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At least 145 records · Page 8

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗

SEDONA SpEctroscopic Detection Of Nerve Agents

Although the threat of a liquid explosive attack on a passenger aircraft has been mitigated by limiting the size of carry-on bottles, highly potent chemicals (e.g., nerve agents) are a very serious threat. A single travel bottle full of such chemicals would cause great harm to many people and create a national security incident disrupting civilian air travel. Current screening methods to detect highly potent chemicals require opening a closed bottle. Experts at Los Alamos National Laboratory have developed SEDONA, a low magnetic field nuclear magnetic resonance (NMR) to detect chemical threats through unopened bottles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

X-Ray Energy Deposition Model for Simulating Asteroid Response to a Nuclear Planetary Defense Mitigation Mission

Abstract In the event of a potentially catastrophic asteroid impact, with sufficient warning time, deploying a nuclear device remains a powerful option for planetary defense if a kinetic impactor or other means of deflection proves insufficient. Predicting the effectiveness of a potential nuclear deflection or disruption mission depends on accurate multiphysics simulations of the device's X-ray energy deposition into the asteroid and the resulting material ablation. The relevant physics in these simulations span many orders of magnitude, require a variety of different complex physics packages, and are computationally expensive. Having an efficient and accurate way of modeling this system is necessary for exploring a mission's sensitivity to the asteroid's range of physical properties. To expedite future simulations, we present a completed X-ray energy deposition model developed using the radiation-hydrodynamics code Kull that can be used to initiate a nuclear mitigation mission calculation. The model spans a wide variety of possible mission initial conditions: four different asteroid-like materials at a range of porosities, two different source spectra, and a broad range of radiation fluences, source durations, and angles of incidence. Using blowoff momentum as the primary metric, the model-initiated simulation results match the full radiation-hydrodynamics results to within 10%.

79 ASTRONOMY AND ASTROPHYSICS↗

Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 degree incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval assimilation.

SMOS↗

Independent Review of the Proof-of-Concept Cyber100 Compass Cybersecurity Risk Tool

The U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER), and Office of Electricity (OE) commissioned the National Renewable Energy Laboratory (NREL) to develop a method and tool to enable electric utilities to understand and manage the risk of cybersecurity events that can lead to physical effects like blackouts. This tool, called Cyber100 Compass, uses cybersecurity data elicited from cybersecurity experts, then incorporates that data into a tool designed to be usable by cybersecurity non-experts who understand the system itself. The tool estimates dollar-valued risks for a current or postulated future electric power digital control configuration, in order to enable utility risk planners to prioritize among proposed cybersecurity risk mitigation options. With the development of the Cyber100 Compass tool for quantification of future cyber-physical security risks, NREL has taken an initial bold step in the direction of enabling and indeed encouraging electric utilities to address the potential for cybersecurity incidents to produce detrimental physical effects related to electric power delivery. As part of the Cyber100 Compass development process, DOE funded NREL to seek out an independent technical review of the risk methodology embodied in the tool. NREL requested this review from Sandia National Laboratories, and made available to Sandia a very late version of the project report, as well as NREL personnel to provide clarification and to respond to questions. This paper provides the result of the independent review activity.

97 MATHEMATICS AND COMPUTING↗

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

Learning from Past Experiences

Space flight is a risky business. This truism has been bandied about since the earliest days of the space program. When asked by the young daughter of a coworker, one of the Mercury astronauts likened launching into space to "riding a Roman candle" -- it was both exciting and dangerous. Even in these more technologically advanced days, the solid rocket boosters and external tanks of the space shuttle provide a no less exciting, or dangerous, ride into space. However much the phrase "risk mitigation" is bandied about within the U.S. space program, there is still the history of the Apollo 1 fire during a ground test at Cape Canaveral, Fla., the loss of the shuttle Challenger during liftoff, and the loss of the shuttle Columbia when returning to Earth to remind us that while we give lip-service to risk management, we have not learned to manage risk as well as we ought. Moreover, there are many more less dramatic, but equally critical, incidents that have occurred in association with the space program that also highlight our inability to accurately gauge and manage risk. Why do we seem caught in a senseless spiral in which we focus most on risk only after a tragedy? Why do we repeat serious mishaps and not learn from our mistakes? This paper reviews some possible explanations for our risk-taking behavior and provides examples of interest to the NASA centers, while also discussing inter center and intra-center opportunities for sharing information to mitigate risk.

