Development of a numerical optimization approach to ventilation system design to control airborne contaminant dispersion and occupant comfort

Khan, Amirul; Noakes, Catherine; Торопов, В. В.

doi:10.1007/s12273-012-0058-7

Cited by 9 publications

(12 citation statements)

References 34 publications

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“…Simulation of detailed building models may take several minutes in building energy simulation [27] to several hours in computational fluid dynamics (CFD) simulation [92] to complete while the simulation-based optimization techniques often require hundreds or thousands of simulation evaluations. The optimization schemes may therefore become infeasible due to such computationally expensive building models.…”

Section: Optimization Of Computationally Expensive Modelsmentioning

confidence: 99%

“…They also recommended that the use of Kriging models for optimization of complex buildings requires further investigations. In [92], Khan et al used the "moving least squares method" to establish a surrogate model from extremely expensive CFD simulations, then optimized the design of a ventilation system in hospital wards by this surrogate model. Gengembre et al [98] minimize 20-year life cycle cost of a single-zone building model using a Kriging surrogate model and the PSO.…”

Section: Optimization Of Computationally Expensive Modelsmentioning

confidence: 99%

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A review on simulation-based optimization methods applied to building performance analysis

2014

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Recent progress in computer science and stringent requirements of the design of "greener" buildings put forwards the research and applications of simulation-based optimization methods in the building sector. This paper provides an overview on this subject, aiming at clarifying recent advances and outlining potential challenges and obstacles in building design optimization. Key discussions are focused on handling discontinuous multi-modal building optimization problems, the performance and selection of optimization algorithms, multi-objective optimization, the application of surrogate models, optimization under uncertainty and the propagation of optimization techniques into real-world design challenges. This paper also gives bibliographic information on the issues of simulation programs, optimization tools, efficiency of optimization methods, and trends in optimization studies. The review indicates that future researches should be oriented towards improving the efficiency of search techniques and approximation methods (surrogate models) for largescale building optimization problems; and reducing time and effort for such activities. Further effort is also required to quantify the robustness in optimal solutions so as to improve building performance stability.

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Section: Optimization Of Computationally Expensive Modelsmentioning

confidence: 99%

Section: Optimization Of Computationally Expensive Modelsmentioning

confidence: 99%

A review on simulation-based optimization methods applied to building performance analysis

2014

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“…This capability is being exploited in the rapidly-growing research field of Computational Fluid Dynamics (CFD) optimization which is being utilised across a range of areas including aerospace engineering [2,3], tribology [4], polymer moulding [5], ship design [6], vehicle aerodynamics [7][8][9][10], hospital ward ventilation [11] and jet pump design [12]. Although these examples demonstrate the versatility of CFD-based optimization, there is one aspect which can prove problematic: the presence of numerical noise in the CFD responses [10,[13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Dealing with numerical noise in CFD-based design optimization

Gilkeson¹,

Торопов²,

Thompson³

et al. 2014

Computers & Fluids

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SUMMARYNumerical noise is an inevitable by-product of Computational Fluid Dynamics (CFD) simulations which can lead to challenges in finding optimum designs. This article draws attention to the issue, illustrating the difficulties it can cause for road vehicle aerodynamics simulations. Firstly a benchmark problem is used to assess a range of turbulence models and grid types. Large noise amplitudes up to 22% are evident for solutions computed on unstructured tetrahedral grids whereas computations on hexahedral and polyhedral grid structures exhibit substantially less noise. The Spalart Allmaras turbulence model is shown to be far less susceptible to noise levels than two other commonly-used models for this application.Secondly, multi-objective aerodynamic shape optimization is applied to a fairing for a practical road vehicle which is parameterised in terms of three design variables. Moving Least Squares (MLS) metamodels are constructed from 50 highfidelity CFD solutions for two objective functions. Subsequent optimization is successful for the first objective, however numerical noise levels in excess of 7% give rise to difficulties for the second one. A revision to the problem leads to success and the construction of a small Pareto Front. Further analysis underlines the inherent capability of MLS metamodels in dealing with noisy CFD responses.

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“…Simulation-assisted optimization strategies in building design are today mostly used for fine-tuning in specific, later-stage types of inquiry (Augenbroe, 2003), characterized by relatively clear goals and relatively few variables in play; or targeted to specific, constrained types of problems, determined by building type, or use, or objective function, and by the selection of specific issues of inquiry (Daum et al, 2009;Shin, 2011;Khan et al, 2012). This happens in spite of the fact that the variables influencing building performance are numerous and interrelated.…”

Section: Search In Building Designmentioning

confidence: 99%