Heat and mass transfer flow over a stretching surface with Ohmic heating and chemical reaction

The present study analyzes the effect of chemical reaction on an unsteady magnetohydrodynamic boundary layer viscous fluid over a stretching surface embedded in a porous medium with a uniform transverse magnetic field. A Darcy‐Forchheimer drag force model is employed to simulate the effect of second‐order porous resistance. Dissipative heat energy based on both viscous and Joule dissipation along with a heat source/sink is considered to enhance the energy equation. Similarity analysis is imposed to transform the governing differential equations into a set of nonlinear coupled ordinary differential equations. These sets of equations are solved numerically using the Runge‐Kutta fourth‐order scheme followed by the shooting algorithm. The effects of physical parameters such as magnetic field, Prandtl number, Eckert number, Schmidt number, unsteadiness parameter, and chemical reaction parameters have been discussed on velocity, temperature, and concentration fields. Computation for the coefficient of skin friction, rate of heat and mass transfer is done and presented in a table for validation of the present outcomes.     

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was hypothesized on timolol-loaded liposomes. As tutorial data for ANN, causal factors were used, which were fed into the computer program. The number of training cycles has been identified in order to optimize the performance of the ANN. The optimization was performed by minimizing the error between the predicted and real response values in the training step. The results showed that training was stopped at 10?000 training cycles with 80% of the pattern values, because at this point the ANN generalizes better. Minimum validation error was achieved at 12 hidden neurons in a single layer. MLR has great prediction ability, with errors between predicted and real values lower than 1% in some of the parameters evaluated. Thus, the performance of this model was compared to that of the MLR using a factorial design. Optimal formulations were identified by minimizing the distance among measured and theoretical parameters, by estimating the prediction errors. Results indicate that the ANN shows much better predictive ability than the MLR model. These findings demonstrate the increased efficiency of the combination of ANN and design of experiments, compared to the conventional MLR modeling techniques.     

Passivity and synchronisation of complex dynamical networks with multiple derivative couplings

Two network models with multiple derivative couplings and different dimensions of output and input vectors are investigated in this paper. The problem of passivity for the proposed network models is analysed by utilising some inequality techniques and Lyapunov functional method, and several synchronisation conditions for complex dynamical networks with multiple derivative couplings (CDNMDC) are given. Moreover, by employing adaptive state feedback control strategy, some sufficient conditions for guaranteeing passivity and synchronisation of CDNMDC are obtained. In the end, we give two examples to verify the effectiveness of the results.     

Assessment of plastic damage in high strength structural steel using electromagnetic technique

ABSTRACT

High strength structural (HSS) steels are widely used in many construction equipment and infrastructures. Currently, there is a substantial demand of Non-Destructive Testing of these steel structures. In this research, the electromagnetic technique was utilised to assess the plastic damage in a typical HSS steel (i.e. Q690 steel). The results showed that the magnetic hysteresis loop of this material changed apparently after the tensile deformation, and the relevant magnetic parameters such as coercivity, remanence, and maximum permeability were sensitive to the cumulative plastic strain. The results demonstrated that there is a good coherence between the plastic damage evolution and the magnetic parameters variation, which indicated that the electromagnetic technique is an effective method to assess the plastic damage of HSS steel.     

On monitoring the process mean of autocorrelated observations with measurement errors using the w-of-w runs-rules scheme

Runs-rules have been widely used since the 1950s in industrial and nonindustrial process monitoring applications to improve the performance of basic and other traditional monitoring schemes. However, none of the studies on runs-rules have accounted for a process with a combined effect of measurement errors and autocorrelation. Hence, in this paper, the use of the w-of-w runs-rules to improve the performance of the Shewhart $\overline{X}$ scheme using an additive model with a constant variance and a first-order autoregressive model is proposed. To reduce the combined negative effect of measurement errors and autocorrelation, we implement a sampling strategy based on rational subgroups in which (a) multiple measurements per item are taken (instead of a standard single measurement) and (b) non-neighboring observations are gathered. Moreover, the latter sampling strategy is incorporated into the values of probability elements of a Markov chain matrix which is used to derive some closed-form expressions for the zero- and steady-state run-length distribution. The main finding of this study is that, with respect to some overall performance measures, the proposed scheme outperforms the existing Shewhart $\overline{X}$ scheme by a significant margin. A real-life example is used to illustrate the practical implementation of the proposed scheme.     

Investigation of the hydrogen induced cracking behaviour of API 5L X65 pipeline steel

The effect of microstructural features on the hydrogen induced cracking (HIC) susceptibility of two API 5L X65 pipeline steels were investigated by cathodic charging, hydrogen permeation and hydrogen microprint experiments. Microstructural evaluation after hydrogen charging revealed cracks at the mid-thickness (segregation zone) of both plates. However, more severe cracks were observed in the plate with higher dislocation density and residual stresses. The plate with lower plastic strain and more {111}-oriented grains had less severe cracks. Inclusions found along the crack path, comprising of Si-enriched oxides and carbides contributed to the initiation and propagation of cracks. The variation of the trapping behaviour and hydrogen diffusion through the plates were examined. The results confirmed that a higher ratio of reversible to irreversible traps contributes to increasing HIC severity in steels. Additionally, hydrogen transport through the steels was most prominent along the grain boundaries, indicating the importance of grain boundary character to HIC.     

食用百合高效生态栽培技术

文章从食用百合的经济意义入手,分析了现阶段百合生产存在的问题,总结了食用百合高效生态栽培技术,期望为食用百合的栽培提供理论基础与实践经验。     

Bootstrap procedures for detecting multiple persistence shifts in heteroskedastic time series

This article proposes new bootstrap procedures for detecting multiple persistence shifts in a time series driven by non-stationary volatility. The assumed volatility process can accommodate discrete breaks, smooth transition variation as well as trending volatility. We develop wild bootstrap sup-Wald tests of the null hypothesis that the process is either stationary [I(0)] or has a unit root [I(1)] throughout the sample. We also propose a sequential procedure to estimate the number of persistence breaks based on ordering the regime-specific bootstrap p-values. The asymptotic validity of the advocated procedures is established both under the null of stability and a variety of persistence change alternatives. A comparison with existing tests that assume homoskedasticity illustrates the finite sample improvements offered by our methods. An application to OECD inflation rates highlights the empirical relevance of the proposed approach and weakens the case for persistence change relative to existing procedures.     

Effects of graphite nano-flakes on thermal and microstructural properties of TiB2–SiC composites

In the last decades, the production of ultra-high temperature composites with improved thermo-mechanical properties has attracted much attention. This study focuses on the effect of graphite nano-flakes addition on the microstructure, densification, and thermal characteristics of TiB₂–25 vol% SiC composite. The samples were manufactured through spark plasma sintering process under the sintering conditions of 1800 °C/7 min/40 MPa. Scanning electron microscopy images demonstrated a homogenous dispersion of graphite flakes within the TiB₂–SiC composite causing a betterment in the densification process. The thermal diffusivity of the specimens was gained via the laser flash technique. The addition of graphite nano-flakes as a dopant in TiB₂–SiC did not change the thermal diffusivity. Consequently, the remarkable thermal conductivity of TiB₂–SiC remained intact. It seems that the finer grains and more interfaces obstruct the heat flow in TiB₂–SiC–graphite composites. Adding a small amount of graphite nano-flakes enhances the densification of the mentioned composite by preventing the grain growth.