Use of Confocal Raman Microscopy to Characterise Ethyl Cyanoacrylate Adhesive Depth Curing

In situ spatial temporal measurement of monomer conversion during adhesive bondline curing remains a challenging area. The aim of this work was to demonstrate the effectiveness of using confocal Raman microscopy in a specially configured experimental set-up, as a versatile tool for measuring monomer concentration changes as a function of both time and adhesive bond depth during ethyl cyanoacrylate polymerisation. This also allowed monitoring of the extent of polymerisation at the adhesive substrate interface independently of the bulk bondline polymerisation region. Key kinetic parameters such as inhibition time tlag, rate of reaction Rmax and extent of reaction [at]max were obtained by fitting the experimental data to sigmoidal growth curves using simple piecewise regression models. A systematic characterisation of a polymerisation reaction was conducted using different sample substrate types (copper alloy (red brass), aluminium, aluminium alloy, stainless steel and borosilicate glass) and at various reaction temperatures. Reaction rates were found to decrease further away from the substrate interface in the bulk volume region. The fastest kinetics occurred in the vicinity of nucleophilic hydroxyl rich surfaces such as at the copper alloy (red brass). In addition to substrate surface chemistry, surface roughness was also a factor, with the highest reaction rates occurring with a grit blasted (roughened) aluminium alloy (2024 T3) surface. An approximately linear dependence of the ln Rmax vs. 1/T (Arrhenius) plot was recorded within the temperature range of 291–328 K. A better fit was obtained however through the use of two separate linear slopes, possibly indicative of a change of polymerisation reaction mechanism taking place at elevated temperatures with two distinct activation energies. Further work conducted using a larger number of temperatures would be useful to verify this finding. This work confirmed that differences in the rates of interfacial and bulk polymerisation processes could be readily measured in situ using confocal Raman microscopy which is a powerful technique for investigating such surface-confined and bulk polymerisation reaction

Analysis of copper(II) using the ascorbate/oxygen system – a valuable undergraduate resource

In deionised water, ascorbic acid (AH−), through oxidation by oxygen in the presence of copper(II), was found to degrade with zero-order kinetics. The magnitude of the reaction rate varied directly with the copper(II) concentration. At a higher pH (7.4), the same reaction was found to be pseudo-first order. Once again, the magnitude of the rate increased linearly with copper(II) concentration at a micromolar level. Dissolved oxygen levels, in excess AH− and trace copper(II), displayed similar kinetics under both conditions. Monitoring of either AH− levels or dissolved oxygen concentration was found to be a useful novel undergraduate practical laboratory for trace copper(II) determination. Students can measure the kinetics for standards and their unknown copper solution and quantitate the unknown copper

A simple microcalorimetry system to determine the adsorption behaviour of acids in large adhesive bond gaps using base-initiated solution polymerisation of ethyl-2-cyanoacrylate

This work presents the use of a simple microcalorimetry cyanoacrylate (CA) polymerisation system for investigating aspects of CA adhesive cure through gap and adsorption of adhesive acid stabiliser by a range of metal and glass substrates. It is well established that strong acid induced inhibition periods (IPs) are almost directly proportional to the acid concentration in weak base initiated polymerisations of alkyl CAs in tetrahydrofuran (THF). Ethyl cyanoacrylate (ECA) polymerisation IP measurements were used to determine the adsorption of methanesulfonic acid (MSA) in THF or ECA solutions by a range of metal, glass and polypropylene (PP) lap shears surfaces. The extent of substrate acid sorption was found to decrease in the order: Copper- zinc alloy (C23000) \u3e grit blasted mild steel \u3e aluminium alloy 2024T3 \u3e mild steel \u3e glass \u3e aluminium \u3e stainless steel alloy 304 \u3e PP. Differences in the extent of acid sorption were accounted for in terms of two effects: surface acidity/basicity and surface area (roughness). The decrease in MSA concentration following lap shear immersion in an MSA solution was related to the reactivity of the substrates for catalysing bond line polymerisations as described in a recently reported confocal Raman spectroscopic study of ECA /substrate reactivity

