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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 NTRS1993

PC4CAST: A Tool for DSN Load Forecasting and Capacity Planning

Effectively planning the use and evolution of the Deep Space Network (DSN) is a complex problem involving many parameters. The tool that models many of these complexities, yet requires simple structured inputs and provides concise easy-to-understand metrics to aid in the planning process is discussed. The tool, PC4CAST, is used for both load forecasting (predicting how well planned that DSN resources meet expected demand) and as a decision support tool in the capacity-planning process (determining the relative benefits of capacity expansion options). It is now in use in the TDA Planning Office, has been used in numerous studies, and is also being used by the JPL Multimission Operations System Office (MOSO) as an integral part of Resource Allocation Team activities. Experience using the tool has helped to identify additional requirements that will further improve the planning process, which can be met by future PC4CAST versions.

S J Loyola↗
NASA NTRSDate not supplied

Development of a Thermal Radiator Optimization Tool with Alternate Coolants

The development of a modeling tool to optimize the design of a thermal radiator based on capacity, rejection temperature, geometry, type and coolant is presented. The radiator size is determined from the desired capacity, environmental conditions and rejection temperature. Flow through the radiator is derived from the overall heat load and prescribed inlet to outlet delta temperature for a given coolant. The tool considers radiator geometry (i.e., tube spacing and diameter, face-sheet thickness, overall size, etc.) and general type (i.e., parallel/manifold versus serpentine) in the optimization. Selection from a handful of potential coolants is also available in the tool which primarily affects necessary tube diameter to maintain turbulent flow and minimize pressure drop. An Equivalent System Mass (ESM) approach is utilized to include pump power in the optimization. Results from the tool and potential future enhancements are also discussed.

Coolant↗
NASA NTRS1982

EMU battery/SMM power tool characterization study

The power tool which will be used to replace the attitude control system in the SMM spacecraft was modified to operate from a self contained battery. The extravehicular mobility unit (EMU) battery was tested for the power tool application. The results are that the EMU battery is capable of operating the power tool within the pulse current range of 2.0 to 15.0 amperes and battery temperature range of -10 to 40 degrees Celsius.

Palandati, C.↗
NASA NTRS1984

EMU Battery/module Service Tool Characterization Study

The power tool which will be used to replace the attitude control system in the SMM spacecraft is being modified to operate from a self contained battery. The extravehicular mobility unit (EMU) battery, a silver zinc battery, was tested for the power tool application. The results obtained during show the EMU battery is capable of operating the power tool within the pulse current range of 2.0 to 15.0 amperes and battery temperature range of -10 to 40 degrees Celsius.

Palandati, C. F.↗
NASA NTRSDate not supplied

High-Order Methods in NASA’s Next Generation of Computational Fluid Dynamics Tools

