VRV系统并联型压缩机油平衡策略研究

针对直流变频变容量VRV空调系统中并联压缩机间润滑油平衡问题,概述了不同厂家并联型压缩机润滑油平衡策略。并根据不同的压缩机,设计了并联压缩机之间的油平衡系统。     

大型非线性转子-密封-轴承系统的不平衡响应与稳定性

对实际大型汽轮机转子-密封-轴承系统建立了具有超大规模维数的非线性动力学模型,该模型考虑了密封的非线性激振力、可倾瓦轴承的弹性支承力、转子的阻尼力、不平衡质量力和重力.采用Newmark方法对其进行数值求解,模拟出转子升速过程中汽流激振现象的典型特征和发生汽流激振的失稳转速,并且得到系统参数对转子不平衡响应和稳定性的影响规律.结果表明:适当的增大转子的阻尼、密封的半径间隙和密封流体轴向流速可提高转子发生汽流激振的失稳转速,这为在设计和运行中提高实际大型汽轮机转子-密封-轴承系统的稳定性提供了参考依据.     

Δ-Σ型A/D转换芯片CS5550在称重系统中的应用

介绍了△-∑型A／D转换芯片CS5550的特性以及在称重系统中的典型应用。     

DEH数字电液调节系统在CC50-8.83/0.981/0.118型汽轮机上的应用

本文着重介绍了DEH-ⅢA型纯电液调节系统的优越性及在国产CC50-8.83/0.981/0.118型汽轮机液压调节系统上实施改造的具体情况,并针对改造后暴露出来的问题提出了解决办法。     

数据网格资源选择优化模型

为了满足网格数据服务的可靠性和传输时间约束,同时兼顾网络负载及节点资源的有效利用,提出了一种网格数据资源选择优化模型,该模型以网络负载和资源代价为优化目标函数,以节点的传输速度、可靠性、传输距离、网络状态、客户端带宽和容忍度阈值为输入,进而决策出参与服务的最优节点集合,同时模型中设定了权重因子来均衡网络负载与资源代价....     

一种面向应用的光子网格资源联合分配策略

基于对业务驱动的光子网格系统的研究,提出了一种面向应用的光子网格服务提供模型,它将应用资源和光网络资源看作对等的实体,并将其抽象和封装为网格可以控制和共享的服务.基于对光子网格资源分配问题的研究,提出了一种用于资源联合分配的最小代价策略,它从最小化作业执行代价的角度解决了应用资源和光网络资源的联合分配问题.构建光子网格实验平台,并以网格计算业务在分布式岩心图像处理中的应用为例,对资源分配策略进行实验分析.结果表明,最小代价策略能够降低光子网格系统的业务阻塞率和平均处理时间,优化网格应用资源和光网络资源的使用.     

Optimal resource allocation on grid systems for maximizing service reliability using a genetic algorithm

Grid computing system is different from conventional distributed computing systems by its focus on large-scale resource sharing and open architecture for services. The global grid technologies and the Globus Toolkit in particular, are evolving toward an open grid service architecture (OGSA) with which a grid system provides an extensible infrastructure so that various organizations can offer their own services and integrate their resources. Hence, this paper aims at solving the problem of optimally allocating services on the grid to maximize the grid service reliability. Since no existing study has analyzed the grid service reliability, this paper develops initial modeling and evaluation algorithms to evaluate the grid service reliability. Based on the grid service reliability evaluation, we present an optimization model for the grid service allocation problem and develop a genetic algorithm (GA) to effectively solve it. A numerical example is given to show the modeling procedures and efficiency of the GAs.     

Comparison of distributed methods for resource allocation

Resource allocation problems aim to achieve certain goals or objectives by allocating resources. Traditionally, centralized methods are applied to such problems. However, the inherent, decentralized nature of many corporates/companies/factories drives the investigation on decentralized or distributed methods. This paper provides an overview of research activities in the field of distributed methods for resource allocation problems. We concentrate on classifying the resource allocation problems, comparing different methods and discussing how these different methods can be applied to the problems. Finally, a range of open issues and future challenges are highlighted.     

