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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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DOE OSTI2020

Impedance Analysis and PHIL Demonstration of Reactive Power Oscillations in a Wind Power Plant Using a 4-MW Wind Turbine

This paper presents impedance-based analysis, mitigation, and power-hardware-in-the-loop (PHIL) demonstration of reactive power oscillations in a wind power plant using a 4-MW Type III wind turbine drivetrain. Because such low-frequency oscillations result from interactions among slower control loops of wind turbines regulating phasor quantities—active and reactive power output of the wind turbine and the magnitude of voltages at the point of interconnection (POI)—a new type of admittance is defined in terms of phasor quantities for their analysis. The so-called power-domain admittance of a wind turbine is defined as the transfer function from the frequency and magnitude of voltages at the POI to the active and reactive power output of the turbine. The power-domain admittance responses of the 4-MW wind turbine are measured using a 7-MVA grid simulator to identify the source of the reactive power oscillations. Power-domain impedance analysis and PHIL experiments are performed to explain how a resonant mode manifests as turbine-to-turbine and plant-to-grid reactive power oscillations. It is discovered that weaker grids exhibiting high inductive impedance mitigate oscillations in the reactive power output of wind power plants; however, a higher grid impedance does not help in damping turbine-to-turbine reactive power oscillations. This paper presents a simple droop-based solution to eliminate both turbine-to-turbine and plant-to-grid reactive power oscillations.

17 WIND ENERGY↗

DOE OSTI2026

Heat Pump Retrofits for Central Plant Hydronic Heating Systems: A Software Toolkit for Screening and Design

Retrofitting existing central plants with high-efficiency heat pump technologies can play a crucial role in achieving long-term planning goals. Modern heat pump technologies are able to use waste heat recovery to meet a building's heating demand, but there is a lack of accessible tools designed for non-HVAC experts, such as building owners, to quickly and easily conduct what-if analysis, e.g., estimating retrofit costs and payback period for their partial or full equipment replacement. This paper introduces an open-source software toolkit designed to facilitate the initial screening and decision-making of heat pump retrofits in existing central plants using a building's yearly load profile from metered or utility bill data. The toolkit evaluates the technical and economic viability of replacing traditional central plant equipment with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users to compare current central plant configurations with retrofit scenarios, assessing energy consumption, life-cycle costs, and environmental impact. The toolkit offers (1) a web-based tool designed for user-friendly access by a broad audience and (2) Python-based source code for researchers and engineers conducting parametric studies and design parameter optimization. The toolkit compares a typical central plant configuration to a configuration that uses a heat pump to supply hydronic heating and cooling. The output metrics include energy consumption and output of each equipment, life-cycle cost analyses and metrics, and environmental impact of the system.

Excell, L↗

DOE OSTI2026

Coalition for Community-Supported Affordable Geothermal Energy Systems (C2SAGES)

The C2SAGES project evaluated the feasibility of a community geothermal system for the planned Windy Ridge affordable housing development in Hinesburg, Vermont. Led by GTI Energy with Vermont Gas Systems, LN Consulting, NREL, and Frontier Energy, the work assessed technical design, energy performance, costs, business models, community engagement, maintenance, workforce development, and permitting. The proposed system was designed to serve 100% of the development’s heating, cooling, and domestic hot water loads. Compared with a baseline using air-source heat pumps and natural gas water heating, the geothermal system was estimated to reduce HVAC and domestic hot water energy use by about 45% to 48%, lower operating and maintenance costs, and reduce 30-year life-cycle costs by 37% for Phase 1 and 10% for Phase 2. Technical testing and modeling indicated that the Windy Ridge site is suitable for a community-scale geothermal system. The project also developed borehole field layouts, piping concepts, pump house designs, controls, maintenance plans, and supporting engineering drawings. The business model analysis found that first cost, ownership structure, and customer affordability remain major deployment challenges. Utility-led maintenance and operation were viewed favorably, but traditional utility cost-recovery models may require subsidy or revised financing structures to be practical for affordable housing. Community engagement highlighted the need for clear public education, transparent financing, reliable long-term maintenance, trained technicians, and the potential to pair geothermal systems with weatherization. Overall, the report concludes that community geothermal is technically feasible and offers meaningful energy, emissions, and life-cycle cost benefits, but broader deployment will depend on workable financing models and workforce readiness.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Decarbonization of the Chemical Industry Through Electrification: Barriers and Opportunities

