Multi-objective optimization of hydro-viscous flexible drive for dynamic characteristics using genetic algorithm

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jianzhong Cui ◽  
Hu Li ◽  
Dong Zhang ◽  
Yawen Xu ◽  
Fangwei Xie
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Characteristics ◽  
Transmission Efficiency ◽  
Outer Radius ◽  
Transmission Model ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Dynamic Transmission Model

Purpose The purpose of this study is to investigate the flexible dynamic characteristics about hydro-viscous drive providing meaningful insights into the credible speed-regulating behavior during the soft-start. Design/methodology/approach A comprehensive dynamic transmission model is proposed to investigate the effects of key parameters on the dynamic characteristics. To achieve a trade-off between the transmission efficiency and time proportion of hydrodynamic and mixed lubrication, a multi-objective optimization of friction pair system by genetic algorithm is presented to obtain the optimal combination of design parameters. Findings Decreasing the engagement pressure or the ratio of inner and outer radius, increasing the lubricating oil viscosity or the outer radius will result in the increase of time proportion of hydrodynamic and mixed lubrication, as well as the transmission efficiency and its maximum value. After optimization, main dynamic parameters including the oil film thickness, angular velocity of the driven disk, viscous torque and total torque show remarkable flexible transmission characteristics. Originality/value Both the dynamic transmission model and multi-objective optimization model are established to analyze the effects of main design parameters on the dynamic characteristics of hydro-viscous flexible drive.

Investigation on the modeling and dynamic characteristics of a fast-response and large-flow water hydraulic proportional cartridge valve

2020 ◽  
Vol 234 (22) ◽  
pp. 4415-4432
Author(s):  
Mingxing Han ◽  
Yinshui Liu ◽  
Kan Zheng ◽  
Youchun Ding ◽  
Defa Wu
Keyword(s):  
Genetic Algorithm ◽  
Flow Rate ◽  
Dynamic Characteristics ◽  
Fast Response ◽  
Dynamics Simulation ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Flow Capacity ◽  
Water Hydraulic ◽  
Large Flow

In large-power and high-pressure hydraulic systems, the maximum instantaneous flow rate is often several thousand liters per minute. Normal proportional valves are often difficult to meet their requirements for large flow rate and fast response at the same time. And the leakage of hydraulic oil will seriously pollute the environment. Therefore, a novel water hydraulic proportional valve with fast response and high flow capacity is presented for the large transient power hydraulic system in this paper. The valve utilizes a two-stage structure with two 2/2-way water hydraulic proportional valves as the pilot stage and a cartridge poppet valve as the main stage to achieve fast-response and large-flow capacity simultaneously. A detailed and precise nonlinear mathematical model of the valve considering both structural parameters and flow force is developed. A comprehensive performance optimization has been carried out, which can be mainly divided into computational fluid dynamics simulation optimization based on reducing flow force and multi-objective optimization based on genetic algorithm. The effects of double U-grooves' parameters on the flow force (flow-induced loads) have been studied in detail by numerical simulation. Through the grooves geometry optimization, the maximum flow force can be reduced by 10%. Then, the influences of structure parameters on the performance of step response have been studied, and the optimal parameters of the valve have been obtained by multi-objective optimization based on genetic algorithm. The maximum overshoot has been reduced from 15% to 6% (about 60%) and the adjusting time has been reduced from 58 ms to 48 ms. The dynamic characteristics of the valve have been improved effectively. Finally, a test apparatus which has the ability to provide transient large flow is built. The accuracy of simulation model and optimization design method is verified by test results.

A Genetic Algorithm Based Multi-Objective Optimization of Squealer Tip Geometry in Axial Flow Turbines: A Constant Tip Gap Approach

2019 ◽  
Vol 142 (2) ◽  
Author(s):  
H. Maral ◽  
C. B. Şenel ◽  
K. Deveci ◽  
E. Alpman ◽  
L. Kavurmacıoğlu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Tip Clearance ◽  
Design Parameters ◽  
Leakage Flow ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Tip Leakage Flow ◽  
Tip Leakage ◽  
Multi Objective ◽  
Blade Tip

Abstract Tip clearance is a crucial aspect of turbomachines in terms of aerodynamic and thermal performance. A gap between the blade tip surface and the stationary casing must be maintained to allow the relative motion of the blade. The leakage flow through the tip gap measurably reduces turbine performance and causes high thermal loads near the blade tip region. Several studies focused on the tip leakage flow to clarify the flow-physics in the past. The “squealer” design is one of the most common designs to reduce the adverse effects of tip leakage flow. In this paper, a genetic-algorithm-based optimization approach was applied to the conventional squealer tip design to enhance aerothermal performance. A multi-objective optimization method integrated with a meta-model was utilized to determine the optimum squealer geometry. Squealer height and width represent the design parameters which are aimed to be optimized. The objective functions for the genetic-algorithm-based optimization are the total pressure loss coefficient and Nusselt number calculated over the blade tip surface. The initial database is then enlarged iteratively using a coarse-to-fine approach to improve the prediction capability of the meta-models used. The procedure ends once the prediction errors are smaller than a prescribed level. This study indicates that squealer height and width have complex effects on the aerothermal performance, and optimization study allows to determine the optimum squealer dimensions.

