Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Risk Model”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Enter Gaussian Mixture Modeling Extensions for Improved False Discovery Rate Estimation in GC-MS Metabolomics

Identifying small molecules (e.g., metabolites) is key towards driving scientific advancement in metabolomics, and gas chromatography–mass spectrometry (GC-MS) is an analytic method that may be applied to facilitate this process. The typical GC-MS identification workflow involves quantifying the similarity of an observed sample spectrum and other features (e.g. retention index) to that of several references, noting the compound of the best-matching reference spectrum as the identified metabolite. While a deluge of similarity metrics exists, none characterize the error rate of generated identifications, thereby presenting an unknown risk of false identification or discovery. To quantify this unknown risk, we propose a model-based framework for estimating the false discovery rate (FDR) among a set of identifications. Extending the traditional mixture modeling framework, our method incorporates both similarity score and experimental information in estimating the FDR. We apply these models to identification lists derived from across 548 samples of varying complexity and sample type (e.g., fungal species, standard mixtures, etc.), comparing their performance to that of the traditional Gaussian mixture model (GMM). Through simulation, we additionally assess the impact of reference library size on the accuracy of FDR estimates. In comparing the best performing model extensions to the GMM, our results indicate relative decreases in median absolute estimation error (MAE) ranging from 12% to 70%, based on comparisons of the median MAEs across all hit-lists. Results indicate that these relative performance improvements generally hold despite library size, however FDR estimation error typically worsens as the set of reference compounds diminishes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw: Modeling Archive

This Modeling Archive is in support of a NGEE Arctic publication in review "Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw". The study used a cryohydrology model to assess the potential risk of abrupt permafrost thaw triggered by melting ground ice, a key open question associated with permafrost response to a warming Arctic. The spatially resolved simulations are for a small catchment 465 ice-wedge polygons in polygonal tundra near Utqiagvik, Alaska in the high-emissions RCP8.5 climate scenario. The simulations are compared to runoff, evapotranspiration and subsidence in the current climate and agree well. The study used the ATS code configured as an intermediate-scale cryohydrology model (Advanced Terrestrial Simulator, Version v2). The archive includes input files for spinup (1985 to 2005) and projections (2006 to 2100 - the manuscript reports 2006 to 2098). Three of the projections include the effects of subsidence and microtopography change with different depth profiles of ice content corresponding to the median, 20th percentile and 80th percentile. The fourth projection has subsidence turnoff and uses the reference case (median) ice content. Spatially averaged or aggregated output variables are included for the projections. Selected checkpoint files for the projections and postprocessing scripts are also included. Files included are *.xml; *.h5; *.exo; *.py; *.sh, *. nb, mesh files, and one file in the original Excel format plus *.csv and *.pdf to conserve formatting contained in the original file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Assessing the Health and Performance Risks of Reduced Carbon Dioxide Exposures and Resource Utilization

There have been a cluster of anecdotal reports that ISS crews are experiencing adverse health effects from on orbit exposure to CO2 levels well below the current Spacecraft Maximum Allowable Concentration (SMAC), which is 5.3 mmHg for 180 days of exposure. Developing evidence that this standard should be reduced to protect crew health is not a simple process. Dr. John James' team looked at the reports of headaches by the crew during private medical conferences and matched these with CO2 levels around the time of these reports. They then compared these to CO2 levels when there were no reports of headache. Using benchmark dose modeling, they found that the risk of headache could be predicted in concentration ranges from 2 to 5 mmHg. However, the data are incomplete because there were insufficient data when crews were exposed to concentrations below 2 mmHg. James' team also asked whether neuro-cognitive effects could be identified with CO2 exposure levels and found that these could not be associated with CO2 levels. Finally, they addressed the question of resource use to meet various levels of CO2 control if the SMACs were lowered. They estimated that CO2 restrictions approaching 2 mmHg would require substantial increases in power use and up-mass resources. They are refining their data on CO2 and headaches, and are looking at potential interactions of intracranial pressure and CO2 levels in eliciting ocular effects.

