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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 sources NASA NTRS DOE OSTI

NASA NTRS2012

General MACOS Interface for Modeling and Analysis for Controlled Optical Systems

The General MACOS Interface (GMI) for Modeling and Analysis for Controlled Optical Systems (MACOS) enables the use of MATLAB as a front-end for JPL s critical optical modeling package, MACOS. MACOS is JPL s in-house optical modeling software, which has proven to be a superb tool for advanced systems engineering of optical systems. GMI, coupled with MACOS, allows for seamless interfacing with modeling tools from other disciplines to make possible integration of dynamics, structures, and thermal models with the addition of control systems for deformable optics and other actuated optics. This software package is designed as a tool for analysts to quickly and easily use MACOS without needing to be an expert at programming MACOS. The strength of MACOS is its ability to interface with various modeling/development platforms, allowing evaluation of system performance with thermal, mechanical, and optical modeling parameter variations. GMI provides an improved means for accessing selected key MACOS functionalities. The main objective of GMI is to marry the vast mathematical and graphical capabilities of MATLAB with the powerful optical analysis engine of MACOS, thereby providing a useful tool to anyone who can program in MATLAB. GMI also improves modeling efficiency by eliminating the need to write an interface function for each task/project, reducing error sources, speeding up user/modeling tasks, and making MACOS well suited for fast prototyping.

Sigrist, Norbert↗

NASA NTRSDate not supplied

Modeling Spacesuit-Human Interaction for Injury Risk Identification

Performing functional tasks while inside of the space suit introduces additional ergonomic challenges which can lead to musculoskeletal stresses and injuries in astronauts. Computational modeling of the suit-body interaction can be used alongside human-in-the-loop testing to understand and mitigate these risks and potentially improve the work performance. In this work, a static rigid-body model of the human body was integrated with the space suit and the process is described. This model enables prediction of the resulting joint torques and musculoskeletal loading from a simulated extravehicular activity (EVA) task. For representative EVA tasks, joint torque and body angles were used as parameters to predict the muscle strength required to achieve the task, as well as the percentage of the general and astronaut-like population that could achieve that strength demand. Population strength capability can be used as an indicator of the difficulty of a task and the level of injury risk for the given task types and crew anthropometry. The sensitivity of the model to inputs such as body joint location within the space suit and individual anthropometry will also be evaluated. Future work will use a database of3D human body scans and the movements of the body inside the suit during different EVA tasks to identify potential soft tissue contact points. The specific locations and magnitudes of contacts between the body and suit are expected to identify risk of repetitive tissue contact stresses. Overall, this model will provide a new tool to structurally identify the injury risks of EVA tasks and evaluate alternate strategies to reduce injury risk.

Garima Gupta↗

DOE OSTI2025

Evaluating FRI3D for Cost Savings in Fire Hazard Analysis at DOE Sites

A fire hazard analysis, required for many U.S. Department of Energy (DOE) facilities, is a complex, cumbersome, and costly process. Fire hazard analyses may be viewed as a checkbox, but ideally and in spirit with the DOE-STD-1066, the fire hazard analysis (FHA) should be a part of the workflow and used to help in modifications, maintenance, and improving operational safety. With current FHA development processes, it is both time and cost prohibitive for true integration. A tool called Fire Risk Investigation in 3D or FRI3D was developed under the DOE Light Water Reactor Sustainability program to simplify and automate many aspects of a fire probabilistic risk analysis for existing nuclear power plants. The FRI3D tool automates fire scenarios by combining approved fire simulation codes, U.S. Nuclear Regulatory Commission fire calculations methods, 3D modeling and visualization, and probabilistic risk analysis models into a single workflow supported with a user interface. FRI3D was initially designed for used in combination with a PRA, this case study, evaluated using FRI3D for a plant modification, determined the benefits that detailed fire modeling can have for U.S. Department of Energy facilities with or without a PRA model. It also looked at what tasks from DOE requirements could be reduced using the tool and what is needed to integrate fire hazard analysis into site workflow.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Reduced-order modeling through machine learning and graph-theoretic approaches for brittle fracture applications

