Development of an expert system based on fuzzy logic as support for heat pipes design

Luis Alonso Betancur Arboleda, Pamela Hulse, L. Krambeck, J. Ascanio-Villabona, O. Lengerke, Camilo Sandoval
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引用次数: 0

Abstract

Heat pipe design and selection require specialist knowledge due to numerous possible combinations and restrictions that should be taken into account. The general objective of this work is to design a Specialist System that assists future engineers in material and working fluid selection for a suitable heat pipe application, based on the technical operating requirements. The methodology consisted of a qualitative perspective through interviews with two specialist engineers in the heat pipes area. The resulting information from the interviews was organized into a library, working as a source for the specialist system. In addition, several books from the literature completed the information in the library. Based on the operating conditions and the provided library, the program recommends suitable materials and working fluids and the necessity of porous media for the application, similar to a consult with a heat pipe specialist. The new expert system can be a tool for researchers and engineers in heat pipe design as passive control systems, providing more suitable solutions for each application
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基于模糊逻辑的热管设计支持专家系统的开发
热管的设计和选择需要专业知识,因为需要考虑到许多可能的组合和限制。这项工作的总体目标是设计一个专家系统,帮助未来的工程师根据技术操作要求选择合适的热管应用的材料和工作流体。该方法包括通过采访热管领域的两名专业工程师进行定性分析。从访谈中得到的信息被组织成一个图书馆,作为专家系统的来源。此外,还有几本来自文献的书,完成了图书馆的信息。根据操作条件和提供的库,程序建议适合的材料和工作流体以及应用的多孔介质的必要性,类似于咨询热管专家。新的专家系统可以作为热管被动控制系统的研究人员和工程师的工具,为每个应用提供更合适的解决方案
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来源期刊
CiteScore
1.90
自引率
0.00%
发文量
140
审稿时长
7 weeks
期刊介绍: *Industrial Engineering: 1 . Ergonomics 2 . Manufacturing 3 . TQM/quality engineering, reliability/maintenance engineering 4 . Production Planning 5 . Facility location, layout, design, materials handling 6 . Education, case studies 7 . Inventory, logistics, transportation, supply chain management 8 . Management 9 . Project/operations management, scheduling 10 . Information systems for production and management 11 . Innovation, knowledge management, organizational learning *Mechanical Engineering: 1 . Energy 2 . Machine Design 3 . Engineering Materials 4 . Manufacturing 5 . Mechatronics & Robotics 6 . Transportation 7 . Fluid Mechanics 8 . Optical Engineering 9 . Nanotechnology 10 . Maintenance & Safety *Computer Science: 1 . Computational Intelligence 2 . Computer Graphics 3 . Data Mining 4 . Human-Centered Computing 5 . Internet and Web Computing 6 . Mobile and Cloud computing 7 . Software Engineering 8 . Online Social Networks *Electrical and electronics engineering 1 . Sensor, automation and instrumentation technology 2 . Telecommunications 3 . Power systems 4 . Electronics 5 . Nanotechnology *Architecture: 1 . Advanced digital applications in architecture practice and computation within Generative processes of design 2 . Computer science, biology and ecology connected with structural engineering 3 . Technology and sustainability in architecture *Bioengineering: 1 . Medical Sciences 2 . Biological and Biomedical Sciences 3 . Agriculture and Life Sciences 4 . Biology and neuroscience 5 . Biological Sciences (Botany, Forestry, Cell Biology, Marine Biology, Zoology) [...]
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