Rapid Contingency Simulation Modeling of the NASA Crew Launch Vehicle

The NASA Crew Launch Vehicle is a two-stage orbital launcher designed to meet NASA's current as well as future needs for human space flight. In order to free the designers to explore more possibilities during the design phase, a need exists for the ability to quickly perform simulation on both the baseline vehicle as well as the vehicle after proposed changes due to mission planning, vehicle configuration and avionics changes, proposed new guidance and control algorithms, and any other contingencies the designers may wish to consider. Further, after the vehicle is designed and built, the need will remain for such analysis in the event of future mission planning. An easily reconfigurable, modular, nonlinear six-degree-of-freedom simulation matching NASA Marshall's in-house high-fidelity simulator is created with the ability to quickly perform simulation and analysis of the Crew Launch Vehicle throughout the entire launch profile. Simulation results are presented and discussed, and an example comparison fly-off between two candidate controllers is presented

Embedded Relative Navigation Sensor Fusion Algorithms for Autonomous Rendezvous and Docking Missions

bd Systems (a subsidiary of SAIC) has developed a suite of embedded relative navigation sensor fusion algorithms to enable NASA autonomous rendezvous and docking (AR&D) missions. Translational and rotational Extended Kalman Filters (EKFs) were developed for integrating measurements based on the vehicles' orbital mechanics and high-fidelity sensor error models and provide a solution with increased accuracy and robustness relative to any single relative navigation sensor. The filters were tested tinough stand-alone covariance analysis, closed-loop testing with a high-fidelity multi-body orbital simulation, and hardware-in-the-loop (HWIL) testing in the Marshall Space Flight Center (MSFC) Flight Robotics Laboratory (FRL)

Real-Time Simulation of Ares I Launch Vehicle

The Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) has been developed for use by the Ares I launch vehicle System Integration Laboratory (SIL) at the Marshall Space Flight Center (MSFC). The primary purpose of the Ares SIL is to test the vehicle avionics hardware and software in a hardware-in-the-loop (HWIL) environment to certify that the integrated system is prepared for flight. ARTEMIS has been designed to be the real-time software backbone to stimulate all required Ares components through high-fidelity simulation. ARTEMIS has been designed to take full advantage of the advances in underlying computational power now available to support HWIL testing. A modular real-time design relying on a fully distributed computing architecture has been achieved. Two fundamental requirements drove ARTEMIS to pursue the use of high-fidelity simulation models in a real-time environment. First, ARTEMIS must be used to test a man-rated integrated avionics hardware and software system, thus requiring a wide variety of nominal and off-nominal simulation capabilities to certify system robustness. The second driving requirement - derived from a nationwide review of current state-of-the-art HWIL facilities - was that preserving digital model fidelity significantly reduced overall vehicle lifecycle cost by reducing testing time for certification runs and increasing flight tempo through an expanded operational envelope. These two driving requirements necessitated the use of high-fidelity models throughout the ARTEMIS simulation. The nature of the Ares mission profile imposed a variety of additional requirements on the ARTEMIS simulation. The Ares I vehicle is composed of multiple elements, including the First Stage Solid Rocket Booster (SRB), the Upper Stage powered by the J- 2X engine, the Orion Crew Exploration Vehicle (CEV) which houses the crew, the Launch Abort System (LAS), and various secondary elements that separate from the vehicle. At launch, the integrated vehicle stack is composed of these stages, and throughout the mission, various elements separate from the integrated stack and tumble back towards the earth. ARTEMIS must be capable of simulating the integrated stack through the flight as well as propagating each individual element after separation. In addition, abort sequences can lead to other unique configurations of the integrated stack as the timing and sequence of the stage separations are altered

Impact of spectral effects on the electrical parameters of multijunction amorphous silicon cells

