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NASA NTRS2002

Cross-Cultural Perspectives of Service Quality and Risk in Air Transportation

This study compares US and Korean customers in terms of their perceptions of airline service quality based on SERVPERF and industry-based measures, as well as their perceptions of risks involved in the airline choice. SERVPERF is a set of multi-dimensional measures of customer evaluations of service quality. The results indicate that: (1) US passengers are generally more satisfied with their airline service than Korean customers on most of the SERVPERF dimensions; (2) Koreans are generally more satisfied with the bumping procedures whereas US participants feel more satisfied with the airline's baggage handling, operations/safety, and connections; and (3) US participants perceive higher levels of performance and financial risks whereas Koreans feel greater social risk in choosing an airline. This study also examines the SERVPERF, industry-based measure, and perceived risk in predicting customer satisfaction with, and intention to repatronize the airline. The results suggest that US customers consider service reliability, in-flight comfort, and connections as the key factors determining satisfaction with airline service whereas Korean passengers generally regard reliability, assurance, and risk factors as predictors of satisfaction. The determining factors of customer intention to repatronize the airline are reliability and empathy for US, and reliability and overall risk for Korean customers. The study demonstrates the applicability of SERVPERF as a cross-cultural tool and indicates the importance of perceived risk in cross-cultural studies.

Cunningham, Lawrence F.↗

NASA NTRS2016

Preliminary Results From a Heavily Instrumented Engine Ice Crystal Icing Test in a Ground Based Altitude Test Facility

Preliminary results from the heavily instrumented ALF502R-5 engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory are discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This same model engine, serial number LF01, was used during the inaugural icing test in the Propulsion Systems Laboratory facility. The uncommanded reduction of thrust (rollback) events experienced by this engine in flight were simulated in the facility. Limited instrumentation was used to detect icing on the LF01 engine. Metal temperatures on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect/characterize ice accretion, and visualize the ice accretion in the region of interest. Data were acquired at key LF01 test points and additional points that explored: icing threshold regions, low altitude, high altitude, spinner heat effects, and the influence of varying the facility and engine parameters. For each condition of interest, data were obtained from some selected variations of ice particle median volumetric diameter, total water content, fan speed, and ambient temperature. For several cases the NASA in-house engine icing risk assessment code was used to find conditions that would lead to a rollback event. This study further helped NASA develop necessary icing diagnostic instrumentation, expand the capabilities of the Propulsion Systems Laboratory, and generate a dataset that will be used to develop and validate in-house icing prediction and risk mitigation computational tools. The ice accretion on the outer shroud region was acquired by internal video cameras. The heavily instrumented engine showed good repeatability of icing responses when compared to the key LF01 test points and during day-to-day operation. Other noticeable observations are presented.

Enigine Icing↗

NASA NTRS2016

Preliminary Results From a Heavily Instrumented Engine Ice Crystal Icing Test in a Ground Based Altitude Test Facility

Preliminary results from the heavily instrumented ALF502R-5 engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory are discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This same model engine, serial number LF01, was used during the inaugural icing test in the Propulsion Systems Laboratory facility. The uncommanded reduction of thrust (rollback) events experienced by this engine in flight were simulated in the facility. Limited instrumentation was used to detect icing on the LF01 engine. Metal temperatures on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect/ characterize ice accretion, and visualize the ice accretion in the region of interest. Data were acquired at key LF01 test points and additional points that explored: icing threshold regions, low altitude, high altitude, spinner heat effects, and the influence of varying the facility and engine parameters. For each condition of interest, data were obtained from some selected variations of ice particle median volumetric diameter, total water content, fan speed, and ambient temperature. For several cases the NASA in-house engine icing risk assessment code was used to find conditions that would lead to a rollback event. This study further helped NASA develop necessary icing diagnostic instrumentation, expand the capabilities of the Propulsion Systems Laboratory, and generate a dataset that will be used to develop and validate in-house icing prediction and risk mitigation computational tools. The ice accretion on the outer shroud region was acquired by internal video cameras. The heavily instrumented engine showed good repeatability of icing responses when compared to the key LF01 test points and during day-to-day operation. Other noticeable observations are presented.

