Effect of partial replacement of geopolymer binder materials on the fresh and mechanical properties: A review

The growth of demand for concrete raises concerns about the consumption of natural resources and ordinary Portland cement. Geopolymer composites show promise as a sustainable alternative for conventional cement concrete. Considering the wide range of potential geopolymer composites applications (including suitability for transportation infrastructure, underwater applications, repair and rehabilitation of structures as well as recent developments in 3D printing), the desired fresh and mechanical properties of the geopolymer composite may vary between applications: for example, rapid setting can be a merit for certain applications and a demerit for others. Therefore, the desired fresh and mechanical properties (e.g., workability, setting time, compressive strength, etc.) can be controlled for a given geopolymer source material through its partial substitution by natural or by-product materials. Recognizing the critical role of various replacement materials in enhancing the potential applications of geopolymer composites, the present review was undertaken to quantify and understand the effect of partial replacement by fly ash, metakaolin, kaolin, red mud, slag, ordinary Portland cement, and silica fume on the setting time, workability, compressive strength and flexural strength of various source materials addressed in the literature. The review also provides insights into research gaps in the field to promote future research.     

Statistics of ceramic strength: Use ordinary Weibull distribution function or Weibull statistical fracture theory?

“Weibull statistics” for strength distribution analysis refers to either the ordinary Weibull distribution function or the Weibull statistical fracture theory. The ordinary Weibull distribution function is an empirical distribution function on an equal footing with other type of classical empirical distributions such as normal and log-normal distributions for fitting the statistical data of various random variables nonexclusive to materials strength. It has no explicit physical meaning and cannot be used for size scaling and prediction of strength. The Weibull statistical fracture theory is a weakest-link statistical fracture model for a solid with the strength distribution of an elemental volume being described by the ordinary Weibull distribution function. It has the capability of size scaling and prediction of strength for specimens with different geometries and different loading modes. The three-parameter Weibull statistical fracture theory in uniaxial flexure of prismatic beams is reformulated and validated by both numerical and real strength experiments of different ceramics.     

Multisensor data fusion via Gaussian process models for dimensional and geometric verification

An increasing amount of commercial measurement instruments implementing a wide range of measurement technologies is rapidly becoming available for dimensional and geometric verification. Multiple solutions are often acquired within the shop-floor with the aim of providing alternatives to cover a wider array of measurement needs, thus overcoming the limitations of individual instruments and technologies.In such scenarios, multisensor data fusion aims at going one step further by seeking original and different ways to analyze and combine multiple measurement datasets taken from the same measurand, in order to produce synergistic effects and ultimately obtain overall better measurement results.In this work an original approach to multisensor data fusion is presented, based on the development of Gaussian process models (the technique also known as kriging), starting from point sets acquired from multiple instruments. The approach is illustrated and validated through the application to a simulated test case and two real-life industrial metrology scenarios involving structured light scanners and coordinate measurement machines.The results show that not only the proposed approach allows for obtaining final measurement results whose metrological quality transcends that of the original single-sensor datasets, but also it allows to better characterize metrological performance and potential sources of measurement error originated from within each individual sensor.     

基于Kriging代理模型的复杂精馏系统操作参数优化

优化常减压装置的操作参数可有效提升炼化企业的经济效益，但基于其严格机理模型进行迭代寻优将十分耗时。为降低计算成本，提出了一种基于Kriging代理模型的常压精馏系统操作参数智能优化方法。该方法采用Kriging元建模技术构造精馏过程中关键操作参数与主要输出变量间的关系模型，并以此关系模型代理复杂精馏系统的MESH方程组（包括物料守恒方程M、气液平衡方程E、归一方程S、焓守恒方程H），在设计空间中采用粒子群优化（PSO）算法进行操作参数的全局智能搜索。所提方法不仅能够保证寻找到的操作参数全局最优，而且可以大幅度地减少求解的时间，具有十分明显的工程实用性。基于Aspen HYSYS的仿真试验表明了本文所提方法的有效性和优越性。     

全局力平衡PDC钻头布齿优化设计

针对聚晶金刚石复合片(PDC)钻头在钻井破岩过程中因受力不平衡，导致钻井倾斜、井径扩大、钻头产生横向振动和涡动，造成钻头早期失效的问题，基于已有PDC钻头切削力学知识，构建了PDC钻头弯曲力矩及全局力平衡布齿优化设计模型，并提出模型求解方法。布齿设计实例结果表明，采用全局力平衡布齿设计方法得到的布齿结构可使PDC钻头在不同进尺条件下均能保持全局力平衡状态，尤其低进尺（小于1 mm）时的力平衡状态得到极大改善，提高了PDC钻头的钻井稳定性，对于改善钻头受力、提升钻头使用寿命、提高钻井质量与效率具有重要意义。     

