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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Software-Defined Data Center Network Architecture using VXLAN-based BGP EVPN for Dynamic Workflows in a Supercomputing Environment (VXLAN-based BGP EVPN Fabric for HPC) v1

This software repository automates the deployment of a multi-vendor VXLAN-based BGP EVPN architecture, leveraging Containerlab to instantiate a stretched CLOS topology. It integrates Linux, Nokia SR Linux, and Arista cEOS, using BGP for underlay, overlay, and topology extension. The software enables rapid prototyping and testing of advanced network configurations. Its key advantage lies in providing a dynamic, programmable environment for research and development of critical technologies supporting dynamic workflows within supercomputing environments, surpassing the limitations of static, vendor-locked alternatives by fostering interoperability and agility.

Kumar, Ronal [Lawrence Berkeley National Laborator↗
DOE OSTI2025

PySolate : A Python‐Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform

PySolate is a Python‐based toolset that implements the continuous wavelet transform and nonlinear thresholding operations to denoise or designal seismic data, following Langston and Mousavi (2019). This filtering approach can remove microseismic noise to isolate intermediate‐period seismic signals that are key to enabling full‐waveform modeling and analysis of smaller‐magnitude regional events. This approach is best for the application to signals with frequency or time separation of signal and noise, in contrast to Fourier analysis, which is effective when signal and noise are separated in frequency. We demonstrate the Python toolset using the six announced Democratic People’s Republic of Korea declared nuclear tests, showing the effectiveness of isolating the seismic signal compared to standard bandpass filtering. In conclusion, we also demonstrate the ease of using the toolset with any Python processing tools.

Asia↗
DOE OSTI2024

Evaluation of DED and LPBF Fe-based Alloys Process Application Envelopes based on Performance, Process Economics, Supply Chain Risks, and Reactor-specific Targeted Components

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE), Advanced Materials and Manufacturing Technologies (AMMT) program aims to develop extreme-environment materials solutions for use in the deployment of advanced nuclear reactors and the sustainment of the current fleet. To achieve this objective, a combination of experiment, a computational tool, and machine learning (ML) for the design of materials is adopted for the maturation of materials for nuclear technology. Through advanced manufacturing techniques such as laser powder bed fusion (LPBF) and laser powder direct energy deposition (LP-DED), components with complex geometries can be fabricated with reduced time and effort. Such advanced manufacturing methods can also provide the opportunity to improve materials performance through optimized microstructures and mechanical properties. However, existing engineering alloys are not always well suited for fabrication with additive manufacturing (AM), as their compositions have been tuned to optimize fabrication via conventional methods. Thus, similar alloys with modified compositions that are better suited for AM can be studied for improved performance. Over the past three years, the AMMT teams from Argonne National Laboratory (ANL) and Pacific Northwest National Laboratory (PNNL) studied various known Fe-based alloys by evaluating their initial printability using LPBF, and an AMMT-developed down-selection and decision matrix reduced the number of alloys to be studied from six to three in fiscal year (FY) 2024. Additionally, in FY 2024, for parallel evaluation, these three alloys were studied using LPDED. While LPBF is better for small- to medium-sized components with high detail and internal features, LP-DED combines a material feed system to place the powder onto the exact spot where the laser will melt the material. This AM method can be easily scaled to extremely large components and provides high build rate speeds compared to those of conventional LPBF systems. Additionally, DED is a better choice for complex geometries and compositional gradients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Critical Component/Technology Gap in 21 st Century Power Plant Gasification Based Polygeneration: Advanced Ceramic Membranes/Modules for Ultra Efficient Hydrogen (H 2 ) Production/Carbon Dioxide (CO 2 ) Capture for Coal-Based Polygeneration

The 21 st Century Power Plant Gasification Based Polygeneration power plant layout is a relatively straightforward retrofit of well-established ammonia synthesis technology to the baseline IGCC process and envisions co-production of power and chemicals from coal in the context of carbon capture. A Dual Stage Membrane Process (DSMP) for pre-combustion CO 2 capture in a coal fired IGCC power plant has been demonstrated by Media and Process Technology Inc (MPT) (DE-FE0013064) in bench-scale live gas testing at the NCCC. This work, however, highlighted the importance of permeate purge capability to deliver deep H 2 recovery at moderate pressures and high carbon capture performance. Further, in the area of warm gas processing, a permeate purgeable membrane support for a wide range of inorganic high-performance membrane materials (CMS, Pd-alloy, zeolite, ZIF, graphene, etc.) was not available and hence had been a common and significant barrier to their commercialization. Hence, the Critical Technology Gap to implementing the DSMP in the Polygeneration power plant and more broadly in advanced warm gas separation applications was the inability to permeate purge the membranes coupled with the lack of the availability of a high packing density scalable package design. To overcome this Critical Technology Gap, in this project, the primary objective was the development of a permeate purgeable full ceramic support for these high-performance inorganic membranes and the complementary high packing density housing. Our goal and approach were to extend our “candle filter” design to a “dual end open” package to enable permeate purge and scalability. Microporous ceramic membranes have been proven to be a low cost, stable material for high temperature applications under harsh environment. They are the leading support choice of researchers in advanced inorganic membrane development in applications such as pre-combustion CO 2 capture. The new 2nd Generation “dual end open” bundle developed in this project is a universal support for these existing and emerging inorganic membrane technologies that up to now have lacked a pathway out of the laboratory. The full ceramic permeate purgeable support represents a transformational technology and opens the door to commercialization of these advanced membrane materials in a wide array of mega scale commercial applications in gas (and liquid) processing under aggressive conditions not suited to conventional polymeric membranes.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Life Cycle Assessment and Cost Analysis of a Process-Based Sorbent-Based Direct Air Capture with Temperature-Vacuum Swing Adsorption Model

