Multi-objective optimization of a geothermal steam turbine combined with reverse osmosis and multi-effect desalination for sustainable freshwater production

2021 ◽  
pp. 1-19
Author(s):  
Aida Farsi ◽  
Marc A. Rosen
Keyword(s):  
Steam Turbine ◽  
Reverse Osmosis ◽  
Exergy Efficiency ◽  
Mathematical Function ◽  
Multi Objective Optimization ◽  
Total Cost ◽  
Cost Rate ◽  
Multi Objective ◽  
Design Variables ◽  
Seawater Salinity

Abstract A novel geothermal desalination system is proposed and optimized in terms of maximizing the exergy efficiency and minimizing the total cost rate of the system. The system includes a geothermal steam turbine with a flash chamber, a reverse osmosis unit and a multi-effect distillation system. First, exergy and economic analyses of the system are performed using Engineering Equation Software. Then, an artificial neural network is used to develop a mathematical function linking input design variables and objective functions for this system. Finally, a multi-objective optimization is carried out using a genetic algorithm to determine the optimum solutions. The Utopian method is used to select the favorable solution from the optimal solutions in the Pareto frontier. Also, the distributions of the values of design variables within their allowable ranges are investigated. It is found that the optimum exergy efficiency and total cost rate of the geothermal desalination system are 29.6% and 3410 $/h, respectively. Increasing the seawater salinity and decreasing the intake geothermal water temperature results in an improvement in both exergy efficiency and total cost rate of the system, while variations in the flash pressure and turbine outlet pressure lead to a conflict between the exergy efficiency and total cost rate of the geothermal desalination system over the range of their variations.

The Finite Element Analysis and the Multi-Objective Optimization Design of Spindle Systems of CNC Gantry Machine Tools

2016 ◽  
Vol 693 ◽  
pp. 243-250
Author(s):  
Zhi Zhong Guo ◽  
Yun Shun Zhang ◽  
Shi Hao Liu
Keyword(s):  
Machine Tools ◽  
Optimization Design ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Multi Objective ◽  
Vibration Resistance ◽  
Design Variables ◽  
Force Coupling ◽  
The Finite Element Analysis ◽  
Spindle Structure

It is discovered that the vibration resistance of spindle systems needs to be improved based on the statics analysis, modal analysis and heating-force coupling analysis of spindle systems of CNC gantry machine tools. The design variables of optimization are set according to sensitivity analysis, multi-objective and dynamic optimization design is realized and its designing scheme is gained for spindle structure. The research results show that vibration resistance can be improved without change of the quality and static property of spindle systems of CNC gantry machine tools.

Multi-objective optimization of a sports car suspension system using simplified quarter-car models

2020 ◽  
Vol 21 (4) ◽  
pp. 412
Author(s):  
Salman Ebrahimi-Nejad ◽  
Majid Kheybari ◽  
Seyed Vahid Nourbakhsh Borujerd
Keyword(s):  
Numerical Solutions ◽  
Suspension System ◽  
Mode Shapes ◽  
Ride Quality ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Characteristic Roots ◽  
Design Variables ◽  
Stiffness Matrices ◽  
Quarter Car

In this paper, first, the vibrational governing equations for the suspension system of a selected sports car were derived using Lagrange's Equations. Then, numerical solutions of the equations were obtained to find the characteristic roots of the oscillating system, and the natural frequencies, mode shapes, and mass and stiffness matrices were obtained and verified. Next, the responses to unit step and unit impulse inputs were obtained. The paper compares the effects of various values of the damping coefficient and spring stiffness in order to identify which combination causes better suspension system performance. In this regard, we obtained and compared the time histories and the overshoot values of vehicle unsprung and sprung mass velocities, unsprung mass displacement, and suspension travel for various values of suspension stiffness (KS ) and damping (CS ) in a quarter-car model. Results indicate that the impulse imparted to the wheel is not affected by the values of CS and KS . Increasing KS will increase the maximum values of unsprung and sprung mass velocities and displacements, and increasing the value of CS slightly reduces the maximum values. By increasing both KS and CS we will have a smaller maximum suspension travel value. Although lower values of CS provide better ride quality, very low values are not effective. On the other hand, high values of CS and KS result in a stiffer suspension and the suspension will provide better handling and agility; the suspension should be designed with the best combination of design variables and operation parameters to provide optimum vibration performance. Finally, multi-objective optimization has been performed with the approach of choosing the best value for CS and KS and decreasing the maximum accelerations and displacements of unsprung and sprung masses, according to the TOPSIS method. Based on optimization results, the optimum range of KS is between 130 000–170 000, and the most favorable is 150, and 500 is the optimal mode for CS .

Thermodynamic and Economic Analysis and Multi-Objective Optimization of Supercritical CO2 Brayton Cycles

2015 ◽  
Author(s):  
Hang Zhao ◽  
Qinghua Deng ◽  
Wenting Huang ◽  
Zhenping Feng
Keyword(s):  
Supercritical Co2 ◽  
Exergy Efficiency ◽  
Temperature Cycle ◽  
Inlet Temperature ◽  
Brayton Cycle ◽  
Multi Objective Optimization ◽  
Turbine Inlet Temperature ◽  
Multi Objective ◽  
Turbine Inlet ◽  
Thermodynamic Performance