Typically, thousands of computationally expensive micro-scale simulations of brittle crack propagation are needed to upscale lower length scale phenomena to the macro-continuum scale. Running such a large number of crack propagation simulations presents a significant computational challenge, making reduced-order models (ROMs) attractive for this task. Here, the ultimate goal of this research is to develop ROMs that have sufficient accuracy and low computational cost so that these upscaling simulations can be readily performed. However, constructing ROMs for these complex simulations presents its own challenge. Here, we present and compare four different approaches for reduced-order modeling of brittle crack propagation in geomaterials. These methods rely on machine learning (ML) and graph-theoretic algorithms to approximate key aspects of the brittle crack problem. These methods also incorporate different physics-based assumptions in order to reduce the training requirements while maintaining accurate physics as much as possible. Results from the ROMs are directly compared against a high-fidelity model of brittle crack propagation. Further, the strengths and weaknesses of the ROMs are discussed, and we conclude that combining smart physics-informed feature engineering with highly trainable ML models provides the best performance. The ROMs considered here have computational costs that are orders-of-magnitude less than the cost associated with high-fidelity physical models while maintaining good accuracy.

36 MATERIALS SCIENCE↗

NASA NTRS1993

Task planning with uncertainty for robotic systems

In a practical robotic system, it is important to represent and plan sequences of operations and to be able to choose an efficient sequence from them for a specific task. During the generation and execution of task plans, different kinds of uncertainty may occur and erroneous states need to be handled to ensure the efficiency and reliability of the system. An approach to task representation, planning, and error recovery for robotic systems is demonstrated. Our approach to task planning is based on an AND/OR net representation, which is then mapped to a Petri net representation of all feasible geometric states and associated feasibility criteria for net transitions. Task decomposition of robotic assembly plans based on this representation is performed on the Petri net for robotic assembly tasks, and the inheritance of properties of liveness, safeness, and reversibility at all levels of decomposition are explored. This approach provides a framework for robust execution of tasks through the properties of traceability and viability. Uncertainty in robotic systems are modeled by local fuzzy variables, fuzzy marking variables, and global fuzzy variables which are incorporated in fuzzy Petri nets. Analysis of properties and reasoning about uncertainty are investigated using fuzzy reasoning structures built into the net. Two applications of fuzzy Petri nets, robot task sequence planning and sensor-based error recovery, are explored. In the first application, the search space for feasible and complete task sequences with correct precedence relationships is reduced via the use of global fuzzy variables in reasoning about subgoals. In the second application, sensory verification operations are modeled by mutually exclusive transitions to reason about local and global fuzzy variables on-line and automatically select a retry or an alternative error recovery sequence when errors occur. Task sequencing and task execution with error recovery capability for one and multiple soft components in robotic systems are investigated.

Cao, Tiehua↗

DOE OSTI2024

Employing artificial intelligence to steer exascale workflows with colmena

Computational workflows are a common class of application on supercomputers, yet the loosely coupled and heterogeneous nature of workflows often fails to take full advantage of their capabilities. We created Colmena to leverage the massive parallelism of a supercomputer by using Artificial Intelligence (AI) to learn from and adapt a workflow as it executes. Colmena allows scientists to define how their application should respond to events (e.g., task completion) as a series of cooperative agents. In this paper, we describe the design of Colmena, the challenges we overcame while deploying applications on exascale systems, and the science workflows we have enhanced through interweaving AI. The scaling challenges we discuss include developing steering strategies that maximize node utilization, introducing data fabrics that reduce communication overhead of data-intensive tasks, and implementing workflow tasks that cache costly operations between invocations. These innovations coupled with a variety of application patterns accessible through our agent-based steering model have enabled science advances in chemistry, biophysics, and materials science using different types of AI. In conclusion, our vision is that Colmena will spur creative solutions that harness AI across many domains of scientific computing.

Workflows↗

NASA NTRS1988

Estimation of duration and mental workload at differing times of day by males and females

Two experiments are reported which investigated whether male and female operator duration estimation and subjective workload followed conventional circadian fluctuation. In the first experiment, twenty-four subjects performed a filled time-estimation task in a constant blacked-out, noise-reduced environment at 0800, 1200, 1600, and 2000 h. In the second experiment, twelve subjects performed an unfilled time estimation task in similar conditions at 0900, 1400, and 1900 h. At the termination of all experimental sessions, participants completed the NASA TLX workload assessment questionnaire as a measure of perceived mental workload. Results indicated that while physiological response followed an expected pattern, estimations of duration and subjective perception of workload showed no significant effects for time-of-day. In each of the experiments, however, there were significant differences in durational estimates and mental workload response depending upon the gender of the participant. Results are taken to support the assertion that subjective workload is responsive largely to task-related factors and indicates the important differences that may be expected due to operator gender.

