单组份聚氨酯炮孔填塞剂应用性试验

炮孔填塞是爆破施工过程中的一个关键环节,也是践行精细爆破设计理论的重要措施。传统的炮泥填塞存在着诸多不足,为此,研制了以聚氨酯为基材的TK炮孔填塞剂,通过大量基础性能研究和隧道现场工业性试验,论证了其作为炮孔填塞材料可降低炸药单耗,提高单循环进尺和炮孔利用率,减小空气冲击波、爆破噪声等有害效应的影响,且是安全可靠的。TK炮孔填塞剂优良的填塞效果、方便快捷的施工方法及显著的经济效益,方便于在爆破工程中推广应用。     

Weighted preliminary-summation-based principal component analysis for non-Gaussian processes

For industrial chemical process, preliminary-summation-based principal component analysis (PS-PCA), an amended PCA method was recently provided for coping with both Gaussian and non-Gaussian characteristics. By summing the training and monitoring data respectively, PS-PCA is capable of resolving the issue of non-Gaussian processes and achieves higher fault detection rate than the traditional PCA. However, in the PS-PCA summation operation, all data samples are regarded as the same weight, which results in the fault information of newly-samples may be diluted, leading to significant detection delays. To address this challenge, in this paper, we propose a novel weighted PS-PCA (WPS-PCA) method that employs an exponential weighting scheme to put more emphasis on recent information. Subsequently, a mathematical argument demonstrates that when the number of variables is enough plentiful, the obtained summation combined with the generalized central limit theorem conforms to approximately a Gaussian distribution. The kurtosis relationships indicate this conversion will bring out well-pleasing feasibility for conventional PCA. Ultimately, the proposed technique verifies detection performance using the Tennessee Eastman process, which is compared with the existing PCA and PS-PCA schemes, in terms of the fault detection time and fault detection rate. The simulation studies reveal that the proposed method is efficient and superior.     

基于协同优化算法的流速仪检定系统设计

提出了一种小型轻便的流速仪检定系统的设计方案,并运用改进的多学科协同优化方法求解各学科设计变量的最优解。首先介绍了算法思想及改进措施,并根据系统设计要求建立了各学科的设计变量、目标函数和约束条件；其次,运用遗传算法求解各学科设计变量的最优解,并根据优化结果完善了系统的设计方案,同时运用计算机仿真等方法验证了优化结果的可行性。结果表明,优化后的检定系统满足流体力学效应、匀速运动时间、系统重量等设计要求,同时证明了协同优化算法解决多学科设计优化问题的有效性。     

Challenges and new methods for designing reliability experiments

Abstract

Engineers use reliability experiments to determine the factors that drive product reliability, build robust products, and predict reliability under use conditions. This article uses recent testing of a howitzer to illustrate the challenges in designing reliability experiments for complex, repairable systems. We review research in complex system reliability models, failure-time experiments, and experimental design principles. We highlight the need for reliability experiments that account for various intended uses and environments. We leverage lessons learned from current research and propose methods for designing an experiment for a complex, repairable system.     

A practical data-flow verification scheme for business processes

Data in business processes becomes more and more important. Current standard languages for process modeling like BPMN 2.0 which include the data flow reflect this. Ensuring the correctness of the data flow in processes is challenging. Model checking, i.e., verifying properties of process models, is a well-known technique to this end. An important part of model checking is the construction of the state space of the model. However, state-space explosion typically is in the way of an effective verification. We study how to overcome this problem in our context by means of reduction. More specifically, we propose a reduction on the level of the process model. To our knowledge, this is new for the data-flow analysis of processes. The core of our approach are so-called regions of the process model that are relevant for the verification of properties describing the data flow. Non-relevant regions are candidates for reduction of the process model, yielding a smaller state space. Our evaluation shows that our approach works well on industrial process models.     

Pertussis Toxin Inhibits Encephalitogenic T-Cell Infiltration and Promotes a B-Cell-Driven Disease during Th17-EAE

Pertussis toxin (PTX) is a required co-adjuvant for experimental autoimmune encephalomyelitis (EAE) induced by immunization with myelin antigen. However, PTX’s effects on EAE induced by the transfer of myelin-specific T helper cells is not known. Therefore, we investigated how PTX affects the Th17 transfer EAE model (Th17-EAE). We found that PTX significantly reduced Th17-EAE by inhibiting chemokine-receptor-dependent trafficking of Th17 cells. Strikingly, PTX also promoted the accumulation of B cells in the CNS, suggesting that PTX alters the disease toward a B-cell-dependent pathology. To determine the role of B cells, we compared the effects of PTX on Th17-EAE in wild-type (WT) and B-cell-deficient (µMT) mice. Without PTX treatment, disease severity was equivalent between WT and µMT mice. In contrast, with PTX treatment, the µMT mice had significantly less disease and a reduction in pathogenic Th17 cells in the CNS compared to the WT mice. In conclusion, this study shows that PTX inhibits the migration of pathogenic Th17 cells, while promoting the accumulation of pathogenic B cells in the CNS during Th17-EAE. These data provide useful methodological information for adoptive-transfer Th17-EAE and, furthermore, describe another important experimental system to study the pathogenic mechanisms of B cells in multiple sclerosis.     

Sintering of WC-Ni nanocomposite powder: Experimental and artificial neural networks modeling study

The sintering behavior of WC-Ni nanocomposite powder was evaluated through experimental and statistical approaches to study the contribution of involving parameters of chemical composition (Ni wt. %) and sintering temperature on sinterability of system by assessing the resulted densification and microhardness. The experimental process was designed based on factorial experimental design for independent effective parameters of Ni percentage (12, 18 and 23 wt %), and sintering temperature (8 different values within 1350–1485 °C). The resulted products of experimental testing after compaction and sintering were analyzed by FESEM and EDX to image the microstructure and evaluate the chemical composition and elemental distribution. The density and microhardness were measured as well. An artificial neural network (ANN) was applied to describe the corresponding individual and mutual impacts on sintering. The ANN model was developed by feed-forward back propagation network including topology 2:5:2 and trainlm algorithm to model and predict density and microhardness. A great agreement was observed between the predicted values by the ANN model and the experimental data for density and microhardness (regression coefficients (R²) of 0.9983 and 0.9924 for target functions of relative density and microhardness, respectively). Results showed that the relative importance of operating parameters on target functions (relative density and microhardness) was found to be 62% and 38% for sintering temperature and Ni percentage, respectively. Also, ANN model exhibited relatively high predictive ability and accuracy in describing nonlinear behavior of the sintering of WC-Ni nanocomposite powder. The experimental results confirmed that the appropriate sintering temperature was influenced by Ni content. The optimum parameters were found to be 12 wt % Ni sintered at 1460 °C with the highest microhardness and relative density.     

Optimisation of the spark plasma sintering process for high volume fraction SiCp/Al composites by orthogonal experimental design

Based on orthogonal experimental design (OED), the effects of the sintering pressure, sintering temperature and holding time on the mechanical properties of 50 vol% silicon carbide particle (SiCp)/2024Al composites prepared by spark plasma sintering (SPS) were investigated. The sintering pressure had the greatest effect on the density and bending strength of the material among these three factors, followed by sintering temperature and holding time. The optimised process conditions for producing the 50 vol% SiCp/2024Al were sintering at 550 °C for 5 min under 40 MPa, which resulted in a composite material with a density of 99.7% and good interface bonding with a comparatively high bending strength of 766.65 MPa. This work provides a promising method to produce high volume fraction composites that can meet high strength requirements.