检索结果-内蒙古大学图书馆

AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Phillips, Samuel T. Jarrett, Jerome P. Univ Cambridge Dept Engn Cambridge CB2 1PZ England

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

In this paper a new tabu search (TS) implementation of the optimization using multiple dominance relations (MDR) approach is presented. Unlike previous population-based implementations, this new algorithm is able to provide the user with information regarding the development history of the final designs produced. This helps the designer gain physical insights into how the observed performance improvements have been achieved by the optimizer. The ability to provide the physical reasoning behind predicted performance improvements is essential if optimized designs are to be adopted in industry, particularly when safety is critical. The new algorithm is shown to outperform previous implementations when applied to both analytic and airfoil design test cases, with the tracking of design development illustrated using the latter problem. The additional information provided to the user comes at no additional computational cost, increasing the value of each optimization run. The more robust design space searching capabilities of the TS upon which the new implementation is built also facilitates the application of the MDR approach to a new class of more complex design problems.

关键词： Airfoil Robust Design Drag Coefficient Particle Swarm Optimization Lift Coefficient Optimization algorithm multi objective genetic algorithm Computational Fluid Dynamics Unmanned Aerial Vehicle Search algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal Reservoir Optimization Using multiobjective genetic algorithm 11th

Optimal Reservoir Optimization Using Multiobjective Genetic ...

引用

11th International Conference on Swarm Intelligence (ICSI)

作者： Chandra, Vinod S. S. Hareendran, S. Anand Sankar, Saju S. Univ Kerala Ctr Comp Trivandrum Kerala India MITS Dept Comp Sci Kochi Kerala India Govt Polytech Coll Dept Comp Engn Punalur India

ISBN: (纸本)9783030539559;9783030539566

Scarcity of fresh water resources has thrown various challenges to hydrologist. Optimum usage of resource is the only way out to handle this situation. Among the various water resources the most controllable one is the dam reservoirs. This paper deals with optimal reservoir optimization using multi objective genetic algorithm (MOGA). Various parameters like reservoir storage capacity, spill loss, evaporation rate, water used for irrigation, water used for electricity production, rate of inflow, outflow all need to be managed in an optimal way so that water levels are managed and resource specifications are met. This is normally managed using a software, but sudden change in scenarios and change in requirements cannot be handled by such softwares. Hence we are incorporating an optimised software layer to handle such situation. multi objective genetic algorithm was able to optimise the water usage within the usage constrains. The results were assessed based on reliability, vulnerability and resilience indices. In addition, based on a multi-criteria decision-making model, it was evaluated by comparing it with other evolutionary algorithms. The simulated result shows that MOGA derived rules are promising and competitive and can be effectively used for reservoir optimization operations.

关键词： Reservoir optimization multi objective genetic algorithm Resource optimisation Nature inspired computing Software optimisation

来源：评论

学校读者我要写书评

暂无评论

Towards A Common Modeling Environment for Aircraft Power and Thermal Systems Design and Optimization: Introducing the Simulation Platform APTT-SP

Towards A Common Modeling Environment for Aircraft Power and...

引用

AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Iskrenova-Ekiert, E. K. Deppen, Timothy O. Dierker, Dominic J. Patnaik, Soumya S. SUNY Coll Brockport Dept Comp Sci Coll Brockport Brockport NY 14420 USA PC Krause & Associates Indianapolis IN 46268 USA Air Force Res Lab Aerosp Syst Directorate Wright Patterson AFB OH 45433 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Due to expanding availability of computing power, knowledge-based decision support is becoming more relevant in new areas, for example, software architecture design, engineering design, and more specifically, in aircraft design and acquisition. With the ever-increasing number and variety of scientific software, the reproducibility and reusability of software and models is becoming a growing concern. In aircraft power and thermal modeling and simulation, complexity can arise from the need for integration of multi-scale and multi-fidelity models, use of heterogeneous software tools, and collaboration between multi-disciplinary subject matter experts. Domain-specific simulation tools designed to model specific subsystems need to be compatible in order to model a larger complex system. Additionally, it has been recognized that customizable, open-source solutions to facilitate collaboration and reproducibility are highly desirable. In this paper, we introduce the Aircraft Power and Thermal Toolkit - Simulation Platform (APTT-SP). The motivation for the development of the integrated simulation platform APTT-SP, is to address the technical need for a common modeling and simulation environment for aircraft power and thermal model building, execution, optimization, verification and validation, trade space analysis, and knowledge-based decision support in the design of power and thermal engineering systems. APTT-SP has emerged as a one stop simulation platform for launch and storage of power and thermal modeling and simulation tools and provides benefits such as re-usability, reproducibility, repeatability, sharing, and record-keeping. APTT-SP is developed in Eclipse integrated development environment, leverages Sandia Analysis Workbench, and provides a selection of aircraft power and thermal models and simulation tools.