Multi-Objective Optimization Design of Tanker Ships via a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Marcelo Ramos Martins ◽  
Diego F. Sarzosa Burgos
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Optimization Problem ◽  
Pareto Frontier ◽  
Ship Design ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Total Cost ◽  
Multi Objective ◽  
The Cost

The cost of a new ship design heavily depends on the principal dimensions of the ship; however, dimensions minimization often conflicts with the minimum oil outflow (in the event of an accidental spill). This study demonstrates one rational methodology for selecting the optimal dimensions and coefficients of form of tankers via the use of a genetic algorithm. Therein, a multi-objective optimization problem was formulated by using two objective attributes in the evaluation of each design, specifically, total cost and mean oil outflow. In addition, a procedure that can be used to balance the designs in terms of weight and useful space is proposed. A genetic algorithm was implemented to search for optimal design parameters and to identify the nondominated Pareto frontier. At the end of this study, three real ships are used as case studies.

Switching harmonic suppression design based on multi-objective optimization algorithm with constraint processing

2020 ◽  
Vol 39 (4) ◽  
pp. 899-913
Author(s):  
Songtao Huang ◽  
Jie Ye ◽  
Haozhe Wang ◽  
Baojin Li ◽  
Anwen Shen ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Filter Design ◽  
Design Parameters ◽  
Harmonic Suppression ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Filter Parameter ◽  
Content Type ◽  
Domain Experts ◽  
Multi Objective

Purpose Traditional switching harmonic suppressor design methods require domain experts to adjust design parameters due to various complex performance requirements and practical limitations in switching ripple suppressor designs. The purpose of this paper is to present a method for filter parameter design. Design/methodology/approach An improved non-dominated sorting genetic algorithm II (NSGA II) was used in the inductor-capacitor-inductor (LCL) filter design to find the optimal design parameters, and a method was proposed to handle the constraints by transforming the them into decision variables. Findings The performance of the proposed algorithm in parameter designing was verified by simulation on MATLAB and experimental results on hardware-in-the-loop plat-form with StarSim software. The results indicate that the optimization algorithm has a better effect than the traditional expert parameters on each optimization index, especially on the switching harmonic suppression. Originality/value The paper presents an improved multi-objective optimization algorithm with ingenious constraints handing to obtain better filter parameters and reduces switching harmonics.

A Multi-Objective Optimization Method for Coordinated Control

2011 ◽  
Vol 97-98 ◽  
pp. 942-946
Author(s):  
Yun Feng Gao ◽  
Hua Hu ◽  
Tao Wang ◽  
Xiao Guang Yang
Keyword(s):  
Genetic Algorithm ◽  
Optimal Solution ◽  
Optimization Method ◽  
Transmission Model ◽  
Traffic Signal Control ◽  
Cell Transmission Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Weighted Combination ◽  
Single Objective

In this paper, to overcome the limitations of the weighted combination and single objective optimization methods, we presented a multi-objective optimization and simulation methodology for network-wide traffic signal control. A multi-objective genetic algorithm based on Non-dominated Sorting Genetic Algorithm II was given to solve the model directly to obtain Pareto optimal solution set. The objectives were evaluated by Enhanced Cell Transmission Model used to describe traffic dynamics on signalized urban road network. The results showed that the single objective optimization method made some of the objectives worsen when the objective to be optimized reaching optimal, and that the weighted combination optimization method gained a compromised solution, but the multi-objective optimization method gave consideration to more objectives, making the number of optimal or suboptimal ones is more than that of worse ones.

Design Optimization of PERCS in RELAP5 Using Parallel Processing and a Multi-Objective Non-Dominated Sorting Genetic Algorithm

2018 ◽  
Author(s):  
Paul R. Wilding ◽  
Nathan R. Murray ◽  
Matthew J. Memmott
Keyword(s):  
Genetic Algorithm ◽  
Parallel Processing ◽  
Pareto Front ◽  
Operating Time ◽  
Reactor Core ◽  
Normal Operation ◽  
Design Parameters ◽  
Outlet Temperature ◽  
Multi Objective Optimization ◽  
Multi Objective

