Results for “vulnerability assessments” — Page 20

NASA NTRS1999

Time-on-task decrements in "steer clear" performance of patients with sleep apnea and narcolepsy

Loss of attention with time-on-task reflects the increasing instability of the waking state during performance in experimentally induced sleepiness. To determine whether patients with disorders of excessive sleepiness also displayed time-on-task decrements indicative of wake state instability, visual sustained attention performance on "Steer Clear," a computerized simple RT driving simulation task, was compared among 31 patients with untreated sleep apnea, 16 patients with narcolepsy, and 14 healthy control subjects. Vigilance decrement functions were generated by analyzing the number of collisions in each of six four-minute periods of Steer Clear task performance in a mixed-model analysis of variance and linear regression equations. As expected, patients had more Steer Clear collisions than control subjects (p=0.006). However, the inter-subject variability in errors among the narcoleptic patients was four-fold that of the apnea patients, and 100-fold that of the controls volunteers; the variance in errors among untreated apnea patients was 27-times that of controls. The results of transformed collision data revealed main effects for group (p=0.006), time-on-task (p=0.001), and a significant interaction (p=0.022). Control subjects showed no clear evidence of increasing collision errors with time-on-task (adjusted R2=0.22), while apnea patients showed a trend toward vigilance decrement (adjusted R2=0.42, p=0.097), and narcolepsy patients evidenced a robust linear vigilance decrement (adjusted R2=0.87, p=0.004). The association of disorders of excessive somnolence with escalating time-on-task decrements makes it imperative that when assessment of neurobehavioral performance is conducted in patients, it involves task durations and analyses that will evaluate the underlying vulnerability of potentially sleepy patients to decrements over time in tasks that require sustained attention and timely responses, both of which are key components in safe driving performance.

NASA Discipline Space Human Factors↗

NASA NTRS2003

An Overview of the NASA Aviation Safety Program (AVSP) Systemwide Accident Prevention (SWAP) Human Performance Modeling (HPM) Element

An overview is provided of the Human Performance Modeling (HPM) element within the NASA Aviation Safety Program (AvSP). Two separate model development tracks for performance modeling of real-world aviation environments are described: the first focuses on the advancement of cognitive modeling tools for system design, while the second centers on a prescriptive engineering model of activity tracking for error detection and analysis. A progressive implementation strategy for both tracks is discussed in which increasingly more complex, safety-relevant applications are undertaken to extend the state-of-the-art, as well as to reveal potential human-system vulnerabilities in the aviation domain. Of particular interest is the ability to predict the precursors to error and to assess potential mitigation strategies associated with the operational use of future flight deck technologies.

Foyle, David C.↗

NASA NTRS2014

HEMODOSE: A Set of Multi-parameter Biodosimetry Tools

After the events of September 11, 2001 and recent events at the Fukushima reactors in Japan, there is an increasing concern of the occurrence of nuclear and radiological terrorism or accidents that may result in large casualty in densely populated areas. To guide medical personnel in their clinical decisions for effective medical management and treatment of the exposed individuals, biological markers are usually applied to examine the radiation induced changes at different biological levels. Among these the peripheral blood cell counts are widely used to assess the extent of radiation induced injury. This is due to the fact that hematopoietic system is the most vulnerable part of the human body to radiation damage. Particularly, the lymphocyte, granulocyte, and platelet cells are the most radiosensitive of the blood elements, and monitoring their changes after exposure is regarded as the most practical and best laboratory test to estimate radiation dose. The HEMODOSE web tools are built upon solid physiological and pathophysiological understanding of mammalian hematopoietic systems, and rigorous coarse-grained biomathematical modeling and validation. Using single or serial granulocyte, lymphocyte, leukocyte, or platelet counts after exposure, these tools can estimate absorbed doses of adult victims very rapidly and accurately. Some patient data in historical accidents are utilized as examples to demonstrate the capabilities of these tools as a rapid point-of-care diagnostic or centralized high-throughput assay system in a large scale radiological disaster scenario. Unlike previous dose prediction algorithms, the HEMODOSE web tools establish robust correlations between the absorbed doses and victim's various types of blood cell counts not only in the early time window (1 or 2 days), but also in very late phase (up to 4 weeks) after exposure

Hu, Shaowen↗

DOE OSTI2023

Resilience Assessment Framework For Electric Distribution Systems Performance Under Extreme Conditions

