Optimization Of Thermal Systems Research Articles

An efficient yet accurate optimization algorithm for thermal systems integrating heat current method and generalized Benders decomposition

Thermal system optimization is critical for energy conservation but challenging due to highly complicated systems and nonlinear governing equations. Herein, an efficient yet accurate optimization algorithm based on generalized Benders decomposition (GBD) is developed to address this challenge. It decomposes the entire optimization into a subproblem and a master problem. The subproblem performs the system simulation by developing a hybrid simulation method, which uses GBD and fixed-point iteration sequentially for acceleration. The master problem is constructed based on the gradients of the objective with respect to decision variables, where the solution of every iteration gives an approximation of the optimal solution. The two generated problems are iteratively solved in an alternating manner to converge towards the optimal solution. Test results of a supercritical carbon dioxide recompression system indicate that the hybrid simulation method expands the convergence region to ∼167 % which is nearly 4 times larger than that of the fixed-point iteration, and consumes about 10 % calculation time compared with sequential modular method. The optimization algorithm reproduces the results obtained from the genetic algorithm but reduces the calculation time for an order-of-magnitude and has higher stability. The high efficiency and accuracy suggest the proposed algorithm as a powerful system optimization tool.

A contribution to the discussion on the future of thermoeconomics

‘Thermoeconomics’ was introduced and its foundations were laid down by Tribus, Evans and El-Sayed in the late 1950's – early 1960's as a method that combines Thermodynamics (in particular Second-Law quantities) and Economics for the analysis, evaluation and optimization of thermal systems. Since that time, many researchers throughout the world taking various roads helped in developing Thermoeconomics from theoretical point of view and applying it in a variety of systems, thus establishing it as a particular field.Today, questions such as the following may be posed:⁃Is there room for further theoretical development of Thermoeconomics?⁃Are there areas where Thermoeconomics has not been applied yet, however its application would be beneficial?⁃What additional features should Thermoeconomics have, in order to be applied to these areas?⁃Is it possible to introduce other considerations, in addition to thermodynamic and economic, in a more holistic approach? If yes, which are they?The progress to date is presented in brief by mentioning the main methodologies and application areas. Thermoeconomic methods at an early stage of development are mentioned and needs of further development are indicated. Further considerations and application areas of thermoeconomics are mentioned and needs of methodological development are highlighted. The text closes with remarks regarding the aforementioned four questions.

Magneto-nanofluidic thermal transport and irreversibility in semicircular systems with heated wavy bottom under constant fluid volume and cooling surface constraints

PurposeThis study aims to investigate the influence of wall curvature in a semicircular thermal annular system on magneto-nanofluidic flow, heat transfer and entropy generation. The analysis is conducted under constant cooling surface and fluid volume constraints.Design/methodology/approachThe mathematical equations describing the thermo-fluid flow in the semicircular system are solved using the finite element technique. Four different heating wall configurations are considered, varying the undulation numbers of the heated wall. Parametric variations of bottom wall undulation (f), buoyancy force characterized by the Rayleigh number (Ra), magnetic field strength represented by the Hartmann number (Ha) and inclination of the magnetic field (γ) on the overall thermal performance are studied extensively.FindingsThis study reveals that the fluid circulation strength is maximum in the case of a flat bottom wall. The analysis shows that the bottom wall contour and other control parameters significantly influence fluid flow, entropy production and heat transfer. The modified heated wall with a single undulation exhibits the highest entropy production and thermal convection, leading to a heat transfer enhancement of up to 21.85% compared to a flat bottom. The magnetic field intensity and orientation have a significant effect on heat transfer and irreversibility production.Research limitations/implicationsFurther research can explore a wider range of parameter values, alternative heating wall profiles and boundary conditions to expand the understanding of magneto-nanofluidic flow in semicircular thermal systems.Originality/valueThis study introduces a constraint-based analysis of magneto-nanofluidic thermal behavior in a complex semicircular thermal system, providing insights into the impact of wall curvature on heat transfer performance. The findings contribute to the design and optimization of thermal systems in various applications.

