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NASA NTRS1985

Fracture analysis of radial scientific instrument module registration fittings of the space telescope

The space telescope contains various scientific instrument (SI) modules which are mounted to the Focal Plane Structure (FPS) in a statically determinate manner. This is accomplished by using three registration fittings per SI module, one resisting three translations, another resisting two and the third resisting only one. Due to thermal insulating requirements these fittings are complex devices composed of numerous pieces. The structural integrity of these fittings is of great importance to the safety of the orbiter transporting the telescope, so in addition to the stress analyses performed during the design of these components, fracture susceptibility also needs to be considered. The pieces of the registration fittings for the Radial SI Module containing the Wide Field Planetary Camera are examined to determine which would endanger the orbiter if they fractured and what is the likelihood of their fracture. The latter is stated in terms of maximum allowable initial flaw sizes in these pieces.

Springfield, C. W., Jr.↗

NASA NTRS2022

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) series, have been observing severe convection at 15–60-minute intervals for over 40 years. When properly assessed, such a data record can be valuable in efforts of estimating severe storm risk throughout the diurnal cycle based on automated detection of patterns consistently found atop severe storms. Furthermore, environmental conditions favorable for severe weather are well-known and are thought to be represented well by modern reanalysis products. Promoting resilience against such hazards on local and global scales is a chief goal the NASA Disasters program, which seeks to encourage use of satellite observations to mitigate risk. For instance, hail is the costliest severe weather hazard across the globe in terms of insured loss, but reporting inconsistencies for hail events globally make it difficult to develop models that can quantify the risk. Satellite observation and model reanalysis taken together have the potential to, with reasonable skill and specificity, characterize environmental conditions that are favorable for hazardous weather, and thereby enable creation of hazard climatologie. Such climatologies are particularly useful over regions without extensive radar networks or storm reporting. By mapping the multivariate combination of observed cloud features and reanalysis environmental parameters/indices to United States Next Generation Weather Radar (NEXRAD) radar-estimated Maximum Expected Size of Hail (MESH) by way of a deep neural network (DNN), estimates of likelihood for potentially severe hail can be produced. Such estimates are of greater complexity and efficiency than could be performed with previous multivariate or logistic regression analyses for observed points within convective systems. Statistical distributions of convective parameters from satellite and reanalysis are shown to highlight non-severe/severe class separation for well-known hailstorm predictors, e.g., overshooting cloud top characteristics, deep-layer wind shear, mid-level stability, helicity, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN, which can efficiently produce a quantitative hail risk metric with better than 70% detection rate and under 30% false alarms. These hail classifications can then be aggregated across the satellite record to yield a hazard climatology for hail frequency and severity – knowledge of which is of particular interest to those who manage risk (e.g., insurers) and are seeking opportunities to identify hail-prone regions, particularly in developing nations. This NASA study uses satellite observations and model parameters in a DNN to perform climatological hailstorm analysis in support of catastrophe model development, with the hope of promoting risk resilience particularly in regions without adequate weather radar coverage.

Passive Remote Sensing↗

NASA NTRSDate not supplied

Toward The Development of Hailstorm Climatologies Derived From Reanalyses and Infared/Passive Microwave Satellite Imagers

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) and Meteosat series, provide both historical and near-real-time observations of cloud top patterns that are commonly associated with severe convection. Environmental conditions favorable for severe weather are thought to be represented well by reanalyses. Predicting exactly where convection and costly storm hazards like hail will occur using models or satellite imagery alone, however, is extremely challenging. The multivariate combination of satellite-observed cloud patterns with reanalysis environmental parameters, linked to United States Next Generation Weather Radar- (NEXRAD-) estimated Maximum Expected Size of Hail (MESH) using a deep neural network (DNN), enables estimation of potentially severe hail likelihood for any observed storm cell. These estimates are specifically designed to make hail likelihood distinctions based on satellite-indicated points of deep convection within environments favorable for storm development. We seek an approach that can be used to estimate climatological hailstorm frequency and risk throughout the historical satellite data record. This presentation demonstrates that statistical distributions of convective parameters from satellite and reanalysis show separation between non-severe/severe hailstorm classes for predictors including overshooting cloud top temperature and area characteristics, convective available potential energy, vertical wind shear, 500 hPa temperature, mid-level lapse rate, precipitable water, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN to produce a hail likelihood metric with a critical success index of 0.504 and Heidke skill score of 0.403, which is exceptional among recent analogous hail studies. Furthermore, applications of the DNN to select case studies demonstrate good qualitative agreement between hail likelihood and MESH. These hail classifications are aggregated across an 11-year GOES-12/13 image database to derive a hail frequency and severity climatology, which denotes the Central Plains, the Midwest, and northwestern Mexico as being the most hail-prone regions within the domain studied. Opportunities for training and applying DNN-based hailstorm predictions to recently developed GOES-8/10/12/13/16 and Meteosat Second Generation convective storm detection and characterization climatologies over South America and South Africa, respectively, will also be presented.

