温度对混凝土力学性质影响的颗粒流模拟研究

为探索混凝土在热力耦合作用下的宏观力学性质和微裂纹的变化规律,采用PFC软件中的热模块,对5种温度下的混凝土试块进行了数值模拟分析。研究结果表明:(1)温度和峰值强度呈现负相关关系,单轴抗压强度和弹性模量随温度的变化服从幂函数关系,且温度对于强度和变形参数的影响不同,强度相较于变化参数而言,对温度更加敏感。(2)随着温度的升高,由热破裂所造成的损伤不断增加,热损伤集中在界面过渡区。随着温度的升高,混凝土的破坏模式由剪切破坏逐渐转变为劈裂破坏。(3)600℃属于临界温度,在600℃之前,宏观力学性质和微裂纹扩展均变化剧烈;超过600℃以后,宏观力学性质的劣化和微裂纹的发展均放缓。     

Clustering adaptive canonical correlations for high-dimensional multi-modal data

Multi-modal canonical correlation analysis (MCCA) is an important joint dimension reduction method and has been widely applied to clustering tasks of multi-modal data. MCCA-based clustering is usually dimension reduction of high-dimensional data followed by clustering of low-dimensional data. However, the two-stage clustering is difficult to ensure the adaptability of dimension reduction and clustering, which will affect the final clustering performance. To solve the issue, we propose a novel clustering adaptive multi-modal canonical correlations (CAMCCs) method, which constructs a unified optimization model of multi-modal correlation learning and clustering. The method not only realizes discriminant learning of correlation projection directions under unsupervised cases, but also is able to directly obtain class labels of multi-modal data. Additionally, the method also realizes out-of-sample extension in class labels. Solutions of CAMCCs are optimized by an iterative way, and we analyze its convergence. Extensive experimental results on various datasets have demonstrated the effectiveness of the method.     

Efficient estimation of extreme quantiles using adaptive kriging and importance sampling

This study considers an efficient method for the estimation of quantiles associated to very small levels of probability (up to O(10⁻⁹)), where the scalar performance function J is complex (eg, output of an expensive-to-run finite element model), under a probability measure that can be recast as a multivariate standard Gaussian law using an isoprobabilistic transformation. A surrogate-based approach (Gaussian Processes) combined with adaptive experimental designs allows to iteratively increase the accuracy of the surrogate while keeping the overall number of J evaluations low. Direct use of Monte-Carlo simulation even on the surrogate model being too expensive, the key idea consists in using an importance sampling method based on an isotropic-centered Gaussian with large standard deviation permitting a cheap estimation of small quantiles based on the surrogate model. Similar to AK-MCS as presented in the work of Schöbi et al., (2016), the surrogate is adaptively refined using a parallel infill criterion of an algorithm suitable for very small failure probability estimation. Additionally, a multi-quantile selection approach is developed, allowing to further exploit high-performance computing architectures. We illustrate the performances of the proposed method on several two to eight-dimensional cases. Accurate results are obtained with less than 100 evaluations of J on the considered benchmark cases.     

Inverse identification of constitutive parameters from heat source fields: A local approach applied to hyperelasticity

In this paper, a new inverse identification method of constitutive parameters is developed from full kinematic and thermal field measurements. It consists in reconstructing the heat source field from two different approaches by using the heat diffusion equation. The first one requires the temperature field measurement and the value of the thermophysical parameters. The second one is based on the kinematic field measurement and the choice of a thermo-hyperelastic model that contains the parameters to be identified. The identification is carried out at the local scale, ie, at any point of the heat source field, without using the boundary conditions. In the present work, the method is applied to the challenging case of hyperelasticity from a heterogeneous test. Due to large deformations undergone by the rubber specimen tested, a motion compensation technique is developed to plot the kinematic and the thermal fields at the same points before reconstructing the heterogeneous heat source field. In the present case, the constitutive parameter of the Neo-Hookean model has been identified, and its distribution has been characterized with respect to the strain state at the surface of a cross-shaped specimen.     

三甘醇脱水填料塔计算方法适用性分析

塔径计算是进行三甘醇填料脱水塔设计的首要工作,为了选用准确适用的塔径计算方法,详细介绍了多种塔径计算方法。以两个实际项目的数据为计算案例,分别采用贝恩-霍根(Bain-Haugen)关联式、通用压降关联图法(GPDC)、塔负荷系数法、Aspen HYSYS软件等不同方法计算三甘醇填料脱水塔的塔径,并进行了计算结果偏差分析和计算方法适用性分析。结果分析表明,塔负荷系数法、通用压降关联图法(GPDC)、Aspen HYSYS软件计算结果相近,经圆整后的塔径一致。贝恩-霍根(Bain-Haugen)关联式算出的结果偏差较大,过于保守,分别为11.11%和8.73%。由于通用压降关联图法(GPDC)的计算结果受GPDC关联图内数据点影响准确度不易保证,建议选用塔负荷系数法和Aspen HYSYS软件进行三甘醇脱水填料塔塔径的计算。      

Empirical examination of critical failure factors of continuous improvement deployments: stage-wise results and a contingency theory perspective

