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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2002

Analysis for the Progressive Failure Response of Textile Composite Fuselage Frames

A part of aviation accident mitigation is a crashworthy airframe structure, and an important measure of merit for a crashworthy structure is the amount of kinetic energy that can be absorbed in the crush of the structure. Prediction of the energy absorbed from finite element analyses requires modeling the progressive failure sequence. Progressive failure modes may include material degradation, fracture and crack growth, and buckling and collapse. The design of crashworthy airframe components will benefit from progressive failure analyses that have been validated by tests. The subject of this research is the development of a progressive failure analysis for a textile composite, circumferential fuselage frame subjected to a quasi-static, crash-type load. The test data for the frame are reported, and these data are used to develop and to validate methods for the progressive failure response.

Johnson, Eric R.↗
DOE OSTI2025

LDRD Abbreviated report: High-Order General-Discrete-Ordinates Method Enabling Efficient Deterministic Transport in Hydrodynamic Simulations

Deterministic transport simulations for national-security and energy applications often operate in high-dimensional phase-space, where accuracy and cost both become major challenges. A common numerical artifact in such problems is the “ray-effect,” which appears as unphysical streaks. Beyond misinterpretation, these artifacts can contaminate tightly coupled physics, such as fluid dynamics, radiation-hydrodynamics, and laser-plasma interactions, eroding the predictive capability of entire multiphysics workflows. Our objective was to make high-dimension studies practical on modern hardware while mitigating the ray-effect without relying on prohibitively expensive sampling approaches such as Monte Carlo methods. We developed the Generic Discretization Library (GenDiL), a Graphics Processing Unit (GPU)-first framework that uses high-order Discontinuous Galerkin (DG) methods and matrix-free algorithms to reduce memory usage and improve computational efficiency, critical for phase-space simulations. GenDiL supports phase-space adaptivity in both mesh size and polynomial order (hp-adaptivity) to place resolution only where it is needed. A central capability is Local Dimensional Refinement (LDR), which couples lower-dimension continuum models to higher-dimension kinetic models through stable and conservative interfaces, so that high-fidelity physics is applied only in regions where it is essential. Building on the GenDiL framework, we developed the General SN (GSN) family of algorithms as a true generalization of the polar SN approach (discrete ordinates, often denoted SN). Rather than tying discrete ordinates to a specific polar change of coordinates, GSN formulates transport on an arbitrary change of coordinates chosen to reduce ray-effect. We studied two complementary variants: an analytic variant, where the coordinate map is prescribed in advance by a closed-form function; and a data-driven variant, where a quantity of interest, such as the net flux, guides the coordinate system. GenDiL provides the library infrastructure for efficient GPU execution, but the GSN concept is algorithmic and independent of any one library. Across representative high-dimension tests, including non-symmetric solutions, both variants delivered strong ray-effect mitigation at practical cost, moving four- to six-dimensional analysis toward repeatable, routine studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Cybersecurity Center for Offshore Wind Energy (Final Project Report)

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models with SCADA infrastructure, and deployed a scaled physical turbine and associated sensors. High-resolution operational and side-channel data streams were collected and used to refine machine-learning (ML)-based attack detection systems and to extend the WindCRAFT framework to multi-turbine threat scenarios. The project demonstrated a realistic, scalable environment for evaluating cyber threats, validated attack detection approaches using enriched datasets, and identified new multi-turbine and inter-turbine communication attack vectors. The resulting testbed, models, and security mechanisms provide a foundation for ongoing R&D and deployment of cyber-resilient offshore wind energy systems.

