Depicting the role of gas-solid interactions on the hydrodynamics of converging pneumatic riser

The understanding of the flow characteristics and effect of gas-solid interactions in pneumatic risers is fundamental to investigate to ensure effective design cost-effective operation. Thus, to understand the effect of gas-solid interactions on the hydrodynamics of newly proposed conversing risers, this study mainly focused on predicting pressure drop in the dilute phase pneumatic conveying system. The experiments were conducted in a converging riser having a convergence angle of 0.2693°. Various solid particles such as sago, black mustard, and alumina have been considered to study the effect of particle sizes and density on the pressure drop. The experimental outcomes indicate that the total pressure drop increases with an increase in the solid density and gas mass flow rate. Moreover, smaller particle sizes are also increased the pressure drop. An empirical correlation is developed for the prediction of total pressure drop ΔP_T in converging pneumatic riser via dimensional analysis. All dependent variables such as particle and air density, drag force, acceleration due to gravity, the mass flow rate of air and particle, the diameter of particle and converging riser, the height of converging riser were considered to develop the empirical correlation. The established relationship is tested, and experimental data have been fitted for its validation. The estimated relative error of less than 0.05 proved the significance of the developed correlation. Hence, it can be stated that the established relationship is useful in studying the effects of various parameters on the pressure drop across the length of the conversing riser.     

Pulsed laser reshaping and fragmentation of upconversion nanoparticles-from hexagonal prisms to ID nanorods through“Medusa”-like structures

One dimensional(1D)nanostructures attract considerable attention,enabling a broad application owing to their unique properties.However,the precise mechanism of 1D morphology attainment remains a matter of debate.In this study,ultrafast picosecond(ps)laser-induced treatment on upconversion nanoparticles(UCNPs)is offered as a tool for 1 D-nanostructures formation.Fragmentation,reshaping through recrystallization process and bioadaptation of initially hydrophobic(β-Na_1.5Y_{1.5_}F₆:Yb³⁺,Tm³⁺/β-Na_1.5Y_{1.5_}F₆)core/shell nanoparticles by means of one-step laser treatment in water are demonstrated.“True”1D nanostructures through"Medusa^-like structures can be obtained,maintaining anti-Stokes luminescence functionalities.A matter of the one-dimensional UCNPs based on direction of energy migration processes is debated.The proposed laser treatment approach is suitable for fast UCNP surface modification and nano-to-nano transformation,that open unique opportunities to expand UCNP applications in industry and biomedicine.     

The dorsolateral pre‑frontal cortex bi‑polar error‑related potential in a locked‑in patient implanted with a daily use brain–computer interface

While brain computer interfaces (BCIs) offer the potential of allowing those suffering from loss of muscle control to once again fully engage with their environment by bypassing the affected motor system and decoding user intentions directly from brain activity, they are prone to errors. One possible avenue for BCI performance improvement is to detect when the BCI user perceives the BCI to have made an unintended action and thus take corrective actions. Error-related potentials (ErrPs) are neural correlates of error awareness and as such can provide an indication of when a BCI system is not performing according to the user’s intentions. Here, we investigate the brain signals of an implanted BCI user suffering from locked-in syndrome (LIS) due to late-stage ALS that prevents her from being able to speak or move but not from using her BCI at home on a daily basis to communicate, for the presence of error-related signals. We first establish the presence of an ErrP originating from the dorsolateral pre-frontal cortex (dLPFC) in response to errors made during a discrete feedback task that mimics the click-based spelling software she uses to communicate. Then, we show that this ErrP can also be elicited by cursor movement errors in a continuous BCI cursor control task. This work represents a first step toward detecting ErrPs during the daily home use of a communications BCI.     

空间变形记 葡萄牙Morinha仓库改造

该项目原本是一间位于葡萄牙阿马兰蒂的废弃仓库。仓库主人邀请本土设计公司stu.dere对这一老旧空间进行翻新改造,使其从废弃状态脱变成一个通透明亮的崭新空间。仓库内部原先的陈设极其随意,业主希望能够采用开放式布局,且同时具备探索的趣味氛围,使人仿若置身儿童迷宫。设计师将这2点诉求综合考量之后,决定选择以金色的金属网来隔离空间,在形成物理屏障的同时,也保持视觉的通透,一举两得。     

移动机器人助力生活用纸行业技术领先生产商

如今,成功的生产有赖于良好的管理和安全的工作场所。移动机器人可帮助企业实现这些目标,也是主动规划工厂原料和安排运输的一个关键技术部件。移动机器人的革新已经渗透到经销和物流环节,并将最终直接影响每个人,包括到消费者家门口的最后一英里交付。在当今这个产品上市速度和动态生产流程至为关键的世界。     

