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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Sensor-Web Operations Explorer

Understanding the atmospheric state and its impact on air quality requires observations of trace gases, aerosols, clouds, and physical parameters across temporal and spatial scales that range from minutes to days and from meters to more than 10,000 kilometers. Observations include continuous local monitoring for particle formation; field campaigns for emissions, local transport, and chemistry; and periodic global measurements for continental transport and chemistry. Understanding includes global data assimilation framework capable of hierarchical coupling, dynamic integration of chemical data and atmospheric models, and feedback loops between models and observations. The objective of the sensor-web system is to observe trace gases, aerosols, clouds, and physical parameters, an integrated observation infrastructure composed of space-borne, air-borne, and in-situ sensors will be simulated based on their measurement physics properties. The objective of the sensor-web operation is to optimally plan for heterogeneous multiple sensors, the sampling strategies will be explored and science impact will be analyzed based on comprehensive modeling of atmospheric phenomena including convection, transport, and chemical process. Topics include system architecture, software architecture, hardware architecture, process flow, technology infusion, challenges, and future direction.

observation↗
NASA NTRS2011

Space Shuttle Systems Engineering Processes for Liftoff Debris Risk Mitigation

This slide presentation reviews the systems engineering process designed to reduce the risk from debris during Space Shuttle Launching. This process begins the day of launch from the tanking to the vehicle tower clearance. Other debris risks (i.e., Ascent, and micrometeoroid orbital debit) are mentioned) but are not the subject of this presentation. The Liftoff debris systems engineering process and an example of how it works are reviewed (i.e.,STS-119 revealed a bolt liberation trend on the Fixed Service Structure (FSS) 275 level elevator room). The process includes preparation of a Certification of Flight Readiness (CoFR) that includes (1) Lift-off debris from previous mission dispositioned, (2) Flight acceptance rationale has been provided for Lift-off debris sources/causes (3) Lift-off debris mission support documentation, processes and tools are in place for the up-coming mission. The process includes a liftoff debris data collection that occurs after each launch. This includes a post launch walkdown, that records each liftoff debris, and the entry of the debris into a database, it also includes a review of the imagery from the launch, and a review of the instrumentation data. There is also a review of the debris transport analysis process, that includes temporal and spatial framework and a computational fluid dynamics (CFD) analysis. which incorporates a debris transport analyses (DTA), debris materials and impact tests, and impact analyses.

Mitchell, Michael↗
NASA NTRS2013

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development. Currently there is no fully coupled computational tool to analyze this fluid/structure interaction process. The objective of this study was to develop a fully coupled aeroelastic modeling capability to describe the fluid/structure interaction process during the transient nozzle operations. The aeroelastic model composes of three components: the computational fluid dynamics component based on an unstructured-grid, pressure-based computational fluid dynamics formulation, the computational structural dynamics component developed in the framework of modal analysis, and the fluid-structural interface component. The developed aeroelastic model was applied to the transient nozzle startup process of the Space Shuttle Main Engine at sea level. The computed nozzle side loads and the axial nozzle wall pressure profiles from the aeroelastic nozzle are compared with those of the published rigid nozzle results, and the impact of the fluid/structure interaction on nozzle side loads is interrogated and presented.

Wang, Ten-See↗
NASA NTRS2004

TSOS - time based spacecraft operation simulator

This paper describes the Time Based Spacecraft Operation Simulator (TSOS) system. TSOS is part of the Virtual Mission Operation Framework (VMOF). It is a dynamically codigurable executive. TSOS simulates the execution of science observation scenarios on each spacecraft subsystem, propagates subsystem states, and generates the telemetry data.

Lu, Wenwen↗
NASA NTRS2021

Faster Exo-Earth Yield for HabEx and LUVOIR via Extreme Precision Radial Velocity Prior Knowledge

The HabEx and LUVOIR mission concepts reported science yields for mission scenarios in which the instruments must search for potentially habitable planets, determine their orbits, and, if worthwhile, invest the integration time for a spectral characterization. We evaluate the impact of prior knowledge of planet existence and orbital parameters on yield for four mission concept architectures: HabEx 4m telescope with hybrid starshade and coronagraph, HabEx4m telescope with starshade only, HabEx 4m telescope with coronagraph only, and LUVOIR B8m telescope with coronagraph only. We use perfect prior knowledge to establish an upperbound on yield and use partial prior knowledge from a potential future extreme precision radial velocity (EPRV) instrument with3cm∕ssensitivity. We detail a modeling framework that per-forms dynamically responsive observation scheduling with realistic mission constraints. We evaluate exo-Earth yields against three metrics of spectral characterization for the four mission architectures and three levels of prior knowledge (none, partial, and perfect). The EPRV pro-vided prior knowledge increases yields by∼30%and accelerates by a factor of 3 to 6 the time to achieve half of the yield of the mission. Prior knowledge makes all the mission architectures more nimble and powerful, and most especially starshade-based architectures. With prior knowledge, a small telescope with a starshade can achieve comparable yield to a larger telescope with a coronagraph.