17 WIND ENERGY↗
DOE OSTI2024

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Abstract. Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

Geology↗
NASA NTRS1989

Ku-band interferences for the Space Station multiple access link

The multiple access (MA) system, an essential part of the United States Space Station, will be used to provide simultaneous communication services, voice and command, telemetry and video, between the Space Station and all the different coorbiting user vehicles. The system is designed to operate in the Ku-band frequencies between 14 GHz and 14.89 GHz. Within this band, there are other users that could pose serious interference potential. The extent of the interference and its impact on the system operations are analyzed using a Monte Carlo simulation. Worst-case analysis indicated that certain links are very susceptible to interference. Mitigation techniques involving both hardware changes and operation constraints are presented. With the modification of some of the design and implementation of some of the mitigation techniques, the interference levels were found to be only a few percent and to occur in a burst manner.

Loh, Y. C.↗
NASA NTRS2011

USM3D Analysis of Low Boom Configuration

In the past few years considerable improvement was made in NASA's in house boom prediction capability. As part of this improved capability, the USM3D Navier-Stokes flow solver, when combined with a suitable unstructured grid, went from accurately predicting boom signatures at 1 body length to 10 body lengths. Since that time, the research emphasis has shifted from analysis to the design of supersonic configurations with boom signature mitigation In order to design an aircraft, the techniques for accurately predicting boom and drag need to be determined. This paper compares CFD results with the wind tunnel experimental results conducted on a Gulfstream reduced boom and drag configuration. Two different wind-tunnel models were designed and tested for drag and boom data. The goal of this study was to assess USM3D capability for predicting both boom and drag characteristics. Overall, USM3D coupled with a grid that was sheared and stretched was able to reasonably predict boom signature. The computational drag polar matched the experimental results for a lift coefficient above 0.1 despite some mismatch in the predicted lift-curve slope.

Carter, Melissa B.↗
NASA NTRS2014

Development, Verification and Validation of Parallel, Scalable Volume of Fluid CFD Program for Propulsion Applications

There are many instances involving liquid/gas interfaces and their dynamics in the design of liquid engine powered rockets such as the Space Launch System (SLS). Some examples of these applications are: Propellant tank draining and slosh, subcritical condition injector analysis for gas generators, preburners and thrust chambers, water deluge mitigation for launch induced environments and even solid rocket motor liquid slag dynamics. Commercially available CFD programs simulating gas/liquid interfaces using the Volume of Fluid approach are currently limited in their parallel scalability. In 2010 for instance, an internal NASA/MSFC review of three commercial tools revealed that parallel scalability was seriously compromised at 8 cpus and no additional speedup was possible after 32 cpus. Other non-interface CFD applications at the time were demonstrating useful parallel scalability up to 4,096 processors or more. Based on this review, NASA/MSFC initiated an effort to implement a Volume of Fluid implementation within the unstructured mesh, pressure-based algorithm CFD program, Loci-STREAM. After verification was achieved by comparing results to the commercial CFD program CFD-Ace+, and validation by direct comparison with data, Loci-STREAM-VoF is now the production CFD tool for propellant slosh force and slosh damping rate simulations at NASA/MSFC. On these applications, good parallel scalability has been demonstrated for problems sizes of tens of millions of cells and thousands of cpu cores. Ongoing efforts are focused on the application of Loci-STREAM-VoF to predict the transient flow patterns of water on the SLS Mobile Launch Platform in order to support the phasing of water for launch environment mitigation so that vehicle determinantal effects are not realized.

West, Jeff↗
NASA NTRS2014

NASA Space Rocket Logistics Challenges

The Space Launch System (SLS) is the new NASA heavy lift launch vehicle and is scheduled for its first mission in 2017. The goal of the first mission, which will be uncrewed, is to demonstrate the integrated system performance of the SLS rocket and spacecraft before a crewed flight in 2021. SLS has many of the same logistics challenges as any other large scale program. Common logistics concerns for SLS include integration of discreet programs geographically separated, multiple prime contractors with distinct and different goals, schedule pressures and funding constraints. However, SLS also faces unique challenges. The new program is a confluence of new hardware and heritage, with heritage hardware constituting seventy-five percent of the program. This unique approach to design makes logistics concerns such as commonality especially problematic. Additionally, a very low manifest rate of one flight every four years makes logistics comparatively expensive. That, along with the SLS architecture being developed using a block upgrade evolutionary approach, exacerbates long-range planning for supportability considerations. These common and unique logistics challenges must be clearly identified and tackled to allow SLS to have a successful program. This paper will address the common and unique challenges facing the SLS programs, along with the analysis and decisions the NASA Logistics engineers are making to mitigate the threats posed by each.

