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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Fast meta-solvers for 3D complex-shape scatterers using neural operators trained on a non-scattering problem

Three-dimensional target identification using scattering techniques requires high accuracy solutions and very fast computations for real-time predictions in some critical applications. We first train a deep neural operator (DeepONet) to solve wave propagation problems described by the Helmholtz equation in a domain without scatterers but at different wavenumbers and with a complex absorbing boundary condition. We then design two classes of fast meta-solvers by combining DeepONet with either relaxation methods, such as Jacobi and Gauss-Seidel, or with Krylov methods, such as GMRES and BiCGStab, using the trunk basis of DeepONet as a coarse-scale preconditioner. We leverage the spectral bias of neural networks to account for the lower part of the spectrum in the error distribution while the upper part is handled inexpensively using relaxation methods or fine-scale preconditioners. The meta-solvers are then applied to solve scattering problems with different shape of scatterers, at no extra training cost. We first demonstrate that the resulting meta-solvers are shape-agnostic, fast, and robust, whereas the standard standalone solvers may even fail to converge without the DeepONet. We then apply both classes of meta-solvers to scattering from a submarine, a complex three-dimensional problem. We achieve very fast solutions, especially with the DeepONet-Krylov methods, which require orders of magnitude fewer iterations than any of the standalone solvers.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

OFMspert: An architecture for an operator's associate that evolves to an intelligent tutor

With the emergence of new technology for both human-computer interaction and knowledge-based systems, a range of opportunities exist which enhance the effectiveness and efficiency of controllers of high-risk engineering systems. The design of an architecture for an operator's associate is described. This associate is a stand-alone model-based system designed to interact with operators of complex dynamic systems, such as airplanes, manned space systems, and satellite ground control systems in ways comparable to that of a human assistant. The operator function model expert system (OFMspert) architecture and the design and empirical validation of OFMspert's understanding component are described. The design and validation of OFMspert's interactive and control components are also described. A description of current work in which OFMspert provides the foundation in the development of an intelligent tutor that evolves to an assistant, as operator expertise evolves from novice to expert, is provided.

Mitchell, Christine M.↗
NASA NTRS2011

Making Spaceflight Practical and Affordable: Spacecraft Designs and Their Degree of Operability

As we push toward new and diverse space transportation capabilities, reduction in operations cost will become increasingly important. Achieving affordable and safe human spaceflight capabilities will be the mark of success for new programs and new providers. This paper reviews NASA s history in developing and operating human rated spacecraft, reviewing the key aspects of spacecraft design and their resultant impacts on operations phase complexity and cost. Specific examples from current and past programs are provided to tie together early program requirements, design implementation and resulting real-time operations experience into a complete "story" of design decisions and operational results. Based on these experiences, recommended techniques are outlined to enable earlier and more effective assessment of operations concerns during the design process.

Crocker, Alan R.↗
DOE OSTI2023

Early Fault Detection in Particle Accelerator Power Electronics Using Ensemble Learning

Early fault detection and fault prognosis are crucial to ensure efficient and safe operations of complex engineering systems such as the Spallation Neutron Source (SNS) and its power electronics (high voltage converter modulators). Following an advanced experimental facility setup that mimics SNS operating conditions, the authors successfully conducted 21 early fault detection experiments, where fault precursors are introduced in the system to a degree enough to cause degradation in the waveform signals, but not enough to reach a real fault. Nine different machine learning techniques based on ensemble trees, convolutional neural networks, support vector machines, and hierarchical voting ensembles are proposed to detect the fault precursors. Although all 9 models have shown a perfect and identical performance during the training and testing phase, the performance of most models has decreased in the next test phase once they got exposed to realworld data from the 21 experiments. The hierarchical voting ensemble, which features multiple layers of diverse models, maintains a distinguished performance in early detection of the fault precursors with 95% success rate (20/21 tests), followed by adaboost and extremely randomized trees with 52% and 48% success rates, respectively. The support vector machine models were the worst with only 24% success rate (5/21 tests). The study concluded that a successful implementation of machine learning in the SNS or particle accelerator power systems would require a major upgrade in the controller and the data acquisition system to facilitate streaming and handling big data for the machine learning models. In addition, this study shows that the best performing models were diverse and based on the ensemble concept to reduce the bias and hyperparameter sensitivity of individual models.

43 PARTICLE ACCELERATORS↗
NASA NTRS1981

System performance analyzer

The System Performance Analyzer (SPA) designed to provide accurate real time information about the operation of complex systems and developed for use on the Airborne Data Analysis/Monitor System (ADAMS), a ROLM 1666 based system is described. The system uses an external processor to operate an intelligent, simulated control panel. Also provided are functions to trace operations, determine frequency of use of memory areas, and time or count user tasks in a multitask environment. This augments the information available from the standard debugger and control panel, and reduces the time and effort needed by ROLM 1666 users in optimizing their system, as well as providing documentation of the effect of any changes. The operation and state of the system are evaluated.

