Browsing by Author "Yang, Ding"

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Citation - WoS: 9
Citation - Scopus: 16
Impacts of problem scale and sampling strategy on surrogate model accuracy: An application of surrogate-based optimization in building design
(Institute of Electrical and Electronics Engineers Inc., 2016) Ding Yang; Yimin Sun; Danilo Di Stefano; Michela Turrin; I. Sevil Sariyildiz; di Stefano, Danilo; Turrin, Michela; Sariyildiz, Sevil; Sun, Yimin; Yang, Ding
Surrogate-based Optimization is a useful approach when the objective function is computationally expensive to evaluate compared to Simulation-based Optimization. In the surrogate-based method analytically tractable 'surrogate models' (also known as 'Response Surface Models - RSMs' or 'metamodels') are constructed and validated for each optimization objective and constraint at relatively low computational cost. They are useful for replacing the time-consuming simulations during the optimization, quickly locating the area where the optimum is expected to be for further search, and gaining insight into the global behavior of the system. Nevertheless there are still concerns about the surrogate model accuracy and the number of simulations necessary to get a reasonably accurate surrogate model. This paper aims to unveil: 1) the possible impacts of problem scale and sampling strategy on the surrogate model accuracy, and 2) the potential of Surrogatebased Optimization in finding high quality solutions for building envelope design optimization problems. For this purpose a series of multi-objective optimization test cases that mainly consider daylight and energy performance were conducted within the same time frame. Then the results were compared in pair based on which discussions were made. Finally the corresponding conclusions were obtained after the comparative study. © 2017 Elsevier B.V. All rights reserved.
Citation - Scopus: 14
Sports building envelope optimization using Multi-objective Multidisciplinary Design Optimization (M-MDO) techniques
(Institute of Electrical and Electronics Engineers Inc., 2015) Ding Yang; Michela Turrin; I. Sevil Sariyildiz; Yimin Sun; Turrin, Michela; Sariyildiz, Sevil; Sun, Yimin; Yang, Ding
Sports building envelopes are complex systems involving multiple architectural and engineering performance requirements that are sometimes in conflict with each other. Typically daylight usage and energy efficiency as two primary concerns in building envelope design are of those conflicting aspects. To improve overall performance (including daylight and energy performance) by changing the geometries of the envelope windows and shading elements as well as the selection of construction materials Multi-objective Optimization (MOO) is a natural choice. Based on the generated Pareto front trade-off decisions between competing performance objectives can be made. However as the number of design variables from different disciplines increases the huge design space and the specialization of disciplines make the optimization process less efficient. Therefore two possible Multidisciplinary Design Optimization (MDO) frameworks namely Individual Disciplinary Feasible (i.e. IDF a single-level MDO framework) and Collaborative Optimization (i.e. CO a bi-level MDO framework) are investigated to combine with MOO. Resorting to the capability of MDO in decomposition and coordination between different disciplines parallel disciplinary simulations and/or bi-level optimizations can be realized which compresses design cycle time and achieves better overall performance. Through the combination of MOO and MDO Multi-objective Multidisciplinary Design Optimization (M-MDO or multi-objective MDO) problems are expected to be solved more effectively and efficiently. The whole process of the proposed method consists of three phases (i.e. preprocessing solution and post-processing phases) in which variable screening multi-objective MDO solving and Pareto front comparison are performed respectively. An ongoing real project located in China is used as a case study to test the proposed method. For now the research work is in the preprocessing phase. Preliminary observations and results are obtained and future research is discussed. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 6
Sports Building Envelope Optimization Using Multi-objective Multidisciplinary Design Optimization (M-MDO) Techniques Case of Indoor Sports Building Project in China
(IEEE, 2015) Ding Yang; Michela Turrin; Sevil Sariyildiz; Yimin Sun; Turrin, Michela; Sariyildiz, Sevil; Sun, Yimin; Yang, Ding
Sports building envelopes are complex systems involving multiple architectural and engineering performance requirements that are sometimes in conflict with each other. Typically daylight usage and energy efficiency as two primary concerns in building envelope design are of those conflicting aspects. To improve overall performance (including daylight and energy performance) by changing the geometries of the envelope windows and shading elements as well as the selection of construction materials Multi-objective Optimization (MOO) is a natural choice. Based on the generated Pareto front trade-off decisions between competing performance objectives can be made. However as the number of design variables from different disciplines increases the huge design space and the specialization of disciplines make the optimization process less efficient. Therefore two possible Multidisciplinary Design Optimization (MDO) frameworks namely Individual Disciplinary Feasible (i.e. IDF a single-level MDO framework) and Collaborative Optimization (i.e. CO a bi-level MDO framework) are investigated to combine with MOO. Resorting to the capability of MDO in decomposition and coordination between different disciplines parallel disciplinary simulations and/or bi-level optimizations can be realized which compresses design cycle time and achieves better overall performance. Through the combination of MOO and MDO Multi-objective Multidisciplinary Design Optimization (M-MDO or multi-objective MDO) problems are expected to be solved more effectively and efficiently. The whole process of the proposed method consists of three phases (i.e. preprocessing solution and post-processing phases) in which variable screening multi-objective MDO solving and Pareto front comparison are performed respectively. An ongoing real project located in China is used as a case study to test the proposed method. For now the research work is in the preprocessing phase. Preliminary observations and results are obtained and future research is discussed.