A Two-Level Product Model for Simulation-Based Design of Mechanical Systems

1997 ◽  
Author(s):  
Kuang-Hua Chang ◽  
Kyung K. Choi ◽  
Jeff J. Y. Wang ◽  
Chung-Shin Tsai ◽  
Edwin Hardee
Keyword(s):  
Simulation Models ◽  
Design Stage ◽  
Physical Parameters ◽  
Cad Model ◽  
Preliminary Design ◽  
Product Model ◽  
Detailed Design ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Primary Focus

Abstract This paper presents a two-level product modeling method that supports Simulation-Based Design (SBD) of mechanical systems, primarily ground vehicles and heavy equipment, for preliminary and detailed design. A Computer-Aided Design (CAD) model combined with engineering parameters and mathematical equations that describe physical behavior of the mechanical system constitute its product model for SBD. For preliminary design, improvement of system performance, including dynamics and human factors, is the primary focus. A CAD model with reasonably accurate physical parameters, such as mass properties, is defined as the base definition of the product model. A parametric study can be conducted to search for design alternatives using dimension parameters created in the parameterized CAD model. Component designs are the primary focus in the detailed design stage. A detailed product model is evolved from that of the preliminary design, by refining geometric representation of mechanical components in CAD and expanding product assembly into parts and sub-assemblies for further engineering analysis. In the detailed design stage, a systematic design trade-off method is usually needed for design improvement. In both design stages, CAD and Computer-Aided Engineering (CAE) mappings that tie dimension parameters in the CAD model and physical parameters of simulation models facilitate the parametric study and design trade-off by quickly generating simulation models to simulate performance of the modified design. A High Mobility Multi-Purpose Wheeled Vehicle (HMMWV) is employed to illustrate and demonstrate the modeling method.

Study on Design Support Method Considering the Interaction Among Multi-Variables

2008 ◽  
Author(s):  
Junya Noda ◽  
Qiang Yu
Keyword(s):  
Graphical Model ◽  
Simulation Models ◽  
Hierarchical Cluster ◽  
Design Stage ◽  
Concept Design ◽  
Design Quality ◽  
Detailed Design ◽  
Design Support ◽  
Characteristic Values ◽  
Design Factors

Recently, a remarkable shortening of the development and design period becomes possible by the development of CAE and the optimization technologies, and efficient improvement of design quality in the detailed design stage has been achieved. Nevertheless, it is thought that there is a limit to for this kind of improvement in the near future, no matter how much the upgrade of the detailed design stage will be attempted. Therefore, the technology requested in the next step should be a new approach that can improve the quality of design concept and the efficiency of the concept design processes. For the engineers to improve concept design efficiency, they are requested that they should have very good understanding about the physics of their objectives and special experience about know-how for forming the answers to a very complicated problems. Thus, it is necessary to know the complicated physical relation between the design factors and the evaluation characteristic values to upgrade the concept design stage. It is thought that it can make a further improvement on the efficiency of design process if the technique, which can help the engineers to grip this relation, is established. However, it is very difficult for the engineers to understand a real complicated problem by few experiences. There are a lot of reasons for this kind of problems. For example, there will be a various patterns of design factors that achieve the similar design results, if the design factors have strong interacting relation between each other. In this study, the authors proposed a design support method for extracting the relation between the design factors and the evaluation characteristic values by using the results obtained by simulation models, and it was applied to the vehicle design problems in considering the interaction among the multi-variables by using a hierarchical cluster analysis and a graphical model. It was shown that the results given by the proposed approach can help the engineers to find and understand the essence of the phenomena involved.

Analytical Variance-Based Global Sensitivity Analysis in Simulation-Based Design Under Uncertainty

2004 ◽  
Author(s):  
Wei Chen ◽  
Ruichen Jin ◽  
Agus Sudjianto
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Simulation Models ◽  
Design Under Uncertainty ◽  
Global Sensitivity ◽  
Functional Relationships ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Input Variables ◽  
The Impact

The importance of sensitivity analysis in engineering design cannot be over-emphasized. In design under uncertainty, sensitivity analysis is performed with respect to the probabilistic characteristics. Global sensitivity analysis (GSA), in particular, is used to study the impact of variations in input variables on the variation of a model output. One of the most challenging issues for GSA is the intensive computational demand for assessing the impact of probabilistic variations. Existing variance-based GSA methods are developed for general functional relationships but require a large number of samples. In this work, we develop an efficient and accurate approach to GSA that employs analytic formulations derived from metamodels of engineering simulation models. We examine the types of GSA needed for design under uncertainty and derive generalized analytical formulations of GSA based on a variety of metamodels commonly used in engineering applications. The benefits of our proposed techniques are demonstrated and verified through both illustrative mathematical examples and the robust design for improving vehicle handling performance.

