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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women

Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the semantic relationships in the text document although it has been widely applied in text mining. BERTopic, created in 2022, leveraged advances in deep learning and can capture the contextual relationships between words. In this work, we integrated Artificial Intelligence (AI) modules to LDA and BERTopic and provided a comprehensive comparison on the analysis of prescription opioid-related cardiovascular risks in women. Opioid use can increase the risk of cardiovascular problems in women such as arrhythmia, hypotension etc. 1,837 abstracts were retrieved and downloaded from PubMed as of April 2024 using three Medical Subject Headings (MeSH) words: “opioid,” “cardiovascular,” and “women.” Machine Learning of Language Toolkit (MALLET) was employed for the implementation of LDA. BioBERT was used for document embedding in BERTopic. Eighteen was selected as the optimal topic number for MALLET and 23 for BERTopic. ChatGPT-4-Turbo was integrated to interpret and compare the results. The short descriptions created by ChatGPT for each topic from LDA and BERTopic were highly correlated, and the performance accuracies of LDA and BERTopic were similar as determined by expert manual reviews of the abstracts grouped by their predominant topics. The results of the t-SNE (t-distributed Stochastic Neighbor Embedding) plots showed that the clusters created from BERTopic were more compact and well-separated, representing improved coherence and distinctiveness between the topics. Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. In addition, BERTopic has the connection port for ChatGPT-4-Turbo or other large language models in its algorithm for automatic interpretation, while with LDA interpretation must be manually, and needs special procedures for data pre-processing and stop words exclusion. Therefore, while LDA remains valuable for large-scale text analysis with resource constraints, AI-assisted BERTopic offers significant advantages in providing the enhanced interpretability and the improved semantic coherence for extracting valuable insights from textual data.

Research & Experimental Medicine↗
NASA NTRSDate not supplied

Root Cause Analysis of the Data Refinement Process – Medical Conditions Capability Resource Tables

The medical system for spaceflight thus far has been designed to support missions in low earth orbit (LEO). Crew capabilities are limited and heavily dependent on the team of medical support staff at Mission Control Center (MCC) to guide diagnosis and management. However, missions to the Moon and Mars will suffer from several constraints that will make this ground support focused approach to care ineffective. In order to update and modify medical system design, NASA has relied on Probabilistic Risk Assessment (PRA) modeling to mitigate medical risk through trade space analysis. Specifically, capability resource tables (CRT’s) were developed to create a dataset of resources required to manage a list of accepted medical conditions significant in exploration spaceflight. With 120 conditions, this dataset contained hundreds of capabilities and thousands of resources with tens of thousands of cells of data. Initially these tables were built in excel for high throughput during development, but ultimately had to be transferred, managed, and modified into the Evidence Library database for modeling purposes. The process of collating and reviewing the Evidence Library revealed numerous errors in the dataset that had to be corrected through iterative changes. Several error types emerged during this process and can be broken into specific classifications defined as “input”, “transcription”, “structural”, “branching”, and “information”. In reviewing these error types through the root cause analysis (RCA) approach, we were able to identify the contributors to these errors which included single data review points, changing product end goals, limited software selection, time constraints and several others. By reviewing and evaluating the underlying causes we can provide possible system improvements that can be implemented for current and future data management in PRA model inputs.

A. Anderson↗
NASA NTRSDate not supplied

Soyuz Landing Reconstructions

Introduction: Recent data show a landing-attributed injury rate among Soyuz crew members to be higher than predicted in original certification analysis. New vehicles being developed for NASA are being certified using analytical tools to quantify injury risk. This assessment will provide data to allow the Agency to evaluate whether these tools are able to capture true injury risk and allow a comparison between Soyuz landings and upcoming vehicles. Methods: A finite element model (FEM) of the Soyuz descent module (DM) and its landing environment were developed to recreate Soyuz landing conditions. Occupant breakout models composed of the Soyuz seat and Sokol helmet were then developed to evaluate occupant response. These models included both anthropomorphic test device (ATD) and human body model (HBM) surrogates in three anthropometric sizes. A generalized distribution analysis of the Soyuz landing environment was performed using landing variable distributions from available literature. Results were used to identify trends in vehicle landing acceleration with landing conditions and to compare landing model injury risk predictions with those estimated in vehicle certification analysis. Next, historic Soyuz landings identified as inducing occupant injury during were reconstructed using the developed landing model and estimated landing conditions. Results and Discussion: This assessment demonstrated the capability of certification metrics, which include a combination of vehicle- and occupant-level injury risk analysis, to identify elevated injury risk landing conditions. However, the developed landing load predictions were limited by available vehicle and landing condition data. Additional data, particularly landing acceleration data specific to historic Soyuz landing conditions, would greatly enhance this assessment’s findings.

