Ultrasonic Phased Array Simulations of Welded Components at NASA

Comprehensive and accurate inspections of welded components have become of increasing importance as NASA develops new hardware such as Ares rocket segments for future exploration missions. Simulation and modeling will play an increasing role in the future for nondestructive evaluation in order to better understand the physics of the inspection process, to prove or disprove the feasibility for an inspection method or inspection scenario, for inspection optimization, for better understanding of experimental results, and for assessment of probability of detection. This study presents simulation and experimental results for an ultrasonic phased array inspection of a critical welded structure important for NASA future exploration vehicles. Keywords: nondestructive evaluation, computational simulation, ultrasonics, weld, modeling, phased arra

Ultrasonic Phased Array Inspection Simulations of Welded Components at NASA

Comprehensive and accurate inspections of welded components have become of increasing importance as NASA develops new hardware such as Ares rocket segments for future exploration missions. Simulation and modeling will play an increased role in the future for nondestructive evaluation in order to better understand the physics of the inspection process and help explain the experimental results. It will also help to prove or disprove the feasibility for an inspection method or inspection scenario, help optimize inspections, and allow to a first approximation limits of detectability. This study presents simulation and experimental results for an ultrasonic phased array inspection of a critical welded structure important for NASA future exploration vehicles

Recursive least squares background prediction of univariate syndromic surveillance data

<p>Abstract</p> <p>Background</p> <p>Surveillance of univariate syndromic data as a means of potential indicator of developing public health conditions has been used extensively. This paper aims to improve the performance of detecting outbreaks by using a background forecasting algorithm based on the adaptive recursive least squares method combined with a novel treatment of the Day of the Week effect.</p> <p>Methods</p> <p>Previous work by the first author has suggested that univariate recursive least squares analysis of syndromic data can be used to characterize the background upon which a prediction and detection component of a biosurvellance system may be built. An adaptive implementation is used to deal with data non-stationarity. In this paper we develop and implement the RLS method for background estimation of univariate data. The distinctly dissimilar distribution of data for different days of the week, however, can affect filter implementations adversely, and so a novel procedure based on linear transformations of the sorted values of the daily counts is introduced. Seven-days ahead daily predicted counts are used as background estimates. A signal injection procedure is used to examine the integrated algorithm's ability to detect synthetic anomalies in real syndromic time series. We compare the method to a baseline CDC forecasting algorithm known as the W2 method.</p> <p>Results</p> <p>We present detection results in the form of Receiver Operating Characteristic curve values for four different injected signal to noise ratios using 16 sets of syndromic data. We find improvements in the false alarm probabilities when compared to the baseline W2 background forecasts.</p> <p>Conclusion</p> <p>The current paper introduces a prediction approach for city-level biosurveillance data streams such as time series of outpatient clinic visits and sales of over-the-counter remedies. This approach uses RLS filters modified by a correction for the weekly patterns often seen in these data series, and a threshold detection algorithm from the residuals of the RLS forecasts. We compare the detection performance of this algorithm to the W2 method recently implemented at CDC. The modified RLS method gives consistently better sensitivity at multiple background alert rates, and we recommend that it should be considered for routine application in bio-surveillance systems.</p

Ultrasonic Phased Array Inspection for an Isogrid Structural Element with Cracks

In this investigation, a T-shaped aluminum alloy isogrid stiffener element used in aerospace applications was inspected with ultrasonic phased array methods. The isogrid stiffener element had various crack configurations emanating from bolt holes. Computational simulation methods were used to mimic the experiments in order to help understand experimental results. The results of this study indicate that it is at least partly feasible to interrogate this type of geometry with the given flaw configurations using phased array ultrasonics. The simulation methods were critical in helping explain the experimental results and, with some limitation, can be used to predict inspection results

Evaluating visible derivative spectroscopy by varimax-rotated, principal component analysis of aerial hyperspectral images from the western basin of Lake Erie

The Kent State University (KSU) spectral decomposition method provides information about the spectral signals present in multispectral and hyperspectral images. Pre-processing steps that enhance signal to noise ratio (SNR) by 7.37–19.04 times, enables extraction of the environmental signals captured by the National Aeronautics and Space Administration (NASA) Glenn Research Center\u27s, second generation, Hyperspectral imager (HSI2) into multiple, independent components. We have accomplished this by pre-processing of Level 1 HSI2 data to remove stripes from the scene, followed by a combination of spectral and spatial smoothing to further increase the SNR and remove non-Lambertian features, such as waves. On average, the residual stochastic noise removed from the HSI2 images by this method is 5.43 ± 1.42%. The method also enables removal of a spectrally coherent residual atmospheric bias of 4.28 ± 0.48%, ascribed to incomplete atmospheric correction. The total noise isolated from signal by the method is thu

Targeting Human Central Nervous System Protein Kinases: An Isoform Selective p38αMAPK Inhibitor that Attenuates Disease Progression in Alzheimer\u27s Disease Mouse Models

The first kinase inhibitor drug approval in 2001 initiated a remarkable decade of tyrosine kinase inhibitor drugs for oncology indications, but a void exists for serine/threonine protein kinase inhibitor drugs and central nervous system indications. Stress kinases are of special interest in neurological and neuropsychiatric disorders due to their involvement in synaptic dysfunction and complex disease susceptibility. Clinical and preclinical evidence implicates the stress related kinase p38αMAPK as a potential neurotherapeutic target, but isoform selective p38αMAPK inhibitor candidates are lacking and the mixed kinase inhibitor drugs that are promising in peripheral tissue disease indications have limitations for neurologic indications. Therefore, pursuit of the neurotherapeutic hypothesis requires kinase isoform selective inhibitors with appropriate neuropharmacology features. Synaptic dysfunction disorders offer a potential for enhanced pharmacological efficacy due to stress-induced activation of p38αMAPK in both neurons and glia, the interacting cellular components of the synaptic pathophysiological axis, to be modulated. We report a novel isoform selective p38αMAPK inhibitor, MW01-18-150SRM (=MW150), that is efficacious in suppression of hippocampal-dependent associative and spatial memory deficits in two distinct synaptic dysfunction mouse models. A synthetic scheme for biocompatible product and positive outcomes from pharmacological screens are presented. The high-resolution crystallographic structure of the p38αMAPK/MW150 complex documents active site binding, reveals a potential low energy conformation of the bound inhibitor, and suggests a structural explanation for MW150\u27s exquisite target selectivity. As far as we are aware, MW150 is without precedent as an isoform selective p38MAPK inhibitor or as a kinase inhibitor capable of modulating in vivo stress related behavior