Experimental study to assess the effect of carbon nanotube addition on the through-thickness electrical conductivity of CFRP laminates for aircraft applications

The present paper tests experimentally the through-thickness electrical conductivity of carbon fiber-reinforced polymer (CFRP) composites laminates for aircraft applications. Two types of samples were prepared: Type A samples with carbon nanotubes (CNTs) and Type B samples without CNTs. During the electrical experiments, electrical currents of several mA were injected through the specimens. Electrical resistance was monitored simultaneously in order to deduce the changes in the through-the-thickness electrical conductivity caused by the addition of CNTs. Improvement of electrical conduction by two orders of magnitude was achieved through the addition of 1 wt% carbon nanotubes as compared to classic CFRP without CNTs. For moisture saturated samples, the influence of moisture absorption on such measures was found to be negligible.     

Using constraints and their value for optimization of large ODE systems

We provide analytical tools to facilitate a rigorous assessment of the quality and value of the fit of a complex model to data. We use this to provide approaches to model fitting, parameter estimation, the design of optimization functions and experimental optimization. This is in the context where multiple constraints are used to select or optimize a large model defined by differential equations. We illustrate the approach using models of circadian clocks and the NF-κB signalling system.     

Detection of multiple low-energy impact damage in composite plates using Lamb wave techniques

This work assesses the suitability of the two zero-order Lamb wave modes to detect multiple barely-visible impact damage in composite material. Three specimens were subjected to damage at three different low-energy levels and one was left as an undamaged reference sample. Ultrasonic Lamb wave modes were selectively generated by surface-bonded piezoceramic wafer transducers in two tuned configurations. By using an algorithm based on the Akaike Information Criterion the time-of-flight of the Lamb modes was determined, allowing their threshold detection capabilities for the studied application to be successfully benchmarked. The results were consistently validated by digital shearography, ultrasonic C-scan and optical microscopy. A study of the effects on structural integrity was completed with an assessment of the damping ratio and residual bending strength proving to be sensitive parameters to the induced damage.     

Demonstration of pseudo-ductility in unidirectional hybrid composites made of discontinuous carbon/epoxy and continuous glass/epoxy plies

A new, partially discontinuous architecture is proposed to improve the mechanical performance of pseudo-ductile, unidirectional (UD) interlayer carbon/glass hybrid composites. The concept was successfully demonstrated in different laminates with high strength and high modulus carbon and S-glass epoxy UD prepregs. The novel hybrid architecture provided pseudo-ductile tensile stress–strain responses with a linear initial part followed by a wide plateau and a second linear part, all connected by smooth transitions. The best hybrid configuration showed 60% improvement in modulus compared to pure glass, 860 MPa plateau stress and 2% pseudo-ductile strain. The initial modulus, the plateau stress and the overall tensile stress–strain response of each specimen configuration were predicted accurately.     

Effects of ethylene-octene copolymer (POE) on the brittle to ductile transition of high-density polyethylene/POE blends

Three kinds of ethylene-octene copolymers (POE) were melt-blended with high-density polyethylene (PE-HD) in different proportions. Detailed characterizations were conducted to analyze their structural differences of POE and its effects in toughening PE-HD. The higher molecular weight POE can improve the toughness of PE-HD. 60:40 PE-HD/POE is elongated to break up to 700% while impact strength is 84.7 kJ/m² at −30°C, which is 21-fold of PE-HD. In the brittle to ductile transition (BDT) during impact, the fracture mechanism changes from the crazing mode to the shear yield-plastic deformation mode. The BDT temperature decreases as the POE molecular weight and its content increase. The interface strength in tension is estimated to access their effects. The Boltzmann-type models were successfully extended to describe the typical S-shaped curves in BDT of notched impact strength vs POE content or temperature. The supplementary decay model is suggested for the attenuation in toughening. Transition map in impact is proposed to select the use range of composition (c ) and temperature (T ) for high toughness. The curves are converted into 3D graph of T -c -impact strength for illustrating their coupling-separate effects, and further into the contour map of impact strength in T -c space for finding their partial equivalence.     

Acoustic emission analysis using Bayesian model selection for damage characterization in ceramic matrix composites

Acoustic emission (AE) during tensile testing of three-dimensional woven SiC/SiC composites was analyzed by a statistical modeling method based on a Bayesian approach to quantitatively evaluate the fracture process. Gaussian mixture models and Weibull mixture models were utilized as candidate models describing the AE time-series data. After fitting AE time-series data to these models with Markov Chain Monte Carlo (MCMC) methods, the model selection was conducted by stochastic complexity. Among the candidate models, the two-component Weibull mixture model was automatically selected. It was confirmed that the component distributions in the two-component Weibull mixture model were corresponding to the evolution of matrix cracking and fiber breakage, respectively. Since the proposed AE analysis method can determine the number of component distributions without the decision of researchers and inspectors, it is expected to be useful for an understanding of the fracture process in newly developed materials and the reliability assessment in service.     

Consideration of multi‐coil type magnetization system for magnetic particle testing of omnidirectional crack in all surfaces of 3D shape test object

Mechanical parts, plants, and cross‐linkages inspected with magnetic‐particle testing (MT) are typically complex 3D shapes. In complex 3D shape portions, because a magnetizer often cannot be configured to inspection portions and the test object cannot be appropriately magnetized, there is a possibility of overlooking a crack in such an instance. Thus, MT system development that was successfully able to detect omnidirectional cracks in 3D shape portions was considered in this study's trials. Two multi‐coil type magnetizers were hence arranged face‐to‐face, and the magnetization of omnidirectional scenarios for all surfaces of 3D shape test object was evaluated.     

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%.     

Blockchain verification and validation: Techniques,challenges, and research directions

As blockchain technology is gaining popularity in industry and society, solutions for Verification and Validation (V&V) of blockchain-based software applications (BC-Apps) have started gaining equal attention. To ensure that BC-Apps are properly developed before deployment, it is paramount to apply systematic V&V to verify their functional and non-functional requirements. While existing research aims at addressing the challenges of engineering BC-Apps by providing testing techniques and tools, blockchain-based software development is still an emerging research discipline, and therefore, best practices and tools for the V&V of BC-Apps are not yet sufficiently developed. In this paper, we provide a comprehensive survey on V&V solutions for BC-Apps. Specifically, using a layered approach, we synthesize V&V tools and techniques addressing different components at various layers of the BC-App stack, as well as across the whole stack. Next, we provide a discussion on the challenges associated with BC-App V&V, and summarize a set of future research directions based on the challenges and gaps identified in existing research work. Our study aims to highlight the importance of BC-App V&V and pave the way for a disciplined, testable, and verifiable BC development.     

起重机械移动综合检测平台的研制开发

起重机械作为工业发展的基础性产业，其安全使用一直备受关注，有关的检测技术和手段日新月异。文中结合起重机械检验检测工作特点和流程，基于目前日趋成熟的移动实验室技术，提出了起重机械移动综合检测平台的设计方案。对现有检测手段、业务流程、办公软件、网络系统等进行整合，将检测平台结构分为车载基础和业务测试2个功能模块，实现了起重机械一站式的业务服务、检验检测、远程联检等功能，推进检验检测工作提质增效，并具有一定的扩展性，为智慧特检提供了一种思路。