再生骨料管孔透水混凝土关键性能及预测

针对普通再生骨料透水混凝土（RAPC）强度低的问题，从孔隙存在形式入手，提出了一种再生骨料管孔透水混凝土，即将随机分布的孔隙集中成上下连通的管孔，必要时嵌入管材，研究不同管孔参数（数量、直径、材料、分布形式等）的组合对其性能的影响及变化规律，并提出强度折减系数法，构建抗压强度与管孔参数理论计算模型，同时建立了基于管流公式和达西定律的透水系数计算模型。结果表明：再生骨料管孔透水混凝土的强度与透水性能远优于RAPC；再生骨料管孔透水混凝土的孔数越少，管径越小，抗压强度越高，透水系数越小，反之亦反；抗压强度理论模型能够较准确地量化孔数、孔径、孔分布对再生骨料管孔透水混凝土抗压强度的折减作用；透水系数与再生骨料管孔透水混凝土的孔数、孔径、孔糙率有显著的线性关系。可根据实际需求自行设计再生骨料管孔透水混凝土的管孔结构。     

透水混凝土强度与透水系数关系模型研究

为建立透水混凝土抗压强度与透水系数的定量关系模型,制备了透水混凝土试件,并测试了试件的有效孔隙率、透水系数和28 d抗压强度.结合现有模型,建立了基于Griffith断裂理论的数学关系模型,并验证了模型的有效性;基于本文提出的模型,选取合适参数,可以对透水混凝土性能进行有效预测.     

透水混凝土的研究与应用

通过优选原材料,研究了水灰比、骨料和胶凝材料对透水混凝土的抗压强度、透水系数、孔隙率影响规律,分析了强度和透水性能的关系和强度增长规律.并结合实际需要进行了工程应用,阐述了透水混凝土的生产工艺及施工过程.     

工作性能指标量化在透水混凝土制备中的应用

通过对透水混凝土拌合物工作性能进行指标量化,通过不同的配合比试配研究透水混凝土实际孔隙率随性能指标的变化规律,并对性能指标化的实际应用效果进行实例验证。结果表明,实际孔隙率、抗压强度均与工作性能指标呈线性关系,工程应用实例所得实际孔隙率和设计孔隙率相差无几,工作性能指标化在透水混凝土的制备中应用效果明显。     

掺合料增强透水混凝土的试验研究

透水混凝土是一种多孔、轻质的绿色生态建筑材料,其透水性和强度是一对相互矛盾的性能指标。研究掺入不同种类掺合料(粉煤灰、玄武岩纤维、EVA聚合物乳液)对透水混凝土强度和透水性能的影响,结果表明双掺粉煤灰与EVA聚合物乳液或玄武岩纤维与EVA聚合物乳液,能保证透水混凝土的透水性基本不变,提高抗压强度20%以上,提高抗折强度30%以上,实现透水混凝土强度增强;但是同时掺入三种掺合料不利于透水混凝土强度和透水性的提高。     

功能透水混凝土的配合比设计与性能

以体积填充法对透水混凝土配合比进行了优化设计,研究了不同级配碎石、不同设计空隙率对透水混凝土强度及透水性能的影响规律,探究了透水混凝土实际孔隙率与设计空隙率的一致关联性,并探索了搅拌站生产透水混凝土的整体配套方案。     

海绵城市背景下硅砂透水砖性能研究

采用氢化双酚A型环氧树脂改性硅砂透水砖,探究硅砂粒径(35目、50目、70目)与环氧树脂掺量(2%、4%、6%、8%)对硅砂透水砖的强度、透水性能、保水性能、滤水性能以及防滑性能的影响规律。试验结果表明：当硅砂粒径为50目、环氧树脂掺量为4%时,硅砂透水砖的抗压、抗折和防滑性能最好,透水速率为1.5 mL/(min·cm²)、保水率为0.068 g/cm³,滤水率为90.2%。     

预拌透水混凝土及其应用

研究了预拌透水混凝土的制备、性能及应用,研究了预拌透水混凝土专用外加剂对透水混凝土的性能指标和工作性能的影响,并通过与现拌透水混凝土试验对比,确认预拌透水混凝土在力学性能上优于现拌透水混凝土,透水混凝土的其他性能指标完全满足CJJ/T 135—2009《透水水泥混凝土路面技术规程》的要求,此项技术已在赣州蓉江新区公园及道路绿化工程中应用和推广.     