The missions of the National Aeronautics and Space Administration (NASA) routinely produce unique requirements and challenges for development and application of Computational Fluid Dynamics (CFD) methods. NASA presently embodies four distinct Mission Directorates: Aeronautics Research, Exploration Systems, Science, and Space Operations. These missions generate requirements for systems that operate in a wide variety of environments. They range from the high-speed flight of aerodynamically optimized vehicles operating in the earth’s atmosphere to spacecraft designed for missions that don’t favor aerodynamic optimization, some operating in the atmosphere of planets and planetary moons such as Mars and Venus or Saturn’s moon Titan. Systems supporting these vehicles, such as rocket and jet propulsion, reaction control systems, fluid and thermal transfer systems, etc. can also generate their own unique set of flow phenomena that challenge today’s CFD methodology. Through the NASA Engineering and Safety Center (NESC), NASA annually conducts state-of-the-discipline assessments in fifteen distinct engineering disciplines. These assessments are performed by the NASA Technical Fellows that lead Technical Discipline Teams (TDT) of recognized experts in these fifteen areas. In the Aerosciences discipline, three topics have been identified as the top challenges for the discipline: aero-plume interaction prediction, unsteady separated flows, and aerothermodynamic prediction. These challenge areas are defined by the Agency’s high-risk projects and problems on which the NESC is requested to perform independent testing, analysis, and assessments. When viewed as a whole, these tests, analyses, and assessments provide a clear view of the recurring technical challenges facing Agency engineers and researchers and can be used to guide future research and technology development. The present state-of-the-art in the application of CFD at NASA is the use of Reynolds-Averaged Navier- Stokes (RANS) solvers, primarily executed in a steady-state mode of operation. In isolated cases, Unsteady RANS (URANS) solvers have been employed when steady RANS solutions produce poorly converging or oscillating results or in cases, such as aeroelastic analysis, which require unsteady aerodynamic simulation. For most traditional external and internal aerodynamic flows, structured overset grids or unstructured grids are employed to minimize geometric modeling and grid generation times. Grid adaptation, primarily as a series of coarse-grain intermediate processing steps is also seeing use on particularly complex flow problems and configurations. In the case of aerothermodynamic flows, engineers have been forced to continue to employ structured grid techniques as the present unstructured grid methodology has proven inadequate in the prediction of surface heating. In the area of aero-plume interaction modeling, two-gas, frozen chemistry simulation is generally the state-of-the- art, with some production solvers capable of predicting flows with only a single gas component. Prediction of flows falling into the afore-mentioned top Aerosciences technical challenges have severely stressed the present state-of-the-art in CFD prediction and for some problems, such as unsteady separated flows and aero-plume interaction cases, engineers have begun employing Large Eddy Simulation (LES) and Hybrid RANS/LES techniques. In some isolated aero-propulsion interaction cases, chemically reacting flow simulations have been applied. These methods are highly evolutionary and engineers have little experience in their application, so they cannot be heavily relied upon in today’s application environment. Therefore, this leads one to muse over which numerical technologies will be included in the CFD tools that will be employed 30 years in the future. This presentation will describe specific technical problems that have stressed NASA’s traditional CFD methods to their breaking point and will link these issues to the Agency’s top Aerosciences technical challenges. The discussion will then shift to the characteristics of future CFD solvers that will be required to attack these challenges and how these characteristics differ from the present state-of-the- art. High-order methods certainly appear to have a place in the development of future CFD tools and some of the physical characteristics of our most challenging problems suggest that high-order methods are the only way to effectively solve them. But there are some relatively severe implementation issues that face these methods, particularly in the area of general applicability and robust operation as an engineering tool. Desired characteristics of next-generation CFD solvers will be discussed and the author’s view of which emerging numerical technologies might be employed to address these attributes will also be presented

David M Schuster↗
NASA NTRSDate not supplied

Advancing Wildfire Monitoring with TEMPO and ML tools: Hourly Smoke and Fire‑Front Mapping and Near‑Surface NO₂ Predictions

Wildfires impose substantial impacts on communities and regions downwind of wildfire smoke. We present a TEMPO‑enabled workflow that generates value‑added Level‑3 smoke‑plume masks and fire‑front maps for large wildfires, such as 2024 Park Fire, using the self‑supervised deep learning system SIT‑FUSE, along with near‑surface NO₂ predictions produced by a foundation model (Microsoft Aurora). We conclude by outlining a roadmap for expanding these capabilities to additional Western U.S. wildfire events and for delivering actionable tools to stakeholders. This open-source, reproducible workflow provides a scalable framework for cross-agency wildfire monitoring to overcome traditional limitations in smoke-cloud discrimination and air-quality forecasting by incorporating TEMPO data and beyond.

Xiaohua Pan↗
NASA NTRS2026

Spacecraft Disposal Rosetta Stone: Parametric Tool for Orbital Lifetime, Disposal, and Cost Assessment

This Technical Memorandum documents a simplified, parametric method for evaluating spacecraft orbital lifetime, disposal compliance, and disposal-related cost impacts during early mission formulation and preliminary design. The method captures the dominant drivers of orbital decay—effective ballistic coefficient, operating altitude, and solar-cycle variability—using conservative bounding assumptions. Solar maximum conditions are used to bound achievable mission lifetime, while solar minimum conditions are used to bound disposal timelines and compliance with orbital debris requirements. A single tabulated dataset provides orbital lifetime under both solar-cycle extremes together with representative disposal ΔV required to ensure compliant disposal, enabling rapid assessment of disposal feasibility, cost sensitivity, and system-level impacts prior to committing to higher-fidelity analyses.

