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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
DOE OSTI2025

A Dark Photon Dark Matter Search with a Widely-Tunable SRF Cavity

The SERAPH (SupERconducting Axion and Paraphoton Haloscope) experiment is a family of superconducting haloscopes being developed by the Superconducting Quantum Materials and Systems (SQMS) Center to search for wavelike dark matter. This presentation will focus on preliminary results from our dark photon dark matter search using a widely-tunable SRF cavity operating between 4-7 GHz, nicknamed the “plunger cavity.” I will present the cavity design and characterization, analyze the impact of microphonics on system performance and haloscope sensitivity, and describe our tuning methodology for this Q~10^8 cavity. The presentation will cover our haloscope analysis approach and discuss sensitivity limits achieved within this frequency range. Finally, I will outline lessons learned from this first search, implications for future axion searches, and proposed improvements for subsequent SERAPH experiments.

Cervantes, Raphael [Fermilab]↗
DOE OSTI2025

A Dark Photon Dark Matter Search with a Widely-Tunable SRF Cavity

The SERAPH (SupERconducting Axion and Paraphoton Haloscope) experiment is a family of superconducting haloscopes being developed by the Superconducting Quantum Materials and Systems (SQMS) Center to search for wavelike dark matter. This presentation will focus on preliminary results from our dark photon dark matter search using a widely-tunable SRF cavity operating between 4-7 GHz, nicknamed the "plunger cavity." I will present the cavity design and characterization, analyze the impact of microphonics on system performance and haloscope sensitivity, and describe our tuning methodology for this Q~10^8 cavity. The presentation will cover our haloscope analysis approach and discuss sensitivity limits achieved in this frequency range. Finally, I will outline lessons learned from this first search, implications for future axion searches, and proposed improvements for subsequent SERAPH experiments.

Cervantes, Raphael [Fermilab]↗
DOE OSTI2026

Design Considerations for Phase Change Material-Incorporated Heat Exchangers in Water Heating

In recent years, the buildings sector has seen major pushes towards decarbonization through innovations that promote deep electrification. 20% of an average household's energy use comes from water heating, and in the US, over half of all households still use gas water heaters. Of those that use electricity for water heating, the majority use resistive elements rather than heat pump water heaters (HPWHs), the latter of which use 60-70% less energy than the former. However, HPWHs tend to have larger dimensions, preventing current 50-80-gallon tanks on the market from fitting into smaller utility closets sized for 30-40 gallons, such as those found in manufactured housing. Additionally, these smaller HPWHs tend to underperform relative to their larger counterparts. One solution that addresses both space and performance concerns is thermal energy storage, and in particular, phase change materials (PCMs). This study outlines the design process used to produce novel PCM heat exchangers for use in small-volume HPWH tanks, including the identification of design constraints and performance targets relevant to real-world applications. To ensure optimal PCM utilization and tank storage capacity, this works seeks to co-maximize surface area and PCM volume; therefore, this research targets triply periodic minimal surface (TPMS) lattices, which boast enhanced heat transfer capabilities compared to traditional heat exchanger geometries. Starting with a suite of TPMS lattices, we demonstrate a systematic approach for narrowing down feasible designs that comply with identified constraints while meeting PCM performance objectives. Our current results indicate that tuning lattice properties can effectively produce geometries that provide enough energy storage to achieve a 50-gallon capacity out of a 40-gallon HPWH, even when placing the PCM heat exchanger inside the tank. Additionally, we demonstrate successful fabrication of lattices with these tuned properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Zero and Finite Temperature Quantum Simulations Powered by Quantum Magic

We introduce a quantum information theory-inspired method to improve the characterization of many-body Hamiltonians on near-term quantum devices. We design a new class of similarity transformations that, when applied as a preprocessing step, can substantially simplify a Hamiltonian for subsequent analysis on quantum hardware. By design, these transformations can be identified and applied efficiently using purely classical resources. In practice, these transformations allow us to shorten requisite physical circuit-depths, overcoming constraints imposed by imperfect near-term hardware. Importantly, the quality of our transformations is t u n a b l e : we define a 'ladder' of transformations that yields increasingly simple Hamiltonians at the cost of more classical computation. Using quantum chemistry as a benchmark application, we demonstrate that our protocol leads to significant performance improvements for zero and finite temperature free energy calculations on both digital and analog quantum hardware. Specifically, our energy estimates not only outperform traditional Hartree-Fock solutions, but this performance gap also consistently widens as we tune up the quality of our transformations. In short, our quantum information-based approach opens promising new pathways to realizing useful and feasible quantum chemistry algorithms on near-term hardware.