Helbig, H. R.↗
DOE OSTI2021

Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

It is widely known that neural networks (NNs) are universal approximators of continuous functions. However, a less known but powerful result is that a NN with a single hidden layer can accurately approximate any nonlinear continuous operator. This universal approximation theorem of operators is suggestive of the structure and potential of deep neural networks (DNNs) in learning continuous operators or complex systems from streams of scattered data. Here, in this work, we thus extend this theorem to DNNs. We design a new network with small generalization error, the deep operator network (DeepONet), which consists of a DNN for encoding the discrete input function space (branch net) and another DNN for encoding the domain of the output functions (trunk net). We demonstrate that DeepONet can learn various explicit operators, such as integrals and fractional Laplacians, as well as implicit operators that represent deterministic and stochastic differential equations. We study different formulations of the input function space and its effect on the generalization error for 16 different diverse applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

SCALE Analyses of Scenarios in the Molten Salt Reactor Fuel Cycle

In support of the US Nuclear Regulatory Commission non-light-water reactor fuel cycle demonstration project, the capabilities of SCALE 6.3.1 for radionuclide characterization, criticality, and shielding were demonstrated through several scenarios in a molten salt reactor (MSR) nuclear fuel cycle. Three scenarios were selected for this study, with the molten salt breeder reactor (MSBR) serving as the reference design. The original thorium-based fuel salt used in MSBR was replaced with a 235 U-enriched fuel salt to better reflect anticipated future MSR concepts. The first scenario focused on the fuel salt preparation stage. Criticality analyses, using SCALE/CSAS-Shift and SCALE/SAMPLER, examined potential critical configurations in the fresh fuel salt container based on variables such as 235 U enrichment, UF 4 molar fraction, temperature, and container geometry. The second scenario explored the release of fission products during reactor operation in which the tritium buildup in the primary fuel salt was quantified through depletion calculations using SCALE/TRITON with continuous fuel makeup and fractional fission product removal. This scenario also assessed radioactivity levels in the off-gas system (OGS), quantifying radiotoxic nuclides that could be released into the environment. SCALE/SAMPLER was employed to perform uncertainty quantification to identify key operating parameters influencing the buildup of radiotoxic nuclides in the OGS. Additionally, radiation dose rates were calculated using SCALE/MAVRIC to estimate the maximum exposure levels within the reactor cell complex during operation. The final scenario evaluated the decay heat and radioactivity of the primary fuel salt collected in the drain tank, as well as the radiation dose rate outside the building from the presence of the drain tank. Overall, the application of SCALE’s various capabilities for radionuclide inventory generation, criticality analysis, and shielding in MSR fuel cycles was successfully demonstrated across these scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2022

The Cooling Loop A Anomaly of 2013: A Case Study in Human-Systems Resilience

Throughout the history of human spaceflight, NASA has employed an operational paradigm of 24/7 dependence on experts in Mission Control Center (MCC). In addition to nominal flight control and mission operations, these 85+ experts per shift manage anomaly detection, diagnosis, and response, and support the crew in real-time in performing maintenance and repair, procedure execution, and other complex mission operations. Future long-duration exploration missions (LDEMs) beyond low-Earth orbit (LEO) will not operate successfully using this same Human-Systems Integration Architecture (HSIA) where crew rely on ground controllers, have ready access to resupply, and have a fallback plan of evacuation. As distance from Earth increases and the communication delay grows, crews will need to respond independently and adequately to time-critical vehicle malfunctions. It will not always be sufficient or even possible to ‘safe the system’ and then wait upon ground intervention. A new and radically different HSIA is needed to accommodate the paradigm shift of deep-space travel. Historical International Space Station (ISS) data show that for a 30-day mission, the likelihood of a high-consequence vehicle anomaly of uncertain origin that requires rapid response is greater than 10%. The likelihood of such an event is 50% by the fourth month of the mission, and it grows exponentially with time. Our team has conducted in-depth investigations into these events and their corresponding anomaly resolution activities. Using MCC and Mission Evaluation Room (MER) anomaly resolution artifacts (including meeting summaries, caution and warning data, and ISS daily summaries), we created timelines detailing ground actions and in-orbit events for two significant anomalies. We then mapped these timelines onto Mars transit conditions, introducing a ground-crew communications time delay and shifting immediate response, time-critical task execution, and vehicle commanding to the crew. In detailing successful anomaly resolution in transit to Mars, the timelines highlight where effective resolution requires drastically evolved onboard capabilities. Though this research has yielded a rich data set based on ground response in past missions, there is still insufficient knowledge to assess the potential impact of inflight anomalies on a small autonomous crew on future LDEMs beyond LEO. To begin building an evidence base that will inform future HSIA standards and requirements, we are developing an approach to systematically capture crew anomaly response and procedure execution during early Artemis missions. Being the first human spaceflight beyond LEO since Apollo, early Artemis missions provide a rare and unique opportunity to serve as a testbed for Mars missions. Our work aims to capitalize on planned data collection to derive crew operational responses to anomalous events in real-time. Our team is also researching the level of simulation fidelity required for empirically validating proposed HSIA standards and evaluating HSIA implementations for LDEMs beyond LEO. This work will produce a trade space study of HSIA simulation objectives and fidelity requirements. Ultimately, these research efforts will assist in developing the standards and technologies needed to build a next-generation HSIA for LDEMs beyond LEO.

