检索结果-内蒙古大学图书馆

AIAA SciTech Forum

作者： Wang, Bingran Orndorff, Nicholas C. Joshy, Anugrah Jo Hwang, John T. Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92093 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Recently, the graph-accelerated non-intrusive polynomial chaos (NIPC) methods have been introduced to effectively address a variety of uncertainty quantification (UQ) challenges in multi-disciplinary and multi-point models. The essence of these graph-accelerated NIPC methods lies in leveraging tensor-grid input points for sampling the random space and using a computational graph transformation method, AMTC, to efficiently perform the tensor-grid evaluations by taking advantage of the inherent sparsity within the computational graph of the computational model. Despite their advancements, the effectiveness of these methods in tackling optimization under uncertainty (OUU) problems remains unexplored. This paper presents a detailed case study for a laser-beam-powered aircraft design problem. The focus is on applying the graph-accelerated NIPC methods to solve a large-scale multidisciplinary design optimization problem under uncertainty. This study not only compares the results of multidisciplinary optimization (MDO) and OUU but also highlights the effectiveness of the graph-accelerated NIPC method in tackling OUU challenges. The numerical results show that the OUU-optimized design is more robust under the variations of the flight conditions. Additionally, the AMTC method accelerates the optimization time by a factor of five, making the computational cost of the OUU problem only twice that of the MDO problem.

关键词： Multidisciplinary Design and optimization Aeroplane Uncertainty Quantification Aircraft Design Aerodynamic Force Wing Box Structure Structural Analysis optimization algorithm Vortex Lattice Method Unmanned Aircraft

来源：评论

学校读者我要写书评

暂无评论

Signal Conducting System with Effective optimization Using Deep Learning for Schizophrenia Classification

引用

Computer Systems Science & Engineering 2023年第5期45卷 1869-1886页

作者： V.Divya S.Sendil Kumar V.Gokula Krishnan Manoj Kumar School of Electrical and Electronics Engineering Sathyabama Institute of Science and TechnologyChennaiTamilnaduIndia Department of Electrical and Electronics Engineering S A Engineering CollegeChennaiTamilnaduIndia Department of Computer Science and Information Technology CVR College of EngineeringMangalpallyHyderabadTelanganaIndia School of Computer Science University of Petroleum and Energy StudiesDehradunIndia

Signal processing based research was adopted with Electroencephalogram(EEG)for predicting the abnormality and cerebral *** proposed research work is intended to provide an automatic diagnostic system to determine the EEG signal in order to classify the brain function which shows whether a person is affected with schizophrenia or *** detection and intervention are vital for better ***,the diagnosis of schizophrenia still depends on clinical observation to *** reliable biomarkers,schizophrenia is difficult to detect in its early phase and hence we have proposed this *** this work,the EEG signal series are divided into non-linear feature mining,classification and validation,and t-test integrated feature selection *** this work,19-channel EEG signals are utilized from schizophrenia class and normal ***,the datasets initially execute the splitting process based on raw 19-channel EEG into 6250 sample point’s *** this process,1142 features of normal and schizophrenia class patterns can be *** other hand,157 features from each EEG patterns are utilized based on Non-linear feature extraction process where 14 principal features can be identified in terms of considering the essential *** last,the Deep Learning(DL)technique incorporated with an effective optimization technique is adopted for classification process called a Deep Convolutional Neural Network(DCNN)with mayfly optimization *** proposed technique is implemented into the platform of MATLAB in order to obtain better results and is analyzed based on the performance analysis framework such as accuracy,Signal to Noise Ratio(SNR),Mean Square Error,Normalized Mean Square Error(NMSE)and *** comparison,the proposed technique is proved to a better technique than other existing techniques.

关键词： Deep learning optimization algorithm signal conducting system schizophrenia convolutional neural network mayfly optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Black-Box Online Aerodynamic Performance optimization for a Seamless Wing with Distributed Morphing

引用

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2023年第3期46卷 560-570页

作者： Ruland, Oscar Mkhoyan, Tigran De Breuker, Roeland Wang, Xuerui Delft Univ Technol Fac Aerosp Engn Dept Control & Operat Kluyverweg 1 NL-2629 HS Delft Netherlands Delft Univ Technol Fac Aerosp Engn Dept Aerosp Struct & Mat Kluyverweg 1 NL-2629 HS Delft Netherlands

来源：评论

学校读者我要写书评

暂无评论

optimization of Aerodynamic Performance of Multistage Axial Flow Compressor Based on S2 Analysis Code

Optimization of Aerodynamic Performance of Multistage Axial ...