关键词： Aircrafts Integrated Development Environments High Performance Computing Eclipses Software Architecture Aircraft Design Software Tool Thermal Modeling multi objective genetic algorithm Statistical Analysis

来源：评论

学校读者我要写书评

暂无评论

Aerodynamic Nose Optimization of a Jet Trainer Aircraft

Aerodynamic Nose Optimization of a Jet Trainer Aircraft

引用

AIAA Aviation Forum

作者： Kandemir, Omer Gomec, Fazil Selcuk Turkish Aerosp Ind Inc Aerodynam Dept Aircraft Grp TR-06980 Ankara Turkey

ISBN: (数字)9781624105982

ISBN: (纸本)9781624105982

The nose geometry of an aircraft influences the characteristics of performance, stability and post stall aerodynamics. This paper studies the nose optimization process of a jet trainer in the aspects of wave drag, longitudinal pitch-up tendency and directional stability. The parametrization of the nose geometry is divided into two subsections including lateral and frontal cross sections. Two independent design spaces representing these cross sections are created and solved at definite flight conditions by a RANS flow solver. Artificial neural network models are created with the results of these analyses as aerodynamics data generator. The final geometry is optimized by a multi objective genetic algorithm.

关键词： Trainer Aircraft Aerodynamic Characteristics Artificial Neural Network Reynolds Averaged Navier Stokes multi objective genetic algorithm Directional Stability Post Stall Angle of Attack Lift to Drag Ratio Computational Fluid Dynamics

来源：评论

学校读者我要写书评

暂无评论

Air-Racer Design Exploration using Latin Hypercube and genetic algorithm Methods

Air-Racer Design Exploration using Latin Hypercube and Genet...

引用

AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Burton, Scott A. Kao, Jason Y. White, Trenton L. Reich, Gregory W. Kolonay, Raymond M. Amer Optimizat LLC Springboro OH 45066 USA Univ Dayton Res Inst Dayton OH 45469 USA Air Force Res Lab Aerosp Syst Directorate Wright Patterson AFB OH 45433 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

The multidisciplinary Science and Technology Center at the Air Force Research Laboratory (AFRL) is conducting research into new conceptual design processes to facilitate the design of next generation air vehicles. The main thrust of this effort involves including high-fidelity analyses associated with preliminary and detailed design into the conceptual design process. This paper examines the design of an air-racer vehicle using a multidisciplinary analysis that includes geometry, aerodynamics, structures, and cost disciplines. Two design approaches are considered: a Latin Hypercube-based (LH) design exploration method and a multi-objective genetic algorithm (GA) optimization. Both approaches leverage the AFRL-developed Bond/MSTC-Engineering software for large-scale desktop grid computing. The results demonstrate the superior computational efficiency of the GA in characterizing the Pareto front over the LH in two and three multi-objective air-racer vehicle optimization studies.

关键词： multi objective genetic algorithm Air Force Research Laboratory Commercial Aircraft Stability Derivatives Grid Computing Landing Gear MATLAB Angle of Attack Flight Optimization System Wing Span

来源：评论

学校读者我要写书评

暂无评论

Orthogonal based ANN and multiGA for optimization on WEDM of Ti-48Al intermetallic alloys

引用

ARTIFICIAL INTELLIGENCE REVIEW 2019年第1期52卷 671-706页

作者： Yusoff, Yusliza Zain, Azlan Mohd Amrin, Astuty Sharif, Safian Haron, Habibollah Sallehuddin, Roselina UTM Skudai Dept Comp Sci Fac Comp Skudai 81310 Johor Malaysia UTM Kuala Lumpur UTM Razak Sch Engn & Adv Technol Jalan Sultan Yahya Petra Kuala Lumpur 54100 Malaysia UTM Skudai Dept Mfg & Ind Engn Fac Mech Engn Skudai 81310 Johor Malaysia

As surveyed, many efforts have been made to model the performances of electrical discharge machining (EDM) using artificial neural network (ANN). However, the selections of the network parameters were mostly prepared in a random manner, resulting to unnecessary trials. Thus, orthogonal array (Taguchi) is employed in the procedure of network function and network architecture assortment to avoid excessive random trial experimentations. This proposed orthogonal based ANN modelling is employed on WEDM of Ti-48Al intermetallic alloys. Meanwhile modified multi objective genetic algorithm (multiGA) is used as the optimization technique. Material removal rate (MRR), surface roughness (Ra), cutting speed (Vc) and width of kerf (Dk) are the machining performances considered in this study. Five machining parameters observed from the previous researches are chosen as significant factors to the machining performances in this study, which are pulse on time, pulse off time, peak current, feed rate and servo voltage. Experimental studies are carried out to verify the machining performances suggested by this approach. Feed forward back propagation neural network (FFNN) is found to be the best network type on the selected dataset. Two hidden layer 5-6-6-4 FFNN showed the most precise and generalized network architecture with very good prediction accuracy. The proposed approach, OrthoANN, reduced ANN experimentation time by a large scale and produced viable results for machining optimization when integrated with multiGA.