Hancock, P. A.↗

NASA NTRS1983

Development of strain tolerant thermal barrier coating systems, tasks 1 - 3

Insulating ceramic thermal barrier coatings can reduce gas turbine airfoil metal temperatures as much as 170 C (about 300 F), providing fuel efficiency improvements greater than one percent and durability improvements of 2 to 3X. The objective was to increase the spalling resistance of zirconia based ceramic turbine coatings. To accomplish this, two baseline and 30 candidate duplex (layered MCrAlY/zirconia based ceramic) coatings were iteratively evaluated microstructurally and in four series of laboratory burner rig tests. This led to the selection of two candidate optimized 0.25 mm (0.010 inch) thick plasma sprayed partially stabilized zirconia ceramics containing six weight percent yttria and applied with two different sets of process parameters over a 0.13 mm (0.005 inch) thick low pressure chamber sprayed MCrAlY bond coat. Both of these coatings demonstrated at least 3X laboratory cyclic spalling life improvement over the baseline systems, as well as cyclic oxidation life equivalent to 15,000 commercial engine flight hours.

Anderson, N. P.↗

NASA NTRS1992

Computer Data-Entry System Facilitates Proofreading

Visual optical-electronic display for encoding and measurement (VODEM) is system of computer data-entry and display equipment and associated software. Designed to reduce significantly rate of errors in text or other data entered manually or by optical character-recognition equipment and eases task of proofreading those data. Accuracy increased and stress reduced. Provides head-on display including two texts or sets of data to be compared. Developed in large-screen and small-screen version differing mainly in display equipment. Large-screen version includes cathode-ray-tube video display; small-screen version includes smaller liquid-crystal display mounted on computer-controlled x-y drive.

Woo, John, Jr.↗

NASA NTRSDate not supplied

Logical Shadow Tomography: Efficient Estimation of Error-mitigated Observables

In near-term quantum applications, reducing errors and improving device reliability is an essential task. Towards these ends, various techniques have been introduced in recent literature, collectively referred to as quantum error mitigation techniques, for reducing errors in pre-fault-tolerant devices. Here, we introduce logical shadow tomography as a versatile error mitigation method. Our technique uses a stabilizer code to encode information in a logical state. Instead of doing active error correction, quantum states will be measured at the end of computation via shadow tomography and non-logical errors are projected out in the classical post-processing. Relative to quantum subspace expansion which requires O(2(M-1)L) experiments to estimate an logical Pauli observable encoded by an [[M, L, d]] code, our technique only requires 2L experiments, an important practical reduction in resources.

Hong-Ye Hu↗

NASA NTRS2007

The DaveMLTranslator: An Interface for DAVE-ML Aerodynamic Models

It can take weeks or months to incorporate a new aerodynamic model into a vehicle simulation and validate the performance of the model. The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) has been proposed as a means to reduce the time required to accomplish this task by defining a standard format for typical components of a flight dynamic model. The purpose of this paper is to describe an object-oriented C++ implementation of a class that interfaces a vehicle subsystem model specified in DAVE-ML and a vehicle simulation. Using the DaveMLTranslator class, aerodynamic or other subsystem models can be automatically imported and verified at run-time, significantly reducing the elapsed time between receipt of a DAVE-ML model and its integration into a simulation environment. The translator performs variable initializations, data table lookups, and mathematical calculations for the aerodynamic build-up, and executes any embedded static check-cases for verification. The implementation is efficient, enabling real-time execution. Simple interface code for the model inputs and outputs is the only requirement to integrate the DaveMLTranslator as a vehicle aerodynamic model. The translator makes use of existing table-lookup utilities from the Langley Standard Real-Time Simulation in C++ (LaSRS++). The design and operation of the translator class is described and comparisons with existing, conventional, C++ aerodynamic models of the same vehicle are given.

