Search

Glutamate is the most abundant excitatory neurotransmitter in the central nervous system, and its precise control is vital to maintain normal brain function and to prevent excitotoxicity1. The removal of extracellular glutamate is achieved by plasma-membrane-bound transporters, which couple glutamate transport to sodium, potassium and pH gradients using an elevator mechanism2–5. Glutamate transporters also conduct chloride ions by means of a channel-like process that is thermodynamically uncoupled from transport6–8. However, the molecular mechanisms that enable these dual-function transporters to carry out two seemingly contradictory roles are unknown. Here we report the cryo-electron microscopy structure of a glutamate transporter homologue in an open-channel state, which reveals an aqueous cavity that is formed during the glutamate transport cycle. The functional properties of this cavity, combined with molecular dynamics simulations, reveal it to be an aqueous-accessible chloride permeation pathway that is gated by two hydrophobic regions and is conserved across mammalian and archaeal glutamate transporters. Our findings provide insight into the mechanism by which glutamate transporters support their dual function, and add information that will assist in mapping the complete transport cycle shared by the solute carrier 1A transporter family. Glutamate transporters conduct chloride ions through an aqueous channel with hydrophobic gates that forms during the glutamate transport cycle.

This work aims to address the effectiveness and challenges of using active infrared thermography (IRT) onboard an unmanned aerial vehicle (UAV) platform. The work seeks to assess the performance of small low-powered forms of excitation which are suitable for active thermography and the ability to locate subsurface defects on composites. An excitation source in multiple 250 W lamps is mounted onto a UAV and is solely battery powered with a remote trigger to power cycle them. Multiple experiments address the interference from the UAV whilst performing an active IRT inspection. The optimal distances and time required for a UAV inspection using IRT are calculated. Multiple signal processing techniques are used to analyse the composites which help locate the sub-surface defects. It was observed that a UAV can successfully carry the required sensors and equipment for an Active thermographic NDT inspection which can provide access to difficult areas. Most active thermographic inspection equipment is large, heavy, and expensive. Furthermore, using such equipment for the inspection of complex structures is time-consuming. For example, a cherry picker would be required to inspect the tail of an aircraft. This solution looks to assist engineers in inspecting complex composite structures and could potentially significantly reduce the time and cost of a routine inspection. Engineering and Physical Sciences Research Council (EPSRC): EP/N509450/1 and Innovate UK: 105625.

An effective implementation of enhanced sampling algorithms for molecular dynamics simulations requires a priori knowledge of the approximate reaction coordinate describing the relevant mechanisms in the system. Here we demonstrate how the artificial intelligence based recent State Predictive Information Bottleneck (SPIB) approach can learn such a reaction coordinate as a deep neural network even from under-sampled trajectories. We demonstrate its usefulness by achieving more than 40 magnitudes of acceleration in simulating two test-piece biophysical systems through well-tempered metadynamics performed by biasing along the SPIB learned reaction coordinate. These include left- to right- handed chirality transitions in a synthetic protein (Aib)(9), and permeation of a small, asymmetric molecule benzoic acid through a synthetic, symmetric phospholipid bilayer. In addition to significantly accelerating the dynamics and achieving back-and-forth movement between different metastable states, the SPIB based reaction coordinate gives mechanistic insight into the processes driving these two important problems.

Structural Health Monitoring (SHM) aims to shift aircraft maintenance from a time-based to a condition-based approach. Within all the SHM techniques, Acoustic Emission (AE) allows for the monitoring of large areas by analyzing Lamb waves propagating in plate like structures. In this study, the authors proposed a Time Reversal (TR) methodology with the aim of reconstructing an original and unaltered signal from an AE event. Although the TR method has been applied in Narrow-Band (NwB) signal reconstruction, it fails when a Broad-Band (BdB) signal, such as a real AE event, is present. Therefore, a novel methodology based on the use of a Frequencies Compensation Transfer Function (FCTF), which is capable of reconstructing both NwB and real BdB signals, is presented. The study was carried out experimentally using several sensor layouts and materials with two different AE sources: (i) a Numerically Built Broadband (NBB) signal, (ii) a Pencil Lead Break (PLB). The results were validated numerically using Abaqus/CAETM with the implementation of absorbing boundaries to minimize edge reflections.