turbomachinery↗

NASA NTRSDate not supplied

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to three combined HZE-irradiated mouse datasets

Radiation health risks are predominantly derived from low linear energy transfer (LET) terrestrial exposures; however, space radiation includes exposure to high-LET and high-charge, high-energy (HZE) particles. Accurately quantifying the differences in radiation quality between the space and terrestrial radiation environments is important for assessing and predicting health risks for astronauts. Weil et al. 2009 and 2014 used two different inbred mouse strains to study differences in hepatocellular carcinoma (HCC) tumorigenesis after exposures to low- and high- LET radiation. More recently, Edmundson et al. 2020 provided valuable new tumor data in outbred mice that were exposed to low- and high-LET radiation. The present study aims to rigorously investigate a relative biological effectiveness (RBE) factor by leveraging the HCC tumor data from Weil et al. 2009, Weil et al. 2014, and Edmundson et al. 2020. The three experiments were similarly designed, allowing the raw data to be combined into a pooled dataset to estimate excess relative risk (ERR) and excess absolute risk (EAR) models using Bayesian Poisson regression. These effect estimates from the pooled data provide greater power to calculate a data driven RBE. Extensive sensitivity analyses test the robustness of RBE estimates to various model assumptions. The following questions will be explored through the sensitivity analyses: • Is the shape of the dose response different for low-LET radiation and HZE radiation, indicating that RBE is a function of dose? • Does attained age modify the effect estimates differently for low-LET radiation and HZE radiation, indicating RBE is a function of attained age? • Are the effect estimates and RBE estimates different for inbred mouse strains and outbred mouse strains? • Do assumptions about differences in ERR models and EAR models change the estimated RBE? Additional studies would be needed to validate the findings from these exploratory analyses.

Lori J. Chappell↗

NASA NTRSDate not supplied

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to three combined HZE-irradiated mouse datasets

Lori J. Chappell↗

NASA NTRSDate not supplied

Overview of the NASA Earth Action Strategies Wildland Fire Initiative

As part of NASA’s new Earth Action strategy, the Wildland Fire initiative was established, which includes both the NASA Wildland Fire Program (WFP) and the FireSense project. NASA has over 50 years of experience generating data and technology to enhance fire science and operational management. The WFP’s mission is threefold: 1) assemble communities of practice through collaborative efforts with government, academia, and the private sector; 2) co-develop knowledge and applications with relevant partners and stakeholders in the wildfire community; and 3) improve wildland fire management through the transitioning of NASA data, technology, tools, and science to stakeholder organizations. The WFP is focusing on supporting proactive fire management, including situational awareness, preparedness, and risk mitigation. This will be accomplished through selected projects that identify management challenges, relevant to partners and end users, and the NASA data that will be utilized to deliver innovative solutions to enhance the management of wildland fires. Examples include: i) investigation of evaporative stress from OpenET to help predict the risk of wildfire occurrence in watersheds; ii) incorporation of space based LiDAR for the generation of 3-dimensional forest fuel metrics, used to improve wildfire risk and behavior models; iii) integration of global, multi-platform geostationary active-fire data in near-real-time into NASA’s Fire Information for Resource Management System (FIRMS); and iv) identification of post-fire ecohydrological conditions using thermal, multispectral, synthetic aperture radar (SAR), and hyperspectral remotely-sensed data to improve flood hazard forecast models. The FireSense project is a US-focused 5-year project that will focus on delivering NASA’s unique Earth science and technological capabilities to operational agencies, striving towards enhancing fire fighting and air quality management. The project will include airborne campaigns and new technology that will likely have global implications. Initial stakeholder engagement led FireSense to focus on four use-cases focused on the characterization and measurement of: (i) pre-fire fuels conditions, (ii) active fire-dynamics; (iii) post-fire impact and threats; and iv) air quality impacts and forecasting, each-developed with identified stakeholders.