Orbital debris mitigation↗
NASA NTRSDate not supplied

Trajectory Engineering with Modular Patched Conics for Entry Systems and TPS (TEMPEST)

Brief Presenter Biography (35 word limit): Bohdan Wesely is an Aerospace Engineer in the Entry Systems and Technology Division at Ames. He has worked on a variety of projects for NASA including integrated TPS (thermal protection system) flight hardware deliveries and testing services for commercial partners. Introduction: TEMPEST is a new trajectory analysis framework that is designed to fill the gap between dedicated flight mechanics tools and aerothermal and TPS sizing tools. The project started as an SJSU master’s thesis and has since evolved into a general conceptual design tool capable of studying a wide variety of entry problems. Development is ongoing in the Entry Systems and Technology Division at NASA ARC. Why TEMPEST: Space missions involving entry into a planetary atmosphere involve a series of unique requirements across multiple disciplines. Whether it is traditional entry descent and landing (EDL), or aerocapture, the vehicle must navigate to its target landing location or orbit state, and the TPS must protect the payload during entry. The design process typically involves iterative handoffs between various flight mechanics, flow solver, and material response level tools. During the early conceptual phase, a wide variety of feasible trajectories are simulated in a Monte Carlo scenario which broadly satisfy the mission or landing requirements. Next, computational fluid dynamics (CFD), direct simulation Monte Carlo (DSMC), and other flow solver analyses are performed at various key trajectory points to generate an aero-database, heating and TPS design requirements also emerge at this stage. At this point, with updated aerodynamics from the various flow solvers, trajectories can be re-run, this in turn can change the required freestream conditions for the CFD tools, and as a project progresses, these analyses converge, and uncertainty is reduced. However, there is always a “hand-off” occurring between two inherently coupled phenomena. Analysis Description: One of the goals with TEMPEST is to use a variety of first principles estimation methods coupled with an atmosphere model to predict vehicle aerothermodynamics across the entire flight regime while propagating a 3 or 6 degree of freedom (DoF) trajectory. Aerodynamics methods include modified Newtonian, Maxwell and Cercignani- Lampis-Lord (CLL) for continuum, transitional, and free molecular flow regimes. Aerothermodynamics include boundary layer and reference enthalpy methods, and Mutation++ for non-equilibrium chemistry modeling. TEMPEST is also capable of stitching multiple trajectory segments together to study mission scenarios like multi-pass aerocapture and aero-gravity assists. Most of the program is implemented in MATLAB using modern system objects, it relies on several C++ shared libraries for supporting tools like Gmsh, the Global Reference Atmospheric Model (GRAM), and Mutation++. The various first principles aerothermal estimation methods are discretized across either a structured axisymmetric panel mesh or an unstructured tri-mesh generated from an open-source tool such as Gmsh, this allows solutions on the same mesh to be compared across tools such as CB-Aero. CFD Coupling. A physics-aware, gaussian process CFD anchoring scheme is proposed to adjust the various first principles methods as a CFD database is populated. One goal for this anchoring module is to inform the project where CFD should be run. Full knowledge of the entire trajectory, atmosphere, and aerothermodynamics allows for easier identification of high sensitivity areas and uncertainty quantification. While the first principles effects are well known and proven accurate in existing tools such as CB- Aero and Cart3D, a physics aware CFD anchoring scheme increases tool credibility across a project lifecycle. Material Response Modeling. Correct TPS sizing is critical for optimizing mass for science payloads and ensuring mission success. The process typically involves a thermal analysis along the trajectory with surface heating environments as a boundary condition. Several design constraints are maximum bondline temperature and maximum recession with various margining techniques. The material response tool FIAT, developed out of NASA Ames, is currently being integrated into the TEMPEST environment. TPS recession, shape change, mass loss, and mass property alteration are all factors that can perturb an entry trajectory. For missions like Mars 2020, recession was minimal and was safely handled separately as a post process. For missions such as Jupiter Galileo with a high TPS mass fraction or asteroid entries, recession plays a major role. The proposed fully coupled scheme is to use an epoch-based approach where the trajectory integration is halted after a recession threshold, the energy balance and FIAT are solved at each panel, the mesh, aerodynamics, and mass properties are updated, and the trajectory continues. Several computational tradeoffs have been made during the development of TEMPEST to limit the cost of a single trajectory and preserve its utility as a conceptual, rapid iteration tool. Conclusion: Development of TEMPEST is ongoing and the project is still in its infancy. This talk aims to showcase its unique capabilities to support future NASA entry systems missions.