The chemical industry is a major source of economic productivity and employment globally and among the top 3 industrial sources of greenhouse gas (GHG) emissions, along with steel and cement. As global demand for chemical products continues to grow, there is an urgency to develop and deploy sustainable chemical production pathways and to reconsider continued investment in current emission-intensive production technologies. This perspective describes the challenges and opportunities to decarbonize the chemical industry via electrification powered by low-carbon electricity supply, both in the near term and long term, and it discusses four technological pathways ranging from the more mature direct substitution of heat with electricity and use of hydrogen to technologically less mature, yet potentially more selective, approaches based on electrochemistry and plasma. Finally, we highlight the key elements of integrating an electrified industrial process with the power sector to leverage process flexibility to reduce energy costs of chemical production and provide valuable power grid support services. Unlocking such plant-to-grid coordination and the four electrification pathways has significant potential to facilitate rapid and deep decarbonization of the chemical industry sector.

chemical synthesis↗

DOE OSTI2024

Geometric and thermodynamic characterization of binary neutron star accretion discs

Accretion disks formed in binary neutron star mergers play a central role in many astrophysical processes of interest, including the launching of relativistic jets or the ejection of neutron-rich matter hosting heavy element nucleosynthesis. In this work we analyze in detail the properties of accretion disks from 44 ab initio binary neutron star merger simulations for a large set of nuclear equations of state, binary mass ratios, and remnant fates, with the aim of furnishing reliable initial conditions for disk simulations and a comprehensive characterization of their properties. We find that the disks have a significant thermal support, with an aspect ratio decreasing with the mass ratio of the binary from ~0.7 to 0.3. Even if the disk sample spans a broad range in mass and angular momentum, their ratio is independent from the equation of state and from the mass ratio. This can be traced back to the rotational profile of the disk, characterized by a constant specific angular momentum (as opposed to a Keplerian one) of 3 – 5×10 16 cm 2 s –1 . The profiles of the entropy per baryon and of the electron fraction depend on the mass ratio of the binary. For more symmetric binaries, they follow a sigmoidal distribution as a function of the rest mass density, for which we provide a detailed description and a fit. Furthermore, the disk properties discussed in this work can be used as a robust set of initial conditions for future long-term simulations of accretion disks from binary neutron star mergers, posing the basis for progress in the quantitative study of the outflow properties.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

On Hydrodynamics Generated from Electrostatic Discharges: A Heat Source Perspective

A parameter space map of a heat source depositing energy into a cylindrical spark channel modeling the hydrodynamic effects of an electrostatic discharge event is explored. The four parameters of spatial weight, λ R , rise time, τ r , fall time, τ f , and energy per unit length deposited in to the system, E 0 /h, were varied to observe resulting hydrodynamic phenomena. The energy budget con-sequences of the associated hydrodynamic flow are discussed in terms of the remaining electrical energy available for the joule heating of sensitive energetic materials (or “victims”) are discussed,where hydrodynamic simulations are validated by experimental data. Future results and conclusions will be added to this report as they are produced.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Improving an Acoustic Vehicle Detector Using an Iterative Self-Supervision Procedure

In many non-canonical data science scenarios, obtaining, detecting, attributing, and annotating enough high-quality training data is the primary barrier to developing highly effective models. Moreover, in many problems that are not sufficiently defined or constrained, manually developing a training dataset can often overlook interesting phenomena that should be included. To this end, we have developed and demonstrated an iterative self-supervised learning procedure, whereby models are successfully trained and applied to new data to extract new training examples that are added to the corpus of training data. Successive generations of classifiers are then trained on this augmented corpus. Using low-frequency acoustic data collected by a network of infrasound sensors deployed around the High Flux Isotope Reactor and Radiochemical Engineering Development Center at Oak Ridge National Laboratory, we test the viability of our proposed approach to develop a powerful classifier with the goal of identifying vehicles from continuously streamed data and differentiating these from other sources of noise such as tools, people, airplanes, and wind. Using a small collection of exhaustively manually labeled data, we test several implementation details of the procedure and demonstrate its success regardless of the fidelity of the initial model used to seed the iterative procedure. Finally, we demonstrate the method’s ability to update a model to accommodate changes in the data-generating distribution encountered during long-term persistent data collection.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Physics‐based iterative reconstruction for dual‐source and flying focal spot computed tomography