Wildland Fire program↗

NASA NTRS2018

Variability in Galactic Cosmic Radiation- Induced DNA Damage Response in Inbred Mice Is Modulated by Genetics

In radiation biology, the ability to predict cancer risk associated with exposure to low doses of high-LET (Linear Energy Transfer) ionizing radiation remains a challenge. Epidemiological methods lack the sensitivity and power to provide detailed risk estimates for cancer and ignore individual sensitivity. We have hypothesized that DNA repair capacity is the primary factor differentiating peoples radiation sensitivity. We previously showed in immortalized human cell lines that characterizing the dose and time dependence of p53-binding protein 1 (53BP1) foci formation in the nucleus following X-rays exposure is sufficient to predict DNA repair response to any other LET in the same cell line. We now tested this hypothesis across a population of mice with different genetic background. Fibroblast cells were extracted and cultivated from 76 individual mice from 15 different strains and exposed to HZE (high (H) atomic number (Z) and energy (E) galactic cosmic ray particles) particles and X-rays. Individual radiation sensitivities were investigated by high throughput measurement of DNA repair kinetics that evaluated 53bp1 foci numbers as a surrogate for DNA double-strand breaks at various times post-irradiation. Instead of just counting foci which can be hard to distinguish for high-LET or high doses, we also took into account the track structure of high-LET particles to compute the remaining number of unrepaired tracks as a function of time post-irradiation. As expected, the percentage of unrepaired track over a 48 hours follow-up period increased with LET. In addition, repair rate was modulated by genetics, with animals from the same strain showing small variance while large rate differences were observed between strains. Radiation strain sensitivity ranking was estimated based on repair rates from exposure to each LET evaluated in this work, and ranking for high-LET correlated better with ranking from high dose of X-ray, not low dose. At the in-vivo level, drops in T-cells and B-cells number measured 24 hours after 0.1 Gy (Gray) X-ray exposure, correlated with slower DNA repair kinetic in fibroblast cells of the same strains of mice. At the genomic level, mouse genome wide association (GWA) analysis identified seven significant genetic loci on chromosomes 2, 3, 7, 10, 11, 13 and 19 with different significance depending on the LET. Interestingly, for the two highest LET, a common locus on Chromosome 10 was identified with high enrichment for DNA repair associated genes.Overall, this work suggests that repair kinetics of primary skin fibroblasts is a good surrogate marker for in-vivo radiation sensitivities in other tissues and that this response is modulated by genetics. Our study also confirms that DNA repair kinetics following high doses of X-ray can be used to predict radiation sensitivity to high-LET.

High-LET Radiation↗

NASA NTRS1993

Developing interpretable models with optimized set reduction for identifying high risk software components

Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault frequency components so that testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents the Optimized Set Reduction approach for constructing such models, intended to fulfill specific software engineering needs. Our approach to classification is to measure the software system and build multivariate stochastic models for predicting high risk system components. We present experimental results obtained by classifying Ada components into two classes: is or is not likely to generate faults during system and acceptance test. Also, we evaluate the accuracy of the model and the insights it provides into the error making process.

Briand, Lionel C.↗

NASA NTRS2016

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account system integration risks such as those attributable to manufacturing and assembly. These sources often dominate component level risk. While consequence of failure is often understood, using predicted values in a risk model to estimate the probability of occurrence may underestimate the actual risk. Managers and decision makers use the probability of occurrence to influence the determination whether to accept the risk or require a design modification. The actual risk threshold for acceptance may not be fully understood due to the absence of system level test data or operational data. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗

NASA NTRS2020

Great Basin Ecological Forecasting II: Assessing and Forecasting Live Fuel Moisture Content of Wildfire Fuels for the Eastern Great Basin to Improve Wildfire Timing and Severity Predictions