防护用非织造土工布——针刺技术领域新方法

正采用天然材料稳定和硬化土木工程材料的原理可追溯至公元前3 000年。据记载,织物和芦荟在古巴比伦就被用作土木工程材料。历经数千年,其基本原理未变,但方法和材料都发生了很大的变化。尽管在20世纪,木头、石头、混凝土甚至棉花等仍被用于公路建设,但更多的是使用合成聚合物(较常见的为塑料)。非织造布(包括热黏合纺黏垫)于20世纪     

Physics-informed deep learning for one-dimensional consolidation

Neural networks with physical governing equations as constraints have recently created a new trend in machine learning research.In this context,a review of related research is first presented and discussed.The potential offered by such physics-informed deep learning models for computations in geomechanics is demonstrated by application to one-dimensional(1D)consolidation.The governing equation for 1D problems is applied as a constraint in the deep learning model.The deep learning model relies on automatic differentiation for applying the governing equation as a constraint,based on the mathematical approximations established by the neural network.The total loss is measured as a combination of the training loss(based on analytical and model predicted solutions)and the constraint loss(a requirement to satisfy the governing equation).Two classes of problems are considered:forward and inverse problems.The forward problems demonstrate the performance of a physically constrained neural network model in predicting solutions for 1D consolidation problems.Inverse problems show prediction of the coefficient of consolidation.Terzaghi’s problem,with varying boundary conditions,is used as a numerical example and the deep learning model shows a remarkable performance in both the forward and inverse problems.While the application demonstrated here is a simple 1D consolidation problem,such a deep learning model integrated with a physical law has significant implications for use in,such as,faster realtime numerical prediction for digital twins,numerical model reproducibility and constitutive model parameter optimization.     

F-TR锁座静态载荷反演试验应用研究

F-TR锁座是铁路货车运输中重要的部件,对其进行载荷反求研究对于提高车辆性能具有重要意义。工程设计中,采用定额载荷来评价产品强度及刚度等参数是否满足设计标准,在设计过程中需要对试件进行载荷评价。文中提出一种新的载荷反求算法,其能够得到最佳应变片的位置,并对测量得到的应变数据进行处理,推导求得其实际所受载荷大小,对常见的X70货车F-TR锁座进行了静态载荷反求应用研究。研究结果显示:该试验仿真方法所提供的最佳布片位置,能够为实际试验提供较好的布片点,但是对布片点的位置及角度有一定要求,其结果是值得参考的,这些成果为后期载荷反求的深入研究提供了有意义的参考。     

Revealing the relationships between alloy structure,composition and plastic deformation in a ternary alloy system by a combinatorial approach

A high-throughput approach based on magnetron co-sputtering of alloy libraries is employed to inves-tigate mechanical properties of crystalline and amorphous alloys in a ternary palladium(Pd)-tungsten(W)-silicon(Si)system with the aim to reveal the difference in plastic deformation response and extract the relevant structure-property relationships of the alloys in the system.It was found that in contrast to crystalline alloys,the amorphous ones,i.e.,metallic glasses,exhibited a much smaller fluctuation range in the plasticity parameters(Er2/H and Wp/Wt),indicating a significant difference in the plastic deformation mechanism controlling the mechanical properties for the respective alloys.We propose that the inho-mogeneous deformation of amorphous alloys localized in thin shear bands is responsible for the weaker compositional dependence of both plasticity parameters,while dislocation gliding in crystalline materials is significantly more dependent on the exact structure,thus resulting in a larger scattering range.Based on the representative efficient cluster packing model,a set of composition-dependent atomic structural models is proposed to figure out the structure-property relationships of amorphous alloys in Pd-W-Si alloy system.     

Three-dimensional visualization and quantification of microporosity in aluminum castings by X-ray micro-computed tomography

Porosity is a major issue in solidification processing of metallic materials.In this work,wedge die casting experiments were designed to investigate the effect of cooling rate on microporosity in an aluminum alloy A356.Microstructure information including dendrites and porosity were measured and observed by optical microscopy and X-ray micro-computed tomography(XMCT).The effects of cooling rate on secondary dendrite arm spacing(SDAS)and porosity were discussed.The relationship between SDAS and cooling rate was established and validated using a mathematical model.Three-dimensional(3-D)porosity information,including porosity percentage,pore volume,and pore number,was determined by XMCT.With the cooling rate decreasing from a lower to a higher position of the wedge die,the observed pore number decreases,the porosity percentage increases,and the equivalent pore radius increases.Sphericity of the pores was discussed as an empirical criterion to distinguish the types of porosity.For different cooling rates,the larger the equivalent pore radius is,the lower the sphericity of the pores.This research suggests that XMCT is a useful tool to provide critical 3-D porosity information for integrated computational materials engineering(ICME)design and process optimization of solidification products.