Physics↗
DOE OSTI2026

AMVOS: Additive Manufacturing Video Object Segmentation Dataset

This dataset provides labeled video frames from four additive manufacturing (AM) processes for video object segmentation (VOS) tasks. It contains 90 video segments comprising 900 individually annotated frames across five AM datasets: laser hot-wire directed energy deposition (LHW-DED), tungsten inert gas wire arc additive manufacturing (TIG-WAAM), plasma arc welding (PAW), visible-light polymer extrusion (visPolymer), and near-infrared polymer extrusion (irPolymer). Each video segment consists of 10 contiguous frames with corresponding pixel-level object instance annotations. Depending on the process, two of four object classes are labeled per frame: Melt Pool, Feed Wire, Nozzle, or Material. Raw frames are provided as .jpg files and annotations as palettized .png files. The dataset follows the directory structure of established VOS benchmarks (DAVIS, YouTube-VOS, MOSE), enabling direct integration into VOS model training and evaluation pipelines for foundation model fine-tuning, domain adaptation, or zero-shot performance benchmarking. Data was collected at Oak Ridge National Laboratory's Manufacturing Demonstration Facility.

Wetzel, Jon [ORNL]↗
NASA NTRS1979

Exhaust emission reduction for intermittent combustion aircraft engines

Three concepts for optimizing the performance, increasing the fuel economy, and reducing exhaust emission of the piston aircraft engine were investigated. High energy-multiple spark discharge and spark plug tip penetration, ultrasonic fuel vaporization, and variable valve timing were evaluated individually. Ultrasonic fuel vaporization did not demonstrate sufficient improvement in distribution to offset the performance loss caused by the additional manifold restriction. High energy ignition and revised spark plug tip location provided no change in performance or emissions. Variable valve timing provided some performance benefit; however, even greater performance improvement was obtained through induction system tuning which could be accomplished with far less complexity.

Moffett, R. N.↗
NASA NTRS1989

Appendix: Results obtained to date

Optimization procedures are described for the rotor blade design process by integrating appropriate disciplines and accounting for important interactions among the disciplines. Progress is reported in the areas of aerodynamic performance optimization, dynamic optimization, optimum placement of tuning masses for vibration reduction, and structural optimization. Selected results from these activities are highlighted in this appendix.

Walsh, Joanne L.↗
NASA NTRS1989

Optical alignment and testing of the Diffuse IR Background Experiment IR cryogenic telescope

Diffuse Infrared Background Experiment (DIRBE) optical alignment and testing methods are discussed. Using strobe videography, vibration and performance testing of a 32 hz tuning-fork chopper was carried out. The Cosmic Background explorer satellite provides improved microwave and IR all-sky maps of the cosmic background radiation from a polar orbit. A liquid helium cryostat houses the DIRBE and the Far IR Absolute Spectrophotometer (FIRAS) instruments at a temperature of 2 K. Differential MicRowave Radiometers (DMRs) provide large scale maps of anisotropy of the 3 K background at wavelengths of 3.3, 5.7, and 9.6 mm. The DIRBE telescope is an IR photometric instrument with 10 wavelength bands between 1 and 300 microns, designed to measure radiation from the epoch of galaxy formation. Stringent stray light requirements mean that the DIRBE flight instrument has to be built and tested in a class 100 environment.

Wood, H. John↗
NASA NTRS1997

Strategy for Developing Expert-System-Based Internet Protocols (TCP/IP)

The Satellite Networks and Architectures Branch of NASA's Lewis Research is addressing the issue of seamless interoperability of satellite networks with terrestrial networks. One of the major issues is improving reliable transmission protocols such as TCP over long latency and error-prone links. Many tuning parameters are available to enhance the performance of TCP including segment size, timers and window sizes. There are also numerous congestion avoidance algorithms such as slow start, selective retransmission and selective acknowledgment that are utilized to improve performance. This paper provides a strategy to characterize the performance of TCP relative to various parameter settings in a variety of network environments (i.e. LAN, WAN, wireless, satellite, and IP over ATM). This information can then be utilized to develop expert-system-based Internet protocols.

Ivancic, William D.↗
NASA NTRS1998

Workload Characterization of CFD Applications Using Partial Differential Equation Solvers

Workload characterization is used for modeling and evaluating of computing systems at different levels of detail. We present workload characterization for a class of Computational Fluid Dynamics (CFD) applications that solve Partial Differential Equations (PDEs). This workload characterization focuses on three high performance computing platforms: SGI Origin2000, EBM SP-2, a cluster of Intel Pentium Pro bases PCs. We execute extensive measurement-based experiments on these platforms to gather statistics of system resource usage, which results in workload characterization. Our workload characterization approach yields a coarse-grain resource utilization behavior that is being applied for performance modeling and evaluation of distributed high performance metacomputing systems. In addition, this study enhances our understanding of interactions between PDE solver workloads and high performance computing platforms and is useful for tuning these applications.