引用

Asia-Pacific International Symposium on Aerospace Technology (APISAT)

作者： Li, Bin Chen, Jiang Liu, Yi Xiang, Hang Beihang Univ Sch Energy & Power Engn Beijing 100191 Peoples R China

ISBN: (纸本)9789819740123;9789819740109;9789819740093

The full 3-dimensional (3D) aerodynamic optimization of axial flow compressors is a typical high-dimensional and expensive optimization problem, which has multiple variables and long evaluation time. To address this challenge, this study first establishes a novel aerodynamic optimization platform for multistage axial compressors, which reduces the time of single sample evaluation by a dimensionality reduction method which adoptsquasi-3-dimensional aerodynamic calculation instead of full 3D numerical simulation. The optimization platform also adopts radial basis function (RBF) parameterization technique. It can control the deformation of 3D geometry by fewer control points, and thus the control variables of single blade and the dimension of the optimization problem are reduced. Then the aerodynamic performance of a 3.5-stage highly loaded compressor is optimized based on the optimization platform. The results show that after optimization, within the basically unchanged total pressure ratio and surge margin, the efficiency of design point is increased by a maximum of 2.2% and the optimized characteristics curves are in good agreementwith the 3Dcalculation results. Compared to the full 3D aerodynamic optimization, the optimization platform in this article can save more than 10 times the time. Thus, the effectiveness of the optimization platform in compressor aerodynamic optimization is verified.

关键词： S2 throughflow analysis method Aerodynamic performance Parameterization method optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Active and reactive power optimization control of photovoltaic and energy storage based on grid forming inverters 4

Active and reactive power optimization control of photovolta...

引用

4th Power System and Green Energy Conference (PSGEC)

作者： Wang, Qingshan Li, Yan Zhang, Qun Wang, Decheng State Grid Jiangsu Econ & Technol Res Inst Elect State Grid Jiangsu Elect Power Co Ltd Nanjing Peoples R China

ISBN: (纸本)9798350365573;9798350365580

Currently, grid forming inverters are used to support frequency and voltage in distribution networks. Hence, grid forming inverter is very important for active and reactive power optimization control. This paper first introduces the virtual synchronous generator control method. The Successive Quadratic Programming (SQP) algorithm and particle swarm optimization (PSO) algorithm are respectively used to optimize the active and reactive power control parameters. The simulation results validate that the optimization algorithm can improve the frequency and voltage dynamic performance of the system.

关键词： grid forming inverter frequency control voltage control parameter optimization optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Approximate Jacobian Eigenanalysis For Unstructured Mesh optimization of Finite Volume Simulations

Approximate Jacobian Eigenanalysis For Unstructured Mesh Opt...

引用

AIAA SciTech Forum

作者： Zandsalimy, Mohammad Ollivier-Gooch, Carl Univ British Columbia Mech Engn Adv Numer Simulat Lab Vancouver BC V6T 1Z4 Canada

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This paper presents a novel method for approximate eigenanalysis of large linear systems, with a specific focus on unstable eigenvalues in the Lyapunov sense. The method utilizes residual vector analysis, principal component analysis, and dynamic mode decomposition to identify unstable solution modes efficiently. Outlier detection models are employed to find the problematic cells on the unstructured mesh in the case of residual vector and principal component analysis while the dynamic mode decomposition points directly to the control volumes of interest without such help. By extracting and assembling corresponding rows of the Jacobian matrix, the large system is projected on a new matrix with significantly fewer degrees of freedom, leading to improved computational efficiency. The eigenvalue problem is then solved on this smaller matrix, and the obtained results are utilized for mesh optimization, enhancing the local stability of the dynamic system. By addressing the challenges of computational complexity and automation faced by previous methods, this novel approach offers a comprehensive and automated solution for the eigenanalysis of large linear systems. The potential impact of this method extends to various fields, providing a more efficient eigenanalysis process and opening new avenues for exploring and optimizing complex systems.

关键词： Dynamic Mode Decomposition Anomaly Detection Finite Volume Method Linear Time Invariant System Finite Difference Method optimization algorithm Numerical Simulation Steepest Descent Method Computing Primitive Variable

来源：评论

学校读者我要写书评

暂无评论

optimization of Multi-Mission Space Exploration Campaign Schedules Subject to Stochastic Launch Delay

Optimization of Multi-Mission Space Exploration Campaign Sch...

引用

AIAA SciTech Forum

作者： Gollins, Nicholas Ho, Koki Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Atlanta GA 30332 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Future plans for deep-space exploration campaigns, targeting locations such as the Moon and Mars, feature a multitude of interdependent missions. For example, a crewed mission may require robotic pre-cursor scouting missions, or supporting cargo delivery missions. As campaign complexity and mission inter-dependency increases, the potential knock-on effects and costs of launch delays also increase. Understanding the potential impacts of delays is an important part of architecture trade-offs in the early definition phase of a project, but quantifying those impacts for a large number of potential architecture solutions is difficult. This work aims to solve this issue by producing a method to both quantify the impact of launch delay and compare possible campaign launch schedules, in order to find robust and near-optimal solutions, by measuring the expected value of the optimization objective and expected probability of infeasibility due to the launch uncertainty. The method is applied specifically to potential lunar exploration architectures in a case study.

