Effect of PyC interface phase on the cyclic ablation resistance and flexural properties of two-dimensional Cf/HfC composites

Composites based on hafnium carbide and reinforced with continuous naked carbon fiber with and without PyC interface were prepared at low temperature by precursor infiltration and pyrolysis and chemical vapor deposition method. The microstructure, mechanical property, cyclic ablation and fiber bundle push-in tests of the composites were investigated. The results show that after three times ablation cycles, the bending strength of samples without PyC interface decreased by 63.6 %; the bending strength of samples with PyC interface only decreased by 37.8 %. The force displacement curve of the samples with PyC interface presented a well pseudoplastic deformation state. The mechanical behavior difference of two kinds of composites was due to crucial function of PyC interface phase including protection of fiber and weakening of fiber/matrix interface.     

Ultrasonic tomographic velocimeter for visualization of axial flow fields in pipes

An ultrasonic tomographic velocimeter to provide quantitative images of axial flow fields in pipes is developed and presented in this work. To detect the flow in various directions and positions, a novel transducer configuration strategy is proposed. All-in-one transducers are mounted in two sectional planes of the pipe. In each plane, N transducers are equally spaced along the circumference. Overlapped propagation paths are introduced by the configuration strategy, and the influence of the vortex flow can be eliminated theoretically by averaging the line velocities of the overlapped paths. To achieve a fast detection speed, the projection data is collected via an electrical scan in a fan-beam mode. After rearrangement and interpolation of the projection data, the parallel beam filtered back projection (FBP) algorithm is implemented to reconstruct the axial flow field. Numerical simulations with the theoretical velocity profiles were performed. The compensation method for the vortex flow is proved to be effective and necessary, and the number of transducers required for reconstruction of common flow profiles was estimated. Accordingly, an ultrasonic tomographic velocimeter consisting of 2×12 transducers was fabricated. Experiments were conducted in the straight pipe and downstream of a single bend pipe and compared with the computational fluid dynamics (CFD) simulation results. As demonstrated, the ultrasonic tomographic velocimeter was capable of visualizing both symmetric and asymmetric axial flow fields with high reliability.     

Three-dimensional crumpled graphene-based platinum–gold alloy nanoparticle composites as superior electrocatalysts for direct methanol fuel cells

High performance of electrocatalysts for direct methanol fuel cells was demonstrated by three-dimensional (3D) graphene (GR) decorated with platinum (Pt)–gold (Au) alloy nanoparticles (3D-GR/PtAu). The 3D-GR/PtAu composite with a morphology like a crumpled paper ball was synthesized from a colloidal mixture of GR and Pt–Au alloy nanoparticles with aerosol spray drying. The 3D-GR/PtAu had a high specific surface area and electrochemical surface area of up to 238 and 325 m²/g(Pt), respectively, and the electrocatalytic applications of the 3D-GR/PtAu were examined through methanol oxidation reactions. The 3D-GR/PtAu had the highest electrocatalytic activity for methanol oxidation reactions compared with commercial Pt–carbon black and Pt-GR. The 3D-GR/PtAu was also highly sensitive electrocatalytic activity in the methanol oxidation reaction compared with the 2D-GR/Pt–Au. Furthermore, the electrocatalytic activity of the 3D-GR/PtAu had the highest performance among the catalysts containing Pt, Au, and GR for the methanol oxidation reactions. The increased electrocatalytic activity is attributed to the high specific surface area of the 3D formation and the effective surface structure of the Pt–Au alloy nanoparticles.     

A Two-Dimensional Numerical Analysis for Thermal Performance of an Intermittently Operated Radiant Floor Heating System in a Transient External Climatic Condition

Abstract

Building thermal inertia and operation control strategies have impacted on the thermal performance of a radiant floor heating system. This study conducts a two-dimensional numerical analysis of an intermittently operated radiant floor heating system using the Re-Normalization Group model with Discrete Ordinates Radiation model. A detailed numerical simulation setups and various analyses are provided, including grid independency analysis, initial condition, time step sizes and external boundary conditions. Three different weekend day intermittent operation strategies are investigated. The results showed that Case 3 designed with pre-heating of 20?h has better performance compared to Case 1 designed with pre-heating of 8?h and Case 2 designed with pre-heating of 14?h. The average indoor air temperature differences of approximate 2.1, 1.6 and 1.2 K are observed for Case 1, Case 2 and Case 3, respectively, when comparing two-time slot at 8:00am on Friday morning and Monday morning. This significantly highlights the effect of thermal inertia and the potential of energy saving due to the utilization of intermittent operation. Therefore, the current study presents numerical simulation potential in evaluating the radiant floor heating effects on indoor thermal environment, taking into account building thermal inertia and transient external climatic conditions.     