Convective heat transport and entropy generation in butterfly-shaped magneto-nanofluidic systems with bottom heating and top cooling

PurposeThe purpose of this study is to carry out a comprehensive analysis of magneto-hydrodynamics (MHD), nanofluidic flow dynamics and heat transfer as well as thermodynamic irreversibility, within a novel butterfly-shaped cavity. Gaining a thorough understanding of these phenomena will help to facilitate the design and optimization of thermal systems with complex geometries under magnetic fields in diverse applications.Design/methodology/approachTo achieve the objective, the finite element method is used to solve the governing equations of the problem. The effects of various controlling parameters such as butterfly-shaped triangle vertex angle (T), Rayleigh number (Ra), Hartmann number (Ha) and magnetic field inclination angle (γ ) on the hydrothermal performance are analyzed meticulously. By investigating the effects of these parameters, the authors contribute to the existing knowledge by shedding light on their influence on heat and fluid transport within butterfly-shaped cavities.FindingsThe major findings of this study reveal that the geometrical shape significantly alters fluid motion, heat transfer and irreversibility production. Maximum heat transfer, as well as entropy generation, occurs when the Rayleigh number reaches its maximum, the Hartmann number is minimized and the angle of the magnetic field is set to 30° or 150°, while the butterfly wings angle or vertex angle is kept at a maximum of 120°. The intensity of the magnetic field significantly controls the heat flow dynamics, with higher magnetic field strength causing a reduction in the flow strength as well as heat transfer. This configuration optimizes the heat transfer characteristics in the system.Research limitations/implicationsFurther research can be expanded on this study by examining thermal performance under different curvature effects, orientations, boundary conditions and additional factors. This can be accomplished through numerical simulations or experimental investigations under various multiphysical scenarios.Practical implicationsThe geometric configurations explored in this research have practical applications in various engineering fields, including heat exchangers, crystallization processes, microelectronic devices, energy storage systems, mixing processes, food processing, air-conditioning, filtration and more.Originality/valueThis study brings value by exploring a novel geometric configuration comprising the nanofluidic flow, and MHD effect, providing insights and potential innovations in the field of thermal fluid dynamics. The findings contribute a lot toward maximizing thermal performance in diverse fields of applications. The comparison of different hydrothermal behavior and thermodynamic entropy production under the varying geometric configuration adds novelty to this study.

Numerical Analysis of Heat Transfer in the Carbon Nanotube-Water Based Nanofluid Flowing Around a Square Cylinder Inside the Channel

The nanofluid with exceptional thermo-physical properties exhibits its significance effect over the convectional fluids for improved heat transfer characteristics. The numerical analysis of heat transfer rate is crucial in many designing and optimizing thermal systems including, heat exchangers, power plants and engines. In this work, numerical investigations carried out for forced convection heat transfer of CNT-water nanofluid over a 45.- inclined square cylinder. The aim of the study to determine the optimum conditions for maximum heat transfer. The value of Reynolds number, CNTs nanoparticles volume fraction, and confinement ratio are consider as input variables, Response Surface Methodology (RSM) is used for optimization to identify the optimal values of the input variables that will result in the best response of heat transfer. The response surface equation is evaluated using the design of the experiments, model fitting, and model optimization. The numerical simulation is performed for different Reynolds numbers (1 ≤ Re ≤ 40), the volume fraction of CNTs (0 ≤ Φ ≤ 0.05), and the confinement ratio (0.1 ≤ λ ≤ 0.5). It was found that the heat transfer enchancement is observed by increasing the Reynolds number, volume fraction and confinement ratio, consequently the temperature gradient increases near the square cylinder. It is also found that the maximum Nusselt number is found at Re = 40, Φ = 0.05 and λ = 0.5. A comparison is also made between the numerical results obtained from the CFD analysis and RSM. Overall, the finding highlighted optimum value of Re, Φ and λ makes the CNTs nanofluid suitable for effective heat transfer applications, aiding in design and thermal system optimization.

Exergoeconomic Analysis of a Mechanical Compression Refrigeration Unit Run by an ORC.