Rhonda Morgan↗
NASA NTRSDate not supplied

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries↗
NASA NTRS2024

Development of a Single Level Assessment Module for Simulating the Human Factors Concept Trade Space

This paper is a synopsis of the design and development of the Single Level Assessment Module (SLAM), a habitation mockup aimed at simulating volumetric conditions for astronauts in transit to Mars. Utilizing repurposed materials to enable low cost and constrained by various other design requirements from its parent vehicle, the SLAM embodies a critical step towards understanding human/habitat dynamics and interactions within the framework of the Mars Transit Habitat (TH) concept trade space. The synopsis begins by outlining the design constraints and goals, focusing on material availability and functional area volume requirements. Through various 3D design solutions, the SLAM emerges as a versatile habitat prototype, capable of accommodating various functional areas within its reconfigurable framework. The construction phase is then explored, highlighting the practical challenges and solutions encountered in assembling the SLAM's components. From panel assembly to outfitting functional areas, the construction process demonstrates a methodical approach to realizing the habitat's design intent. Looking ahead, the paper outlines future work, emphasizing the SLAM's adaptability for analysis and its potential to inform the design trade space future habitation concepts across the Moon to Mars architecture. By incorporating hinges for reconfigurability and facilitating volume assessments, the SLAM emerges as a crucial tool in advancing NASA’s ability to assess focused habitation configurations in conjunction with the development of the Moon to Mars architecture. In conclusion, this paper showcases the iterative process of habitat design, from conceptualization to construction.

Keith Lindsey↗
NASA NTRS2007

Robustness Analysis of Integrated LPV-FDI Filters and LTI-FTC System for a Transport Aircraft

This paper proposes an analysis framework for robustness analysis of a nonlinear dynamics system that can be represented by a polynomial linear parameter varying (PLPV) system with constant bounded uncertainty. The proposed analysis framework contains three key tools: 1) a function substitution method which can convert a nonlinear system in polynomial form into a PLPV system, 2) a matrix-based linear fractional transformation (LFT) modeling approach, which can convert a PLPV system into an LFT system with the delta block that includes key uncertainty and scheduling parameters, 3) micro-analysis, which is a well known robust analysis tool for linear systems. The proposed analysis framework is applied to evaluating the performance of the LPV-fault detection and isolation (FDI) filters of the closed-loop system of a transport aircraft in the presence of unmodeled actuator dynamics and sensor gain uncertainty. The robustness analysis results are compared with nonlinear time simulations.

Khong, Thuan H.↗
NASA NTRSDate not supplied

A Verification Framework for Runtime Assurance of Autonomous UAS

Runtime Assurance (RTA) is a design-time architecture for safety-critical systems where an internal monitor acts upon detecting a violation of a property. The simplex architecture is an instance of RTA, where the action taken is to hand control of the overall system to a trusted controller when an untrusted one violates a safety property. Simplex RTA is emerging as a method for allowing AI/ML and other unverified software to be integrated into safety-critical applications like aircraft. To this end, the American Society for Testing and Materials (ASTM) and NASA have each published guidelines on the use of RTA in such systems. In the simplex RTA framework, a system has an advanced controller (AC) and a reversionary controller (RC). The system is allowed to operate with the AC until a runtime monitor detects that some property has been violated and then the RC takes over. Assuming that the sample rate of the monitor will detect improper functioning with enough time for the RC to correct the impending problem, and that the RC is trusted, the system will operate as intended. This use of the simplex RTA framework can allow for the integration of untrusted, but possibly more performant, controllers in a safe way. This paper presents a formalization of a simplex RTA framework in the Prototype Verification System (PVS) theorem prover using an embedding of differential dynamic logic (DDL) called Plaidypvs. A novel feature of this framework is that it can be instantiated at different levels of abstraction. This feature allows for the formal verification of a system with an untrusted black box component, such as an AI/ML controller. This paper does not address the many difficulties in deploying RTA in an industrial-level system. Instead, the focus is on the formal verification of the simplex RTA framework in the language of hybrid programs. Hybrid programs are programs that include both discrete and continuous dynamics and can be used to model complex cyber-physical systems. Plaidypvs is a tool that enables formalization of hybrid programs in the PVS theorem prover. Plaidypvs enables the verification of the general simplex RTA framework and then, by specializing some components of the hybrid program, verifying instances of the framework while treating the untrusted component as a black box. A selection of Unmanned Aircraft Systems (UAS) operations are shown as instances of the general RTA framework in PVS. This offers the benefit of design time verification of relevant safety properties to the system, and it also gives requirements on the sample rate of sensors that determine the time interval in which the ‘switch’ property of the RTA framework is checked.

