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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

High Risk Spacecraft Materials Offgassing

NASA-STD-6001B, Determination of Offgassed Products (Test 7), provides the offgassing characteristics under standardized conditions for materials and assembled articles to be located within habitable spacecraft environments. Experience with Test 7 has found certain material types to be of higher risk for offgassing undesirable compounds aboard spacecraft than others. Formaldehyde and acrolein are historically high T value offgassed components of the offgassed compound target list because they have low spacecraft maximum allowable concentration (SMAC) values assigned by the JSC Toxicology Group. Carbon disulfide, benzene, acrylonitrile, and furan are additional target compounds of concern due to their lower thresholds of toxicity as determined by the JSC Toxicology Group. Materials offgassing siloxanes are also of concern due to their degradation effects on environmental control and life support system (ECLSS) components and performance. Spacecraft materials and articles defined in this manuscript as high risk were identified after examining and condensing data for these compounds of concern from approximately 3000 tests performed over 30 years. Summaries of high risk material and article types based on highest Multi-Purpose Crew Vehicle (MPCV) T values are also presented. Historical analysis shows high risk components are produced largely from test materials and articles in the general categories of electronic/powered components, foams, paints/coatings/films, adhesives/tapes, epoxy/resins, liquids/gels, Nomex® with surface treatments, markers/pens/inks, dry film lubricants, thermoplastics, hygiene items (deodorants, lip balms), and silicone rubber. These data are intended to be a resource for spacecraft materials and processes managers, designers, and toxicologists. High risk materials and articles intended for use aboard spacecraft should be tested in accordance with NASA-STD-6001B Test 7.

Vanessa D Buchanan↗

Assessment of atomic oxygen erosion of silver interconnects on Intelsat 6, F3

Intelsat 6 F-3 was launched from Cape Canaveral on a Titan 3 launch vehicle. Failure of the launch vehicle resulted in the satellite being marooned in Low Earth Orbit (LEO). During its sojourn in LEO, Intelsat 6 is exposed to an unanticipated environment consisting primarily of atomic oxygen, which will subject the unprotected silver interconnects (nominally 12.5 microns thick) on the solar panel to oxidation and erosion. Rescue by Space Shuttle is being examined. Consequently, Intelsat and Comsat have joined in an effort to determine the condition of the silver interconnects at the anticipated time of reboost and to assess the long term risks to the intended geostationary mission. Ground based tests, theoretical analysis, and a flight experiment aboard STS-41 were executed, and new software was written to calculate the expected total atomic oxygen fluence on the interconnects.

A. Dunnet↗

Fractal analysis of heart rate dynamics as a predictor of mortality in patients with depressed left ventricular function after acute myocardial infarction. TRACE Investigators. TRAndolapril Cardiac Evaluation

A number of new methods have been recently developed to quantify complex heart rate (HR) dynamics based on nonlinear and fractal analysis, but their value in risk stratification has not been evaluated. This study was designed to determine whether selected new dynamic analysis methods of HR variability predict mortality in patients with depressed left ventricular (LV) function after acute myocardial infarction (AMI). Traditional time- and frequency-domain HR variability indexes along with short-term fractal-like correlation properties of RR intervals (exponent alpha) and power-law scaling (exponent beta) were studied in 159 patients with depressed LV function (ejection fraction <35%) after an AMI. By the end of 4-year follow-up, 72 patients (45%) had died and 87 (55%) were still alive. Short-term scaling exponent alpha (1.07 +/- 0.26 vs 0.90 +/- 0.26, p <0.001) and power-law slope beta (-1.35 +/- 0.23 vs -1.44 +/- 0.25, p <0.05) differed between survivors and those who died, but none of the traditional HR variability measures differed between these groups. Among all analyzed variables, reduced scaling exponent alpha (<0.85) was the best univariable predictor of mortality (relative risk 3.17, 95% confidence interval 1.96 to 5.15, p <0.0001), with positive and negative predictive accuracies of 65% and 86%, respectively. In the multivariable Cox proportional hazards analysis, mortality was independently predicted by the reduced exponent alpha (p <0.001) after adjustment for several clinical variables and LV function. A short-term fractal-like scaling exponent was the most powerful HR variability index in predicting mortality in patients with depressed LV function. Reduction in fractal correlation properties implies more random short-term HR dynamics in patients with increased risk of death after AMI.