To improve the efficiency of a diesel internal combustion engine (ICE), the waste heat carried out by the combustion gases can be recovered with an organic Rankine cycle (ORC) that further drives a vapor compression refrigeration cycle (VCRC). This work offers an exergoeconomic optimization methodology of the VCRC-ORC group. The exergetic analysis highlights the changes that can be made to the system structure to reduce the exergy destruction associated with internal irreversibilities. Thus, the preheating of the ORC fluid with the help of an internal heat exchanger leads to a decrease in the share of exergy destruction in the ORC boiler by 4.19% and, finally, to an increase in the global exergetic yield by 2.03% and, implicitly, in the COP of the ORC-VCRC installation. Exergoeconomic correlations are built for each individual piece of equipment. The mathematical model for calculating the monetary costs for each flow of substance and energy in the system is presented. Following the evolution of the exergoeconomic performance parameters, the optimization strategy is developed to reduce the exergy consumption in the system by choosing larger or higher-performance equipment. When reducing the temperature differences in the system heat exchangers (ORC boiler, condenser, and VCRC evaporator), the unitary cost of the refrigeration drops by 44%. The increase in the isentropic efficiency of the ORC expander and VCRC compressor further reduces the unitary cost of refrigeration by another 15%. Following the optimization procedure, the cost of the cooling unit drops by half. The cost of diesel fuel has a major influence on the unit cost of cooling. A doubling of the cost of diesel fuel leads to an 80% increase in the cost of the cold unit. The original merit of the work is to present a detailed and comprehensive model of optimization based on exergoeconomic principles that can serve as an example for any thermal system optimization.

Optimizing geometrical structure of a residential parabolic solar collector relying on hydrothermal assessment and second law analysis

Researchers are interested in the optimization of thermal systems due to the rising demand towards renewable and green energy to reduce greenhouse gasses and expenses. To achieve this, the present work aims to conduct the numerical modeling on the residential scale trough solar collector. For this purpose, the lattice Boltzmann method is employed with special treatment for the curved physical boundaries. To enhance the thermal capability of the solar collector, the CuO-water nanofluid is utilized, which its thermal conductivity is estimated using Koo–Kleinstreuer and Li (KKL) model. Furthermore, the Brownian motion effect on the dynamic viscosity is taken into account. In addition, the local and volumetric second law analysis is performed. Besides, the heat line visualization is done to capture the path-line of heat energy within the solar collector. The thermal distribution, flow field, local entropy production (i.e. fluid friction irreversibility and heat transfer irreversibility maps), volumetric entropy generation, Bejan number, and average Nusselt number are the studied items in terms of the governing parameters. The Rayleigh number (103 ≤ Ra ≤ 106), CuO nanoparticle concentration (φ = 0, 0.01, 0.02, 0.03, 0.04) and four structural design of the solar collector (Single-pipe, Double-pipe, Triple-pipe, Quadruple-pipe) are assumed as the governing parameters.

Entropy generation analysis of CNT‐based nanofluid flows induced by a moving plate

AbstractCarbon nanotubes have garnered considerable interest from academia and industry due to their unique properties and potential applications. This study examines fluid flow induced by a plate moving at a constant velocity towards/receding from normal stagnation point flow. The plate's surface is immersed with ethylene glycol and two types of carbon nanotubes: single‐walled and multi‐walled. The Reynolds number, proportional to the plate's velocity, governs the flow. Thermal transport analysis includes Ohmic heating, heat source/sink effects for constant wall temperature and prescribed surface temperature, and entropy generation analysis. Similarity ansatz is used to obtain non‐dimensional ordinary differential equations, and numerical and asymptotic solutions are computed using MATLAB's bvp4c routine (finite difference‐based approach). By varying the relevant parameters, the study interprets the behavior of entropy generation, Bejan number, skin frictions, Nusselt number, flow, and energy profiles. The numerical solutions are observed to match their asymptotic behaviors within an intermediate range of small and large Reynolds numbers for the wall stress parameter. The magnetic parameter produces a resistive force that reduces fluid flow but enhances the system's energy. Moreover, understanding the flow and heat transfer characteristics of CNT‐based nanofluids induced by a moving plate can provide insights into the design and optimization of thermal systems, including efficient heat exchangers used in power generation, chemical, and petrochemical industries.

