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.

Optimization of a Turboprop UAV for Maximum Loiter and Specific Power Using Genetic Algorithm

2016 ◽  
Vol 33 (3) ◽  
Author(s):  
Ali Dinc
Keyword(s):  
Genetic Algorithm ◽  
Pressure Ratio ◽  
Specific Power ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Burner Exit ◽  
First Case ◽  
Turboprop Engine ◽  
Compressor Pressure Ratio ◽  
Aerial Vehicle

AbstractIn this study, a genuine code was developed for optimization of selected parameters of a turboprop engine for an unmanned aerial vehicle (UAV) by employing elitist genetic algorithm. First, preliminary sizing of a UAV and its turboprop engine was done, by the code in a given mission profile. Secondly, single and multi-objective optimization were done for selected engine parameters to maximize loiter duration of UAV or specific power of engine or both. In single objective optimization, as first case, UAV loiter time was improved with an increase of 17.5% from baseline in given boundaries or constraints of compressor pressure ratio and burner exit temperature. In second case, specific power was enhanced by 12.3% from baseline. In multi-objective optimization case, where previous two objectives are considered together, loiter time and specific power were increased by 14.2% and 9.7% from baseline respectively, for the same constraints.

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.

Multi-Objective Optimization of a Regenerative Rotorcraft Powerplant: Quantification of Fuel Economy and Environmental Impact

2015 ◽  
Author(s):  
Fakhre Ali ◽  
Konstantinos Tzanidakis ◽  
Ioannis Goulos ◽  
Vassilios Pachidis ◽  
Roberto d’Ippolito
Keyword(s):  
Heat Exchanger ◽  
Environmental Impact ◽  
Fuel Economy ◽  
Pareto Front ◽  
Pressure Ratio ◽  
Nox Emissions ◽  
Fuel Burn ◽  
Engine Design ◽  
Compressor Pressure Ratio ◽  
Pressure Compressor

A computationally efficient and cost effective simulation framework has been proposed to perform a multidisciplinary design and optimization of a conceptual regenerative rotorcraft powerplant configuration at mission level. A generic rotorcraft model, representative of a modern twin-engine light civil rotorcraft has been investigated, operating under a representative passenger air taxi mission. The design space corresponding to the conceptual regenerative engine thermodynamic cycle parameters as well as engine and mission design outputs in terms of low pressure compressor pressure ratio, high pressure compressor pressure ratio, turbine entry temperature, mass flow, heat exchanger effectiveness, engine design point specific fuel consumption, engine weight, mission fuel burn and mission CO2 and NOx emissions has been thoroughly investigated through the application of a latin hypercube sampling, design of experiment approach. The interdependencies between the various engine design inputs/outputs are quantified by establishing the corresponding linear correlations between the aforementioned engine inputs/outputs as well as for the corresponding mission output parameters. A multi-objective Particle Swarm Optimizer is employed to derive Pareto front models quantifying the optimum interrelationship between the mission fuel burn and NOx emissions inventory. The acquired engine cycle design parameters corresponding to the span of the Pareto front suggest that the heat exchanger design effectiveness is the key design parameter representing the interdependency between engine fuel economy and environmental impact. The acquired optimum engine models, obtained from the Pareto front, are subsequently deployed for the design of conceptual rotorcraft engine configurations, targeting improved mission fuel economy, enhanced payload-range capability and overall environmental impact.

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.