PVS↗
NASA NTRS2005

Development of a Modeling Framework to Support Control Investigations of Sailcraft Missions A First Cut: ABLE Sailcraft Dynamics Model

Solar Sailcraft, the stuff of dreams of the H.G. Wells generation, is now a rapidly maturing reality. The promise of unlimited propulsive power by harnessing stellar radiation is close to realization. Currently, efforts are underway to build, prototype and test two configurations. These sails are designed to meet a 20m sail requirement, under guidance of the In-Space Propulsion (ISP) technology program office at MSFC. While these sails will not fly , they are the first steps in improving our understanding of the processes and phenomena at work. As part of the New Millennium Program (NMP) the ST9 technology validation mission hopes to launch and fly a solar sail by 2010 or sooner. Though the Solar Sail community has been studying and validating various concepts over two decades, it was not until recent breakthroughs in structural and material technology, has made possible to build sails that could be launched. With real sails that can be tested (albeit under earth conditions), the real task of engineering a viable spacecraft has finally commenced. Since it is not possible to accurately or practically recreate the actual operating conditions of the sailcraft (zero-G, vacuum and extremely low temperatures), much of the work has focused on developing accurate models that can be used to predict behavior in space, and for sails that are 6-10 times the size of currently existing sails. Since these models can be validated only with real test data under "earth" conditions, the process of modeling and the identification of uncertainty due to model assumptions and scope need to be closely considered. Sailcraft models that exist currently, are primarily focused on detailed physical representations at the component level, these are intended to support prototyping efforts. System level models that cut across different sail configurations and control concepts while maintaining a consistent approach are non-existent. Much effort has been focused on the areas of thrust performance, solar radiation prediction, and sail membrane behavior vis-a-vis their reflective geometry, such as wrinkling/folding/furling as it pertains to thrust prediction. A parallel effort has been conducted on developing usable models for developing attitude control systems (ACS), for different sail configurations in different regimes. There has been very little by way of a system wide exploration of the impact of the various control schemes, thrust prediction models for different sail configurations being considered.

Sarathy, Sriprakash↗
NASA NTRS2017

Dynamic Routing of Aircraft in the Presence of Adverse Weather Using a POMDP Framework

Each year weather-related airline delays result in hundreds of millions of dollars in additional fuel burn, maintenance, and lost revenue, not to mention passenger inconvenience. The current approaches for aircraft route planning in the presence of adverse weather still mainly rely on deterministic methods. In contrast, this work aims to deal with the problem using a Partially Observable Markov Decision Processes (POMDPs) framework, which allows for reasoning over uncertainty (including uncertainty in weather evolution over time) and results in solutions that are more robust to disruptions. The POMDP-based decision support system is demonstrated on several scenarios involving convective weather cells and is benchmarked against a deterministic planning system with functionality similar to those currently in use or under development.

Decision making↗
NASA NTRS2008

Random Testing and Model Checking: Building a Common Framework for Nondeterministic Exploration

Two popular forms of dynamic analysis, random testing and explicit-state software model checking, are perhaps best viewed as search strategies for exploring the state spaces introduced by nondeterminism in program inputs. We present an approach that enables this nondeterminism to be expressed in the SPIN model checker's PROMELA language, and then lets users generate either model checkers or random testers from a single harness for a tested C program. Our approach makes it easy to compare model checking and random testing for models with precisely the same input ranges and probabilities and allows us to mix random testing with model checking's exhaustive exploration of non-determinism. The PROMELA language, as intended in its design, serves as a convenient notation for expressing nondeterminism and mixing random choices with nondeterministic choices. We present and discuss a comparison of random testing and model checking. The results derive from using our framework to test a C program with an effectively infinite state space, a module in JPL's next Mars rover mission. More generally, we show how the ability of the SPIN model checker to call C code can be used to extend SPIN's features, and hope to inspire others to use the same methods to implement dynamic analyses that can make use of efficient state storage, matching, and backtracking.