Bayesian Optimization for Simulation-Based Design of Multi-Model Systems

2020 ◽  
Author(s):  
Siyu Tao ◽  
Anton van Beek ◽  
Daniel W. Apley ◽  
Wei Chen
Keyword(s):  
Simulation Models ◽  
Model Systems ◽  
Bayesian Optimization ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Need To Evaluate ◽  
Complex Engineering ◽  
Component Models ◽  
Knowledge Gradient ◽  
Expensive Model

Abstract We address the problem of simulation-based design using multiple interconnected expensive simulation models, each modeling a different subsystem. Our goal is to find the globally optimal design with minimal model evaluation costs. To our knowledge, the best existing approach is to treat the whole system as a single expensive model and apply an existing Bayesian optimization (BO) algorithm. This approach is likely inefficient due to the need to evaluate all the component models in each iteration. We propose a multi-model BO approach that dynamically and selectively evaluates one component model per iteration based on linked emulators for uncertainty quantification and the system knowledge gradient (KG) as acquisition function. Building on this, we resolve problems with constraints and feedback couplings that often occur in real complex engineering design by penalizing the objective emulator and reformulating the original problem into a decoupled one. The superior efficiency of our approach is demonstrated through solving an analytical problem and a multidisciplinary design problem of electronic packaging optimization.

Learning abstract models for system design

1996 ◽  
Vol 10 (2) ◽  
pp. 167-169
Author(s):  
Sudhakar Y. Reddy
Keyword(s):  
Machine Learning ◽  
Early Stage ◽  
Simulation Models ◽  
Preliminary Design ◽  
Engineering Systems ◽  
Design Decisions ◽  
Detailed Design ◽  
Stage Design ◽  
Detailed Simulation ◽  
Early Stage Design

AbstractThough simulation models are extensively used for detailed design analysis, they find limited role in preliminary design decisions. We have developed a machine learning based approach to enable detailed simulation models to be harvested for supporting early-stage design of engineering systems.

Applied parametrized and automated airframe modeling methods in the preliminary design phase

2015 ◽  
Vol 06 (04) ◽  
pp. 1550037 ◽  
Author(s):  
Dominik B. Schwinn
Keyword(s):  
Design Process ◽  
Aircraft Design ◽  
Design Stage ◽  
Model Generation ◽  
Preliminary Design ◽  
Generation Process ◽  
Design Phase ◽  
Worst Case ◽  
Detailed Design ◽  
Preliminary Design Stage

The design process of new air- and rotorcraft is commonly separated into three different consecutive phases. In the conceptual design phase, the viability of different designs is investigated with respect to customer requirements and/or the market situation. It usually ends with the identification of a basic aircraft lay-out. In the subsequent preliminary design stage the various disciplines are introduced, thus redefining the design process as a multidisciplinary optimization (MDO) task. The objective of this design stage is to enhance the initial aircraft configuration by establishing an advanced design comprising a loft provided with primary structure. This updated aircraft configuration represents a global optimum solution for the specified requirements which will then be optimized on a local level in the concluding detailed design phase with particular regard to manufacturing aspects. The investigations in the preliminary design phase comprise the generation of numerous similar but still different analytical and finite element (FE) models. Even though computational power is constantly increasing the model generation process is still a time-consuming task. Moreover, it is also a potential source of errors which — in the worst case — may lead to time- and cost-intensive redesign activities during the detailed design. As the preliminary design stage, therefore, is of particular importance during the overall design process the model generation process benefits from parametric models and automated process chains. The presented paper overviews the tools used for the automated generation of FE models developed and used at the Institute of Structures and Design (BT) of the German Aerospace Center (DLR) for the subsequent use in numerical simulations. Furthermore, basic requirements for the effective use of parametrization and automation like a common data format and infrastructure will be introduced. Exemplary models and applications will be presented to illustrate the positive impact on efficiency in aircraft design. Concluding, future development steps and possible applications will be discussed.

Simulation Based Design of a Pediatric-Sized Hydraulic Ankle-Foot Orthosis

2016 ◽  
Author(s):  
Brett Cullen Neubauer ◽  
William K. Durfee
Keyword(s):  
Performance Metrics ◽  
Preliminary Design ◽  
Ankle Foot Orthosis ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Ankle Foot Orthoses ◽  
Computer Controlled ◽  
Optimal Stiffness ◽  
Foot Orthosis ◽  
Gait Impairments

Cerebral palsy can cause gait impairments in children that require the prescription of passive ankle-foot orthoses. This project aims to develop a pediatric-sized hydraulic active ankle-foot orthosis with computer-controlled stiffness. The orthosis will allow a clinician to investigate a range of AFO stiffnesses while collecting gait performance metrics to determine the optimal stiffness value for the AFO prescription. The ankle-foot orthosis uses hydraulic technology to generate the large required torques in a light, compact package. The preliminary design uses additive manufacturing to further reduce the weight of the manifolds on the medial and lateral sides of the ankle. The simulation prototype of the design illustrated that the orthosis should be capable of generating 91 Nm of ankle torque and a maximum angular velocity of 483 °/sec. The device will be a valuable resource in the clinic, saving time and resources in the AFO prescription process while improving the healthcare of the patient.

