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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Environmental Degradation in Advanced Reactor Environments

The Advanced Materials and Manufacturing Technologies (AMMT) program operating under the Department of Energy Office of Nuclear Energy is accelerating the qualification and deployment of additively manufactured materials in advanced reactor environments. Laser powder bed fusion (LPBF) has emerged as a promising additive manufacturing technique to fabricate complex components with the potential of tailored material properties. In the nuclear industry, metal additive manufacturing can offer numerous advantages, such as reduced lead times, streamlined quality assurance, and cost-effective low-volume production of new and replacement components with conventional or novel materials and geometries. The rapid and effective qualification of the effect of processing variability on the performance and degradation of additively manufactured materials is essential for the deployment of these components into advanced reactor environments. This talk presents an overview of the Environmental Effects area activities within AMMT. AMMT is performing irradiation and corrosion testing of several materials built by LPBF, including 316L and 316H stainless steels. Our irradiation efforts encompass neutron irradiation testing and ion irradiation testing to provide a robust technical basis for understanding the effect of process variability on materials degradation. We develop focused irradiation test plans that align well with risk-informed and technologically inclusive approaches to licensing. We will also discuss our plans and specific concerns for corrosion testing additively manufactured material, with a primary focus on molten salt and liquid sodium environments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Virtual Inspection of Advanced Manufacturing via Process-Scale Digital Twins (Abbreviated Report)

Inspection and certification comprise the most significant bottlenecks in advanced manufacturing for NNSA applications, often requiring far more time and resources than the fabrication of the parts themselves. Traditional methods, such as manual review and X-ray computed tomography, are not only slow and costly, but also struggle to provide a clear connection between manufacturing instructions and the final performance of critical components. This gap limits both the agility and assurance needed to support the modernization and safety of the United States nuclear stockpile. In response, our Strategic Initiative established a digital twin framework that integrates realtime process monitoring, automated data analysis, and immersive virtual reality collaboration into a unified inspection pipeline. By leveraging data from sensors, machine instructions, and imaging, we created high-fidelity virtual models of manufactured parts that could be rapidly analyzed and certified. This approach was first demonstrated with Direct Ink Write, and then extended to other manufacturing settings, including conventional (or “subtractive”) manufacturing and to predict the end of life performance of parts per the aging and lifetimes programs. The result is a transformational capability: inspection times have been reduced by a factor of 120,000 without loss of accuracy and while simultaneously improving traceability and confidence in part quality. This framework not only streamlines certification for critical applications, but also positions the national security enterprise to respond more flexibly to emerging challenges, supporting agile manufacturing and digital engineering practices across a broad range of mission-relevant domains.

42 ENGINEERING↗
DOE OSTI2026

Improvements to In-Canal Assay of High Specific Activity 60Co at the ATR

Improvements to the quality of measurements in the assaying of High Specific Activity (HSA) cobalt 60 produced at the Advanced Test Reactor at the Idaho National Laboratory are presented. Such assays are conducted regularly between cycles at the ATR, and due to the radiological safety concerns, they are performed within the ATR canal. A standard ion chamber detector was placed in a collimated assay tube within the canal. Another tube, parallel to the detector, was used to position various cobalt 60 standards and targets. The collimated port between these tubes allows for the targets to be pulled across via a winch system. Previous measurements were performed at discrete 1.5-inch steps using a hand-cranked winch system. Charge was collected and integrated for 10 seconds at each discrete step during a scan. Two substantial improvements to the assay include an electronically controlled, motor-driven winch system and a software controlled continuous charge collection. Combined, these changes improved the quality of measurements as well as streamline the assay process. Further examination of these charge profiles indicated a reasonable amount of photon scattering, or shine, before a line-of-sight is established. This created inaccuracies in the reported activity of the cobalt targets. A series of MCNP-6.3 calculations were performed in an effort to quantify and correct for this shine effect. The results of the calculations and how they were employed to a create shine correction factor for the in-canal cobalt assay at the ATR are presented. The overall bias showed an overestimation of the HSA cobalt 60 activity by around 7-8%.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2025

MLBS Halo scanning Lidar / Reviewed Data / Fixed-point vertical scans

This dataset contains high-frequency vertical velocity recorded by fixed-point vertical scans done by the University of Virginia Halo Streamline scanning lidar at the MLBS station. The quality control is performed according to the algorithm of Goring & Nikora (2002).

17 WIND ENERGY↗
DOE OSTI2024

Cool GTL for the Conversion of Biogas to Jet Fuel

Cool GTL is a new process under development for conversion of biogas from digestors or CO2 +H2 to high quality drop in jet fuel. Cool GTL is designed to be a streamlined simplified low cost process which can be cost effective for small scale biogas applications. Cool GTL has the advantage that it uses a high activity bi-reforming catalyst, in a streamlined electric reformer design, to make the synthesis gas for a high conversion slurry fischer Tropsch process followed by a trailing wax cracking reactor. In this way high quality jet fuel can be directly produced. Recent experimental test data will be presented showing product quality. The life cycle analysis LCA will also be presented as well.