Hulet, Michael W.↗

Large Solar-Rejection Filter

NASA utilized Image Intensified Video Cameras for ATV data acquisition from a jet flying at 12.8 km. Afterwards the video was digitized and then analyzed with a modified commercial software package, Image Systems Trackeye. Astrometric results were limited by saturation, plate scale, and imposed linear plate solution based on field reference stars. Time-dependent fragment angular trajectories, velocities, accelerations, and luminosities were derived in each video segment. It was evident that individual fragments behave differently. Photometric accuracy was insufficient to confidently assess correlations between luminosity and fragment spatial behavior (velocity, deceleration). Use of high resolution digital video cameras in future should remedy this shortcoming. A scenically accurate description of matter interpreted as a substance made up of corpuscular constituents was established during the course of the 19th century. In this description, atoms--the building blocks of the matter--form molecules. The properties of the molecules were described by chemistry or thermodynamics depending on what characteristics of the matter were investigated. In both theories, the molecules can dissociate to atoms when the kinetic energies of the atoms exceed the strength of the chemical bonds. The number of atoms is always preserved in a closed system. This is not true, however, when the matter takes up much higher energies at relativistic scales. New particles can be produced at the expense of the kinetic energy. The number of particles is no longer preserved. There are other conserved quantities, however, these quantities, the charge, baryon number, lepton number, are associated with particles that are considered elementary today. The properties and behavior of these elementary particles is the subject of Particle Physics or High Energy Physics. Practice Page: A crewmember touching a positively charged surface was thought to be galvanically isolated from the vehicle ground analogous to a bird on a high voltage power wire. Recent analysis confirms that positive floating potentials, ionospheric currents to the EVA suit, can be hazardous. The analysis is wrong in that the ionospheric plasma itself can close the circuit. Parametric analysis of very low voltage exposures (2 to 15 volts) could cause pain and/or involuntary muscle tetani or spinal cord shock. NASA worked with the Naval Health Research Center Detachment Directed Energy Bioeffects Laboratory to examine the affects electrical hazards could have on extravehicular activity using two models. The results of the two computational models were combined to predict areas of the body in which neurons of different diameters would be excited. They predicted that physiologically active current could be conducted across the crew member causing catastrophic hazards. Future work to analyze additional current paths was proposed. The FUSE spectrum of BB Dor, observed in a high state, is modeled with an accretion disk with a very low inclination (possibly lower than 10 degrees). Assuming an average WD mass of 0.8 solar mass leads to a distance of the order of approximately 650pc, consistent with the extremely low galactic reddening in its direction, and a mass accretion rate of 10 (exp -9) solar mass a year. The spectrum presents some broad and deep silicon and sulfur absorption lines, indicating that these elements are over-abundant: silicon is 3 times solar, and sulfur is 20 times solar. The FUSE spectrum of BB Dor, observed in a high state, is modeled with an accretion disk with a very low inclination (possibly lower than 10 degrees). Assuming an average WD mass of 0.8 solar mass leads to a distance of the order of approximately 650pc, consistent with the extremely low galactic reddening in its direction, and a mass accretion rate of 10 (exp -9) solar mass a year. The spectrum presents some broad and deep silicon and sulfur absorption lines, indicating that