Nonsimilar solution of a boundary layer flow of a Reiner–Philippoff fluid with nonlinear thermal convection

The thermodynamics modeling of a Reiner–Philippoff-type fluid is essential because it is a complex fluid with three distinct probable modifications. This fluid model can be modified to describe a shear-thinning, Newtonian, or shear-thickening fluid under varied viscoelastic conditions. This study constructs a mathematical model that describes a boundary layer flow of a Reiner–Philippoff fluid with nonlinear radiative heat flux and temperature- and concentration-induced buoyancy force. The dynamical model follows the usual conservation laws and is reduced through a nonsimilar group of transformations. The resulting equations are solved using a spectral-based local linearization method, and the accuracy of the numerical results is validated through the grid dependence and convergence tests. Detailed analyses of the effects of specific thermophysical parameters are presented through tables and graphs. The study reveals, among other results, that the buoyancy force, solute and thermal expansion coefficients, and thermal radiation increase the overall wall drag, heat, and mass fluxes. Furthermore, the study shows that amplifying the space and temperature-dependent heat source parameters allows fluid particles to lose their cohesive force and, consequently, maximize flow and heat transfer.     

Numerical simulation of the influence of confined multi-point ignited H2–O2 mixture on the propagation of shock waves towards a deformable plate

The study of shock wave propagation in a detonation chamber is of great importance as a part of the plate forming process. Investigations related to the effects of premixed gas detonation on the deflection of a plate require in-depth examination. An Eulerian-Lagrangian numerical simulation is conducted using the space-time conservation element and solution element method of LS-DYNA software to study the effect of confined multi-point ignited gaseous mixture on the dynamic response of thin plates clamped at the end of a combustion chamber. The FSI couples a Lagrangian finite element solver with a Eulerian fluid solver in a 2D space with detailed chemistry of H₂–O₂ mixture. The solution contains the detonation wave propagation through the combustion chamber and its interaction with the plate. The influence of variation in the multi-point ignition locations and combustion chamber dimensions on the pressure history and plate deflection is studied. To verify the model, a comparison with the experimental study is carried out using an adjustable model representative of the real experiment. The verified model is used to link the evolution of plate shape with the arrival time and intensity of shock waves within the chamber. It is found that a longer distance between the ignition point and the plate intensifies the ultimate deflection of the plate. In addition, a fairly large combustion area employed in a direction rather than transverse to the plate surface is unable to influence the ultimate deformation of the plate.     

Meticulously tailoring phase boundary in KNN-based ceramics to enhance piezoelectricity and temperature stability

Although KNN-based ceramics with high electrical properties are obtained through a variety of strategies, the temperature sensitivity is still one of the key technical bottlenecks hindering practical applications. Here, we use a new strategy, meticulously tailoring phase boundary, to refine the ferroelectric boundary of KNN-based ceramics, leading to high piezoelectricity companied with improving temperature stability. The highest d₃₃ value in this system reaches 501 pC/N with a T_C ∼ 240°C, whereas a large strain of ∼0.134% can be kept with 10% lower deterioration until 100°C. The origin of high piezoelectricity is mainly attributed to the well-preserved multiphase coexistence and the appearance of nanodomains, which greatly facilitate the polarization rotation. Instead of the changed intrinsic thermal insensitivity, the precision phase boundary engineering plays an important role in strengthening the temperature stability of electric-induced strain. This work provides a simple and effective method to obtain both high electrical properties and excellent thermal stability in KNN-based ceramics, which is expected to promote the practical applications in the future.     

Data envelopment analysis based on team reasoning

Existing approaches to data envelopment analysis focus mainly on the derivation of the efficiency of the individual decision‐making unit (DMU) or on the calculation of the weights of multiple inputs or outputs, but pay little attention to the team interest of all the DMUs. Motivated by the idea of team reasoning, in which the benefit of the team is of higher importance than that of each individual, this paper considers all the DMUs as a team and introduces the team indexes including the overall efficiencies, variance, boundaries of all the DMUs, and relationships between DMUs. Several models are first developed to estimate values of the team indexes based on which decision makers can provide their preferences regarding them. Then, models are established to obtain the interval efficiencies of individual DMUs under the condition that the team indexes are satisfied. Several examples are given to illustrate the proposed approaches and verify their applicability.     

Optimal design of Raman fibre amplifier based on terminal value optimization strategy and shuffled frog leaping algorithm

This paper introduces an evolutionary algorithm, Shuffled Frog Leaping Algorithm (SFLA), to solve the optimization problem in designing the multi-pumped Raman Fibre Amplifier (RFA). SFLA is a powerful optimizer tool because of its efficient mathematical expressions and global search capability. We utilize SFLA to determine the optimal pump wavelengths and pump powers by minimizing the gain ripple of RFA. To accelerate calculations, a terminal value optimization strategy (TVOS) is incorporated into the evolution of SFLA. This proposed strategy takes the terminal power values of pumps as the decision variables in optimization. Then, the optimal original power values of the pumps are obtained by solving the Power Coupled Equations once, without using the traditional method of repetitive guesses.The combination of SFLA and TVOS enhances the efficiency of optimization and accelerates calculation, while satisfying the design requirements of RFA.The simulation results show that nearly 65% of computational time has been saved compared with the traditional average power analysis. The 4-pumped C+L band of backward multi-pumped RFA with the average net gain of 0 dB, 1 dB and 2 dB are designed individually, where the gain ripple is less than 0.64 dB. The combination of SFLA and TVOS enhance the optimization efficiency and improve the performance of RFA with good gain profile.     