A novel transfer matrix-based method for steady-state modeling and analysis of thermal systems

Performance analysis and optimization of thermal systems are unprecedentedly crucial in pursuing higher energy efficiency. However, the precise modeling and high-efficiency calculation of modern, complex thermal systems are still challenging. Here we present a transfer matrix-based system modeling method to tackle these challenges. The transfer matrix of heat exchangers is defined to describe the temperature mapping relation between inlet and outlet nodes. Heat-work conversion devices are described by the working fluid temperature variation. The system modeling follows a three-step procedure: (1) building system transfer matrix by aggregating component models; (2) separate given and unknown node temperatures by removing redundant rows and columns in the system transfer matrix; (3) rearrange the reduced system transfer matrix to calculate internal and outlet node temperatures. The constructed system model does not introduce unnecessary simplifications and describes the system’s nonlinearity accurately. The proposed modeling method is first presented and validated on a parallel-series and a multi-loop heat exchanger network. Numerical results with both constant and varying fluid properties confirm the method’s validity. Case studies on three thermodynamic systems further validate the method’s capability and efficiency. The proposed method is finally compared with conventional modeling methods and heat current method to highlight its features and advantages.

Numerical Analysis of Entropy Generation in a Double Stage Triangular Solar Still Using CNT-Nanofluid under Double-Diffusive Natural Convection

The analysis of entropy generation provides valuable information for the design and optimization of thermal systems. Solar stills are used for water desalination and purification. Using renewable energies, they provide a sustainable solution for drinking water supply in remote areas and off-grid situations. This work focuses on the 3D numerical study of entropy generation in a two-stage solar still subjected to the natural double diffusion convection phenomenon in the presence of CNT nanoparticles. The effects of Rayleigh number, buoyancy ratio, and nanofluid concentration on thermal, solutal, and viscous irreversibilities and flow structure were studied. The results show that increasing the buoyancy ratio leads to an increase in thermal and solutal entropy generation. The results of this study also show that total entropy is minimal for positive volume force ratios, N, at a nanoparticle volume fraction of around 3%, and for negative N ratios, at a volume fraction of around 4%.

Preface

This proceeding consists of the peer-reviewed papers from the 3rd International Conference on Sustainable Energy Solutions for a Better Tomorrow (SESBT 2022), which was organized by the School of Mechanical Engineering of Vellore Institute of Technology, Chennai in collaboration with Energy and Sustainability Research Institute of Groningen (ESRIG), University of Groningen, Netherlands on July 23rd and 24th, 2022. For more details about SESBT 2022, please visit www.vitsesbt.com. However, due to the COVID 19 pandemic the conference was held Online. The main objective of SESBT 2022 is to provide a platform for researchers and technocrats from both academic institutions and industries to meet and share cutting-edge developments in the areas of sustainable energy and associated disciplines. This conference also provided an opportunity to exchange research evidence and innovative ideas and also the issues related to sustainable energy. This proceeding will include presentations on the latest research areas such as Carbon Neutrality, Electric & Hybrid Vehicles, Green and Energy Efficient Buildings, Energy Storage, Computational Models for Energy Systems, Advanced Cryo techniques, AI in Energy Systems, Thermal System Optimization and Renewable Energy.The conference was inaugurated on July 23, 2022 by the renowned scientist, Shri.S.Raghupathy, Director – Reactor Design and Technology Group, EIG, Indira Gandhi Centre for Atomic Research, Kalpakkam, India in the presence of Dr.M.Muthuraman, Additional General Manager, Environment Management Group, NTPC Sipat. International Chair, Prof.P.V.Aravind, Full Professor and Chair of Energy Conversion, University of Groningen, Netherlands, Prof.P.C.Sabumon, Dean Academics Research, VIT Chennai and Conference Chair, Dr.K.Annamalai, Dean and Professor, School of Mechanical Engineering, VIT Chennai also felicitated the ceremony.This conference had gathered an excellent group of keynote speakers from across the globe on 12 different topics such as Nuclear Power to Combat Climate Change, On the Design of Latent Thermal Energy Storage for Air conditioning and Space Heating, Thermodynamic Performance Assessment of Solar Chimney Power Plants: Design, Climate and Operational Aspects, Renewable Energy for Sustainable Automotive Engineering, Optimization of a Polymer Electrolyte Membrane Electrolyser – Every Little Helps, Desalination Process based on Renewable Energy, Liquid Cooled Electric Motors for High Performance, Sustainable Composite Materials for Future, Green Hydrogen: Seizing Today’s Opportunities, Chromogenic Materials for Energy Saving, Influence of Reflectors on Photovoltaic Module Efficiency for Sewage Treatment and Wayanad Carbon Neutrality Program.The keynote speakers are Shri.S.Raghupathy from IGCAR, Dr.Simone Mancin from University of Padua, Italy, Dr.Erdem Cuce from Recep Tayyip Erdogan University Rize, Turkey, Prof. M.M.Noor Universiti Malaysia Pahang, Dr.Mamdud Hossain from Robert Gordon University, UK, Prof.K.Srithar from Thiagarajar College of Engineering, Madurai, India, Prof.Satish Kumar from Georgia Tech, USA, Dr.Devendran Thirunavukarasu from ST Advanced Composites Chennai, India, Prof.S.Vasudevan from CECRI, Dr.Alessandro from Politechnico di bari, Italy, Prof.Mohd Zulkifly Abdullah from University Sains Malaysia, and Dr.P.V.Aravind from University of Groningen. In addition, a special talk on Sustainability with nuclear power – small modular reactor by Mr.Aniket Joshi from The Open University, UK was arranged.This year, SESBT 2022 received more than 200 technical articles from across the globe. A total of 154 research articles were shortlisted and 140 research articles were presented. Based on the scope of the IOP Conference Series: Earth and Environmental Science (EES) and submission of undertaking by authors, only 35 papers were uploaded in Morressier platform. Upon completion of the single blind peer review process, 16 papers were accepted for publication in IOP Conference Series: Earth and Environmental Science (EES). The evaluation of all the papers was performed based on the reports from anonymous reviewers.List of SESBT 2022 – Committee Members, Advisory Committee, Conference Chairs, International Expert Committee, Executive Committee, Technical Committee, Organizing Committee, Editors are available in the pdf.

