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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Robust Rapid Cellular Metabolite Sensing Using Benchtop NMR and SABRE-Hyperpolarized [1- 13 C]Pyruvate

Hyperpolarized NMR has emerged as a powerful analytical technique to significantly enhance targeted NMR signals, improving the sensitivity for investigations of unique chemical and biological dynamics. Here, we demonstrate the use of a hyperpolarization strategy based on Signal Amplification By Reversible Exchange (SABRE) to generate highly reproducible doses of a hyperpolarized [1- 13 C]pyruvate probe for benchtop characterization of yeast metabolism. This method allows rapid, scalable, and benchtop preparation of biocompatible hyperpolarized solutions suitable for live-cell experiments. We show that this production can be dove-tailed into a modular, compact workflow to characterize real-time metabolism in cell cultures, using Saccharomyces cerevisiae (Baker’s yeast) as a model organism. With high temporal resolution, we show that this method can resolve the conversion of hyperpolarized [1- 13 C]pyruvate into oxidative decarboxylation products CO 2 and bicarbonate. This conversion exhibits sustained and detectable metabolic activity for over 300 s after introduction of the agent to the cells. We model the metabolite kinetics to show decarboxylation activity and derive estimates of the pH over time from the CO 2 and bicarbonate (carbonic acid buffer system) equilibrium to probe changes in the cellular environment during active metabolism. These results highlight the utility of benchtop SABRE-hyperpolarized [1- 13 C]pyruvate as a scalable, specific probe for metabolic phenotyping of living cells using compact, low-cost instrumentation well-suited for future high-throughput applications across microbial engineering, drug response profiling, and dynamic metabolic screening.

fungi↗
DOE OSTI2025

Insights into catalyst degradation during alkaline water electrolysis under variable operation

Energy conversion technologies that are key to decarbonization efforts face significant durability challenges due to variable operation. Understanding the impact of variable operation on catalytic stability and identifying the key variables that dictate degradation is crucial for developing robust technologies. Here, we present a comprehensive investigation of the effects of variable operation on liquid alkaline water electrolysis. Our findings reveal that variable operation induces severe degradation of Ni, Fe, and Co catalytic films that is not observed during steady-state operation. By systematically interrogating the electrode discharge during simulated shutdown tests using Raman spectroscopy and mass spectrometry techniques, we uncover significant alterations caused by reverse currents in real time. These include changes in crystal structure, composition, film thickness, electronic conductivity, and dissolution rates. Lab-scale electrolyzer experiments further highlight the impact of variable operation on catalyst materials under relevant conditions. Finally, we provide guidelines for leveraging these insights to advance electrocatalysis research. This work underscores the importance of integrating realistic stressors into stability testing and offers practical guidelines for catalyst design, performance evaluation, and industrial implementation. Collectively, insights from this study will drive the development of more resilient energy conversion technologies.

Marquez, Raul A. [Univ. of Texas, Austin, TX (Unit↗
DOE OSTI2023

Development of ML FPGA Filter for Particle Identification and Tracking in Real Time

Real-time data processing is a frontier field in experimental particle physics. Machine Learning methods are widely used and have proven to be very powerful in particle physics. The growing computational power of modern FPGA boards allows us to add more sophisticated algorithms for real time data processing. Many tasks could be solved using modern Machine Learning (ML) algorithms which are naturally suited for FPGA architectures. The FPGA-based machine learning algorithm provides an extremely low, sub-microsecond, latency decision and makes information-rich data sets for event selection. We report work has started to evaluate an FPGA based Machine Learning (ML) algorithm for a real-time particle identification and tracking with Transition Radiation Detector (TRD) and e/m calorimeter. The first target is the GlueX experiment, with a plan to build a TRD based on GEM technology. GlueX trigger latency is 3.3 μs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Priority research directions for in situ data management: Enabling scientific discovery from diverse data sources