骨料和配合比参数对透水混凝土基本性能影响

基于体积法设计透水混凝土配合比,系统研究了骨料种类、水灰比、水泥用量和砂率对透水混凝土基本性能的影响规律。试验结果表明:骨料粒径越大,透水混凝土强度越小、透水系数越大;骨料强度越高,透水混凝土强度也越高。减小水灰比在提高浆体强度的同时还可能导致浆体流动性不佳,造成透水混凝土强度降低。增加水泥用量或使用细砂取代部分碎石,虽能使强度提升但同时也牺牲了部分透水性能。     

高透水性生态混凝土强度变化规律试验研究

试验分析了高透水混凝土强度随着龄期变化的增长规律,拟合出其变化曲线,提出早期养护方法对其强度增长的必要性。并对高透水混凝土的抗压强度与劈裂强度进行了试验分析,指出二者有较强的相关性。为分析研究高透水混凝土性能具有一定的参考价值。     

透水性混凝土强度-渗透性模型试验研究

高透水性是透水性混凝土的重要特征,现有的透水性混凝土渗透系数测试装置存在试件侧壁渗漏问题,为此提出了一种试件侧面防水涂抹+柔性夹层+套筒刚性壁的防侧漏复合结构,提高了渗透系数测试精度。透水性混凝土的透水性和强度是一对矛盾体,此消彼长,但目前对它们之间关系缺乏系统的研究。通过室内渗透性和强度试验研究了多种因素（如：水灰比、集灰比、孔隙率）对透水性混凝土的强度和透水性的影响,建立了强度孔隙率模型、渗透性孔隙率模型和强度渗透性模型。研究结果表明：透水性混凝土与普通混凝土不同,存在一个最佳水灰比,最佳水灰比对应的强度最大;强度和水灰比成开口向下的二次抛物线关系,而孔隙率和集灰比均与渗透系数成正相关关系;透水性混凝土强度和渗透性关系服从Lorentzian函数,强度随渗透性的增大而逐渐降低,降低速度先快后慢。在工程设计中应根据具体要求,确定最佳的强度和渗透性组合。     

混凝土强度预测的混合神经网络模型

针对由于混凝土配方的多样性,直接利用神经网络模型对其进行强度预测存在精度差和收敛差的缺点,采用多种神经网络模型相结合的方法,建立了混凝土强度预测的混合神经网络模型。模型的建立主要包括以下三个过程:(1)建立混凝土强度影响参数样本数据库;(2)利用自组织神经网络对样本数据分类;(3)以混凝土原材料和制作工艺为输入参数,混凝土最终性能为输出参数,训练双并联神经网络模型。通过实例验证了模型的可靠性。     

活性掺合料对路面水泥混凝土性能的影响和应用研究

针对粉煤灰和硅粉等活性掺合料对路面水泥混凝土性能的影响进行了研究.采用正交法设计了十种混凝土配合比,对在标准条件下养护28天的各配比混凝土试件进行了抗折强度、抗压强度、抗渗透性能和抗冻融性能的测试,并通过回归方法建立了各指标与配合比的关系.试验结果表明,通过添加适量的粉煤灰和硅粉,可以在不降低混凝土强度的基础上有效地提高混凝土的密实性和抗渗性能,并改善其抗冻融性能.同时,再通过技术、经济比较及现场验证,得出适合当地实际情况的最佳配合比.     

Prediction of the performance of impact hammer by adaptive neuro-fuzzy inference system modelling

Impact type excavators are widely used for excavations, performed in weak-laminated-foliated-anisotropic rocks. Therefore the prediction of the performance of impact hammer is very important in many mining and civil engineering projects.This paper describes the construction of adaptive neuro-fuzzy inference system model for predicting the performance of impact hammer type excavator by considering rock and excavating machine properties such as block punch strength index, geological strength index system and impact hammer power. Extensive field and laboratory studies were conducted in the tunnel construction route of the second stage of Izmir Metro Project, which excavated in laminated-foliated flysch rocks. The results of the constructed adaptive neuro-fuzzy inference system and traditional multiple regression models were compared. Although the prediction performance of traditional multiple regression model is high, it is seen that adaptive neuro-fuzzy inference model exhibits better prediction performance according to statistical performance indicators. By means of the developed model, the performance of impact type excavators can be predicted in terms of net excavation based on the selected rock and machine properties.     

Mix proportions for HPC incorporating multi-cementitious composites using artificial neural networks

High performance concrete (HPC) is defined in terms of both strength and durability performance under anticipated environmental conditions. HPC can be manufactured involving up to 10 different ingredients whilst having to consider durability properties in addition to strength. The number of ingredients and the number of properties of HPC, which needs to be considered in its design, are more than those for ordinary concrete. Therefore, it is difficult to predict the mix proportions and other properties of this type of concrete using statistical empirical relationship. An alternative approach is to use an artificial neural network (ANN). Based on the experimentally obtained results, ANN has been used to establish its applicability to the prediction and optimization of mix proportioning for HPC. It was demonstrated that mix proportioning for HPC can be predicted using ANN. However, some trial mixes are necessary for better performance and elimination of material variability factors from place to place. ANN procedure provides guidelines to select appropriate material proportions for required strength and rheology of concrete mixes and will reduce the number of trial mixes.     

