Can hydrogen be the sustainable fuel for mobility in India in the global context?

This article provides a critical assessment of H₂ from the standpoint of more widespread use as a sustainable fuel for Indian mobility applications in the global context. The potential techno-economic advantages of utilizing H₂ for automobiles rather than battery electric vehicles or conventional internal combustion engine vehicles are emphasized. The present assessment demonstrates that H₂ production, storage, and distribution costs are the primary challenges, and a significant improvement is still necessary for H₂ to compete either against the internal combustion engine vehicle or the battery electric vehicle to win the race, arguably. The secondary challenges have also been demonstrated, which include the cost of the fuel cell stack and the modifications associated with internal combustion engine vehicles, as well as regulatory and safety concerns, which impede the widespread usage of H₂. It is critical that policy-making for sustainable mobility in India is possible with the aid of a National H₂ Energy Road-Map. This in turn can achieve a cost target of $0.5/kg for H₂.     

Magnetic recyclable ZnO/SrFe12O19 photocatalyst for effective photodegradation of rhodamine B under simulated sunlight

This work develops a novel magnetic photocatalysts ZnO/SrFe₁₂O₁₉ (ZS) synthesized with hydrothermal process. The introduction of SrFe₁₂O₁₉ not only enhances the photocatalytic behavior of ZnO towards Rhodamine B (RhB) decomposition, but also reinforces the recycling stability. Especially, ZS-5 composite exhibits the optimal photocatalytic performance, and the RhB decomposition reaches 99.5% after being exposed to simulative sunlight for 70 min, which is obviously superior to that of bare ZnO. Furthermore, the ZS-5 can be recovered from RhB solution by an extra magnet space and reused. After five recycles, the RhB removal efficiency can still be maintained over 90%. Such prominent photocatalytic property and stability of ZS-5 are associated with the greatly improved detachment efficiency of photoexcited carriers in a magnetic field. This study could provide a new-type recyclable photocatalyst that can effectively purify dye wastewater for convenient recovery.     

Enhanced gaseous hydrogen solubility in ferritic and martensitic steels at low temperatures

Metals that are exposed to high pressure hydrogen gas may undergo detrimental failure by embrittlement. Understanding the mechanisms and driving forces of hydrogen absorption on the surface of metals is crucial for avoiding hydrogen embrittlement. In this study, the effect of stress-enhanced gaseous hydrogen uptake in bulk metals is investigated in detail. For that purpose, a generalized form of Sievert's law is derived from thermodynamic potentials considering the effect of microstructural trapping sites and multiaxial stresses. This new equation is parametrized and verified using experimental data for carbon steels, which were charged under gaseous hydrogen atmosphere at pressures up to 1000 bar. The role of microstructural trapping sites on the parameter identification is critically discussed. Finally, the parametrized equation is applied to calculate the stress-enhanced hydrogen solubility of thin-walled pipelines and thick-walled pressure vessels during service.     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

PID Control of Planar Nonlinear Uncertain Systems in the Presence of Actuator Saturation

This paper investigates PID control design for a class of planar nonlinear uncertain systems in the presence of actuator saturation. Based on the bounds on the growth rates of the nonlinear uncertain function in the system model, the system is placed in a linear differential inclusion. Each vertex system of the linear differential inclusion is a linear system subject to actuator saturation. By placing the saturated PID control into a convex hull formed by the PID controller and an auxiliary linear feedback law, we establish conditions under which an ellipsoid is contractively invariant and hence is an estimate of the domain of attraction of the equilibrium point of the closed-loop system. The equilibrium point corresponds to the desired set point for the system output. Thus, the location of the equilibrium point and the size of the domain of attraction determine, respectively, the set point that the output can achieve and the range of initial conditions from which this set point can be reached. Based on these conditions, the feasible set points can be determined and the design of the PID control law that stabilizes the nonlinear uncertain system at a feasible set point with a large domain of attraction can then be formulated and solved as a constrained optimization problem with constraints in the form of linear matrix inequalities (LMIs). Application of the proposed design to a magnetic suspension system illustrates the design process and the performance of the resulting PID control law.      

Tabular data: Deep learning is not all you need

A key element in solving real-life data science problems is selecting the types of models to use. Tree ensemble models (such as XGBoost) are usually recommended for classification and regression problems with tabular data. However, several deep learning models for tabular data have recently been proposed, claiming to outperform XGBoost for some use cases. This paper explores whether these deep models should be a recommended option for tabular data by rigorously comparing the new deep models to XGBoost on various datasets. In addition to systematically comparing their performance, we consider the tuning and computation they require. Our study shows that XGBoost outperforms these deep models across the datasets, including the datasets used in the papers that proposed the deep models. We also demonstrate that XGBoost requires much less tuning. On the positive side, we show that an ensemble of deep models and XGBoost performs better on these datasets than XGBoost alone.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

基于特征建模的TDD系统大气波导干扰控制体系研究

大气波导干扰是特定气象条件下发生的时分双工（time-division duplex，TDD）系统内干扰，是TDD移动通信系统大规模组网面临的顽疾。在总结分析大气波导干扰成因和分类等的基础上，对大气波导干扰进行建模和表征，验证了海量干扰源在时域和频域的功率集总特征，并结合大量4G/5G现网实测数据给出了典型条件下内陆波导和海面波导的量化干扰信号传播模型，对于干扰的预测和预防具有重要意义。基于干扰特征，给出了TDD系统预防大气波导干扰的帧结构与组网的4项设计原则，5G现网数据表明干扰控制方案有效，上行干扰下降10 dB以上，相关原则对于6G系统的设计也具有指导意义。     

Synthesis and performance evaluation of a new drag reducer based on acrylamide/12-allyloxydodecyl acid sodium

Hydraulic fracturing with slickwater is a field-proven stimulation technology used in tight reservoirs. Because of the high pumping rate associated with slickwater fracturing, drag reduction (DR) is critical in minimizing pressure drop and the success of oilfield operations. In this paper, a new type of drag reducer (SPR) was synthesized with acrylamide and 12-allyloxydodecyl acid sodium, and its drag reduction performance was evaluated. The results showed that the new drag reducer features low molecular weight, fast-dissolving rate and low interfacial tension. The algorithm of estimating the drag reduction rate of non-Newtonian fluid SPR was proposed and validated. Empirical or semianalytical models for estimating the friction ratio (σ) or friction factor (λ or f) were used to simulate the turbulence behavior of the SPR drag reducer under different Reynolds numbers (Re). The modified Virk's correlation could accurately model the turbulent behavior of the SPR drag reducer. A unified calculation formula was established in this study for different pipe diameters.