Search for an Optimum in Thermal Systems and Processes

Abstract This paper considers the optimization of thermal systems and processes, which are of interest in a wide range of practical applications, on the basis of mathematical and numerical modeling as well as experimental data. Many complexities, such as property variations, complicated regions, combined transport mechanisms, chemical reactions, and intricate boundary conditions, typically arise in these systems, making experimentation and numerical simulation quite challenging. Consequently, many studies have obtained detailed results on the processes without going further into system design. Also, many important systems have not been optimized for best performance or output. This paper focuses on the practical aspects of obtaining an optimum in thermal systems and processes. Of particular interest are validation of the model and linking the simulation with system performance, design, and optimization. Optimization is considered both for the operating conditions as well as for the hardware of the system. Starting with a feasible domain that leads to an acceptable design, different optimization strategies may be employed. Both deterministic conditions and those with uncertainty are of interest and are outlined. Of particular interest is multiobjective optimization, since most thermal systems involve several important objectives, such as heat transfer rate and pressure in electronic cooling systems and product quality and production rate in manufacturing systems. The optimization is often a constrained one due to limitations on materials, cost, and operating conditions that determine the acceptable domain. Nature is replete with interesting examples where constrained multiobjective optimization is employed by various living creatures for food, safety, mobility, and other aspects of survival. A study of such natural phenomena can also be used in technology as we seek an optimum. Such nature-inspired optimization is discussed. Overall, the focus is on realistic and practical approaches that may be adopted to optimize thermal systems and processes to minimize energy consumption, enhance productivity, reduce environmental impact, improve heat transfer and achieve other objectives.

Exergy analysis and development of flat plate solar collectors: A Review

The exergy comes from the need to find some energy of a system that can be quantified to take advantage of its mechanical, electrical or any other type of work, it is limited in terms of investment of time and research, due to this fact, the need arises to be able to innovate with data collection on the exergy calculation models developed in flat solar collectors. In the present research, a search of the literature regarding the development of exergy in flat plate solar collectors was carried out, to then analyze and determine forty innovative articles in the last six years, which were reflected in a data matrix in the The formulas and factors that define the exergy are presented, as well as the theoretical designs of the collector and working fluids used in flat solar collectors. With the results of the table, a broad panorama of current data is obtained, on the most used in the formulation of exergetic efficiency, which stands out as an essential tool for the design, analysis and optimization of thermal systems.