Neeley, James R.↗
NASA NTRS2014

Advanced Interval Management (IM) Concepts of Operations

This document provides a high-level description of several advanced IM operations that NASA is considering for future research and development. It covers two versions of IM-CSPO and IM with Wake Mitigation. These are preliminary descriptions to support an initial benefits analysis

Barmore, Bryan E.↗
NASA NTRS2010

Mission Enabling and Enhancing Spacecraft Capabilities with MicroNewton Electric Propulsion

The capability to significantly improve current spacecraft pointing, precision orbit maintenance and disturbance mitigation were considered using precision, quiescent microNewton electric propulsion systems. Analysis results showed that electric propulsion systems operating in the microNewton to hundreds of microNewtons thrust range can offer significant improvements over state-of-the-art mission capabilities to enable 30 m Earth-fixed orbital tubes, constellation spacecraft position control to within nanometers and exoplanet observatory pointing with 0.1 milliarcsecond precision. Specific thrust levels and profiles required to support these capabilities are discussed.

micro propulsion↗
NASA NTRS2019

Orbital Debris Ontology, Terminology, and Knowledge Modeling

The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does this hazard, but so does the sea of data. The problem is also an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data and information management aspect of developing solutions for a sustainable and safe orbital space environment. The corresponding author’s in-progress work to develop an orbital debris domain ontology is summarized in order to discuss knowledge modeling for this domain. Methodological approaches of this effort can also contribute to standards efforts and address terminological and policy questions. Leveraging the growing volumes of orbital debris and space situational awareness (SSA) data will create a more complete picture of the orbital space environment. Part of the solution will be: consistent and correct data interpretation, sharing orbital debris and SSA data in one form or another, terminology development & harmonization, and knowledge or domain modeling. To facilitate this, [Rovetto, 2015/16] discussed ontology development for the orbital debris domain. This paper lists concepts from that paper, and subsequently developed concepts [2-9]. Ontology engineering is an interdisciplinary field related to knowledge representation and reasoning in artificial intelligence, semantic technologies and the so-called semantic web. An ontology is effectively a computable and semantically rich terminology that presents a knowledge or domain model for a topic area. Expressions of knowledge or assertions are stored using formally defined term. This knowledge base is reasoned over to yield answers to queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, enterprise knowledge graphs, etc. Ontologies support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO), and related ontologies [Rovetto & Kelso 2016] [Rovetto 2016, 2017], were proposed to help achieve this. ODO, for instance, is intended as a domain ontology that can be used across federated databases, offering an explicitly specified set of concepts describing the orbital debris domain. Its meaning-rich taxonomy will provide a sharable semantics for orbital debris data to, in part, consistently communicate the meaning of data to both humans and machines, and tag data elements in space object catalogs to help afford inference tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) is part of the overall Orbital Space Domain Ontology concept, which is conceived as a broader domain reference ontology. It aims to provide a knowledge representation structure of the orbital space environment, a common semantic model, and develop a sharable terminology. Collectively this will provide common meaning for datasets, a high-level taxonomy or classification for orbital space objects, and thus means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications and interdisciplinary partnerships include web-based platforms, web apps, visualizations, and academia projects. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, the proposed conceptual, terminological and ontological analysis may contribute to such efforts as the Space Debris Mitigation Requirements in the International Standards Organization by developing more precise, consistent and coherent terms and definitions. Projects that seek to develop in-house ontologies can use ODO and related ontologies as domain reference ontologies. This paper was developed independent of author affiliations. Readers are encouraged to contact corresponding author(1) with general interest and potential opportunities to support or realize the described project.

