负温混凝土的力学性能及其影响因素的研究

主要研究了水灰比,矿物掺合料,外加剂及预养制度对负温混凝土抗压强度、抗折强度、轴心抗压强度和静弹性模量的影响。结果表明:负温混凝土-7+28d的各项力学性能的损失率随水灰比的增大而增加。防冻剂和引气剂可以有效地降低混凝土-7+28d的上述各项力学性能损失率,同引气剂相比防冻剂更有效;除抗压强度外,粉煤灰和矿渣对混凝土的-7+28d的各项力学性能不利;经48h预养后所有配合比混凝土的力学性能损失率均显著减小,预养时间对负温混凝土的力学性能的影响要比水灰比、引气剂、防冻剂、矿渣及粉煤灰明显;同其他三种力学性能相比,负温混凝土的轴心抗压强度损失率明显较大。     

免振高性能混凝土力学性能及耐久性研究

采用超细磨粉煤灰和复合高效减水剂双掺技术研制出了Ｃ６０～Ｃ８０免振高性能混凝土,在优选了免振高性能混凝土配合比主要设计参数的基础上,对免振与振捣成型的高性能混凝土的抗压强度、劈裂抗拉强度、抗折强度、弹性模量、抗冻性能、干综性能等进行了对比试验研究。结果表明：免振高性能混缔造人有优异的物理力学性能及耐久性。     

特细砂砌筑砂浆7d推定28d抗压强度试验研究

本文通过对不同配比特细砂砌筑砂浆7d和28d抗压强度的试验研究,分析了7d与28d强度的抗压强度的相关关系,得出的关系式对砂浆施工生产和施工中的强度控制以及砂浆配合比调整的辅助设计具有现实指导意义。     

基于性价比优化的混凝土配方设计模型

收集了502组混凝土配方作为训练数据,基于BP神经网络、遗传算法及粒子群算法,构建了一种混凝土配方设计模型,可用于控制混凝土成本和配方优化.所构建的模型考虑了混凝土的原材料成本以及影响混凝土抗压强度的多个关键因素,引入惩罚函数对粒子群算法的目标函数适应度值进行惩罚,解决了混凝土配方设计中非线性约束离散变量问题和连续变量问题,从而达到控制混凝土成本并优化配方的目标.按照构建模型输出27组降低成本后的混凝土配方,并进行抗压强度试验,结果表明：所得配方成本与目标成本的契合度接近97%;降低混凝土单方成本5、10、15元后,所输出的配方均能满足混凝土立方体抗压强度要求.     

按耐久性设计高性能混凝土的原则和方法

高性能混凝土不是一个混凝土的品种,而是表明混凝土的“性能（performance）或者 质量、状态、水平的一种称谓,是按照具体工程要求和所处环境条件,满足特殊组合的性能而均匀、致密的高质量混凝土。高性能混凝土的耐久性设计步及原材料选择与控制、配合比设计、制备工艺和施工质量控制的全过程。按工程要求的耐久性选定原材料后,从“NEL法的氯离了扩散系数－渗透性关系”中初选水胶比,用绝对体积法计算配合比,进行试配和强度样核。     

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.     

高性能混凝土配合比设计及力学强度试验研究

为提高混凝土的抗压强度和抗冲磨强度,通过不同配合比对普通混凝土进行试验分析。通过试验得出:石粉、灰土和钢渣对混凝土的抗压强度影响并不显著。随着石粉比例的增多,混凝土的抗压强度几乎无明显变化;随着灰土比例的增高,混凝土的抗压强度会出现降低趋势;而随着钢渣比例的增多,混凝土的抗压强度也会出现下降趋势,但影响较小;水灰比对混凝土的抗压强度的变化具有显著性,而砂率和用水量比例则对抗压强度的影响不大。当水灰比逐渐增大时,混凝土的抗压强度逐渐减小;砂率比例逐渐增大时,混凝土的抗压强度无明显变化;用水量比例增多时,混凝土的抗压强度会逐渐上升,但影响较小;石粉、灰土和钢渣对混凝土的抗冲磨强度影响并不显著。随着石粉比例的增加,混凝土抗冲磨强度增大,当石粉比例逐渐增加时,混凝土抗冲磨强度明显增大;随着灰土比例的增多,混凝土的抗冲磨强度减小,并且随着时间的增加,其强度减小趋势便更加明显;随着钢渣比例的增加,混凝土的抗冲磨强度下降,但影响不大。通过试验结果得出最佳混凝土配合比,并通过分析高性能混凝土与混凝土的微观特征得出:普通混凝土内部结构疏松并且有大量的孔洞、分布排列杂乱;而高性能混凝土内部结构较为密集,孔洞较少,高性能混凝土水化后,Ca和Si含量最多,而这两种元素能够形成稳定的结构,因此使得高性能混凝土抗压强度和抗冲磨强度提高。     