Kristopher Bedka↗

NASA NTRS1982

Total ozone-solar activity relationship

Approximately six years of global ozone monthly mean data from the Nimbus 4 BUV instrument are compared with monthly values of solar activity using 10.7-cm flux, F(10.7), as a parameter. Several techniques are explored in calculating the correlation between the two data sets, and all are found to yield relatively high correlations, ranging from R = 0.68 for 'raw' monthly means to 0.94 using a six-month running mean for each data set. It is shown, however, that the bulk of the correlation derives from the long-term decreasing trends in both data sets. When the long-term trends are removed, a cross-correlation analysis produces a maximum with no phase shift or with the ozone variations leading the solar variations by one month, thereby reducing the likelihood of a cause and effect relationship on time scales of this order. In view of the current uncertainty in the long-term stability of the BUV instrument and the resulting uncertainty in any long-term trend derived from its data, it is considered unrealistic to draw firm conclusions about a solar cycle influence on total ozone from this satellite data set.

Reber, C. A.↗

NASA NTRS2021

A Study of the Swelling and Bursting of the High Pressure Coupling (HPC) of a Two-Stage Light Gas Gun

A consistent picture of the swelling and bursting of the high pressure couplings (HPC) of two NASA Ames two-stage light gas guns is developed. The following information is used to construct the model. 1. Experimental measurements of the swelling and bursting of the HPCs of two two-stage light gas guns. 2. Stress-strain calculations of the swelling and bursting of thick walled steel tubes. 3. Experimental measurements swelling and bursting of thick walled steel tubes. 4. CFD calculations of the maximum pressures in the HPC of a two-stage light gas gun using the code LGGUN 5. Correlation of maximum HPC pressures and piston energies It is suggested that the techniques described herein could be used to assess the likelihood of swelling and bursting of the HPCs of various different two stage light gas guns.

David W Bogdanoff↗

NASA NTRS2015

Suzaku Observation of the Classical Nova V2491 Cyg in Quiescence

We present Suzaku XIS observation of V2491 Cyg (Nova Cyg 2008 No. 2) obtained in quiescence, more than two years after the outburst. The nova was detected as a very luminous source in a wide spectral range from soft to hard X-rays. A very soft blackbody-like component peaking at 0.5 keV indicates that either we observe remaining, localized hydrogen burning on the surface of the white dwarf, or accretion onto a magnetized polar cap. In the second case, V2491 Cyg is a candidate "soft intermediate polar". We obtained the best fit for the X-ray spectra with several components: two of thermal plasma, a blackbody and a complex absorber. The later is typical of intermediate polars. The X-ray light-curve shows a modulation with an approximately 38 min period. The amplitude of this modulation is strongly energy dependent and reaches maximum in the 0.8-2.0 keV range. We discuss the origin of the X-ray emission and pulsations, and the likelihood of the intermediate polar scenario.

cataclysmic variables: general aEuro" nova: indivi↗

NASA NTRSDate not supplied

Predicting Maximum Temperatures of a Li-ion Battery on a Simulated Flight Profile using a Model-based Prognostics