Waheed, Abdul↗
NASA NTRS2014

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

VanZwieten, Tannen↗
NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden C. Szeto↗
NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden Szeto↗
DOE OSTI2020

Beam-beam effects in the Super Proton-Proton Collider

The Supper Proton-Proton Collider is a next-generation hadron collider that is now being designed. A baseline design aims for a peak luminosity of about 1*10^35 cm^-2 s^-1. The focus of this article is the effect of beam-beam interactions which are expected to strongly influence stability in the beams. We start with a discussion of a scheme to generate the crossing angles at the interaction points while also correcting the dispersion thus created. The optics constraints on the achievable \b{eta}* were studied. Weak-strong simulations were performed to study single particle dynamics via tune footprints, frequency map analysis and dynamic aperture calculations. The long-range interactions with the smallest separations are shown to determine the dynamic aperture. Empirical scaling laws for the dependence of the dynamic aperture on the transverse separations and on the number of long-range interactions are found. A tune scan shows several alternative working points with slightly better dynamic aperture than the baseline choice. Finally an option to significantly increase the dynamic aperture by increasing the crossing angle for different choices of \b{eta}* was studied.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Power system model parameter conditioning tool

A power system model parameter conditioning tool including a server control processor in communication with phasor measurement unit monitored data records of multiple disturbance events, a model calibration unit providing event screening, power system model simulation, and simultaneous tuning of model parameters. The model calibration performing a simulation using default model parameters, the processor comparing the simulation results to the monitored data. If the prediction is within threshold, then terminating conditioning; else performing parameter identifiability analysis to determine differing effects of various model parameters on power system model accuracy, selecting a parameter set causing a degradation in power system model prediction, and updating the default model parameters corresponding to members of the parameter set with values selected to reduce the degradation. A method and a non-transitory computer readable medium are also disclosed.

Baone, Chaitanya Ashok↗
DOE OSTI2025

Use of AI for Interpreting Technical Specifications for Power Uprates in Nuclear Power Plants

Powerpoint presentation. Background information provided on power plant uprates. Discussion of the current and proposed approaches to power plant uprates. Explanation of what data is used to draft a LAR. Methods such as retrieval augmented generation (RAG) and fine-tuning are discussed. Use case analysis is performed. Different failure types are examined. Conclusions are drawn from the analysis. Future work is proposed.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Ternary and Quaternary Nickel-Iron-Oxide-Based Thin Films as Oxygen Evolution Reaction Catalysts in Alkaline Media

Alkaline water electrolyzers are a promising technology for energy storage and conversion through the electrochemical production of hydrogen, however the slow kinetics of the oxygen evolution reaction (OER) pose a major challenge. The alkaline environment enables the use of non-Pt-group metals as OER catalysts, in particular NiFe-based materials. In this study, Mn and/or Cr were elementally mixed with NiFe to further improve the OER catalyst properties through a controlled, systematic synthesis process involving thin films prepared by electron beam-induced physical vapor deposition (PVD). By exploring both simultaneous co-deposition and serial deposition of the different metals, the OER performance was investigated as a function of both the location of Mn or Cr in the multi-metal NiFe-based catalysts and the difference between surface versus bulk mixing. The distinct differences in the redox dynamics, surface oxidation, and stability of the seven studied catalysts reveal metal Cr- and/or Mn-overlayers as a promising synthesis approach for fine-tuning of catalyst properties and improving the OER performance.

Alkaline Water Electrolysis↗
DOE OSTI2022

Design of a Combined Proportional Integral Derivative Controller to Regulate the Temperature Inside a High-Temperature Tubular Solar Reactor

Solar fuels are proven to be promising candidates for thermochemical energy storage. However, the transient nature of solar radiation is an obstacle to maintaining a stable operational temperature inside a solar reactor. To overcome this challenge, the temperature of a solar reactor can be regulated by controlling the incoming solar radiation or the feedstock flowrate inside the reactor. In this work, a combined proportional integral derivative (PID) controller is implemented to regulate the temperature inside a high-temperature tubular solar reactor with counter-current flowing gas/particles. The control model incorporates two control systems to regulate incoming solar radiation and gas flow simultaneously. The design of the controller is based on a reduced-order numerical model of a high-temperature tubular solar reactor that is vertically oriented with an upward gas flow and downward particle flow. The reactor receives heat circumferentially through its wall over a finite segment of its length. Formulation of the heat transfer model is presented by applying the energy balance for the reactor tube and considering heat and mass transfer inside. A set of governing differential equations are solved numerically by using the finite volume method to obtain reactor wall, particles, and gas temperatures along the reactor length with various boundary conditions. Simulation results are used to tune the PID controller parameters by utilizing the Ziegler–Nichols tuning method. Both the simulation results and the controller performance are visualized on the LABVIEW platform. The controller is challenged to track different temperature setpoints with different scenarios of transient solar radiation. Here, the performance of the PID controller was compared to experimental results obtained from an industrial PID controller embedded in a 7 kW electric furnace. Results show that the combined PID controller is successful in maintaining a stable temperature inside the reactor by regulating the incoming solar radiation and the flowrate via small steady-state error and reasonable settling time and overshoot.

14 SOLAR ENERGY↗