Mathematical Modelling of Heat Transfer Performance of Heat Exchanger using Nanofluids

Title: Mathematical Modelling of Heat Transfer Performance of Heat Exchanger using Nanofluids
Author: Chandrahas C. Handa, Neetu Gyanchandani, Pramod Belkhode, Prashant Maheshwary
ISBN: 1032478756 / 9781032478753
Format: Hard Cover
Pages: 148
Publisher: CRC Press
Year: 2023
Availability: 2 to 3 weeks.

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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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Preface

Chapter 1 : Nanofluids
Chapter 2 : Concept of Experimental Data-Based Modelling
Chapter 3 : Design of Experimentation
Chapter 4 : Mathematical Models
Chapter 5 : Analysis using SPSS Statistical Packages Software
Chapter 6 : Analysis of Model using Artificial Neural Network Programming
Chapter 7 : Analysis of the Indices of Model
Chapter 8 : Optimization and Sensitivity Analysis
Chapter 9 : Interpretation of the Simulation

Index