基于拓扑优化的某航天产品支架结构设计与试验验证

本文利用拓扑优化技术对某航天产品的支架结构进行拓扑寻优,找到了结构最佳传力路径,设计了满足重量要求情况下基频最大的支架结构。最终产品基频能够满足要求,而且仿真与试验结果呈现较好的一致性,达到了节省研制周期和成本的目的,表明了文中所述方法的合理有效性。     

岛屿地形下的核电厂护岸防洪设计研究

对国内第一个岛屿地形下核电厂的护岸防洪设计进行了研究,提出直立式护岸结构方案以满足核电厂防洪和避让毗邻海岛的要求。在波浪数值模拟计算结果基础上,开展了波浪整体物理模型试验、波浪局部整体物理模型试验和波浪断面物理模型试验,对护岸的越浪量和结构稳定性进行了优化验证。研究结果表明,岛屿地形下,波浪破碎和波能集中导致护岸堤身坡脚处波高增大,须加高挡浪墙和优化挡浪墙结构型式;在相同的越浪量标准下,采用直立堤结构相对斜坡堤结构对应的护岸挡浪墙的高程须明显加高;利用部分海岛地形斜坡高地作为厂区护岸一部分时,原状海岛地形斜坡高地处的波浪爬高效应明显,须加高邻近护岸挡浪墙的高程。     

韦伯-费希纳定律在区域生态环境质量评价中的应用

文章利用韦伯-费希纳定律建立区域生态环境评价的新模型,并通过实例研究了区域生态环境质量状况,即巢湖流域总体以及分区巢湖市、六安市的生态环境质量为Ⅵ级、分区合肥市为Ⅲ级。与未确知测度评价方法进行比较,取得了满意的结果,实例应用表明:该评价模型结构严谨,评价结果合理,为区域生态环境质量评价提供了一种简单而适用的评价方法。     

海拔对局部放电特性的影响

高压电气设备的绝缘结构长期处于工作场强作用下，在全部寿命期存在着一定强度的局部放电。局部放电测量及局部放电对设备的危害程度受海拔的影响较大。本文以６ｋＶ级高压电机线棒的局部放电特性随海拔变化的模拟试验结果，从理论上分析海拔对局部放电特性的影响，提出对局部放电测量进行海拔修正的建议，为高压电气设备的设计制造提供基础资料。     

基于Kriging模型的载人航天某装置结构优化设计研究

对于处在振动环境中的载人航天某装置复杂结构,设计过程中存在最小化质量、同时最大化一阶整体振动频率的多目标优化问题,可以利用多目标遗传算法(NSGA-II)求解得到Pareto最优解集,但利用NSGA-II进行求解计算量大,对于复杂结构更甚。为了节省计算时间,提出基于Kriging代理模型的复杂结构多目标优化设计方法,首先通过拉丁超立方采样获得样本点,然后通过样本点创建Kriging模型,最后利用多目标遗传算法求解代理模型得到Pareto最优解集,方便设计师从中选择最优解,优化结果表明本文所述方法合理有效。     

某车载大型相控阵天线支架多工况拓扑优化设计

为满足某车载大型相控阵天线支架在风载荷、振动和冲击试验刚度要求基础上实现支架的轻量化设计，基于变密度法以4种载荷工况下的支架重量为目标，以装配关系为约束条件对支架进行拓扑优化研究。根据相控阵天线支架的装机空间和可装配性设计支架初始三维模型，结合工程可行性分析和多工况拓扑优化形成天线支架结构设计方法，并对优化后的天线支架进行风载荷、振动和冲击强度校核。结果表明，采用该方法优化后的支架结构在满足力学环境使用条件下，重量仅为初始设计的58%，满足设计要求，该方法工程应用前景广阔。     

成渝经济区旅游发展效率测度及其影响因素研究

利用DEA分析方法,测度了成渝经济区2010—2015年的旅游发展效率;通过Malmquist指数分析全要素生产率变动,建立面板模型验证了旅游发展效率的影响因素及其作用强度。研究表明:成渝经济区综合效率总体呈现出波动中曲折上升的发展趋势,纯技术效率下降,主要依靠规模效率提升;2012年综合效率呈负增长,短时间内大量资源和技术的涌入没有得到有效利用;旅游发展全要素生产率增长率得益于技术进步、规模效率的整体提高;经济发展水平、政府对旅游经济的干预程度、产业结构、交通便利程度、城市化水平对旅游发展效率均有积极影响。根据实证结果提出发挥政府旅游调控职能、优化旅游产业结构、完善旅游交通体系、优化资源投放结构、提高经济发展水平、刺激旅游消费需求等建议。     

