检索结果-内蒙古大学图书馆

Synthesize multiple V/H directional beams for high altitude platform station based on deep-learning algorithm

SCIENTIFIC REPORTS 2025年第1期15卷 1-22页

作者： Mahmoud, Korany R. Montaser, Ahmed M. Helwan Univ Fac Engn Elect & Commun Dept Cairo 11795 Egypt Natl Telecommun Regulatory Author NTRA Giza 12577 Egypt Sohag Univ Fac Technol & Educ Elect Engn Dept Sohag 82524 Egypt

This paper investigates the integration of High-Altitude Platform Stations (HAPS) with Deep Learning (DL) models to enhance coverage capabilities. Recognizing the inherent limitations of traditional HAPS coverage, which is typically confined to a circular area, this work proposes a novel approach utilizing a 60-element Concentric Circular Array (CCA) operating at 2.1 GHz. To dynamically generate multiple vertical/horizontal (V/H) directional beams, the system integrates a Deep Neural Network (DNN) with a modified version of the Gravitational Search algorithm and Particle Swarm optimization (MGSA-PSO) algorithm. This hybrid approach optimizes the feeding phases of the CCA elements, enabling the system to effectively cover diverse road paths. Furthermore, the study incorporates realistic scenarios by utilizing the Computer Simulation Technology-Microwave Studio Suite (CST) with the Earth Explorer (EE) user interface tool to model real-world road paths, including those traversing challenging terrains such as rugged deserts with mountain chains and forested areas.

关键词： Deep learning Deep neural network optimization algorithm Antenna array Beamforming technique

来源：评论

学校读者我要写书评

暂无评论

Lamination Parameter-Based Two-Dimension Sampling optimization Method for Stacking Sequence Design of Composite Laminates

引用

AIAA JOURNAL 2022年第5期60卷 3225-3250页

作者： Jing, Zhao Northwestern Polytech Univ Sch Aeronaut Xian 710072 Shaanxi Peoples R China

A novel two-dimension sampling optimization method (2DSO) is proposed for the stacking sequence design of composite laminates. The concept of using lamination parameters (LPs) to characterize distances of different stacking sequences is introduced. The first step involves using the boundary vertices and boundary lines of the LPs to yield randomly and uniformly distributed continuous variables in the LP design space. In the second step, stacking sequences are generated randomly and evaluated with a dynamic distance constraint to ensure their LPs are close to previous continuous variables. Following this, objective values are computed for these feasible points;and several best point candidates are identified. Next, the local sampling optimization is performed by generating new stacking sequences in the vicinity of the aforementioned best point candidates. The preceding two steps are repeated until the best objective converges. Lastly, a sequential permutation search (SPS) serves as a local optimization solver to target the global optimum. Because design optimization is always conducted in the stacking sequence design domain and the LP is employed to measure the distances of distinct stacking sequences and ensure uniform distribution of initial points, no feasible constraint is needed for LP;therefore, the optimal vortices are captured efficiently. The 2DSO method is used to optimize the fundamental frequency and buckling load of composite plates and shells, and the results are compared to a layerwise optimization approach (LOA), the SPS, and a genetic algorithm (GA). The results demonstrate that 2DSO outperforms LOA and SPS, and it has similar robustness to GA while being significantly more efficient.

关键词： Fiber Reinforced Composites Vortices Genetic algorithm Composite Cylindrical Panels optimization algorithm Free Vibrations Poisson's Ratio Structural Response Fuselages Buckling Problem

来源：评论

学校读者我要写书评

暂无评论

Aerodynamic Shape optimization of an S-Duct Intake for a Boundary-Layer Ingesting Engine

引用

JOURNAL OF AIRCRAFT 2022年第3期59卷 725-741页

作者： Chiang, Christopher Koo, David Zingg, David W. Univ Toronto Inst Aerosp Studies Toronto ON M3H 5T6 Canada Univ Toronto Inst Aerosp Studies Computat Aerodynam & Sustainable Aviat Toronto ON M3H 5T6 Canada

