一种“KooN”结构的马尔可夫简并建模和简化计算的方法

IEC61508等标准提出了几种计算安全仪表系统需求时平均失效概率的方法,但是,对于具有冗余配置的复杂系统,随着组件数量的增加,系统的中间状态数量快速增长,用户难以构建马尔可夫模型,即便借助计算机来建模运算也较为耗时。提出了一种同型“K oo N”简并状态的马尔可夫建模的通用方法,首先是根据降级状态进行判断,将符合条件的状态进行简并,然后对标记为危险失效状态的概率进行计算。通过严格的理论推导,该简并状态方法可以在不损失精度的前提下简化马尔可夫建模。     

Combined effect of channel to rib width ratio and gas diffusion layer deformation on high temperature – Polymer electrolyte membrane fuel cell performance

The present study investigates the combined influence of Channel to Rib Width (CRW) ratio and clamping pressure on the structure and performance of High Temperature-Polymer Electrolyte Membrane Fuel Cell (HT-PEMFC) using a three-dimensional numerical model developed previously. It also considers the impact of interfacial contact resistance between the Gas Diffusion Layer (GDL) and Bipolar Plate (BPP). The structural analysis of the single straight channel HT-PEMFC geometry shows that the von-Mises stress greatly increases in the GDL under the ribs as the CRW ratio increases resulting in considerably high deformation. The cell performance analysis depicts the significance of ohmic resistance and concentration polarization for different CRW ratios, particularly at higher operating current densities. However, in low to medium current density regions, the CRW ratio has little influence on cell performance. A substantial impact on the species, overpotential, and current distributions is observed. The findings also reveal that the CRW ratio significantly affects the temperature distribution in the cell.     

天问一号高分相机多状态可靠性建模方法

为了分析天问一号火星高分相机不同状态对性能的影响,最大限度提高使用效率,对高分相机的多状态、状态变化过程和仿真方法开展研究。首先,分析相机的组成和不同功能单元退化产生的影响。然后,分析相机在轨工作的多状态变化规律,建立转化过程模型。最后,提出基于多状态的仿真建模方法。案例仿真分析结果表明:考虑调整后实际有效数据获取概率提高评估准确性,通过敏感度分析也可有效提出调焦单元可靠性要求。多状态分析方法可有效评估火星相机或其他航天光学载荷可靠性水平,有效指导可靠性要求的制定和工程设计。     

Acidification of the electrolyte during the galvanic corrosion of AA7075: A numerical and experimental study

The electrochemical interactions between aluminum alloy 7075 and low-carbon steels under gelled electrolytes were studied. Such electrolytes provided the opportunity to investigate both thick and thin electrolyte systems. The electrolyte was chemically modified to visually track the acidic fronts during the anodic reaction and the subsequent hydrolysis process. Two mathematical models were validated for both thick and ultrathin electrolytes. The acidification of thick electrolytes was extended some millimeters beyond the aluminum alloy surface, whereas the acidic front was localized next to the metallic joint using ultrathin electrolytes. The combination of both numerical and experimental results allows proving (and explaining why) that the acidification process is more aggressive under dilute than under concentrated electrolytes.     

Form selection of concomitant polymorphs: A case study informed by crystallization kinetics modeling

Molecular mechanisms and process kinetics of crystallizing concomitant polymorphs remain poorly understood. Solvent-mediated phase transformation and concomitant crystallization are difficult to be distinguished in practice, as multiple forms can be detected at the same time. Herein, we developed a population balance model to simulate a concomitant crystallization process of two polymorphs of tolfenamic acid. Our kinetic modeling aims to understand concomitant crystallization and help guide form selection of such a molecular system. Crystallization kinetics of ethanolic solutions were uncovered from induction time measurements, as well as seeded and unseeded crystallization experiments. Experimental and simulation results demonstrate that the stable form I crystallizes concomitantly with the metastable form II. The faster growing form II results in an intermediate decline in the composition of form I in crystallized samples, a characteristic feature of the concomitantly crystallized system. A four-quadrant scheme of attainable polymorph outcome was simulated under various crystallization conditions.     

A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network

Identification of feasible region of operations in multivariate processes is a problem of interest in several fields. This is particularly challenging when the process model is black-box in nature and/or is computationally expensive, as analytical solutions are not available and the number of possible model evaluations is limited. An efficient methodology is required to identify samples where the model is evaluated for developing a computationally efficient surrogate model. In this work, an artificial neural network based surrogate model is proposed which is integrated with a statistical-based approach (Jack-knifing) to estimate the variance of the surrogate model prediction. This allows implementation of an adaptive sampling approach where new samples are identified close to the feasible region boundary or in regions of high prediction uncertainty. The proposed approach performs better than a previously published kriging based method for different dimensionality case studies.     

Mathematical Modeling of Drying Processes of Selected Fruits and Vegetables

This study investigates the behavior of fruit and vegetable samples during drying. The experimental data are fitted to several different thin-layer drying models. Regression analysis is used to determine model parameters, while statistical indicators serve to evaluate the goodness of fit. The power function model gives the best fit for all examined samples. Based on this model, different drying and heat storage technologies can be combined to ensure that the required residual moisture content of an agricultural product is reached. It is demonstrated on the case of a specific Togolese processing plant that under favorable conditions, fossil fuel consumption can be decreased by 33 %.     

Understanding the asymmetric perceptions of smartphone security from security feature perspective: A comparative study

Smartphones are being used and relied on by people more than ever before. The open connectivity brings with it great convenience and leads to a variety of risks that cannot be overlooked. Smartphone vendors, security policy designers, and security application providers have put a variety of practical efforts to secure smartphones, and researchers have conducted extensive research on threat sources, security techniques, and user security behaviors. Regrettably, smartphone users do not pay enough attention to mobile security, making many efforts futile. This study identifies this gap between technology affordance and user requirements, and attempts to investigate the asymmetric perceptions toward security features between developers and users, between users and users, as well as between different security features. These asymmetric perceptions include perceptions of quality, perceptions of importance, and perceptions of satisfaction. After scoping the range of smartphone security features, this study conducts an improved Kano-based method and exhaustively analyzes the 245 collected samples using correspondence analysis and importance satisfaction analysis. The 14 security features of the smartphone are divided into four Kano quality types and the perceived quality differences between developers and users are compared. Correspondence analysis is utilized to capture the relationship between the perceived importance of security features across different groups of respondents, and results of importance-satisfaction analysis provide the basis for the developmental path and resource reallocation strategy of security features. This article offers new insights for researchers as well as practitioners of smartphone security.     

Multiple material domain‐based computational tools for ease assessment of modal parameter in photonic crystal fibers

We report here the development of two computational tools PCFPS (Photonic Crystal Fiber Parameter Study) and PCFPA (Photonic Crystal Fiber Parameter Analysis), equipped with graphical user interface (GUI) for modeling of photonic crystal fiber. The tools are based on different structural parameters, and they provide characteristic analysis of the modal parameters from the structural parameters. The main feature of PCFPS is that it enables the user to find out the values of each defining modal parameter that has an immense contribution towards the manufacture of photonic crystal fiber. Additionally, PCFPA allows the user to observe the variation in the modal parameters with respect to the changes in structural parameters (such as d, Λ, d/Λ, and λ/>Λ). Besides their ease of use, these two schemes have high computational precision and adaptability, giving a novel platform to optical engineers to modulate the microstructured fibers according to their requirement.