Longitudinal permeability determination of dual-scale fibrous materials

In this work, the longitudinal permeability of squarely packed dual-scale fiber preforms is studied theoretically. These fiber preforms are composed of aligned porous tows and the tows are tightly packed. The effective permeability is calculated as a parallel-like network of intra-tow permeability and inter-tow permeability, which are quantified by Darcy’s law and the inscribed radius between tows, respectively. The jump velocity at the interface between inter-tow fluids and porous tows is considered, as derived by substituting Beavers and Joseph’s correlation into Brinkman’s equation. We further examine the effects of intra-tow permeability on the effective permeability of the fibrous system with three interface conditions: (1) interface velocity = 0, (2) interface velocity = mean intra-tow velocity, and (3) interface velocity = jump velocity. The jump-velocity-based model is found to be closest to numerical data. The influence of the fiber volume fraction of tows on the effective permeability is also analyzed.     

Off‐grid DoA estimation method of wideband signals

In this paper, an off‐grid direction of arrival (DoA) estimation method is proposed for wideband signals. This method is based on the sparse representation (SR) of the array covariance matrix. Similar to the time domain DoA estimation methods, the correlation function of the sources was assumed to be the same and known. A new measurement vector is obtained using the lower‐left triangular elements of the covariance matrix. The DoAs are estimated by quantizing the entire range of continuous angle space into discrete grid points. However, the exact DoAs may be located between two grid points; therefore, this estimation has errors. The accuracy of DoA estimation is improved by the minimization of the difference between the new measurement vector and its estimated values. Simulation results revealed that the proposed method can enhance the DoA estimation accuracy of wideband signals.     

干扰条件下的“北斗”信号解扩重构DOA估计

在干扰条件下，卫星导航抗干扰波束形成算法往往需要卫星信号波达方向（Direction-of-Arrival，DOA）的先验信息。但当存在低信噪比信号或主动干扰源时，常规的DOA估计算法性能急剧下降甚至失效。针对此问题，提出了一种被干扰信号压制的低信噪比“北斗”信号的DOA估计算法。该算法首先通过对接收信号进行子空间投影抑制干扰信号，然后对抑制干扰后的信号进行解扩重构处理，最后通过多重信号分类算法完成对“北斗”信号的DOA估计。仿真结果表明，在干扰信号干信比80 dB条件下，“北斗”信号DOA估计误差在5°以内，为下一步进行波束形成计算提供了高精度的入射角信息。     

Analysis of adhesively bonded CFRE composite scarf joints modified with MWCNTs

The main objective of the present work is to improve the performance of bonded joints in carbon fiber composite structures through introducing Multi-Walled Carbon Nanotubes (MWCNTs) into Epocast 50-A1/946 epoxy, which was primarily developed for joining and repairing of composite aircraft structures. Results from tension characterizations of structural adhesive joints (SAJs) with different scarf angles (5–45°) showed improvement up to 40% compared to neat epoxy (NE)–SAJs. Special attention was considered to investigate the performance of SAJs with 5° scarf angle under different environments. The tensile strength and stiffness of both NE-SAJs and MWCNT/E-SAJs were dramatically decreased at elevated temperature. Water absorption showed a marginal drop of about 2.0% in the tensile strength of the moist SAJs compared to the dry one. Cracks initiation and propagation were detected effectively using instrumented-SAJs with eight strain gauges. The experimental results agree well with the predicted using three-dimensional finite element analysis model.     

Stochastic free vibration analyses of composite shallow doubly curved shells – A Kriging model approach

This paper presents the Kriging model approach for stochastic free vibration analysis of composite shallow doubly curved shells. The finite element formulation is carried out considering rotary inertia and transverse shear deformation based on Mindlin’s theory. The stochastic natural frequencies are expressed in terms of Kriging surrogate models. The influence of random variation of different input parameters on the output natural frequencies is addressed. The sampling size and computational cost is reduced by employing the present method compared to direct Monte Carlo simulation. The convergence studies and error analysis are carried out to ensure the accuracy of present approach. The stochastic mode shapes and frequency response function are also depicted for a typical laminate configuration. Statistical analysis is presented to illustrate the results using Kriging model and its performance.     

Piezoresistive in-situ strain sensing of composite laminate structures

Various methods have been developed to monitor the health and strain state of carbon fiber reinforced polymers, each with a unique set of pros and cons. This research assesses the use of piezoresistive sensors for in situ strain measurement of carbon fiber and other composite structures in multidirectional laminates. The piezoresistive sensor material and the embedded circuitry are both evaluated. For the piezoresistive sensor, a conductive nickel nanocomposite sensor is compared with the piezoresistivity of the carbon fiber itself. For the circuit, the use of carbon fibers already present in the structure is compared with the use of nickel coated carbon fiber. Successful localized strain sensing is demonstrated for several sensor and circuitry configurations. Numerous engineering applications are possible in the ever-growing field of carbon-composites.     

Microwave assisted-in situ synthesis of porous titanium/calcium phosphate composites and their in vitro apatite-forming capability

Microwave irradiation has been proven to be an effective heating source in synthetic chemistry, and can accelerate the reaction rate, provide more uniform heating and help in developing better synthetic routes for the fabrication of bone-grafting implant materials. In this study, a new technique, which comprises microwave heating and powder metallurgy for in situ synthesis of Ti/CaP composites by using Ti powders, calcium carbonate (CaCO₃) powders and dicalcium phosphate dihydrate (CaHPO₄·2H₂O) powders, has been developed. Three different compositions of Ti:CaCO₃:CaHPO₄·2H₂O powdered mixture were employed to investigate the effect of the starting atomic ratio of the CaCO₃ to CaHPO₄·2H₂O on the phase, microstructural formation and compressive properties of the microwave synthesized composites. When the starting atomic ratio reaches 1.67, composites containing mainly alpha-titanium (α-Ti), hydroxyapatite (HA), beta-tricalcium phosphate (β-TCP) and calcium titanate (CaTiO₃) with porosity of 26%, pore size up to 152 μm, compressive strength of 212 MPa and compressive modulus of 12 GPa were formed. The in vitro apatite-forming capability of the composite was evaluated by immersing the composite into a simulated body fluid (SBF) for up to 14 days. The results showed that biodissolution occurred, followed by apatite precipitation after immersion in the SBF, suggesting that the composites are suitable for bone implant applications as apatite is an essential intermediate layer for bone cells attachment. The quantity and size of the apatite globules increased over the immersion time. After 14 days of immersion, the composite surface was fully covered by an apatite layer with a Ca/P atomic ratio approximately of 1.68, which is similar to the bone-like apatite appearing in human hard tissue. The results suggested that the microwave assisted-in situ synthesis technique can be used as an alternative to traditional powder metallurgy for the fabrication of Ti/CaP biocomposites.     

基于三维胞元空间的MA双向并行路由算法

针对传统移动代理(MA)在监测无线传感器网络(WSNs)的感兴趣信息时产生的延迟较大和能耗较多问题,提出了基于三维胞元空间的MA双向并行(3D-BPMA)路由算法.3D-BPMA将MA与传统的客户/服务器(c/S)模式相结合,在胞元内利用C/S模式搜集信息,在单层胞元系统和路由器与路由器之间采用MA双向并行的策略进行传输.仿真结果表明:3D-BPMA与LCF,DSG-MIP算法相比减少了平均响应时间和网络平均能耗,提高了MA发送率.     

Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.