The eastern Great Basin (EGB) extends throughout the states of Arizona, Colorado,Idaho, Utah, and Wyoming, covering approximately 411,000 km2. In recent years, wildfires in the EGB have increased in frequency and size, representing a growing concern for our partners at the Bureau of Land Management (BLM), the National Weather Service (NWS), and the Great Basin Coordination Center (GBCC). Live fuel moisture (LFM) is an important factor in predicting wildfire risk, as dry vegetation requires less energy to combust than wet vegetation. Land managers currently derive LFM levels from just 165 in situ sites in the EGB. In order to provide partners with a more accurate assessment of LFM, the team used data from the National Elevation Dataset, Aqua and Terra Moderate Resolution Imaging Spectroradiometer, and Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite. These datasets include vegetation indices, evapotranspiration, and topographic variables, which were used to create biweekly forecasts of LFM throughout the EGB. An accuracy assessment was conducted using historical in situ data from our partners at the BLM and the GBCC. This model allowed our partners to make informed decisions regarding resource allocation in response to the predicted timing and severity of wildfires in the EGB.

Ecological Forecasting↗

NASA NTRS2020

Great Basin Ecological Forecasting II: Assessing and Forecasting Live Fuel Moisture Content of Wildfire Fuels for the Eastern Great Basin to Improve Wildfire Timing and Severity Predictions

The eastern Great Basin (EGB) extends throughout the states of Arizona, Colorado, Idaho, Utah, and Wyoming, covering approximately 411,000 sq.km. In recent years, wildfires in the EGB have increased in frequency and size, representing a growing concern for our partners at the Bureau of Land Management (BLM), the National Weather Service (NWS), and the Great Basin Coordination Center (GBCC). Live fuel moisture (LFM) is an important factor in predicting wildfire risk, as dry vegetation requires less energy to combust than wet vegetation. Land managers currently derive LFM levels from just 165 in situ sites in the EGB. In order to provide partners with a more accurate assessment of LFM, the team used data from the National Elevation Dataset, Aqua and Terra Moderate Resolution Imaging Spectroradiometer, and Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite. These datasets include vegetation indices, evapotranspiration, and topographic variables, which were used to create biweekly forecasts of LFM throughout the EGB. An accuracy assessment was conducted using historical in situ data from our partners at the BLM and the GBCC. This model allowed our partners to make informed decisions regarding resource allocation in response to the predicted timing and severity of wildfires in the EGB.

Ecological Forecasting↗

NASA NTRS2009

Biophysics Representation of the Two-Hit Model of Alzheimer's Disease for the Exploration of Late CNS Risks from Space Radiation

A concern for long-term space travel outside the Earth s magnetic field is the late effects to the central nervous system (CNS) from galactic cosmic ray (GCR) or solar particle events (SPE). Human epidemiology data is severely limited for making CNS risk estimates and it is not clear such effects occur following low LET exposures. We are developing systems biology models based on biological information on specific diseases, and experimental data for proton and heavy ion radiation. A two-hit model of Alzheimer s disease (AD) has been proposed by Zhu et al.(1), which is the framework of our model. Of importance is that over 50% of the US population over the age of 75-y have mild to severe forms of AD. Therefore we recommend that risk assessment for a potential AD risk from space radiation should focus on the projection of an earlier age of onset of AD and the prevention of this possible acceleration through countermeasures. In the two-hit model, oxidative stress and aberrant cell cycle-related abnormalities leading to amyloid-beta plaques and neurofibrillary tangles are necessary and invariant steps in AD. We have formulated a stochastic cell kinetics model of the two-hit AD model. In our model a population of neuronal cells is allowed to undergo renewal through neurogenesis and is susceptible to oxidative stress or cell cycle abnormalities with age-specific accumulation of damage. Baseline rates are fitted to AD population data for specific ages, gender, and for persons with an apolipoprotein 4 allele. We then explore how low LET or heavy ions may increase either of the two-hits or neurogenesis either through persistent oxidative stress, direct mutation, or through changes to the micro-environment, and suggest possible ways to develop accurate quantitative estimates of these processes for predicting AD risks following long-term space travel.

Cucinotta, Francis A.↗

NASA NTRS1982

State of the art: Design for noise II

Charts relating to helicopter noise reduction design efforts are given. Information regarding priorities, design guidelines, design margins, risks, noise prediction, derivative trends, design impact, and cost impact is given.

