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.     

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.     

Interval analysis of mode shapes to identify damage in beam structures

Various damage detection methods have been proposed by several researchers in the past few decades. Amongst them, the efficiency of mode shapes in detecting damage has been demonstrated by many researchers when further processed. In most cases, the processing involves expansion or reduction of the mode shape data. However, vital information that are damage-prints are often lost during processing of the mode shape data. In addition, most of these processes involve long and complex computation, thus, leading to inaccurate damage identification. In this study, a simple and fast damage identification technique is proposed to identify damage in beam structures. Interval analysis is applied to the mode shapes of a beam structure in the damaged and undamaged states. The interval situations of each of the beam's segment via mode shape are derived to obtain the upper and lower bounds and the derived bounds are compared. To establish a relationship for identify the damaged point, a possibility of damage existence is defined for each segment of the beam structure. The mode shape increment is defined as the increase in the mode shape value. Furthermore, a damage measure index that provide enhance damage information is obtained as the product of the possibility of damage existence and mode shape increment. A numerical model of a simply supported steel beam is applied to demonstrate this method by imposing damage through thickness reduction of elements in segments. In addition, a parametric analysis is carried out to evaluate noise effect by considering varying damage severities and different noise levels. The results showed that this method is simple and provides considerable accurate results.     

Thermal performance and energy saving investigation in a modified baseboard radiator and compare it with conventional heating systems—Experimental and CFD approach

In the present work, thermal performance of a new modified baseboard radiator is investigated experimentally based on the European Standard EN-442. Temperature distribution and thermal comfort conditions of the floor heating system and panel radiator is compared with the present system numerically. To validation of the simulation results, a comparison has been made between the simulation and the experimental obtained results. Comparison shows that there is a good agreement between them. The heat output rate of the new system increased about 46.06% compared with conventional baseboard radiant model and also the baseboard heating system is capable of providing better thermal comfort conditions than two other systems. Energy consumption in three systems is investigated experimentally by smart temperature control mechanism. Results show that energy consumption in the baseboard radiant is 83.03% and 55.96% lower than floor heating system and panel radiator, respectively.     

汽轮机运行调节方式优化策略探析

分析了汽轮机的喷嘴调节、节流调节、旁通调节、定压调节和滑压调节等几种基本调节方式的特点,指出现役燃煤火电机组多因调节方式单一而普遍存在着调峰能力不足、负荷响应迟缓以及因长期偏离设计工况致使运行安全经济性下降等诸多问题,提出了通过调节方式的优化组合,采用(节流)定压-滑压-(喷嘴)定压-旁通调节的复合调节方式,以实现煤电机组安全、经济、灵活、快速地参与电网的深度调峰,破解具有强随机波动性的新能源电量规模化并网的困境。     

多约束下距离加权最优滑模末制导律

为解决多约束下制导炮弹的精确制导问题,采用带有相对距离权函数的最优滑模末制导律,将权函数引入到最优制导律中,通过改变制导炮弹的运动轨迹、运动时间,进而增强制导精度。针对单权函数难以同时满足制导精度与导引头视线角、过载等约束的问题,采用不同权函数的分段加权方法解决加权最优末制导引起的制导问题。结合滑模变结构控制理论,设计分段加权最优滑模末制导律,增强制导系统的抗干扰能力。仿真验证结果表明,该末制导律既能解决过载、导引头视线角、落角等多约束情况下的精确制导问题,同时又具有一定的鲁棒性。     

A robust locating multi-optima approach for damage identification of plate-like structures

This paper proposes a robust optimization approach for multiple damage identification of plate-like structures. Different from traditional particle swarm optimizations (PSOs), a combined PSO and niche technique (NPSO) is proposed to solve multimodal optimization problems, with the full consideration of subswarm creation, merging and absorbing mechanism. As a hypersensitive parameter to damage, the curvature mode shape is adopted to construct the objective function. Case studies are conducted to investigate the effectiveness and robustness of the algorithm on multi-damage identification. Simulation results show that the proposed algorithm exhibits robust search performance on identifying damage locations accurately with good convergence behavior. It is hoped that this study can provide guidance on robust damage detection, especially when the structure is subject to multiple damages and external disturbances.