A high-fidelity aerodynamic shape optimization framework based on the Reynolds-averaged Navier-Stokes equations is applied to the optimization of a boundary-layer ingesting S-duct designed for embedded engines on a high-subsonic, unmanned flight vehicle. The optimizations initially target a cruise operating condition and are further extended to single-point and multipoint optimizations considering descent and climb. Two different composite objective functions are used. The first combines distortion and swirl at the fan interface plane as well as total pressure recovery, with user-defined weights for each objective, whereas the second involves pressure recovery, fan blade load variation, and fan blade incidence variation. Pareto fronts show the tradeoffs between objectives. The results indicate that compared to the baseline geometry, a simultaneous improvement in all objectives contained in the composite objective function can be obtained, depending on the priorities of each objective pre-assigned by the user. It was also found that if swirl can be ignored, then fan-face distortion can be greatly reduced while simultaneously reducing total pressure loss in the S-duct. Similarly, fan blade load variation and fan blade incidence variation can be significantly reduced while reducing total pressure loss. Finally, the multipoint optimization results show that a single S-duct geometry can perform well during cruise, climb, and descent conditions.

关键词： Momentum Boundary Layer Aerodynamic Shape optimization Reynolds Averaged Navier Stokes Fan Blades Flight Vehicle Blade Loading Aerodynamic Performance Flow Conditions optimization algorithm Sparse Nonlinear Optimizer

来源：评论

学校读者我要写书评

暂无评论

Relaying Fast In-Flight Alignment Method Based on Adaptive Multiconstraints

引用

IEEE SENSORS JOURNAL 2024年第2期24卷 1264-1274页

作者： Wang, Jinwen Deng, Zhihong Bo, Yuming Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Beijing Inst Technol Key Lab Intelligent Control & Decis Complex Syst Beijing 100081 Peoples R China

In-flight alignment is the basis of projectile strapdown inertial navigation system (SINS) accurate navigation. In-flight alignment of guided projectile SINS is faced with "high" complexity, such as satellite interference and random wind disturbance, and "high" dynamics, such as high velocity (>= 500 m/s), high spin (>= 20 r/s), and high overload (>= 10 000 g). Thus, this article proposes a relaying fast in-flight alignment method based on adaptive multiconstraints, which is mainly divided into the optimization stage and filtering stage. First, the initial attitude angles are taken as the optimization object to establish the optimization model, and the K matrix is taken as the state variable to establish the filtering model. Then, the internal relaying mode in the optimization stage and the external relaying mode from the optimization stage to the filtering stage are designed. The rapidity of the optimization algorithm is exerted via adaptive multiconstraint mode to speed up the alignment process. Taking the filtering stage as the main step, the high precision of the filtering algorithm is brought into play to improve alignment accuracy. Simulation and experimental results show that the alignment accuracy and alignment time of this method are better than those of traditional methods.

关键词： Adaptive multiconstraint high dynamic in-flight alignment optimization algorithm relaying strapdown inertial navigation system (SINS)

来源：评论

学校读者我要写书评

暂无评论

Ship Trajectory Prediction Model Based on Improved Bi-LSTM

引用

ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING 2024年第3期10卷

作者： Li, Weifeng Lian, Yifan Liu, Yaochen Shi, Guoyou Dalian Maritime Univ Nav Coll Dalian 116026 Peoples R China

Ship trajectory prediction plays an important role in ensuring ship safety;through accurate ship positioning, the future trajectory of ships and their encounter time and location can be obtained, which facilitates the maritime regulatory authorities to assess the risks of ship encounters and implement effective traffic control. Meanwhile, with the rapid development of the shipping industry, the increasingly complex maritime traffic poses potential risks, which may cause serious traffic accidents and huge economic losses. To improve the accuracy of ship navigation risk prediction and ensure the safety of ship navigation, automatic identification system (AIS) data and deep learning models are used to extract the ship trajectory change feature pattern and apply it to ship trajectory prediction. This study builds the improved bidirectional long short-term memory network (Bi-LSTM) model based on rectified adaptive moment estimation (Radam) and lookahead, respectively. The AIS data of the Port of Tianjin area were selected for model training, and the results of comparison experiments show that the improved Bi-LSTM model has a stronger generalization ability, which further improves the trajectory prediction accuracy, and shows excellent predictive performance. The prediction model is feasible for the prediction of ship navigation trajectory.