Purpose For single‐source helical Computed Tomography (CT), both Filtered‐Back Projection (FBP) and statistical iterative reconstruction have been investigated. However, for dual‐source CT with flying focal spot (DS‐FFS CT), a statistical iterative reconstruction that accurately models the scanner geometry and acquisition physics remains unknown to researchers. Therefore, our purpose is to present a novel physics‐based iterative reconstruction method for DS‐FFS CT and assess its image quality. Methods Our algorithm uses precise physics models to reconstruct from the native cone‐beam geometry and interleaved dual‐source helical trajectory of a DS‐FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture. In addition, we design forward system models to compute the locations of deflected focal spots, the dimension, and sensitivity of voxels and detector units, as well as the length of intersection between x‐rays and voxels. The forward system models further represent the coordinated movement between the dual sources by computing their x‐ray coverage gaps and overlaps at an arbitrary helical pitch. With the above models, we reconstruct images by an advanced Consensus Equilibrium (CE) numerical method to compute the maximum a posteriori estimate to a joint optimization problem that simultaneously fits all models. Results We compared our reconstruction with Siemens ADMIRE, which is the clinical standard hybrid iterative reconstruction (IR) method for DS‐FFS CT, in terms of spatial resolution, noise profile, and image artifacts through both phantoms and clinical scan datasets. Experiments show that our reconstruction has a higher spatial resolution, with a Task‐Based Modulation Transfer Function (MTF task ) consistently higher than the clinical standard hybrid IR. In addition, our reconstruction shows a reduced magnitude of image undersampling artifacts than the clinical standard. Conclusions By modeling a precise geometry and avoiding data rebinning or interpolation, our physics‐based reconstruction achieves a higher spatial resolution and fewer image artifacts with smaller magnitude than the clinical standard hybrid IR.

Wang, Xiao↗

DOE OSTI2026

New perspectives on materials and device dynamics using time-resolved full-field diffraction X-ray imaging

Understanding how materials evolve during synthesis, processing, or device operation requires experimental access to structural dynamics across wide ranges of length and time scales, often in bulk samples or even within packaged devices. Time-resolved full-field diffraction X-ray microscopy has recently emerged as a powerful way to meet this need by combining the penetration and structural sensitivity of X-ray diffraction with objective-lens-based magnification, sensitive high-resolution X-ray imaging detectors, and pump-probe and real-time imaging strategies. Advances in full-field X-ray diffraction microscopy, often termed dark-field X-ray microscopy (DFXM), enable simultaneous imaging of extended fields of view while retaining crystallographic selectivity. Time-resolved DFXM promises to enable advances in materials processing and dynamics, electrochemical and photochemical processes, and the design of electronic devices. This Perspective summarizes the key instrumental concepts that define the performance of these methods, including the choice of imaging optics, detector considerations, and the impact of source time structure at synchrotron light sources and X-ray free-electron lasers (XFELs). We discuss the simultaneous use of complementary imaging modes that are increasingly used in practice. The early demonstrations of the potential of time-resolved DFXM include real-time defect and grain-boundary dynamics during metal annealing, stroboscopic imaging of functional devices with high strain sensitivity, and ultrafast pump-probe implementations at XFELs that directly visualize acoustic-wave propagation and energy dissipation in bulk crystals.

Dark-field X-ray microscopy↗

DOE OSTI2021

A generalized machine learning workflow to visualize mechanical discontinuity

Accurate detection and mapping of mechanical discontinuity in materials has widespread industrial and research applications. Herein, we developed a generalized machine-learning framework for visualizing single mechanical discontinuity embedded in material of any composition, velocity, density, porosity, and size with limited data. The proposed visualization of discontinuity requires accurate estimations of the length, location, and orientation of the embedded discontinuity by processing multipoint wave-transmission measurements. k-Wave simulator is used to create a large dataset of elastic waveforms recorded during multi-point wave-transmission measurements through materials containing single mechanical discontinuity. k-Wave simulator considers the wave attenuation, dispersion, and mode conversion in wave motion. Discrete wavelet transform (DWT) and statistical feature extraction are essential for data preprocessing prior to the data-driven model development. DWT also minimizes the effect of noise. Using hyper-parameter tuning and cross validation, gradient boosting regression can visualize the mechanical discontinuity with an accuracy of 0.85, in terms of coefficient of determination. A double-layered neural network-based regression has better performance with an accuracy of 0.95. Use of convolutional neural network converts the predictive task from a waveform processing to an image processing problem. Convolutional neural network achieved a generalization performance of 0.91. The proposed generalized workflow requires robust simulation of wave propagation, signal processing, feature engineering, and model evaluation. Sensors closest to the source and those located opposite the source are the most significant for the desired visualization. Notably, the sensors closest to the source capture the non-linear associations, whereas the sensor on the border opposite to the source capture the linear associations between the measured waveforms and the properties of the mechanical discontinuity.