Supercritical CO2 Brayton cycles (SCO2BC) offer the potential of better economy and higher practicability due to their high power conversion efficiency, moderate turbine inlet temperature, compact size as compared with some traditional working fluids cycles. In this paper, the SCO2BC including the SCO2 single-recuperated Brayton cycle (RBC) and recompression recuperated Brayton cycle (RRBC) are considered, and flexible thermodynamic and economic modeling methodologies are presented. The influences of the key cycle parameters on thermodynamic performance of SCO2BC are studied, and the comparative analyses on RBC and RRBC are conducted. Based on the thermodynamic and economic models and the given conditions, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used for the Pareto-based multi-objective optimization of the RRBC, with the maximum exergy efficiency and the lowest cost per power ($/kW) as its objectives. In addition, the Artificial Neural Network (ANN) is chosen to establish the relationship between the input, output, and the key cycle parameters, which could accelerate the parameters query process. It is observed in the thermodynamic analysis process that the cycle parameters such as heat source temperature, turbine inlet temperature, cycle pressure ratio, and pinch temperature difference of heat exchangers have significant effects on the cycle exergy efficiency. And the exergy destruction of heat exchanger is the main reason why the exergy efficiency of RRBC is higher than that of RBC under the same cycle conditions. Compared with the two kinds of SCO2BC, RBC has a cost advantage from economic perspective, while RRBC has a much better thermodynamic performance, and could rectify the temperature pinching problem that exists in RBC. Therefore, RRBC is recommended in this paper. Furthermore, the Pareto front curve between the cycle cost/ cycle power (CWR) and the cycle exergy efficiency is obtained by multi-objective optimization, which indicates that there is a conflicting relation between them. The optimization results could provide an optimum trade-off curve enabling cycle designers to choose their desired combination between the efficiency and cost. Moreover, the optimum thermodynamic parameters of RRBC can be predicted with good accuracy using ANN, which could help the users to find the SCO2BC parameters fast and accurately.

Approximate Multi-Objective Optimization of Medical Foot Support: Case of 3D Shape Optimization

2009 ◽  
Author(s):  
Shin-ichiro Miyake ◽  
Suguru Nakao ◽  
Masao Arakawa
Keyword(s):  
Physical Therapists ◽  
Daily Life ◽  
Radial Basis Function Network ◽  
Medical Doctors ◽  
Multi Objective Optimization ◽  
3D Shape ◽  
Multi Objective ◽  
Maximum Reduction ◽  
Design Variables ◽  
Function Network

Splayfoot seems not serious diseases. However, it cause fatigue in the daily life. In that sense, if we can solve these problems it might support daily life much comfortable especially for elder people. To support splayfoot, there are some commercial ones. But they just add small amount of support and not made up for each person. Besides, when the height of support is not suitable for patients, it sometimes makes situation worse. We have tried it and measured by using myoelectric potential measurements, and see differences of three patients. Even if we use the same commercial support its effectiveness differs to each other and sometimes it makes worse. Physical therapists make foot support for each patient but they make them owing to their experience. There are studies on the positions of bone of foot and its portrait of the desired positions has been reported by medical doctors. One of them is called Mizuno standard [1]. In the previous study, we tried to design foot support aiming to make portrait of this standard in vertical space. For that purpose, we used approximate multi-objective optimization using Radial Basis Function network. For validation, we used electromyography again. As a result the foot support by the proposed method showed the maximum reduction in integral of myoelectric. However, in the previous study [2], we only used two design variables, and we have only designed vertical phase. Therefore, we have not completely designed the support. In this study, we use 3D spline expression to make support, and try to design 3D shape of support. In validation, the results of approximate multi-objective optimization show the best reduction in integral of myoelectric, and show the effectiveness of the proposed method.

scholarly journals Multi-objective optimization of thermal modelled cubicles considering the total cost and life cycle environmental impact

2015 ◽  
Vol 88 ◽  
pp. 335-346 ◽  
Author(s):  
Joan Carreras ◽  
Dieter Boer ◽  
Gonzalo Guillén-Gosálbez ◽  
Luisa F. Cabeza ◽  
Marc Medrano ◽  
...  
Keyword(s):  
Life Cycle ◽  
Environmental Impact ◽  
Multi Objective Optimization ◽  
Total Cost ◽  
Multi Objective

Multi-Objective Optimization of Metal Forming Processes Based on the Kalai and Smorodinsky Solution

2015 ◽  
Vol 651-653 ◽  
pp. 1387-1393 ◽  
Author(s):  
Lorenzo Iorio ◽  
Lionel Fourment ◽  
Stephane Marie ◽  
Matteo Strano
Keyword(s):  
Optimization Problems ◽  
Good Method ◽  
Wire Drawing ◽  
Bargaining Problem ◽  
Mathematical Function ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cooperative Approach ◽  
The Game Theory

The Game Theory is a good method for finding a compromise between two players in a bargaining problem. The Kalai and Smorodinsky (K-S) method is a solution the bargaining problem where players make decisions in order to maximize their own utility, with a cooperative approach. Interesting applications of the K-S method can be found in engineering multi-objective optimization problems, where two or more functions must be minimized. The aim of this paper is to develop an optimization algorithm aimed at rapidly finding the Kalai and Smorodinsky solution, where the objective functions are considered as players in a bargaining problem, avoiding the search for the Pareto front. The approach uses geometrical consideration in the space of the objective functions, starting from the knowledge of the so-called Utopia and Nadir points. An analytical solution is proposed and initially tested with a simple minimization problem based on a known mathematical function. Then, the algorithm is tested (thanks to a user friendly routine built-in the finite element code Forge®) for FEM optimization problem of a wire drawing operation, with the objective of minimizing the pulling force and the material damage. The results of the simulations are compared to previous works done with others methodologies.

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