these elements are over-abundant: silicon is times solar, and sulfur is 20 times solar. From its previously observed optical emission lines, P831-57 (WD 0334 6400 or Ret 1 in A Catalog and Atlas of Cataclysmic Variables: Living Edition) has been suspected to contain an accretion disk associated with a companion star in orbit around a subdwarf star with a temperature T is greater than 21,000K. P831-57 has therefore been classified as a nova-like. However, our present observations show it to be a DA + dMe binary. The analysis of its Far Ultraviolet Spectroscopic Explorer (FUSE) spectrum (continuum and lines) reveal an average mass white dwarf (Log(g) approximately equals 7.8 plus or minus 0.1)with a temperature T approximately equals 37,000 plus or minus 500K, an extremely low projected rotational velocity, and a distance of about 115 plus or minus 5pc. The photosphere contains C, N, Si, and S (at about 1% of solar abundances). The dMe star is seen as a flux excess in near-infrared photometry and appears to show occasional flaring of about one magnitude as seen in the Harvard plates. There is no evidence of periodic variability in the spectroscopic or photometric data. We find no evidence of a an accretion disk, instead we find evidence of wind accretion as the stellar carbon abundance (N(C)/N(H) = 2.5 x 10 (exp -6) is about ten times larger than predicted by radiative levitation for such a gravity and temperature. The power needs and solutions for the space exploration and lunar mobility program are discussed. Long term missions in space and on the lunar surface require high energy batteries. Rechargeable batteries for mobility systems and portable utility pallet are needed for successful exploration missions. Nanomaterial usage increases the energy density of the cells apart from increasing the power density. The symptoms and threats from acute mountain sickness (AMS) are discussed. The underlying assumptions concerning spacecraft atmosphere mean there is a potential risk to astronauts. The baseline worst case scenario is about 25% based on direct ascent to 8.0 psia with 32% O2. The practical mitigation approach is a staged depressurization scheme. Due to the uncertainty about potential AMS risk the flight surgeon should prepare, focused research should proceed, and current analytical efforts should continue. This slide presentation reviews the threat astronauts face from acute mountain sickness (AMS). The incidence of AMS is highly variable and the risk to astronauts is unclear. However, the potential risk is higher than current EAAs suggest and precautions should be implemented. Due to the uncertain nature of the risk flight surgeons should prepare, and focused research should proceed. Quasiparticle tunneling can be understood at low temperatures using a non-equilibrium kinetic theory. Low-temperature tunneling can be suppressed using existing techniques: island-lead gap engineering, lead cooling with SIN junctions, and quasiparticle traps. The slide presentation reviews the science goals and mission planning for the proposed Jupiter System Observer (JSO). The spacecraft would accommodate 9 instruments making the instrument payload more capable than any previously flown to Jupiter. The would-be mission includes study programs for Jupiter's satellites, interior, magnetosphere and atmosphere. The power needs and solutions for the space exploration and lunar mobility program are discussed. Long term missions in space and on the lunar surface require high energy batteries. Rechargeable batteries for mobility systems and portable utility pallet are needed for successful exploration missions. Nanomaterial usage increases the energy density of the cells apart from increasing the power density. This slide presentation reviews the power requirements for the space exploration and the lunar surface mobility programs. It includes information about the specifications for high energy batteries and the power requirements for lunar rovers,

