混凝土有效弹性模量计算模型的探讨

本文阐述了由四相球面模型分析混凝土三相复合材料的方法,考虑了集料最大粒径及其级配对混凝土有效弹性模量的影响。并介绍了两种计算方法,方法一通过计算混凝土有效体积模量求得有效弹性模量,方法二直接利用弹性理论计算混凝土有效弹性模量。有力论证了四相球面模型的合理性,最后讨论了集料最大粒径及其级配和界面过渡区性质对混凝土有效弹性模量的影响。     

溶蚀粉煤灰混凝土强度和弹性模量退化的试验研究

通过加速试验方法研究了粉煤灰混凝土抗压强度、劈裂强度和弹性模量随溶蚀时间的退化规律。在该试验中,粉煤灰掺量分别为0、10%、20%、30%。试验结果表明,粉煤灰混凝土的抗压强度、劈裂强度和弹性模量均随着溶蚀时间的延长而下降。在混凝土中加入一定量的粉煤灰,可以减小混凝土强度和弹性模量的下降率,当粉煤灰掺量为20%时,效果最佳。对于给定的溶蚀时间,粉煤灰混凝土的溶蚀深度低于普通混凝土的溶蚀深度,而且加入粉煤灰可以明显减小溶蚀混凝土中大孔的数量。     

Prediction of punching shear strength of two-way slabs

The punching shear strength of two way slabs without shear reinforcement and without unbalanced moment transfer is estimated using both neural networks and new simplified punching shear equations. An artificial neural network (ANN) was used to predict the punching shear strength of internal slab-column connections. Neural network analysis is conducted using 244 test data available in the literature and experiments conducted by the authors to evaluate the influence of concrete strength, reinforcement ratio and slab effective depth on punching shear strength. A wide range of slab thicknesses (up to 500 mm) and reinforcement ratios were used. In general, the results obtained from the neural network are very close to the experimental data available. The test results were used to develop two new simplified practical punching shear equations. The equations also showed a very good match with available experimental data. Four equations for the punching shear strength prescribed in well-known specifications were evaluated based on the available experimental results. This paper includes a discussion of the parameters of punching shear strength in the American, Canadian, British and European specifications.     

Estimation of rock modulus: For intact rocks with an artificial neural network and for rock masses with a new empirical equation

The elastic modulus of intact rock is used for many rock engineering projects, such as tunnels, slopes, and foundations, but due to the requirements of high-quality core samples and associated sophisticated test equipment, instead the use of empirical models to obtain this parameter has been an attractive research topic. In the rock mechanics literature, some empirical relations exist between the elastic modulus of intact rock and other rock properties, such as the uniaxial compressive strength (σ_ci), unit weight (γ), Schmidt hammer rebound number, point load index and petrographic composition. However, the past use of specific rock types is the main limitation of the existing empirical equations. In other words, they are not open to the general purpose use. To eliminate this deficiency, a total of 529 datasets, including uniaxial compressive strength, unit weight and elastic modulus of intact rock (E_i), were collected via an extensive literature review. In addition to these datasets, a further total of 80 datasets was obtained from laboratory tests performed on greywacke and agglomerate core samples for this study. To prepare a chart for the prediction of the elastic modulus of intact rock, an artificial neural network was constructed using the large database. In addition, after a brief overview of existing empirical equations, a new empirical equation, which considers RMR and the elastic modulus of intact rock (E_i) as input parameters, is also proposed using worldwide data.     

Production of high strength concrete by use of industrial by-products

Blast furnace slag aggregates (BFSA) were used to produce high-strength concretes (HSC). These concretes were made with total cementitious material content of 460–610 kg/m³. Different water/cement ratios (0.30, 0.35, 0.40, 0.45 and 0.50) were used to carry out 7- and 28-day compressive strength and other properties. Silica fume and a superplasticizer were used to improve BFSA concretes. Slump was kept constant throughout this study. Ten percent silica fume was added as a replacement for ordinary portland cement (OPC) in order to obtain HSC. The silica fume was used as highly effective micro-filler and pozzolanic admixture. Superplasticizer at dosages of 2%, 1.5%, 1%, 0.5% and 0% by OPC weight for 0.30, 0.35, 0.40, 0.45 and 0.50 w/c ratios, respectively, were adopted. Results showed that compressive strength of BFSA concretes were approximately 60–80% higher than traditional (control) concretes for different w/c ratios. These concretes also had low absorption and high splitting tensile strength values. It is concluded that BFSA, in combination with other supplementary cementitious materials, can be utilized in making high strength concretes.     

贫混凝土基层强度与模量研究

作为路面基层材料,贫混凝土得到越来越多的应用.通过室内试验,研究了振捣贫混凝土与碾压贫混凝土的28d弯拉强度与抗压强度,得出二者之间的相关关系;进行弯拉弹性模量试验,得出贫混凝土28d弯拉弹性模量与弯拉强度之间的关系,据此得出对应关系表作为模量推荐值.     

