scholarly journals Performance Optimizations with Single-, Bi-, Tri-, and Quadru-Objective for Irreversible Diesel Cycle

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 826
Author(s):  
Shuangshuang Shi ◽  
Lingen Chen ◽  
Yanlin Ge ◽  
Huijun Feng
Keyword(s):  
Objective Function ◽  
Power Density ◽  
Power Output ◽  
Thermal Efficiency ◽  
Maximum Power ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Deviation Index ◽  
Diesel Cycle

Applying finite time thermodynamics theory and the non-dominated sorting genetic algorithm-II (NSGA-II), thermodynamic analysis and multi-objective optimization of an irreversible Diesel cycle are performed. Through numerical calculations, the impact of the cycle temperature ratio on the power density of the cycle is analyzed. The characteristic relationships among the cycle power density versus the compression ratio and thermal efficiency are obtained with three different loss issues. The thermal efficiency, the maximum specific volume (the size of the total volume of the cylinder), and the maximum pressure ratio are compared under the maximum power output and the maximum power density criteria. Using NSGA-II, single-, bi-, tri-, and quadru-objective optimizations are performed for an irreversible Diesel cycle by introducing dimensionless power output, thermal efficiency, dimensionless ecological function, and dimensionless power density as objectives, respectively. The optimal design plan is obtained by using three solution methods, that is, the linear programming technique for multidimensional analysis of preference (LINMAP), the technique for order preferences by similarity to ideal solution (TOPSIS), and Shannon entropy, to compare the results under different objective function combinations. The comparison results indicate that the deviation index of multi-objective optimization is small. When taking the dimensionless power output, dimensionless ecological function, and dimensionless power density as the objective function to perform tri-objective optimization, the LINMAP solution is used to obtain the minimum deviation index. The deviation index at this time is 0.1333, and the design scheme is closer to the ideal scheme.

scholarly journals Performance Optimizations with Single-, Bi-, Tri-, and Quadru-Objective for Irreversible Atkinson Cycle with Nonlinear Variation of Working Fluid’s Specific Heat

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4175
Author(s):  
Shuangshuang Shi ◽  
Yanlin Ge ◽  
Lingen Chen ◽  
Huijun Feng
Keyword(s):  
Specific Heat ◽  
Power Density ◽  
Compression Ratio ◽  
Power Output ◽  
Thermal Efficiency ◽  
Maximum Power ◽  
Maximum Power Density ◽  
Multi Objective Optimization ◽  
Nonlinear Variation ◽  
Atkinson Cycle

Considering nonlinear variation of working fluid’s specific heat with its temperature, finite-time thermodynamic theory is applied to analyze and optimize the characteristics of an irreversible Atkinson cycle. Through numerical calculations, performance relationships between cycle dimensionless power density versus compression ratio and dimensionless power density versus thermal efficiency are obtained, respectively. When the design parameters take certain specific values, the performance differences of reversible, endoreversible and irreversible Atkinson cycles are compared. The maximum specific volume ratio, maximum pressure ratio, and thermal efficiency under the conditions of the maximum power output and maximum power density are compared. Based on NSGA-II, the single-, bi-, tri-, and quadru-objective optimizations are performed when the compression ratio is used as the optimization variable, and the cycle dimensionless power output, thermal efficiency, dimensionless ecological function, and dimensionless power density are used as the optimization objectives. The deviation indexes are obtained based on LINMAP, TOPSIS, and Shannon entropy solutions under different combinations of optimization objectives. By comparing the deviation indexes of bi-, tri- and quadru-objective optimization and the deviation indexes of single-objective optimizations based on maximum power output, maximum thermal efficiency, maximum ecological function and maximum power density, it is found that the deviation indexes of multi-objective optimization are smaller, and the solution of multi-objective optimization is desirable. The comparison results show that when the LINMAP solution is optimized with the dimensionless power output, thermal efficiency, and dimensionless power density as the objective functions, the deviation index is 0.1247, and this optimization objective combination is the most ideal.

scholarly journals Four-Objective Optimizations for an Improved Irreversible Closed Modified Simple Brayton Cycle

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 282 ◽  
Author(s):  
Chenqi Tang ◽  
Lingen Chen ◽  
Huijun Feng ◽  
Yanlin Ge
Keyword(s):  
Power Density ◽  
Power Output ◽  
Thermal Efficiency ◽  
Variable Temperature ◽  
Ecological Function ◽  
Cycle Performance ◽  
Heating Process ◽  
Brayton Cycle ◽  
Nsga Ii ◽  
Deviation Index