The devastating impact of extreme weather-related events is increasingly evident on power grids, especially on distribution grids. The severity of their potential impact calls for 1) developing a suitable resilience assessment framework to capture the system performance and 2) assessing relevant mitigative strategies to lessen the impact of such events. This paper proposes a framework to identify grid vulnerabilities using the energy-at-risk concept to select, disconnect and isolate grid portions due to a resilience event. The proposed framework mainly consists of two steps; i) processing the utility's available infrastructure, i.e., a network model, possible switching combinations, and outage information for those combinations, as a graph-based database, and ii) implementing a novel optimal switching algorithm leveraging database and grid simulated metrics. These switching actions are generated to implement load curtailment in a rolling manner during anticipated grid scarcity conditions. In this study, a test case is created using two taxonomy feeders and is simulated against an extreme temperature event, e.g., a long, relatively cold, and prolonged freeze peak, thereby creating stress on the grid. It is demonstrated that the proposed framework allows utilities to predict the energy-at-risk during such resilience events and design suitable outage management strategies.

Poudel, Shiva↗

NASA NTRS2001

Formal assessment of network security risks with an integrated assessment instrument

Explore the source record for details and available documents.

checking security verification↗

NASA NTRS2024

Evaluating Liftoff Debris for NASA’s Space Launch System (SLS) Prior to the Artemis I Launch

The SLS Artemis I launch vehicle is the first of several planned Artemis launch vehicles, with a number of design differences from earlier NASA missions that incur liftoff debris risk to the mission. As a test vehicle, the Artemis I hardware also endured environments and tests not planned for future missions, which led to several additional factors contributing to an evolving liftoff debris risk to the SLS vehicle. This paper will summarize these risk factors and address the processes used to evaluate and communicate the risks to support a successful Artemis I launch. It will discuss how the evolving risks that were quantified and evaluated by a Cross-Program team of debris Subject Matter Experts to mitigate liftoff debris hazards and communicate updated risk to the SLS vehicle. This process was performed through the inaugural use of an SLS debris day-of-launch (DOL) standard operating procedure that will be used for subsequent Artemis missions. This paper addresses the risk of liftoff debris, debris released by the vehicle or from the launch pad during liftoff through vehicle tower clear. Expected liftoff debris is well understood from previous NASA programs’ experience and from tests of materials, processes and functions that are known to release liftoff debris. These expected sources were assessed and cleared well ahead of launch day. However, given the ever-changing schedules and environments, processes were in place to evaluate any additional potential liftoff debris risks identified during launch countdown. Although many of the Artemis vehicle hardware components are similar to those on the NASA Shuttle Program, there are important differences in the architecture of the Artemis I vehicle which require new assessments of liftoff debris risk for the Artemis missions. The more favorable Artemis crew module location and surfaces are far less vulnerable to debris impacts; however, the longer vehicle can result in higher liftoff debris impact energies to those components on the aft end of the vehicle. Additionally, the positional change of the RS-25 liquid engines to nearer the Booster nozzle exit plane along with the change in Booster throat plug design is a disadvantage to the overall liftoff debris risk which resulted in additional test and analysis efforts for evaluating the integrated vehicle debris risk. In spite of the comprehensive tests and analyses of Artemis I expected liftoff debris, a number of additional tests/processes were completed prior to the Artemis I mission that were required to support a complete understanding of a new launch vehicle, but increased the risk of releasing liftoff debris. The hardware endured several additional cryogenic loading cycles, including the Green Run tests at Stennis Space Center, Wet Dress Rehearsals at Kennedy Space Center, and multiple launch attempts. Each of these cycles induced stresses in the thermal protection system (TPS) materials, increasing the risk of damage to and release of the TPS. Additionally, induced and weather environmental factors that could increase the likelihood of debris release were significant. Vibrations and stresses in the TPS were induced by a required roll-back to the Vehicle Assembly Building before Hurricane Ian to protect the vehicle from damage by high winds. Wind damage and potential internal stresses to several outer mold line materials on the integrated SLS vehicle and mobile launcher were caused by weathering Hurricane Nicole at Pad 39B the week before launch. A thorough imagery scan of the vehicle was performed after each event and the damage observed was repaired, removed, or assessed and the risk to the mission evaluated. Mitigation of debris risk can occur by tests and analyses to show debris impacted components as damage tolerant, by new/improved processes for prevention of debris availability, or redesign. Risk mitigation processes for Artemis I-specific liftoff debris events and the development and use of the SLS debris day of launch (DOL) procedures that will be used for subsequent Artemis missions will be described.