Prediction of the shear strength of reinforced masonry walls using a large experimental database and artificial neural networks

This paper analyses the accuracy of a selection of expressions currently available to estimate the in-plane shear strength of reinforced masonry (RM) walls, including those presented in some international masonry codes. For this purpose, predictions of such expressions are compared with a set of experimental results reported in the literature. The experimental database includes specimens built with ceramic bricks and concrete blocks tested in partially and fully grouted conditions, which typically present a shear failure mode. Based on the experimental data collected and using artificial neural networks (ANN), this paper presents alternative expressions to the different existing methods to predict the in-plane shear strength of RM walls. The wall aspect ratio, the axial pre-compression level on the wall, the compressive strength of masonry, as well as the amount and spacing of vertical and horizontal reinforcement throughout the wall are taken into consideration as the input parameters for the proposed expressions. The results obtained show that ANN-based proposals give good predictions and in general fit the experimental results better than other calculation methods.     

Wet and dry cured compressive strength of concrete containing ground granulated blast-furnace slag

This paper reports a part of an ongoing laboratory investigation in which the compressive strength of ground granulated blast-furnace slag (GGBFS) concrete studied under dry and wet curing conditions. In the study, a total of 45 concretes, including control normal Portland cement (NPC) concrete and GGBFS concrete, were produced with three different water-cement ratios (0.3, 0.4, 0.5), three different cement dosages (350, 400, 450 kg/m³) and four partial GGBFS replacement ratios (20%, 40%, 60%, 80%). A hyperplasticizer was used in concrete at various quantities to provide and keep a constant workability. Twelve cubic samples produced from fresh concrete were de-moulded after a day, then, six cubic samples were cured at 22±2 °C with 65% relative humidity (RH), and the remaining six cubic samples were cured at 22±2 °C with 100%RH until the samples were used for compressive strength measurement at 28 days and three months. Three cubic samples were used for each age and curing conditions. The comparison was made on the basis of compressive strength between GGBFS concrete and NPC concrete. GGBFS concretes were also compared within themselves. The comparisons showed that compressive strength of GGBFS concrete cured at 65%RH was influenced more than that of NPC concrete. It was found that the compressive strength of GGBFS concrete cured at 65%RH was, at average, 15% lower than that of GGBFS concrete cured at 100%RH. The increase in the water-cementitious materials ratios makes the concrete more sensitive to dry curing condition. The influence of dry curing conditions on GGBFS concrete was marked as the replacement ratio of GGBFS increased.     

Prediction of web crippling strength of cold-formed steel sheetings using neural networks

This study considers the use of neural networks (NNs) to predict the web crippling strength of cold-formed steel decks. Web crippling is critical for slender webs as in the case of trapezoidal sheetings which are widely used in roofing applications. The elastoplastic behaviour of web crippling is quite complex and difficult to handle. There is no well established analytical solution due to complex plastic behaviour. This leads to significant errors in various design codes. The objective of this study is to provide a fast and accurate method of predicting the web crippling strength of cold-formed steel sheetings and to introduce this in a closed-form solution which has not been obtained so far. The training and testing patterns of the proposed NN are based on well established experimental results from literature. The trained NN results are compared with the experimental results and current design codes (NAS 2001) and found to be considerably more accurate. Moreover, a trained neural network gives the results significantly more quickly than the design codes and finite element (FE) models. The web crippling strength is also introduced in closed-form solution based on the parameters of the trained NN. Extensive parametric studies are also performed and presented graphically to examine the effect of geometric and mechanical properties on web crippling strength.     

混凝土早期弹性模量的预测RBF模型

混凝土的早期弹性模量对施工的进度和工程的可靠度有重要的影响。借鉴RBF神经网络具有很强的非线性映射功能,在测定混凝土早期强度的基础上利用RBF神经网络对其弹性模量进行预测。讨论了RBF神经网络的拓扑结构和修正算法。通过对检验结果进行分析比较,证明了利用RBF网络能对混凝土早期的弹性模量进行精确的预测。     

砂的细度模数与混凝土抗压强度

混凝土抗压强度随着用砂细度模数的变化而发生显著变化，对砂的细度模数与砂率、平均粒径及其级配之间的关系进行了分析，指出工地控制砂的细度模数是施工质量监理中监控混凝土强度的一个十分有效的手段。     

Prediction of geological hazardous zones in front of a tunnel face using TSP-203 and artificial neural networks

This research aims at improving the methods of prediction of hazardous geotechnical structures in the front of a tunnel face. We propose and showcase our methodology using a case study on a water supply system in Cheshmeh Roozieh, Iran. Geotechnical investigations had previously reported three measurements of the newly established method of TSP-203 (Tunnel Seismic Prediction) along 684 m of the 3200 m long tunnel up to a depth of 600 m. We use the results of TSP-203 in a trained artificial neural network (ANN) to estimate the unknown nonlinear relationships between TSP-203 results and those obtained by the methods of Rock Mass Rating classification (RMR – treated here as real values). Our results show that an appropriately trained neural network can reliably predict the weak geological zones in front of a tunnel face accurately.     

