Fluid‐structure coupling of linear elastic model with compressible flow models

Cavitation erosion is caused in solids exposed to strong pressure waves developing in an adjacent fluid field. The knowledge of the transient distribution of stresses in the solid is important to understand the cause of damaging by comparisons with breaking points of the material. The modeling of this problem requires the coupling of the models for the fluid and the solid. For this purpose, we use a strategy based on the solution of coupled Riemann problems that has been originally developed for the coupling of 2 fluids. This concept is exemplified for the coupling of a linear elastic structure with an ideal gas. The coupling procedure relies on the solution of a nonlinear equation. Existence and uniqueness of the solution is proven. The coupling conditions are validated by means of quasi‐1D problems for which an explicit solution can be determined. For a more realistic scenario, a 2D application is considered where in a compressible single fluid, a hot gas bubble at low pressure collapses in a cold gas at high pressure near an adjacent structure.     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

Landau-Zener模型中纠缠演化及转移的研究

研究了受外场驱动的两个二能级系统分别与两个单模量子化光场相互作用模型中纠缠演化及转移问题。该工作主要是对外场驱动的Landau-Zener模型进行了研究，采用旋转波近似的方法，通过数值计算详细分析了二能级系统初始状态、能级间的耦合常数以及驱动外场的参数对子系统间纠缠和转移特性的影响。结果表明，适当调节模型中的参数，可以使系统初始纠缠完全转移为光腔场间的纠缠，实现二能级系统与光场间的最大纠缠转移。     

Sustainability of ride-hailing services in China’s mobility market: A simulation model of socio-technical system transition

As a symbol of sharing economy, ride-hailing services have spread to Asia, where various forms of services have been established according to the existing socio-technical regimes, including legal, policy, and environmental concerns. China, in particular, has accepted ride-hailing services by revising existing institutions. This study analyzes China’s acceptance of ride-hailing services in the socio-technical system context set up for legacy services. Simulation modeling, combined with transition theory and an agent-based model, is used to analyze the data. This study calculates consumer disutility based on mobility market share, reflecting consumer preference, and predicts the sustainability of ride-hailing services. The simulation results conclude that legalization and socio-technical context are of importance for sustainable mobility.     

An analytical model for optimizing the performance of graphene based silicon Schottky barrier solar cells

In this paper, a model taking into account the effects of carrier loss mechanisms has been developed. The model simulates the photovoltaic properties of the graphene/n-type silicon Schottky barrier solar cells (G/n-Si_SBSC), and it can reproduce the experimentally determined parameters of the G/n-Si_SBSC. To overcome the low efficiencies of G/n-Si_SBSC, their performances have been optimized by modifying the work function of graphene and Si properties, accounted for variation of its thickness and doping level. The obtained results show that the work function of graphene has the major impact on the device performance. Also, the temperature dependence of the G/n-Si_SBSC performance is investigated.     

A survey of surface tension,molar volume and density for Sn–Ag–Cu–Bi–Sb quinary alloys as lead-free solders

ABSTRACT

By applying the geometric models and the theoretical equation, the surface tension, the molar volume and the density were studied. The empirical calculations were carried out in temperature range 623?K?≤?T?≤?1123?K. Only few thermophysical properties were estimated for eight quinary alloys: Sn3.55Ag0.5Cu3Bi3Sb, Sn3.48Ag0.5Cu3Bi5Sb, Sn3.48 Ag0.5Cu5Bi3Sb, Sn3.40 Ag0.5Cu5Bi5Sb, Sn3.53Ag1Cu3Bi3Sb, Sn3.46Ag1Cu3Bi5Sb, Sn3.46Ag1Cu5Bi3Sb, Sn3.38Ag1Cu5Bi5Sb. The results show that surface tension and density have a linear appearance for all temperatures. We have also studied the influence of the composition and temperature in the studied alloys. The obtained theoretical results are compared with the experimental ones and with the conventional Pb–Sn welds.     

基于电化学老化衰退模型的锂离子动力电池外特性

当前锂离子动力电池电化学模型存在模型复杂、建模难度大、计算效率低、老化评估效果差的问题,本文提出一种考虑电池衰退老化的机理模型(ADME).本文首先通过有限差分法对伪二维(P2D)电化学模型进行离散降阶处理,得到简化伪二维(SP2D)模型.在SP2D模型的基础上,基于阴阳两极发生的副反应导致的衰退老化现象,提出一种考虑电池衰退老化的机理模型.其次,使用多变量偏差补偿最小二乘法实现模型参数辨识.最后通过动力电池衰退老化性能循环实验,对比分析了恒流、脉冲工况下SP2D模型和ADME模型的终端电压输出.结果表明:ADME模型较为简单、计算效率和估算精度高,可以有效评估电池容量老化衰退,得到理想的锂离子动力电池外特性曲线.     

基于Kronecker型替换的黑盒多项式稀疏插值

本文基于新的Kronecker型替换,给出两个由黑盒表示的稀疏多项式的新确定性插值算法.令f∈R[x1,……,xn]是一个稀疏黑盒多项式,其次数上界为D.当R是C或者是有限域时,相对于已有算法,新算法具有更好的计算复杂度或者关于D的复杂度更低.特别地,对于一般黑盒模型,D是复杂度中的主要因素,而在所有的确定性算法中,本文的第二个算法的复杂度关于D是最低的.     

A Biosilification Fusion Protein for a ‘Self‐immobilising’ Sarcosine Oxidase Amperometric Enzyme Biosensor

Monomeric sarcosine oxidase (mSOx) fusion with the silaffin peptide, R5, designed previously for easy protein production in low resource areas, was used in a biosilification process to form an enzyme layer electrode biosensor. mSOx is a low activity enzyme (10–20 U/mg) requiring high amounts of enzyme to obtain an amperometric biosensor signal, in the clinically useful range <1 mM sarcosine, especially since the K_m is >10 mM. An amperometric biosensor model was fitted to experimental data to investigate dynamic range. mSOx constructs were designed with 6H (6×histidine) and R5 (silaffin) peptide tags and compared with native mSOx. Glutaraldehyde (GA) cross‐linked proteins retained ～5 % activity for mSOx and mSOx‐6H and only 0.5 % for mSOx‐R5. In contrast R5 catalysed biosilification on (3‐mercaptopropyl) trimethoxysilane (MPTMS) and tetramethyl orthosilicate (TMOS) particles created a ‘self‐immobilisation’ matrix retaining 40 % and 76 % activity respectively. The TMOS matrix produced a thick layer (>500 μm) on a glassy carbon electrode with a mediated current due to sarcosine in the clinical range for sarcosinemia (0–1 mM). The mSOx‐R5 fusion protein was also used to catalyse biosilification in the presence of creatinase and creatininase, entrapping all three enzymes. A mediated GC enzyme linked current was obtained with dynamic range available for creatinine determination of 0.1–2 mM for an enzyme layer ～800 nm.     

The Szegö kernel on a class of non-compact CR manifolds of high codimension

We generalize Nagel’s formula for the Szegö kernel and use it to compute the Szegö kernel on a class of non-compact CR manifolds whose tangent space decomposes into one complex direction and several totally real directions. We also discuss the control metric on these manifolds and relate it to the size of the Szegö kernel.