09 BIOMASS FUELS↗
DOE OSTI2024

PIPES (Pipeline for Integrated Projects in Energy Systems) [SWR-24-89]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. https://github.com/nrel-pipes/pipes-api https://github.com/nrel-pipes/pipes-web https://github.com/nrel-pipes/nrel-pipes

Gu, Jianli↗
DOE OSTI2025

Pipeline for Integrated Projects in Energy Systems (PIPES): A Tool for Integrated System Planning [Slides]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. This presentation introduces PIPES a multi-model tool for integrated system planning; it describes the underlying architecture, deep dives into common user workflows, and outlines the upcoming development roadmap beyond its current alpha state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters

High-precision calorimeter simulation at current and future colliders imposes rapidly growing computational demands, motivating the development of machine-learning surrogates for traditional Monte Carlo tools such as Geant4. Flow matching and diffusion-based generative models have become leading approaches for high-dimensional fast simulation because of their sample quality, but typically require ${\cal O}(100)$ function evaluations at inference and often rely on auxiliary networks to constrain global observables, compromising streamlined end-to-end generation. We introduce a unified framework that improves the balance between speed, shower quality, and physics fidelity. The method combines: (i) an average velocity field integrator that enables sampling in one or a few evaluations; (ii) a learned generative prior in shower space, constructed from data rather than random noise; and (iii) physics-guided loss terms that impose inductive biases on key observables during training. These elements are training time regularizers, preserving end-to-end inference with no additional cost. With only one or a few evaluation steps, the model achieves shower quality competitive with state-of-the-art flow and diffusion approaches, tested on several public high granularity calorimeter datasets. The results demonstrate inter-layer shower structure consistent with the underlying physics, providing a strong candidate for future fast simulation workflows.

Jiang, Cheng [Edinburgh U.]↗
DOE OSTI2025

Porous carbon from lignocellulosic biomass with emphasis on corn plant waste residue for energy storage

The rising global demand for sustainable energy storage materials has driven the search for environmentally friendly and cost-effective electrode options. Hydrothermal conversion of lignocellulosic biomass has gained attention due to its low energy requirements and operation at relatively low temperatures, presenting a green alternative to traditional thermochemical methods. The resulting solid product, hydrochar, has been used as an adsorbent and soil amendment; however, chemical/thermal treatment significantly enhances its physical properties. These structural modifications transform hydrochar into an effective porous carbon electrode, offering abundant sites for electrolyte ion transport, critical for high-performance devices like supercapacitors and batteries. This review first discusses various waste biomass and sustainable feedstocks available globally. It compares two primary thermochemical conversion techniques, pyrolysis and hydrothermal carbonization/liquefaction, and examines their respective solid products, biochar and hydrochar, analyzing differences in their physical and chemical characteristics. The focus is placed on hydrochar, summarizing activation methods to produce porous carbon suitable for energy storage applications. Additionally, this review will include a dedicated section on the application of porous carbon derived from corn plant waste residue, considering that corn is one of the most abundant crops grown worldwide, which makes it an important and promising source for sustainable porous carbon production. The role of machine learning models in optimizing hydrothermal processes to produce high-quality hydrochar is also discussed, emphasizing how data-driven approaches can streamline process development. Finally, the review identifies the current challenges and prospects for lignocellulosic biomass-derived porous carbon as a sustainable electrode material in next-generation energy storage technologies.

25 ENERGY STORAGE↗
DOE OSTI2024

In-Plane Liftout and Push-to-Pull for In Situ Mechanical Testing of Irradiated Inconel X-750

A streamlined sample preparation method for nanomechanical testing is needed to improve the quality of specimens, reduce the cost, and increase the versatility of specimen fabrication. This work outlines an in-plane liftout focused ion beam (FIB) fabrication procedure to prepare electron-transparent specimens for in situ transmission electron microscopy (TEM) nanomechanical testing. Ion etching and electron backscatter diffraction (EBSD) techniques were used to lift out a [110] oriented grain from a neutron-irradiated bulk X-750 alloy. Careful control of voltages and currents ensured precision. Top surface thinning sweeps prevented resurfacing and redeposition while dog-bone geometries were shaped with a 1:4 gauge width-to-milling pattern diameter ratio. Nanotensile testing in the TEM with a picoindenter allowed for the estimation of an ultimate tensile strength of 2.41 GPa, and inspection revealed a high density of bubbles in the X-750 matrix. The proposed fabrication procedure is significant for preparing samples from radioactive materials, studying complex structures that are orientation-dependent, and analyzing desired planar areas.

36 MATERIALS SCIENCE↗
DOE OSTI2025

WREF Halo Streamline scanning lidar / Derived data / RHI

This dataset contains streamwise velocity retrieved from the Range Height Indicator (RHI) scans done by the UC Davis scanning Lidar. The quality control of the radial wind speed is performed following the algorithm of Beck & Kuhn (2017). Instantaneous realizations characterized by wind misalignment greater than 60 degrees (based on the closest VAD scan in time) are discarded.

17 WIND ENERGY↗
DOE OSTI2025

An Open-Source Python Package for CFD Solution Verification

Informed decision-making using computational fluid dynamics (CFD) results requires quantifying the errors and uncertainties of a simulation. Verification, validation, and uncertainty quantification (VVUQ) methods were developed to address this need and have matured. However, these VVUQ analyses are often non-trivial and require CFD analysts and practitioners to have specific skill sets. This has led to the uneven adoption of VVUQ analyses, in part, based on the availability of software tools to aid CFD analysts and practitioners. Solution verification, a procedure to evaluate the accuracy of a simulation by estimating potential errors arising from the computational model and computing the uncertainties without comparing to results from a physical system, is one of the lagging VVUQ analyses as the absence of software has forced CFD analysts and practitioners to develop their own codes or piece together incomplete software from across the internet. This work presents an opensource Python package, CFDverify, to lower the barrier of entry and fill in the technological gap in solution verification. CFDverify also provides a streamlined framework to remove some potential errors in post-processing CFD results. The hope is that CFDverify can improve the quality and quantity of CFD solution verification in scientific and research studies and attract interest in developing a communal tool. This paper describes the design, features, and an example use of CFDverify.

Weinmeister, Justin [ORNL] (ORCID:0000000160090237↗