基于有限元的大型风力发电机轮毂的分析研究

本文中,通过UG软件的三维绘图功能创建了750KW大型风力机轮毂的实体模型,并采用有限元进行了静力学结构分析。计算出了轮毂的最大应力和最大应变。经过校核可知,最大值在材料的许用范围内。分析结果表明,通过ANSYS软件分析的结果与实际情况很接近。本文为后续设计出高性能的大型风机轮毂以及大型风力发电机机组的设计、优化提供一定的设计依据。     

Identification of key genes and expression profiles in osteoarthritis by co-expressed network analysis

BackgroundThe underlying molecular characteristics of osteoarthritis (OA), a common age-related joint disease, remains elusive. Here, we aimed to identify potential early diagnostic biomarkers and elucidate underlying mechanisms of OA using weighted gene co-expression network analysis (WGCNA).Material and methodsWe obtained the gene expression profile dataset GSE55235, GSE55457, and GSE55584, from the Gene Expression Omnibus. WGCNA was used to investigate the changes in co-expressed genes between normal and OA synovial membrane samples. Modules that were highly correlated to OA were subjected to functional enrichment analysis using the R clusterProfiler package. Differentially expressed genes (DEGs) between the two samples were screened using the “limma” package in R. A Venn diagram was constructed to intersect the genes in significant modules and DEGs. RT -PCR was used to further verify the hub gene expression levels between normal and OA samples.ResultsThe preserved significant module was found to be highly associated with OA development and progression (P < 1e-200, correlation = 0.92). Functional enrichment analysis suggested that the antiquewhite4 module was highly correlated to FoxO signaling pathway, and the metabolism of fatty acids and 2-oxocarboxylic acid. A total of 13 hub genes were identified based on significant module network topology and DEG analysis, and RT-PCR confirmed that these genes were significantly increased in OA samples compared with that in normal samples.ConclusionsWe identified 13 hub genes correlated to the development and progression of OA, which may provide new biomarkers and drug targets for OA.     

A note on “Location of hubs in a competitive environment”

This note suggests modifications to two models for locating hubs in a competitive environment introduced by Marianov et al. [European Journal of Operational Research 114 (1999) 363–371]. They make it possible to provide optimal solutions much faster. It is also shown that the implementation of the heuristic proposed by Marianov et al. contains a flaw. Yet the heuristic itself is correct.     

机房局域网组建系统方案探析

本文介绍了不同配置的微机机房中,基于Ethernet的组建系统方案,可实现Client端快速登录共享服务器资源、提高低档微机利用价值的目的。     

Uncapacitated Euclidean Hub Location: Strengthened Formulation,New Facets and a Relax-and-cut Algorithm

The multiple allocation uncapacitated hub location problem is considered. This problem arises in transportation systems when several locations send and receive passengers and/or express packages and the performance of these systems can be improved by using transshipment points (hubs), where the passengers/packages are collected and distributed. An Integer Programming formulation, the one giving the best computational results until now, serves as a basis for the solution method. Using the fact that the transportation costs between hubs satisfy the triangle inequality, an analysis of the set of solutions that are not candidates to be optimal is carried out and, as a consequence, the formulation of the problem can be strengthened by means of powerful valid inequalities obtained through the study of the intersection graph of an associated set packing problem. The algorithm developed uses the most promising of these inequalities in a Lagrangian relaxation context to reduce the size of the branching tree and improve the computational times. This improvement is shown by means of a computational study, where a set of instances are optimally solved with low computational effort.     

基坑深层搅拌桩及超前钢管的施工与质量控制

以广东移动通信枢纽大楼的基坑支护为例，介绍基坑深层搅拌桩和超前钢管的施工及质量控制。     

Hub and spoke network design with single-assignment,capacity decisions and balancing requirements

In this paper, an extension of the capacitated single-allocation hub location problem is considered in which the capacity of the hubs is part of the decision making process and balancing requirements are imposed on the network. The decisions to be made comprise (i) the selection of the hubs, (ii) the allocation of the spoke nodes to the hubs, (iii) the flow distribution through the sub network defined by the hubs and (iv) the capacity level at which each hub should operate. In the latter case, for each potential hub, a set of available capacities is considered among which one can be chosen. The objective is to minimize the total cost, which includes the setup cost for the hubs as well as the flow routing cost. Economies of scale are assumed for the costs. Balancing requirements are imposed to the network. In particular, a value is considered for the maximum difference between the maximum and minimum number of spoke nodes that are allocated to the hubs. Two mixed-integer linear programming formulations are proposed and analyzed for this problem. The results of a set of computational experiments using an off-the-shelf commercial solver are presented. These tests aim at evaluate the possibility of solving the problem to optimality using such a solver with a particular emphasis to the impact of the balancing requirements. The tests also allow an analysis of the gap of the bounds provided by linear relaxation.     

An aggregate stochastic programming model for air traffic flow management

In this paper, we present an aggregate mathematical model for air traffic flow management (ATFM), a problem of great concern both in Europe and in the United States. The model extends previous approaches by simultaneously taking into account three important issues: (i) the model explicitly incorporates uncertainty in the airport capacities; (ii) it also considers the trade-off between airport arrivals and departures, which is a crucial issue in any hub airport; and (iii) it takes into account the interactions between different hubs.The level of aggregation proposed for the mathematical model allows us to solve realistic size instances with a commercial solver on a PC. Moreover it allows us to compute solutions which are perfectly consistent with the Collaborative Decision-Making (CDM) procedure in ATFM, widely adopted in the USA and which is currently receiving a lot of attention in Europe. In fact, the proposed model suggests the number of flights that should be delayed, a decision that belongs to the ATFM Authority, rather than assigning delays to individual aircraft.     

Stochastic uncapacitated hub location

We study stochastic uncapacitated hub location problems in which uncertainty is associated to demands and transportation costs. We show that the stochastic problems with uncertain demands or dependent transportation costs are equivalent to their associated deterministic expected value problem (EVP), in which random variables are replaced by their expectations. In the case of uncertain independent transportation costs, the corresponding stochastic problem is not equivalent to its EVP and specific solution methods need to be developed. We describe a Monte-Carlo simulation-based algorithm that integrates a sample average approximation scheme with a Benders decomposition algorithm to solve problems having stochastic independent transportation costs. Numerical results on a set of instances with up to 50 nodes are reported.     

Allocation strategies in hub networks

In this paper, we study allocation strategies and their effects on total routing costs in hub networks. Given a set of nodes with pairwise traffic demands, the p-hub median problem is the problem of choosing p nodes as hub locations and routing traffic through these hubs at minimum cost. This problem has two versions; in single allocation problems, each node can send and receive traffic through a single hub, whereas in multiple allocation problems, there is no such restriction and a node may send and receive its traffic through all p hubs. This results in high fixed costs and complicated networks. In this study, we introduce the r-allocation p-hub median problem, where each node can be connected to at most r hubs. This new problem generalizes the two versions of the p-hub median problem. We derive mixed-integer programming formulations for this problem and perform a computational study using well-known datasets. For these datasets, we conclude that single allocation solutions are considerably more expensive than multiple allocation solutions, but significant savings can be achieved by allowing nodes to be allocated to two or three hubs rather than one. We also present models for variations of this problem with service quality considerations, flow thresholds, and non-stop service.