Robert J. Rovetto↗
NASA NTRSDate not supplied

In-Time Safety Assessment & Risk Prediction for Unmanned Aerial Systems

One of the critical challenges in emerging autonomous systems is timely mitigation of hazards encountered during operation which may not be known or accounted for at the time of design. Efficient execution of unmanned systems therefore demands a paradigm shift from scheduled periodic maintenance to predictive risk analysis that includes condition-based-monitoring, real-time reliability assessment and hazard mitigation. Particularly, the state-of-health parameters needs to be computed at the component level, unit level as well as the integrated system level. While in the former two levels, the physics of health propagation may be based on underlying electro-mechanical properties, system level prognostics often relies on data-driven models. Further, uncertainty from model, measurements and input sources should be accurately quantified to generate meaningful prediction results that can be fed into reliable decision making processes. Finally, the expected risk and time to failure has to be computed based on the current state-of-health of the overall system. This talk presents a conceptual design of such an in-time safety assurance approach for unmanned aerial vehicles (UAV) operating at low altitudes near and over populated areas. Typical in-flight hazard incidents include unplanned detour, proximity to obstacles, mid-flight component faults, limited battery life and poor quality of GPS measurements. Safety assessment therefore comprises trajectory generation and re-plan, battery RUL computation, distributed fault diagnostics and uncertainty management of predicted trajectory based on GPS measurement noise. The entire monitoring framework will be demonstrated on simulated as well as real UAV flight experiments conducted at the NASA Langley Research Center. This tutorial will therefore guide the audience through a step-by-step tracking of an autonomous system with focus on in-time risk prediction in the presence of unforeseen hazards and uncertain environment.

diagnostics↗
NASA NTRS2002

Analysis for the Progressive Failure Response of Textile Composite Fuselage Frames

A part of aviation accident mitigation is a crash worthy airframe structure, and an important measure of merit for a crash worthy structure is the amount of kinetic energy that can be absorbed in the crush of the structure. Prediction of the energy absorbed from finite element analyses requires modeling the progressive failure sequence. Progressive failure modes may include material degradation, fracture and crack growth, and buckling and collapse. The design of crash worthy airframe components will benefit from progressive failure analyses that have been validated by tests. The subject of this research is the development of a progressive failure analysis for textile composite. circumferential fuselage frames subjected to a quasi-static, crash-type load. The test data for these frames are reported, and these data, along with stub column test data, are to be used to develop and to validate methods for the progressive failure response.

Johnson, Eric R.↗
DOE OSTI2025

Techno-Economic Analysis of Data-Driven and Transactive Approaches for Resilience Enhancement

As extreme weather events lead to more frequent power outages, understanding and enhancing grid resilience is critical to mitigating economic losses and non-energy impacts from service disruptions. Here, this study introduces a novel techno-economic analysis framework for evaluating resilience enhancement mechanisms. The framework combines grid response modeling with a co-simulation approach and valuation methodology to provide a comprehensive assessment. We apply this framework to a realistic case study of the Texas grid during Winter Storm Uri in February 2021. Two advanced resilience strategies are analyzed: a data-driven rolling outage mechanism and a transactive energy (TE) based allocation scheme. The rolling outage scheme selectively serves customers based on real-time curtailment needs, while the TE scheme allows customers to trade energy allocations according to their preferences. Our findings show that both the rolling outage and TE schemes significantly outperform conventional methods (i.e. controlled outages) by reducing the amount of energy not supplied to customers by 41% and 64%, respectively. These approaches also enhance flexibility and customer satisfaction, while improving energy utilization for greater resilience. Additionally, they maintain thermal comfort about 3.5 times better and substantially lower customer risk exposure. A key contribution of this study is addressing both utility and customer perspectives while considering both energy and non-energy impacts. The techno-economic analysis indicates that implementing these resilience enhancement strategies would incur an additional 1.1Bto1.6B in utility costs but has the potential to avoid 17.3Bto18B of customer losses as compared to existing solutions, thereby underscoring the value of investing in advanced resilience, as it provides significant societal benefits to customers.