James, John T.↗
NASA NTRS2000

Forecasting disease risk for increased epidemic preparedness in public health

Emerging infectious diseases pose a growing threat to human populations. Many of the world's epidemic diseases (particularly those transmitted by intermediate hosts) are known to be highly sensitive to long-term changes in climate and short-term fluctuations in the weather. The application of environmental data to the study of disease offers the capability to demonstrate vector-environment relationships and potentially forecast the risk of disease outbreaks or epidemics. Accurate disease forecasting models would markedly improve epidemic prevention and control capabilities. This chapter examines the potential for epidemic forecasting and discusses the issues associated with the development of global networks for surveillance and prediction. Existing global systems for epidemic preparedness focus on disease surveillance using either expert knowledge or statistical modelling of disease activity and thresholds to identify times and areas of risk. Predictive health information systems would use monitored environmental variables, linked to a disease system, to be observed and provide prior information of outbreaks. The components and varieties of forecasting systems are discussed with selected examples, along with issues relating to further development.

Disease Outbreaks↗
DOE OSTI2022

NRAP-Open-IAM: NRAP Open Source Integrated Assessment Model

Note: This is the last version (a2.6.1) of NRAP-Open-IAM released during NRAP Phase II in 2022. The latest version of NRAP-Open-IAM is available here: https://edx.netl.doe.gov/dataset/phase-iii-nrap-open-iam NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability. NRAP-Open-IAM represents the next-generation in a line of systems-based computational models developed for quantitative geological carbon storage (GCS) risk assessment. The model comprises a set of reduced-order and analytical models of various components of the GCS system, potential leakage pathways, receptors of concern including impact to groundwater resources and the atmosphere, a framework to support stochastic simulation, time stepping, uncertainty quantification, other analytical functionality for scenario and risk-performance evaluation, and a basic graphical user interface to support scenario development, data input simulation definition, and basic post-processing and results display. As the NRAP Open-IAM functionality continues to evolve, we continue to add to its capability to develop quantitative, probabilistic, and time-dependent profiles of the evolution of risk at a GCS site and evaluate the influence of uncertain parameters on uncertainty in predicted risk. It can be used to quantify the dynamics of reservoir saturation plume and pressure-affected area, for evaluation of the area of potential groundwater impact (i.e., Area of Review) and monitoring requirements to support cost and regulatory analysis, and for consideration of different post-injection site care and closure scenarios. This submission contains the current version of NRAP-Open-IAM available for evaluation and testing. To use the NRAP-Open-IAM, download the source code (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/4c24a3da-3b40-4ffe-9892-c807ae9f8760) then open the NRAP-Open-IAM user's guide (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669) to read more about the tool. Installation instructions for Windows, Mac, and Linux can be found in the "installers" folder of the extracted NRAP-Open-IAM folder and describe setup of environment (e.g., Python libraries) needed for proper work of the tool. Test of installation can be done by running "python openiam_setup_tests.py" in the "setup" folder. The installation test also runs a test suite to see if the NRAP-Open-IAM has been installed correctly. To run the test suite separately, run "python iam_test.py" in the "test" folder. User's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669 Developer's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/3bc6ee7d-609d-4eb6-80ba-fa6130ee0313 