Hill, Melissa A.↗

NASA NTRS2000

Autonomous Performance Monitoring System: Monitoring and Self-Tuning (MAST)

Maintaining the long-term performance of software onboard a spacecraft can be a major factor in the cost of operations. In particular, the task of controlling and maintaining a future mission of distributed spacecraft will undoubtedly pose a great challenge, since the complexity of multiple spacecraft flying in formation grows rapidly as the number of spacecraft in the formation increases. Eventually, new approaches will be required in developing viable control systems that can handle the complexity of the data and that are flexible, reliable and efficient. In this paper we propose a methodology that aims to maintain the accuracy of flight software, while reducing the computational complexity of software tuning tasks. The proposed Monitoring and Self-Tuning (MAST) method consists of two parts: a flight software monitoring algorithm and a tuning algorithm. The dependency on the software being monitored is mostly contained in the monitoring process, while the tuning process is a generic algorithm independent of the detailed knowledge on the software. This architecture will enable MAST to be applicable to different onboard software controlling various dynamics of the spacecraft, such as attitude self-calibration, and formation control. An advantage of MAST over conventional techniques such as filter or batch least square is that the tuning algorithm uses machine learning approach to handle uncertainty in the problem domain, resulting in reducing over all computational complexity. The underlying concept of this technique is a reinforcement learning scheme based on cumulative probability generated by the historical performance of the system. The success of MAST will depend heavily on the reinforcement scheme used in the tuning algorithm, which guarantees the tuning solutions exist.

Peterson, Chariya↗

NASA NTRS1990

Optimal Allocation Of Tasks In Hypercube Computers

Uniform tasks distributed uniformly or else assigned to one processor. Investigation in theory of scheduling yielded optimal scheme for allocation of tasks among digital data processors in hypercube ensemble. Applies to tasks that require equal time to execute, performed in any order, and between any two of which equal amounts of communication required. Reduces overall processing time for given set of computational tasks.

Salama, Moktar A.↗

NASA NTRS2012

Motion-Capture-Enabled Software for Gestural Control of 3D Models

Current state-of-the-art systems use general-purpose input devices such as a keyboard, mouse, or joystick that map to tasks in unintuitive ways. This software enables a person to control intuitively the position, size, and orientation of synthetic objects in a 3D virtual environment. It makes possible the simultaneous control of the 3D position, scale, and orientation of 3D objects using natural gestures. Enabling the control of 3D objects using a commercial motion-capture system allows for natural mapping of the many degrees of freedom of the human body to the manipulation of the 3D objects. It reduces training time for this kind of task, and eliminates the need to create an expensive, special-purpose controller.

Norris, Jeffrey S.↗

NASA NTRS2019

Validation of Floating Node Method Using Three-Point Bend Doubler Under Quasi-Static Loading

The NASA Advanced Composite Project (ACP), an industry/government/university partnership, has embarked upon the task of developing technology that can aid in reducing the time line for structural certification of aircraft composite parts using a combination of technologies, one of which is high fidelity damage progression computational methods. Phase II of this project included a task for validating an approach based on the Floating Node Method combined with Directional Cohesive Elements (FNM-DCZE). This paper discusses predicted damage onset and growth in a three-point bend doubler specimen compared to experimental results. Sensitivity of the simulations to mesh refinement as well as key material properties and thermal effects are studied and reported. Overall, qualitative results suggest the main aspects of the damage progression have been captured, with the simulated damage morphology and sequence of events resembling closely what was observed experimentally. Quantitatively, the first load-peak is predicted. However, the re-loading observed in the experiments, after the first load peak, is not captured numerically, suggesting further investigation may be worth pursuing.

Selvarathinam, Alex S.↗

NASA NTRS1989

Task-oriented display design: Concept and example

The general topic was in the area of display design alternatives for improved man-machine performance. The intent was to define and assess a display design concept oriented toward providing this task-oriented information. The major focus of this concept deals with the processing of data into parameters that are more relevant to the task of the human operator. Closely coupled to this concept of relevant information is the form or manner in which this information is actually presented. Conventional forms of presentation are normally a direct representation of the underlying data. By providing information in a form that is more easily assimilated and understood, a reduction in human error and cognitive workload may be obtained. A description of this proposed concept with a design example is provided. The application for the example was an engine display for a generic, twin-engine civil transport aircraft. The product of this concept was evaluated against a functionally similar, traditional display. The results of this evaluation showed that a task-oriented approach to design is a viable concept with regard to reducing user error and cognitive workload. The goal of this design process, providing task-oriented information to the user, both in content and form, appears to be a feasible mechanism for increasing the overall performance of a man-machine system.

Abbott, Terence S.↗

NASA NTRS1989

Task-oriented display design - Concept and example

Abbott, Terence S.↗