In January 2019, the US Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions (PRDs) for in situ data management (ISDM). A fundamental finding of this workshop is that the methodologies used to manage data among a variety of tasks in situ can be used to facilitate scientific discovery from many different data sources—simulation, experiment, and sensors, for example—and that being able to do so at numerous computing scales will benefit real-time decision-making, design optimization, and data-driven scientific discovery. This article describes six PRDs identified by the workshop, which highlight the components and capabilities needed for ISDM to be successful for a wide variety of applications—making ISDM capabilities more pervasive, controllable, composable, and transparent, with a focus on greater coordination with the software stack and a diversity of fundamentally new data algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Ripple-Type Voltage Control for Extreme-Event Contingencies: Preprint

Frequent and intense extreme events make grid operation unprecedentedly challenging. Disruptive events could lead to dangerous voltage drops and even voltage collapse if corrective actions are not quickly taken. In this paper, we present a real-time algorithm for voltage control suitable for mitigating electric grid damage scenarios. In our strategy, when agents (generators, substations) experience a dangerous undervoltage, they first respond locally. When the local control resources are depleted, agents seek assistance from peer nodes over a communication network. The algorithm is simulated on a realistic test transmission system. Using fragility curve methodology, we simulate hurricane damages to the components of the synthetic 2000-bus grid representing the ERCOT system. Although being tested over a damaged grid after a hurricane event, our algorithm can be equally successfully applied to any other emergency low-voltage situation.

extreme weather events↗
NASA NTRS1984

Network ST radar and related measurements at Pennsylvania State University

Mesoscale meteorological measurements, analysis and prediction are some of the principal areas of research in the Department of Meteorology at Penn State. In anticipation of a staged turn-on of the three systems during the Summer and Fall of 1984, the nonconstruction-related efforts have focused on the software development necessary to allow essentially immediate use of network data. A 16-bit microcomputer has been programmed to serve as the network controller, communications interface and, at least for real-time purposes, the operational display system. Insofar as possible we have in this task built upon our substantial accumulated experience in working with the processing and display of Doppler sodar system signals. Once the radar-derived wind and turbulence profiles are communicated to the various interconnected Departmental computers they become just one component of a comprehensive data base which can be applied to a diverse set of ongoing basic and operational research programs.

Thomson, D. W.↗
NASA NTRS1992

An expert system/ion trap mass spectrometry approach for life support systems monitoring

Efforts to develop sensor and control system technology to monitor air quality for life support have resulted in the development and preliminary testing of a concept based on expert systems and ion trap mass spectrometry (ITMS). An ITMS instrument provides the capability to identify and quantitate a large number of suspected contaminants at trace levels through the use of a variety of multidimensional experiments. An expert system provides specialized knowledge for control, analysis, and decision making. The system is intended for real-time, on-line, autonomous monitoring of air quality. The key characteristics of the system, performance data and analytical capabilities of the ITMS instrument, the design and operation of the expert system, and results from preliminary testing of the system for trace contaminant monitoring are described.

Palmer, Peter T.↗
NASA NTRS1993

A stepped-frequency Delta-K microwave radar for oceanographic studies

A stepped-frequency Delta-K (SFDK) radar was developed to remotely sense ocean surface characteristics. This C-band radar uses frequency diversity and real-time signal processing for improved Delta-K measurements. In this paper, we show how frequency diversity can be implemented to enhance the energy of the resonant peak of the cross-product spectrum relative to the background energy. This feature is essential for making real-time measurements of resonant peak frequency over extended time periods. The SFDK was used in a month-long field experiment at N. Truro (Massachusetts). The results presented show that the phase velocity of ocean surface waves could be precisely measured 87 percent of the time.

Popstefanija, Ivan↗
NASA NTRS1999

Experimental Analysis of Mast Lifting and Bending Forces on Vibration Patterns Before and After Pinion Reinstallation in an OH-58 Transmission Test Rig

As part of a cooperative research program between NASA Ames Research Center, NASA Glenn Research Center, and the U.S. Army Laboratories, a series of experiments are being performed on the 500 HP OH-58a Transmission Test Rig at NASA Glenn Research Center. The findings reported in this paper were drawn from Phase 1 of a two-phase experiment, and are focused on the vibration response of an undamaged pinion gear and planetary system operating in situ in the transmission test rig. Phase 2 of the experiment, which is reported elsewhere, introduced a seeded fault into the pinion gear and tracked its progress in real-time. Based on methods presented here, further experimental research will be conducted to examine planetary system faults.