An efficient method for estimating time-dependent failure possibility by combining adaptive Kriging with adaptive truncated fuzzy simulation

Time-dependent failure possibility (TDFP) can measure the structural safety level for a time interval of interest under fuzzy uncertainty, but its calculational cost is unaffordable by using fuzzy simulation (FS) due to a required large size of FS candidate sampling pool (CSP). Although time-dependent adaptive Kriging model (T-AK) combined with FS (T-AK-FS) was presented to reduce the number of calling performance function, a large FS CSP still makes training T-AK time-consuming. To improve its efficiency, an adaptive truncated FS (ATFS) with T-AK (T-AK-ATFS) is proposed by CSP size reduction approach. By T-AK-ATFS, the largest safety hypercube in fuzzy standard space is adaptively searched, in which the samples are in safety states and can be removed from the FS CSP. Moreover, T-AK is adaptively trained to search the largest safety hypercube and estimate TDFP simultaneously. In adaptively searching process, the FS CSP is divided into several sub-CSPs, on which training T-AK is more time-saving. Overall, strategies of T-AK-ATFS include proposing ATFS to reduce the FS CSP, adaptively searching the largest safety hypercube, estimating the TDFP with the same T-AK and training T-AK in the sub-CSPs sequentially. Verified by examples, these strategies make T-AK-ATFS more efficient than existing FS and T-AK-FS.     

基于Kriging代理模型的TP304不锈钢裂尖驱动力概率预测（英文）

为了探究材料和载荷的随机性对TP304不锈钢裂尖驱动力的影响规律,通过将弹塑性有限元和Kriging代理模型相结合,实现裂尖驱动力的概率预测。为了提高有限元分析的效率,使用MATLAB对ABAQUS软件的前置处理和后置处理程序进行二次开发,实现随机样本的自动更改、批量计算和概率预测结果的自动分析。研究得到了随机因素作用下TP304不锈钢材料裂尖驱动力的统计分布规律,以及失效概率、失效概率密度函数、累计概率密度函数等概率特征,并对各随机因素的灵敏度进行了分析。最后,通过与Monte Carlo法对比分析了该方法的有效性和效率。结果表明,载荷和材料参数的随机性会显著影响TP304不锈钢裂纹尖端的驱动力,从而影响TP304不锈钢的失效概率,载荷和应变硬化指数对奥氏体TP304不锈钢材料裂尖驱动力的分散性影响最大。     

矿业地质统计学在我国的应用现状及对影响克立格估计的若干因素的研究

地质统计学已用于我国多个矿床的储量计算。变程Ａ是一个很稳健的变异参数，块金Ｃ０、基台Ｃ以及估计邻域的大小较大地影响着克立格估计。     

An emission-weighted proximity model for air pollution exposure assessment

Background

Among the most common spatial models for estimating personal exposure are Traditional Proximity Models (TPMs). Though TPMs are straightforward to configure and interpret, they are prone to extensive errors in exposure estimates and do not provide prospective estimates.

Method

To resolve these inherent problems with TPMs, we introduce here a novel Emission Weighted Proximity Model (EWPM) to improve the TPM, which takes into consideration the emissions from all sources potentially influencing the receptors. EWPM performance was evaluated by comparing the normalized exposure risk values of sulfur dioxide (SO₂) calculated by EWPM with those calculated by TPM and monitored observations over a one-year period in two large Texas counties. In order to investigate whether the limitations of TPM in potential exposure risk prediction without recorded incidence can be overcome, we also introduce a hybrid framework, a ‘Geo-statistical EWPM’. Geo-statistical EWPM is a synthesis of Ordinary Kriging Geo-statistical interpolation and EWPM. The prediction results are presented as two potential exposure risk prediction maps. The performance of these two exposure maps in predicting individual SO₂ exposure risk was validated with 10 virtual cases in prospective exposure scenarios.

Results

Risk values for EWPM were clearly more agreeable with the observed concentrations than those from TPM. Over the entire study area, the mean SO₂ exposure risk from EWPM was higher relative to TPM (1.00 vs. 0.91). The mean bias of the exposure risk values of 10 virtual cases between EWPM and ‘Geo-statistical EWPM’ are much smaller than those between TPM and ‘Geo-statistical TPM’ (5.12 vs. 24.63).

Conclusion

EWPM appears to more accurately portray individual exposure relative to TPM. The ‘Geo-statistical EWPM’ effectively augments the role of the standard proximity model and makes it possible to predict individual risk in future exposure scenarios resulting in adverse health effects from environmental pollution.