CFRP加固高强混凝土柱抗剪性能的分析研究

利用碳纤维改善混凝土结构的抗剪性能是一种有效的加固方法。通过试验和有限元分析方法对碳纤维布改善高强混凝土柱的抗剪性能进行了分析研究。考虑了轴压比、纤维布粘贴方式、纤维布用量对加固效果的影响。试验结果表明,加固后柱的承载力得到提高,延性得到改善。有限元分析结果与试验结果吻合较好,试件的抗剪性能在用碳纤维布加固后得到了明显提高,验证了碳纤维抗剪加固方法的有效性,说明了分析中合理采用有限元模型,可以较好地预测碳纤维加固混凝土柱抗剪受力性能,为今后进行相关的有限元分析提供参考。     

碳纤维布加固混凝土桥面板受弯性能试验研究

通过碳纤维布加固混凝土梁和未加固梁模型的受弯性能对比试验 ,研究了初始弯矩大小对极限承载力、刚度、裂缝形态的影响 ,为碳纤维布加固混凝土桥面板工程的实际应用提供了依据     

碳纤维布加固达到承载力极限状态混凝土梁有限元分析

我国建筑物基数较大,其中一些建筑物的部分构件可能已经达到了极限承载力状态,对于此类构件的加固是非常重要的。碳纤维布作为一种新型材料对混凝土梁的加固有良好的效果。为了更好地研究分析碳纤维布加固达到承载力极限状态混凝土梁的力学性能,本文利用有限元软件ANSYS对试验梁的抗弯性能进行模拟分析,在试验的基础上,建立分析模型,并通过单元生死来实现粘贴碳纤维布的过程。ANSYS分析结果与试验结果基本一致,以此确定了ANSYS软件的可行性。以该模型为基础,在混凝土梁达到承载力极限状态之后,通过改变卸载程度的大小发现,卸载越多,碳纤维布的加固效果越好。     

碳纤维布加固钢筋混凝土圆柱的轴心受压试验研究

通过对钢筋混凝土圆柱模型缠绕碳纤维布的轴心受压试验研究 ,详细介绍了用碳纤维布加固后的圆柱破坏特征 ,其受力性能及破坏机理 ,碳纤维布约束混凝土与钢筋及钢管约束混凝土的差异。并提出了用碳纤维加固钢筋混凝土柱的轴心受压承载力计算方法。     

碳纤维布加固钢纤维混凝土梁的受弯性能试验研究

对碳纤维布加固钢纤维混凝土梁的受弯性能进行了试验研究。试验结果表明，用碳纤维布加固钢纤维混凝土梁可以充分发挥碳纤维布和钢纤维两种材料的性能，使受弯承载力明显提高。根据试验结果和理论分析，提出了一种简化的碳纤维布加固钢纤维混凝土梁的受弯承载力计算方法。经过对比，计算结果与试验结果具有较好的吻合性。     

碳纤维布加固混凝土柱的斜截面受剪承载力计算

碳纤维布加固混凝土结构是一种新型结构加固方法。本文进行了６个碳纤维布加固混凝土柱和一个对比混凝土柱的受剪试验研究,分析了碳纤维布的受剪加固机理及其影响碳纤维布受剪加固效果的因素。试验研究表明,碳纤维布受剪系数ν与碳纤维配箍特征值λ_（ＣＦＳ）、剪跨比和轴压比等因素有关。根据试验结果分析,提出了碳纤维布受剪系数ν的计算方法和碳纤维布加固混凝土柱受剪承载力计算公式,计算值与试验值吻合较好。     

碳纤维布加固小偏压钢筋混凝土柱承载力分析

通过对3根碳纤维布加固小偏压钢筋混凝土柱及对比柱的静载试验和理论分析，表明采用横向缠绕碳纤维布加固后小偏压柱的极限承载力有不同程度的提高，变形能力得到改善。横向碳纤维约束了混凝土的变形，提高了混凝土的极限抗压强度。提出了碳纤维加固小偏压柱的承载力计算公式和设计建议。     