Reservoir simulation data used in some examples distributed with NRAP-Open-IAM: - Kimberlina: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/eb62cece-61b2-4037-9b6d-32407dde2ab8 - Kimberlina (compartmentalized): https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/366f9530-3b32-4b84-affe-ab2df1d9a8b5 - FutureGen 2.0: https://edx.netl.doe.gov/dataset/futuregen-2-0-1008-simulation-reservoir-lookup-table NRAP-Open-IAM GitLab repository: https://gitlab.com/NRAP/OpenIAM Related publications: - Bacon, D., Yonkofski, C., Brown, C., Demirkanli, D. and Whiting, J., 2019. Risk-based post injection site care and monitoring for commercial-scale carbon storage: Reevaluation of the FutureGen 2.0 site using NRAP-Open-IAM and DREAM. International Journal of Greenhouse Gas Control 90: 102784. - Bacon, D. Demirkanli, D., and White, S., 2020. Probabilistic risk-based Area of Review (AoR) determination for a deep-saline carbon storage site. International Journal of Greenhouse Gas Control 102: 103153. - Harp, D., Oldenburg, C., and Pawar, R., 2019. A metric for evaluating conformance robustness during geologic CO2 sequestration operations. International Journal of Greenhouse Gas Control 85: 100-108. - Lackey, G., Vasylkivska, V., Huerta, N., King, S., and Dilmore, R., 2019. Managing well leakage risks at a geologic carbon storage site with many wells, International Journal of Greenhouse Gas Control, 88 :182-194. - Vasylkivska, V., Dilmore, R., Lackey, G., Zhang, Y., King, S., Bacon, D., Chen, B., Mansoor, K., and Harp, D., 2021. NRAP-Open-IAM: A flexible open-source integrated assessment model for geologic carbon storage risk assessment and management, Environmental Modelling & Software, 143: 105114. Presentations: - Chen, B., Harp, D., and Pawar, R., A data assimilation approach (ES-MDA) coupling with NRAP-Open-IAM for quantifying uncertainty reduction in geological CO2 sequestration. AGUFM 2019: T44A-02. - Chen, B., and Harp, D., Improving risk analysis precision for geologic CO2 sequestration by quantifying the uncertainty reduction before and after acquiring monitoring data. 14th Greenhouse Gas Control Technologies Conference, Melbourne, Australia, 2018, pp. 21-26. - Harp, D., National Risk Assessment Partnership Task 2: Containment Assurance. No. LA-UR-19-28654, Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2019. - Vasylkivska, V., King, S., Bacon, D., Harp, D., Chen, B., Mansoor, K., Onishi, T., Yang, Y., Zhang, Y., and Keating, E., NRAP-Open-IAM: An open-source integrated assessment model, poster, Mastering the Subsurface Through Technology Innovation, Partnerships and Collaboration: Carbon Storage and Oil and Natural Gas Technologies Review Meeting, Pittsburgh, PA, August 13-16, 2018. - Vasylkivska, V., Lackey, G., King, S., Wentworth, A., Huerta, N., Creason, C., DiGiulio, J., Yang, Y., and Dilmore, R., Long-term risk analysis of a geologic CO2 storage project during the post-injection period, SIAM Conference on Computational Science and Engineering, Spokane, WA, February 25-March 1, 2019. - Vasylkivska, V., Overview of the NRAP-Open-IAM tool for carbon storage (beta release), 2019 Annual NRAP Tool Users Meeting, Pittsburgh, PA, August 27, 2019. - Vasylkivska, V., Bacon, D., Chen, B., Dilmore, R., Harp, D., King, S., Lackey, G., Lindner, E., Liu, G., Mansoor, K. and Zhang, Y., NRAP-Open-IAM: A new, open-source code for integrated assessment of geologic carbon storage containment effectiveness and leakage risk, poster, American Geophysical Union Fall Meeting 2020 (virtual meeting), December 2020. - Vasylkivska, V., NRAP open-source integrated assessment model and relevant application, oral presentation, NRAP workshop "NRAP Tools for Geologic Carbon Storage Risk-Based Decision Making" held in conjunction with Groundwater Protection Council (GWPC) 2021 Annual Forum (virtual meeting), Salt Lake City, UT, September 2021. - Vasylkivska, V., NRAP-Open-IAM: open-source integrated assessment model, digital poster/demonstration, software demonstration session, 2022 Carbon Management Project Review Meeting, August 16, 2022

