MRC Laboratory of Molecular Biology
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A macroscale finite element approach for simulating the bending behaviour of biaxial fabrics
No full textA macroscale finite element (FE) model was developed to simulate the forming behaviour of biaxial fabrics, incorporating the effects of bending stiffness to predict fabric wrinkling. The dependency of the bending stiffness on the fibre orientation was addressed by extending a non-orthogonal constitutive framework previously developed for biaxial fabric materials. The nonlinear bending behaviour of a biaxial non-crimp fabric (NCF) with pillar stitches was characterised by a revised cantilever test using structured light scanning to measure specimen curvature, providing input data for the material model. Simulations were performed to replicate the bias-extension behaviour of the NCF material, showing good agreement with experimental data. Wrinkles were observed within the central area of the specimen at low extension, which consequently affect the uniformity of the shear angle distribution in the region where pure shear is expected
Wind impacts on suspended sediment transport in the largest freshwater lake of China
No full textPoyang Lake, the largest freshwater lake in China, distinguishes itself by its complicated suspended sediment (SS) dynamics. Apart from lake currents, wind is an important form of natural disturbance in driving SS transport. Combining field data, laboratory experiments, and numerical simulations, we gained valuable insight into the wind impacts on SS dynamics in Poyang Lake. Several results stand out: (1) the lake current patterns exert great influence on the level of wind impacts. Due to the reduced sediment carrying capacity, SS under the weak current suffers from a stronger wind influence than those under strong currents; (2) The wind speed determines the degree of the wind impact. It not only affects the horizontal SS transport, but also regulates the vertical dynamics. Winds exceeding the critical intensity can enhance the horizontal transport through both surface drift and Stokes drift at different water depths, triggering sediment suspension to feed the loads in overlying water. (3) Wind impact is influenced by the lake morphology. The broad water surface in the central lake permits the formation of continuous waves, leading to the largest SS fluctuation, from -10.05 mg·L-1 to +20.17 mg·L-1, while the average variation in the south and north part of the lake is only from -6.59 mg·L-1 to +10.36 mg·L-1.(4) SS in four reserves are characterized by a notable wind impact, while in the other two reserves SS show no obvious departure from the values without wind
Development of an HTS magnet for ultra-compact MRI System: Optimization using genetic algorithm (GA) Method
No full textThis paper presents the design of an HTS magnet for an ultra compact MRI system, potentially for the rapid and early diagnosis of brain trauma. Early diagnosis and therapy stratification can reduce the risk for critically brain ill patients with the use of near patient imaging, and can aid with precision medicine. High temperature superconductors (HTS) have the ability to carry large currents in the cryogen free contrition, which can make the MRI system even smaller and lighter. The design and Genetic Algorithm (GA) optimization were based on the FEM package COMSOL Multiphysics with the LiveLink for MATLAB, together with the GA module in the MATLAB optimization toolbox. The relatively thick HTS tape, ST-12-L from the Shanghai Superconductor Technology was chosen and that made more difficulty on optimization process. Genetic Algorithm method improved the optimization performance, and the uniformity achieved 2.36 ppm in a 10 × 10 × 10 cm DSV. Two cases of the end double-pancake were compared. Further sensitivity studies were performed on the homogeneity with its relationship to the magnet length, and the thickness of HTS tape
Modulation of the resistive switching of BiFO<inf>3</inf> thin films through electrical stressing
No full textThe resistive switching (RS) of Au/BiFeO3/SrRuO3 samples was shown to be controllable by using a thermal treatment and an electrical stressing method. Such a modulation of resistive switching effect can be associated to the oxygen vacancy movement and redistribution within the BiFeO3 thin film and the trapping/detrapping of charge carriers at the interfaces. After the application of a negative voltage to the thin film for a stressing period, a resistive switching reversal effect occurred and the current retention ability in the low resistance state increased, indicating an increase in the trap density at the interface and an enhancement of the charge carrier trapping ability. The trap density, trap level, and Schottky barrier height all display corresponding trends in their values as a result of the modulation of RS effect. The results indicate that the greater the accumulation of oxygen vacancies at any the film/electrode interface, when a reverse bias is applied the higher the resistance ratio was under reverse bias. Its diffusion process was likely to be hindered and the trapped charge carriers could be retained after a long time of electrical stressing
Multi-agent systems and complex networks: Review and applications in systems engineering
No full textSystems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant
Plant-Inspired Polyaleuritate–Nanocellulose Composite Photonic Films
No full textPlant epidermis is a complex composite material composed by the cuticle and the epidermal cells. In order to prevent dehydration the cuticle is a water barrier composed of an outer layer (proper cuticle) connected to the cell wall of the epidermal cells via a complex matrix often referred to as cutinised cell wall, that acts as compatibilizer for the water repellent cutin and the hydrophilic polysaccharides in the cell walls. Here, biomimetic plant epidermis-inspired films with selective reflection properties were prepared by formation of an aliphatic polyester coating on chiral nematic cellulose nanocrystal (CNC) films. Aleuritic acid, a polyhydroxylated fatty acid, was sprayed on CNC films and polymerized by hot-pressing. The micromorphology of the resultant samples was characterized by scanning electron microscopy (SEM). Polarised optical microscopy confirmed the CNCs helicoidal organization in the films, responsible for the reflection of circularly polarised light, before and after the hot-pressing. The chemical analysis by attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) confirmed the polymerization of aleuritic acid into polyaleuritate with differences between filter paper and woodpulp substrates that were ascribed to water elimination during polycondensation. The characterization of the mechanical (Young’s modulus and hardness from nanoindentation tests) and hydrodynamic (water uptake and water vapor transmission rate) properties indicated that this process enhances the robustness and waterproof behaviour of CNC films. These properties were comparable to those of commercial and biodegradable materials commonly used in packaging such as polyesters and cellulose derivatives, thus making these natural composite ideal for optically responsive packaging applications