混凝土小砌块灌芯砌体抗压及弹性模量试验研究

通过22个混凝土小砌块灌心砌体抗压强度及弹性模量试件的试验,分析研究了试件的受力状况及其应力-应变关系,提出了相应的计算方法。     

The effect of cylindrical specimen size on the compressive strength of concrete

In this study, the influence of size and capping type of cylindrical specimens on compressive strength of concrete is investigated. For this purpose, eight series of concrete mixtures were designed to have water/cement ratios of 37%, 42%, 47%, 48%, 55%, 62%, 71% and 77% (by volume). Three hundred and eighty-four cylindrical specimens having dimensions of 150/300 and 120/200 mm were casted. At the end of 28-day standard curing period, the uniaxial compressive strength of capped and uncapped specimens was determined. Cement, gypsum and sulphur are used as capping materials. The results of the experimental study reveal that the suitable average conversion factor (the ratio of compressive strength of 100/200 mm cylinder to 150/300 mm cylinder—f_c100/f_c150) can be taken as 103%. Linear and nonlinear regression analyses were employed between f_c100 and f_c150. Linear and nonlinear regression analyses exhibited better performance.     

Long term study on compressive and bond strength of coconut shell aggregate concrete

Effects of three types of curing on coconut shell aggregate concrete have been studied for long term performance. The pore structure of coconut shell has been studied through scanning electron microscope (SEM). The pore structures in coconut shell behave like a reservoir. Intermittent curing produced the highest coconut shell aggregate concrete strength, followed by full water, and then by air-dry curing. Biological decay was not evident as the concrete cubes gained strength even after 365 days. Up to an age of 90 days, the samples under all types of curing conditions showed improved response on the pulse velocity and subsequently an insignificant drop. The ultimate bond strength of coconut shell aggregate concrete under all types of curing conditions was much higher compared to the theoretical bond strength as per BS 8110 and IS 456. Bonding between the cement paste and the coconut shell aggregate has been studied by measuring fissure between the coconut shell and the cement paste through SEM analysis. It shows a tendency of narrowing the fissure due to its age, which shows that the bond appears to be better between the coconut shell and the cement paste.     

Prediction of long-term effects of GGBFS on compressive strength of concrete by artificial neural networks and fuzzy logic

In this study, artificial neural networks and fuzzy logic models for prediction of long-term effects of ground granulated blast furnace slag on compressive strength of concrete under wet curing conditions have been developed. For purpose of constructing these models, 44 different mixes with 284 experimental data were gathered from the literature. The data used in the artificial neural networks and fuzzy logic models are arranged in a format of five input parameters that cover the age of specimen, Portland cement, ground granulated blast furnace slag, water and aggregate, and output parameter which is 3, 7, 14, 28, 63, 90, 119, 180 and 365-day compressive strength. In the models of the training and testing results have shown that artificial neural networks and fuzzy logic systems have strong potential for prediction of long-term effects of ground granulated blast furnace slag on compressive strength of concrete.     

粉煤灰高性能混凝土弹性模量的试验研究

在现有混凝土弹性模量测试方法的基础上提出了测试混凝土试件受压变形的新方法,试验表明了该方法的可行件。并采用该方法对粉煤灰混凝土的弹性模量进行了测试,考察了不同等级的粉煤灰以不同的掺量混合掺入混凝土中对弹性模量的影响．并初步探讨其影响机理。同时采用F检验和T法对试验结果进行显著性分析。     

Experimental study of mechanical properties of normal-strength concrete exposed to high temperatures at an early age

In China, accidental fires are known to occur during construction, causing concrete to be exposed to high temperatures when it is at an early age (i.e. “young”). In this paper, compressive and splitting tensile strengths of concretes cured for different periods and exposed to high temperatures were obtained. The effects of the duration of curing, maximum temperature and the type of cooling on the strengths of concrete were investigated. Experimental results indicate that after exposure to high temperatures up to 800 °C, early-age concrete that has been cured for a certain period can regain 80% of the compressive strength of the control sample of concrete. The 3-day-cured early-age concrete was observed to recover the most strength. The type of cooling also affects the level of recovery of compressive and splitting tensile strength. For early-age concrete, the relative recovered strengths of specimens cooled by sprayed water are higher than those of specimens cooled in air when exposed to temperatures below 800 °C, while the changes for 28-day concrete are the converse. When the maximum temperature exceeds 800 °C, the relative strength values of all specimens cooled by water spray are lower than those of specimens cooled in air.     

泡沫混凝土弹性模量的测试方法探讨

为获得密度为800 kg/m3的泡沫混凝土的弹性模量数据,设计了一种振弦式应变计测试的方法,并采用该方法测试了采用普通水泥和双快水泥配制的两种泡沫混凝土的应力应变,绘制了变化曲线,计算了弹性模量.采用普通水泥配制的泡沫混凝土,7 d的弹性模量在200～300MPa之间,采用双快水泥配制的泡沫混凝土,2 h的弹性模量在350～500MPa之间.测试表明该方法操作方便、速度快、测试结果离散性小、数值符合泡沫混凝土的特点和强度水平.