Space Launch System↗

NASA NTRSDate not supplied

Evaluating Liftoff Debris for NASA’s Space Launch System (SLS) Prior to the Artemis I Launch

The SLS Artemis I launch vehicle is the first of several planned Artemis launch vehicles, with a number of design differences from earlier NASA missions that incur liftoff debris risk to the mission. As a test vehicle, the Artemis I hardware also endured environments and tests not planned for future missions, which led to several additional factors contributing to an evolving liftoff debris risk to the SLS vehicle. This paper will summarize these risk factors and address the processes used to evaluate and communicate the risks to support a successful Artemis I launch. It will discuss how the evolving risks that were quantified and evaluated by a Cross-Program team of debris Subject Matter Experts to mitigate liftoff debris hazards and communicate updated risk to the SLS vehicle. This process was performed through the inaugural use of an SLS debris day-of-launch (DOL) standard operating procedure that will be used for subsequent Artemis missions. This paper addresses the risk of liftoff debris, debris released by the vehicle or from the launch pad during liftoff through vehicle tower clear. Expected liftoff debris is well understood from previous NASA programs’ experience and from tests of materials, processes and functions that are known to release liftoff debris. These expected sources were assessed and cleared well ahead of launch day. However, given the ever-changing schedules and environments, processes were in place to evaluate any additional potential liftoff debris risks identified during launch countdown. Although many of the Artemis vehicle hardware components are similar to those on the NASA Shuttle Program, there are important differences in the architecture of the Artemis I vehicle which require new assessments of liftoff debris risk for the Artemis missions. The more favorable Artemis crew module location and surfaces are far less vulnerable to debris impacts; however, the longer vehicle can result in higher liftoff debris impact energies to those components on the aft end of the vehicle. Additionally, the positional change of the RS-25 liquid engines to nearer the Booster nozzle exit plane along with the change in Booster throat plug design is a disadvantage to the overall liftoff debris risk which resulted in additional test and analysis efforts for evaluating the integrated vehicle debris risk. In spite of the comprehensive tests and analyses of Artemis I expected liftoff debris, a number of additional tests/processes were completed prior to the Artemis I mission that were required to support a complete understanding of a new launch vehicle, but increased the risk of releasing liftoff debris. The hardware endured several additional cryogenic loading cycles, including the Green Run tests at Stennis Space Center, Wet Dress Rehearsals at Kennedy Space Center, and multiple launch attempts. Each of these cycles induced stresses in the thermal protection system (TPS) materials, increasing the risk of damage to and release of the TPS. Additionally, induced and weather environmental factors that could increase the likelihood of debris release were significant. Vibrations and stresses in the TPS were induced by a required roll-back to the Vehicle Assembly Building before Hurricane Ian to protect the vehicle from damage by high winds. Wind damage and potential internal stresses to several outer mold line materials on the integrated SLS vehicle and mobile launcher were caused by weathering Hurricane Nicole at Pad 39B the week before launch. A thorough imagery scan of the vehicle was performed after each event and the damage observed was repaired, removed, or assessed and the risk to the mission evaluated. Mitigation of debris risk can occur by tests and analyses to show debris impacted components as damage tolerant, by new/improved processes for prevention of debris availability, or redesign. Risk mitigation processes for Artemis I-specific liftoff debris events and the development and use of the SLS debris day of launch (DOL) procedures that will be used for subsequent Artemis missions will be described.

Space Launch System↗

DOE OSTI2020

A PROVEN APPROACH FOR EFFECTIVE COMPUTER SECURITY SELF-ASSESSMENTS AT NUCLEAR FACILITIES

A proven method for conducting cybersecurity self-assessments at nuclear power plants is now available for international use. This method was originally developed by Pacific Northwest National Laboratory, under the sponsorship of the U.S. Nuclear Regulatory Commission (NRC), for use at U.S. nuclear power plants. The “Method,” described in NUREG/CR-6847 “Cyber Security Self-Assessment Method for U.S. Nuclear Power Plants,” was originally a limited release document that was withheld from public disclosure but is now publicly available. The Method provides a systematic, phased, and risk-informed approach to help decision makers and security specialists understand their relative cybersecurity posture. Completed Method assessments may be used to support or validate selection of computer security controls to mitigate cyber threats as well as demonstrate compliance with regulations or statutes enacted by competent authorities. The Method assesses the cybersecurity posture of key systems at a nuclear facility with a focus on protection of design base functions. It considers both physical and digital elements of system vulnerabilities and the resulting potential consequences from exploitation. It is well-suited for addressing blended cyberattacks. A semi-quantitative analytical approach is used in the evaluation of potential vulnerabilities, consequences, and risks and provides a technical basis for the selection of security controls to mitigate cyberattacks. The Method’s application at U.S. nuclear power plants has been very encouraging. The only nuclear plant in the United States that did not have adverse findings during its initial NRC computer security inspection prepared for inspection through the diligent application of this self-assessment method and the implementation of recommendations that came out of that self-assessment. Nuclear facilities around the world might find application of the Method extremely helpful for making cost-effective, risk-based decisions regarding computer security and for preparing to pass computer security inspections by their competent authorities.