A network flow algorithm for optimal resource allocation

This paper introduces a network flow method for manpower scheduling and resource allocation. The network formulation of the problem permits the development of an algorithm that determines the minimal flow of resources through the network. The method presented here corresponds to the Simplex method, for in both methods the value of the objective function is optimized while the capacity limitations are preserved. The procedure proposed here, however, uses a more economical problem representation and is computationally more efficient. The efficacy of the minimal flow algorithm and its use is illustrated for a production system but the applicability of the procedure is sufficiently broad for it to work in other problem situations just as well.     

Cost optimal segregated targeting for resource allocation networks

In this paper, a generalised methodology is proposed to target cost optimal allocation of resources in segregated targeting problems. Cost optimal segregated targeting problems are characterised by the existence of multiple zones; each consisting of a set of demands and using a unique resource with given cost and a single quality index (e.g., emissions factor, contaminant concentrations, etc.). All these zones share a common set of internal sources. This paper presents a rigorous mathematical proof of the decomposition principle that decomposes the problem into a sequence of sub-problems. Decomposition of the original problem is performed based on the prioritised costs for each external resource, attached to a particular zone. Prioritised cost of a resource depends on the pinch quality, quality of the resource and its cost. Applicability of the proposed methodology is illustrated by examples from carbon-constrained energy planning and water allocation networks.     

一个面向异构多核处理器Cell的资源分配模型

为了充分利用多核处理器提供的多级并行和解决多核资源分配问题,提出了一种将多任务并行程序映射到多核处理器平台上的模型驱动的方法。该方法首先创建一个三维优化空间来表示资源分配配置,而后通过搜索该空间为应用生成多种并行机制,最后对各种并行机制进行静态评估从而找出最优的机制。该方法同时考虑了任务并行、数据并行以及通讯开销。在异构多核处理器Cell上利用一个图像处理应用对此方法进行了测试。实验表明,这种模型驱动的方法能够很好地评估性能并为应用确定有效的并行机制。     

Sequential resource allocation utilizing agents

Many manufacturing systems allocate resources, such as machines, sequentially. Sequential allocation of resources can be viewed as a digraph where each vertex represents resources forming nodes in a distributed system and the arcs represent the allocation. The allocation of such resources can be considered to be a distributed problem. Agents are a distributed artificial intelligence paradigm applicable to distributed problems and, therefore, have a potential to be applicable to sequential resource allocation. This paper presents a method of sequential resource allocation utilizing agents, and an AGV system is presented as an example application area. This system was utilized in experiments to test the agent application. Results and an analysis are also presented.     

Optimal resource allocation for multicast sessions in multi-hop wireless networks

In this paper, we extend recent results on fair and stable resource allocation in wireless networks to include multicast sessions, in particular multi-rate multicast. The solution for multi-rate multicast is based on scheduling virtual (shadow) 'traffic' that 'moves' in reverse direction from destinations to sources. This shadow scheduling algorithm can also be used to control delays in wireless networks.     

A bi-objective robust model for emergency resource allocation under uncertainty

Emergency resource allocation constitutes one of the most critical elements of response operations in the field of emergency management. This paper addresses an emergency resource allocation problem which involves multiple competing affected areas and one relief resource centre under supply shortage and uncertainty in the post-disaster phase. In humanitarian situations, both the efficiency and fairness of an allocation policy have a considerable influence on the effectiveness of emergency response operations. Thus, we formulate a bi-objective robust emergency resource allocation (BRERA) model which tries to maximise efficiency as well as fairness under different sources of uncertainties. To obtain decision-makers’ most preferred allocation policy, we propose a novel emergency resource allocation decision method which consists of three steps: (1) develop a bi-objective heuristic particle swarm optimisation algorithm to search the Pareto frontier of the BRERA model; (2) select a coefficient to measure fairness; and (3) establish a decision method based on decision-makers’ preference restricted by the fairness coefficient. Finally, a real case study taken from the 5 December 2008 Wenchuan Earthquake demonstrates the effectiveness of the proposed method through numerical results. The solution and model robustness are also analysed.