AoR↗
NASA NTRS1999

Three-Dimensional, Transgenic Cell Models to Quantify Space Genotoxic Effects

The space environment contains radiation and chemical agents known to be mutagenic and carcinogenic to humans. Additionally, microgravity is a complicating factor that may modify or synergize induced genotoxic effects. Most in vitro models fail to use human cells (making risk extrapolation to humans more difficult), overlook the dynamic effect of tissue intercellular interactions on genotoxic damage, and lack the sensitivity required to measure low-dose effects. Currently a need exists for a model test system that simulates cellular interactions present in tissue, and can be used to quantify genotoxic damage induced by low levels of radiation and chemicals, and extrapolate assessed risk to humans. A state-of-the-art, three-dimensional, multicellular tissue equivalent cell culture model will be presented. It consists of mammalian cells genetically engineered to contain multiple copies of defined target genes for genotoxic assessment,. NASA-designed bioreactors were used to coculture mammalian cells into spheroids, The cells used were human mammary epithelial cells (H184135) and Stratagene's (Austin, Texas) Big Blue(TM) Rat 2 lambda fibroblasts. The fibroblasts were genetically engineered to contain -a high-density target gene for mutagenesis (60 copies of lacl/LacZ per cell). Tissue equivalent spheroids were routinely produced by inoculation of 2 to 7 X 10(exp 5) fibroblasts with Cytodex 3 beads (150 micrometers in diameter). at a 20:1 cell:bead ratio, into 50-ml HARV bioreactors (Synthecon, Inc.). Fibroblasts were cultured for 5 days, an equivalent number of epithelial cells added, and the fibroblast/epithelial cell coculture continued for 21 days. Three-dimensional spheroids with diameters ranging from 400 to 600 micrometers were obtained. Histological and immunohistochemical Characterization revealed i) both cell types present in the spheroids, with fibroblasts located primarily in the center, surrounded by epithelial cells; ii) synthesis of extracellular matrix; and iii,, mitotic cells located throughout the spheroids. Spheroidal integrity and cell viability were retained for the 30-day test period after removal of spheroids from the bioreactor. Potential utility of this three-dimensional, transgenic model for genotoxicity was initially assessed by exposure of spheroids to 0-2 Gy neon at dose rates of 0.3 to 1.5 Gy/min (National Institute of Radiological Sciences, Chiba, Japan). Quantification of mutation at the lacl gene revealed a linear dose response for mutation induction. Limited sequencing analysis of mutant clones revealed higher frequencies of deletions and multiple base sequence changes with increasing dose. These results suggest that our three-dimensional, transgenic model is applicable to a wide variety of studies involving the quantification, identification, and characterization of genotoxicity incurred in space and on Earth. This model uniquely allows investigation of the interaction of relevant factors, namely cell-to-cell interactions and the mechanistic interaction of microgravity with radiation insults and DNA repair. Using this three-dimensional model will allow us to obtain dual genotoxic information (i.e., mutation rate plus chromosome aberration data) from the same system so that one endpoint can be used to reference the other, thereby increasing the fidelity of the data set. Moreover, the tissue-equivalent nature of the three-dimensional model provides high confidence for relevance of risk assessment, i.e., the establishment of quality factors directly applicable to the microgravity environment.

Gonda, S. R.↗
NASA NTRSDate not supplied

Development of A Crew Health and Performance System Probabilistic Risk Assessment Tool: Proof-of-Concept Approach

The crew health and performance (CHP) system represents the span of technological interventions and tested processes and procedures that in combination address the human risk to space flight. The Human Research Program (HRP) mental model of the CHP system breaks the capabilities needed to meet NASA human flight systems standards into specific categories (i.e., countermeasures, behavioral health, medical intervention). These categories are further broken down into specific sub-groups generally associated with the human system risks that these capabilities seek to mitigate. Like the approach used to develop the Integrated Medical Model (IMM) and the Medical Extensible Dynamic Probabilistic Risk Analysis Tool (MEDPRAT), HRP tasked NASA GRC’s Cross-Cutting Computational Modeling Project with developing a CHP probabilistic risk assessment tool, the CHP-PRA. The CHP-PRA model seeks to quantify and relatively assess the human risk state within the crew health and performance domain, using a combination of knowledge about human system risks and technology and practices likely to be applied during space flight missions. This modeling system will incorporate customer and stakeholder feedback and be flexible enough to address multiple different questions about important low-level mission-specific parameters. This presentation will introduce the initial concept and development timeline for this tool and demonstrate proof-of-concept through an application addressing a specific human risk question posed within the Artemis program.

