Numerical Simulation and Optimization in Thermal Processes

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Chemical Processes and Systems".

Deadline for manuscript submissions: 30 October 2024 | Viewed by 1189

Special Issue Editors


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Guest Editor
School of Safety Science and Engineering, Changzhou University, Changzhou 213164, China
Interests: thermokinetic; thermal analysis; thermal safety; thermal runaway; Li-ion battery safety; water mist; chemical engineering safety
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
College of Safety Science and Engineering, Nanjing Tech University, Nanjing 211816, China
Interests: thermal safety; thermal runaway assessment; gas/dust explosion prevention and control; quantitative risk assessment technology; hydrogen energy safety; synthesis and application of solid hydrogen storage materials
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Numerical simulation and optimization techniques have revolutionized the field of thermal processes, enabling engineers and researchers to analyze, design, and optimize complex thermal systems efficiently. This Special Issue explores the latest advancements in numerical simulation and optimization methods applied to thermal processes. From computational fluid dynamics (CFD) and finite element analysis (FEA) to multi-objective optimization algorithms and machine-learning-based approaches, researchers are continuously developing innovative methodologies to enhance thermal system performance. By accurately modeling heat transfer, fluid flow, and thermal behavior, engineers can optimize parameters, improve energy efficiency, and ensure safe operation.

This Special Issue aims to showcase the latest advancements in numerical simulation and optimization techniques applied to thermal processes. Whether your research focuses on computational fluid dynamics (CFD), finite element analysis (FEA), multi-objective optimization algorithms, or machine learning-based approaches, we encourage you to share your valuable insights and findings. By contributing to this Special Issue, you will contribute to the advancement of thermal processes, optimizing parameters, improving energy efficiency, and ensuring safe operation. We look forward to receiving your contributions and fostering meaningful discussions in this important field.

Dr. An-Chi Huang
Prof. Dr. Yun-Ting Tsai
Guest Editors

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Keywords

  • numerical simulation
  • CFD
  • FEA
  • machine learning
  • thermal processes

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Published Papers (1 paper)

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Research

19 pages, 9912 KiB  
Article
A Feasibility Study for the Hot-Air-Assisted Reflow Soldering Process Based on Computational Fluid Dynamics
by Natcha Kanjad, Chanapat Chanbandit and Jatuporn Thongsri
Processes 2024, 12(10), 2142; https://doi.org/10.3390/pr12102142 - 1 Oct 2024
Viewed by 598
Abstract
In hard disk drive (HDD) manufacturing, a reflow soldering process (RSP) employs heat generated at the welding tip (WT) to bond tiny electrical components for assembling an HDD. Generally, the heat was generated by an electric current applied to the WT. This article [...] Read more.
In hard disk drive (HDD) manufacturing, a reflow soldering process (RSP) employs heat generated at the welding tip (WT) to bond tiny electrical components for assembling an HDD. Generally, the heat was generated by an electric current applied to the WT. This article reports a feasibility study of using hot air based on computational fluid dynamics (CFD), a choice to assist heat generation. First, the WT and hot air tube (HAT) prototypes were designed and created. The HAT is a device that helps to supply hot air directly to generate heat at the WT. Then, the experiment was established to measure the temperature (T) supplied by the hot air. The measure results were employed to validate the CFD results. Next, the prototype HAT was used to investigate the T generated at the WT by CFD. The comparison revealed that the T measured by the experiment was in the 106.2 °C–133.5 °C range and that the CFD was in the 107.3 °C–136.6 °C range. The maximum error of the CFD results is 2.3% compared to the experimental results, confirming the credibility of the CFD results and methodology. The CFD results revealed that the operating conditions, such as WT, HAT designs, hot air inlet velocity, and inlet temperature, influence the T. Last, examples of suitable operating conditions for using hot air were presented, which confirmed that hot air is a proper choice for a low-temperature RPS. Full article
(This article belongs to the Special Issue Numerical Simulation and Optimization in Thermal Processes)
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