Roberts, William↗

Observations of C-Band Brightness Temperature and Ocean Surface Wind Speed and Rain Rate in Hurricanes Earl And Karl (2010)

Ocean surface emission is affected by: a) Sea surface temperature. b) Wind speed (foam fraction). c) Salinity After production of calibrated Tb fields, geophysical fields wind speed and rain rate (or column) are retrieved. HIRAD utilizes NASA Instrument Incubator Technology: a) Provides unique observations of sea surface wind, temp and rain b) Advances understanding & prediction of hurricane intensity c) Expands Stepped Frequency Microwave Radiometer capabilities d) Uses synthetic thinned array and RFI mitigation technology of Lightweight Rain Radiometer (NASA Instrument Incubator) Passive Microwave C-Band Radiometer with Freq: 4, 5, 6 & 6.6 GHz: a) Version 1: H-pol for ocean wind speed, b) Version 2: dual ]pol for ocean wind vectors. Performance Characteristics: a) Earth Incidence angle: 0deg - 60deg, b) Spatial Resolution: 2-5 km, c) Swath: approx.70 km for 20 km altitude. Observational Goals: WS 10 - >85 m/s RR 5 - > 100 mm/hr.

Miller, Timothy↗

NASA's Human Research Program at The Glenn Research Center: Progress and Opportunities

The NASA Human Research Program is aimed at correcting problems in critical areas that place NASA human spaceflight missions at risk due to shortfalls in astronaut health, safety and performance. The Glenn Research Center (GRC) and partners from Ohio are significant contributors to this effort. This presentation describes several areas of GRC emphasis, the first being NASA s path to creating exercise hardware requirements and protocols that mitigate the effects of long duration spaceflight. Computational simulations will be a second area that is discussed. This includes deterministic models that simulate the effects of spaceflight on the human body, as well as probabilistic models that bound and quantify the probability that adverse medical incidents will happen during an exploration mission. Medical technology development for exploration will be the final area to be discussed.

Nall, Marsha↗

Cyber Threat Landscape and Engineering Mitigations for Grid Forming Inverters

This talk will cover the cyber threat landscape and engineering mitigations for grid forming (GFM) inverters. It will discuss the penetration of inverter-based resources (IBRs) in the United States and expected growth. It will then discuss the threat landscape for IBRs based on current and expected penetration. Real-world examples of cyber incidents affecting IBRs will be presented, concluding with an introduction to Cyber-Informed Engineering (CIE) and a guide on applying it to GFM inverters.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Supporting Hazard Analysis for Wildfire Response Using fmdtools and MIKA

The System Wide Safety (SWS) Safety Demonstrator (SD) Series drives development of an increasingly capable In-Time Aviation Safety Management System (IASMS) focusing on humanitarian applications, starting with wildfire response (SD-1). The goals of this report are to (1) provide an early hazard analysis and mitigation evaluation of wildfire response to support these efforts and (2) provide a demonstration of capabilities of the Fault Model Design Tools (fmdtools) and Manager for Intelligent Knowledge Access (MIKA) tools. fmdtools provides a modeling, simulation, and resiliency analysis framework in which a wildfire response model, the System Modeling and Analysis of Resiliency in Scalable Traffic Management for Emergency Response Operations (SMARt-STEReO), is built. MIKA is an intelligent knowledge manager with several capabilities, including assisting in hazard analysis by extracting and analyzing hazards from historical incident reports. The following topics are covered in the report: Understanding Wildfire Hazard Dynamics. We provide a description and simulated examples of how hazards occur in the SMARt-STEReO model of wildfire response and their effect on its outcome. This provides a common mental model and focuses the analysis presented in the remainder of the report. Wildfire Hazard Identification. MIKA identifies wildfire hazards from three relevant datasets: the ICS-209-PLUS, SAFECOM, and SAFENET. Hazards are manually organized into a taxonomy and MIKA analyzes each hazard’s effects, likelihood, severity, and risk. Evaluating Mitigation Strategies. The SMARt-STEReO wildfire response model built in fmdtools evaluates a subset of identified hazards. Specifically, we simulate the effect of communications faults and equipment faults on operator safety, the effect of changing winds and flammability, and a scenario with multiple ignition points and heavy smoke. Tool Limitations and Usage Considerations. We provide a discussion of appropriate tool use cases as well as limitations and considerations for usage. The tool findings are used to synthesize recommendations for wildfire response operations, which can be captured as part of an IASMS. Key recommendations are as follows: Hazards are identified from a broad spectrum of sources including aircraft subsystems, operational sources, and ground crew operations. Highest risk operational environment hazards identified are Evacuations. The highest risk manned aerial operations hazard categorized is Jumper Operations Mishap. Ground crew hazards that are highest risk are Burns, Cargo Operations Overhead, Dehydration, Entrapment, Falling Objects, Heart Attacks, Heat Exhaustion, Inadequate Training or Certification, Vehicle Breakdown, and Vehicle Collision. Modelled containment failures arise from a mismatch between the difficulty of the firefighting scenario and the capacity (e.g., speed, effectiveness, awareness) of the response. In firefighting scenarios where containment is possible (e.g., because the fire does not spread too quickly), these mismatches can occur because of a change in environmental conditions (e.g., wind, flammability, etc) or because of planning, equipment, or communications faults. Improvements to communications increase the capacity of the firefighting response by reducing the time needed to respond to the fire. While surveillance does not increase this capacity by itself, it increases operator safety by increasing state awareness, enabling firefighters to evade approaching fires. Increasing both has a synergistic effect. In general, these performance and resilience increases generalize over fault scenarios as well as unforeseen changes to circumstances (i.e., wind, aridity, etc.). However, these improvements need to be designed so as not to make the system prone to persistent large-scale communications outages, which can reduce performance.