The influence of spectral variation on the efficiency of single-, double- and triple-junction amorphous silicon cells has been investigated. The average photon energy (APE) proves to be a useful device-independent environmental parameter for quantifying the average hue of incident spectra. Single-junction devices increase in efficiency as light becomes blue shifted, because more of the incident spectrum lies within the absorption window and less in the redlinfra-red tail; this is denoted the primary spectral effect. Double- and triple-junction devices also exhibit a secondary spectral effect due to mismatch between the device structure and the incident spectrum. These both reach a maximum efficiency, which drops off as light is red or blue shifted. The effect is more pronounced for triple-junction than double-junction devices, as mismatch between junctions is statistically more likely

Real-Time Hardware-in-the-Loop Simulation of Ares I Launch Vehicle

The Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) has been developed for use by the Ares I launch vehicle System Integration Laboratory at the Marshall Space Flight Center. The primary purpose of the Ares System Integration Laboratory is to test the vehicle avionics hardware and software in a hardware - in-the-loop environment to certify that the integrated system is prepared for flight. ARTEMIS has been designed to be the real-time simulation backbone to stimulate all required Ares components for verification testing. ARTE_VIIS provides high -fidelity dynamics, actuator, and sensor models to simulate an accurate flight trajectory in order to ensure realistic test conditions. ARTEMIS has been designed to take advantage of the advances in underlying computational power now available to support hardware-in-the-loop testing to achieve real-time simulation with unprecedented model fidelity. A modular realtime design relying on a fully distributed computing architecture has been implemented

Effects of Image Quantity and Image Source Variation on Machine Learning Histology Differential Diagnosis Models

Aims: Histology, the microscopic study of normal tissues, is a crucial element of most medical curricula. Learning tools focused on histology are very important to learners who seek diagnostic competency within this important diagnostic arena. Recent developments in machine learning (ML) suggest that certain ML tools may be able to benefit this histology learning platform. Here, we aim to explore how one such tool based on a convolutional neural network, can be used to build a generalizable multi-classification model capable of classifying microscopic images of human tissue samples with the ultimate goal of providing a differential diagnosis (a list of look-alikes) for each entity. Methods: We obtained three institutional training datasets and one generalizability test dataset, each containing images of histologic tissues in 38 categories. Models were trained on data from single institutions, low quantity combinations of multiple institutions, and high quantity combinations of multiple institutions. Models were tested against withheld validation data, external institutional data, and generalizability test images obtained from Google image search. Performance was measured with macro and micro accuracy, sensitivity, specificity, and f1-score. Results: In this study, we were able to show that such a model\u27s generalizability is dependent on both the training data source variety and the total number of training images used. Models which were trained on 760 images from only a single institution performed well on withheld internal data but poorly on external data (lower generalizability). Increasing data source diversity improved generalizability, even when decreasing data quantity: models trained on 684 images, but from three sources improved generalization accuracy between 4.05% and 18.59%. Maintaining this diversity and increasing the quantity of training images to 2280 further improved generalization accuracy between 16.51% and 32.79%. Conclusions: This pilot study highlights the significance of data diversity within such studies. As expected, optimal models are those that incorporate both diversity and quantity into their platforms

Intelligence within BAOR and NATO's Northern Army Group

During the Cold War the UK's principal military role was its commitment to the North Atlantic Treaty Organisation (NATO) through the British Army of the Rhine (BAOR), together with wartime command of NATO's Northern Army Group. The possibility of a surprise attack by the numerically superior Warsaw Pact forces ensured that great importance was attached to intelligence, warning and rapid mobilisation. As yet we know very little about the intelligence dimension of BAOR and its interface with NATO allies. This article attempts to address these neglected issues, ending with the impact of the 1973 Yom Kippur War upon NATO thinking about warning and surprise in the mid-1970s. It concludes that the arrangements made by Whitehall for support to BAOR from national assets during crisis or transition to war were - at best - improbable. Accordingly, over the years, BAOR developed its own unique assets in the realm of both intelligence collection and special operations in order to prepare for the possible outbreak of conflict