Experimental study on nucleate pool boiling heat transfer characteristics of R32 + R1234yf binary mixtures

• Boiling heat transfer deteriorated most at x R32 = 0.4277 for different heat fluxes. • Mass transfer resistance weakened the bubble coalescences at high heat flux. • Phase equilibria and physical property together affected heat transfer of mixtures. • The accuracies of two existing correlations were improved to within 5.6%. Although R1234yf is a new environmentally-friendly refrigerant with low GWP, its thermal performance is inferior to that of conventional refrigerants. Mixing R1234yf with R32 can overcome the respective shortcomings of each component. Therefore, understanding the pool boiling heat transfer characteristics of R32 + R1234yf mixtures is of great importance to the design of heat exchangers and the optimization of thermal systems. This study carried out the pool boiling experiments of R32, R1234yf, and their binary mixtures. The boiling curves, heat transfer coefficients, and bubble images of pure and mixed refrigerants were obtained. The results showed that the addition of R32 effectively improved the heat transfer performance of R1234yf. Meanwhile, the mixing effect weakened the bubble coalescence and enhanced the heat transfer performance under high heat flux. It was found that the heat transfer deterioration of mixtures was not only influenced by the vapor–liquid phase equilibrium but also related to the nonlinearly varying physical properties. Based on the experimental data, eleven widely used correlations for boiling heat transfer coefficient of binary mixtures were analyzed with two selected and further modified. The prediction performances of the modified correlations improved significantly, with the mean absolute relative deviation (MARD) reducing to 5.16% and 5.53%, respectively.

EXPERIMENTAL METHODOLOGY FOR THE STUDY OF NATURAL CONVECTION ON FLAT AND CORRUGATED PLATES

Natural convection is present in the most different Thermal Engineering systems, such as solar collectors, electric furnaces, electronic equipment cooling, lubrication, thermal comfort projects in buildings, etc. In the last decade, the number of research on natural convection heat transfer has increased considerably, especially in the areas of physical-numerical modeling and validation, experimental construction and efficiency optimization of thermal systems, and related technologies. This work presents an experimental methodology for studying natural convection on flat and corrugated plates. The design and construction stages of the experimental apparatus, data processing and analysis, physical-mathematical modeling and uncertainty analysis were extensively explored. The applications and extensions of the proposed methodology were discussed in the numerical-experimental validation of physical-numerical modeling methodologies, design and optimization of the experimental apparatus and also of measuring instruments and, finally, in sensitivity analysis studies to reduce the propagation of uncertainties. The limitations of the proposed methodology were discussed, pointing out suggestions for future work.

Integral identification of fluid specific heat capacity and heat transfer coefficient distribution in heat exchangers based on multiple-case joint analysis

Estimating detailed heat transfer characteristics efficiently is crucial for analysis and optimization of thermal systems. However, there still lacks accurate methods for identifying local parameters in heat exchangers, mainly due to the hindrance of sensor placement. This work proposes a method for identifying fluid specific heat capacity and heat transfer coefficient distribution in heat exchangers from lumped datasets consisting of multiple working cases, which only include mass flow rates of fluids and their inlet and outlet temperatures. Dividing the fluid temperature range in the dataset and combining energy conservation equations of all cases gives a matrix equation. Solving it with the least squares method gives the specific heat capacity distribution. Combining this method and reinforcement learning offers a two-stage strategy for identifying the heat transfer coefficient distribution. The first stage gives an approximation of the distribution, and the second stage refines the approximation by considering secondary effects such as radial property variation. A heat transfer process between supercritical carbon dioxide (sCO2) and water is used to validate the method. Results show that relative identification errors of sCO2 specific heat capacity and heat transfer coefficient distributions are within 3.1% and 6.3%, respectively. The satisfying accuracy proves the proposed method’s efficacy.

An online parameter identification and real-time optimization platform for thermal systems and its application

Real-time performance optimization of thermal systems is crucial for energy conservation but also challenging because of the high system complexity and time sensitivity. Herein, an online parameter identification and real-time optimization platform for thermal systems is developed, and a gas-steam combined cycle cogeneration system is used to demonstrate its capability. The platform integrates data collection, parameter identification, system simulation, and real-time optimization modules. The data preprocessing and parameter identification modules collects real-time operation parameters for optimization. The system simulation module applies the heat current method to model the cogeneration system precisely, and a high-efficiency simulation procedure is proposed using the hierarchical and categorized (H&C) algorithm. The system optimization module introduces the artificial neural network technology to ensure the response time of real-time optimization. Meanwhile, the H&C algorithm and genetic algorithm are combined to update the database to improve the optimization performance gradually. The platform is first validated on three typical conditions. It is further deployed at a power plant, where a field test is conducted for the practical verification. Field test results show that the standard coal consumption of the cogeneration system could be reduced by 0.415 g/kWh by using the platform, which proves its practicability.