废旧橡胶颗粒再生骨料透水混凝土抗压强度和透水性能正交试验研究

废旧橡胶颗粒再生骨料透水混凝土是一种新型绿色环保建筑材料。采用体积法设计再生骨料透水混凝土的配合比,完成9组不同配比28d抗压强度、透水系数及连续孔隙率试验,通过正交试验方法,考察成型锤击次数、废旧橡胶颗粒细度和增强剂掺量对再生骨料透水混凝土抗压强度、透水性能的影响。     

Mechanical properties of concrete with recycled coarse aggregate

This paper reports the results of an experimental study on some of the mechanical properties of recycled aggregate concrete (RAC) as compared to those of the conventional normal aggregate concrete (NAC). Ten mixes of concrete with target compressive cube strength ranging from 20 to 50 MPa were cast using normal or recycled coarse aggregates. The development of the cube compressive strength and the indirect shear strength at ages of 1, 3, 7, 14, 28 and 56 days, the compressive strength, the strains at maximum compressive stress and the modulus of elasticity tested by using concrete cylinders at 28 days are reported. The results show that the 28-day cube and cylinder compressive strength, and the indirect shear strength of recycled aggregate concrete were on the average 90% of those of natural aggregate concrete with the same mix proportions. For concrete with cylinder compressive strengths between 25 and 30 MPa, the modulus of elasticity of RAC was only 3% lower than that of NAC. The trends in the development of compressive and shear strength and the strain at peak stress in recycled aggregate concrete were similar to those in natural aggregate concrete.     

钢纤维再生混凝土在路面工程中的应用研究

本文通过上海市某道路改建工程实例,对含50％再生粗集料的钢纤维混凝土路面进行了较为系统的研究。首先在室内对再生粗集料的密度、洛杉矶磨耗、压碎指标等基本性能进行了测试。然后针对拟定的三组不同配合比的钢纤维再生混凝土试件,在室内进行了抗折强度、抗压强度等试验,最后根据试验结果并结合工程经验,选取了一组较为理想的钢纤维再生混凝土配合比,完成了钢纤维再生混凝土路面的施工。同时对试验路段进行了全面的现场检测,结果证明钢纤雏再生混凝土在普通路面上的应用是安全可行的,而且会有很好的发展前景。     

水泥乳化沥青砂浆强度计算模型

为了建立水泥乳化沥青砂浆（CA砂浆）28d抗压强度计算模型,通过正交试验校验了多种配合比参数对CA砂浆28d抗压强度影响的显著性,通过SEM观察了CA砂浆的微观形貌,分析了配合比参数影响砂浆强度的机理.借鉴混凝土微观力学的理论,建立了基于孔隙率与水化程度的CA砂浆28d抗压强度的理论模型.结果表明：在较大的范围内,该理论模型的计算结果与实测强度有良好的一致性.     

基于预拌浓浆法的再生骨料混凝土性能试验研究

通过机理分析及试验验证,提出了一种能提高再生骨料混凝土性能的预拌浓浆法,并分别采用该方法和传统拌制工艺,对比研究了再生骨料混凝土28d抗压强度的统计分布规律.结果表明:与传统拌制工艺相比,预拌浓浆法能使再生骨料混凝土28d抗压强度提高8%~19%;同时,预拌浓浆法能够在不改变配合比的条件下,使再生骨料混凝土抗冻性明显改善.     

含水率对粉煤灰混凝土强度增长的影响研究

通过测试不同配合比、不同含水率的混凝土的抗压强度,研究含水率对混凝土强度发展的影响规律。结果显示,混凝土在28d标准养护后,含水率大的混凝土抗压强度增长较含水率小的混凝土要小。     

双掺粉煤灰和矿渣粉对改性陶粒混凝土性能影响的研究

研究了双掺粉煤灰与矿渣粉对陶粒混凝土和易性及早期强度、后期强度的影响,试验中采用松散体积法对陶粒混凝土的配合比进行设计,以确定最佳配合比,测定了12组不同配合比陶粒混凝土的抗压强度.研究结果表明:对陶粒混凝土进行拌合之前应将陶粒提前预湿6h;随着双掺掺合料比例的增加,双掺掺合料陶粒混凝土的抗压强度也随之增加;45％比例...     

Compressive strength and stability of sustainable self-consolidating concrete containing fly ash,silica fume,and GGBS

This paper presents the findings of an experimental program seeking to understand the effect of mineral admixtures on fresh and hardened properties of sustainable self-consolidating concrete (SCC) mixes where up to 80% of Portland cement was replaced with fly ash, silica fume, or ground granulated blast furnace slag. Compressive strength of SCC mixes was measured after 3, 7, and 28 days of moist curing. It was concluded in this study that increasing the dosage of fly ash increases concrete flow but also decreases segregation resistance. In addition, for the water-to-cement ratio of 0.36 used in this study, it was observed that the compressive strength decreases compared to control mix after 28 days of curing when cement was partially replaced by 10%, 30%, and 40%of fly ash. However, a fly ash replacement ratio of 20% increased the compressive strength by a small margin compared to the control mix. Replacing cement with silica fume at 5%, 10%, 15%, and 20% was found to increase compressive strength of SCC mixes compared to the control mix. However, the highest 28 day compressive strength of 95.3 MPa occurred with SCC mixes in which 15% of the cement was replaced with silica fume.     