碳纤维布加固钢筋混凝土梁受弯剥离承载力计算

碳纤维布加固混凝土结构技术的研究近年来发展很快。在已有试验结果分析的基础上 ,本文对碳纤维布加固钢筋混凝土梁受弯剥离的破坏形态进行了研究 ,通过粘结区域各种应力的解析 ,提出了剥离破坏的数学判据 ,以此建立了相应的剥离承载力计算方法 ,该方法中考虑了粘结正应力和剪应力的综合作用。经与试验结果的比较 ,证明本文方法计算碳纤维布加固钢筋混凝土梁受弯剥离承载力具有较高的精度 ,从而完善了碳纤维布加固混凝土梁的设计理论。     

碳纤维布加固钢筋混凝土圆柱的试验研究

用碳纤维布加固混凝土结构是一种优点多,效果明显的加固新方法。本文采用碳纤维布,分别对未加载的钢筋混凝土圆柱及加载至开裂的钢筋混凝土圆柱进行加圆,通过试验了研究纤维环箍加固对钢筋混凝土圆柱在轴心受压情况下极限承载力的提高程度,并对碳纤维布加固的混凝土圆柱的受力特点及影响承载力的因素作了分析。     

碳纤维加固混凝土偏压柱正截面承载力研究

从理论上分析了碳纤维布加固混凝土偏压柱的受力状态,并在基本假定的基础上推导出了碳纤维布加固偏压柱的承载力计算公式。并通过对比计算得出碳纤维布适合用于加固混凝土小偏压柱（其抗压承载力最大可提高1.64倍）,并不适合用于加固混凝土大偏压柱。     

地下水动态预报模型的精度评价

本文提出了地下水动态预报模型的精度检验指标和评价标准，它是全面评价预报模型的预报可靠性和预报精度的依据。     

改进的 BP 神经网络在混凝土碳化深度预测中的应用

通过对混凝土碳化深度实测资料的分析,建立了基于 BP 神经网络原理的混凝土碳化深度预测方法.由于传统的 BP 神经网络有收敛慢,易陷入局部极小点的问题,采用改进的 BP 神经网络,通过与混凝土碳化深度的实测值、理论值的对比,证明了该方法在混凝土碳化深度预测方面的有效性并且具有令人满意的精度。     

基于神经网络方法的钢筋混凝土双筋植筋的锚固性能研究

通过试验资料分析,建立了基于神经网络方法的钢筋混凝土双筋植筋的锚固性能预测的BP算法结构模型,通过模型预测值与试验结果的比较,证明了该模型的有效性和精度可以用于预测钢筋混凝土双筋植筋的锚固性能,最后,对其影响因素进行了初步分析.     

大型地下厂房三种涌水量预测模型分析

在地下工程开挖过程中,地下涌水量对施工人员的安全及工程的安全性有较大的影响。由于地下涌水量的影响因素复杂且呈非线性关系,为了能更准确地预测涌水量,采用某大型厂房地下涌水量的原始数据,通过对地下涌水量建立灰色预测模型、回归预测模型以及时间序列预测模型,预测出地下涌水量的发展趋势,对比分析表格数据、图表特征以及预测精度,得出灰色预测模型预测效果最佳。研究表明,灰色预测模型可以在较少数据的基础上达到合理预测的目的。研究结果可对工程安全提供参考,为类似工程提供借鉴。     

黄茨滑坡预测预报分析

在介绍了黄茨滑坡地质概况的基础上,简要介绍了滑坡预测预报理论与方法,既而引入基于位移信息的Verhulst灰色模型和日本斋藤的蠕变模型两种方法对黄茨滑坡进行了预测预报系统分析。     

肋筋模板钢-混凝土组合板承载力的试验研究

针对一种新型的组合板———肋筋模板钢 -混凝土组合板 (以下简称肋筋模板组合板 ) ,进行了 39块板的试验研究。分析了这种组合板在施工阶段的承载能力、稳定性及破坏形式 ,以及在使用阶段不考虑底模作用时的荷载 -变形关系、钢材和混凝土的应变和裂缝的发展等。试验结果表明 :肋筋模板组合板在施工阶段具有良好的稳定性 ,在使用阶段具有较高的承载力和良好的延性 ,即肋筋模板组合板具有较好的工作性能。     