Risk analysis↗
DOE OSTI2021

New Approach Methodology for Assessing Inhalation Risks of a Contact Respiratory Cytotoxicant: Computational Fluid Dynamics-Based Aerosol Dosimetry Modeling for Cross-Species and In Vitro Comparisons

Regulatory agencies are considering alternative approaches to assessing inhalation toxicity that utilizes in vitro studies with human cells and in silico modeling in lieu of additional animal studies. In support of this goal, computational fluid-particle dynamics models were developed to estimate site-specific deposition of inhaled aerosols containing the fungicide, chlorothalonil, in the rat and human for comparisons to prior rat inhalation studies and new human in vitro studies. Under bioassay conditions, the deposition was predicted to be greatest at the front of the rat nose followed by the anterior transitional epithelium and larynx corresponding to regions most sensitive to local contact irritation and cytotoxicity. For humans, simulations of aerosol deposition covering potential occupational or residential exposures (1–50 µm diameter) were conducted using nasal and oral breathing. Aerosols in the 1–5 µm range readily penetrated the deep region of the human lung following both oral and nasal breathing. Under actual use conditions (aerosol formulations >10 µm), the majority of deposited doses were in the upper conducting airways. Beyond the nose or mouth, the greatest deposition in the pharynx, larynx, trachea, and bronchi was predicted for aerosols in the 10–20 µm size range. Only small amounts of aerosols >20 µm penetrated past the pharyngeal region. Using the ICRP clearance model, local retained tissue dose metrics including maximal concentrations and areas under the curve were calculated for each airway region following repeated occupational exposures. These results are directly comparable with benchmark doses from in vitro toxicity studies in human cells leading to estimated human equivalent concentrations that reduce the reliance on animals for risk assessments.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2024

Linking Threat Agents to Targeted Organizations: A Pipeline for Enhanced Cybersecurity Risk Metrics

In this study, we present a methodology leveraging Large Language Models (LLMs) to transform Cybersecurity Threat Intelligence (CTI) narratives into actionable insights for individual organizations. Our approach automates the extraction of machine-readable adversary SKRAM (Skills, Knowledge, Resources, Authorities, and Motivation) attributes from open-source reports, extending LLM utility beyond typical interactions. This innovation enables precise, automated assessments of cybersecurity risks posed by various adversaries. Using a chain-of-thought and multi-shot prompting strategy, our methodology advances the automation of cybersecurity feature extraction for new machine-learning models that predict the risk of adversary targeting. This approach is refined using a substantial dataset of over 150 analyst-validated threat reports and synthetic organizational data from 900 companies. Here, by bootstrapping the training data with a rule-based heuristic over synthetic data, we have developed a high-accuracy machine-learning model that allows entities to dynamically prioritize threats and defensive actions.

Cyber Threat Intelligence↗
DOE OSTI2022

Impact of Concurrent Solubilization and Fines Migration on Fracture Aperture Growth in Shales during Acidized Brine Injection

Acidic hydraulic fracturing fluid chemically and physically alters shale rock fabric during injection and shut-in, creating a “reaction-altered zone” along the fracture faces. To better characterize the variable thickness and composition of this reaction-altered zone under advective flow, we take a coupled experimental and modeling approach. A fluidic cell, with six fiducial markers, is first fabricated to keep the rock sample in place during the core floods and to allow image alignment of acquired images. Then, we conduct a series of reactive core floods in a clay-rich siliceous Wolfcamp shale sample with 10 wt % carbonate, using a synthetic fracturing fluid under no confining stress and at room temperature. High-resolution computed tomography (CT) scans are periodically conducted to observe the spatial alteration of the fracture network. We then perform scanning electron microscopy (SEM-EDS) on the two orthogonal surfaces (fracture surface and freshly cut profile face) to generate high-resolution elemental maps that show the change in mineralogy, both with distance along a given flow path along a fracture surface and with depth from the fracture surface into the shale matrix. These results are contrasted against a two-dimensional (2D) advection-diffusion reaction model developed previously for batch reactions between shale and synthetic fracturing fluids. The model simulates the geochemical interaction occurring at the fracture/matrix interface and penetrating into the shale matrix during the reactive core flood. Both model and experimental results show that the acidic brine is neutralized during the core flood, corresponding to an increase in fracture aperture as a function of fluid volume injected with the greatest change near the inlet. SEM-EDS scans reveal significant dissolution of carbonates on the fracture surface without pyrite oxidation. The reactive transport model indicates that carbonate depletion into the shale interior should be observable, yet SEM-EDS shows no discernible loss of carbonate in the orthogonal profile face. The combination of these observations suggests an additional fracture evolution mechanism in the reactive system, i.e., fines migration. We show that fines migration enhances the access of fracturing fluid to the matrix resulting in a more pronounced fracture widening. Finally, we conclude that coupled mineral dissolution and fines migration govern fracture aperture growth during acidized brine injection. In this work, we effectively show the underlying risk of relying solely on models that do not include an important (transport) process that can alter the system significantly and propose a combined chemomechanical mechanism for fracture evolution appropriate for this shale mineralogy.