Hazard analysis↗

AI-Guided Reasoning-Based Operator Support System for the Nuclear Power Plant Management

The Decision-making process in the Nuclear Power Plant (NPP) control room faces some challenges: operator incomplete knowledge, insufficient time for responding to the highly dynamic events, and a large number of indicators to monitor. Because of the complexity of the NPP system, it is hard to pre-plan all the failures/mitigative actions. An intelligent operator support system is vital to mitigate these shortcomings. In this paper, an AI declarative approach (Answer Set Programming (ASP)) is employed to represent our knowledge of the nuclear power plant in the form of logic rules. This represented knowledge is structured to form a reasoning-based operator support system. When an incident occurs, this ASP-based reasoning support system is demonstrated to be capable of fault identification (diagnosis), informing the operator of different scenarios and consequences, and generating the control options (decision making).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Performance of Graphene/Polydimethylsiloxane Surfaces against S. aureus and P. aeruginosa Single- and Dual-Species Biofilms

The increasing incidence of implant-associated infections has prompted the development of effective strategies to prevent biofilm formation on these devices. In this work, pristine graphene nanoplatelet/polydimethylsiloxane (GNP/PDMS) surfaces containing different GNP loadings (1, 2, 3, 4, and 5 wt%) were produced and evaluated on their ability to mitigate biofilm development. After GNP loading optimization, the most promising surface was tested against single- and dual-species biofilms of Staphylococcus aureus and Pseudomonas aeruginosa. The antibiofilm activity of GNP/PDMS surfaces was determined by the quantification of total, viable, culturable, and viable but nonculturable (VBNC) cells, as well as by confocal laser scanning microscopy (CLSM). Results showed that 5 wt% GNP loading reduced the number of total (57%), viable (69%), culturable (55%), and VBNC cells (85%) of S. aureus biofilms compared to PDMS. A decrease of 25% in total cells and about 52% in viable, culturable, and VBNC cells was observed for P. aeruginosa biofilms. Dual-species biofilms demonstrated higher resistance to the antimicrobial activity of GNP surfaces, with lower biofilm cell reductions (of up to 29% when compared to single-species biofilms). Still, the effectiveness of these surfaces in suppressing single- and dual-species biofilm formation was confirmed by CLSM analysis, where a decrease in biofilm biovolume (83% for S. aureus biofilms and 42% for P. aeruginosa and dual-species biofilms) and thickness (on average 72%) was obtained. Overall, these results showed that pristine GNPs dispersed into the PDMS matrix were able to inhibit biofilm growth, being a starting point for the fabrication of novel surface coatings based on functionalized GNP/PDMS composites.