基于GA-BP神经网络的UHPC抗压强度预测与配合比设计

开展了不同配合比条件下超高性能混凝土(UHPC)的制备与抗压强度试验,并结合已有数据形成了神经网络训练样本;根据UHPC原材料组成和性能需求设计了包含神经网络输入层(7节点)、隐层(8节点)和输出层(1节点)的拓扑结构,并引入遗传算法(GA)优化了UHPC抗压强度预测网络的初始权值和阈值;采用试验样本模拟训练了不同配合比条件下的UHPC抗压强度预测GA-BP神经网络,并以此为基础建立了基于不同性能需求的配合比设计方法.对比试验数据和传统BP神经网络方法计算结果发现,GA-BP神经网络能更好地指导UHPC抗压强度预测和配合比设计.     

土壤固化剂稳定粉质黏土性能的试验研究

以河南省境内某段高速公路附近的粉质黏土为原材料,通过室内试验,首先对比了掺或不掺固化剂的情况下,水泥质量分数分别为5%,10%,15%和20%时集合料的7 d无侧限抗压强度,结果表明掺固化剂能明显提高集合料的无侧限抗压强度;其次制备了不同配合比的集合料试件,分析了水泥和固化剂含量对集合料最大干密度、最佳含水量、7 d和28 d无侧抗压强度2、8 d间接抗拉强度的影响,综合试验结果与成本等因素,选定了最优配合比为m(水泥)∶m(固化剂)∶m(粉质黏土)=4∶8∶88;最后,对该最优配合比进行了延迟和干缩等路用性能试验及SEM微观分析,并在某高速公路选取100 m的底基层进行了现场试验和追踪调查,结果表明上述最优配合比集合料完整密实且强度较高,未出现病害,路用性能较好.     

Hybrid random aggregation model and Bayesian optimization-based convolutional neural network for estimating the concrete compressive strength

Numerous experimental studies have shown the type and gradation of coarse aggregates effect on the mechanical properties of concrete. The type and gradation of coarse aggregates have not been taken into account in the available machine learning prediction models. In this study, a two-dimensional concrete microscopic image was generated by using a random aggregate model (RAM), and the coarse aggregate and other concrete ingredients were represented innovatively using polygons and trichromatic chromaticity values in the RAM images. The RAM image set was created by applying this method to represent 1110 sets of different concrete mixes. Then based on the Bayesian optimization algorithm and the image set, a compressive strength prediction model considering the effect of coarse aggregate types and gradations was developed utilizing a convolutional neural network (CNN) model. Meanwhile, an artificial neural network (ANN) compressive strength prediction model was developed using 1110 sets of mix ratio data. The results show that the proposed RAM image generation method has the capability to represent different concrete mix ratios collected in this study. The prediction performance of the CNN compressive strength model considering aggregate types and gradations is better than that of the ANN model. The method can provide a new perspective for predicting other concrete mechanical properties and technically support performance-based intelligent concrete mix design.     

Multiple linear regression,artificial neural network,and fuzzy logic prediction of 28 days compressive strength of concrete

Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete is acknowledged as the most ordinary method, however, it is very difficult to predict the compressive strength of concrete since it is affected by many factors such as different mix designs, methods of mixing, curing conditions, compaction, etc. In this paper, considering the experimental results, three different models of multiple linear regression model (MLR), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) are established, trained, and tested within the Matlab programming environment for predicting the 28 days compressive strength of concrete with 173 different mix designs. Finally, these three models are compared with each other and resulted in the fact that ANN and ANFIS models enables us to reliably evaluate the compressive strength of concrete with different mix designs, however, multiple linear regression model is not feasible enough in this area because of nonlinear relationship between the concrete mix parameters. Finally, the sensitivity analysis (SA) for two different sets of parameters on the concrete compressive strength prediction are carried out.     

无硅灰C80高性能混凝土研究

本文在混凝土理论配合比的基础上，仅改变各掺合料的比例及总掺合料与水泥的比例关系，采用混凝土用中砂配制砂浆，探索了一条以砂浆流动性指导高强高性能混凝土配制的新方法，并应用该方法以290kg/m^3，42．5R普通硅酸盐水泥及粉煤灰、矿渣粉和沸石粉等矿物掺合料配制出28d强度为96MPa的无硅高性能混凝土。