Cyber security, Nuclear security, Self-assessment↗

DOE OSTI2025

Resilient information and inference networks under mixed-trust sensing

With ubiquitous digitization, sensing, and computational intelligence deployed in increasingly more and broader domains, including critical infrastructure, potentially misleading and destabilizing effects of multimodal anomalies and adversarial behavior are growing in importance. Here, we develop randomized and reinforcement learning-based strategies for strategically recruiting and utilizing deployed (and, thus, vulnerable and potentially faulty and/or compromised) nodes from information and inference networks, while defending against adversaries that attempt to misguide assessments of inferred variables. Recognizing that, besides communication and other costs, sampling from any observable node can either provide true data or dangerously expose our inference to misinformation (without being easily distinguishable what actually happens), the proposed strategies proceed by progressively recruiting nodes and cautiously scaling their information contribution based on assumed, or, in our reinforcement learning approach, intelligently weighed trustworthiness, with the learning approach also considering network-wide, threat-inclusive risk/value tradeoffs. While avoiding the hardware, communication, analytical and computational burden of explicit redundancy, the proposed defensive schemes enable on-the-fly assessments of underlying processes, and system-wide situational awareness with demonstrable resilience against adversarial activities.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Uncertainty quantification and reliability assessment for intermodal freight transportation

Intermodal freight optimization models support cost-effective, low-emission, and timely goods movement by coordinating trucks, rail, and barges. These models determine optimal flows, routing, and modal switches while respecting infrastructure and operational constraints. However, their real-world utility is often undermined by pervasive uncertainties-such as fluctuating transportation costs and emissions, variable terminal capacities, and uncertain freight demand-that distort key performance outcomes, including total system cost, carbon footprint, and transit time reliability. This study presents a structured framework for quantifying uncertainty in intermodal freight transportation (IFT) optimization. The framework evaluates how input uncertainty affects system performance and reliability, a critical need for ensuring that model-based decisions remain robust under real-world variability, especially amid volatile fuel prices, shifting demand, and growing disruptions. It integrates three complementary methods: (1) Sobol-based global sensitivity analysis to identify influential parameters affecting cost, emissions, and transit time, (2) Monte Carlo-based capacity perturbation analysis to assess robustness under probabilistic facility disruptions, and (3) Monte Carlo filtering with Bayesian inference to detect threshold-based performance vulnerabilities. The results highlight diesel truck unit cost as the dominant driver of variability. To improve system resilience, planners should prioritize uncertainty in fuel-related parameters when designing intermodal strategies.

Intermodal freight transportation↗

DOE OSTI2025

Scenario Generation for Built Environment Decision Support under Uncertainty: Case Studies of Airflow Modeling and Climate-Resilient Infrastructure System Design

When confronted with unforeseen challenges, practicing informed decision making is crucial for enhancing resilience in the built environment. While scan-to-building information modeling (BIM) is a well-established approach for creating detailed digital representations of physical assets, its application in assessing and improving infrastructure resilience remains underexplored. This study addresses this gap by proposing a novel application of scan-to-BIM, namely, scan-to-BIM-to-digital twin (S-BIM-DT) workflow. By integrating reality capture and digital twin technologies, this workflow creates continuously updated and accurate digital representations of physical assets, enabling the generation of various scenarios. Unlike traditional methods, the S BIM-DT workflow facilitates continuous model refinement, supporting informed resilience strategies. By combining these technologies into a cohesive process, the workflow facilitates decision making under uncertainty, enabling stakeholders to evaluate and respond to various scenarios effectively. We demonstrate the implementation of the S-BIM-DT workflow through two use cases that highlight its capability to enhance resilience at different scales. The first use case involves the Combined Transportation, Emergency, and Communications Center (CTECC) in Austin, Texas. BIM-enriched computational fluid dynamics (CFD) modeling simulates airflow and develops alternative scenarios for optimizing the heating, ventilation, and air conditioning (HVAC) systems. This approach enhances resilience against airborne health threats in a postCOVID context. The second use case focuses on designated areas within Beaumont, Texas, as part of the Southeast Texas Urban Integrated Field Laboratory (SETx-UIFL) research. By developing inundation maps to assess extreme weather events, this modeling aids in preparedness efforts and informs the development of climate-resilient infrastructure in vulnerable neighborhoods. Results indicate that the S-BIM-DT workflow effectively generates scenarios that enhance resilience in the built environment by facilitating informed decision making. Furthermore, this study serves as a bridge between advanced scan-to-BIM methodologies and the practical strategies needed to improve built infrastructure resilience.

