Dimensional considerations on the mechanical properties of 3D printed polymer parts

Additive manufacturing offers a useful and accessible tool for prototyping and manufacturing small volume functional parts. Polylactic acid (PLA) and thermoplastic polyurethane (TPU) are amongst the most commonly used materials. Characterising 3D printed PLA and TPU is potentially important for both designing and finite element modelling of functional parts. This work explores the mechanical properties of additively manufactured PLA/TPU specimens with consideration to design parameters including size, and infill percentage. PLA/TPU specimens are 3D-printed in selected ISO standard geometries with 20%, 60%, 100% infill percentage. Tensile and compression test results suggest that traditional ISO testing standards might be insufficient in characterising 3D printed materials for finite element modelling or application purposes. Infill percentage in combination to design size, may significantly affect the mechanical performance of 3D printed parts. Dimensional variation may cause inhomogeneity in mechanical properties between large and small cross section areas of the same part. The effect was reduced in small cross section parts where reducing the nominal infill had less effect on the resulting specimens. The results suggest that for 3D printed functional parts with significant dimensional differences between sections, the material properties are not necessarily homogeneous. This consideration may be significant for designers using 3D printing for applications, which include mechanical loading.     

Predicting Regioselectivity in Radical C−H Functionalization of Heterocycles through Machine Learning

Radical C−H bond functionalization provides a versatile approach for elaborating heterocyclic compounds. The synthetic design of this transformation relies heavily on the knowledge of regioselectivity, while a quantified and efficient regioselectivity prediction approach is still elusive. Herein, we report the feasibility of using a machine learning model to predict the transition state barrier from the computed properties of isolated reactants. This enables rapid and reliable regioselectivity prediction for radical C−H bond functionalization of heterocycles. The Random Forest model with physical organic features achieved 94.2 % site accuracy and 89.9 % selectivity accuracy in the out-of-sample test set. The prediction performance was further validated by comparing the machine learning results with additional substituents, heteroarene scaffolds and experimental observations. This work revealed that the combination of mechanism-based computational statistics and machine learning model can serve as a useful strategy for selectivity prediction of organic transformations.     

变刚度梁柱理论及其应用

为解决井斜控制实践中存在的不等截面尺寸梁柱问题, 讨论了典型的变刚度纵横弯曲梁力学 模型. 根据变刚度梁柱变形的挠曲线微分方程和边界条件及连续条件, 得到了梁柱变形和端 部转角的解析计算式, 进而应用梁柱理论叠加原理可解决有集中力作用下的井下控制工具和 带变径稳定器的底部钻具组合(BHA)受力分析问题. 变刚度梁柱理论在BHA力学分析中得到了 成功应用, 为井下控制工具设计、钻具组合优化及井斜控制提供了理论依据.     

一种基于混合策略的自适应多输出高斯过程响应面法

针对工程结构数值模拟常常是矢量与函数(矢量函数)混合输出的特点,提出一种基于混合策略的含索引变量的矢量高斯过程响应面法,同时提出一种设计点自适应加密方法进一步提高效率。算例显示:本文方法能够优先拾取预测误差最大的点作为加密点;真实误差全部都落在最大可能误差范围之内,最大误差1.4%~1.6%远小于预设误差限5%,验证了本文方法的有效性。     

纳米铜自修复性能评价标准研究

为了建立纳米抗磨添加剂自修复性能的评价标准,提出了以磨损试验后试块质量增重为衡量依据的实验设想。以商品纳米Cu抗磨自修复剂作为考察对象,在高速环块磨损试验机上,发现了在不同试验力、转速、试验时间和添加剂浓度等试验条件下,试块摩擦增重的变化规律,从而提出了对添加剂自修复性能进行评定的试验方法和条件,并进行了重复性和再现性测试。通过扫描电子显微镜、X射线能量色散谱仪等对磨痕表面形貌和元素的分析,证实了添加剂的抗磨自修复性能和评价方法的可行性。     

漫谈统计学的应用与发展(4)

本文分两部分:第一部分通过20多个实际案例说明统计学在各个领域的广泛应用,希望使更多的人对统计学有更全面、更深切的了解;第二部分简要介绍统计学在国内外的发展概况,并通过其发展进程的介绍,进一步阐明统计学的意义与价值。同时列举更多的论据说明近代统计学是当今最重要的科学技术之一。     

广义Pareto模型统计推断及其应用

广义Pareto分布能很好地拟合数据分布的尾部,广泛地应用于金融市场的风险管理、风险经营问题的研究。利用概率加权矩法得到了三参数广义Pareto模型的参数估计式,给出了阈值的选取方法和风险值的计算公式;利用计算机模拟,计算得出了KS检验统计量的临界值。     

LARGE DEVIATIONS AND MODERATE DEVIATIONS FOR SUMS OF NEGATIVELY DEPENDENT RANDOM VARIABLES

In this article, we obtain the large deviations and moderate deviations for negatively dependent (ND) and non-identically distributed random variables defined on (-∞, +∞). The results show that for some non-identical random variables, precise large deviations and moderate deviations remain insensitive to negative dependence structure.     

概率论与数理统计课程改革的创新机制

针对课程改革的目的,结合教学实践,就概率统计课程建设和教学改革的必要性进行综合分析并主张：通过讲述概率统计理论发展史,引导学生明确学习重点;借助多媒体教学,整合教学大纲内容,系统教学;将理论与实际相联系,激发学生学习兴趣;立足基本理论,开设统计学软件实验课程．     

非Lipschitz条件Hilbert空间上扩散过程的短时间大偏差原理

Under the non-Lipschitzian condition, a small time large deviation principle of diffusion processes on Hilbert spaces is established. The operator theory and Gronwall inequality play an important role.