42 ENGINEERING↗
NASA NTRSDate not supplied

ISS EVA80 EMU Water in the Helmet Failure and Associated Analytical Response

On March 23rd, 2022, during Extra-Vehicular Activity (EVA) 80 aboard the International Space Station (ISS) crew identified an 8-10-inch diameter thin film of water in the pressure bubble of the suit during repress. This launched an investigation to determine the cause of the water in the helmet as well as short- and long-term mitigation efforts to enable return to EVA as quickly as possible. The investigation analysis efforts in combination with hardware inspection and testing determined the most likely cause of the water in the helmet to be sublimator carryover as a result of high latent loading put on the system. In parallel with this investigation, efforts were being made to mitigate any future water in the helmet events. The short-term mitigation strategy developed is to install absorbent material in the pressure bubble to capture water as it enters the helmet before it can impact the astronauts. This hardware is referred to as the Helmet Absorption Band (HAB) and Helmet Absorption Pad – Extender (HAP-E). Longer-term mitigation strategies include a device to capture small water events before entering the helmet by installing a water capture system in the vent loop of the Extravehicular Mobility Unit (EMU). This effort is coined the T2 Water Capture System. Additionally, developing an on-orbit sublimator challenge test which will be able to verify sublimator performance before and after EVAs. The sublimator is the hardware which condenses water vapor and removes it from the vent loop, and this hardware is referred to as the EMU Moisture Injection Test System (EMITS). Based on the investigation and short-term water capture solutions the ISS Program decided to return to nominal EVAs on October 7, 2022. With the addition of the long-term mitigation strategies, the team hopes to be able to prevent any future water in the helmet events.

Veronica Lee Pizor↗
NASA NTRS1993

Separation dynamics of the COMET FreeFlyer and an upper stage STAR-48V motor

In this report, the orbital separation between a STAR-48V upperstage motor and the COMET FreeFlyer is investigated. The time from nominal STAR-48 engine burnout is to be determined such that the STAR-48 will not collide with the FreeFlyer once the separation process has been initiated. To analyze this separation, the forces acting upon both the FreeFlyer and the STAR-48 are described in a body fixed coordinate system. These coordinates are then transformed into an Euler coordinate system and then further transformed into a relative inertial coordinate system. From this analysis and some basic assumptions about the Star-48/FreeFlyer vehicle, it can be concluded that the STAR-48 will not collide with the Free Flyer if the separation occurs at 120 seconds after nominal burnout of the STAR-48. In fact, the separation delay could be a shorter period of time, but it is recommended that this separation delay be as long as possible for risk mitigation. This delay is currently designed to be 120 seconds and the analysis presented in this report shows that this time is acceptable.

Fuller, Kevin M.↗
DOE OSTI2024

Optimizing Carbon Capture, Transport, and Storage: Overcoming Challenges with Machine Learning and Cost-Benefit Analysis

Carbon Capture, Utilization, and Storage (CCUS) is a critical strategy for reducing CO₂ emissions and mitigating climate change. However, its widespread deployment faces numerous challenges across the capture, transport, and storage phases. These challenges include the technical complexity of predicting subsurface behaviors during CO₂ injection, ensuring long-term storage integrity, optimizing transportation networks, and balancing the economic and environmental trade-offs. Addressing these issues requires an integrated approach combining advanced subsurface modeling with system-level analyses to assess costs, risks, and benefits. This presentation provides an overview of studies conducted by the National Energy Technology Laboratory (NETL) to tackle these challenges. NETL’s efforts encompass cutting-edge research in subsurface fluid behavior machine learning predictions, alongside the development of innovative tools for system optimization and economic evaluation. By bridging technical expertise and strategic analysis, NETL aims to advance the deployment of CCUS technologies to support global decarbonization efforts. Presented at the Carnegie Mellon University CEE IESS Student Seminar October 4, 2024.

Shih, Chung Yan↗