This presentation discusses different aspects of LCA and TEA of sorbent-based case study updates and methodologies utilized for carbon dioxide removal technologies. The combined TEA and LCA approach adopted herein provides insight into trade-offs between environmental performance and cost efficiency under various energy supply scenarios.

carbon dioxide removal↗
DOE OSTI2025

GenAI-Based Digital Twins Aided Data Augmentation Increases Accuracy in Real-Time Cokurtosis-Based Anomaly Detection of Wearable Data

Early detection of potential infectious disease outbreaks is crucial for developing effective interventions. In this study, we introduce advanced anomaly detection methods tailored for health datasets collected from wearables, offering insights at both individual and population levels. Leveraging real-world physiological data from wearables, including heart rate and activity, we developed a framework for the early detection of infection in individuals. Despite the availability of data from recent pandemics, substantial gaps remain in data collection, hindering method development. To bridge this gap, we utilized Wasserstein Generative Adversarial Networks (WGANs) to generate realistic synthetic wearable data, augmenting our dataset for training. Subsequently, we use these augmented datasets to implement a cokurtosis-based technique for anomaly detection in multivariate time-series data. Our approach includes a comprehensive assessment of uncertainties in synthetic data compared to the actual data upon which it was modeled, as well as the uncertainty associated with fine-tuning anomaly detection thresholds in physiological measurements. Through our work, we present an enhanced method for early anomaly detection in multivariate datasets, with promising applications in healthcare and beyond. This framework could revolutionize early detection strategies and significantly impact public health response efforts in future pandemics.

Data-Driven Digital Twins↗
DOE OSTI2024

Multi-Modal Characterization of Interfacial Corrosion of Ni-based Alloys in Chloride-based Molten Salts

The United States Department of Energy (DOE) is committed to the advancement of nuclear reactor technology through initiatives such as the Advanced Reactor Development Program (ARDP), to diversify the United States energy portfolio towards more sustainable energy options. The ARDP includes demonstration by industry partners of molten salt fast reactors (MSRs). Construction of molten salt reactor technology requires qualified nuclear structural materials. Unfortunately, there are no current materials that meet current qualification requirements dictated by the Nuclear Regulatory Commission for construction of MSRs. Adapting current structural material qualifications requires expansion of our current knowledgebase on corrosion performance. In this investigation, we assess microstructural changes in a Ni-based superalloy after exposure to a chloride-containing salt system through a correlated multi-modal approach combining several advanced characterization techniques. Namely we will highlight the impact of grain boundary phenomena at the onset of corrosion attack, including the role of intergranular crack propagation and development of internal corrosion products. The findings from this investigation will further expand our assessment of the corrosion performance of structural materials being investigated for construction of MSR components.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Convergence of Cloud Droplet Spectral Relative Dispersion During Entrainment‐Mixing Based on Particle‐Resolved Direct Numerical Simulations

Entrainment-mixing processes critically impact cloud microphysical properties, but their effects on the relative dispersion (d) of cloud droplet size distributions (CDSDs) remain elusive. A direct numerical simulation model is initialized with different CDSDs to fill the gap. These results show that d decreases for broad CDSDs and increases for narrow ones, ultimately converging to approximately 0.5 regardless of initial CDSDs during the evaporation-dominated mixing stage. The supersaturation fluctuation and the shape of CDSDs jointly influence the convergence behavior of d. Further sensitivity tests show that the initial microphysical/dynamical/thermodynamical conditions exert negligible effects on the final converged value of d but affect the convergence rate (k). The k generally increases with increasing droplet number concentration and dissipation rate, and increases with decreasing liquid water content, relative humidity of entrained air, and mixing fraction of cloudy air. A conceptual model with two timescales is proposed; k and the timescales are negatively correlated, meaning that slow mixing and/or evaporation process results in slow convergence of d. In conclusion, this finding provides an important reference for improving understanding and parameterization of d during the entrainment-mixing processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Local order, disorder, and everything in between: using 91 Zr solid-state NMR spectroscopy to probe zirconium-based metal–organic frameworks

Characterization of metal centers in metal–organic frameworks (MOFs) is critical for rational design and further understanding of structure–property relationships. The short-range structure about Zr atoms is challenging to properly elucidate in many Zr MOFs, particularly when local disorder is present. Static 91 Zr solid-state NMR spectra of the seven zirconium MOFs UiO-66, UiO-66-NH 2 , UiO-67, MOF-801, MOF-808, DUT-68 and DUT-69 have been acquired at high magnetic fields of 35.2 T and 19.6 T, yielding valuable information on the local structure, site symmetry and order about Zr. 91 Zr NMR is very sensitive to differences in MOF short-range structure caused by guest molecules, linker substitution and post-synthetic treatment. Complementary density functional theory (DFT) calculations assist in the interpretation and assignment of 91 Zr solid-state NMR spectra, lend insight into structural origins of 91 Zr NMR parameters and enable determination of local Zr coordination environments. This approach can be extended to many other materials containing zirconium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