An Integrated Simulation-Based Design and Manufacturing Environment Using Intranet and CORBA

1997 ◽  
Author(s):  
Edwin Hardee ◽  
Chung-Shin Tsai ◽  
Kyung K. Choi
Keyword(s):  
Manufacturing Environment ◽  
Product Model ◽  
Design Data ◽  
Modeling Tools ◽  
Product Data ◽  
Integrated Simulation ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Design And Manufacturing ◽  
Store Product

Abstract An intranet-based tool for integrating an enterprise-wide simulation-based design and manufacturing environment for mechanical systems is presented. The tool is invoked as a Java applet from a web page. Users can browse global product model data from the applet and retrieve and store product data between the global product data server (called the Design Data Server) and their local workspaces. Network connections are based on the CORBA standard. This environment enables the achievement of concurrent engineering goals. It gives the members of an enterprise-wide product development team a convenient, uniform interface to the global product data from different platforms. It allows their various simulation and modeling tools on the different platforms to interoperate through the Design Data Server.

Integration Infrastructure for a Simulation-Based Design Environment

1995 ◽  
Author(s):  
Chung-Shin Tsai ◽  
Kuang-Hua Chang ◽  
Jia-Yi Wang
Keyword(s):  
Mechanical System ◽  
Computer Aided Design ◽  
Large Scale ◽  
Product Development Process ◽  
Design Stage ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Computer Aided ◽  
Aided Design ◽  
Functional Components

Abstract In this paper, the integration infrastructure for a simulation-based design (SBD) environment for mechanical system design developed at Center for Computer-Aided Design at the University of Iowa is presented. The SBD environment comprises the integration infrastructure and workspaces/tools that exploit Computer Aided Design (CAD)/Computer Aided Engineering (CAE) and software engineering technologies in support of design of large scale mechanical systems. The principal functional components of the SBD environment are engineering workspaces and CAD/CAE tools that bring engineers, servicemen, and customers early in the product development process to assess design of the product concurrently. The infrastructure is based on the newly invented engineering views that allow engineers from various disciplines to view the product with their own perspectives. The infrastructure allows engineers to create CAD and simulation models of the mechanical system, access engineering workspaces and CAD/CAE tools to perform multidisciplinary engineering analyses, use planning tools to create and manage simulation processes, communicate and exchange engineering data, and conduct design trade-off analyses and make informed decisions to yield a robust optimum design. The presentation given in this paper assumes that simulation-based design activities are performed in the product detailed design stage. The environment is being extended to support concept design.

Multi-Model Bayesian Optimization for Simulation-Based Design (DETC2020-22651)

2021 ◽  
pp. 1-39
Author(s):  
Siyu Tao ◽  
Anton van Beek ◽  
Daniel Apley ◽  
Wei Chen
Keyword(s):  
Simulation Models ◽  
Global Optimum ◽  
Bayesian Optimization ◽  
System Response ◽  
Engineering Systems ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Need To Evaluate ◽  
Complex Engineering ◽  
Component Models

Abstract We enhance the Bayesian optimization (BO) approach for simulation-based design of engineering systems consisting of multiple interconnected expensive simulation models. The goal is to find the global optimum design with minimal model evaluation costs. A commonly used approach is to treat the whole system as a single expensive model and apply an existing BO algorithm. This approach is inefficient due to the need to evaluate all the component models in each iteration. We propose a multi-model BO approach that dynamically and selectively evaluates one component model per iteration based on the uncertainty quantification of linked emulators (metamodels) and the knowledge gradient of system response as the acquisition function. Building on our basic formulation, we further solve problems with constraints and feedback couplings that often occur in real complex engineering design by penalizing the objective emulator and reformulating the original problem into a decoupled one. The superior efficiency of our approach is demonstrated through solving two analytical problems and the design optimization of a multidisciplinary electronic packaging system.

scholarly journals A Multilevel Product Model for Simulation-Based Design of Mechanical Systems

1998 ◽  
Vol 6 (2) ◽  
pp. 131-144 ◽  
Author(s):  
Kuang-Hua Chang ◽  
Kyung K. Choi ◽  
Jeff Wang ◽  
Chung-Shin Tsai ◽  
Edwin Hardee
Keyword(s):  
Mechanical Systems ◽  
Product Model ◽  
Simulation Based Design ◽  
Simulation Based
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