神经网络在配制高强预拌泵送混凝土中的应用

基于人工神经网络的原理 ,提出了解决高强预拌泵送混凝土配制问题的BP神经网络方法 ,据此开发的混凝土配合比设计应用软件 ,能较好地进行强度及流动性能的预测     

Novel high-precision grey forecasting model

Although the grey forecasting model has been successfully utilized in many fields and demonstrated promising results, literatures show its performance still could be improved. For this purpose, this paper proposes a novel forecasting model termed MFGMn(1,1). In this proposed model, this work modifies the algorithm of the grey forecasting model to enhance the tendency catching ability. Besides, Fourier series and Markov chain also integrated within MFGMn(1,1) to model the system periodic and stochastic phenomenon for further improving the forecasting precision. Two practical cases, the typhoon rainfall events and steel price fluctuations, are adopted for demonstration. As shown in simulation results, the proposed model can increase the prediction accuracy. Particularly when the system is instable, MFGMn(1,1) can effectively predict the system developing.     

A Decision Support Model for Construction Cash Flow Management

Abstract: The excessive level of construction business failures and their association with financial difficulties has placed financial management in the forefront of many business imperatives. This has highlighted the importance of cash flow forecasting and management that has given rise to the development of several forecasting models. The traditional approach to the use of project financial models has been largely a project‐oriented perspective. However, the dominating role of “project economics” in shaping “corporate economics” tends to place the corporate strategy at the mercy of the projects. This article approaches the concept of cash flow forecasting and management from a fresh perspective. Here, the use of forecasting models is extended beyond their traditional role as a guideline for monitoring and control of progress. They are regarded as tools for driving the project in the direction of corporate goals. The work is based on the premise that the main parties could negotiate the terms and attempt to complement their priorities. As part of this approach, a model is proposed for forecasting and management of project cash flow. The mathematical component of the model integrates three modules: an exponential and two fourth‐degree polynomials. The model generates a forecast by potentially combining the outcome of data analysis with the experience and knowledge of the forecaster/organization. In light of corporate objectives, the generated forecast is then manipulated and replaced by a range of favorable but realistic cash flow profiles. Finally, through a negotiation with other parties, a compromised favorable cash flow is achieved. This article will describe the novel way the model is used as a decision support tool. Although the structure of the model and its mathematical components are described in detail, the data processing and analysis parts are briefly described and referenced accordingly. The viability of the model and the approach are demonstrated by means of a scenario.     

Forecasting the sales of precast concrete building products

Sales of precast concrete building products are influenced by the general demand for construction. This demand is subject to substantial fluctuations, caused by such diverse factors as capital spending by Government, the general strength of the economy, the demand for housing — which in turn reflects mortgage interest rates -and also by seasonal factors and weather. These are some of the difficulties associated with sales forecasting in the precast concrete industry. Sales forecasting is crucial managerial practice and its accuracy is vital for any company's business survival. A survey of the current forecasting and planning practices in the industry concluded that forecasting, especially for major product groups, is fairly basic and not reliable. Against this background, a forecasting model has been developed to analyse historical data and forecast demand for 12 months ahead. Two forecasting methods were applied to historical data of 12 groups of products of a major manufacturer. The results of the forecasting model were encouraging and more accurate than the manufacturer's existing forecasting system. The authors interviewed the firm's marketing and sales staff to identify the advantages and disadvantages of the forecasting system and identify the factors which affect sales and forecasting in general. Some tangible indication of the practical use of this work is the support given to this research project by staff of this company, at all levels. The work described in this paper is part of a more general computerized capacity planning system for the precast industry. This would be suitable for major companies, most of whom produce a large number of different products in a number of different manufacturing plants dispersed throughout the UK.