Huff, Edward M.↗
NASA NTRS2015

Assimilation of GRACE Terrestrial Water Storage Observations into a Land Surface Model for the Assessment of Regional Flood Potential

We evaluate performance of the Catchment Land Surface Model (CLSM) under flood conditions after the assimilation of observations of the terrestrial water storage anomaly (TWSA) from NASA's Gravity Recovery and Climate Experiment (GRACE). Assimilation offers three key benefits for the viability of GRACE observations to operational applications: (1) near-real time analysis; (2) a downscaling of GRACE's coarse spatial resolution; and (3) state disaggregation of the vertically-integrated TWSA. We select the 2011 flood event in the Missouri river basin as a case study, and find that assimilation generally made the model wetter in the months preceding flood. We compare model outputs with observations from 14 USGS groundwater wells to assess improvements after assimilation. Finally, we examine disaggregated water storage information to improve the mechanistic understanding of event generation. Validation establishes that assimilation improved the model skill substantially, increasing regional groundwater anomaly correlation from 0.58 to 0.86. For the 2011 flood event in the Missouri river basin, results show that groundwater and snow water equivalent were contributors to pre-event flood potential, providing spatially-distributed early warning information.

flood↗
DOE OSTI2026

A Smart Vision-Aided RICH (Robotic Interface Control and Handling) System for VULCAN

High-flux neutron beams and high-efficiency detectors enable rapid neutron diffraction measurements at the Engineering Materials Diffractometer (VULCAN) at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory (ORNL). To optimize beam time utilization, efficient sample exchange, alignment, and automated measurements are essential. Recent advances in artificial intelligence (AI) have expanded the capabilities of robotic systems. Here, we report the development of a Robotic Interactive Control and Handling (RICH) system for sample handling at VULCAN, designed to support high-throughput experiments and reduce overhead time. The RICH system employs a six-axis desktop robot integrated with AI-based computer vision models capable of recognizing and localizing samples in real time from instrument and depth-resolving cameras. Vision algorithms combine these detections to align samples with designated measurement positions or place them within complex sample environments such as furnaces. This integration of machine learning-assisted vision with robotic handling demonstrates the feasibility of autonomous sample detection and preparation, offering a pathway toward fully unmanned neutron scattering experiments.

automation↗
NASA NTRS2013

Recent Development in the CESE Method for the Solution of the Navier-Stokes Equations Using Unstructured Triangular or Tetrahedral Meshes With High Aspect Ratio

In the multidimensional CESE development, triangles and tetrahedra turn out to be the most natural building blocks for 2D and 3D spatial meshes. As such the CESE method is compatible with the simplest unstructured meshes and thus can be easily applied to solve problems with complex geometries. However, because the method uses space-time staggered stencils, solution decoupling may become a real nuisance in applications involving unstructured meshes. In this paper we will describe a simple and general remedy which, according to numerical experiments, has removed any possibility of solution decoupling. Moreover, in a real-world viscous flow simulation near a solid wall, one often encounters a case where a boundary with high curvature or sharp corner is surrounded by triangular/tetrahedral meshes of extremely high aspect ratio (up to 106). For such an extreme case, the spatial projection of a space-time compounded conservation element constructed using the original CESE design may become highly concave and thus its centroid (referred to as a spatial solution point) may lie far outside of the spatial projection. It could even be embedded beyond a solid wall boundary and causes serious numerical difficulties. In this paper we will also present a new procedure for constructing conservation elements and solution elements which effectively overcomes the difficulties associated with the original design. Another difficulty issue which was addressed more recently is the wellknown fact that accuracy of gradient computations involving triangular/tetrahedral grids deteriorates rapidly as the aspect ratio of grid cells increases. The root cause of this difficulty was clearly identified and several remedies to overcome it were found through a rigorous mathematical analysis. However, because of the length of the current paper and the complexity of mathematics involved, this new work will be presented in another paper.