Preston Greenhalgh↗
NASA NTRSDate not supplied

Assessing Environmental and Socioeconomic Factors of Urban Flood Vulnerability in Kansas City, Kansas

Pluvial flooding, over-saturated ground, and drainage systems disproportionately impact historically marginalized urban neighborhoods during extreme rainfall events. These communities are impacted by physical and socioeconomic factors that make them vulnerable to flooding events, such as high concentrations of impervious landcover, high precipitation rates, and a combined sewer system framework. Despite known vulnerability to environmental hazards, understanding potential pluvial street-level flooding events are largely unknown. Using the open-source National Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation model, NASA DEVELOP examined neighborhood scale runoff retention and potential economic damages for risk mapping throughout Kansas City, Kansas. The generated outputs aid in identifying vulnerable neighborhoods susceptible to flooding and in need of future intervention. Previous studies have applied this model framework to understand urban flood vulnerability regarding ecosystem services, urban planning, and flood mitigation strategies. We utilized the InVEST outputs to develop indices pertaining to environmental justice factors of race, socioeconomic status, social vulnerability, and health. The findings indicate that historically redlined neighborhoods in Kansas City, Kansas face disproportional impacts from flood events and are subject to greater environmental stressors. This research provides an approach to utilizing an open-source flood vulnerability model to empower neighborhood-scale environmental justice analysis, enhancing the local communities' understanding of present-day impacts of historical environmental injustices.

Hadwynne Gross↗
NASA NTRS2009

Probabilistic Risk Assessment for Decision Making During Spacecraft Operations

Decisions made during the operational phase of a space mission often have significant and immediate consequences. Without the explicit consideration of the risks involved and their representation in a solid model, it is very likely that these risks are not considered systematically in trade studies. Wrong decisions during the operational phase of a space mission can lead to immediate system failure whereas correct decisions can help recover the system even from faulty conditions. A problem of special interest is the determination of the system fault protection strategies upon the occurrence of faults within the system. Decisions regarding the fault protection strategy also heavily rely on a correct understanding of the state of the system and an integrated risk model that represents the various possible scenarios and their respective likelihoods. Probabilistic Risk Assessment (PRA) modeling is applicable to the full lifecycle of a space mission project, from concept development to preliminary design, detailed design, development and operations. The benefits and utilities of the model, however, depend on the phase of the mission for which it is used. This is because of the difference in the key strategic decisions that support each mission phase. The focus of this paper is on describing the particular methods used for PRA modeling during the operational phase of a spacecraft by gleaning insight from recently conducted case studies on two operational Mars orbiters. During operations, the key decisions relate to the commands sent to the spacecraft for any kind of diagnostics, anomaly resolution, trajectory changes, or planning. Often, faults and failures occur in the parts of the spacecraft but are contained or mitigated before they can cause serious damage. The failure behavior of the system during operations provides valuable data for updating and adjusting the related PRA models that are built primarily based on historical failure data. The PRA models, in turn, provide insight into the effect of various faults or failures on the risk and failure drivers of the system and the likelihood of possible end case scenarios, thereby facilitating the decision making process during operations. This paper describes the process of adjusting PRA models based on observed spacecraft data, on one hand, and utilizing the models for insight into the future system behavior on the other hand. While PRA models are typically used as a decision aid during the design phase of a space mission, we advocate adjusting them based on the observed behavior of the spacecraft and utilizing them for decision support during the operations phase.