关键词： Automatic identification system (AIS) Trajectory prediction Deep learning optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Exploration of the Effects of Rotor Blade Twist on Whirl-Flutter Stability Boundaries

引用

JOURNAL OF AIRCRAFT 2024年第2期61卷 570-585页

作者： Muscarello, Vincenzo Quaranta, Giuseppe RMIT Univ Melbourne Vic 3082 Australia Polytech Univ Milan Dept Aerosp Sci & Technol I-20156 Milan Italy

This paper investigates the influence of tiltrotor blade twist on whirl-flutter stability boundaries. Preliminary evaluations indicate that the whirl-flutter speed can be increased if the blade twist slope is reduced. This positive effect results from the shift in the overall thrust toward the blade tip, increasing the flapwise bending moment at the blade root and the trim coning angle. This, in turn, generates a positive pitch-lag coupling, increasing the whirl-flutter speed. However, the shift of high sectional thrust forces toward the blade tip sections returns a higher induced drag, showing the tendency to increase the power required. The paper shows that, by using blade twist laws based on piecewise linear functions and adding the wing airfoil thickness as a second design parameter, it is possible to identify aircraft configurations that improve the whirl-flutter stability boundaries without penalizing the power required in airplane and helicopter mode flight. This is possible because the blade twist and the wing airfoil thickness have an impact on both power required and whirl-flutter speed, so a simple optimization algorithm can identify good tradeoffs. A detailed tiltrotor model representative of the Bell XV-15 is used to display the effectiveness of the proposed approach. The examples show that increases up to 21% on the whirl-flutter speed are achievable without penalties in the aircraft power required and with the additional benefit of a benign impact on rotor pitch link loads.

关键词： optimization algorithm Tiltrotor Aeroelasticity Whirl Flutter Twisted Rotor Blade Aircraft Performance VTOL Aircraft Aero Structural Design Thickness-to-Chord Ratio Flight Envelope

来源：评论

学校读者我要写书评

暂无评论

Assessing district heating potential at large scale: Presentation and application of a spatially-detailed model to optimally match heat sources and demands.

引用

APPLIED ENERGY 2024年 372卷

作者： Spirito, G. Denarie, A. Fattori, F. Muliere, G. Motta, M. Persson, U. Politecn Milan Dept Energy I-20156 Milan Italy Univ Insubria Dipartimento Sci Teor & Applicate I-21100 Varese Italy Halmstad Univ Sch Business Engn & Sci POB 823 S-30118 Halmstad Sweden

This paper presents a newly developed methodology aimed at assessing at national level the techno-economic potential of district heating (DH) based on renewables and excess heat sources. The novelty of the model lies in the use of an optimization approach to match heat demand and heat sources at large scale level, while keeping a high degree of spatial detail. Areas suitable for DH adoption are identified by minimizing heat delivery costs, and therefore by choosing the most economical technology between district heating and the alternative individual solution. The optimization approach, usually applicable at limited analytical scope because of the computational burden, is here adapted to large scale analysis through the introduction of novel methodological elements with which the network topology is simulated nationwide. The methodology applies to preliminarily identified maps of available heat sources and eligible heat demand, with the quantification of the latter including retrofitting and low connection rate scenarios. It then consists in two steps: connecting elements in a graph through triangulation and routing algorithms and optimizing connections to minimize the overall heat delivery costs, either by adopting district heating or individual heating systems. The whole methodology is based on open-source data and tools for broad applicability. The paper presents the elaborated methodology together with the application of the entire model to Italy. The outcome is a map of the potential district heating systems identified with significant spatial detail nationwide. A four-fold

关键词： District heating potential Matching heat demand and sources optimization algorithm Routing algorithm GIS Energy graph

来源：评论

学校读者我要写书评

暂无评论

Scheduling an Agile Multipayload Earth-Observing Satellite

引用

JOURNAL OF SPACECRAFT AND ROCKETS 2024年第1期61卷 143-156页

作者： Zhang, Wenyuan Zheng, Gangtie Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China