One of the challenges in using Li-ion packs in aeronautics is their safety, and thermal runaway (TR) is a major concern. The current engineering solutions to prevent a Li-ion pack from a catastrophic TR require additional mass and volume to isolate cells. The excess mass could be reduced by improving detection and, thus, preventing a TR event. One of the possible early warning indicators of a TR is crossing a threshold temperature. We have developed an approach, based on the Unscented Kalman Filter (UKF), to predict the likelihood of reaching the threshold temperature for simulated flight profiles. The current battery prognostics algorithms for aerospace predict state-of-charge (SOC) and end-of-life (EOL) [1]. We extended this two-level algorithm to predict the maximum temperature during discharge. The amount of heat generated in a cell depends on factors such as cell chemistry, cell packaging, total cycles, operating temperature, and abuse history [2]. Our semi-empirical thermal model depends on three phenomenological parameters which account for those factors. In addition, a two-parameter reduced-order model is developed to predict the temperature rise for short bursts of “random-walk” (RW) discharge current sequence, which simulates a flight's current-loading profile. The performance of these models on different datasets and types of current loading will be presented. To predict the maximal temperatures for future cycles we must estimate the evolution of thermal parameters as the batteries age. It is found that the parameters of the 3-parametric thermal model cannot be estimated only from the RW data. To address the issue, we will present two alternative approaches: i) expanding the datasets to include discharge profiles beyond RWs; ii) model reduction to a two-parametric model. The two approaches will be illustrated by an application to the cycling data from a commercial LG 18650 cell. References: 1. M. Daigle, C.S. Kulkarni, End-of-discharge and End-of-life Prediction in Lithium-ion Batteries with Electrochemistry-based Aging Models, in: AIAA Infotech @ Aerospace, American Institute of Aeronautics and Astronautics, San Diego, California, USA, 2016. 2. M. Börner, et. al, Correlation of aging and thermal stability of commercial 18650-type lithium ion batteries, Journal of Power Sources. 342 (2017) 382–392.

Thermal runaway↗

NASA NTRS1988

The Kara and Ust-Kara impact structures (USSR) and their relevance to the K/T boundary event

The Kara and Ust-Kara craters are twin impact structures situated at about 69 deg 10 min N; 65 deg 00 min E at the Kara Sea. For Kara a diameter of about 55 km would be a very conservative estimate, and field observations indicate a maximum current diameter of about 60 km. The diameter of Ust-Kara has to be larger than 16 km. A better estimate might be 25 km but in all likelihood it is even larger. Suevites and impactites from the Kara area have been known since the beginning of the century, but had been misidentified as glacial deposits. Only about 15 years ago the impact origin of the two structures was demonstrated, following the recognition of shock metamorphism in the area. The composition of the target rocks is mirrored by the composition of the clasts within the suevites. In the southern part of Kara, Permian shales and limestones are sometimes accompanied by diabasic dykes, similar to in the central uplift. Due to the high degree of shock metamorphism the shocked magmatic rocks are not easily identified, although most of them seem to be of diabasic or dioritic composition. The impact melts (tagamites) are grey to dark grey fine grained crystallized rocks showing very fine mineral components and are the product of shock-melting with later recrystallization. The impact glasses show a layered structure, inclusions, and vesicles, and have colors ranging from translucent white over brown and grey to black. A complete geochemical characterization of the Kara and Ust-Kara impact craters was attempted by analyzing more than 40 samples of target rocks, shocked rocks, suevites, impact melts, and impact glasses for major and trace elements.

Koeberl, Christian↗

NASA NTRS1997

Maximum a posteriori decoder for digital communications

A system and method for decoding by identification of the most likely phase coded signal corresponding to received data. The present invention has particular application to communication with signals that experience spurious random phase perturbations. The generalized estimator-correlator uses a maximum a posteriori (MAP) estimator to generate phase estimates for correlation with incoming data samples and for correlation with mean phases indicative of unique hypothesized signals. The result is a MAP likelihood statistic for each hypothesized transmission, wherein the highest value statistic identifies the transmitted signal.

Altes, Richard A.↗

NASA NTRSDate not supplied

A Study of the Swelling and Bursting of the High Pressure Coupling (HPC) of a Two-Stage Light Gas Gun

A consistent picture of the swelling and bursting of the high pressure couplings (HPC) of two NASA Ames two-stage light gas guns is developed. The following information is used to construct the model. 1. Experimental measurements of the swelling and bursting of the HPCs of two two-stage light gas guns. 2. Stress-strain calculations of the swelling and bursting of thick walled steel tubes. 3. Experimental measurements swelling and bursting of thick walled steel tubes. 4. CFD calculations of the maximum pressures in the HPC of a two-stage light gas gun using the code LGGUN It is suggested that the techniques described herein could be used to assess the likelihood of swelling and bursting of the HPCs of various different two stage light gas guns.

