Po Ting Lin, Hae Chang Gea, Yogesh Jaluria^*

Frontiers in Heat and Mass Transfer, Vol.1, No.1, pp. 1-20, 2010, DOI:10.5098/hmt.v1.1.3003

Abstract Thermal systems play significant roles in the engineering practice and our lives. To improve those thermal systems, it is necessary to model and optimize the design and the operating conditions. More importantly, the design uncertainties should be considered because the failures of the thermal systems may be very dangerous and produce large loss. This review paper focuses on a systematic strategy of modeling and optimizing of the thermal systems with the considerations of the design uncertainties. To demonstrate the proposed strategy, one of the complicated thermal systems, Chemical Vapor Deposition (CVD), is simulated, parametrically modeled, and optimized. The operating conditions,… More >

Jiarui Wu¹, Yuzhen Kang², Junxiao Feng^1,*

Energy Engineering, Vol.120, No.12, pp. 2783-2802, 2023, DOI:10.32604/ee.2023.029358

Abstract To enhance system stability, solar collectors have been integrated with air-source heat pumps. This integration facilitates the concurrent utilization of solar and air as energy sources for the system, leading to an improvement in the system's heat generation coefficient, overall efficiency, and stability. In this study, we focus on a residential building located in Lhasa as the target for heating purposes. Initially, we simulate and analyze a solar-air source heat pump combined heating system. Subsequently, while ensuring the system meets user requirements, we examine the influence of solar collector installation angles and collector area on the performance of the solar-air… More >

Changyong Chu^1,2,*, Chengfang Yin¹, Shuo Shi¹, Shaohui Su¹, Chang Chen¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1413-1434, 2023, DOI:10.32604/cmes.2022.022395

Abstract To enhance the efficiency of system modeling and optimization in the conceptual design stage of satellite parameters, a system modeling and optimization method based on System Modeling Language and Co-evolutionary Algorithm is proposed. At first, the objectives of satellite mission and optimization problems are clarified, and a design matrix of discipline structure is constructed to process the coupling relationship of design variables and constraints of the orbit, payload, power and quality disciplines. In order to solve the problem of increasing non-linearity and coupling between these disciplines while using a standard collaborative optimization algorithm, an improved genetic algorithm is proposed and… More > Graphic Abstract

Weixing Zhang, Chunxia He^*

Journal of Renewable Materials, Vol.10, No.12, pp. 3263-3283, 2022, DOI:10.32604/jrm.2022.020516

Abstract With the exponential growth of the computing power, machine learning techniques have been successfully used in various applications. This paper intended to predict and optimize the shear strength of single lap cassava starchbased adhesive joints for comparison with the application of artificial intelligence (AI) methods. The shear strength was firstly determined by the experiment with three independent experimental variables (starch content, NaOH concentration and reaction temperature). The analysis of range (ANORA) and analysis of variance (ANOVA) were applied to investigate the optimal combination and the significance of each factor for the shear strength based on the orthogonal experiment. The performance… More >

A. F. Mohamed^1,2, J. Abu Alsoud¹, Mujahed Al-Dhaifallah^3,*, Hegazy Rezk^4,5, Mohamed K. Hassan^1,6

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 71-83, 2022, DOI:10.32604/cmc.2022.019257

Abstract In power plants, flue gases can cause severe corrosion damage in metallic parts such as flue ducts, heat exchangers, and boilers. Coating is an effective technique to prevent this damage. A robust fuzzy model of the surface roughness (R_a and R_z) of flue gas ducts coated by protective composite coating from epoxy and nanoparticles was constructed based on the experimental dataset. The proposed model consists of four nanoparticles (ZnO, ZrO₂, SiO₂, and NiO) with 2%, 4%, 6%, and 8%, respectively. Response surface methodology (RSM) was used to optimize the process parameters and identify the optimal conditions for minimum surface roughness… More >