Bohdan O Wesely↗
NASA NTRS2010

Ares I-X Ground Diagnostic Prototype

Automating prelaunch diagnostics for launch vehicles offers three potential benefits. First, it potentially improves safety by detecting faults that might otherwise have been missed so that they can be corrected before launch. Second, it potentially reduces launch delays by more quickly diagnosing the cause of anomalies that occur during prelaunch processing. Reducing launch delays will be critical to the success of NASA's planned future missions that require in-orbit rendezvous. Third, it potentially reduces costs by reducing both launch delays and the number of people needed to monitor the prelaunch process. NASA is currently developing the Ares I launch vehicle to bring the Orion capsule and its crew of four astronauts to low-earth orbit on their way to the moon. Ares I-X will be the first unmanned test flight of Ares I. It is scheduled to launch on October 27, 2009. The Ares I-X Ground Diagnostic Prototype is a prototype ground diagnostic system that will provide anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage thrust vector control (TVC) and for the associated ground hydraulics while it is in the Vehicle Assembly Building (VAB) at John F. Kennedy Space Center (KSC) and on the launch pad. It will serve as a prototype for a future operational ground diagnostic system for Ares I. The prototype combines three existing diagnostic tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool that is commercially produced by Qualtech Systems, Inc. It uses a qualitative model of failure propagation to perform fault isolation and diagnostics. We adapted an existing TEAMS model of the TVC to use for diagnostics and developed a TEAMS model of the ground hydraulics. The second tool, Spacecraft Health Inference Engine (SHINE), is a rule-based expert system developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification. The prototype uses the outputs of SHINE as inputs to TEAMS. The third tool, the Inductive Monitoring System (IMS), is an anomaly detection tool developed at NASA Ames Research Center and is currently used to monitor the International Space Station Control Moment Gyroscopes. IMS automatically "learns" a model of historical nominal data in the form of a set of clusters and signals an alarm when new data fails to match this model. IMS offers the potential to detect faults that have not been modeled. The three tools have been integrated and deployed to Hangar AE at KSC where they interface with live data from the Ares I-X vehicle and from the ground hydraulics. The outputs of the tools are displayed on a console in Hangar AE, one of the locations from which the Ares I-X launch will be monitored. In a previous publication, we discussed how we selected the three tools based primarily on their ability to be certified for human spaceflight and described our plans for the prototype. This abstract is due October 23, 2009, and the Ares I-X launch is currently scheduled for October 27, 2009. If this abstract is accepted, then the full paper will describe how the prototype performed before the launch. It will include an analysis of the prototype's accuracy, including false-positive rates, false-negative rates, and receiver operating characteristics (ROC) curves. It will also include a description of the prototype's computational requirements, including CPU usage, main memory usage, and disk usage. If the prototype detects any faults during the prelaunch period then the paper will include a description of those faults. Similarly, if the prototype has any false alarms then the paper will describe them and will attempt to explain their causes. Also, the paper will describe the three tools and how they are used in the prototype. It will include a description of the TEAMS models of the Ares I-X first-stage TVC and associated ground hydraulics and how we adapted the TVC model for use in real-time diagnostics. It will describe the SHINE rules used for fault detection and mode identification and the software architecture that interfaces the various pieces of existing software that are part of the prototype to one another. It will describe how we selected the sensor values and commands that were used to train the IMS model and how we optimized the number of clusters in the IMS model. It will include screen shots of the graphical display that we developed in Java to display the outputs of the three tools. Because Ares I-X data was not yet available to us while we were developing the prototype, we used historical data from the Space Shuttle's Solid Rocket Booster (SRB) TVCs and the associated ground hydraulics to train IMS and to test the entire prototype. Because most of the failure modes that we modeled have never occurred in the Shuttle we inserted simulated failures into the Shuttle data. The Ares I-X first-stage TVC is very similar to the SRB TVC and we expect the data will be very similar. After the launch, we will determine how similar the data actually is and report how any differences in the data affected the diagnostic accuracy of the prototype. Finally, although we did not get the prototype certified, we designed it in a way that it could be certified and wrote a preliminary certification plan. The paper will include a brief summary of how we considered the need for certification in the design of the prototype, how we tested the prototype before deploying it to Hangar AE, and how we would propose to get it certified if it were deployed as an operational system. The paper will conclude with a description of some of the challenges we faced and some of the lessons learned in developing and deploying the prototype.