Micro-Turbine Design Point Definition Using Genetic Algorithm With Single and Multi-Objective Optimization

2012 ◽  
Author(s):  
Diogo F. Cavalca ◽  
Cleverson Bringhenti
Keyword(s):  
Genetic Algorithm ◽  
Gas Turbine ◽  
Pressure Ratio ◽  
Inlet Temperature ◽  
Specific Work ◽  
Multi Objective Optimization ◽  
Total Cost ◽  
Design Point ◽  
Multi Objective ◽  
Engine Design

During a gas turbine development phase an important engineer task is to find the appropriate engine design point that meet the required specifications. This task can be very arduous because all possible operating points in the gas turbine operational envelope need to be analyzed, for the sake of verification of whether or not the established performance might be achieved. In order to support engineers to best define the engine design point that meet required performance a methodology was developed in this work. To accomplish that a computer program was written in Matlab®. In this program was incorporated the thermoeconomic and thermodynamic optimization. The thermodynamic calculation process was done based in enthalpy and entropy function and then validated using a commercial program. The methodology uses genetic algorithm with single and multi-objective optimization. The micro gas turbine cycle chosen to study was the recuperated. The cycle efficiency, total cost and specific work were chosen as objective functions, while the pressure ratio, compressor and turbine polytropic efficiencies, turbine inlet temperature and heat exchange effectiveness were chosen as decision variables. For total cost were considered the fixed costs (equipment, installation, taxes, etc.) and variable costs (fuel, environmental and O&M). For emissions were taken into account the NOx, CO and UHC. An economic analysis was done for a recuperated cycle showing the costs behavior for different optimized design points. The optimization process was made for: single-objective, where each objective was optimized separately; two-objectives, where they were optimized in pairs; three-objectives, where it was optimized in trio. After, the results were compared each other showing the possible design points.

Multi-objective optimization of squirrel cage fan for range hood based on Kriging model

2021 ◽  
pp. 095440622199586
Author(s):  
Qianhao Xiao ◽  
Jun Wang ◽  
Boyan Jiang ◽  
Weigang Yang ◽  
Xiaopei Yang
Keyword(s):  
Flow Rate ◽  
Optimization Design ◽  
Volume Flow Rate ◽  
Kriging Model ◽  
Volume Flow ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

Multi-objective structural optimization of a wind turbine blade using NSGA-II algorithm and FSI

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ramazan Özkan ◽  
Mustafa Serdar Genç
Keyword(s):  
Structural Optimization ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Design Parameters ◽  
Aerodynamic Optimization ◽  
Nsga Ii ◽  
Content Type ◽  
Multi Objective ◽  
Optimization Study

Purpose Wind turbines are one of the best candidates to solve the problem of increasing energy demand in the world. The aim of this paper is to apply a multi-objective structural optimization study to a Phase II wind turbine blade produced by the National Renewable Energy Laboratory to obtain a more efficient small-scale wind turbine. Design/methodology/approach To solve this structural optimization problem, a new Non-Dominated Sorting Genetic Algorithm (NSGA-II) was performed. In the optimization study, the objective function was on minimization of mass and cost of the blade, and design parameters were composite material type and spar cap layer number. Design constraints were deformation, strain, stress, natural frequency and failure criteria. ANSYS Composite PrepPost (ACP) module was used to model the composite materials of the blade. Moreover, fluid–structure interaction (FSI) model in ANSYS was used to carry out flow and structural analysis on the blade. Findings As a result, a new original blade was designed using the multi-objective structural optimization study which has been adapted for aerodynamic optimization, the NSGA-II algorithm and FSI. The mass of three selected optimized blades using carbon composite decreased as much as 6.6%, 11.9% and 14.3%, respectively, while their costs increased by 23.1%, 29.9% and 38.3%. This multi-objective structural optimization-based study indicates that the composite configuration of the blade could be altered to reach the desired weight and cost for production. Originality/value ACP module is a novel and advanced composite modeling technique. This study is a novel study to present the NSGA-II algorithm, which has been adapted for aerodynamic optimization, together with the FSI. Unlike other studies, complex composite layup, fiber directions and layer orientations were defined by using the ACP module, and the composite blade analyzed both aerodynamic pressure and structural design using ACP and FSI modules together.

