Influence of density on the post-suffusion behavior of gap-graded sand with fines

Suffusion erosion, characterized as the selective detachment and transportation of finer particles by seepage flow, is hazardous to the stability and serviceability of geotechnical structures. The removal of finer particles deteriorates the structure and fabric of the soil, leading to the degradation of its mechanical properties. Studies into the effects of suffusion on mechanical behavior have so far produced disparate results depending on the pre-erosion relative density of the specimens tested. To investigate this issue, small cyclic and monotonic loading tests were performed on intact and eroded gap-graded silty sand specimens in three dispersed density states, using a triaxial cell modified for the purpose of erosion. The variation of Young's modulus showed an inverse relationship with the pre-erosion density of the specimen, as the small strain stiffness decreased in the dense cases and increased in the loose cases. Conversely, Poisson's ratio increased in value as suffusion progressed regardless of the initial density of the specimens. In the contractive phase of monotonic loading, the densification of the coarse soil skeleton by the downward seepage flow resulted in a decrease in contractiveness and an increase in secant stiffness. In the dilative phase, the increase in porosity by the erosion of finer particles reduced the dilatancy and peak strength of the specimens. The results suggest that the pre-suffusion density determines the primary locus of affected mechanical behavior in triaxial compression, which shifts from the contractive phase to the dilative phase with the increase in pre-suffusion density. The critical state strength, inferred using stress–dilatancy theory, was largely unaffected by the erosion of finer particles. As the results indicate, pre-erosion density may be of practical significance in assessing the vulnerability to deterioration and collapse of geotechnical formations and structures subjected to suffusion erosion.     

基于DSP的智能电源控制单元设计与实现

本文利用TI公司TMS320F28335芯片高效的浮点运算能力,结合片上丰富的外设,设计并实现了一种具有高可靠性的智能电源控制单元。该控制单元周期性地对各片上外设进行自检维护,完成多路负载通道控制、电压、电流的实时监控,并对故障进行指示、处理和上报,同时提供人机交互界面更新状态信息。经过验证,该控制单元工作稳定,具备良好的工程应用价值。     

A novel adaptive convolutional neural network for fault diagnosis of hydraulic piston pump with acoustic images

As an essential part of hydraulic transmission systems, hydraulic piston pumps have a significant role in many state-of-the-art industries. Thus, it is important to implement accurate and effective fault diagnosis of hydraulic piston pumps. Owing to the heavy reliance of shallow machine learning models on the expertise and experience of engineers, fault diagnosis based on deep models has attracted significant attention from academia and industry. To construct a deep model with good performance, it is necessary and challenging to tune the hyperparameters (HPs). Since many existing methods focus on manual tuning and use common search algorithms, it is meaningful to explore more intelligent algorithms that can automatically optimize the HPs. In this paper, Bayesian optimization (BO) is employed for adaptive HP learning, and an improved convolutional neural network (CNN) is established for fault feature extraction and classification in a hydraulic piston pump. First, acoustic signals are transformed into time–frequency distributions by a continuous wavelet transform. Second, a preliminary CNN model is built by setting initial HPs. The range of each HP to be optimized is identified. Third, BO is employed to select the optimal combination of HPs. An improved model called CNN-BO is constructed. Finally, the diagnostic efficiency of CNN-BO is analyzed using a confusion matrix and t-distributed stochastic neighbor embedding. The classification performance of different models is compared. It is found that CNN-BO has a higher accuracy and better robustness in fault diagnosis for a hydraulic piston pump. This research will provide a basis for ensuring the reliability and safety of the hydraulic pump.     