Non-NASA Center↗

Differential Drag Efficacy for Close Approach Remediation

Differential drag has become a viable alternative to propulsion for satellites to avoid collisions, but there is little guidance in the literature to aid mission designers in developing a differential drag capability that verifiably meets collision avoidance efficacy standards or requirements, if such requirements were to exist. This paper proposes a differential drag efficacy determination approach based on empirical conjunctions from the NASA Conjunction Assessment Risk Analysis historical database, focusing on energy dissipation rate and change in ballistic coefficient as the key satellite parameters correlated to efficacy. The data analysis informs the discussion toward adoption of recommended differential drag requirements. A case study is presented to walk through the process to determine efficacy of a proposed mission assuming several potential requirements.

conjunction remediation↗

Enhancing Risk Analysis of Accidental Release Using CFD Modeling and Machine Learning

This project report presents the results from the AU31 project that is entitled “Enhancing Risk Analysis of Accidental Release Using CFD Modeling and Machine Learning” performed between FY2021 and FY2022. The technical objective of this project is to enhance risk analysis of accidental release of radioactive materials and provide novel risk forecasting and capabilities for assessing unplanned hazardous chemical releases for the U.S. Department of Energy (DOE). The approach includes a cross-platform finite element analysis of airborne chemical release, machine learning (ML) for simulation and forecasting, and a big data approach to data management, transformation and analysis capable of handling petabyte-scale unstructured and structured data. The outcome of these findings were assembled and accessible as a final output via an intuitive web hosted geospatial-based user interface for demonstration and general dissemination. These new results also provide a mechanism of combining this knowledge in a risk analysis framework tool. The geospatial analysis and output can utilize 5 years of qualified meteorological data to illustrate projected plume footprints that are generated from computational aspects of this study. Specifically, we show the development of a geospatial risk analysis capabilities to respond to and plan for accidental release of radioactive materials and to provide a risk forecasting tool for assessing hazardous chemical releases for the DOE. The focus of this effort is germane to common practices in risk analysis; and it is highly relevant to the timely and transparent release of information related to materials at risk including hazardous materials and chemical vapors and rapid assessment of the potential impacts on the workforce at active sites across the DOE complex.

42 ENGINEERING↗

Moving Beyond Mortality: Development and Application of a Desirability of Outcome Ranking (DOOR) Endpoint for Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia

Abstract Background Hospital-acquired and ventilator-associated bacterial pneumonia (HABP/VABP) are frequently caused by multidrug-resistant organisms. Patient-centered endpoints in clinical trials are needed to develop new antibiotics for HABP/VABP. Desirability of outcome ranking (DOOR) is a paradigm for the design, analysis, and interpretation of clinical trials based on a patient-centered, benefit-risk evaluation. Methods A multidisciplinary committee created an infectious diseases DOOR endpoint customized for HABP/VABP, incorporating infectious complications, serious adverse events, and mortality. We applied this to 2 previously completed, large randomized controlled trials for HABP/VABP. ZEPHyR compared vancomycin to linezolid and VITAL compared linezolid to tedizolid. For each trial, we evaluated the DOOR distribution and probability, including DOOR component and partial credit analyses. We also applied DOOR in subgroup analyses. Results In both trials, the HABP/VABP DOOR demonstrated similar overall clinical outcomes between treatment groups. In ZEPHyR, the probability that a participant treated with linezolid would have a more desirable outcome than a participant treated with vancomycin was 50.2% (95% confidence interval [CI], 45.1%­−55.3%). In VITAL, the probability that a participant treated with tedizolid would have a more desirable outcome than a participant treated with linezolid was 48.7% (95% CI, 44.8%–52.6%). The DOOR component analysis revealed that participants treated with tedizolid had a less desirable outcome than those treated with linezolid when considering clinical response alone. However, participants with decreased renal function had improved overall outcomes with tedizolid. Conclusions The HABP/VABP DOOR provided more granular information about clinical outcomes than is typically presented in clinical trials. HABP/VABP trials would benefit from prospectively using DOOR.

Immunology↗

From Ensemble Climate to Ensemble Impacts

Many climate-risk tools rely on ensemble mean projections or endpoint climate snapshots to characterize future hazards. Although convenient for communication, these representations remove the statistical, temporal, and physical information that real infrastructure systems respond to. Infrastructure degradation and failure arise from extremes, sequences, cumulative stress, compound hazards, and nonlinear fragility relationships, none of which survive ensemble averaging or temporal compression. Power-system failure statistics and cascading failure models further show that infrastructure risk is dominated by tail events and path-dependent dynamics rather than by mean conditions. This paper demonstrates why ensemble mean or endpoint-only climate representations are mathematically and physically inconsistent with engineering-grade risk analysis. We outline a model-resolved, time-series-based workflow that preserves extremes, variability, and sequencing by propagating each climate-model realization independently through hazard formation, exposure, fragility, and cascading failure mechanisms. Taking the ensemble of impacts—rather than the ensemble of climate—provides a defensible, physically coherent foundation for infrastructure resilience planning, regulatory compliance, and long-term investment decisions.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗

Effect of Dietary Countermeasures and Impact of Gravity on Renal Calculi Size Distributions Predicted by PBE-System and PBE-CFD Models

Renal stone disease is not only a concern on earth but can conceivably pose a serious risk to the astronauts health and safety in Space. In this work, two different deterministic models based on a Population Balance Equation (PBE) analysis of renal stone formation are developed to assess the risks of critical renal stone incidence for astronauts during space travel. In the first model, the nephron is treated as a continuous mixed suspension mixed product removal crystallizer and the PBE for the nucleating, growing and agglomerating renal calculi is coupled to speciation calculations performed by JESS. Predictions of stone size distributions in the kidney using this model indicate that the astronaut in microgravity is at noticeably greater but still subcritical risk and recommend administration of citrate and augmented hydration as effective means of minimizing and containing this risk. In the second model, the PBE analysis is coupled to a Computational Fluid Dynamics (CFD) model for flow of urine and transport of Calcium and Oxalate in the nephron to predict the impact of gravity on the stone size distributions. Results presented for realistic 3D tubule and collecting duct geometries, clearly indicate that agglomeration is the primary mode of size enhancement in both 1g and microgravity. 3D numerical simulations seem to further indicate that there will be an increased number of smaller stones developed in microgravity that will likely pass through the nephron in the absence of wall adhesion. However, upon reentry to a 1g (Earth) or 38g (Mars) partial gravitational fields, the renal calculi can lag behind the urinary flow in tubules that are adversely oriented with respect to the gravitational field and grow agglomerate to large sizes that are sedimented near the wall with increased propensity for wall adhesion, plaque formation, and risk to the astronauts.

Renal Stones↗

Managing Technical and Cost Uncertainties During Product Development in a Simulation-Based Design Environment

An approach for objective and quantitative technical and cost risk analysis during product development, which is applicable from the earliest stages, is discussed. The approach is supported by a software tool called the Analytical System for Uncertainty and Risk Estimation (ASURE). Details of ASURE, the underlying concepts and its application history, are provided.

Karandikar, Harsh M.↗

Flexible Siting Criteria and Staff Minimization for Micro-Reactors

The economic potential of micro-reactors is vast and underestimated. Commonly-emphasized applications include niche markets such as remote communities, mines and military bases. However, micro-reactors could be used as flexible energy generators also for larger markets, such as mobile and containerized agriculture and manufacturing facilities, district heating, micro-grids for data centers, sea ports, airports and hospitals. The implication is that micro-reactors may have to be deployed also in non-remote locations. Successful implementation of micro-reactors needs a navigable and predictable licensing process, technology-appropriate siting restrictions, risk-informed emergency and safety requirements, and practical operating and maintenance requirements. The primary goal of this project was to develop siting criteria that are tailored to micro-reactors deployable in densely-populated areas, e.g., urban environments. To achieve that goal, we compared the characteristics of the MIT research reactor (MITR) with those of leading micro-reactor concepts (e.g., eVinci, USNC, Aurora), and evaluated whether and how the MITR design basis (e.g., inherent safety features, engineered safety systems, source term, emergency planning and emergency operating procedures) and associated regulations may be applicable to these new micro-reactors as well. What makes MITR a unique analogue in this context is its small power rating (6 MWt) and physical size, mode of operations (24/7 with a somewhat more commercial flavor than typical university reactors), and especially its urban location. Of course significant differences exist, such as mission (power production vs. research) and the reactor design itself. Leveraging the MITR experience, this project was able to generate criteria that will allow micro-reactors to realize their full economic potential as flexible heat and electricity generators for a diverse portfolio of applications in non-remote locations. As such, the outcome of this project might encourage investment in and use of micro-reactors. A second goal of the project was to conceptualize a model of operations for micro-reactors that would minimize the staffing requirements, and thus reduce the cost of electricity and heat generated by these systems. Here too our approach was to systematically review the MITR experience and requirements, as well as survey the innovations in autonomous control technologies and monitoring (e.g., advanced sensors, drones, robotics, AI) that would permit a dramatic reduction in staffing at future micro-reactor installations. The scope of work was expanded after the start date to include also an evaluation of micro-reactor security, using the so-called consequence-based analysis, and the development of a methodology to perform dynamic risk assessment for micro-reactors, using system theory and modeling and simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Review of Cybersecurity Risk and Consequences for Critical Infrastructure

This paper reviews the state of the art in risk assessment and consequences related to critical infrastructure. Different risk assessment methods are analyzed based on their goals, application domains, impacts, and consequences. This paper depicts an in-depth analysis of the existing risk assessment methods and highlights the advantages, and disadvantages associated with those methods. In addition, this paper also articulates the research challenges that are associated with developing an economically quantifiable risk assessment method or framework.

