高压气淬设备与工艺

简要介绍了气体淬火介质及ECM气体淬火设备的特性,同时介绍了ECM气体分级淬火工艺的原理,并结合实际生产案例,论述了分级气淬工艺较普通气淬工艺的优越性。     

Modified La0.6Sr0.4Co0.2Fe0.8O3-δ cathodes with the infiltration of Er0.4Bi1.6O3 for intermediate-temperature solid oxide fuel cells

Aiming to lower the activation energy and expedite the oxygen reduction reaction (ORR) process of La_0.6Sr_0.4Co_0.2Fe_0.8O_3-δ (LSCF) cathodes for application in intermediate-temperature solid oxide fuel cells (IT-SOFCs), Er_0.4Bi_1.6O₃ (ESB) modified LSCF was prepared by infiltrating using organic solvents. The infiltration of ESB dramatically reduces the polarization resistances of LSCF cathodes (from 0.27 to 0.11 Ω cm² at 700 °C, from 0.58 to 0.25 Ω cm² at 650 °C), and lowers their activation energy (from 100.28 to 97.15 kJ mol^?1). Also, ESB makes the rate-limiting step of LSCF cathodes at high frequency change from the charge transfer process on the cathode to the adsorption and diffusion of oxygen on cathode surface. The single cell with ESB infiltrated LSCF cathodes shows a peak power density of 469 mW cm^?2 at 700 °C using humid hydrogen and air as fuels and oxidants, respectively, as well as a good short-term stability for 50 h.     

Exploring the biomechanics of walking and crowd “flow”

Crowd movement simulation models are generally based on aggregated speed and flow data collected more than 50 years ago. There appears to be no validated modelling capability to include the impact of recent and future changes in population demographics, resulting from an ageing population and increasing obesity rates. New analytical approaches and data gathering are required to successfully model crowd movement and safety for current and future generations. This study carried out (a) a review of the primary components of crowd movement, demographics and analytical techniques, (b) prototype experiments to investigate age-related aspects of space and potential points of contact and (c) a new predictive model for crowd flow analysis based on pedestrian biomechanics and anthropometric data. The model uses the physical space taken up by the biomechanical walking process and the spatial buffer between points of potential contact with other pedestrians to predict the speed of movement at different levels of congestion. The new analytical model was used to predict single file speeds (for people with different demographics in congested space), which compared well with published experimental data. The next steps for model development for wider “flows” and additional experiments to provide data sets for wider demographics are also proposed.     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.     

细化变质处理对铸造A356铝合金组织性能及共晶硅生长机制的影响

研究了采用新型Al-5Ti-1B-1RE中间合金和Al-10Sr中间合金对A356铝合金进行单一或复合细化变质处理后的组织、力学性能和共晶硅生长机制的影响。结果表明：单一细化变质处理中Al-5Ti-1B-1RE中间合金对A356铝合金中α-Al相有明显的细化作用,合金的强度和维氏硬度显著提高；Al-10Sr 中间合金对共晶硅有强的变质作用,合金的伸长率明显提高；而经复合细化变质处理后α-Al相形状和尺寸变得更均匀细小,晶界更清晰,共晶硅相几乎都转变成更弥散、更细小的纤维状,片层状共晶硅也几乎完全消失,共晶硅长度由铸态40-60 μm降低到1-2 μm之间,达到完全变质效果,其力学性能显著高于铸态、单一细化变质剂处理的A356铝合金。未细化变质的A356铝合金中的共晶Si的生长方式为典型的小平面台阶生长,复合细化变质处理的共晶硅以孪晶凹槽机制生长为主,小平面生长特征逐渐减弱直至消失。     