Multi-objective optimization is a powerful tool that has been successfully applied to many fields but has seen minimal use in the design and development of nuclear power plant systems. When applied to design, multi-objective optimization involves the manipulation of key design parameters in order to develop optimal designs. These design parameters include continuous and/or discrete variables and represent the physical design specifications. They are modified across a specific design space to accomplish a number of set objective functions, representing the goals for both system design and performance, which conflict and cannot be combined into a single objective function. In this paper, a non-dominated sorting genetic algorithm (NSGA) and parallel processing in Python 3 were used to optimize the design of the passive endothermic reaction cooling system (PERCS) model developed in RELAP5/MOD 3.3. This system has been proposed as a retrofit to currently-operating light water reactors (LWR) and is designed to remove decay heat from the reactor core via the endothermic decomposition of magnesium carbonate (MgCO3) and natural circulation of the reactor coolant. The PERCS design is currently a shell-and-tube heat exchanger, with the coolant flowing through the tube side and MgCO3 on the shell side. During a station blackout (SBO), the PERCS initially keeps the reactor core outlet temperature from exceeding 635 K and then reduces it to below 620 K for 30 days. The optimization of the PERCS was performed with three different objectives: (1) minimization of equipment costs, (2) minimization of deviation of the core outlet temperature during a SBO from its normal operation steady-state value, and (3) minimization of fractional consumption of MgCO3, a metric that is measurable and directly related to the operating time of the PERCS. The manipulated parameters of the optimization include the radius of the PERCS shell, the pitch, hydraulic diameter, thickness and length of the PERCS tubes, and the elevation of the PERCS with respect to the reactor core. The NSGA methodology works by creating a population of PERCS options with varying design parameters. Using the evolutionary concepts of selection, reproduction, mutation, and survival of the fittest, the NSGA method repeatedly generates new PERCS options and gets rid of less fit ones. In the end, the result was a Pareto front of PERCS designs, each thermodynamically viable and optimal with respect to the three objectives. The Pareto front of options as a whole represents the optimized trade-off between the objectives.

Mathematical Modelling and Multi-Objective Optimization Design of a Large Flow Water Hydraulic Proportional Cartridge Valve

2017 ◽  
Author(s):  
Mingxing Han ◽  
Yinshui Liu ◽  
Huaijiang Tan ◽  
Defa Wu
Keyword(s):  
Dynamic Characteristics ◽  
High Performance ◽  
Step Response ◽  
Design Parameters ◽  
Main Stage ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Water Hydraulic ◽  
Simulation Results ◽  
Large Flow

The large flow water hydraulic proportional cartridge valve is one of the most important components and also the technical difficulties in the high performance large-tonnage engineering machinery, such as the die casting machine. The structure and principle of the large flow water hydraulic proportional cartridge valve are presented in this paper. The valve utilizes a two-stage structure with the high performance proportional valves as the pilot stage and the cartridge poppet valve as the main stage to overcome the fundamental tradeoff between the flow capacity and dynamic characteristics. A detailed and precise nonlinear mathematical model of the cartridge valve considering both structural parameters and nonlinear factors (compressibility of water, leakage, friction, flow force, etc.) is established. And then MATLAB/Simulink software is employed to build the simulation model and the dynamic simulation is carried out. Compared with the simulation results of the valve with different design parameters, the static and dynamic characteristics of the proportional cartridge throttle valve have been analyzed. The impacts of the parameters on the performance of step-response have been studied. Finally, based on multi-objective optimization method, the optimal parameters of the cartridge valve have been obtained. The simulation results show that the performances have been significantly improved.

Optimization of turboprop ESFC and NOx emissions for UAV sizing

2017 ◽  
Vol 89 (3) ◽  
pp. 375-383 ◽  
Author(s):  
Ali Dinc
Keyword(s):  
Pressure Ratio ◽  
Nox Emission ◽  
Design Parameters ◽  
Nox Emissions ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Engine Design ◽  
Turboprop Engine ◽  
Compressor Pressure Ratio

Purpose This paper aims to present a genuine code developed for multi-objective optimization of selected parameters of a turboprop unmanned air vehicle (UAV) for minimum landing-takeoff (LTO) nitrogen oxide (NOx) emissions and minimum equivalent power specific fuel consumption (ESFC) at loiter (aerial reconnaissance phase of flight) by using a genetic algorithm. Design/methodology/approach The genuine code developed in this study first makes computations on preliminary sizing of a UAV and its turboprop engine by analytical method for a given mission profile. Then, to minimize NOx emissions or ESFC or both of them, single and multi-objective optimization was done for the selected engine design parameters. Findings In single objective optimization, NOx emissions were reduced by 49 per cent from baseline in given boundaries or constraints of compressor pressure ratio and compressor polytropic efficiency in the first case. In second case, ESFC was improved by 25 per cent from baseline. In multi-objective optimization case, where previous two objectives were considered together, NOx emissions and ESFC decreased by 26.6 and 9.5 per cent from baseline, respectively. Practical implications Variation and trend in the NOx emission index and ESFC were investigated with respect to two engine design parameters, namely, compressor pressure ratio and compressor polytropic efficiency. Engine designers may take into account the findings of this study to reach a viable solution for the bargain between NOx emission and ESFC. Originality/value UAVs have different flight mission profiles or characteristics compared to manned aircraft. Therefore, they are designed in a different philosophy. As a number of UAV flights increase in time, fuel burn and LTO NOx emissions worth investigating due to operating costs and environmental reasons. The study includes both sizing and multi-objective optimization of an UAV and its turboprop engine in coupled form; compared to manned aircraft.

MULTI-OBJECTIVE OPTIMIZATION OF OFFSHORE TSUNAMI OBSERVATION POINTS BY GENETIC ALGORITHM

2020 ◽  
Vol 76 (2) ◽  
pp. I_325-I_330
Author(s):  
Kazutoshi KURAMOTO ◽  
Fumiyasu MAKINOSHIMA ◽  
Anawat SUPPASRI ◽  
Fumihiko IMAMURA
Keyword(s):  
Genetic Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective
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