关键词： Deep Space Exploration Earth Lunar Exploration Moon optimization algorithm Evolutionary algorithm Space Logistics optimization Propellant Lunar Orbit NASA

来源：评论

学校读者我要写书评

暂无评论

Efficient Hybrid Energy optimization Method in Location Aware Unmanned WSN

引用

Intelligent Automation & Soft Computing 2023年第1期35卷 705-725页

作者： M.Suresh Kumar G.A.Sathish Kumar Department of CSE Sri Venkateswara College of EngineeringSriperumbudur602117India Department of ECE Sri Venkateswara College of EngineeringSriperumbudur602117India

The growth of Wireless Sensor Networks(WSNs)has revolutionized thefield of technology and it is used in different application *** edges and other critical locations can be monitored using the navigation sensor *** WSN required low energy consumption to provide a high network and guarantee the ultimate *** main objective of this work is to propose hybrid energy optimization in local aware *** hybrid proposed work consists of clustering,optimization,direct and indirect communication and *** aim of this research work is to provide and framework for reduced energy and trusted communication with the shortest path to reach source to destination in WSN and an extending lifetime of wireless *** proposed Artificial Fish Swarm optimization algorithm is used for energy optimization in military applications which is simulated using Network Simulator(NS)*** work optimizes the energy level and the same is compared with various genetic algorithms(GA)and also the cluster selection process was compared with thefission-fusion(FF)selection *** results of the proposed work show,improvement in energy optimization,throughput and time delay.

关键词： Wireless sensor networks(WSNs) optimization algorithm routing algorithm military applications

来源：评论

学校读者我要写书评

暂无评论

optimization algorithms for spectral coarse-graining of complex networks

引用

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2019年 514卷 925-935页

作者： Jia, Zhen Zeng, Lang Wang, Ying-Ying Wang, Pei Guilin Univ Technol Coll Sci Guilin 541004 Peoples R China Henan Univ Sch Math & Stat Inst Appl Math Lab Data Anal Technol Kaifeng 475004 Peoples R China

Coarse-graining techniques of large-scale complex networks have been an important approach to reduce network size, which merge nodes who share the same or similar properties while preserving some significant functions or properties of the original networks. However, reducing network size is often at the cost of worsening network performance. Thus, there is a trade-off between the coarse-grained network sizes and network performance. To find the balance between the two sides and based on the spectral coarse-graining approach (SCG), we propose two optimization algorithms, which are called variable step size optimization algorithm (VSSOA) and variable scale optimization algorithm (VSOA). The two algorithms can calculate the optimal coarse-grained step size and the optimal scale to reduce the share size of the network. The two algorithms are applied to the coarse-graining of several typical networks. And the feasibility and validity of the proposed algorithms are further verified by phase synchronization of coupled Kuramoto oscillators on typical networks. The related investigation provides a deep insight to the coarse-graining of larg-escale complex networks. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Complex network Spectral coarse-graining optimization algorithm Synchronization

来源：评论

学校读者我要写书评

暂无评论

Static Task Scheduling for Parallel Execution of Large-Scale Multidisciplinary Design optimization Models

Static Task Scheduling for Parallel Execution of Large-Scale...

引用

AIAA SciTech Forum

作者： Sperry, Mark Z. Kondap, Kavish Hwang, John T. Univ Calif San Diego Dept Mech & Aerosp Engn 9500 Gilman Dr La Jolla CA 92093 USA Francis Parker Sch 6501 Linda Vista Rd San Diego CA 92111 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Multidisciplinary design optimization (MDO) models are built by assembling sub-models that represent varying disciplines and design conditions. Consequently, such models are often computationally expensive, requiring their evaluation in a parallel computing environment to decrease solution time. MDO modeling frameworks, which are software tools to allow construction of MDO models, generally require manual user input to specify where to parallelize their code. However, this process can be tedious if the model is large or complex. In this paper, we propose a method heavily inspired by scheduling theory that aims to fully automate parallelization of MDO models. We use static task scheduling to partition mathematical operations in the model to different processors prior to model execution. Additionally, our approach supports adjoint-based derivative computation to enable the use of gradient-based optimization algorithms. Our results show a significant performance improvement when applying our method to several MDO applications. We believe our approach enables MDO modelers to solve computationally expensive problems in a more efficient manner.

关键词： Multidisciplinary Design and optimization Parallel Computing Environment optimization algorithm Software Tool Uncertainty Quantification Computing Vortex Lattice Method Blade Element Momentum Theory Asynchronous Communications Dynamic Scheduling algorithm

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：