An improved irreversible closed modified simple Brayton cycle model with one isothermal heating process is established in this paper by using finite time thermodynamics. The heat reservoirs are variable-temperature ones. The irreversible losses in the compressor, turbine, and heat exchangers are considered. Firstly, the cycle performance is optimized by taking four performance indicators, including the dimensionless power output, thermal efficiency, dimensionless power density, and dimensionless ecological function, as the optimization objectives. The impacts of the irreversible losses on the optimization results are analyzed. The results indicate that four objective functions increase as the compressor and turbine efficiencies increase. The influences of the latter efficiency on the cycle performances are more significant than those of the former efficiency. Then, the NSGA-II algorithm is applied for multi-objective optimization, and three different decision methods are used to select the optimal solution from the Pareto frontier. The results show that the dimensionless power density and dimensionless ecological function compromise dimensionless power output and thermal efficiency. The corresponding deviation index of the Shannon Entropy method is equal to the corresponding deviation index of the maximum ecological function.

scholarly journals Performance Analysis and Four-Objective Optimization of an Irreversible Rectangular Cycle

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1203
Author(s):  
Qirui Gong ◽  
Yanlin Ge ◽  
Lingen Chen ◽  
Shuangshaung Shi ◽  
Huijun Feng
Keyword(s):  
Decision Making ◽  
Power Density ◽  
Power Output ◽  
Expansion Ratio ◽  
Maximum Power ◽  
Maximum Power Density ◽  
Density Point ◽  
Nsga Ii ◽  
Effective Power ◽  
Maximum Power Output

Based on the established model of the irreversible rectangular cycle in the previous literature, in this paper, finite time thermodynamics theory is applied to analyze the performance characteristics of an irreversible rectangular cycle by firstly taking power density and effective power as the objective functions. Then, four performance indicators of the cycle, that is, the thermal efficiency, dimensionless power output, dimensionless effective power, and dimensionless power density, are optimized with the cycle expansion ratio as the optimization variable by applying the nondominated sorting genetic algorithm II (NSGA-II) and considering four-objective, three-objective, and two-objective optimization combinations. Finally, optimal results are selected through three decision-making methods. The results show that although the efficiency of the irreversible rectangular cycle under the maximum power density point is less than that at the maximum power output point, the cycle under the maximum power density point can acquire a smaller size parameter. The efficiency at the maximum effective power point is always larger than that at the maximum power output point. When multi-objective optimization is performed on dimensionless power output, dimensionless effective power, and dimensionless power density, the deviation index obtained from the technique for order preference by similarity to an ideal solution (TOPSIS) decision-making method is the smallest value, which means the result is the best.

scholarly journals Thermodynamic Assessment and Multi-Objective Optimization of Performance of Irreversible Dual-Miller Cycle

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 4000 ◽  
Author(s):  
Shahriyar Abedinnezhad ◽  
Mohammad Hossein Ahmadi ◽  
Seyed Mohsen Pourkiaei ◽  
Fathollah Pourfayaz ◽  
Amir Mosavi ◽  
...  
Keyword(s):  
Thermal Efficiency ◽  
Multidimensional Analysis ◽  
Coefficient Of Performance ◽  
Miller Cycle ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Programming Technique ◽  
Multi Objective ◽  
Optimum Solution ◽  
Linear Programming Technique

In this study, a new series of assessments and evaluations of the Dual-Miller cycle is performed. Furthermore, the specified output power and the thermal performance associated with the engine are determined. Besides, multi-objective optimization of thermal efficiency, ecological coefficient of performance (ECOP) and ecological function ( E u n ) by means of NSGA-II technique and thermodynamic analysis are presented. The Pareto optimal frontier obtaining the best optimum solution is identified by fuzzy Bellman-Zadeh, Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision-making techniques. Based on the results, performances of dual-Miller cycles and their optimization are improved. For the results of the condition that (n < k) the best point has been LINMAP answer. The thermal efficiency for this point has been 0.5388. In addition, ECOP and E u n have been 1.6899 and 279.221, respectively. For the results of the condition that (n > k) the best point has been LINMAP and TOPSIS answer. The thermal efficiency for this point has been 0.5385. Also, ECOP and E u n have been 1.6875 and 279.7315, respectively. Furthermore, the errors are examined through comparison of the average and maximum errors of the two scenarios.

scholarly journals Multi-objective optimization design of spur gear based on NSGA-II and decision making

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401882493 ◽  
Author(s):  
Qizhi Yao
Keyword(s):  
Decision Maker ◽  
Optimization Design ◽  
Optimal Solution ◽  
Spur Gear ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Deviation Index ◽  
Decision Variables