Optimisation of chaotically perturbed acoustic limit cycles
No full textIn an acoustic cavity with a heat source, the thermal energy of the heat source can be converted into acoustic energy, which may generate a loud oscillation. If uncontrolled, these acoustic oscillations, also known as thermoacoustic instabilities, can cause mechanical vibrations, fatigue and structural failure. The objective of manufacturers is to design stable thermoacoustic configurations. In this paper, we propose a method to optimise a chaotically perturbed limit cycle in the bistable region of a subcritical bifurcation. In this situation, traditional stability and sensitivity methods, such as eigenvalue and Floquet analysis, break down. First, we propose covariant Lyapunov analysis and shadowing methods as tools to calculate the stability and sensitivity of chaotically perturbed acoustic limit cycles. Second, covariant Lyapunov vector analysis is applied to an acoustic system with a heat source. The acoustic velocity at the heat source is chaotically perturbed to qualitatively mimic the effect of the turbulent hydrodynamic field. It is shown that the tangent space of the acoustic attractor is hyperbolic, which has a practical implication: the sensitivities of time-averaged cost functionals exist and can be robustly calculated by a shadowing method. Third, we calculate the sensitivities of the time-averaged acoustic energy and Rayleigh index to small changes to the heat-source intensity and time delay. By embedding the sensitivities into a gradient-update routine, we suppress an existing chaotic acoustic oscillation by optimal design of the heat source. The analysis and methods proposed enable the reduction of chaotic oscillations in thermoacoustic systems by optimal passive control. Because the theoretical framework is general, the techniques presented can be used in other unsteady deterministic multi-physics problems with virtually no modification
On the generation and segregation of helicity in geodynamo simulations
No full textHelicity, the inner product of velocity and vorticity, is considered an important ingredient for the maintenance of a dipolar magnetic field in the geodynamo. Outside the tangent cylinder- an imaginary cylinder which circumscribes the inner core-a spatial segregation of helicity has been observed in several simulations, being negative in the north and positive in the south. Such a segregation pattern is important for a dynamo that relies on the α-effect. However, the origin of this pattern in these simulations is poorly understood. In this paper, we use three strongly forced numerical dynamo solutions to study the various sources of helicity, including those due to buoyancy (HT ), Coriolis, Lorentz and viscous forces. We find a strong spatial correlation between the segregation pattern of helicity and HT both in the instantaneous and the time-averaged results. Our results show that, outside the tangent cylinder, HT is dominated by the product -μz∂T/∂, where uz is the vertical velocity component and T is the temperature perturbation. It is known that when inertial waves are launched from a localized buoyant anomaly, HT takes the same sign as the local helicity. We conjecture that this is the reason for the spatial correlation between HT and helicity in our simulation results. The flow in our simulations being strongly turbulent, this effect seems to be a statistical one and manifests itself most clearly in the averaged quantities
Blow-off mechanisms of turbulent premixed bluff-body stabilised flames operated with vapourised kerosene fuels
No full textThe lean blow-off (LBO) behaviour of unconfined lean premixed blu -body stabilised flames with various fuels was investigated. Methane and vapourised ethanol, heptane, Jet-A1, and an alternative alcohol-derived kerosene (Gevo) were used. OH* chemiluminescence (5 kHz), OH- and Fuel-PLIF (5 kHz), and CH2O-PLIF (10 Hz) were deployed. For all fuels, as the flame approached LBO fragmentation was observed downstream, the two sides of the flame merged at the axis, pockets of OH and CH2O were found in the recirculation zone (RZ), and eventually the individual fragments extinguished. The CH2O seemed to enter into the RZ from downstream early in the LBO process, with reactants following suit at times closer to LBO. During LBO, the integrated OH* signal decreased slowly to zero and the duration of this transition was 25 (d=UBO) in the methane and ethanol flames and 60 (d=UBO) in flames operated with heptane and the two kerosenes (where d is the blu -body diameter and UBO the LBO velocity). This large di erence could be due to re-ignitions of partially-quenched fluid inside the RZ during the LBO event. Additionally, for the same bulk velocity, the kerosene flames blow-o at higher equivalence ratios than the single-component fuelled flames, which is possibly due to the higher Lewis number and lower extinction strain rates of these fuels. The results suggest that the blow-o mechanism is qualitatively similar for each of the fuels; however, the complex chemistry associated with heavy hydrocarbons appears to result in a prolonged LBO event
Cost-sensitive learning classification strategy for predicting product failures
No full textIn the current era of Industry 4.0, sensor data used in connection with machine learning algorithms can help manufacturing industries to reduce costs and to predict failures in advance. This paper addresses a binary classification problem found in manufacturing engineering, which focuses on how to ensure product quality delivery and at the same time to reduce production costs. The aim behind this problem is to predict the number of faulty products, which in this case is extremely low. As a result of this characteristic, the problem is reduced to an imbalanced binary classification problem. The authors contribute to imbalanced classification research in three important ways. First, the industrial application coming from the electronic manufacturing industry is presented in detail, along with its data and modelling challenges. Second, a modified cost-sensitive classification strategy based on a combination of Voronoi diagrams and genetic algorithm is applied to tackle this problem and is compared to several base classifiers. The results obtained are promising for this specific application. Third, in order to evaluate the flexibility of the strategy, and to demonstrate its wide range of applicability, 25 real-world data sets are selected from the KEEL repository with different imbalance ratios and number of features. The strategy, in this case implemented without a predefined cost, is compared with the same base classifiers as those used for the industrial problem