
Mathematical Modelling of Heat Transfer Performance of Heat Exchanger using Nanofluids
- 136 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Mathematical Modelling of Heat Transfer Performance of Heat Exchanger using Nanofluids
About this book
The book presents a detailed discussion of nanomaterials, nanofluids and application of nanofluids as a coolant to reduce heat transfer. It presents a detailed approach to the formulation of mathematical modelling applicable to any type of case study with a validation approach and sensitivity and optimization.
- Covers the aspects of formulation of mathematical modelling with optimization and sensitivity analysis
- Presents a case study based on heat transfer improvement and performs operations using nanofluids
- Examines the analysis of experimental data by the formulation of a mathematical model and correlation between input data and output data
- Illustrates heat transfer improvement of heat exchangers using nanofluids through the mathematical modelling approach
- Discusses applications of nanofluids in cooling systems
This book discusses the aspect of formulation of mathematical modelling with optimization and sensitivity analysis. It further presents a case study based on the heat transfer improvement and performing operations using nanofluids. The text covers sensitivity analysis and analysis from the indices of the model. It also discusses important concepts such as nanomaterials, applications of nanomaterials, and nanofluids. It will serve as an ideal reference text for senior undergraduate, and graduate students in fields including mechanical engineering, chemical engineering, aerospace engineering, industrial engineering, and manufacturing engineering.
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Information
Table of contents
- Cover
- Half Title
- Title
- Copyright
- Contents
- Preface
- Author Bios
- 1 Nanofluids
- 2 Concept of Experimental Data-Based Modelling
- 3 Design of Experimentation
- 4 Mathematical Models
- 5 Analysis using SPSS Statistical Packages Software
- 6 Analysis of Model using Artificial Neural Network Programming
- 7 Analysis from the Indices of the Model
- 8 Optimization and Sensitivity Analysis
- 9 Interpretation of the Simulation
- References
- Index