dynamic analysis↗
NASA NTRS2001

Impact of Functionally Graded Cylinders: Theory

This final report summarizes the work funded under the Grant NAG3-2411 during the 04/05/2000-04/04/2001 period. The objective of this one-year project was to generalize the theoretical framework of the two-dimensional higher-order theory for the analysis of cylindrical functionally graded materials/structural components employed in advanced aircraft engines developed under past NASA Glenn funding. The completed generalization significantly broadens the theory's range of applicability through the incorporation of dynamic impact loading capability into its framework. Thus, it makes possible the assessment of the effect of damage due to fuel impurities, or the presence of submicron-level debris, on the life of functionally graded structural components. Applications involving advanced turbine blades and structural components for the reusable-launch vehicle (RLV) currently under development will benefit from the completed work. The theory's predictive capability is demonstrated through a numerical simulation of a one-dimensional wave propagation set up by an impulse load in a layered half-plane. Full benefit of the completed generalization of the higher-order theory described in this report will be realized upon the development of a related computer code.

Aboudi, Jacob↗
NASA NTRS1984

Issues in Developing a Normative Descriptive Model for Dyadic Decision Making

Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.

Serfaty, D.↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
NASA NTRS2015

Model-Based Prognostics of Hybrid Systems

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

prognosis↗
NASA NTRS2013

Impacts of Disturbance History on Forest Carbon Stocks and Fluxes: Merging Satellite Disturbance Mapping with Forest Inventory Data in a Carbon Cycle Model Framework

Forest carbon stocks and fluxes are highly dynamic following stand-clearing disturbances from severe fire and harvest and this presents a significant challenge for continental carbon budget assessments. In this work we use forest inventory data to parameterize a carbon cycle model to represent post-disturbance carbon trajectories of carbon pools and fluxes for specific forest types growing in high and low site productivity class settings. We then apply these trajectories to landscapes and regions based on forest age distributions derived from either the FIA data or from Landsat time series stacks (1985-2006) for 54 representative scenes throughout most of the conterminous United States. We estimate the net carbon uptake in forests caused by post-disturbance growth and decomposition ("regrowth sink") for forested regions across the country. At the landscape scale, the prevailing condition of positive net ecosystem productivity (NEP) is in stark contrast to local patches with large sources, particularly in the west where fires and clear cuts create contiguous disturbed patches. At the continental scale, regional differences in disturbance rates reflect management patterns of high disturbance rates in the Southeastern and South Central states, and lower disturbance rates in the Northeast and Northern Lakes States. Despite low contemporary disturbance rates in the Northeast and Northern Lakes States (0.61 and 0.74% y(exp −1)), the regrowth sink there remains of moderate to large strength (88 and 57 g C m(exp −2) y(exp −1)) owing to the continued legacy from historical clearing. Large regrowth sinks are also found in the Southeast, South Central, and Pacific Southwest regions (85, 86, and 95 g C m(exp −2) y(exp −1)) where disturbance rates also tend to be higher (1.59, 1.38, and 0.93% y(exp −1)). Overall, the Landsat-derived disturbance rates are elevated relative to FIA-derived rates (1.19 versus 0.93% y(exp −1)) particularly for western regions. The differences only modestly adjust regional- and continental-scale carbon budgets, reducing NEP from forest regrowth by about 8%.

carbon↗
NASA NTRS1997

A Categorization of Dynamic Analyzers

Program analysis techniques and tools are essential to the development process because of the support they provide in detecting errors and deficiencies at different phases of development. The types of information rendered through analysis includes the following: statistical measurements of code, type checks, dataflow analysis, consistency checks, test data,verification of code, and debugging information. Analyzers can be broken into two major categories: dynamic and static. Static analyzers examine programs with respect to syntax errors and structural properties., This includes gathering statistical information on program content, such as the number of lines of executable code, source lines. and cyclomatic complexity. In addition, static analyzers provide the ability to check for the consistency of programs with respect to variables. Dynamic analyzers in contrast are dependent on input and the execution of a program providing the ability to find errors that cannot be detected through the use of static analysis alone. Dynamic analysis provides information on the behavior of a program rather than on the syntax. Both types of analysis detect errors in a program, but dynamic analyzers accomplish this through run-time behavior. This paper focuses on the following broad classification of dynamic analyzers: 1) Metrics; 2) Models; and 3) Monitors. Metrics are those analyzers that provide measurement. The next category, models, captures those analyzers that present the state of the program to the user at specified points in time. The last category, monitors, checks specified code based on some criteria. The paper discusses each classification and the techniques that are included under them. In addition, the role of each technique in the software life cycle is discussed. Familiarization with the tools that measure, model and monitor programs provides a framework for understanding the program's dynamic behavior from different, perspectives through analysis of the input/output data.

Lujan, Michelle R.↗