以旋转设计研究竹帘胶合板的静曲强度（MOR）和弹性模量（MOE）

本文以回归的旋转设计为数学懊型，研究了竹帘胶合板的ＭＯＲ和ＭＯＥ，分析了影响因素。结果表明：二次正文旋转组合设计选用正确，竹帘胶合板的纵向和横向的ＭＯＲ和ＭＯＥ，都达到了日本结构胶合板的标准。     

低强度等级混凝土弹性模量影响因素试验

为满足大型科学装置的防微振要求,其地基基础采用C15混凝土换填处理,要求混凝土28d弹性模量要求大于2.2×104N/mm2.通过试验探究不同因素如水胶比、掺合料掺量、砂率等对低强度等级混凝土弹性模量的影响,制备出符合工程需求的混凝土,并在实际使用中得了良好的效果.     

多层实木复合地板将引领精装修主流趋势

多层实木复合地板具备优异的表面技术处理,所以尽管其表层较薄,但其耐磨强度经过国家人造板质量监督检验中心检测,耐磨值是国家标准的2倍。正是因为这样,多层实木复合地板将引领精装修主流趋势。     

多层实木复合地板将引领精装修主流趋势

多层实木复合地板具备优异的表面技术处理,所以尽管其表层较薄,但其耐磨强度经过国家人造板质量监督检验中心检测,耐磨值是国家标准的2倍。正是因为这样,多层实木复合地板将引领精装修主流趋势。最近常逛建材市场的人会发现,多层实木复合地板正成为很多消费者热衷了解,商家极力推荐的首选产品。早在2007年1举办的2007年地板流行趋势发布会上,某知名品牌发言人也合地板。     

对混凝土弹性模量影响因素的探讨

探讨了影响混凝土弹性模量的各种因素，并对混凝土的抗压强度与弹性模量之间的关系进行了说明。     

机制砂高强混凝土强度和弹性模量试验研究

为研究采用机制砂配制高强混凝土的力学性能,对机制砂替代率为30%～100%、强度等级C60以上混凝土进行了不同龄期的立方体和棱柱体抗压强度、劈裂抗拉强度和弹性模量试验。分析了机制砂替代率对混凝土强度、棱柱体与立方体抗压强度比值以及弹性模量的影响。结果表明,在其他材料和用水量相同条件下,用机制砂部分或全部替代天然砂的混凝土强度和弹性模量均有所提高;棱柱体与立方体抗压强度比值仍可按现行《混凝土结构设计规范》(GB 50010—2010)的相关公式计算。同时,通过试验数据的回归分析,提出了考虑机制砂替代率影响的弹性模量计算公式,该公式的计算结果与试验结果吻合良好。     

“北美枫情”成功研发“和居二代”超耐磨实木复合地板

实木复合地板因兼具实木地板的质感及强化地板的稳定性,近年来越来越受到消费者的青睐,并成为实木地板的最佳替代产品。近期,一款超耐磨、耐刮擦的实木复合地板由“北美枫情”成功研发。     

基于回弹法测试岩石表面强度影响因素分析

为了测试集料加工宕口岩石的力学性能,应用回弹仪测试不同类型岩石的表面强度,对比各类岩石在非饱和及饱和状态下的回弹强度和抗压强度等。研究结果表明利用回弹仪测试岩石的表面强度方法简便、有效;岩石在非饱和及饱和状态下岩石的回弹强度差异较小;岩石具有明显软弱面时回弹强度会较小;岩石结构致密回弹值较大;岩石的测试区域的选取对结果具有明显的影响。     

砌体弹性模量影响因素的分析及其计算式的拟合

通过对相关实验结果分析得出的砌体弹性模量计算式和推导出的砌体弹性模量计算式计算出的弹性模量值与规范值进行对比,并进行了精确度的比较以及分析砌体弹性模量的主要影响因素。同时在已有数据的基础上通过运用数据分析软件Origin8．0对这些常用的砌体弹性模量值进行拟合,得出了精确度极高的砌体弹性模量的计算式以及比较直观的砌体弹性模量三维图形     

配筋率对钢筋混凝土构件弹性模量影响的试验研究

弹性模量是结构分析的主要力学参数之一。目前,在结构分析中,钢筋混凝土构件的弹性模量取值多取素混凝土的弹性模量值,很少涉及配筋率对钢筋混凝土构件弹性模量的影响。推导了钢筋混凝土构件弹性模量与配筋率的关系,设计制作了11组共计33件不同配筋率的钢筋混凝土试件,分别测得各试件的弹性模量;用最小二乘法回归得到混凝土构件弹性模量和配筋率关系的曲线,回归结果与理论推导结果基本一致。列举了一个悬臂梁的算例,分析了弹性模量对结构分析的影响。研究结果表明,配筋率对钢筋混凝土构件的弹性模量有影响,进行结构动力计算且配筋率较高时,若忽略钢筋对构件弹性模量的影响,会引起较大的误差。     

Empirical models and design codes in prediction of modulus of elasticity of concrete

Modulus of Elasticity (MOE) is a key parameter in reinforced concrete design. It represents the stress-strain relationship in the elastic range and is used in the prediction of concrete structures. Out of range estimation of MOE in the existing codes of practice strongly affect the design and performance of the concrete structures. This study includes: (a) evaluation and comparison of the existing analytical models to estimating the MOE in normal strength concrete, and (b) proposing and verifying a new model. In addition, a wide range of experimental databases and empirical models to estimate the MOE from compressive strength and density of concrete are evaluated to verification of the proposed model. The results show underestimation of MOE of conventional concrete in majority of the existing models. Also, considering the consistency between density and mechanical properties of concrete, the predicted MOE in the models including density effect, are more compatible with the experimental results.     