Using aerial platforms for Non-Destructive Inspection (NDI) of large and complex structures is a growing field of interest in various industries. Infrastructures such as: buildings, bridges, oil and gas, etc. refineries require regular and extensive inspections. The inspection reports are used to plan and perform required maintenance, ensuring their structural health and the safety of the workers. However, performing these inspections can be challenging due to the size of the facility, the lack of easy access, the health risks for the inspectors, or several other reasons, which has convinced companies to invest more in drones as an alternative solution to overcome these challenges. The autonomous nature of drones can assist companies in reducing inspection time and cost. Moreover, the employment of drones can lower the number of required personnel for inspection and can increase personnel safety. Finally, drones can provide a safe and reliable solution for inspecting hard-to-reach or hazardous areas. Despite the recent developments in drone-based NDI to reliably detect defects, several limitations and challenges still need to be addressed. In this paper, a brief review of the history of unmanned aerial vehicles, along with a comprehensive review of studies focused on UAV-based NDI of industrial and commercial facilities, are provided. Moreover, the benefits of using drones in inspections as an alternative to conventional methods are discussed, along with the challenges and open problems of employing drones in industrial inspections, are explored. Finally, some of our case studies conducted in different industrial fields in the field of Non-Destructive Inspection are presented.

Piezoelectric lead zirconate titanate (PZT) sensors are widely used in various structural health monitoring (SHM) applications, where data acquired by the PZT sensors are used for damage detection. Any failure of the PZT sensors will have a detrimental effect in the ability of SHM systems to detect damage. Therefore, detecting faulty PZT sensor is critical to reduce any false-calls associated with malfunctioning sensor to ensure proper functionality of SHM systems. This paper proposes a self-diagnostic method to monitoring the health of PZT sensors using the electro-mechanical impedance (EMI) data in two steps. In the first detection step, the onedimensional convolutional autoencoder (1D-CAE) is employed to obtain the reconstruction error as anomaly scores from the raw EMI data. Hence, the faulty PZT sensors can be detected by comparing the anomaly score with a pre-defined threshold. In the second diagnostic step, the data feature is first extracted with the 1D-CAE. The extracted feature is then fed into a multilayer perceptron (MLP) classifier to classify the fault type of the PZT sensor. The proposed method was validated through experiments, where typical in-service induced damages such as impact, environmental effect, sensor breakage localized high temperature heating, etc. were introduced. The results demonstrate the effectiveness of the proposed method for both detection and diagnosis of various types of PZT sensor damage., Health Monitoring of Structural and Biological Systems XV, March 22-27, 2021, United States, Series: Proceedings of SPIE

Unmanned Aerial Vehicles (UAVs) that can fly around an aircraft carrying several sensors, e.g., thermal and optical cameras, to inspect the parts of interest without removing them can have significant impact in reducing inspection time and cost. One of the main challenges in the UAV based active InfraRed Thermography (IRT) inspection is the UAV’s unexpected motions. Since active thermography is mainly concerned with the analysis of thermal sequences, unexpected motions can disturb the thermal profiling and cause data misinterpretation especially for providing an automated process pipeline of such inspections. Additionally, in the scenarios where post-analysis is intended to be applied by an inspector, the UAV’s unexpected motions can increase the risk of human error, data misinterpretation, and incorrect characterization of possible defects. Therefore, post-processing is required to minimize/eliminate such undesired motions using digital video stabilization techniques. There are number of video stabilization algorithms that are readily available, however, selecting the best suited one is also challenging. Therefore, this paper evaluates video stabilization algorithms to minimize/mitigate undesired UAV motion and proposes a simple method to find the best suited stabilization algorithm as a fundamental first step towards a fully operational UAV-IRT inspection system.

Approximately up to one-fifth of the direct operating cost of a commercial civilian fixed-wing aircraft is projected to be due to inspection and maintenance alone. Managing aircraft health with minimal human intervention and technologies that can perform continuous or on-demand monitoring/evaluation of aircraft components without having to take the aircraft out of service can have a significant impact on increasing availability while reducing maintenance cost. The ambition of these monitoring technologies is to shift aircraft maintenance practice from planned maintenance (PM), where the aircraft is taken out of service for scheduled inspection/maintenance, to condition-based maintenance (CBM), where aircraft is taken out of service only when maintenance is required, while maintaining the required levels of safety. Structural health monitoring (SHM) techniques can play a vital role in progressing towards CBM practice. Therefore, this chapter aims to provide the reader with a brief overview of the different SHM techniques and their use, as well as, challenges in implementing them for aircraft applications., Series: Springer Aerospace Technology

Membrane transporters are key gatekeeper proteins at cellular membranes that closely control the traffic of materials. Their function relies on structural rearrangements of varying degrees that facilitate substrate translocation across the membrane. Characterizing these functionally important molecular events at a microscopic level is key to our understanding of membrane transport, yet challenging to achieve experimentally. Recent advances in simulation technology and computing power have rendered molecular dynamics (MD) simulation a powerful biophysical tool to investigate a wide range of dynamical events spanning multiple spatial and temporal scales. Here, we review recent studies of diverse membrane transporters using computational methods, with an emphasis on highlighting the technical challenges, key lessons learned, and new opportunities to illuminate transporter structure and function.