Optimization design of spur gear is a complicated work because the performance characteristics depend on different types of decision variables and objectives. Traditional single-objective optimization design of the spur gear always results in poor outcomes relative to other objectives due to objectives’ competition with each other. Therefore, this study works on the spur gear design based on the multi-objective optimization model of elitist non-dominated sorting genetic algorithm (NSGA-II). In the model, gear module, teeth number, and transmission ratio are decision variables, while center distance, bearing capacity coefficient, and meshing efficiency are objectives. Final optimal solutions are picked out from Pareto frontier calculated from NSGA-II using the decision makers of Shannon Entropy, linear programming technique for multidimensional analysis of preference (LINMAP), and technique of order preference by similarity to an ideal solution (TOPSIS). Meanwhile, a deviation index is used to evaluate the reasonable status of the optimal solutions. From triple-objective and dual-objective optimization results, it is found that the optimal solution selected from LINMAP decision maker shows a relatively small deviation index. It indicates that LINMAP decision maker may yield better optimal solution. This study could provide some beneficial information for spur design.

scholarly journals Multi-Objective Lightweight Optimization of Parameterized Suspension Components Based on NSGA-II Algorithm Coupling with Surrogate Model

Machines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 107
Author(s):  
Rongchao Jiang ◽  
Zhenchao Jin ◽  
Dawei Liu ◽  
Dengfeng Wang
Keyword(s):  
Ride Comfort ◽  
Lightweight Design ◽  
Dynamic Performance ◽  
Vehicle Dynamic ◽  
Multi Objective Optimization ◽  
Original Design ◽  
Dynamic Simulations ◽  
Nsga Ii ◽  
Torsion Beam ◽  
Multi Objective

In order to reduce the negative effect of lightweighting of suspension components on vehicle dynamic performance, the control arm and torsion beam widely used in front and rear suspensions were taken as research objects for studying the lightweight design method of suspension components. Mesh morphing technology was employed to define design variables. Meanwhile, the rigid–flexible coupling vehicle model with flexible control arm and torsion beam was built for vehicle dynamic simulations. The total weight of control arm and torsion beam was taken as optimization objective, as well as ride comfort and handling stability performance indexes. In addition, the fatigue life, stiffness, and modal frequency of control arm and torsion beam were taken as the constraints. Then, Kriging model and NSGA-II were adopted to perform the multi-objective optimization of control arm and torsion beam for determining the lightweight scheme. By comparing the optimized and original design, it indicates that the weight of the optimized control arm and torsion beam are reduced 0.505 kg and 1.189 kg, respectively, while structural performance and vehicle performance satisfy the design requirement. The proposed multi-objective optimization method achieves a remarkable mass reduction, and proves to be feasible and effective for lightweight design of suspension components.

scholarly journals Design and characterization of effective solar cells

2021 ◽  
Author(s):  
Varun Ojha ◽  
Giorgio Jansen ◽  
Andrea Patanè ◽  
Antonino La Magna ◽  
Vittorio Romano ◽  
...  
Keyword(s):  
Solar Cells ◽  
Quantum Efficiency ◽  
Cost Benefit Analysis ◽  
Cost Minimization ◽  
Cell Structure ◽  
Cost Benefit ◽  
Structure Design ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective

AbstractWe propose a two-stage multi-objective optimization framework for full scheme solar cell structure design and characterization, cost minimization and quantum efficiency maximization. We evaluated structures of 15 different cell designs simulated by varying material types and photodiode doping strategies. At first, non-dominated sorting genetic algorithm II (NSGA-II) produced Pareto-optimal-solutions sets for respective cell designs. Then, on investigating quantum efficiencies of all cell designs produced by NSGA-II, we applied a new multi-objective optimization algorithm II (OptIA-II) to discover the Pareto fronts of select (three) best cell designs. Our designed OptIA-II algorithm improved the quantum efficiencies of all select cell designs and reduced their fabrication costs. We observed that the cell design comprising an optimally doped zinc-oxide-based transparent conductive oxide (TCO) layer and rough silver back reflector (BR) offered a quantum efficiency ($$Q_e$$ Q e ) of 0.6031. Overall, this paper provides a full characterization of cell structure designs. It derives relationship between quantum efficiency, $$Q_e$$ Q e of a cell with its TCO layer’s doping methods and TCO and BR layer’s material types. Our solar cells design characterization enables us to perform a cost-benefit analysis of solar cells usage in real-world applications.

Sign in / Sign up

Export Citation Format

Share Document