短碳纤维混凝土的弹性模量及泊松比性能试验

对短切碳纤维掺量为1%,2%的混凝土的150×150×150立方体的静力受压弹性模量及泊松比进行了试验,并和未掺短切碳纤维的普通混凝土的基体静力受压弹性模量及泊松比做了比较和分析,据此研究了一定基体混凝土强度下不同碳纤维体积分数对混凝土静力受压弹性模量及泊松比变化的影响,以期为以后研究积累经验。     

基于FWD弯沉数据的模量反算方法及影响因素

从模量反算问题的提出入手，对模量反算的方法和模量反算的影响因素进行了探讨，通过一定的理论分析计算，进一步说明了基于FWD弯沉数据模量反算的科学性与可行性，可为后续研究提供理论基础。     

埋藏条件下软弱夹层变形模量研究

在工程建设中,软弱夹层是影响岩体工程特性的重要因素,因软弱夹层揭露后易松弛,且松弛速度快,通常情况下很难得到初始条件变形模量参数。通过在玄武岩地区百余米深的平洞内进行的原位特大型变形试验,在预留软弱带上部的保护岩层以防软弱带松弛条件下,得到软弱夹层与上部不同厚度盖层的综合模量。利用弹性力学的原理求得软弱夹层在深埋原位状态下的变形模量,研究结果表明软弱带在深埋条件下具有较高的变形模量。     

不同温度条件下柔性保温砂浆弹性模量试验研究

针对普通保温砂浆受冷热环境的交替作用容易开裂问题,研制了高柔性保温砂浆,对柔性砂浆在不同温度条件下的抗压强度和弹性模量进行了研究与测试,证明柔性砂浆抵抗变形的能力增强,提高了保温砂浆的抗裂性能.     

Predicting uniaxial compressive strength,modulus of elasticity and index properties of rocks using the Schmidt hammer

The Schmidt hammer test is a non-destructive method which can be used in both laboratory and field to provide a quick and relatively inexpensive measure of rock hardness. The study investigated the relationship between the Schmidt hardness and modulus of elasticity, uniaxial compressive strength and index properties of nine types of rock including travertine, limestone, dolomitic limestone and schist. The empirical equations developed indicated the Schmidt hardness rebound values have a reliable relationship with the uniaxial compressive strength of rock (r = 0.92). Comparing the results with those reported by other researchers, it is concluded that no single relationship can be considered reliable for all rock types. Whilst the equations developed in this study may be useful at a preliminary stage of design, they should be used with caution and only for the specified rock types.      

Models to predict the uniaxial compressive strength and the modulus of elasticity for Ankara Agglomerate

Determination of the uniaxial compressive strength (UCS) and modulus of elasticity of block-in-matrix rocks (bimrocks) is often impossible in the laboratory since the preparation of the standard core samples from bimrocks is extraordinarily difficult. For this reason, some predictive models were developed to estimate the UCS and modulus of elasticity based on the volumetric portion of blocks in Ankara Agglomerate, which is composed of black and pink andesite blocks in a tuff matrix. The ratio of E_imin of blocks (5.99 GPa) to E_imax of the tuff matrix (2.83 GPa) is 2.2 for Ankara Agglomerate. In addition to this contrast, the minimum ratio of UCS values of andesite blocks (34.99 MPa) to matrix tuff (14.4 MPa) is 2.4. In the first stage of the study, fuzzy logic was used as a tool for the prediction of the UCS of Ankara Agglomerate based on its block and matrix constituents. UCS values for 164 agglomerate cores were evaluated in the prediction model based on fuzzy logic. A triangular chart expressed by “if-then” rules considers different constituent composition of the agglomerate. Considering the membership functions depending on the portion of constituents, a Mamdani fuzzy algorithm was constructed and a fuzzy triangular chart was obtained for the estimation of the UCS of the agglomerate. The ‘variance accounts for’ (VAF) and the root mean square error (RMSE) indices were calculated as 56.9% and 7.3, respectively, to characterize the prediction performance of the triangular chart. In the second stage of the study, the goal was to construct a prediction model for the estimation of the modulus of the elasticity. Regression analyses were performed using 103 UCSs and the unit weight data obtained from core samples prepared from tuff matrix, black and pink andesite blocks and agglomerate. An equation having a correlation coefficient of 0.951 was obtained from the regression analyses. The VAF and RMSE indices for the multiple regression equation were obtained as 88.8% and 0.84, respectively. Both correlation coefficient and the performance indices indicated that the prediction capacity of the equation is high.