Acoustic Emission (AE) monitoring can be used to detect and locate structural damage such as growing fatigue cracks. The accuracy of damage location and consequently the inference of its significance for damage assessment is dependent on the wave propagation properties in terms of wave velocity, dispersion, attenuation and wave mode conversion. These behaviors are understood and accounted for in simplistic structures, however, actual structures are geometrically complex, with components comprising of different materials. One of the key challenges in such scenarios is the ability to positively identify wave modes and correctly associate their properties for damage location analysis. In this study, a novel method for wave mode identification is presented based on phase and instantaneous frequency analysis. Finite Element (FE) simulations and experiments on a representative aircraft wing structure were conducted to evaluate the performance of the technique. The results show how a phase analysis obtained from a Hilbert Transform of the wave signal in combination with variations of the instantaneous frequency of the wave signal, can be used to determine the arrival and therefore identification of the different wave modes on a complex structure. The methodology outlined in this paper was proven on an Automatic Sensor Test wave signal, Pencil Lead Breaks and Hanning windows and it was shown that the percentage difference is between 3% and 15% for the A0 and S0 wave speed respectively.

The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipid-protein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.

Structural health monitoring has focused on the use of computational models to capture the effect of crack-like discontinuities on the behaviour of acoustic-ultrasonic signals. However, few models have taken into account the effect of geometric complexity in combination with residual stresses generated during the fatigue crack growth process. In this study, a finite element analysis model of a C-channel type aeronautical structure is evaluated under a pitch-catch scenario. Three different finite element model configurations were considered in order to understand the effects that residual stresses of a fatigue crack emanating from a through-hole have on the guided Lamb wave propagation behaviour. The results demonstrate that numerical modelling is able to capture the change in amplitude and the effect of a phase shift on the guided Lamb wave behaviour due to the presence of the discontinuity and the stress field generated during the fatigue crack growth process.

In this paper, a one-sided, in situ method based on the time of flight measurement of ultrasonic waves was described. The primary application of this technique was to non-destructively measure the stiffness properties of isotropic and transversely isotropic materials. The method consists of generating and receiving quasi-longitudinal and quasi-shear waves at different through-thickness propagation angles. First, analytical equations were provided to calculate the ultrasonic wave velocities. Then, an inverse method based on non-linear least square technique was used to calculate the stiffness constants using the ultrasonic wave velocities. Sensitivity analysis was performed by randomly perturbing the velocity data, thus observing the effects of perturbations on the calculated stiffness constants. An improved algorithm was proposed and tested to reduce the effects of random errors. Based on the sensitivity analysis, minimum number of angles required to inversely calculate the stiffness constants were suggested for isotropic and transversely isotropic material. The method was experimentally verified on an isotropic 7050-T7451 aluminum with two different thicknesses and a transversely isotropic composite laminate fabricated using 24 plies of CYCOM 977-2 12 k HTA unidirectional carbon fiber reinforced polymer (CFRP) prepregs. The results demonstrated that this technique is able to accurately measure the material properties of isotropic material. As for the transversely isotropic material, this method was able to accurately measure the material properties if the experimental errors can be reduced to less than 1 %.

Rotor blades of Bell CH-146 Griffon helicopter experience excessive solid particle erosion at low altitudes in desert environment. The rotor blade is made of an advanced light-weight composite which, however, has a low resistance to solid particle erosion. Coatings have been developed and applied to protect the composite blade. However, due to the influence of coating process on composite material, the compatibility between coating and composite base, and the challenges of repairing damaged coatings as well as the inconsistency between the old and new coatings, replaceable thin metal shielding is an alternative approach; and titanium, due to its high-specific strength and better formability, is an ideal candidate. This work investigates solid particle erosion behaviors of carbon-fiber epoxy composite and titanium in order to assess the feasibility of titanium as a viable candidate for erosion shielding. Experiment results showed that carbon-fiber epoxy composite showed a brittle erosion behavior, whereas titanium showed a ductile erosion mode. The erosion rate on composite was 1.5 times of that on titanium at impingement angle 15° and increased to 5 times at impact angle 90°.