Touhiduzzaman, Md↗

Diversion Path Analysis: A Proposed Methodology to Develop an MC&A Approach for Liquid-Fueled Molten Salt Reactors

Nuclear material control and accounting (MC&A) is a critical element of both the US Nuclear Regulatory Commission (NRC) and US Department of Energy (DOE)’s domestic safeguards and security requirements. NRC licensees are required, under Title 10 of the Code of Federal Regulations (10 CFR) Part 74 to establish and maintain an MC&A program that captures and records the quantities and locations of special nuclear material (SNM) at the facility. Along with physical protection, MC&A is a key element of domestic nuclear material safeguards that enables the NRC to ensure that SNM is controlled and accounted for. SNM, per 10 CFR Part 74, refers to plutonium, 233 U, and uranium enriched in the isotope 233 U or 235 U, but does not include source material. Periodic physical inventories, coupled with material balance evaluations, are effective and demonstrated tools to account for and detect theft or diversion of SNM in facilities containing SNM in bulk material form (i.e., not in discrete, countable items). Historically in the United States, these types of facilities have included fuel fabrication, conversion, and enrichment facilities. In comparison, reactors have relied on item counting of assemblies and control of SNM while in containment (e.g., a sealed reactor pressure vessel) because, to date, reactor fuel has been in item form. In liquid-fueled molten salt reactors (MSRs), unlike traditional light water reactors (LWRs) or bulk facilities, bulk SNM quantities can change significantly during operation as a result of depletion and transmutation. This introduces challenges to the use of traditional periodic physical inventories and material balance evaluations to detect theft or diversion of SNM in reactors that use SNM in bulk material form. Liquid-fueled (i.e., salt-fueled) MSR facilities are MSRs that use SNM within a salt eutectic as the fuel. The SNM is in a bulk material form any time it is outside of fresh or spent fuel storage containers. Some examples of when SNM will be in bulk form in the facility are during addition of fuel to the reactor system, while fuel is circulating in operation, and while fuel is in a drain tank. Periodic physical inventories and material balance evaluations can likely be effectively applied to many portions of an MSR facility, including all areas where depletion and transmutation are not significantly changing the quantities of SNM within the control area. Within an MSR facility, this would include fresh fuel receipt and loading, waste streams that may contain SNM, irradiated fuel storage outside of the reactor core, and any irradiated fuel processing that may happen after SNM has been removed from the reactor. All of these process steps could rely on measurements of SNM quantities compared with documented inventories. Any discrepancies from predicted (i.e., book) inventories and measured inventories could be quantified as inventory differences, consistent with traditional MC&A guidance from the NRC (e.g., in NUREG-1065 Revision 2, NUREG-2159 Revision 1, and RG 5.29 Revision 2). Within the reactor system, additions and removals to the book inventory include depletion of the SNM (e.g., fission of 235 U), which complicates the use of physical inventories. SNM control, however, can also likely be effectively applied to detect theft of SNM throughout a liquid-fueled MSR facility. To complement these approaches, prior technical reports have identified that a diversion path analysis may be a useful, risk-informed, and performance-based tool to determine suitable elements of an MC&A approach for the reactor system within a liquid-fueled MSR facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Proteomic Tissue-Based Classifier for Early Prediction of Prostate Cancer Progression

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. Identification of biomarkers for early detection of aggressive disease is a key challenge. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we used targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. Sixteen proteins that differed significantly in an initial set of 105 samples were evaluated in the entire cohort (n = 338). A five-protein classifier which combined FOLH1, KLK3, TGFB1, SPARC, and CAMKK2 with existing clinical and pathological standard of care variables demonstrated significant improvement in predicting distant metastasis, achieving an area under the receiver-operating characteristic curve of 0.92 (0.86, 0.99, p = 0.001) and a negative predictive value of 92% in the training/testing analysis. This classifier has the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance.