袋式除尘器结构优化设计与虚拟装配关键技术

针对袋式除尘器大型化后在结构轻质化、模块化结构的可靠装配和焊接变形控制等方面面临的诸多问题,开展了系统的研究,发展了不同结构类型袋式除尘器快速参数化建模、整体和局部联合计算、梁柱连接节点的简化设计、整体计算中复杂花板结构简化、非线性多约束结构优化等复杂关键技术,开发了袋式除尘器结构计算和优化设计软件;提出了基于世界树的实体层次系统结构建模框架,开发了大型模块化袋式除尘器虚拟装配软件;分析了主要结构焊接变形、应力和应变分布及变化规律,提出了反变形法消除焊接变形的控制方法,并开展了实验验证。     

游客感知视角下的城市夜间旅游形象结构研究——以广州市为例北大核心

夜间旅游是当代旅游发展理论体系中重要的研究领域。以旅游形象结构为理论基础,以广州夜间旅游为例,利用805份游客调查问卷,采用质性与量化研究方法探讨城市夜间旅游形象结构。结果表明:水上夜游、灯光节庆活动、景观塔夜游、休闲街区夜游和夜市美食游成为游客最喜爱和最常游的广州夜间旅游产品。城市夜间旅游形象结构由“认知形象—氛围形象—情感形象—意动形象”组成,其中:认知形象包括视觉形象、物质经济形象、自然环境形象、人文环境形象、物理空间形象和整体感官形象6个维度,以整体感官形象和物质经济形象最为突出;氛围形象和情感形象以正面为主,表明游客认为广州夜间旅游具有良好的氛围及情感。最后,从完善城市夜游政策体系、优化夜游发展宏观环境、构建夜游多核空间格局等方面提出优化城市夜间旅游形象的建议。     

游客感知视角下的城市夜间旅游形象结构研究——以广州市为例北大核心

夜间旅游是当代旅游发展理论体系中重要的研究领域。以旅游形象结构为理论基础,以广州夜间旅游为例,利用805份游客调查问卷,采用质性与量化研究方法探讨城市夜间旅游形象结构。结果表明:水上夜游、灯光节庆活动、景观塔夜游、休闲街区夜游和夜市美食游成为游客最喜爱和最常游的广州夜间旅游产品。城市夜间旅游形象结构由“认知形象—氛围形象—情感形象—意动形象”组成,其中:认知形象包括视觉形象、物质经济形象、自然环境形象、人文环境形象、物理空间形象和整体感官形象6个维度,以整体感官形象和物质经济形象最为突出;氛围形象和情感形象以正面为主,表明游客认为广州夜间旅游具有良好的氛围及情感。最后,从完善城市夜游政策体系、优化夜游发展宏观环境、构建夜游多核空间格局等方面提出优化城市夜间旅游形象的建议。     

基于水资源环境承载力约束的工业结构调整模型研究——以辽河上游铁岭段为例

根据2006年铁岭市工业各行业的结构特点及各行业对水环境的污染特点，建立水资源环境承载力的工业结构多目标优化模型，选取工业生产总值最大及废水和COD、NH3-N排放量最小作为优化目标，对模型进行计算，量化铁岭市2010年工业结构指标，选择出符合铁岭经济发展“十一五”规划目标和环境保护目标工业结构优化方案，获得既符合经济发展目标又满足水环境保护要求的合理工业结构，提供可借鉴的思路和方法。     

Optimum Heat Conductance Distribution for Power Optimization of a Regenerated Closed Brayton Cycle

In this paper, the power output of the cycle is taken as objective for performance optimization of an irreversible regenerated closed Brayton cycle coupled to constant-temperature thermal energy reservoirs in the viewpoint of finite time thermodynamics (FTT) or entropy generation minimization (EGM). The analytical formulae about the relations between power output and pressure ratio are derived with the heat resistance losses in the hot- and cold-side heat exchangers and the regenerator, the irreversible compression and expansion losses in the compressor and turbine, and the pressure drop loss in the piping. The maximum power output optimization is performed by searching the optimum heat conductance distribution corresponding to the optimum power output among the hot- and cold-side heat exchangers and the regenerator for the fixed total heat exchanger inventory. The influence of some design parameters, including the temperature ratio of the heat reservoirs, the total heat exchanger inventory, the efficiencies of the compressor and the turbine, and the pressure recovery coefficient, on the optimum heat conductance distribution and the maximum power output are provided. The power plant design with optimization leads to smaller size including the compressor, turbine, and the hot- and cold-side heat exchangers and the regenerator.     