基于正交试验的再生骨料透水混凝土性能影响研究

利用再生骨料制备透水混凝土,分析多因素对再生骨料透水混凝土性能的影响,基于正交试验设计对再生骨料透水混凝土的基本物理性能进行试验和分析,研究了不同水平下目标孔隙率、水胶比、矿物掺合料掺量等因素对再生骨料透水混凝土有效孔隙率、28 d抗压强度和透水系数等性能的影响,并通过拟合28 d抗压强度与透水系数试验数据的相关关系,研究建立了两者的线性预测模型。结果表明:各因素对再生骨料透水混凝土的28 d抗压强度和透水系数影响的综合排序为:目标孔隙率>水胶比>矿物掺合料掺量;再生骨料透水混凝土的28 d抗压强度和透水系数呈反相关的线性关系,其线性回归模型可用于实际工程的预测。     

Deep neural network with high‐order neuron for the prediction of foamed concrete strength

The article presents a deep neural network model for the prediction of the compressive strength of foamed concrete. A new, high‐order neuron was developed for the deep neural network model to improve the performance of the model. Moreover, the cross‐entropy cost function and rectified linear unit activation function were employed to enhance the performance of the model. The present model was then applied to predict the compressive strength of foamed concrete through a given data set, and the obtained results were compared with other machine learning methods including conventional artificial neural network (C‐ANN) and second‐order artificial neural network (SO‐ANN). To further validate the proposed model, a new data set from the laboratory and a given data set of high‐performance concrete were used to obtain a higher degree of confidence in the prediction. It is shown that the proposed model obtained a better prediction, compared to other methods. In contrast to C‐ANN and SO‐ANN, the proposed model can genuinely improve its performance when training a deep neural network model with multiple hidden layers. A sensitivity analysis was conducted to investigate the effects of the input variables on the compressive strength. The results indicated that the compressive strength of foamed concrete is greatly affected by density, followed by the water‐to‐cement and sand‐to‐cement ratios. By providing a reliable prediction tool, the proposed model can aid researchers and engineers in mixture design optimization of foamed concrete.     

聚合物砂浆与混凝土抗拉粘结性能研究

高强不锈钢绞线网-渗透性聚合物砂浆加固技术是近年来兴起的新型加固工艺。对该加固技术的研究表明:加固层发生剥离破坏是其主要破坏方式之一,如何保证加固层与混凝土界面的粘结性能是加固成败的关键。通过243个测点的正拉粘结强度试验,分析聚合物砂浆与混凝土界面粘结抗拉性能,阐述混凝土强度、界面粗糙度、龄期、修补方位对正拉粘结强度的影响,最后提出正拉粘结强度的计算模型。     

浅析透水混凝土配合比设计技术

通过透水混凝土配合比的设计实例,介绍了透水混凝土配合比设计的方法和步骤,分析了影响透水混凝土性能的因素。文中的透水混凝土按体积法的设计原理,以粗集料空隙率、目标孔隙率、水灰比为配合比主要指标,对试件的透水系数、抗压强度、抗折强度进行综合控制．从而获得最终配合比。     

Effect of partial replacement of sand with dry oyster shell on the long-term performance of concrete

To evaluate the practical application of crushed oyster shells (OS) as construction materials, an experimental study was performed based on equal materials proportion and the partial replacement of saturated-surface-dry (SSD) sand with dry oyster shell. More specifically, the long-term mechanical properties and durability of concrete with OS partially substituted for fine aggregate were investigated.Test results indicate that long-term strength of concrete with 10% OS replacement is almost identical to that of normal concrete. However, the long-term strength of concrete with 20% OS replacement is appreciably lower than that of normal concrete. Therefore, higher OS substitution has the possibility of negatively influencing the concrete long-term strength increment. Elastic modulus of concrete with OS replacement decreases as the substitution mixture ratio increases. Specifically, the modulus is reduced by approximately 10–15% when OS are used for 20% of the fine aggregate.The drying shrinkage strain increases as the substitution ratio (SR) of OS is increased. In addition, the existing model code for drying shrinkage and creep does not coincide with the test results of the present study. A prediction equation for drying shrinkage has been developed. The utilization of OS as a fine aggregate in concrete has a positive effect on freezing and thawing resistance and water permeability is also considerably improved. However, OS has no apparent effect on carbonation and chemical attack of concrete.Finally, it is noted that the strength, elastic modulus, drying shrinkage, freezing and thawing resistance, and permeability are significantly affected by increased OS substitution, particularly for long-term performance, while other properties such as creep and carbonation, as well as chemical attack test results, were not substantially affected.