Additive manufacturing,quasi-static and dynamic compressive behaviours of ceramic lattice structures

Ceramic lattice structures (CLSs) are used for construction in common and extreme environments because of the extraordinary properties of ceramics. In this study, we designed and additively manufactured CLSs with distinct structural parameters to explore their quasi-static and dynamic compressive behaviours in detail. It was demonstrated that both the relative density (?ρ) and inclination angle (ω) had a significant impact on the quasi-static and dynamic mechanical properties of the CLSs. Furthermore, the mathematical relationships between the quasi-static compressive properties, including quasi-static compressive strength (QS), quasi-static Young’s modulus (QY), and quasi-static energy absorption (QE), versus ?ρ and ω obeyed the Gibson–Ashby and Deshpande and Fleck models, respectively. It was revealed by experiment and simulation that as the stiffness increased, the quasi-static failure mode of the CLSs changed from a parallel-vertical-inclined mixed mode to a parallel-vertical mode. In addition, the relationship between the dynamic mechanical properties of the CLSs versus ?ρ and ω also followed the Gibson–Ashby and Deshpande and Fleck models. The exceptional dynamic increase factor indicated that CLSs are highly suitable for extreme environments. These findings will aid in the research and development of customised additively manufactured CLSs.     

Multi-criteria analysis for screening of reversible metal hydrides in hydrogen gas storage and high pressure delivery applications

Metals and alloys forming reversible hydrides with hydrogen gas are potential building blocks for compact, solid state hydrogen storage systems. Based on the materials’ thermodynamic characteristics, their use as temperature-swing gas compression and delivery systems in the hydrogen economy is also possible. Given the wide variety of materials developed and tested at laboratory and pilot scales, a harmonized method of selecting the feasible material(s) for a particular real-life application is required. This study proposes a system selection framework based on a normalized, multi-criteria metric. Using calculated values of multi-criteria metric, multi-criteria screening and ranking of potential materials has been demonstrated for a particular use case. It is found that the alloy TiMn_1.52 having value of additive metric between 0.25 and 0.35 represents the best material for a single stage system. The alloy pair CaNi₅–Ti_1.5CrMn represents the best alternative for a two-stage system with additive metric values between 0.63 and 0.82. Energy and economic characteristics of the metal hydride gas compression and delivery systems are evaluated and compared with an equivalent mechanical compression system producing the same final effect (i.e., delivery of a given quantity of gas at a defined pressure).     

STAR-Lite: A light-weight scalable self-taught learning framework for older adults’ activity recognition

Recognizing activities for older adults is challenging as we observe a variety of activity patterns caused due to aging (e.g., limited dexterity, limb control, slower response time) or/and underlying health conditions (e.g., dementia). However, existing literature with deep learning methods has successfully recognized activities when the dataset contains high-quality annotations and is captured in a controlled environment. On the contrary, data captured in a real-world environment, especially with older adults exhibiting memory-related symptoms, varying psychological and mental health status, reliance on caregivers to perform daily activities, and unavailability of domain-specific annotators, makes obtaining quality data with annotations challenging; leaving us with limited labeled data and abundant unlabeled data. In this paper, we hypothesize that projecting the labeled data representations comprising a specific set of activities onto a new representation space characterized by the unlabeled data comprising activities beyond the limited activities in the labeled dataset would help us rely less on the annotated data to improve activity detection performance. Motivated by this, we propose STAR-Lite, a self-taught learning framework that involves a pre-training framework to prepare the new representation space considering activities beyond the initial labels in the labeled dataset. STAR-Lite projects the labeled data representations on the new representation space characterized by unlabeled data labels and learns higher-level representations of the labeled dataset while optimizing inter- and intra- class distances without explicitly using a computation hungry similarity-based approach. We demonstrate that our proposed approach, STAR-Lite (a) improves activity recognition performance in a supervised setting and (b) is feasible for real-world deployment. To enhance the feasibility of deploying STAR-Lite on devices with limited memory resources, we explore model compression techniques such as pruning and quantization and propose a novel layer-wise pruning-rate optimization technique that effectively compresses the network while preserving the model performance. The evaluation was performed using the Alzheimer’s Activity Recognition dataset (AAR) captured from 25 individuals living in a retirement community center with IRB approval (#Y18NR12035) using an in-house SenseBox infrastructure while concurrently assessing the clinical evaluation of the participants for dementia, and independent living. Our extensive evaluation reveals that STAR-Lite can detect activities with an F1-score of 85.12% despite 62% reduction in model size and 5% improvement of execution time on a resource constrained device.     

基于磁开关技术的静电除尘脉冲电源

为提高静电除尘器的工作效率得到陡化的脉冲,提出基于磁开关技术的脉冲供电方式。在分析了多级磁脉冲压缩网络的工作原理及给出磁开关的参数选择基础上,通过PSPICE实现了对二级磁脉冲压缩电路的仿真,仿真结果表明,磁开关可有效陡化高压高频脉冲。     

Investigation into the long-term strength of rocks under loading with a constant rate

The test data are presented for tensile and compressive strength of some rocks depending on the rate of loading by three-point bending and then uniaxial rigid compression. The constants of Zhurkov’s kinetic equation of durability are determined for the tested rocks. __________ Translated from Fiziko-Tekhnicheskie Problemy Razrabotki Poleznykh Iskopaemykh, No. 6, pp. 37–44, November–December, 2007.     

压力分散型预应力锚索在高边坡加固中的应用

介绍了长珲公路的工程及地质概况、压力分散型预应力锚索在该工程中的应用、作用机理、施工工艺及张拉实验。     

多级围压下岩石三轴试验方法研究

作者在刚性伺服三轴试验机上通过简单的控制方式,采用单块或少量试件,实现多级围压作用下加载的三轴试验,并对砂岩、泥岩等试验结果进行了分析。使用该方法确定的粘聚力低于常规试验值而内摩擦角变化不大;同时该方法可以降低岩石试件间的差异对试验结果的影响。     

深部矿井内热源分析

深部矿井内的热害问题越来越受关注。介绍了深部矿井内热量的成因,将主要的十种热源进行了分类并给出了相关的物理公式和计算方法。     

一种用标贯击数直接确定粉土,砂土压缩模量的方法

本文通过对现行确定粉土、砂土压缩模量方法的利弊进行分析．提出一种使用标贯击数（标准值）直接确定粉土、砂土压缩模量Es1-2（标准值）的方法，并对其适用性结合已有经验公式和具体工程进行评价．具有一定的推广价值。     

砂岩单轴三轴压缩试验研究

研究了砂岩在饱和、自然、风干三种状态下的单轴抗压强度特性和三轴抗压强度特性。在单轴、三轴压缩试验中得到了应力与纵向应变、横向应变、体应变之间的关系曲线，单轴应力一纵向应变曲线在峰值前可分为3个阶段，三轴应力一纵向应变全过程曲线可分为4个阶段。根据三轴轴向应力和围压绘制丁莫尔圆，采用回归分析得到了强度准则和强度参数C、Φ值，并且分析了含水量对岩石强度的影响，其实验结果能为工程提供参考与借鉴。