International Space Station↗
NASA NTRS2010

Ares I-X Ground Diagnostic Prototype

The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

Machine Learning↗
NASA NTRSDate not supplied

Advances in Design Capabilities for Planetary Missions from the NASA Entry Systems Modeling and Instrumentation Portfolio

The Entry Systems Modeling project (ESM) is supported by both the NASA Space Technology and the Science Mission Directorates and focuses on developing simulation tools and validated models for characterizing the performance of entry systems tailored to planetary destinations across the Solar System. ESM is organized into six technical capability areas that together address all relevant factors related to spacecraft entry, as well as some aspects of descent: Thermal Protection System (TPS) Materials; Aerothermodynamics; Entry & Descent Vehicle Dynamics; Guidance, Navigation, and Control; Vehicle Systems Analysis; and Advanced Tools and Numerical Methods. Development within the capability areas is undertaken explicitly with a focus on transition and infusion to science missions, human exploration missions, and commercial space activities. The present talk details developments that specifically impact science missions, including simulation tool capabilities that aid in mission design and model development to understand entry system performance at a given destination. Examples of the successful infusion and transition of such project outcomes to science missions also are provided. Several simulation tool development efforts within ESM have resulted in new design capabilities for missions. One such outcome is improved toolsets for mission trajectory and concept of operations design. Specifically, an initiative to couple a leading tool for entry, ascent/descent, and orbital trajectory optimization (Program to Optimize Simulated Trajectories II or POST2) to those used within the Agency for interplanetary trajectory optimization (Copernicus and Monte) has made substantial progress, with the outcomes to date promising to allow efficient trajectory optimization across mission phases. Additionally, toolchains for the evaluation of vehicle performance during entry and descent have been developed that allow assessment of multi-dimensional aeroheating on detailed vehicle geometries, characterization of deployment and inflation of parachutes, and assessment of vehicle dynamic stability during descent. These capabilities are achieved by coupling diverse sets of physics together – material response, computational fluid dynamics, radiation, and vehicle dynamics – to suitably describe complex entry and descent phenomena. Several model development and validation efforts for specific destinations and entry regimes also are underway within the ESM project. For instance, new experimental capabilities to validate radiation models at low densities/high altitudes recently have been established with project support, specifically the Low-Density Shock Tube (LDST) at the NASA Ames Research Center Electric Arc Shock Tube (EAST) facility. The LDST is being leveraged to develop improved models of shock layer kinetics and radiation in Titan atmospheres, while future studies will be conducted in the LDST and the existing high velocity shock tube to provide validation data for radiation models of Venus, Ice Giants, and Mars atmospheres. Models describing the aerothermal and thermo-structural performance of Thermal Protection System (TPS) materials has been another focus, with multiscale modeling activities on-going for the two leading TPS materials applicable to a range of entry conditions and science missions: the Phenolic-Impregnated Carbon Ablator (PICA) and woven materials like 3D Mid-Density Carbon Phenolic (3MDCP). A continual effort is made to infuse and transition outcomes from ESM simulation tool and model development activities into relevant science missions. Significant progress has been made on this front, with missions such as Dragonfly, DAVINCI, and Mars Missions benefitting from project outcomes. The groundwork also is being laid to provide insights into forward looking missions to Gas/Ice Giants as well as for potential sample returns.

Justin Haskins↗
NASA NTRS1993

A SIMULINK Environment for Flight Dynamics and Control Analysis - Application to the DHC-2 'Beaver', Part 1. Implementation of a Model Library in SIMULINK

The design of advanced Automatic Aircraft Control Systems (AACS's) can be improved upon considerably if the designer can access all models and tools required for control system design and analysis through a graphical user-interface, from within one software environment. This MSc-thesis presents the first step in the development of such an environment, which is currently being done at the Section for Stability and Control of Delft University of Technology, Faculty of Aerospace Engineering. The environment is implemented within the commercially available software package MATLAB/SIMULINK. The report consists of two parts. Part I gives a detailed description of the AACS design environment. The heart of this environment is formed by the SIMULINK implementation of a nonlinear aircraft model in block-diagram format. The model has been worked out for the old laboratory aircraft of the Faculty, the De Havilland DHC-2 'Beaver', but due to its modular structure, it can easily be adapted for other aircraft. Part I also describes MATLAB programs which can be applied for finding steady-state trimmed-flight conditions and for linearization of the aircraft model, and it shows how the built-in simulation routines of SIMULINK have been used for open-loop analysis of the aircraft dynamics. Apart from the implementation of the models and tools, a thorough treatment of the theoretical backgrounds is presented. Part II of this report presents a part of an autopilot design process for the 'Beaver' aircraft, which clearly demonstrates the power and flexibility of the AACS design environment from part I. Evaluations of all longitudinal and lateral control laws by means of nonlinear simulations are treated in detail. The AACS design environment from part I proved to be a very useful tool for designing the control laws of the 'Beaver' autopilot within a very tight time-schedule. The autopilot design process itself will be used as a guideline for future AACS research at the Faculty of Aerospace Engineering. Flight tests of the 'Beaver' autopilot, done after evaluating the control laws in the SIMULINK package, proved to be quite successful. In the future, the AACS design package will evolve into a standardized, integrated design environment which can be applied to virtually any type of aircraft. The AACS design cycle will be shortened further by developing tools for automatically porting control laws from the MATLAB/SIMULINK environment to a piloted real-time flight simulator and the Flight Control Computers of the aircraft.