58 GEOSCIENCES↗
NASA NTRS2012

Object-Oriented Bayesian Networks (OOBN) for Aviation Accident Modeling and Technology Portfolio Impact Assessment

The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.

Shih, Ann T.↗
NASA NTRS2010

Risk Analysis of On-Orbit Spacecraft Refueling Concepts

On-orbit refueling of spacecraft has been proposed as an alternative to the exclusive use of Heavy-lift Launch Vehicles to enable human exploration beyond Low Earth Orbit (LEO). In these scenarios, beyond LEO spacecraft are launched dry (without propellant) or partially dry into orbit, using smaller or fewer element launch vehicles. Propellant is then launched into LEO on separate launch vehicles and transferred to the spacecraft. Refueling concepts are potentially attractive because they reduce the maximum individual payload that must be placed in Earth orbit. However, these types of approaches add significant complexity to mission operations and introduce more uncertainty and opportunities for failure to the mission. In order to evaluate these complex scenarios, the authors developed a Monte Carlo based discrete-event model that simulates the operational risks involved with such strategies, including launch processing delays, transportation system failures, and onorbit element lifetimes. This paper describes the methodology used to simulate the mission risks for refueling concepts, the strategies that were evaluated, and the results of the investigation. The results of the investigation show that scenarios that employ refueling concepts will likely have to include long launch and assembly timelines, as well as the use of spare tanker launch vehicles, in order to achieve high levels of mission success through Trans Lunar Injection.

Cirillo, William M.↗
DOE OSTI2022

Cybersecurity for Electric Vehicle Charging Infrastructure

As the U.S. electrifies the transportation sector, cyberattacks targeting vehicle charging could impact several critical infrastructure sectors including power systems, manufacturing, medical services, and agriculture. This is a growing area of concern as charging stations increase power delivery capabilities and must communicate to authorize charging, sequence the charging process, and manage load (grid operators, vehicles, OEM vendors, charging network operators, etc.). The research challenges are numerous and complicated because there are many end users, stakeholders, and software and equipment vendors interests involved. Poorly implemented electric vehicle supply equipment (EVSE), electric vehicle (EV), or grid operator communication systems could be a significant risk to EV adoption because the political, social, and financial impact of cyberattacks — or public perception of such — would ripple across the industry and produce lasting effects. Unfortunately, there is currently no comprehensive EVSE cybersecurity approach and limited best practices have been adopted by the EV/EVSE industry. There is an incomplete industry understanding of the attack surface, interconnected assets, and unsecured inter faces. Comprehensive cybersecurity recommendations founded on sound research are necessary to secure EV charging infrastructure. This project provided the power, security, and automotive industry with a strong technical basis for securing this infrastructure by developing threat models, determining technology gaps, and identifying or developing effective countermeasures. Specifically, the team created a cybersecurity threat model and performed a technical risk assessment of EVSE assets across multiple manufacturers and vendors, so that automotive, charging, and utility stakeholders could better protect customers, vehicles, and power systems in the face of new cyber threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Securing Vehicle Charging Infrastructure