关键词： Orthogonal array Regression Artificial neural network (ANN) multi objective genetic algorithm Optimization Electrical discharge machining (EDM)

来源：评论

学校读者我要写书评

暂无评论

multidisciplinary and multifidelity Framework for Evaluating System-of-Systems Capabilities of Unmanned Aircraft

引用

JOURNAL OF AIRCRAFT 2020年第2期57卷 317-332页

作者： Papageorgiou, Athanasios Olvander, Johan Amadori, Kristian Jouannet, Christopher Linkoping Univ Div Machine Design Dept Management & Engn SE-58183 Linkoping Sweden SAAB Aeronaut Adv Design & Survivabil SE-58188 Linkoping Sweden

The operational environment of aerospace products can have a big impact on their performance, and therefore it is an aspect that should be considered as early as possible in their development process. In this light, this paper presents an analysis and optimization framework that can be used in the development of unmanned aerial vehicles (UAV) in order to efficiently explore the design space when considering system-of-systems (SoS) formulations. In this work, the problem is decomposed with a multilevel architecture, and it is divided into three parts, which enable a multifidelity evaluation of the SoS, constituent systems (CS), and subsystems (SS) levels. To be able to capture the collaboration between different assets at an SoS level the framework includes an in-house tool for performing agent-based simulations, whereas the specifications of each CS are analyzed through a set of basic aeronautical disciplines and a number of SS models. The framework is tested against two surveillance scenarios by considering existing as well as new UAV designs, and overall it is shown that the exploration of SoS enables to identify better capabilities;that the operational environment poses different requirements on all system levels;and that fleet tactics have a profound effect on mission performance.

关键词： Unmanned Aircraft Surrogate Model Electrical Systems Space Exploration Tricycle Landing Gear Fuel Consumption multi objective genetic algorithm Aspect Ratio Turbofan Engines Aircraft Manufacturing

来源：评论

学校读者我要写书评

暂无评论

Design and Optimisation of a 20kW Horizontal Axis Wind Turbine using HARP_Opt 9

Design and Optimisation of a 20kW Horizontal Axis Wind Turbi...

引用

9th International Conference on Power and Energy Systems (ICPES)

作者： Singh, Krishneel A. Ahmed, Mohammed R. Univ South Pacific Sch Engn & Phys Suva Fiji

ISBN: (纸本)9781728126586

The design of a 20 kW horizontal axis small wind turbine was carried out using the analysed wind data and the Weibull parameters of a site in Vanuatu. The airfoils were generated for the 20 kW SWT and optimized using XFOIL. The initial airfoil was parameterized using a 7th order Bezier curve. Three airfoils with thicknesses of 21%, 14% and 9% were generated for the root region, mid region and the tip region respectively. The performance characteristics were studied and Harp_Opt was used to design and optimize the 20 kW wind turbine. A cut-in wind speed of 2 m/s and a rated wind speed of 10 m/s were shown by the power curve. The annual energy production (AEP) of the designed turbine was calculated to be 66.75 MWh/year with a capacity factor of around 38.1%. Small wind turbines will be ideal for the Pacific Island Countries (PICs) since they can operate at low wind speeds and Reynolds numbers less than 500,000. Using larger commercial turbines are not ideal for the PICs due to frequent cyclones and logistics issues thus a SWT is designed in the present work.

关键词： Horizontal axis wind turbine small wind turbine multi objective genetic algorithm HARP_Opt optimization

来源：评论

学校读者我要写书评

暂无评论

Aerodynamic Design of a Compressor Rotor using an Optimization-under-Uncertainty Approach

Aerodynamic Design of a Compressor Rotor using an Optimizati...

引用

AIAA Science and Technology (SciTech) Forum and Exposition

作者： Meyer, Marcus Becker, Bernd Vasilopoulos, Ilias Gambitta, Marco Poloni, Carlo Rolls Royce Deutschland Eschenweg 11 D-15827 Blankenfelde Mahlow Germany Univ Trieste Piazzale Europa 1 I-34127 Trieste Italy

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

This paper describes the application of an Optimization-under-Uncertainty (OuU) approach for the probabilistic design of engine components in an industrial setting. After a short discussion of recent OuU applications for turbomachinery components we will describe the model used for this study as well as its design and noise parameterization. This is followed by a description of the OuU method employed and the results obtained. Finally we will draw conclusions based on our experience and identify opportunities for improvement towards industrially viable OuU approaches.

关键词： Design of Compressor Turbomachinery Robust Design Probability Density Functions Surrogate Model CFD Simulation multi objective genetic algorithm Rotor Blades High Performance Computing Foreign Object Damage

来源：评论

学校读者我要写书评

暂无评论

Search-based Testing using EFSMs 30

Search-based Testing using EFSMs

引用

30th IEEE International Symposium on Software Reliability Engineering (ISSRE)

作者： Turlea, Ana Univ Bucharest Fac Math & Comp Sci Bucharest Romania Univ Bucharest ICUB Bucharest Romania

ISBN: (纸本)9781728151380

Extended finite state machines are widely used in model based testing. Since testing is such a critical step from the software development process, it is important to have many different test suites, generated on different criteria. This paper presents a test suite generation algorithm for EFSMs. The algorithm produces a set of feasible transition paths that cover all transitions using a modified NSGA-II and a NSGA-III algorithm (based on different feasibility optimization) and a Hybrid genetic algorithm to generate input values that trigger all the paths.

关键词： genetic algorithms search based testing test case generation model based testing extended finite state machines multi objective genetic algorithm nsga-iii

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：