Oliveira, Isabel M.↗

Hybrid target design for imprint mitigation in direct-drive inertial confinement fusion

A target design for mitigating the Rayleigh-Taylor instability is proposed for use in high energy density and direct-drive inertial confinement fusion experiments. In this scheme, a thin gold membrane is offset from the main target by several-hundred microns. A strong picket on the drive beams is incident upon this membrane to produce x rays which generate the initial shock through the target. The main drive follows shortly thereafter, passing through the ablated shell and directly driving the main target. The efficacy of this scheme is demonstrated through experiments performed at the OMEGA EP facility, showing a reduction of the Rayleigh-Taylor instability growth which scales exponentially with frequency, suppressing development by at least a factor of 5 for all wavelengths below 100 μm. Furthermore, this results in a delay in the time of target perforation by ~40%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Farmers’ Perception of Climate Change and Its Impacts on Agriculture

Climate change and climate variability drive rapid glacier melt and snowpack loss, extreme precipitation and temperature events, and alteration of water availability in the Himalayas. There is increasing observational evidence of climate change impacts on water resource availability and agricultural productivity in the central Himalayan region. Here, we assess the farmers’ perception of climate change and its impacts on agriculture in western Nepal. We interviewed 554 households and conducted eight focus group discussions to collect farmers’ perceptions of temperature and rainfall characteristics, water availability, onset and duration of different seasons, and the impacts of such changes on their lives and livelihoods. Our results indicate that the farmers’ perceptions of rising annual and summer temperatures are consistent with observations. Perception, however, contradicts observed trends in winter temperature, as well as annual, monsoon, and winter precipitation. In addition, farmers are increasingly facing incidences of extreme events, including rainfall, floods, landslides, and droughts. These hazards often impact agricultural production, reducing household income and exacerbating the economic impacts on subsistence farmers. Integrated assessment of farmers’ perceptions and hydrometeorological observations is crucial to improving climate change impact assessment and informing the design of mitigation and adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗

An Overview of the NASA Aviation Safety Program Propulsion Health Monitoring Element

The NASA Aviation Safety Program (AvSP) has been initiated with aggressive goals to reduce the civil aviation accident rate, To meet these goals, several technology investment areas have been identified including a sub-element in propulsion health monitoring (PHM). Specific AvSP PHM objectives are to develop and validate propulsion system health monitoring technologies designed to prevent engine malfunctions from occurring in flight, and to mitigate detrimental effects in the event an in-flight malfunction does occur. A review of available propulsion system safety information was conducted to help prioritize PHM areas to focus on under the AvSP. It is noted that when a propulsion malfunction is involved in an aviation accident or incident, it is often a contributing factor rather than the sole cause for the event. Challenging aspects of the development and implementation of PHM technology such as cost, weight, robustness, and reliability are discussed. Specific technology plans are overviewed including vibration diagnostics, model-based controls and diagnostics, advanced instrumentation, and general aviation propulsion system health monitoring technology. Propulsion system health monitoring, in addition to engine design, inspection, maintenance, and pilot training and awareness, is intrinsic to enhancing aviation propulsion system safety.

Simon, Donald L.↗

Leveraging AI and Spatial Data to Unlock Pipeline Integrity Insights: NETL’s Advanced Infrastructure Integrity Model (AIIM)

Maintaining the integrity of natural gas infrastructure plays a critical role in ensuring energy security. Robust, data-driven foundational AI models for pipeline integrity can help address risk management and mitigation issues. Trusted foundational models can help with industry adoption and accelerate innovation by enhancing integrity predictions, reduce costs, and informing infrastructure build-out. The AIIM dashboard was released in 2022 and utilizes multi-ML models for ensemble-type insights. It was expanded to include analytics on reported incidents. It was developed as an ESRI Dashboard to support data visualization & interrogation and contains pipeline data and model results.

Advanced Infrastructure Integrity Model (AIIM)↗