Preface

This proceeding consists of the peer-reviewed papers from the 2nd International Conference on Sustainable Energy Solutions for a Better Tomorrow (SESBT 2021), which was organized by the School of Mechanical Engineering of Vellore Institute of Technology, Chennai on July 23rd and 24th, 2021. For more details about SESBT 2021, please visit www.vitsesbt.com. However, due to the COVID 19 pandemic the conference was held Online. The main objective of SESBT 2021 is to provide a platform for researchers and technocrats from both academic institutions and industries to meet and share cutting-edge developments in the areas of sustainable energy and associated disciplines. This conference also provided an opportunity to exchange research evidence and innovative ideas and also the issues related to sustainable energy. This proceeding will include presentations on the latest research areas such as Carbon Neutrality, Electric & Hybrid Vehicles, Green and Energy Efficient Buildings, Sustainable Computing, Energy Storage, Computational Models for Energy Systems, Advanced Cryotechniques, AI in Energy Systems, Thermal System Optimization and Renewable Energy.The conference was inaugurated on July 23, 2021 by the renowned scientist, Dr. A.K. Tyagi, Associate Director (Chemistry Group), Bhabha Atomic Research Centre, Mumbai in the presence of Guest of Honour Dr. Santhoji Katare, Technical Leader and General Manager, Ford Motor Company, Chennai. International Chair, Prof. P.V. Aravind, Full Professor and Chair of Energy Conversion, University of Groningen, Netherlands, Prof. P.C. Sabumon, Dean Sponsored Research, VIT Chennai and Conference Chair, Dr. R. Sivakumar, Dean and Professor, School of Mechanical Engineering, VIT Chennai also facilitated the ceremony.List of Sesbt 2021 - Committee Members is available in this pdf.

Numerical modeling of entropy production in Al2O3/H2O nanofluid flowing through a novel Bessel-like converging pipe

Optimization of thermal systems requires higher heat transfer rate and lower entropy production rate. The review of literature shows that there are limited works on entropy production rate of nanofluids flowing through a converging pipe as the available ones only considered entropy production rate in a linear converging pipe. In this study, a 2D-computational fluid dynamic model is set up to investigate entropy production rate of Al2O3 nanofluid flowing through novel Bessel-like convergent pipes in laminar flow regime. The effect of Reynolds number $$\left( {300 \le {\text{Re}} \le 1200} \right)$$ , nanoparticle concentration $$\left( {0 \le \varphi \le 0.1} \right)$$ , and convergent index $$\left( {n = 0 - 3} \right)$$ on the entropy production rate, heat transfer effectiveness number, and irreversibility distribution ratio were considered. The results obtained revealed that increase in convergent index enhances viscous entropy production rate, but diminishes thermal entropy production rate. For instance, the reduction in thermal entropy production rate at $${\text{Re}} = 900$$ between pipe corresponds to $$n = 0$$ and $$n = 3$$ was 51.98% while the increase in viscous entropy production rate was 753.65%. Furthermore, a new correlation was developed using response surface methodology to estimate the entropy production rate as a function of the Reynolds number, nanoparticle concentration, and convergence index. The overall result shows that the usage of converging pipe in place of straight pipe is more advantageous.

Optimization of energy systems using the concept of balance in the nature.

In this paper, a concept of balance is used to improve the important parameters of the thermal systems. In fact, using this concept give the designer to propose some new configuration which is more efficient. To show the benefit of this concept, firstly, the proposed balancing method is introduced for a simple case study after that its application is used in optimization of thermal systems. In this regard, to achieve the better optimal results in each problem, the unbalanced factors are detected and some solutions are presented to reduce the system unbalancing. Three case studies including Rankine cycle, plate fin heat exchanger, and double pipe heat exchanger are discussed and optimized to show the benefits of this method.