Abstract:In the present work, a multiobjective heat transfer search (MOHTS) algorithm is proposed and investigated for thermo‐economic and thermodynamic optimization of a plate–fin heat exchanger (PFHX). Heat exchanger effectiveness and total annual cost (TAC) are considered as thermo‐economic objective functions. Similarly, entropy generation rate and heat exchanger effectiveness are considered as thermodynamic objective functions. Six design variables including flow length of cold and hot streams, no flow length, fin… Show more
“…These noticeable advantages of the HTS algorithm are observed at the cost of computation time. HTS has been successfully applied to different benchmarking problems pertaining to different fields [27,28,29,30,31]. However, to the best of the authors’ knowledge, no study has been reported on the application of HTS for manufacturing problems.…”
Nitinol, a shape-memory alloy (SMA), is gaining popularity for use in various applications. Machining of these SMAs poses a challenge during conventional machining. Henceforth, in the current study, the wire-electric discharge process has been attempted to machine nickel-titanium (Ni55.8Ti) super-elastic SMA. Furthermore, to render the process viable for industry, a systematic approach comprising response surface methodology (RSM) and a heat-transfer search (HTS) algorithm has been strategized for optimization of process parameters. Pulse-on time, pulse-off time and current were considered as input process parameters, whereas material removal rate (MRR), surface roughness, and micro-hardness were considered as output responses. Residual plots were generated to check the robustness of analysis of variance (ANOVA) results and generated mathematical models. A multi-objective HTS algorithm was executed for generating 2-D and 3-D Pareto optimal points indicating the non-dominant feasible solutions. The proposed combined approach proved to be highly effective in predicting and optimizing the wire electrical discharge machining (WEDM) process parameters. Validation trials were carried out and the error between measured and predicted values was negligible. To ensure the existence of a shape-memory effect even after machining, a differential scanning calorimetry (DSC) test was carried out. The optimized parameters were found to machine the alloy appropriately with the intact shape memory effect.
“…These noticeable advantages of the HTS algorithm are observed at the cost of computation time. HTS has been successfully applied to different benchmarking problems pertaining to different fields [27,28,29,30,31]. However, to the best of the authors’ knowledge, no study has been reported on the application of HTS for manufacturing problems.…”
Nitinol, a shape-memory alloy (SMA), is gaining popularity for use in various applications. Machining of these SMAs poses a challenge during conventional machining. Henceforth, in the current study, the wire-electric discharge process has been attempted to machine nickel-titanium (Ni55.8Ti) super-elastic SMA. Furthermore, to render the process viable for industry, a systematic approach comprising response surface methodology (RSM) and a heat-transfer search (HTS) algorithm has been strategized for optimization of process parameters. Pulse-on time, pulse-off time and current were considered as input process parameters, whereas material removal rate (MRR), surface roughness, and micro-hardness were considered as output responses. Residual plots were generated to check the robustness of analysis of variance (ANOVA) results and generated mathematical models. A multi-objective HTS algorithm was executed for generating 2-D and 3-D Pareto optimal points indicating the non-dominant feasible solutions. The proposed combined approach proved to be highly effective in predicting and optimizing the wire electrical discharge machining (WEDM) process parameters. Validation trials were carried out and the error between measured and predicted values was negligible. To ensure the existence of a shape-memory effect even after machining, a differential scanning calorimetry (DSC) test was carried out. The optimized parameters were found to machine the alloy appropriately with the intact shape memory effect.
“…Detailed pseudocode of the HTS algorithm is given in Figure . Few application of HTS algorithm for the optimization of engineering system are available in the literature …”
Recent developments in nanotechnology provided an opportunity to solve many complex problems in the field of energy. Performance investigation of the nanoscale thermal cycles can prove crucial in the development of efficient and less polluting energy system. Due to the influence of boundary phenomenon and quantum degeneracy effects, a nanoscale engine performs according to statistical quantum thermodynamics instead of classical thermodynamics. In this study, a nanoscale Stirling engine operating on an ideal Maxwell-Boltzmann gas is investigated for multiobjective optimization.Optimization problem of Stirling cycle is formed considering the thermal efficiency, ecological coefficient of performance and entropy generation. An application example of a nanoscale Stirling engine is presented and solved using Heat Transfer Search algorithm. Maxwell-Boltzmann gas restricted in a finite domain is studied and the effect of different parameters, such as surface area ratio, volume ratio, and temperature ratio of the domain, is investigated. Sensitivity analysis is carried out to identify the effect of design variables on the performance parameters. Further, influence of the source temperature and the number of particles of working fluid on the objective functions is studied and presented.
“…The MOHTS algorithm uses Ɛ ‐dominance based updating method to check the domination of the solution in the archive. Extended details about MOHTS algorithm is documented in the references …”
Section: Heat Transfer Search (Hts) Algorithmmentioning
The present work focused on the comparative analysis of organic Rankine cycle (ORC) operated with nanoparticles. The effect of CuO and Al2O
3 nanoparticles synthesized with water and circulated within heat exchangers are examined. Thermal efficiency and levelized energy cost (LEC) of the nanofluid based ORC are evaluated simultaneously in the present work. The optimization problem of ORC is formed and solved using heat transfer search algorithm. Operating parameters of the nanofluid based ORC such as pinch point temperature difference of heat exchangers, evaporation pressure, the mass flow rate of refrigerant, and concentration of nanoparticles are investigated in the optimization study. Further, the effect of turbine ratio, heat source temperature, and mass flow rate of heat source fluid on CuO and Al
2O
3 based ORC is explored and discussed. It was observed that a total variation of 35.2% was obtained at the cost of 3.5% variation in LEC between extreme design points. The maximum thermal efficiency of 19.3% and 19.32% can be obtained with CuO and Al
2O
3 with 2.616 and 2.62 $/kWh, respectively. Comparative results reveal that CuO based ORC shows dominance in terms of economic performance over Al
2O
3 based ORC for any given value of the thermal efficiency.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.