human-systems integration architecture↗
NASA NTRS1994

Prototyping Cassini Mission Operations

The Cassini mission to Saturn plans to employ several new operations concepts to decrease the complexity of Mission Operations and to maximize science return in a cost constrained environment.

operations requirements↗
NASA NTRSDate not supplied

ATM-X: Air Traffic Management – eXploration: Urban Air Mobility Overview

The UAM market is expected to be big in the billions of dollars. And, of course, UAM will need to be able to readily access and operate in the airspace for this to happen. In the ATM-X UAM sub-project, we are focused on NASA’s top-level goal of enabling UAM Maturity Level-4 (UML-4) operational density and complexity, with hundreds of simultaneous operations in a metropolitan area managed through a UTM-like architecture with third-party provided traffic management services. We are doing this by developing a concept of operations with the FAA and the UAM community that serves as a framework and guide for community research and development. We are also doing this by conducting research to define system requirements based on the concept and developing the UAM airspace management system for the AAM National Campaign.

urban air mobility↗
NASA NTRSDate not supplied

Usage-based Lifing of Lithium-Ion Battery with HybridPhysics-Informed Neural Networks

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.

Lithium-ion Battery↗
NASA NTRSDate not supplied

Analyzing Launch Operations using the Spaceport Throughput Analysis Resource (STAR)

NASA’s Kennedy Space Center (KSC) and Cape CanaveralSpace Force Station (CCSFS) are the world’s preeminent multi-user spaceport, providing facilities and launch capabilities to the agency, NASA’s commercial partners, and other government agencies. KSC works to ensure an environment in which NASA’s programs and other users can safely and effectively carry out their operations. Approximately 100 launches are expected to take place in 2024. KSC needs to meet the needs of customers who request launches based on their own schedules, but who may not be aware of KSC-wide resource limitations and external constraints on launch operations. KSC-wide resources include telecommunications, range tracking, commodities such as Helium and Nitrogen, and special equipment needed to support launches. External constraints include seasonal launch operations. Since space vehicles are complex and launch operations are uncertain, unexpected events can also cause delays in operations. The Spaceport Throughput AnalysisResource (STAR) assesses whether a specific set of pro-posed launches and associated activities can be performed given the resources KSC currently has available, and external constraints imposed on KSC operations. STAR integrates short-horizon scheduling and simulation of launches using a monte-carlo approach driven by configurable probabilities of different classes of event outcomes, including de-lays and worst-case use of resources. The resulting analyses inform stakeholders of key constraints preventing customers from being able to perform their missions as desired, and give insight into how to improve spaceport throughput. The rest of the paper is organized as follows. In 2 we de-scribe the problem STAR is intended to solve. In Section3 we formally describe the scheduling problem ingredients. In Section 4 we describe how manifests are simulated. InSection 5 we describe the constraints problem that is solved when rescheduling. In Section 6 we describe what information is recorded during manifest simulation in order to evaluate delays. In Section 7 we describe the specific problem solved for KSC. In Section 8 we describe the challenges of knowledge engineering for STAR.

Planning Scheduling Analysis↗
NASA NTRS1994

Risk reduction methodologies and technologies for the Earth Observing System (EOS) Operations Center (EOC)

This paper will discuss proposed Flight Operations methodologies and technologies for the Earth Observing System (EOS) Operations Center (EOC), to reduce risks associated with the operation of complex multi-instrument spacecraft in a multi-spacecraft environment. The EOC goals are to obtain 100 percent science data capture and maintain 100 percent spacecraft health, for each EOS spacecraft. Operations risks to the spacecraft and data loss due to operator command error, mission degradation due to mis-identification of an anomalous trend in component performance or mis-management of resources, and total mission loss due to improper subsystem configuration or mis-identification of an anomalous condition. This paper discusses automation of routine Flight Operations Team (FOT) responsibilities, Expert systems for real-time non-nominal condition decision support, and Telemetry analysis systems for in-depth playback data analysis and trending.