dynamic fault trees↗
NASA NTRS2011

Cancer Risk Map for the Surface of Mars

We discuss calculations of the median and 95th percentile cancer risks on the surface of Mars for different solar conditions. The NASA Space Radiation Cancer Risk 2010 model is used to estimate gender and age specific cancer incidence and mortality risks for astronauts exploring Mars. Organ specific fluence spectra and doses for large solar particle events (SPE) and galactic cosmic rays (GCR) at various levels of solar activity are simulated using the HZETRN/QMSFRG computer code, and the 2010 version of the Badhwar and O Neill GCR model. The NASA JSC propensity model of SPE fluence and occurrence is used to consider upper bounds on SPE fluence for increasing mission lengths. In the transport of particles through the Mars atmosphere, a vertical distribution of Mars atmospheric thickness is calculated from the temperature and pressure data of Mars Global Surveyor, and the directional cosine distribution is implemented to describe the spherically distributed atmospheric distance along the slant path at each elevation on Mars. The resultant directional shielding by Mars atmosphere at each elevation is coupled with vehicle and body shielding for organ dose estimates. Astronaut cancer risks are mapped on the global topography of Mars, which was measured by the Mars Orbiter Laser Altimeter. Variation of cancer risk on the surface of Mars is due to a 16-km elevation range, and the large difference is obtained between the Tharsis Montes (Ascraeus, Pavonis, and Arsia) and the Hellas impact basin. Cancer incidence risks are found to be about 2-fold higher than mortality risks with a disproportionate increase in skin and thyroid cancers for all astronauts and breast cancer risk for female astronauts. The number of safe days on Mars to be below radiation limits at the 95th percent confidence level is reported for several Mission design scenarios.

Kim, Myung-Hee Y.↗
NASA NTRS2002

Radiation Effect on Human Tissue

Predicting the occurrence of human cancer following exposure of an epidemiologic population to any agent causing genetic damage is a difficult task. To an approximation, this is because the uncertainty of uniform exposure to the damaging agent, and the uncertainty of uniform processing of that damage within a complex set of biological variables, degrade the confidence of predicting the delayed expression of cancer as a relatively rare event within clinically normal individuals. This situation begs the need for alternate controlled experimental models that are predictive for the development of human cancer following exposures to agents causing genetic damage. Such models historically have not been of substantial proven value. It is more recently encouraging, however, that developments in molecular and cell biology have led to an expanded knowledge of human carcinogenesis, and of molecular markers associated with that process. It is therefore appropriate to consider new laboratory models developed to accomodate that expanded knowledge in order to assess the cancer risks associated with exposures to genotoxic agents. When ionizing radiation of space is the genotoxic agent, then a series of additional considerations for human cancer risk assessment must also be applied. These include the dose of radiation absorbed by tissue at different locations in the body, the quality of the absorbed radiation, the rate at which absorbed dose accumulates in tissue, the way in which absorbed dose is measured and calculated, and the alterations in incident radiation caused by shielding materials. It is clear that human cancer risk assessment for damage caused by ionizing radiation is a multidisciplinary responsibility, and that within this responsibility no single discipline can hold disproportionate sway if a risk assessment model of radiation-induced human cancer is to be developed that has proven value. Biomolecular and cellular markers from the work reported here are considered for use in assessing human cancer risk related to exposure to space radiation. This potential use must be integrated within the specified multidisciplinary context in order to create a new tool of molecular epidemiology that can hopefully then realistically assess this cancer risk.

Richmond, Robert C.↗
NASA NTRS2012

Response Surface Modeling Tolerance and Inference Error Risk Specifications: Proposed Industry Standards

This paper reviews the derivation of an equation for scaling response surface modeling experiments. The equation represents the smallest number of data points required to fit a linear regression polynomial so as to achieve certain specified model adequacy criteria. Specific criteria are proposed which simplify an otherwise rather complex equation, generating a practical rule of thumb for the minimum volume of data required to adequately fit a polynomial with a specified number of terms in the model. This equation and the simplified rule of thumb it produces can be applied to minimize the cost of wind tunnel testing.

DeLoach, Richard↗
NASA NTRS1992

Software reliability through fault-avoidance and fault-tolerance

Accomplishments in the following research areas are summarized: structure based testing, reliability growth, and design testability with risk evaluation; reliability growth models and software risk management; and evaluation of consensus voting, consensus recovery block, and acceptance voting. Four papers generated during the reporting period are included as appendices.

Vouk, Mladen A.↗
NASA NTRS2017

Modeling Oxygen Prebreathe Protocols for Exploration Extravehicular Activities Using Variable Pressure Suits

Exploration missions are expected to use variable pressure extravehicular activity (EVA) spacesuits as well as a spacecraft "exploration atmosphere" of 56.5 kPa (8.2 psia), 34% O2, both of which provide the possibility of reducing the oxygen prebreathe times necessary to reduce decompression sickness (DCS) risk. Previous modeling work predicted 8.4% DCS risk for an EVA beginning at the exploration atmosphere, followed by 15 minutes of in-suit O2 prebreathe, and 6 hours of EVA at 29.6 kPa (4.3 psia). In this study we model notional prebreathe protocols for a variable pressure suit where the exploration atmosphere is unavailable.