Indoor boundary layer chemistry modeling

Ozone (O₃) chemistry is thought to dominate the oxidation of indoor surfaces. We consider the hypothesis that reactions taking place within indoor boundary layers result in greater than anticipated hydroxyl radical (OH) deposition rates. We develop models that account for boundary layer mass‐transfer phenomena, O₃‐terpene chemistry and OH formation, removal, and deposition; we solve these analytically and by applying numerical methods. For an O₃‐limonene system, we find that OH flux to a surface with an O₃ reaction probability of 10^?8 is 4.3 × 10^?5 molec/(cm² s) which is about 10 times greater than predicted by a traditional boundary layer theory. At very low air exchange rates the OH surface flux can be as much as 10% of that for O₃. This effect becomes less pronounced for more O₃‐reactive surfaces. Turbulence intensity does not strongly influence the OH concentration gradient except for surfaces with an O₃ reaction probability >10^?4. Although the O₃ flux dominates OH flux under most conditions, OH flux can be responsible for as much as 10% of total oxidant uptake to otherwise low‐reactivity surfaces. Further, OH chemistry differs from that for ozone; therefore, its deposition is important in understanding the chemical evolution of some indoor surfaces and surface films.     

Enhancing the Tribological Behavior of Lubricating Oil by Adding TiO2, Graphene,and TiO2/Graphene Nanoparticles

This article investigates the tribological behavior of nanoparticles (NPs) of titanium dioxide anatase TiO₂ (A), graphene, and TiO₂ (A) + graphene added to the pure base oil group ΙΙ (PBO-GΙΙ). The morphology of these two nanostructures of TiO₂ (A) and graphene was characterized by transmission electron microscopy (TEM). Oleic acid (OA) was blended as a surfactant into the formulation to help stabilize the NPs in the lubricant oil. A four-ball test rig was used to determine the tribological performance of six different samples, and an image acquisition system was used to examine and measure the wear scar diameter of the stationary balls. Field emission–scanning electron microscopy (FE-SEM) was used to examine the wear morphology. Energy-dispersive X-ray spectroscopy (EDX), element mapping, and Raman spectroscopy were employed to confirm the presence of (TiO₂ (A) + graphene) and the formation of a tribolayer/film on the mating surfaces. Moreover, a 3D optical surface texture analyzer was utilized to investigate the scar topography and tribological performance. The experiments proved that adding (0.4?wt% TiO₂ (A) + 0.2?wt% graphene) to the PBO-GΙΙ optimized its tribological behavior. These excellent results can be attributed to the dual additive effect and the formation of a tribofilm of NPs during sliding motion. Furthermore, the average reductions in the coefficient of friction (COF), wear scar diameter (WSD), and specific wear rate (SWR) were 38.83, 36.78, and 15.78%, respectively, for (0.4?wt% TiO₂ (A) + 0.2?wt% graphene) nanolubricant compared to plain PBO-GΙΙ lubricant.     

Methods for constructing analytic phase function for small spherical particle polydispersions

Two ways of constructing analytic phase function for a polydispersion of small spherical non-absorbing particles have been investigated. First one is a straightforward procedure emanating from the implementation of single particle scattering input into the defined polydisperse phase function. This results in an analytic phase function in terms of moments of the distribution. The second approach is a new strategy, based on the Lagrange mean value theorem. A clear understanding of the relationship between these two approaches has been developed. The efficacy and accuracy of the scattering phase functions is illustrated by applying it to a power-law size distributed sphere ensemble.     

Maximization of quadruple phase boundary for alkaline membrane fuel cell using non-stoichiometric α-MnO2 as cathode catalyst

Oxygen can only be reduced at the quadruple phase boundary (catalyst, carbon support, ionomer and oxygen) of the cathode catalyst layer with non-conducting electrocatalyst. To maximize the quadruple phase boundary sites is crucial to increase the peak power density of each membrane electrode assembly. The quadruple phase boundary is depending on the ratio of catalyst, carbon support and ionomer. The loading of catalyst layer is also crucial to the fuel cell performance. In this study, non-stoichiometric α-MnO₂ manganese dioxide nanorod material has been synthesized and the ratios of carbon, ionomer and catalyst loadings were optimized in alkaline membrane fuel cell. In total, ten membrane electrode assemblies have been manufactured and tested. Taguchi design method has been applied in order to understand the effect of each parameter. The conclusion finds out the ionomer has more influence on the alkaline membrane fuel cell peak power performance than carbon and loading.     

DCNN深度特征与交替方向乘子的相关滤波跟踪

针对采用相关滤波的判别式目标跟踪遇到的瓶颈问题：由于目标快速移动引起边界效应，使得相关滤波器在学习与更新过程中可能会引入错误，最终错误的累积将导致跟踪失败。在采集深度学习特征与样本相似性度量的基础上，提出一种引入交替方向乘子方法的改进相关滤波目标跟踪算法，选择DCNN深度特征有效地表征待跟踪目标的初始状态，通过在线分类过程中样本相似性比对与半监督学习，辅助解决相关滤波器在学习过程中存在的自学习问题。所提目标跟踪算法特别适合训练样本为持续获得的、同时存储空间较小的机器学习过程，提高目标在快速运动与部分遮挡等复杂情况下的跟踪成功率，针对VOT2016标准测试视频的实验表明：当目标面临快速运动时，对比CN、SAMF、STC算法，所提DA-CFT跟踪算法将跟踪成功率分别由60.4%～73.4%、67.2%～82.9%、80.9%～88.1%提升至85.6%～91.0%。