ZnIn2S4/In(OH)3 hollow microspheres fabricated by one-step l-cysteine-mediated hydrothermal growth for enhanced hydrogen production and MB degradation

An intervening barrier for photocatalytic water decomposition and pollutant degradation is the frustratingly quick recombination of e⁻ - h⁺ pairs. Delicate design of heterojunction photocatalysts by coupling the semiconductors at nanoscale with well-matched geometrical and electronic alignments is an effective strategy to ameliorate the charge separation. Here a facile and environment-friendly l-cysteine-assisted hydrothermal process under weakly alkaline conditions is demonstrated for the first time to fabricate ZnIn₂S₄/In(OH)₃ hollow microspheres with intimate contact, which are verified by XRD, SEM, (HR)TEM, XPS, N₂ adsorption-desorption, UV–Vis DRS and photoluminescence spectra. ZnIn₂S₄/In(OH)₃ heterostructure (L-cys/Zn²⁺ = 4, molar ratio) with a band-gap of 2.50 eV, demonstrates the best photocatalytic performance for water reduction and MB degradation under visible light, outperforming its counterparts (In(OH)₃ and ZnIn₂S₄). The excellent activity of ZnIn₂S₄/In(OH)₃ heterostructure arises from the intercrossed band-edge positions as well as the unique hollow structure with large surface area and wide pore-size distribution, which are beneficial for the efficient charge migration from bulk to surface as well as at the interface between ZnIn₂S₄ and In(OH)₃. This work provides an efficient and eco-friendly strategy for one-pot synthesis of heterostructured composites with intimate contact for photocatalytic application.     

Experiments and simulations of the mechanical performance of repaired panels

Firstly, the compress experiment is undertaken to investigate the efficiency of repaired panels in this paper, and then modeling of the mechanical behavior of the repaired composite panel under compressive static load is conducted by using of the finite element method. The effect of geometric non-linearity on the stress–strain response is considered in the numeric analysis. Fatherly, the user material subroutine (UMAT) is integrated with the ABAQUS package with the geometric non-linearity effect for studying the damage initiation and its progression in the composite structure, and quadrilateral, linear, thick shell elements (S8R) are adopted. Finally, the predicted strain distribution, damage evolution and strength of the laminate are compared with the test results.     

物联网在公交车智能监控调度系统中的应用研究

介绍了物联网技术的概念、基本特征、发展现状以及物联网中的关键技术,提出了一种公交车智能监控调度模型,并分析了该系统架构中各个模块的功能,以便在一定程度上促进公交系统的发展,同时也促进物联网的建设与发展。     

Design and implementation of a new tuned hybrid intelligent model to predict the uniaxial compressive strength of the rock using SFS-ANFIS

This study proposes a novel design to systematically optimize the parameters for the adaptive neuro-fuzzy inference system (ANFIS) model using stochastic fractal search (SFS) algorithm. To affirm the efficiency of the proposed SFS-ANFIS model, the predicting results were compared with ANFIS and three hybrid methodologies based on ANFIS combined with genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO). Accurate prediction of uniaxial compressive strength (UCS) is of great significance for all geotechnical projects such as tunnels and dams. Hence, this study proposes the use of SFS-ANFIS, GA-ANFIS, DE-ANFIS, PSO-ANFIS, and ANFIS models to predict UCS. In this regard, the fresh water tunnel of Pahang–Selangor located in Malaysia was considered and the requirement data samples were collected. Different statistical metrics such as coefficient of determination (R²) and mean absolute error were used to evaluate the models. Referring to the efficiency results of SFS-ANFIS, it can be found that the SFS-ANFIS (with the R² of 0.981) has higher ability than PSO-ANFIS, DE-ANFIS, GA-ANFIS, and ANFIS models in predicting the UCS.

     

A novel deep learning scheme for multi-condition remaining useful life prediction of rolling element bearings

The remaining useful life (RUL) prediction of a rolling element bearing is important for more reasonable maintenance of machinery and equipment. Generally, the information of a failure can hardly be acquired in advance while running and the degradation process varies in terms of different faults. Thus, fault identification is indispensable for a multi-condition RUL prediction, where, however, the fault identification and RUL prediction are separated in most studies. A new hybrid scheme is proposed in this paper for the multi-condition RUL prediction of rolling element bearings. The proposed scheme contains both classification and regression, where the 2D-DCNN based classifier and predictors are built concerning typical fault conditions of a bearing. For the online prediction, the raw signals are spanned in the time-frequency domain and then transferred into images as the input of the scheme. The classifier is used to monitor the vibration of rolling bearings for online fault recognition and excite the corresponding predictor for RUL prediction once a fault is detected. The output from the predictor is amended by the proposed adaptive delay correction method as the final prediction results. A demonstration is performed based on the XJTU-SY datasets and the results are compared with those from the state-of-the-art methods, which proves the superiority of the proposed scheme in improving the accuracy and linearity of RUL prediction. The time cost of the proposed online prediction scheme is also investigated and the results indicate high time effectiveness.     

基于OPC的焦化厂备煤系统异构网络化控制系统设计

针对焦化厂备煤生产车间内部由于具有多种网络体系或者结构的现场总线及控制系统而造成信息无法共享的问题,提出了一种基于OPC技术的异构网络化控制系统的设计方案,详细介绍了系统的OPC服务器/客户端的设计开发。该系统通过基于工业以太网的TCP/IP体系连接所有子系统,并利用OPC技术为异构数据源提供统一数据接口,使数据管理层能够获取各种数据,解决了异构网络中数据信息转换、集成及存储问题,满足了企业生产过程中信息互操作以及与企业信息系统集成的要求。