Causality and sensitivity analysis in distributed design simulation
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, February 2002.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2005
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| Online Access: | http://hdl.handle.net/1721.1/8329 |
| _version_ | 1826188921704284160 |
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| author | Kim, Jaehyun, 1970- |
| author2 | David R. Wallace. |
| author_facet | David R. Wallace. Kim, Jaehyun, 1970- |
| author_sort | Kim, Jaehyun, 1970- |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, February 2002. |
| first_indexed | 2024-09-23T08:06:44Z |
| format | Thesis |
| id | mit-1721.1/8329 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:06:44Z |
| publishDate | 2005 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/83292022-01-13T07:54:36Z Causality and sensitivity analysis in distributed design simulation Kim, Jaehyun, 1970- David R. Wallace. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering Mechanical Engineering. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, February 2002. Includes bibliographical references (leaves 109-111). Numerous collaborative design frameworks have been developed to accelerate the product development, and recently environments for building distributed simulations have been proposed. For example, a simulation framework called DOME (Distributed Object-oriented Modeling and Evaluation) has been developed in MIT CADlab. DOME is unique in its decentralized structure that allows heterogeneous simulations to be stitched together while allowing proprietary information an simulation models to remain secure with each participant. While such an approach offers many advantages, it also hides causality and sensitivity information, making it difficult for designers to understand problem structure and verify solutions. The purpose of this research is to analyze the relationships between design parameters (causality) and the strength of the relationships (sensitivity) in decentralized web-based design simulation. Algorithms and implementations for the causality and sensitivity analysis are introduced. Causality is determined using Granger's definition of causality, which is to distinguish causation from association using conditional variance of the suspected output variable. Sensitivity is estimated by linear regression analysis and a perturbation method, which transfers the problem into a frequency domain by generating periodic perturbations. Varying Internet latency and disturbances are issues with these methods. Thus, algorithms are developed and tested to overcome these problems. by Jaehyun Kim. Ph.D. 2005-08-23T19:14:13Z 2005-08-23T19:14:13Z 2001 2002 Thesis http://hdl.handle.net/1721.1/8329 50499447 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 111 leaves 7144848 bytes 7144603 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Kim, Jaehyun, 1970- Causality and sensitivity analysis in distributed design simulation |
| title | Causality and sensitivity analysis in distributed design simulation |
| title_full | Causality and sensitivity analysis in distributed design simulation |
| title_fullStr | Causality and sensitivity analysis in distributed design simulation |
| title_full_unstemmed | Causality and sensitivity analysis in distributed design simulation |
| title_short | Causality and sensitivity analysis in distributed design simulation |
| title_sort | causality and sensitivity analysis in distributed design simulation |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/8329 |
| work_keys_str_mv | AT kimjaehyun1970 causalityandsensitivityanalysisindistributeddesignsimulation |