As the US electrifies the transportation sector, cyber attacks targeting vehicle charging could bring consequences to electrical system infrastructure. This is a growing area of concern as charging stations increase power delivery and must communicate to a range of entities to authorize charging, sequence the charging process, and manage load (grid operators, vehicles, OEM vendors, charging network operators, etc.). The research challenges are numerous and are complicated because there are many end users, stakeholders, and software and equipment vendors interests involved. Poorly implemented electric vehicle supply equipment (EVSE), electric vehicle (EV), or grid communication system cybersecurity could be a significant risk to EV adoption because the political, social, and financial impact of cyberattacks - or public perception of such - ripples across the industry and has lasting and devastating effects. Unfortunately, there is no comprehensive EVSE cybersecurity approach and limited best practices have been adopted by the EV/EVSE industry. There is an incomplete industry understanding of the attack surface, interconnected assets, and unsecured interfaces. Thus, comprehensive cybersecurity recommendations founded on sound research are necessary to secure EV charging infrastructure. This project is providing the power, security, and automotive industry with a strong technical basis for securing this infrastructure by developing threat models, determining technology gaps, and identifying or developing effective countermeasures. Specifically, the team is creating a cybersecurity threat model and performing a technical risk assessment of EVSE assets, so that automotive, charging, and utility stakeholders can better protect customers, vehicles, and power systems in the face of new cyber threats.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2006

Quality Interaction Between Mission Assurance and Project Team Members

Mission Assurance independent assessments started during the development cycle and continued through post launch operations. In operations, Health and Safety of the Observatory is of utmost importance. Therefore, Mission Assurance must ensure requirements compliance and focus on process improvements required across the operational systems including new/modified products, tools, and procedures. The deployment of the interactive model involves three objectives: Team member Interaction, Good Root Cause Analysis Practices, and Risk Assessment to avoid reoccurrences. In applying this model, we use a metric based measurement process and was found to have the most significant effect, which points to the importance of focuses on a combination of root cause analysis and risk approaches allowing the engineers the ability to prioritize and quantify their corrective actions based on a well-defined set of root cause definitions (i.e. closure criteria for problem reports), success criteria and risk rating definitions.

quality↗
NASA NTRSDate not supplied

Developing A New Medical Condition List for Exploration Spaceflight

For the last decade, the National Aeronautics and Space Administration (NASA) has utilized a probabilistic risk analysis tool called the Integrated Medical Model (IMM), which contains 100 medical conditions, to conduct medical trade-space analyses and risk assessments for International Space Station (ISS) operations. Planning for future missions to the Moon and Mars will require updated tools and evidence that consider the unique features of exploration missions. To address this need, the Exploration Medical Capability (ExMC) Element of the NASA Human Research Program is developing an advanced trade-space analysis tool suite, IMPACT. As a part of this effort, ExMC has produced the IMPACT version 1 Condition List (ICL 1.0) which expands the scope and definition of medical conditions.

Amy Jean Kreykes↗
DOE OSTI2026

Hybrid Power Purchase Agreements for Flexible 24/7 Energy Delivery – A Comprehensive Review of Current Practices and Research Pathways

Power Purchase Agreements (PPAs) are becoming increasingly preferred among large energy consumers, such as data centers, to secure cost-effective energy and meet accelerating demand growth. Traditionally, variable renewable energy (VRE)-based PPAs operate on a pay-as-produced basis, balancing supply and demand for a relatively longer duration (e.g., annually). However, the focus is shifting toward matching supply and demand on an hourly basis to fully meet energy needs. This shift requires the integration of flexible energy resources, such as hydropower, thermal generation, and energy storage, to complement VRE sources like wind and solar, forming the foundation for 24/7 PPA. This work contributes by: (i) reviewing emerging market trends and current practices in PPA procurement, supported by data on PPA prices and technology portfolios; (ii) synthesizing the existing literature on modeling approaches for contract pricing, quantities, hybrid resource procurement, and risk management in 24/7 PPA design, while identifying key research gaps; and (iii) proposing an integrated 24/7 PPA design framework along with two contracting mechanisms from the perspectives of both PPA providers and consumers. The proposed framework highlights critical modeling challenges, risk-allocation issues, and future research opportunities for 24/7 PPA design.

24/7↗