Cox, C. R.↗

NASA NTRS2000

Ceruloplasmin and cardiovascular disease

Transition metal ion-mediated oxidation is a commonly used model system for studies of the chemical, structural, and functional modifications of low-density lipoprotein (LDL). The physiological relevance of studies using free metal ions is unclear and has led to an exploration of free metal ion-independent mechanisms of oxidation. We and others have investigated the role of human ceruloplasmin (Cp) in oxidative processes because it the principal copper-containing protein in serum. There is an abundance of epidemiological data that suggests that serum Cp may be an important risk factor predicting myocardial infarction and cardiovascular disease. Biochemical studies have shown that Cp is a potent catalyst of LDL oxidation in vitro. The pro-oxidant activity of Cp requires an intact structure, and a single copper atom at the surface of the protein, near His(426), is required for LDL oxidation. Under conditions where inhibitory protein (such as albumin) is present, LDL oxidation by Cp is optimal in the presence of superoxide, which reduces the surface copper atom of Cp. Cultured vascular endothelial and smooth muscle cells also oxidize LDL in the presence of Cp. Superoxide release by these cells is a critical factor regulating the rate of oxidation. Cultured monocytic cells, when activated by zymosan, can oxidize LDL, but these cells are unique in their secretion of Cp. Inhibitor studies using Cp-specific antibodies and antisense oligonucleotides show that Cp is a major contributor to LDL oxidation by these cells. The role of Cp in lipoprotein oxidation and atherosclerotic lesion progression in vivo has not been directly assessed and is an important area for future studies.

NASA Discipline Cell Biology↗

NASA NTRS2004

Gene Expression Profile Analysis as a Prognostic Indicator of Normal Tissue Response to Simulated Space Radiations

This project was funded as a pilot project to determine the feasibility of using gene expression profiles to characterize the response of human cells to exposure to particulate radiations such as those encountered in the spaceflight environment. We proposed to use microarray technology to examine the gene expression patterns of a bank of well-characterized human fibroblast cell cultures. These fibroblast cultures were derived from breast or head and neck cancer patients who exhibited normal, minimal, or severe normal tissue reactions following low LET radiation exposure via radiotherapy. Furthermore, determination of SF2 values from fibroblasts cultured from these individuals were predictive of risk for severe late reactions. We hypothesized that by determining the expression of thousands of genes we could identify gene expression patterns that reflect how normal tissues respond to high Z and energy (HZE) particles, that is, that there are molecular signatures for HZE exposures. We also hypothesized that individuals who are intrinsically radiosensitive may elicit a unique response. Because this was funded as a pilot project we focused our initial studies on logistics and appropriate experimental design, and then to test our hypothesis that there is a unique molecular response to specific particles, in this case C and Fe, for primary human skin fibroblasts.

Story, Michael↗

NASA NTRS2009

Ballistic Performance of Porous-Ceramic, Thermal-Protection-Systems

Porous-ceramic, thermal protection systems are used heavily in current reentry vehicles like the Space Shuttle and are currently being proposed for the next generation of manned spacecraft, Orion. These materials insulate the structural components of a spacecraft against the intense thermal environments of atmospheric reentry. Furthermore, these materials are also highly exposed to space environmental hazards like meteoroid and orbital debris impacts. This paper discusses recent impact testing up to 9 km/s, and the findings of the influence of material equation-of-state on the simulation of the impact event to characterize the ballistic performance of these materials. These results will be compared with heritage models1 for these materials developed from testing at lower velocities. Assessments of predicted spacecraft risk based upon these tests and simulations will also be discussed.

Christiansen, E. L.↗

NASA NTRS2012

Systems-Wide Safety and Assurance Technologies SSAT Project

The SSAT Project goal is to develop validated multidisciplinary tools and techniques to ensure system safety in NextGen to enable proactive management of safety risk through predictive methods.

Mah, Robert W.↗

NASA NTRSDate not supplied

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