42 ENGINEERING↗

DOE OSTI2021

On the merit of hot ion mode for tearing mode stabilization

The stabilization of tearing modes with rf driven current benefits from the cooperative feedback loop between rf power deposition and electron temperature within the island. This effect, termed rf current condensation, can greatly enhance and localize the current driven within magnetic islands. It has previously been shown that the condensation effect opens the possibility of passive stabilization with broad rf profiles, as would be typical of LHCD for steady state operation. Here, we show that this self-healing effect can be dramatically amplified by operation in a hot ion mode, due to the additional electron heat source provided by the hotter ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

The impact of helium on plasma-driven hydrogen permeation and implications for direct internal recycling in the fusion fuel cycle

Abstract Metal foil pumps (MFPs) are the leading technology for direct internal recycling (DIR) of hydrogen isotopes from the plasma exhaust in future fusion plants. MFPs rely on the concept of superpermeation, where superthermal H atoms directly absorb into the metal foil, rapidly diffuse, and desorb downstream. To date, studies of superpermeation have predominantly employed either pure hydrogen or in some cases trace levels of impurities. The plasma exhaust is expected to contain just ∼1% helium, but in DIR the source gas would be enriched in helium as hydrogen isotopes are extracted. In this work, we explore the impact of helium on hydrogen superpermeation at low temperature (75 °C–200 °C) using Pd-based foils. To first order, the flux scaled linearly with the hydrogen mole fraction. Stable permeation was observed until the helium fraction reached ∼80%, where the flux began to decline slowly with time. In addition, short term (1–5 min) exposure to pure helium plasma significantly attenuated subsequent hydrogen plasma permeation, and the degree was more dramatic at elevated temperature. This attenuation was correlated with He retention in the foils, which was detected by time-of-flight secondary ion mass spectrometry at low levels (<0.1 at. %) and limited to the near surface (<10 nm). Similar trends were observed among all alloys (Pd, PdAg, PdCu), and the foils were restored to full performance with an Ar + sputter clean. The potential for helium plasma exposure to impact MFP performance under these conditions has not been previously reported, and these findings have significant implications to the design and implementation of practical DIR systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Repometer v.1.0

SAND2022-4256 O Online version control platforms offer insight into traffic and engagement with source code repositories, but only in limited ways and over short windows of time. Scientific software teams at Sandia National Laboratories and elsewhere want to collect and store engagement data to help tell their story and the impact their work has on the community. Repometer aims to supplement existing capabilities by collecting timely and insightful data from GitHub and GitLab repositories and passing it to a database for longer-term storage. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Mundt, Miranda↗

DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, G. C.↗

DOE OSTI2022

Atomic Force Microscope Active Optical Probe for Single-Molecule Imaging and Time-Resolved Optical Spectroscopy (DOE SBIR Phase II/IIA Final Report)