60 APPLIED LIFE SCIENCES↗

SOSAT: Geohazard Risk Assessment in Carbon Sequestration Operations

Like all operations in which fluids are injected into the subsurface, geologic carbon storage (GCS) presents inherit risks that must be assessed and mitigated to successfully deploy such technology in the field. For example, alterations to pore pressure and the stress state due to fluid injection may trigger certain geohazards, such as potential fault activation and induced seismicity or unintentional hydraulic fracturing. Here we present capabilities for assessing these potential risks using the State of Stress Analysis Tool (SOSAT): a Python library and web-based application capable of probabilistically estimating the subsurface state of stress informed by various field observations. Using posterior distributions of principal stress components, SOSAT can assess the risk of fault activation within the injection formation for either a critically oriented fault or a fault with a user-prescribed orientation. Additionally, SOSAT can estimate the probability of unintentional hydraulic fracturing of the intact reservoir rock. Here, we demonstrate these SOSAT capabilities using a hypothetical GCS site. This type of risk assessment can assist with the effective deployment of GCS technology in the field by informing safe design and management practices.

Haagenson, Ryan J.↗

Simulation Assisted Risk Assessment Applied to Launch Vehicle Conceptual Design

A simulation-based risk assessment approach is presented and is applied to the analysis of abort during the ascent phase of a space exploration mission. The approach utilizes groupings of launch vehicle failures, referred to as failure bins, which are mapped to corresponding failure environments. Physical models are used to characterize the failure environments in terms of the risk due to blast overpressure, resulting debris field, and the thermal radiation due to a fireball. The resulting risk to the crew is dynamically modeled by combining the likelihood of each failure, the severity of the failure environments as a function of initiator and time of the failure, the robustness of the crew module, and the warning time available due to early detection. The approach is shown to support the launch vehicle design process by characterizing the risk drivers and identifying regions where failure detection would significantly reduce the risk to the crew.

Mathias, Donovan L.↗

Space Mission Human Reliability Analysis (HRA) Project

The purpose of the Space Mission Human Reliability Analysis (HRA) Project is to extend current ground-based HRA risk prediction techniques to a long-duration, space-based tool. Ground-based HRA methodology has been shown to be a reasonable tool for short-duration space missions, such as Space Shuttle and lunar fly-bys. However, longer-duration deep-space missions, such as asteroid and Mars missions, will require the crew to be in space for as long as 400 to 900 day missions with periods of extended autonomy and self-sufficiency. Current indications show higher risk due to fatigue, physiological effects due to extended low gravity environments, and others, may impact HRA predictions. For this project, Safety & Mission Assurance (S&MA) will work with Human Health & Performance (HH&P) to establish what is currently used to assess human reliabiilty for human space programs, identify human performance factors that may be sensitive to long duration space flight, collect available historical data, and update current tools to account for performance shaping factors believed to be important to such missions. This effort will also contribute data to the Human Performance Data Repository and influence the Space Human Factors Engineering research risks and gaps (part of the HRP Program). An accurate risk predictor mitigates Loss of Crew (LOC) and Loss of Mission (LOM).The end result will be an updated HRA model that can effectively predict risk on long-duration missions.

Boyer, Roger↗

Novel Approaches and Technologies for Aging Management

As part of the application process for license renewal and subsequent license renewal, nuclear utilities must perform an evaluation to confirm that they have appropriately considered aging effects on plant structures, systems, components within the scope of the license renewal. This effort within the Light Water Reactor Sustainability program’s Risk-informed System Analysis pathway is focused on risk-informed and performance-based approaches for aging management of buried piping, specifically managing selective leaching degradation phenomena. Selective leaching is a commonly occurring aging and degradation mechanism in buried pipes at nuclear power plants. To better understand the extent of selective leaching and its effect on the health of buried components, the licensees currently rely on visual inspections and destructive examinations which require extraction of multiple buried components. This research explores technological solutions that may replace or supplement existing inefficient, costly, and labor-intensive methods used in aging management.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Low-Temperature Geothermal Resources: Relevant Data and PFA Methods to Reduce Development Risk: Preprint

This project is part of a larger national effort focused on demonstrating the multi-faceted value of integrating low-temperature geothermal resources into national decarbonization strategies and community energy plans. Low-temperature geothermal resources are defined as reservoirs-natural or engineered-with temperatures < 150 degrees C. While the focus in the NREL effort is on geothermal heating and cooling (GHC), resources at the upper end of this temperature range can also be used for small-scale power generation. However, low-temperature geothermal resources have not been studied as extensively as higher-temperature geothermal resources. We identified three major classes of low-temperature geothermal play types: sedimentary basins, orogenic systems, and radiogenic systems. We developed workflows for evaluating the potential of these resources building off the Play Fairway Analysis (PFA) approach to de-risking geothermal exploration. This PFA-based approach to low-temperature geothermal resources includes: (1) identifying relevant data; (2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, economic criteria); (3) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and (4) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool. This project will facilitate future deployment of GHC by providing data, tools, and workflows applicable to low-temperature geothermal resources.

favorability maps↗