Chang, Sin-Chung↗
DOE OSTI2025

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗
NASA NTRS1975

A landmark recognition and tracking experiment for flight on the Shuttle/Advanced Technology Laboratory (ATL)

The preliminary design of an experiment for landmark recognition and tracking from the Shuttle/Advanced Technology Laboratory is described. It makes use of parallel coherent optical processing to perform correlation tests between landmarks observed passively with a telescope and previously made holographic matched filters. The experimental equipment including the optics, the low power laser, the random access file of matched filters and the electro-optical readout device are described. A real time optically excited liquid crystal device is recommended for performing the input non-coherent optical to coherent optical interface function. A development program leading to a flight experiment in 1981 is outlined.

Welch, J. D.↗
NASA NTRS1991

Identification of linear multivariable systems from a single set of data by identification of observers with assigned real eigenvalues

This paper presents a formulation for identification of linear multivariable systems from a single set of input-output data. The identification method is formulated with the mathematical framework of learning identification, by extension of the repetition domain concept to include shifting time intervals. This contrasts existing learning approaches that require data from multiple experiments. In this method, the system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded real eigenvalue assignment procedure. Through this relationship, the Markov parameters of the observer are identified. The Markov parameters of the actual system are recovered from those of the observer, and then used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples presented to illustrate the proposed method.

Phan, Minh↗
NASA NTRS1993

Knowledge-based reasoning in the Paladin tactical decision generation system

A real-time tactical decision generation system for air combat engagements, Paladin, has been developed. A pilot's job in air combat includes tasks that are largely symbolic. These symbolic tasks are generally performed through the application of experience and training (i.e. knowledge) gathered over years of flying a fighter aircraft. Two such tasks, situation assessment and throttle control, are identified and broken out in Paladin to be handled by specialized knowledge based systems. Knowledge pertaining to these tasks is encoded into rule-bases to provide the foundation for decisions. Paladin uses a custom built inference engine and a partitioned rule-base structure to give these symbolic results in real-time. This paper provides an overview of knowledge-based reasoning systems as a subset of rule-based systems. The knowledge used by Paladin in generating results as well as the system design for real-time execution is discussed.

Chappell, Alan R.↗
NASA NTRS1986

Fault latency in the memory - An experimental study on VAX 11/780

Fault latency is the time between the physical occurrence of a fault and its corruption of data, causing an error. The measure of this time is difficult to obtain because the time of occurrence of a fault and the exact moment of generation of an error are not known. This paper describes an experiment to accurately study the fault latency in the memory subsystem. The experiment employs real memory data from a VAX 11/780 at the University of Illinois. Fault latency distributions are generated for s-a-0 and s-a-1 permanent fault models. Results show that the mean fault latency of a s-a-0 fault is nearly 5 times that of the s-a-1 fault. Large variations in fault latency are found for different regions in memory. An analysis of a variance model to quantify the relative influence of various workload measures on the evaluated latency is also given.

Chillarege, Ram↗
DOE OSTI2024

Advancing Insights into Electrochemical Pre‐Treatments of Supported Nanoparticle Electrocatalysts by Combining a Design of Experiments Strategy with In Situ Characterization

Activation, break-in, and/or pre-treatment protocols are generally applied to energy conversion devices before regular operation to reach stable performance. There remains much to understand about the relationships among physical properties, performance, and electrochemical pre-treatments. Here, a design-of-experiments (DoE) strategy is employed to address this gap by demonstrating the influence of five pre-treatment parameters for carbon-supported Pt-nanoparticle catalysts on the electrocatalytic oxygen reduction reaction (ORR). A subset of pre-treatments, developed using a central composite design, are tested in a flow cell combined with an inductively-coupled plasma mass spectrometer (on-line ICP-MS). The DoE-based approach facilitates comprehensive insights from two orders of magnitude fewer experiments than a conventional grid search. The coupled on-line ICP-MS setup enables effective catalysis and real-time catalyst dissolution data. Leveraging insights from DoE for on-line ICP-MS and additional characterization, a model is built between the degradation of a multi-dimensional supported Pt surface, its performance, and applied electrochemical parameters. These investigations identify surface modifications, such as oxidation, and subsequent restructuring of Pt during pre-treatment as a primary cause of performance deterioration during ORR. By combining DoE with advanced characterization techniques, a powerful approach is demonstrated to gain a mechanistic understanding of pre-treatment protocols that can be broadly adapted to various reaction chemistries.

Platinum↗