Aircraft Modelling↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. Data-driven techniques have a number of advantages over other methods for monitoring complex space vehicles. Unlike model-based systems, the developer does not need to understand or encode the internal operation of the system. The knowledge required to monitor the system is automatically derived from archived data from system operation. Unlike rule-based systems, data-driven systems do not require system analysts to define nominal relationships among sensors. Analysts can and often do determine these relationships for a system with few sensors; it is more difficult to analytically determine the nominal relationship among a large number of sensors. Data-driven techniques are not limited to low-dimensional spaces and work as effectively with dozens of parameters as they do with a few. Knowledge bases formed by data-driven techniques are also easy to update. As the operating envelope of the monitored system is expanded, data-driven techniques can be quickly retrained to incorporate the new behavior into the knowledge base. The expertise and time-consuming process of updating a model or rule base to maintain consistency with the new operation is not required. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or analysis of archived events. System data is compared with the nominal IMS model to produce a measure of how well current system behavior matches the normal behavior defined by the training data. Significant deviations from the nominal system model can provide alerts to system malfunctions or precursors of significant failures. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments. Initially, the TVSM software will run open loop, providing system health information and recommendations to ground operators, without automatically performing fault-mitigating corrective actions. After the end of the satellite's mission, closed loop tests combining TVSM monitoring and diagnosis with reactive capabilities by the flight software will be performed. In addition to monitoring for long periods of actual operation, the experiment will include fault injection into TacSat-3 data as well as commanded operations to test and evaluate automatic ISHM monitoring and recovery under controlled conditions.

Satellites↗
NASA NTRSDate not supplied

Form Factors, Grey Bodies and Radiation Conductances (Radks)

With today's analysis tools, large, complex thermal radiation problems are easily solved; But, as with any analytical tool, lack of an understanding of the fundamental equations and technique limitations may leave you with the wrong answer; Whether you are a new engineer or a seasoned veteran, an understanding of the techniques employed by these powerful analysis tools is crucial.

Fluids↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
NASA NTRS2009

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, satellite vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed, or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery.

Satellites↗
NASA NTRS1995

Thermal Neutral Format Based on the Step Technology

The exchange of models is one of the most serious problems currently encountered in the practice of spacecraft thermal analysis. Essentially, the problem originates in the diversity of computing environments that are used across different sites, and the consequent proliferation of native tool formats. Furthermore, increasing pressure to reduce the development's life cycle time has originated a growing interest in the so-called spacecraft concurrent engineering. In this context, the realization of the interdependencies between different disciplines and the proper communication between them become critical issues. The use of a neutral format represents a step forward in addressing these problems. Such a means of communication is adopted by consensus. A neutral format is not directly tied to any specific tool and it is kept under stringent change control. Currently, most of the groups promoting exchange formats are contributing with their experience to STEP, the Standard for Exchange of Product Model Data, which is being developed under the auspices of the International Standards Organization (ISO 10303). This paper presents the different efforts made in Europe to provide the spacecraft thermal analysis community with a Thermal Neutral Format (TNF) based on STEP. Following an introduction with some background information, the paper presents the characteristics of the STEP standard. Later, the first efforts to produce a STEP Spacecraft Thermal Application Protocol are described. Finally, the paper presents the currently harmonized European activities that follow up and extend earlier work on the area.

P Planas Almazan↗
NASA NTRS1997

NASA Aerospace Flight Battery Systems Program Update

The objectives of NASA's Aerospace Flight Battery Systems Program is to: develop, maintain and provide tools for the validation and assessment of aerospace battery technologies; accelerate the readiness of technology advances and provide infusion paths for emerging technologies; provide NASA projects with the required database and validation guidelines for technology selection of hardware and processes relating to aerospace batteries; disseminate validation and assessment tools, quality assurance, reliability, and availability information to the NASA and aerospace battery communities; and ensure that safe, reliable batteries are available for NASA's future missions.

Manzo, Michelle↗