Index Catalog // Arch : Northwestern University Institutional Repository

Description:: Engineering design is a systematic process of identifying needs and their translation into functional systems. This is a cyclic process that alternates between the acquisition of data and the synthesis of said data to inform design decisions. Conventionally, data from physical experiments are used to explore the efficacy of alternative...
Keyword:: Uncertainty quantification, Design, Decision making, Machine learning, Data acquisition, and Data synthesis
Subject:: Design and Mechanical engineering
Creator:: van Beek, Anton
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/02/2022
Date Created:: 2021-01-01
Resource Type:: Dissertation
Alternate Identifier:: etdadmin_upload_861337 and http://dissertations.umi.com/northwestern:15848

Description:: Modern design practices rely more and more on computer simulations due to their low cost compared with physical experiments. However, it is still an elusive task to fully unleash the advantages of the simulation models while mitigating their disadvantages for designing complex engineering systems. In simulation-based design, computer simulation models...
Keyword:: Design optimization, Bayesian optimization, Uncertainty quantification, Simulation-based design, Model calibration, and Multidisciplinary design
Subject:: Statistics, Design, and Mechanical engineering
Creator:: Tao, Siyu
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/01/2021
Date Created:: 2020-01-01
Resource Type:: Dissertation
Alternate Identifier:: etdadmin_upload_773686 and http://dissertations.umi.com/northwestern:15350

Description:: Traditionally, simulation analysis has focused on designing a computationally efficient algorithm assuming a correct simulation model is given. As computation becomes cheaper, we are now able to perform more sophisticated simulation analyses involving extensive computation and consider all sources of errors in the simulation model and their effects to the...
Keyword:: Global sensitivity analysis, Model risk, Uncertainty quantification, Simulation optimization, and Input uncertainty
Subject:: Industrial Engineering and Management Sciences
Creator:: Hunhye Song
Owner:: Scholarly Digital Publishing
Date Uploaded:: 03/30/2018
Date Modified:: 03/30/2018
Date Created:: 2017-01-01
Resource Type:: Dissertation

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