Hudson, Richard K.↗
NASA NTRS1995

An Experimental and Analytical Investigation of Stirling Space Power Converter Heater Head

NASA has identified the Stirling power converter as a prime candidate for the next generation power system for space applications requiring 60000 hr of operation. To meet this long-term goal, several critical components of the power converter have been analyzed using advanced structural assessment methods. Perhaps the most critical component, because of its geometric complexity and operating environment, is the power converter's heater head. This report describes the life assessment of the heater head which includes the characterization of a viscoplastic material model, the thermal and structural analyses of the heater head, and the interpolation of fatigue and creep test results of a nickel-base superalloy, Udimet 720 LI (Low Inclusions), at several elevated temperatures for life prediction purposes.

Abdul-Aziz, Ali↗
NASA NTRS2014

A Novel Application of TMA to Converging Runway Operations in a Simulated NextGen Environment

In 2013, the Airspace Operations Laboratory at NASA Ames Research Center conducted a human-in-the-loop simulation that examined the feasibility of applying a number of Next Generation Air Transportation System (NextGen) solutions to complex arrival operations in and around the New York metroplex. The delivery of arrivals to Newark Liberty International Airport (EWR) was the focus of this simulation, which involved extending the Terminal Sequencing and Spacing (TSS) scheduling capability to precisely schedule arrivals to intersecting runways 22 Left and 11. An important enabler for the concept was the availability of a dependent runway scheduler that was able to coordinate arrival times between aircraft landing on intersecting runways. At the time of the study, there was no functionality within the TSS scheduler to automatically create the dependent runway schedules. Instead, a Traffic Management Coordinator (TMC) manually created a de-conflicted schedule, which allowed for the concept to be tested as well as provided valuable insight into the tool requirements for a dependent runway scheduler. Throughout the course of preparations for the simulation, the individual serving as the TMC developed a number of strategies and procedures for manually adjusting the Scheduled Time of Arrival (STA) of the EWR arrivals in order to ensure that adequate spacing was provided between runway 22L and 11 arrival pairs. This paper describes the strategies and procedures that were developed and details how they were successfully applied during the simulation. Results will also be presented that shed additional light on exactly how the schedules were manipulated and their impact on delivery performance and safety. Ideas for additional TSS enhancements and next steps, based on participant feedback, will also be presented.

Homola, Jeffrey↗
NASA NTRS2019

Controlled Rest on the Flight Deck: Profile of Use, Challenges, and Best Practices

Managing fatigue in 24/7 operations is complex; fatigue and performance degradation can have health and safety consequences for the workers and can have economic and community consequences. We will present new findings on sleep, circadian misalignment, and performance in operational personnel. The presentations will shed light on how sleep and circadian misalignment affect workers' performance, safety, and health across multiple operations, and their application in fatigue risk management.As part of this symposium, I will discuss how pilots can use short naps (controlled rest) as a countermeasure to elevated sleepiness in-flight. My presentation will describe how and when controlled rest is used operationally and outline best practice guidelines for maximizing the benefits while managing the associated risks.

aviation↗
NASA NTRS2007

Analysis of Complex Valve and Feed Systems

A numerical framework for analysis of complex valve systems supports testing of propulsive systems by simulating key valve and control system components in the test loop. In particular, it is designed to enhance the analysis capability in terms of identifying system transients and quantifying the valve response to these transients. This system has analysis capability for simulating valve motion in complex systems operating in diverse flow regimes ranging from compressible gases to cryogenic liquids. A key feature is the hybrid, unstructured framework with sub-models for grid movement and phase change including cryogenic cavitations. The multi-element unstructured framework offers improved predictions of valve performance characteristics under steady conditions for structurally complex valves such as pressure regulator valve. Unsteady simulations of valve motion using this computational approach have been carried out for various valves in operation at Stennis Space Center such as the split-body valve and the 10-in. (approx.25.4-cm) LOX (liquid oxygen) valve and the 4-in. (approx.10 cm) Y-pattern valve (liquid nitrogen). Such simulations make use of variable grid topologies, thereby permitting solution accuracy and resolving important flow physics in the seat region of the moving valve. An advantage to this software includes possible reduction in testing costs incurred due to disruptions relating to unexpected flow transients or functioning of valve/flow control systems. Prediction of the flow anomalies leading to system vibrations, flow resonance, and valve stall can help in valve scheduling and significantly reduce the need for activation tests. This framework has been evaluated for its ability to predict performance metrics like flow coefficient for cavitating venturis and valve coefficient curves, and could be a valuable tool in predicting and understanding anomalous behavior of system components at rocket propulsion testing and design sites.

Ahuja, Vineet↗
DOE OSTI2024

Advanced Shuttle Strategies for Parallel QCCD Architectures

Trapped ions (TIs) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The quantum charge-coupled device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift toward more efficacious designs, this article introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities, such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.

43 PARTICLE ACCELERATORS↗