Abercromby, Andrew F. J.↗
NASA NTRS2004

The Local Tissue Environment During the September 29, 1989 Solar Particle Event

The solar particle event (SPE) of September 29, 1989, produced an iron-rich spectrum with energies approaching 1 GeV/amu with an energy power index of 2.5. These high charge and energy (HZE) ions of the iron-rich SPEs challenge conventional methods of SPE shield design and assessment of astronaut risks. Shield and risk assessments are evaluated using the HZETRN code with computerized anatomical man (CAM) model for astronaut s body tissues. Since the HZE spectra decline rapidly with energy and HZE attenuation in materials is limited by their penetration power, details of the mass distributions about the sensitive tissues (shielding materials and the astronaut's body) are important determining factors of the exposure levels. Typical space suit and lightly shielded structures allow significant contributions from HZE components to some critical body tissues and have important implications on the models for risk assessment. Only a heavily shielded equipment room of a space vehicle or habitat provides sufficient shielding for the early response at sensitive organs from this event. The February 23, 1956 event of similar spectral characteristics and ten times this event may have important medical consequences without a well-shielded region.

Kim, M.-H. Y.↗
NASA NTRS2023

Youngstown and Warren Disasters: Mapping Flood Susceptibility, Vulnerability, and Risk and Tree Canopy Coverage in Northern Ohio to Inform Stormwater Management and Flood Mitigation Efforts

Both pluvial and fluvial flooding events pose direct challenges on urban infrastructure and communities across the United States. Heavy rainfall events oversaturate the ground, overflow waterbodies, and overwhelm stormwater infrastructure. Vulnerable areas receive heavy damage from flooding events due to physical factors like increased impervious surfaces, poor stormwater systems, and limited greenspaces. These vulnerable neighborhoods are comprised of aging populations, minority communities, and lower income levels. Lack of data in these communities have made it difficult to implement policymaking and flood mitigation strategies. Using the Urban Flood Risk Mitigation model (InVEST) and the PlanetScope satellite constellation, the team visualized historical flooding and tree canopy coverage as a measure of flood susceptibility. The team also used the Arc-Malstrom model to provide further insight into where flooding accumulates via surface elevation depressions in the study area. To validate these models, the team explored the spatial variation of rainfall events using NASA’s Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG). The resulting maps highlight areas surrounding the cities of Youngstown and Warren as being the most flood susceptible and socially vulnerable, while the city centers contain the lowest tree canopy coverage. The DEVELOP team collaborated with the Environmental Collaborative of Ohio (ECO) to create products for end users within the City of Warren’s Water Pollution Control Department, the Eastgate Regional Council of Governments and the Healthy Community Partnership of Mahoning Valley. These products help identify target areas for preventative flood mitigation measures as well as areas ideal for green infrastructure intervention.

InVEST Urban Flood Risk Mitigation Model↗
NASA NTRS2005

Simulation of Blast Waves with Headwind

The blast wave resulting from an explosion was simulated to provide guidance for models estimating risks for human spacecraft flight. Simulations included effects of headwind on blast propagation, Blasts were modelled as an initial value problem with a uniform high energy sphere expanding into an ambient field. Both still air and cases with headwind were calculated.

Olsen, Michael E.↗
NASA NTRS2008

Emergency Landing Planning for Damaged Aircraft

Considerable progress has been made over the last 15 years on building adaptive control systems to assist pilots in flying damaged aircraft. Once a pilot has regained control of a damaged aircraft, the next problem is to determine the best site for an emergency landing. In general, the decision depends on many factors including the actual control envelope of the aircraft, distance to the site, weather en route, characteristics of the approach path, characteristics of the runway or landing site, and emergency facilities at the site. All of these influence the risk to the aircraft, to the passengers and crew, and to people and property on the ground. We describe an ongoing project to build and demonstrate an emergency landing planner that takes these various factors into consideration and proposes possible routes and landing sites to the pilot, ordering them according to estimated risk. We give an overview of the system architecture and input data, describe our preliminary modeling of risk, and describe how we search the space of landing sites and routes.

