Mathematical modelling of heat transfer performance of heat exchanger using nanofluids. (2023)

• Record Type: Book
• Further Information: Note: Prashant Maheshwary, Chandrahas C. Handa, Neetu Gyanchandani, Pramod Belkhode.
• Authors: Maheshwary, Prashant; Handa, Chandrahas C; Gyanchandani, Neetu; Belkhode, Pramod
• Contents: Chapter 1; Nanofluids 1.1 Nanotechnology; 1.2 Nanomaterials; 1.3 Applications of Nanomaterials; 1.4 Nanofluids; 1.5 Compact Heat Exchangers; 1.6 Heat Transfer Enhancement through Nanofluids; 1.7 Improvement in Heat Exchanger Performance; 1.8 Application of Nanofluid in Cooling Systems; 1.9 Mathematical Modelling Chapter 2; Concept of Experimental Data-Based Modelling 2.1 Introduction; 2.2 Nanofluid for Heat Transfer; 2.3 Brief Methodology of Theory of Experimentation; 2.4 Methods of Experimentation; Chapter 3; Design of Experimentation 3.1 Introduction; 3.2 Design of Experiment – Methodical Approach; 3.3 Experimental Setup and Procedure; 3.4 Two-Wire Method; 3.5 Radiator as a Heat Exchanger: Experimental Procedure; 3.6 Design of Instrumentation for Experimental Setup; 3.7 Components of Instrumentation Systems; 3.8 Identification of Variables in Phenomenon; 3.9 Mathematical Relationship for Heat Transfer Phenomena; 3.10 Formation of Pi Terms for Dependent & Independent; 3.11 Reduction of Variables by Dimensional Analysis; 3.12 Plan for Experimentation; 3.13 Experimental Observations; 3.14 Sample Selection Chapter 4; Mathematical Models 4.1 Introduction; 4.2 Model Classification; 4.3 Formulation of Experimental Data-Based Models (Two-Wire Method); 4.4 Sample Calculations of Pi Terms Chapter 5; Analysis using SPSS Statistical Packages Software 5.1 Introduction; 5.2 Developing the SPSS Model for Individual Pi Terms; 5.3 SPSS Output for Thermal Conductivity Kϕ (Concentration); 5.4 SPSS Output for Thermal Conductivity Kt (Size); 5.5 SPSS Output for Thermal Conductivity Ks (Shape); 5.6 SPSS Output for πD1 (Temperature Difference, ΔT); 5.7 SPSS Output for πD2 (Heat Flow, Q); 5.8 SPSS Output for πD3 (Heat Transfer Coefficient, h) Chapter 6; Analysis of Model using Artificial Neural Network Programming; 6.1 Introduction; 6.2 Procedure for Artificial Neural Network Phenomenon; 6.3 Performance of Models by ANN; 6.3.1 ANN using SPSS o/p for Thermal Conductivity Kϕ; 6.3.2 ANN using SPSS o/p for Thermal Conductivity Kt (Size); 6.3.3 ANN using SPSS o/p for Thermal Conduct. Ks (Shape); 6.3.4 ANN using MATLAB Program for πD1 (Temp. Diffe., ΔT); 6.3.5 Comparison of Various Model Values Chapter 7; Analysis of the Indices of Model 7.1 Introduction; 7.2 Analysis of the Model for Dependent Pi Term πD1 (Kϕ); 7.3 Analysis of the Model for Dependent Pi Term πD2 (Kt); 7.4 Analysis of the Model for Dependent Pi Term πD3 (Ks); 7.5 Analysis of the Model for Dependent Pi Term πD1 (ΔT); 7.6 Analysis of the Model for Dependent Pi Term πD2 (Q); 7.7 Analysis of the Model for Dependent Pi Term πD3 (h) Chapter 8; Optimization and Sensitivity Analysis; 8.1 Introduction; 8.2 Optimization of the Models; 8.3 Sensitivity Analysis for Two-Wire Method; 8.4 Estimation of Limiting Values of Response Variables; 8.5 Performance of the Models; 8.6 Reliability of Models; 8.7 Coefficient of Determinants R2 for Two-Wire Method Chapter 9; Interpretation of the Simulation; 9.1 Interpretation of Independent Variables vs. Response Variables after Optimization; 9.2 Interpretation of Temperature Difference against the Mass Flow Rate; 9.3 Interpretation of Reliability and Coefficient of Determinant; 9.4 Interpretation of Mean Error of Models Corresponding to Response Variables
• Edition: 1st
• Publisher Details: Boca Raton : CRC Press
• Publication Date: 2023
• Extent: 1 online resource (134 pages), illustrations (black and white, and colour)
• Subjects: 621.4025; Heat exchangers -- Mathematical models; Working fluids; Nanofluids; Heat -- Transmission -- Mathematical models
• Languages: English
• ISBNs: 9781000937145
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
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