Built environment↗

NASA NTRS2013

IT Security Support for Spaceport Command and Control System

During the fall 2013 semester, I worked at the Kennedy Space Center as an IT Security Intern in support of the Spaceport Command and Control System under the guidance of the IT Security Lead Engineer. Some of my responsibilities included assisting with security plan documentation collection, system hardware and software inventory, and malicious code and malware scanning. Throughout the semester, I had the opportunity to work on a wide range of security related projects. However, there are three projects in particular that stand out. The first project I completed was updating a large interactive spreadsheet that details the SANS Institutes Top 20 Critical Security Controls. My task was to add in all of the new commercial of the shelf (COTS) software listed on the SANS website that can be used to meet their Top 20 controls. In total, there are 153 unique security tools listed by SANS that meet one or more of their 20 controls. My second project was the creation of a database that will allow my mentor to keep track of the work done by the contractors that report to him in a more efficient manner by recording events as they occur throughout the quarter. Lastly, I expanded upon a security assessment of the Linux machines being used on center that I began last semester. To do this, I used a vulnerability and configuration tool that scans hosts remotely through the network and presents the user with an abundance of information detailing each machines configuration. The experience I gained from working on each of these projects has been invaluable, and I look forward to returning in the spring semester to continue working with the IT Security team.

computer security↗

DOE OSTI2026

Evaluation of Hardware and Software Bill of Materials (HBOMs/SBOMs) Extraction Methods

Hardware and software bills of materials (HBOMs and SBOMs) provide important visibility into the components, dependencies, and supply chain relationships within programmable digital devices. This visibility is critical for advanced nuclear reactor applications, where use of common or shared hardware components, software libraries, suppliers, or manufacturing processes may create common cause failure (CCF) vulnerabilities despite apparent diversity. This paper evaluates current approaches for obtaining and analyzing HBOMs and SBOMs in support of CCF, diversity and defense-in-depth (D3) assessments, and begins to explore potential methods for artificial intelligence/machine learning-based analysis. The availability of BOM information from advanced reactor manufacturers and vendors, representative hardware and software categories found in advanced reactor systems continues to limit research [13]. This paper compares commonly used BOM formats, including CycloneDX, SPDX, and SWID. It also surveys publicly available tools for generating BOMs from source code, compiled binaries, and hardware-related information, noting limitations in language coverage, system age, and format interoperability. Finally, this paper evaluates methods for correlating BOM data with vulnerability and exploitability information, including VEX, CVE, and CWE resources. The findings indicate that publicly available nuclear-vendor BOMs are limited, making third-party extraction and research into novel analysis techniques necessary.

Cybersecurity↗

DOE OSTI2022

A deep learning approach to real-time HIV outbreak detection using genetic data

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Visual Examination of Aluminum Containers for Extended Wet Storage of Non-Aluminum-Clad Spent Nuclear Fuel (FY 2021)

The goal of the Augmented Monitoring and Condition Assessment Program (AMCAP) program is to provide a condition assessment of the storage containers for non-aluminum-clad spent nuclear fuel (NASNF) in L Basin and demonstrate continued safe storage of all NASNF pending retrieval for ultimate disposition. The storage configuration of NASNF is vulnerable to inside-out corrosion attack. The approach being used in AMCAP is to develop and deploy examination methods for remote, in-situ inspection of the bundle storage in VTS and for OSC storage in the OSC racks. A method for Visual Examination (VE) using video-recording cameras was readied as part of the full-scale mockup development, and was deployed in L Basin for the initial condition assessment work. This report describes the development and the deployment of the VE for inspection of selected bundles in L Basin. The first deployment of the VE system was for visually examining five spent fuel bundles. Bundles were chosen based on their vulnerability in terms of inner fuel contents, history, storage duration, storage configuration, and possibility of inside out corrosion due to galvanic coupling of fuel cladding with the aluminum bundle wall.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRSDate not supplied