Actoprobe LLC reports on the results of its DOE SBIR Phase II/IIA project on the development of Atomic Force Microscope Active Optical Probe for Single-Molecule Imaging and Time-Resolved Optical Spectroscopy. While chemistry science and technology greatly benefit from Atomic Force Microscopy in surface characterization, time-resolved chemical imaging on the single-molecule level lags far behind. Current scanning probe microscopy only obtains information about mechanical but not optical/chemical properties. To address this problem, the Actoprobe LLC research team has proposed a novel class of Atomic Force Microscopy probes, Ultra-Fast Pulsed Active Atomic Force Microscopy Optical Probes (UFP AAOPs), that will allow ultrafast time-resolved optical and chemical imaging at the nanoscale. As envisioned, these unique optical probes will perform the functions of conventional Atomic Force Microscopy probes and, in addition, will simultaneously provide chemical information about molecular scale interactions. This innovation is accomplished by integrating an ultrafast pulsed Quantum Dot laser source into an Atomic Force Microscopy probe. This report describes our progress with the fabrication of an ultrafast micrometer-size semiconductor laser, based on “artificial atoms” - Quantum Dots, integrated with an Atomic Force Microscopy probe. In this Phase II/IIA project, we have demonstrated the feasibility of the UFP AAOP concept by fabricating a first prototype of the UFP AAOP. The excellent performance of the probe has been proven in terms of AFM and optical spatial resolution through rigorous tests. The UFP AAOP provides pulses with less than 4 ps duration and higher than 11 GHz repetition rate, and spatial resolution better than 300 nm at 1240 nm wavelength. Technically, it is possible to reduce the pulse width to less than 1 ps and to improve lateral resolution to ~ 0.5 nm, which implies the potential capability for the probe to characterize chemical compounds with single-molecule resolution. The UFP AAOP fabrication procedure has been developed for wafer-scale production of multiple devices, with the yield of the process estimated to be lower than 1% with the limited fabrication capabilities and equipment available for use in the research project. However, using high-volume production tools and special GaAs processing equipment, the yield can be significantly improved, theoretically to ~ 50%. Finally, economic feasibility and scale-up manufacturing potential were analyzed for UFP AAOP and found to be very promising. In summary, the Actoprobe team has successfully demonstrated the feasibility of the UFP AAOP concept.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Research Reactors Division Infrastructure Investment Plan for the High Flux Isotope Reactor

The High Flux Isotope Reactor (HFIR) is a unique national asset. Operational for nearly 60 years, continued investment into the aging infrastructure is necessary to ensure operation for another 6 decades. Additionally, growing missions require HFIR as well as important upgrades. Consequently, carefully integrated planning is required to ensure that infrastructure investments are timely executed to ensure long-term, reliable operation of HFIR. Concerns about challenges to the operational reliability of HFIR resulted in a recommendation from the 2023 Operations Review by the US Department of Energy (DOE) Office of Basic Energy Sciences that a HFIR management strategy be developed to address the infrastructure needs. This report defines the investment needs, which are evolving as new upgrade efforts are better defined. HFIR is part of the three-source strategy within the Neutron Sciences Directorate (NScD) and contributes to the five strategic science areas outlined in the NScD 10 Year Strategic Science Plan: quantum materials, soft matter, materials and engineering, chemistry, and biosciences. Fundamental to this strategy are three core values: operational excellence, responsible stewardship, and servant leadership. These values guide our mission of safe and reliable operation of the reactor and require a strong and just nuclear safety culture, a solemn respect for responsible care of the facility, good workforce development, robust procedures and processes, an effective communication strategy, world-class asset management, a determined customer focus, and a commitment to protecting the environment, the safety and health of the public and our people, and the quality of work performed within our facility. These principles are all essential to operate HFIR at a world-class level. The Research Reactors Division (RRD) will lead a new era of neutron science and isotope production at HFIR through responsible and purposeful leadership and unwavering support of the science community. The approach outlined in this plan highlights the direction leadership is taking to ensure that HFIR is ready to support the science challenges and national needs of the future and that the United States maintains world leadership in neutron sciences. The plan is in alignment with the DOE’s desire to continue operating HFIR and with the NScD strategic science goals for the future. HFIR is an aging facility with numerous infrastructure challenges and needs. It has an aging workforce in relation to the general population of Oak Ridge National Laboratory (ORNL), with many expected retirements over the next 5–10 years. With an increase in work scope caused by changing national priorities and science goals, several critical hires have been identified. To manage HFIR’s infrastructure needs, a prioritized list of equipment upgrades has been identified along with an analysis of future staffing requirements. A desire to operate HFIR at eight cycles per year will necessarily require some significant changes to procedures and processes currently in place as well as targeted staffing additions. Many of the equipment upgrades identified in this plan will significantly increase the reliability of the plant, thus contributing to the effort to reach the goal of safely operating eight cycles per year. A plan to attain eight-cycle operation is being prepared in parallel with the activities identified in this plan, although the actions identified to satisfy both plans will overlap. This plan identifies new infrastructure needs—for both plant equipment and staffing—thus necessitating formulation of future budget requests to fund the increased work scope and improvement activities. Some activities are currently being scheduled with the expectation that funding will be received. Any delays to funding or reductions of funding from the identified cost estimations will directly and negatively affect the plan’s implementation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Pappas, Chris↗