Analysis of a magnetic field and Hall effects in nanoliquid flow under insertion of dust particles

In this study, the two‐phase hydromagnetic flow of a viscous liquid through a suspension of dust and nanoparticles is considered. The influence of the Hall current is also taken into account. The similarity variables are utilized to transform the problem into one independent variable. The obtained expressions in one independent variable are solved through the Runge–Kutta–Fehlberg scheme connected with the shooting procedure. The computed results are sketched for employing multiple values of physical constraints on the temperature and velocity of the nanofluid and dust phase. The characterization of various nanoparticles like Cu, Al₂O₃, TiO_2, and Ag on velocities and temperatures of both phases is made through plots. A comparative analysis in the limiting approach is presented to justify the present solution methodology. The range of emerging parameters is taken as 0 ≤ l ≤ 3, 0.1 ≤ β_t ≤ 3, 0 ≤ m ≤ 2.5, 0 ≤ M² ≤ 2, 0.1 ≤ β_v ≤ 3, 0 ≤ ? ≤ 0.4, and ?0.8 ≤ λ ≤ 0.8. From the study, it is revealed that β_t has the opposite effect on the temperature of dust and nanofluid phases. The Hall parameter m raises the profiles of velocities in the nanoliquid and dust phases. Also, it is found that the transverse velocities h(η) and H((η) and temperatures θ(η) and θ_p(η) rise for larger ?.     

Finite-time decentralized adaptive neural constrained control for interconnected nonlinear time-delay systems with dynamics couplings among subsystems

The problem of finite-time decentralized neural adaptive constrained control is studied for large-scale nonlinear time-delay systems in the non-affine form. The main features of the considered system are that 1) unknown unmatched time-delay interactions are considered, 2) the couplings among the nested subsystems are involved in uncertain nonlinear systems, 3) based on finite-time stability approach, asymmetric saturation actuators and output constraints are studied in large-scale systems. First, the smooth asymmetric saturation nonlinearity and barrier Lyapunov functions are used to achieve the input and output constraints. Second, the appropriately designed Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. Note that, due to unknown time-delay interactions and the couplings among subsystems, the controller design is more meaningful and challenging. At last, based on finite-time stability theory and Lyapunov stability theory, a decentralized adaptive controller is proposed, which decreases the number of learning parameters. It is shown that the designed controller can ensure that all closed-loop signals are bounded and the tracking error converges to a small neighborhood of the origin. The simulation studies are presented to show the effectiveness of the proposed method.     

Identification of factors that accelerate hydrogen production by Clostridium butyricum RAK25832 using casamino acids as a nitrogen source

The ability of Clostridium butyricum RAK25832 to use casamino acids as a nitrogen source was investigated. Strain RAK25832 showed the capacity to utilize different types of carbon sources. With glucose as a carbon source (10 g/L), the preferred final concentration of casamino acids was 26.67 g/L, with a cumulative hydrogen production, production rate, and yield of 2505 mL H₂/L, 160 mL/h, and 1.81 mol H₂/mol glucose, respectively. Eighteen metal elements were screened to identify the most important metals for biohydrogen production, and four elements were optimized. The optimal medium composition was MgCl₂·6H₂O (0.1 g/L), K₂HPO₄·3H₂O (6.67 g/L), NaHCO₃ (2.6 g/L), and FeCl₂·4H₂O (0.002 g/L). Vitamin supplementation of the medium showed no significant effect on hydrogen production. Under the optimized conditions, cumulative hydrogen production reached 3074 mL H₂/L. This is the first study to demonstrate the use of casamino acids as a nitrogen source by C. butyricum.     

Robust model for optimization of forming process for metallic bipolar plates of cleaner energy production system

Energy production systems such as proton-exchange membrane fuel cell (PEMFC) has a promising future in the cleaner energy market due to zero emissions. Rubber pad forming (RPF) process of metallic bipolar plates of PEMFCs is gaining attention among the researchers. Studies based on design of experiments have been conducted to find the crucial parameters of the forming process. These methods are based on the assumptions of the model structure, correlated residuals, etc., which can cause uncertainty in estimation ability of the model on unseen data. Therefore, the present study focuses on the design of robust models of these parameters for PEMFCs using an optimization approach of genetic programming (GP). The inputs from the experiments considered in GP are radius, the friction coefficient, the filling factor and the minimum thickness. Experiments on PEMFCs validates the performance of the GP models. Further, the relationships between the two inputs and the three outputs for PEMFCs are generated as well as the contributions of each input to each of the output. Optimization of the models generated by GP can further determine the forming quality of metallic bipolar plates of PEMFCs by an appropriate setting of the two inputs.     

A parallel noninvasive multiscale strategy for a mixed domain decomposition method with frictional contact

A multiscale extension for a parallel noninvasive mixed domain decomposition method is presented. After briefly exposing our noninvasive implementation of the Latin method, we present how the scalability of the algorithm is obtained by the partial verification of the constitutive law of the interfaces. We propose a new interpretation of the classical macrostrategy that imposes the overall balance of interface's forces. We also propose a new study of the macrostrategy that consists in enforcing the coarse continuity of the interfaces' displacement.     

An extended stochastic pseudo-spectral Galerkin finite element method (XS-PS-GFEM) for elliptic equations with hybrid uncertainties

Nouy and Clement introduced the stochastic extended finite element method to solve linear elasticity problem defined on random domain. The material properties and boundary conditions were assumed to be deterministic. In this work, we extend this framework to account for multiple independent input uncertainties, namely, material, geometry, and external force uncertainties. The stochastic field is represented using the polynomial chaos expansion. The challenge in numerical integration over multidimensional probabilistic space is addressed using the pseudo-spectral Galerkin method. Thereafter, a sensitivity analysis based on Sobol indices using the derived stochastic extended Finite Element Method solution is presented. The efficiency and accuracy of the proposed novel framework against conventional Monte Carlo methods is elucidated in detail for a few one and two dimensional problems.     

设备自诊断系统与数采管控体系论述

近年来,行业提出将信息化与产业的融合创新放在行业高质量发展的重要位置,提出由“制造”向“智造”转变。当前针对烟机设备的主要信息化手段多集中在设备状态监控、故障频次排序、设备故障原因等功能上的整合,主要是对烟机设备上原有各项数据进行后续的数据处理来实现。但是单纯依赖数据处理的方法无法及时有效地甄别出设备本体及工艺质量参数的异常。提出利用自诊断系统与数采管控体系弥补设备本体管控系统的短板,提升自动化生产的综合管控能力,并提出大数据应用方面的设想。     

光纤电流互感器自适应温度补偿系统

针对光纤光栅(FBG)电流互感器容易受到温度影响这一特性，设计了一种基于STM32单片机的光纤光栅电流互感器温度补偿系统。通过单片机实现PID自适应控制算法，锁定电流互感器输出的电压值恒定在静态工作点，从而实现电流互感器不受外界温度影响得到稳定的电流信号输出。实验结果表明，在22~39 ℃范围内，输出电压稳定度在±1%以内，解决了电流互感器受限于环境温度的问题，实现了电流与温度的同时测量。经过此方法改进后的电流互感器测量精度高、系统结构简单、成本低、可靠性高，加快了光纤光栅电流互感器的实用化进程。