滇西北地区特色经济的发展与产业结构优化研究

特色经济是发挥地区资源优势的主要途径,产业结构优化是区域经济稳定发展的保证。通过分析滇西北地区产业结构现状和发展特色经济的优势条件以及存在的问题,分析了特色经济的发展与产业结构优化之间的互动关系,进而提出发展特色经济和提升产业结构的策略。     

A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems

Hybrid renewable energy systems (HRES) turned into an appealing choice for supplying loads in remote areas. The application of smart grid principals in HRES provides a communication between the load and generation from the HRES. Using smart grid in the HRES will optimally utilize the generating resources to reschedule the loads depending on its importance. This paper presents a new proposed design and optimization simulation program for techno-economic sizing of grid-independent hybrid PV/wind/diesel/battery energy system using Cuckoo search (CS) optimization algorithm. Using of CS will help to get the global minimum cost condition and prevent the simulation to be stuck around local minimum. A new proposed simulation program (NPSP) is acquainted using CS to determine the optimum size of each component of the HRES for the lowest cost of generated energy and the lowest value of dummy energy, at highest reliability. A detailed economic methodology to obtain the price of the generated energy has been introduced. Results showed that using CS reduced the time required to obtain the optimal size with higher accuracy than other techniques used iterative techniques, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Numerous significant outcomes can be extracted from the proposed program that could help scientists and decision makers.     

Exergoeconomic Environmental Optimization of Piston-Prop Aircraft Engines

In this study, exergy, exergoeconomic, exergoenvironmental analyses, and exergoeconomic environmental optimization are applied to a four-cylinder, spark ignition, naturally aspirated and air-cooled piston-prop aircraft engine in the cruise phase of flight for the first time to the best of the authors` knowledge. Here, three piston-prop aircraft engine parameters (altitude, air–fuel ratio (AF), and rated power setting (PS)) are selected for optimization purposes. All exergy, exergoeconomic, and exergoenvironmental values are calculated first. These values are then optimized to find the best results of all analyses. The best altitude, AF ratio, and PS values are finally found while the maximum exergy efficiency, the minimum product specific environmental impact, and the minimum average unit fuel exergy cost are obtained. The best results of optimization indicated that the maximum exergy efficiency varied between 19.54% and 19.80%, the minimum unit fuel exergy cost ranged from 126.30 $/GJ to 127.23 $/GJ, and the minimum specific environmental impact of production was in the range of 8.70–9.59 mPts/MJ. Based on the results obtained, for ensuring the optimum conditions, the low AF ratios and the low-altitude flight at high rated power settings have to be selected.     

OPTIMIZING FLOOD CONTROL ALLOCATION FOR A MULTIPURPOSE RESERVOIR1

ABSTRACT. In the last decade much research has been devoted to applying the systems analysis approach to water resources problems. A popular research goal has been determination of the “best” method of operating a multipurpose reservoir. The goal of this study was to derive the economically optimum flood control diagram for a multipurpose reservoir by systems analysis. The technique employed to optimize the flood control diagram was programmed so that the optimization process could be applied to other multipurpose reservoirs. Two computer programs developed at the U.S. Army Corps of Engineers' Hydrologic Engineering Center were utilized with modifications to simulate the operation of Folsom Reservoir in central California. Economic analyses were incorporated along with an optimization technique into the reservoir operations program; and the resultant program was capable of routing a sequence of monthly reservoir inflows, computing benefits for various flood control diagrams (as dictated by the optimization procedure), and selecting the economically optimum flood control diagram. The univariate gradient technique was the optimization procedure employed. The two computer programs are on file at the Hydrologic Engineering Center in Davis, California.     

A novel objective function for optimal DG allocation in distribution systems using meta-heuristic algorithms

Meta heuristic algorithms have been introduced as a powerful method to solve the nonlinear optimization problems. These algorithms have been employed in many complex engineering problems due to their high capability in finding the solutions and reaching the optimal results within a short period of time. Optimization of distributed generation units in distribution systems, which have profoundly impacted on the system losses and voltage profile, is one of these nonlinear problems. In this study, a novel objective function was proposed for optimization procedure by meta-heuristic algorithms. The related objective function consists of the total cost of distributed generation units, cost of the purchased natural gas, cost of distribution system power losses, and penalty for greenhouse gas emissions. The electrical, cooling, and heating loads were considered in this study. In the distribution system, the waste and fuel cell were used to supply the required heating and cooling loads. The meta-heuristic algorithms including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Imperialist Competitive Algorithm (ICA) were employed to find the optimal location and size of distributed generation units in a distribution system. A detailed performance analysis was done on 13 bus radial distribution system. The performances of three algorithms were compared with each other and results showed that the PSO was the fastest; and had the best solution and optimum results. Furthermore, the PSO reached the optimum solution in a fewer number of iterations than the GA and ICA algorithms.