Mitigating Microbial Contamination Risks in CO 2 Removal Systems for Long-Duration Space Missions

Crewed missions to Mars and beyond pose new challenges for the crew and the technological solutions they depend upon. Crucial considerations in designing the next generation of Environmental Control and Life Support Systems (ECLSS) include enhanced reliability and autonomy, given the challenges of resupply and resource recovery in remote missions. One significant challenge faced in various sectors of the International Space Station and ECLSS is the phenomena of microbial growth, particularly biofilm formation. As such, microbial growth is a critical consideration in the design phase of new ECLSS systems. Two novel CO2 removal systems—Liquid-Amines CO2 Removal (LACR) and Cold-Surface CO2 Deposition (CDep)—are currently under development at the NASA Ames Research Center to meet the needs of extended space travel. In this presentation, the authors aim to make a risk assessment of microbial growth in LACR and CDep through: 1) a comprehensive literature review to identify LACR and CDep components most vulnerable to microbial contamination and 2) wet lab testing commencing with a subscale test of the most susceptible component of CDep. The literature review revealed that the hollow-fiber Liqui-Cel membrane employed in CDep exhibits the highest susceptibility to microbial growth. Our wet lab tests corroborated these findings, as airborne microbes introduced into the membrane led to considerable biomass accumulation. These results indicate a significant risk of microbial invasion into the membranes. To prevent microbial growth in CDep or other CO2 removal systems, proper ECLSS arrangement is essential—a CO2 removal system should remain behind the charcoal-HEPA filters, condensing heat exchanger, and Trace Contaminant Control System. In summary, anticipating potential microbial interactions within ECLSS for remote crewed missions is vital to mission success. It should, therefore, be included as one of the many factors when designing future ECLSS systems to perform reliably and consistently to support astronaut life.

A. Nicolas Whitlock↗

NASA NTRS2024

Severe droughts reduce river navigability and isolate communities in the Brazilian Amazon

The Amazon basin is experiencing severe droughts that are expected to worsen with climate change. Riverine communities are especially vulnerable to these extreme events. This study investigates the experiences of Brazilian Amazonian communities during droughts occurring from 2000-2020. We assess the distribution of settlements at risk of prolonged isolation during extreme low-water periods, along with impacts reported in digital news outlets. Using historic time series of river levels from 90 gauges, we look at how long droughts lasted in regions with reported impacts. Results indicate that the droughts in 2005, 2010, and 2016 were the most severe, with over an additional month of low water levels in those years. Such drought events routinely disrupt inland water transport and isolate local populations, limiting access to essential goods (food, fuel, medicine) and basic services (healthcare, education). Given this new reality, Amazon countries must develop long-term strategies for mitigation, adaptation, and disaster response.

Geography↗

NASA NTRS2024

San José Urban Development: Quantifying Canopy Cover and Land Surface Temperature in San José to Identify Future Tree Planting Sites

The urban heat island effect refers to the phenomenon of substantially increased temperatures in urban areas compared to their surrounding suburban or rural counterparts. The City of San José’s Department of Parks, Recreation and Neighborhood Services (PRNS) and Department of Transportation (DOT) work to mitigate the UHI effect through urban forestry initiatives. The PRNS and DOT partnered with NASA DEVELOP to identify areas in need of tree plantings. We examined land surface temperature (LST) throughout the city using data from the Thermal Infrared Sensor (TIRS) and TIRS-2 on NASA’s Landsat 8 and 9 satellites from 2013 to 2024. We also assessed canopy cover in parks using LiDAR data collected in 2020 for the United States Geological Survey’s 3D Elevation Program, and measured vegetation greenness using the Normalized Difference Vegetation Index (NDVI) with PlanetScope imagery from 2018 to 2024. We evaluated social and environmental factors that influence the distribution of heat event impacts by creating a heat vulnerability index. We found that heat is concentrated in urban areas and that poor vegetation health is associated with high LST. We also found that socially vulnerable communities are disproportionately located in areas of high environmental risk. These analyses allow the partners to prioritize tree plantings in parks near areas of high social and environmental risk. We determined that Earth observations can be used to inform urban forestry decision making, but because methodologies for using LiDAR to assess canopy cover vary greatly, it is difficult to make comparisons across different canopy cover assessments.

land surface temperature↗