Meuleau, Nicolas↗
NASA NTRS2010

Space Radiation Heart Disease Risk Estimates for Lunar and Mars Missions

The NASA Space Radiation Program performs research on the risks of late effects from space radiation for cancer, neurological disorders, cataracts, and heart disease. For mortality risks, an aggregate over all risks should be considered as well as projection of the life loss per radiation induced death. We report on a triple detriment life-table approach to combine cancer and heart disease risks. Epidemiology results show extensive heterogeneity between populations for distinct components of the overall heart disease risks including hypertension, ischaemic heart disease, stroke, and cerebrovascular diseases. We report on an update to our previous heart disease estimates for Heart disease (ICD9 390-429) and Stroke (ICD9 430-438), and other sub-groups using recent meta-analysis results for various exposed radiation cohorts to low LET radiation. Results for multiplicative and additive risk transfer models are considered using baseline rates for US males and female. Uncertainty analysis indicated heart mortality risks as low as zero, assuming a threshold dose for deterministic effects, and projections approaching one-third of the overall cancer risk. Medan life-loss per death estimates were significantly less than that of solid cancer and leukemias. Critical research questions to improve risks estimates for heart disease are distinctions in mechanisms at high doses (>2 Gy) and low to moderate doses (<2 Gy), and data and basic understanding of radiation doserate and quality effects, and individual sensitivity.

Cucinotta, Francis A.↗
NASA NTRSDate not supplied

Machine Learning Enabled Quantitative Risk Assessment of Aerial Wildfire Response

Aerial wildfire operations are high risk and account for a large number of firefighter deaths. Increasing intensity of wildfires is driving a surge in aerial operations, while simultaneously there is growing interest in improving system safety and performance. In this work, wildfire aviation mishaps documented using the SAFECOM system are analyzed using a previously developed framework for hazard extraction and analysis of trends (HEAT). Hazards and specific failure modes are extracted from the narrative data in SAFECOM forms using natural language processing techniques. Metrics for each hazard are calculated, including frequency, rate, and severity. We examine whether these metrics change over time, and whether they are related to metadata, such as region and aircraft type. The results of the hazard analysis are presented in a risk matrix, identifying the highest and lowest risk hazards based on rate of occurrence and average severity. Results identify jumper operations hazards as high-risk, in addition to bucket drop failures, cargo let down failures, and severe weather as medium risk.

machine learning↗
NASA NTRS2020

Natural Hazard Risk Assessments at the Global Scale

Since 1990, natural hazards have led to over 1.6 million fatalities globally, and economic losses are estimated at an average of around USD 260–310 billion per year. The scientific and policy communities recognise the need to reduce these risks. As a result, the last decade has seen a rapid development of global models for assessing risk from natural hazards at the global scale. In this paper, we review the scientific literature on natural hazard risk assessments at the global scale, and we specifically examine whether and how they have examined future projections of hazard, exposure, and/or vulnerability. In doing so, we examine similarities and differences between the approaches taken across the different hazards, and we identify potential ways in which different hazard communities can learn from each other. For example, there are a number of global risk studies focusing on hydrological, climatological, and meteorological hazards that have included future projections and disaster risk reduction measures (in the case of floods), whereas fewer exist in the peer-reviewed literature for global studies related to geological hazards. On the other hand, studies of earthquake and tsunami risk are now using stochastic modelling approaches to allow for a fully probabilistic assessment of risk, which could benefit the modelling of risk from other hazards. Finally, we discuss opportunities for learning from methods and approaches being developed and applied to assess natural hazard risks at more continental or regional scales. Through this paper, we hope to encourage further dialogue on knowledge sharing between disciplines and communities working on different hazards and risk and at different spatial scales.

Philip J. Ward↗
NASA NTRSDate not supplied

NASA Radiation Operations Sources, Models, and Standards

Space radiation is one of the major challenges of spaceflight. Astronauts spending time in low Earth orbit, the lunar surface, deep space, and elsewhere will all be exposed to multiple space radiation sources. These sources include trapped radiation in Earth’s upper atmosphere, solar energetic particles, and the omnipresent galactic cosmic radiation, as well as non-ionizing radiation from inside and outside a vehicle or habitat. The Space Radiation Analysis Group (SRAG) at Johnson Space Center is responsible for ensuring astronauts are protected from short- and long-term risks of radiation exposure. This talk details the radiation operational standards employed by NASA.

space radiation↗