Optimal design of a parallel robotic gripper using enhanced multi-objective ant lion optimizer with a sensitivity analysis approach

2020 ◽  
Vol 40 (5) ◽  
pp. 703-721
Author(s):  
Golak Bihari Mahanta ◽  
Deepak BBVL ◽  
Bibhuti B. Biswal ◽  
Amruta Rout
Keyword(s):  
Sensitivity Analysis ◽  
Distribution Function ◽  
Design Parameters ◽  
Objective Functions ◽  
Content Type ◽  
Multi Objective ◽  
The Past ◽  
Design Variables ◽  
Pick And Place ◽  
Ant Lion

Purpose From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems. Design/methodology/approach In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer. Findings This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis. Practical implications The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries. Originality/value In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.

A multi-objective optimization model for logistic planning in the crisis response phase

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Mahdi Ershadi ◽  
Hossein Shams Shemirani
Keyword(s):  
Objective Function ◽  
Optimization Model ◽  
Crisis Response ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Proposed Model ◽  
Different Types ◽  
Response Phase ◽  
Logistic Planning

PurposeProper planning for the response phase of humanitarian relief can significantly prevent many financial and human losses. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of injured people, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified injured people.Design/methodology/approachThe main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized injured people in the network. Besides, the total transportation activities of different types of vehicles are considered as another objective function. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize transportation activities as the second objective function while maintaining the optimality of the first objective function.FindingsThe performances of the proposed model were analyzed in different cases and its robust approach for different problems was shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.Practical implicationsThe proposed methodology can be applied to find the best response plan for all crises.Originality/valueIn this paper, we have tried to use a multi-objective optimization model to guide and correct response programs to deal with the occurred crisis. This is important because it can help emergency managers to improve their plans.

Exploring governments' role in mergers and acquisitions using IVIF MULTIMOORA-COPRAS technique

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Evans Opoku-Mensah ◽  
Yuming Yin ◽  
Love Offeibea Asiedu-Ayeh ◽  
Dennis Asante ◽  
Priscilla Tuffour ◽  
...  
Keyword(s):  
Assessment Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Government Officials ◽  
Content Type ◽  
Training Support ◽  
Multi Objective ◽  
Tax Relief ◽  
Specific Order ◽  
The Government

PurposeExisting studies have found that most merger and acquisition (M&A) activities do not create the intended synergy. These studies have mainly investigated how firms' internal factors contribute to M&A successes or failures. The current study differs from the earlier ones by exploring how governments' activities can contribute to the creation of acquisition synergy.Design/methodology/approachA novel technique based on multi-objective optimization by ratio analysis and complex proportional assessment method under an interval-valued intuitionistic fuzzy (IVIF) environment is proposed to prioritize these government roles needed during the M&A process focusing on the Chinese M&A market.FindingsEnactments of regulations and loan guarantees are the most important strategies to help Chinese acquirers overcome acquisition failures. While tax relief ranks third, government training support ranks fourth. Finally, the result shows that government institutional support is the least to help acquirers overcome acquisition failures.Practical implicationsThe government has a role to play in the acquisition success. Although this study has prioritized governments' role in relative importance order, the authors recommend that governments capable of providing all these strategies should do so without any specific order. However, if otherwise, governments should not neglect the strategies with less weight completely but rather consider reducing capital allocations to such strategies. Moreover, this study shows how firms with stronger business ties with government officials may enjoy success during acquisition activities. The authors recommend that firms intending to make acquisitions develop stronger ties with governments in order to benefits from governments.Originality/valueThis is the first study to develop a theoretical framework showing how government can contribute to M&A success. The study achieves this by extending Keynesian's arguments and identifies five (5) ways in which governments can ensure acquisition success. Second, within fuzzy multi-criteria decision-making (F-MCDM) research, this study is the first to show the applicability of integrated multi-objective optimization by ratio analysis (MULTIMOORA) and complex proportional assessment (COPRAS) techniques in an IVIF environment. The novel methodology proposed in this study offers an insightful research method to future studies focusing on group decision problems.

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