David W Bogdanoff↗

NASA NTRS2023

A Confidence-Based Approach to Including Survivors in a Probabilistic TID Failure Assessment

A probabilistic total ionizing dose (TID) failure assessment is extended to include survivor data, enabling the bounding of failure probability to a desired confidence level (CL) without failure data. The extension provides an avenue for analyzing microelectronics tested for TID without reaching a failure mode, a scenario often encountered by missions utilizing commercial-off-the-shelf (COTS) technologies. Using the type-I censored likelihood formulation and a realistic upper bound on expected device performance, the failure probability space is bounded by confidence contours within the context of a variable environment. The framework accommodates any type of distribution assumed for the part failure or the environment under consideration. Furthermore, the framework can be utilized pre-emptively to plan future device TID tests, minimizing costs while meeting survival requirements. Heritage data may also be used as survivors to further minimize testing costs when parts are from the same lot, but the amount of constraint derived from heritage is limited. Altogether, the framework enables a formal, mathematically rigorous analysis of radiation tolerant devices tested to a maximum dose, as well as flight heritage, in a hardness assurance methodology.

confidence↗

NASA NTRS2014

Application and Evaluation of Control Modes for Risk-Based Engine Performance Enhancements

The engine control system for civil transport aircraft imposes operational limits on the propulsion system to ensure compliance with safety standards. However, during certain emergency situations, aircraft survivability may benefit from engine performance beyond its normal limits despite the increased risk of failure. Accordingly, control modes were developed to improve the maximum thrust output and responsiveness of a generic high-bypass turbofan engine. The algorithms were designed such that the enhanced performance would always constitute an elevation in failure risk to a consistent predefined likelihood. This paper presents an application of these risk-based control modes to a combined engine/aircraft model. Through computer and piloted simulation tests, the aim is to present a notional implementation of these modes, evaluate their effects on a generic airframe, and demonstrate their usefulness during emergency flight situations. Results show that minimal control effort is required to compensate for the changes in flight dynamics due to control mode activation. The benefits gained from enhanced engine performance for various runway incursion scenarios are investigated. Finally, the control modes are shown to protect against potential instabilities during propulsion-only flight where all aircraft control surfaces are inoperable.

emergency operation↗

NASA NTRS2013

Probabilistic Modeling of the Renal Stone Formation Module

The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.

kidney stones↗

NASA NTRS2014

Application and Evaluation of Control Modes for Risk-Based Engine Performance Enhancements

aircraft engine performance↗

NASA NTRS2015

Application and Evaluation of Control Modes for Risk-Based Engine Performance Enhancements

emergency operation↗

NASA NTRS1990

Location of a faulty module in a computing system

Considering the interplay between different phases of fault tolerance, a new problem of locating a faulty module in a computing system is formulated and solved. First, the probability of each module being faulty, or faulty probability, is calculated using the likelihood principle from the model parameters for fault detection, diagnostics, error propagation, and error detection. Then, based on the faulty probabilities and a given required diagnostic coverage, the order in which modules are to be diagnosed and the maximum time allotted to diagnose each module are determined by minimizing the average total diagnostic time. An example is presented and analyzed to answer the question of whether or not a system should delay the diagnosis upon detection of an error until more errors are detected.

Lin, Tein-Hsiang↗

NASA NTRS2017

Analysis of San Francisco Bar Pilot Dispatch Records: Preliminary Report

Maritime pilots licensed by the San Francisco Board of Pilot Commissioners perform safety-critical tasks in a demanding environment, working in all weather and at all times of day and night. Since 1850, San Francisco maritime pilots have been known as Bar Pilots because their duties include guiding ships safely across the large sand bar that lies west of the Golden Gate. Schedules and Work Hours Records for San Francisco Bay Bar Pilots were analyzed to determine the minimum and maximum work periods, the frequency of extended work hours, the frequency of night work and the rotation of work hours. A mathematical model is being applied to predict fatigue in order to identify schedules that may have a high likelihood of fatigue. This presentation provides a progress report on the research thus far.

marine pilots↗

NASA NTRS1988

A catalog of small, optically selected molecular clouds - Optical, infrared, and millimeter properties

A catalog of small, optically selected molecular clouds is presented. The relevant selection criteria were small angular size, large central opacity, and freedom from connecting opaque material. The mean ellipticity of the clouds in the catalog is 2.0, with a maximum ellipticity of 7. The position angle of the clouds is uncorrelated with the direction of the Galactic plane. About 60 percent of the cataloged clouds have associated IRAS Point Source Catalog (PSC) sources in their cores or envelopes. The likelihood of a detection of a PSC source is some 6.1 times higher for the core regions of the clouds than for the envelopes, indicating a strong association of FIR sources and Bok globules. Of a sample of 97 of the clouds observed in the J = 2-1 line of (C-12)O, 70 percent have cold gas kinetic temperatures and approximately sonic line widths. The remaining 30 percent are about equally divided between those clouds likely to be radiatively heated by nearby stars and those undergoing active protostellar collapse or outflows with no bulk gas heating.

Clemens, Dan P.↗