Effect of Cu element on morphology of TiB2 particles in TiB2/Al−Cu composites

In order to explore the influence of Cu element on the morphology evolution of the in-situ TiB₂ particles, the 10 wt.% TiB₂ reinforced Al−5wt.%Cu based composite was prepared by mixed salt casting. The morphology characterization and transformation of TiB₂ reinforcements caused by Cu element were investigated by multi-scale microstructure characterization and statistics techniques. In the case of controlled casting, 5 wt.% Cu addition was found to transform the TiB₂ particle morphology from hexagonal plate with sharp edges and corners to hexagonal or tetragonal prism with chamfered edges and corners with the distinguishing growth steps both on the top surface and the side surface. The TiB₂ growth in Al−Cu matrix followed the rules: nano-scaled spherical nuclei—polyhedron grains—chamfered hexagonal particles—hexagonal plates—chamfered particles with obvious growth steps. The adsorption energy of Cu on different crystal surfaces of TiB₂ was caculated to reveal the influence mechanism and the results indicated that Cu was preferentially adsorbed on the (101(—)1)_TiB2 crystal planes, devoting to the small aspect ratio of TiB₂.     

Observer‐based fuzzy adaptive quantized control for uncertain nonlinear multiagent systems

This paper focuses on consensus quantized control design problem for uncertain nonlinear multiagent systems with unmeasured states. Every follower can be denoted through a system with unmeasurable states, hysteretic quantized input, and unknown nonlinearities. Fuzzy state observer and Fuzzy logic systems are employed to estimate unmeasured states and approximate unknown nonlinear functions, respectively. The hysteretic quantized input can be split into two bounded nonlinear functions to avoid chattering problem. By combining adaptive backstepping and first‐order filter signals, an observer‐based fuzzy adaptive quantized control scheme is designed for each follower. All signals exist in closed‐loop systems are semiglobally uniformly ultimately bounded, and all followers can accomplish a desired consensus results. Finally, a numerical example is employed to elaborate the effectiveness of proposed control strategy.     

A Real-Time Application of Modified Inductor Coupled KY Converter Topology in Speed Control of E-Bikes

Abstract

Congested road network and traffic jam lead to vehicle idling and fuel wastage. An E-bike which is a solution to this is often available with Thumb Throttle Mechanism and single speed operation. A motor controller with multiple output voltage levels and Click Throttle Mechanism is presented in this paper which provides variable speed operation, better power utilization and is highly economical. Proposed modified KY converter utilizes the turns ratio of an On-Line Tap Changer (OLTC) to generate multiple output voltages for variable speed commutation. This possess a stable continuous conduction mode throughout its operation and reduced switching transients when compared to the existing topologies. Mutually independent control variables namely turns ratio and duty ratio, are used here for voltage conversion, which facilitates the flexible transition between multiple output voltage levels. A 15?W prototype of the proposed modified inductor coupled KY converter is realized using Arduino Uno Board.     

Flow visualization and transient behavior analysis of luminescent mini-tufts after a backward-facing step

Luminescent mini-tufts method has been used for surface flow visualization for a long time. One major challenging point of this method is quantitative analysis of transient flows and the dynamic structures. This study is focused on the application of luminescent mini-tufts method in transient flows. A backward-facing step (BFS) is used in this analysis, which is one classic model that consists both flow separation and re-attachment processes. In this study, the instantaneous mini-tufts recognition, image averaging and tuft inclination angle/tuft angle estimation processes are introduced for the analysis of luminescent mini-tufts for the first time on backward-facing step flow (Re_m = 2.0 × 10⁵–7.9 × 10⁵ and Re_h = 1.3 × 10⁴–5.3 × 10⁴). Detailed transient features and characterization process for the backward-facing step model are explained in this study. The combination of optical-oil flow and hot-wire anemometry methods with luminescent mini-tufts are also shown useful to give comprehensive flow field information, including the surface flow behaviors, boundary layer, re-attachment position identification, etc. In addition, the decomposition of the luminescent mini-tufts visualization data is also conducted to give the power spectral density (PSD) and characteristic frequencies for the mini-tufts behaviors under transient fluctuating flow conditions.     

齿轮减速机啮合参数优化设计

提出用单目标函数进行初步的啮合参数优化,以此为基础再进行一次迭代优化计算。在计算中考虑全部啮合参数对齿轮传动的影响,采用复合形优化方法和智能判别系统可得到更加合理的啮合参数,并用实例论述了这种重复优化的与传统设计和单目标优化的效果对比。