基于村落宅图的分类及量化研究——以徽州传统村落群为例

本文以江西省婺源县沱川乡理坑、浙源乡虹关以及思口镇西冲的3次村落测绘作为研究的起点,逐步拓展至对12份徽州传统村落宗族图谱中的村落宅图进行分类及量化研究。通过对村落宅图的研究来还原徽州传统村落群的空间形态,探究其背后的地缘影响、血缘纽带和社会维系,归纳总结出9种村落群的基本构成要素及其所占比率,揭示村落群的空间构成和形态要素。希望在此基础上推演村落群形态的历史演变过程,还原与诠释村落群背后隐藏的内在秩序。     

Optimal data-based binning for histograms and histogram-based probability density models

Histograms are convenient non-parametric density estimators, which continue to be used ubiquitously. Summary quantities estimated from histogram-based probability density models depend on the choice of the number of bins. We introduce a straightforward data-based method of determining the optimal number of bins in a uniform bin-width histogram. By assigning a multinomial likelihood and a non-informative prior, we derive the posterior probability for the number of bins in a piecewise-constant density model given the data. In addition, we estimate the mean and standard deviations of the resulting bin heights, examine the effects of small sample sizes and digitized data, and demonstrate the application to multi-dimensional histograms.     

智能网联汽车变车距队列控制与仿真

智能网联汽车的发展是将来智能交通系统中的一个重要方向,受基础设施条件以及试验成本的限制,目前的测试验证仍以计算机仿真为主。针对现有仿真软件难以满足智能网联汽车测试需求的问题,以开源软件PLEXE为基础,通过对其道路交通模拟器中的车辆动力学模型、通信拓扑结构以及车辆队列控制器等关键模块进行二次开发,设计了面向智能网联汽车队列控制研究的可视化仿真平台,对变车距队列控制算法进行仿真验证。仿真结果表明:上述平台可完成队列控制的可视化仿真,相比其它软件更加直观形象。     

Experimental study of remaining creep life of SA-304L stainless steel using small punch creep test

In this paper, the remaining creep life of SA-304L stainless steel at elevated temperatures is studied. The small punch creep tests (SPCT) were performed on SA-304L virgin and aged materials at constant loads. Times to fracture and the minimum deflection rate in SPCTs were recorded, and the time-temperature parametric analysis was performed, based on experimental results. The constants of the Larson–Miller parameter and the Monkman–Grant relationship were obtained for different consumed creep life ratios, and eventually the equations were established to explain the variation of constants of the Larson–Miller parameter and the Monkman-Grant relationship with respect to the consumed creep life ratio.     

车寨煤矿综采工作面智能化技术

为响应晋煤集团公司实现智慧矿山的号召，全面落实集团公司转型发展的重要措施，真正实现“一矿一策一模式”的建矿理念，车寨矿井全面实施井下智能化综采工作面，充分结合车寨矿井实际情况，坚持整体规划、统一标准、分步实施的原则，在现有技术水平的基础上，因地制宜地开展智能化综采工作面相关技术工作。通过综采工作面智能化技术，对降低成本、减少人员劳动强度、提高设备的使用效率、促进实现本质安全、提高企业管理水平起到非常重要的保障性作用，经过细致规划，精细实施，车寨矿井成为业务信息化、调度可视化、决策智能化的先进智慧化矿山。     

Effect of biohydrogen by overexpressing small RNA RyhB combined with ldh impairment in novel Klebsiella sp. FSoil 024

Biotechnological hydrogen production is considered as an environmentally sustainable alternative to petrochemical sources or electrolysis. Here, disruption of lactate dehydrogenase (LDH) and metabolic regulation via the small RNA RyhB were adopted to improve hydrogen production in the novel Klebsiella sp. strain FSoil 024. The hydrogen production of FSoil 024-L (Δldh) and FSoil 024-L/R (Δldh/RyhB) from glucose in a 5-L fermenter respectively increased by 40 and 50% compared to the wild type. When glycerol was adopted as a more favorable substrate, FSoil 024-L generated 3.3 L/L of hydrogen after 52 h of fermentation, implying its great potential for the utilization of crude glycerol to produce hydrogen. Overexpression of RyhB downregulated formate biosynthesis in FSoil 024, thereby redirecting NADH toward the hydrogen production pathway. This finding provides new insights into the role of cellular reducing power in hydrogen metabolism and establishes a rationale for improving hydrogen production.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.