkor

IDETC-CIE 2023; V03AT03A035https://doi.org/10.1115/DETC2023-115046

Abstract

View Articletitled, Exploration of Building Clustering Potential With Energy Storage in New York City

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Topics: Distributed power generation , Energy storage

Multi-Fidelity Modeling for Dynamic Power Control and Optimization of Nuclear-Renewable Hybrid Energy Systems

In-Bum Chung, Pingfeng Wang

IDETC-CIE 2023; V03AT03A036https://doi.org/10.1115/DETC2023-116914

Abstract

View Articletitled, Multi-Fidelity Modeling for Dynamic Power Control and Optimization of Nuclear-Renewable Hybrid Energy Systems

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Topics: Energy / power systems , Modeling , Optimization

Multiphysics-Informed Machine Learning for Battery Design and Health Monitoring

Parth Bansal, Yumeng Li

IDETC-CIE 2023; V03AT03A037https://doi.org/10.1115/DETC2023-117113

Abstract

View Articletitled, Multiphysics-Informed Machine Learning for Battery Design and Health Monitoring

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Topics: Anodes , Batteries , Design , Lithium-ion batteries , Machine learning

Modeling a Concentrated Solar Collector (CSC) - Convection-Enhanced Evaporation (CEE) System for Small-Scale Brine Management

Nallely Guillen Rodriguez, Mustafa F. Kaddoura, Natasha C. Wright

IDETC-CIE 2023; V03AT03A038https://doi.org/10.1115/DETC2023-117236

Abstract

View Articletitled, Modeling a Concentrated Solar Collector (CSC) - Convection-Enhanced Evaporation (CEE) System for Small-Scale Brine Management

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Topics: Convection , Evaporation , Modeling , Solar collectors , Solar energy , Temperature , Thermal energy , Stress , Water , Control equipment

Design for Additive Manufacturing

Empirically Tuned Mechanical Simulation Model of 3D-Printed Biaxial Weaves

Marc Wirth, Kristina Shea

IDETC-CIE 2023; V03AT03A039https://doi.org/10.1115/DETC2023-111278

Abstract

View Articletitled, Empirically Tuned Mechanical Simulation Model of 3D-Printed Biaxial Weaves

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Topics: Additive manufacturing , Engineering simulation , Simulation , Textiles

Build Orientation Optimization for Five-Axis 3D Printing

Ghazi Alonayni, Matthew I. Campbell

IDETC-CIE 2023; V03AT03A040https://doi.org/10.1115/DETC2023-111726

Abstract

View Articletitled, Build Orientation Optimization for Five-Axis 3D Printing

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Topics: Additive manufacturing , Optimization , Surface quality , Printing , Stability , Manufacturing

Process-Aware Prediction of Geometric Accuracy for Additive Manufacturing via Transfer Learning

Daphne Lin, Carolyn Seepersad

IDETC-CIE 2023; V03AT03A041https://doi.org/10.1115/DETC2023-111826

Abstract

View Articletitled, Process-Aware Prediction of Geometric Accuracy for Additive Manufacturing via Transfer Learning

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Topics: Additive manufacturing , Lasers , Metrology , Polymers , Sintering

Topology Optimization in Consideration of Overhang Constraint for Additive Manufacturing Based on Coupled Fictitious Physical Model in Thermal Design Problem

Mikihiro Tajima, Takayuki Yamada

IDETC-CIE 2023; V03AT03A042https://doi.org/10.1115/DETC2023-112499

Abstract

View Articletitled, Topology Optimization in Consideration of Overhang Constraint for Additive Manufacturing Based on Coupled Fictitious Physical Model in Thermal Design Problem

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Topics: Additive manufacturing , Design , Topology optimization

Application of a Continuous Variable Density Infill: Manipulating Center of Gravity

Patrick N. Murphy, Bashir Khoda

IDETC-CIE 2023; V03AT03A043https://doi.org/10.1115/DETC2023-116644

Abstract

View Articletitled, Application of a Continuous Variable Density Infill: Manipulating Center of Gravity

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Topics: Center of mass , Density , Extruding , Algorithms , Additive manufacturing , Errors , Modeling , Design engineering , Inertia (Mechanics) , Matlab

A Framework Establishing the Bounds of Small Angle Assumptions in Multi-Material Additively Manufactured Compliant Mechanisms

Evelyn Thomas, Nicholas Meisel, Jared Butler

IDETC-CIE 2023; V03AT03A044https://doi.org/10.1115/DETC2023-116865

Abstract

View Articletitled, A Framework Establishing the Bounds of Small Angle Assumptions in Multi-Material Additively Manufactured Compliant Mechanisms

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Topics: Additive manufacturing , Compliant mechanisms , Extruding

Design for Market Systems

Evolutionary Co-Mention Network Analysis via Social Media Mining

Phillip A. O. Gavino, Yinshuang Xiao, Yaxin Cui, Wei Chen, Zhenghui Sha

IDETC-CIE 2023; V03AT03A045https://doi.org/10.1115/DETC2023-115114

Abstract

View Articletitled, Evolutionary Co-Mention Network Analysis via Social Media Mining

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Topics: Mining , Network analysis

Exploring How the Design Hierarchy of Needs Explains Correlations Between Design Decisions and Online Customer Review Ratings

Lisa Retzlaff, Scott Ferguson

IDETC-CIE 2023; V03AT03A046https://doi.org/10.1115/DETC2023-117051

Abstract

View Articletitled, Exploring How the Design Hierarchy of Needs Explains Correlations Between Design Decisions and Online Customer Review Ratings

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Topics: Design

Design for Resilience and Failure Recover

A Reliability-Based Optimization Framework for Planning Operational Profiles for Unmanned Systems

Indranil Hazra, Arko Chatterjee, Joseph Southgate, Matthew J. Weiner, Katrina M. Groth, Shapour Azarm

IDETC-CIE 2023; V03AT03A047https://doi.org/10.1115/DETC2023-116586

Abstract

View Articletitled, A Reliability-Based Optimization Framework for Planning Operational Profiles for Unmanned Systems

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Topics: Reliability-based optimization , Optimization , Reliability , Bayesian network , Control systems , Cooling , Engineering systems and industry applications , Engines , Event history analysis , Maintainability