Numerical modeling and optimization of thermal comfort in building: Central composite design and CFD simulation

Alizadeh, Mostafa; Sadrameli, S.M.

doi:10.1016/j.enbuild.2018.01.006

Cited by 65 publications

(20 citation statements)

References 19 publications

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“…However, the design of radius C is directly affected by angles A and B. Furthermore, outlet width D is a key parameter affecting optimization studies [17]. CCD is an effective alternative to full-factorial design, which enables more data to be obtained through a smaller number of experiments.…”

Section: Optimization Analysis and Discussionmentioning

confidence: 99%

Optimal Design for an Extruder Head Runner Based on Response Surface Method and Simulated Annealing Algorithm

Zhou

Jiang

et al. 2018

International Journal of Polymer Science

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The head runner of a rubber extruder is important for controlling rubber flow and improving extrudate quality. To clarify the effect of the structure parameters of the head runner of a doubleplex tread extruder on extrudate quality and obtain high-quality rubber extrusions, a finite element model of the down head runner was established. The extrusion process was analyzed through numerical simulations, wherein the Bird-Carreau constitutive equation and Navier slip law were used along with some computational methods, such as quadratic interpolation of velocity and linear interpolation of pressure and viscosity. The Newton iteration algorithm was used for numerical calculations. The mean-square deviation of velocity (SDV) of rubber flow in the outlet cross section was selected as the evaluation objective. A Placket-Burman design was used to select three key factors-angles A and B and outlet width D-from among eight runner structure parameters affecting the velocity variance. By using central composite design (CCD), the quadratic response surface model using the three key factors was established, and the influence law of a combination of the three key factors on SDV was obtained. The response surface model was optimized using the simulated annealing (SA) algorithm, and the optimal key factors of the head runner were obtained. The optimal runner design realizes a more uniform velocity distribution in the outlet cross section. Furthermore, a comparison of the simulated flow velocities of the original and optimal head runners at different inlet flow ratios and temperatures indicates that the optimal head runner flow velocity improves the extrusion quality. Thus, an optimal runner with optimal key factors was manufactured. Test results of the rubber flow state indicated that the flow is regular and that warping disappears. The proposed optimization strategy can be used practically for improving the head runner design, shortening the product development cycle, and reducing the production cost.

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Section: Optimization Analysis and Discussionmentioning

confidence: 99%

Optimal Design for an Extruder Head Runner Based on Response Surface Method and Simulated Annealing Algorithm

Zhou

Jiang

et al. 2018

International Journal of Polymer Science

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“…The numerical methods and systems on which CFD modeling is based are constantly improved, which is why the simulation results are becoming more and more reliable. The use of the numerical method of fluid mechanics also allows optimizing the designed structure, and thus generate the material and energy savings, leading to the reduction of the negative environmental impact of various devices and machines, improvement of their safety and performance as well as shortening the time of preparing a new structure [Małecka et al, 2011, Yang et al, 2011, Alizadeh et al, 2018. From an economic point of view, it is reasonable to use computer simulations, because it allows designing and pre-testing a new structure by calculation, eliminating the need to build many prototypes of the modelled device.…”

Section: Journal Of Ecological Engineeringmentioning

confidence: 99%

Modeling of the Aeration System of a Sequencing Batch Reactor

Zaburko¹,

Głowienka²,

Widomski³

et al. 2020

J. Ecol. Eng.

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The use of modern methods as well as modeling and simulation tools in the design of bioreactors allows for the analysis of the flow phenomena in a short period of time without the need of physical model preparation, and thus for the optimization of existing solutions. The article presents the simulations of the aeration process in an SBRtype bioreactor, realized by means of computational fluid dynamics (CFD) and ANSYS 12.1 software. The subject of the analysis was a diffuser of own design. The Design Modeler 12.1 module was used for the preparation of geometry representing the analyzed design, and the discretization of the continuous domain was carried out with the ANSYS Meshing 12.1 tool. The ANSYS Fluent 6.3 solver was used For model calculations. On the basis of the results obtained from the conducted simulations, it is possible to predict the parameters which will increase efficiency and effectiveness without the need to build a real set of prototype models of aeration systems. The results obtained indicate that an increase in the aeration velocity results in a decrease in the minimum Y-axis velocity for both the mixture and air. The observed differences are caused by the shape of the geometric model and the velocity of the air outlet through the openings, which affects the hydraulic process in the chamber. These processes affect both the amount of oxygen dissolved in the bioreactor and the behavior of the suspension in volume. The turbulence intensity during the aeration process is concerned mainly in the range from 3.9 to 8.7% and is comparable with the average values of turbulence degree obtained by other researchers. The air bubble diameter ranged from 0.3 to 4.5 mm, in the case of aeration velocity 5.68 cm/s, a significant part of the chamber were air bubbles with a diameter of 2.6 to 3.9 mm, i.e. they were not the limit values.

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“…The result is significant savings of resources. Alizadeh and Sadrameli [21], for example, employed central composite design to develop a model for thermal comfort in buildings. In another study, Jung et al [22] used a full factorial design to study the energy storage time of the PCM, and Celik et al [23] studied the effect of different parameters on pressure drop of fluid across perforated plates via the use of designed experiments, while Ramkumar and Ragupathy [24] investigated cooling tower performance using Taguchi method.…”

Section: Introductionmentioning

confidence: 99%

A full 34 factorial experimental design for the low energy building’s external wall

2020

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The low energy building concept is based on improving the building envelope to reduce heating and cooling loads. Improvements in building envelopes depend not only on climatic conditions but also on insulation. In this study, the thermal performance of external walls was studied by using a three-level full factorial statistical experimental design. An opaque wall in low energy buildings was chosen in order to study the effect of selected factors of city (A), orientation (B), insulation location (C), and month of the year (D) on heat loss or gain. A software was used to calculate the ANOVA table. As a result, all three factors of months of the year, city and orientation of the building façade were found to be significant factor effects for heat transfer. Two-factor interactions of AB, AD, BD, and CD were found to be significant. Therefore, the effects of season, location and orientation were successfully shown to be effective parameters.

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Numerical modeling and optimization of thermal comfort in building: Central composite design and CFD simulation

Cited by 65 publications

References 19 publications

Optimal Design for an Extruder Head Runner Based on Response Surface Method and Simulated Annealing Algorithm

Optimal Design for an Extruder Head Runner Based on Response Surface Method and Simulated Annealing Algorithm

Modeling of the Aeration System of a Sequencing Batch Reactor

A full 34 factorial experimental design for the low energy building’s external wall

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