Organisations implement various Continuous Improvement (CI) practices such as Total Quality Management, Lean, Six Sigma and Lean Six Sigma (LSS) for improving their processes. Drawing from the success and failure stories of these structured CI practices, scholars enumerated Critical Success Factors and Critical Failure Factors (CFFs). This study empirically examines the occurrence of various CFFs across different stages of CI deployment. Further, from a contingency theoretic perspective, this study investigates their associations with contextual variables by collecting survey data from 213 business units from the USA, the UK, China, and India. Principal Component Analysis is used to group CFFs across five CI deployment stages leading to an empirically refined framework for CI. Crosstab analysis using the chi-square likelihood ratio presented associations of CFFs with contextual variables. Findings reveal significant differences in the occurrence of CFFs across countries. There is evidence that LSS is less prone to failures when compared with TQM, Lean and Six Sigma. The occurrence of CFFs has been relatively lower in smaller and medium-sized enterprises operating in the service sector. Findings also reveal that lessons learned from each CI deployment cycle, contribute to organisational learning, and thence, leading to success at the strategic CI level of maturity.     

铠装硅酸钾胶黏剂在特殊工况下的绝缘失效分析

为探索铠装硅酸盐胶黏剂在特殊环境下的绝缘特性，本文制备不同碱金属离子含量及固液配比的硅酸钾胶黏剂样品，将其固封于不锈钢管体中，在潮湿环境与高温条件下分析其绝缘性能并进行失效分析。结果表明：在潮湿环境中，胶体中的固液配比及碱金属（K⁺）含量会影响铠装试样的整体绝缘性能，当固液配比为2∶1时，硅酸钾与硅溶胶质量比在（2～1）∶1之间时，其绝缘效果较佳；在高温条件下，随着温度的升高及保温时间的延长，铠装壳体中部分合金元素渗入胶体表面，造成样品绝缘性能较大幅度的下降。     

含V型相交裂隙岩体的力学特性及破坏模式试验

为深入了解V型相交裂隙岩体试件的力学特性和裂纹演化规律,采用MTS815电液伺服控制试验机对含不同夹角V型相交裂隙岩体试件进行了常规单轴压缩试验,基于试验结果,详细分析了试件的应力-应变曲线、强度与变形特性、裂纹演化与破坏模式及能量耗散特征。研究结果表明:①裂隙试件的应力-应变曲线进入裂纹萌生与扩展阶段早于完整试件,在峰前出现了明显的应力降现象,在峰后破坏阶段,完整试件表现为应力-应变曲线的快速跌落,而裂隙试件呈现台阶状多阶段性跌落,甚至缓慢水平下降,体现出明显的延性破坏特征;②裂隙试件的峰值应力、弹性模量和峰值应变均有明显减小。峰值强度和弹性模量随裂隙夹角的增加呈先增大后减小的变化趋势。轴向峰值应变主要受裂隙夹角的影响,总体随夹角的增大呈线性减小的趋势;③裂隙的存在能够完全改变岩体试件的破坏模式,随着裂隙夹角的逐渐增加,裂隙试件破坏模式的演化过程为:台阶式张拉-剪切复合破坏(30°)→张拉-八字形剪切复合破坏(60°)→台阶式平行双斜面剪切破坏(90°)。当裂隙夹角为60°时,试件的裂纹演化和破坏模式体现出对加载方向近似的结构对称性特征;④相交裂隙试件单轴压缩破坏的弹性应变能、耗散能、总能量和能量耗散率均较完整试件有大幅度的减小。裂隙试件产生的裂纹数量越多,试件表面的脱落现象越明显,耗散能和能量耗散率也越大。拉-剪复合破坏比单纯剪切破坏要消耗更多的能量。试件的破坏特征和破坏模式能很好地反映试件的能量耗散特性。     

基于广义二次互相关的低信噪比信号时延估计

针对时延估计精度受噪声影响,导致时延估计不准确的问题,在现有广义二次相关算法的基础上,提出了一种改进的广义二次相关算法,通过将二次相关函数先做指数运算,降低噪声干扰,再将傅里叶逆变换得到的相关函数做高次方运算,达到锐化峰值提高时延正确率的目的。仿真结果表明,信噪比(SNR)在0~10 dB时,改进算法的均方根误差明显优于广义二次相关算法,正确率相比于广义二次相关算法也显著提高,且在更低SNR的情况下仍然具有一定优势。     

Estimation of Antenna Correlation Coefficient of N-Port Lossy MIMO Array

This paper proposes a simple yet accurate method for estimating the antenna correlation coefficient (ACC) of a high-order multiple-input multiple-output (MIMO) antenna. The conventional method employed to obtain the ACC from three-dimensional radiation patterns is costly and difficult to measure. An alternate method is to use the S-parameters, which can be easily measured using a network analyzer. However, this method assumes that the antennas are highly efficient, and it is therefore not suitable for lossy MIMO antenna arrays. To overcome this limitation, we define and utilize the non-coupled radiation efficiency in the S-parameter-based ACC formula. The accuracy of the proposed method is verified by the simulation results of a 4-port highly coupled lossy MIMO array. Further, the proposed method can be applied to N-port arrays by expanding the calculation matrix.