A highly integrated Earth-observing satellite can possess several maneuverable payloads to perform different missions simultaneously, which brings some challenges to the method of task scheduling. This paper addresses the selection and scheduling problem of an agile satellite with several independently maneuverable optical payloads. Some differences compared to the traditional scheduling problem of agile satellites are presented and considered in a constrained optimization model. A two-stage method is proposed to accomplish the scheduling of the satellite and payloads in different stages. Clusters are generated from preprocessed tasks by a clique partition algorithm, and their centers are used to calculate the pointing direction of the satellite in the first stage. A multiobjective local search algorithm is introduced to schedule tasks in each selected cluster in the second stage. Considering the time-dependent property of the transition time, the problem of determining the start observation time is transformed into linear programming in a proposed insertion operator that guarantees the feasibility of generated solutions. Two types of instances are created and tested to demonstrate the effectiveness of the proposed method, and some analyses are conducted based on the experimental results.

关键词： Search algorithm optimization algorithm Multi Objective Evolutionary algorithms Computing and Informatics Computer Graphics Earth Observation Satellite

来源：评论

学校读者我要写书评

暂无评论

Distributionally robust system identification for continuous fermentation nonlinear switched system under moment uncertainty of experimental data

引用

APPLIED MATHEMATICAL MODELLING 2024年 127卷 679-695页

作者： Yuan, Jinlong Lin, Sida Zhang, Shaoxing Liu, Chongyang Dalian Maritime Univ Sch Sci Dept Appl Math Dalian 116026 Peoples R China Shandong Technol & Business Univ Sch Math & Informat Sci Yantai 264005 Peoples R China

In this paper, we consider a nonlinear switched dynamical system (NSDS) with unknown system parameters in the context of uncertain experimental data. This system is employed to model the continuous fermentation for the production of 1,3-propanediol through glycerol bioconversion. The uncertain experimental data points are regarded as stochastic variables and only their first-order moment information of the probability distributions is available. The target of this paper is to optimize these system parameters under the environment of uncertain experimental data. Taking these factors into account, we propose a distributionally robust system identification (DRSI) problem (i.e., a bi-level system identification problem) governed by the NSDS. The objective functional comprises two level objectives: (i) the inner-level objective aims to maximize the expectation of the relative error between the solution of the NSDS and the uncertain experimental data with respect to their probability distributions at approximately stable time;and (ii) the outer-level objective is to minimize the expectation with respect to these system parameters. The DRSI problem is equivalently transformed into a single-level system identification (SLSI) problem with non-smooth term through the application of the duality theory in the probability space. A smoothing technique is employed to approximate the non-smooth term in the SLSI problem. Subsequently, an error analysis of the employed smoothing technique is derived. The gradients of the objective functional in the SLSI with respect to these system parameters are obtained. An optimization algorithm is designed to solve the SLSI problem. Finally, the paper concludes with simulation results.

关键词： Distributionally robust system identification Uncertain experimental data Switched dynamical system Error analysis optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A Tutorial on Inverse Design Methods for Metasurfaces

引用

CURRENT OPTICS AND PHOTONICS 2024年第6期8卷 531-544页

作者： Jeong, Jin-Young Latif, Sabiha So, Sunae Korea Univ Dept Control & Instrumentat Engn Sejong 30019 South Korea Korea Univ Inst Photon & Mat Sejong 30019 South Korea

This paper provides a tutorial on inverse design approaches for metasurfaces with a systematic analysis of the fundamental methodologies and underlying principles for achieving targeted optical properties. Traditionally, metasurfaces have been designed with extensive trial-and-error methods using analytical modeling and numerical simulations. However, as metasurface complexity grows, these conventional techniques become increasingly inefficient in exploring the vast design space. Recently, machine learning and optimization algorithms have emerged as powerful tools for overcoming these challenges and enabling more efficient and accurate inverse design. We begin by introducing the fundamentals of optical simulations used for forward modeling of metasurfaces and their relevance to inverse design. Next, we explore recent advancements in applying machine learning techniques such as neural networks, Markov decision processes, and Monte Carlo simulations, as well as optimization algorithms, including automatic differentiation, the adjoint method, genetic algorithms, and particle swarm optimizations, and show their potential to revolutionize the metasurface design process. Finally, we conclude with a summary of key findings and insights from this review.

关键词： Inverse design Machine learning Metasurface optimization 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：