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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 OSTI2024

Development and Demonstration of a Risk Assessment Approach for Approval of a Transportation Package of a Transportable Nuclear Power Plant for Domestic Highway Shipment

The U.S. Department of Defense (DoD) Strategic Capabilities Office (SCO) has tasked PNNL to address the regulatory challenges associated with confirming the safe transport of Transportable Nuclear Power Plants (TNPPs) containing irradiated nuclear fuel. A previous report—Proposed Risk-Informed Regulatory Framework for Approval of Microreactor Transportation Packages (PNNL-31867)—determined that the expected radioactive inventory in the irradiated fuel of a TNPP would likely require shipment in an NRC-approved Type B package (or spent nuclear fuel cask) but that a TNPP “package” is unlikely to meet the entire suite of NRC requirements set forth in Part 71 of Title 10 of the Code of Federal Regulations (CFR) for a Type B package. It was therefore concluded that shipment of this initial TNPP transportation package, as well as possibly others, under existing regulations would likely require NRC approval using the 10 CFR 71.12 (“Specific exemptions”) process that relies on risk-informed decision making supported by quantitative risk assessment (i.e., Probabilistic Risk Assessment).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Low Thermal Resistance (0.5 K/W) Ga 2 O 3 Schottky Rectifiers With Double-Side Packaging

The low thermal conductivity of Ga 2 O 3 has arguably been the most serious concern for Ga 2 O 3 power and RF devices. Despite many simulation studies, there is no experimental report on the thermal resistance of a large-area, packaged Ga 2 O 3 device. This work fills this gap by demonstrating a 15-A double-side packaged Ga 2 O 3 Schottky barrier diode (SBD) and measuring its junction-to-case thermal resistance (R θJC ) in the bottom-side- and junction-side-cooling configurations. The R θJC characterization is based on the transient dual interface method, i.e., JEDEC 51-14 standard. The R θJC of the junction- and bottom-cooled Ga 2 O 3 SBD was measured to be 0.5 K/W and 1.43 K/W, respectively, with the former R θJC lower than that of similarly-rated commercial SiC SBDs. This low R θJC is attributable to the heat extraction directly from the Schottky junction instead of through the Ga 2 O 3 chip. Here, the R θJC lower than that of commercial SiC devices proves the viability of Ga 2 O 3 devices for high-power applications and manifest the significance of proper packaging for their thermal management.

42 ENGINEERING↗
DOE OSTI2023

Valorization of Hemp-Based Packaging Waste with One-Pot Ionic Liquid Technology

The range of applications for industrial hemp has consistently increased in various sectors over the years. For example, hemp hurd can be used as a resource to produce biodegradable packaging materials when incorporated into a fungal mycelium composite, a process that has been commercialized. Although these packaging materials can be composted after usage, they may present an opportunity for valorization in a biorefinery setting. Here, we demonstrate the potential of using this type of discarded packaging composite as a feedstock for biofuel production. A one-pot ionic liquid-based biomass deconstruction and conversion process was implemented, and the results from the packaging material were compared with those obtained from untreated hemp hurd. At a 120 °C reaction temperature, 7.5% ionic liquid loading, and 2 h reaction time, the packaging materials showed a higher lignocellulosic sugar yield and sugar concentrations than hemp hurd. Hydrolysates prepared from packaging materials also promoted production of higher titers (1400 mg/L) of the jet-fuel precursor bisabolene when used to cultivate an engineered strain of the yeast Rhodosporidium toruloides. Box–Behnken experiments revealed that pretreatment parameters affected the hemp hurd and packaging materials differently, evidencing different degrees of recalcitrance. This study demonstrated that a hemp hurd-based packaging material can be valorized a second time once it reaches the end of its primary use by supplying it as a feedstock to produce biofuels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

twoaxistracking – a python package for simulating self-shading of two-axis tracking solar collectors

Self-shading in fields of two-axis tracking collectors typically ranges from 1% to 6% of the annual incident irradiation. It is thus essential to account for shading in order to obtain accurate yield estimates and financing for such solar projects. The present study presents the free and open-source Python package twoaxistracking for simulating self-shading in fields of two-axis tracking collectors. The package is freely available at: https://github.com/pvlib/twoaxistracking. The main steps of the method and mathematical formulation are described. Additionally, a demonstration of how to use the package is presented. The shading calculation method excels over previous methods found in the literature in that it can: handle arbitrary aperture geometries and distinguish between the total and active areas; account for sloped ground and collectors with different heights within the same field; reduce computation time by skipping calculations at high solar elevation angles.

14 SOLAR ENERGY↗
DOE OSTI2026

Generative large language models for predictive maintenance planning

Maintenance planning and the generation of necessary components for tasks can prove time-consuming and complex. Automating the creation of recurring or similar tasks by leveraging previous planning packages and data, while uncovering insights to automate planning package generation, presents an opportunity to conserve valuable time and resources. This work aims to harness the textual and probabilistic capabilities of large language models (LLMs) to automate the generation of planning packages. Utilizing diverse data sources ranging from raw data to handwritten text, both singular and collaborative LLMs are trained and tested. Results demonstrate their capability to generate essential planning package components, effectively replicating the statistical patterns in the data. This demonstrates the use of these tools inside a digital asset for automated planning. This work outlines a methodology for constructing datasets, a training suite, and evaluation methods for LLM-based textual and conversational planning tools utilized in an asset digital twin. Results indicate that the fine-tuned models generate estimated planning information within the statistical ranges observed in real maintenance data. The models achieve high accuracy (>90%) in document question-answering and instruction generation tasks. Furthermore, the conversational retrieval-augmented generation (RAG) assistant system achieves 100% document retrieval accuracy, while conversational information capture exceeds 98% across the majority of work-package assistant modules.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

QuTree: A tree tensor network package

Here we present QuTree, a C++ library for tree tensor network approaches. QuTree provides class structures for tensors, tensor trees, and related linear algebra functions that facilitate the fast development of tree tensor network approaches such as the multilayer multiconfigurational time-dependent Hartree approach or the density matrix renormalization group approach and its various extensions. We investigate the efficiency of relevant tensor and tensor network operations and show that the overhead for managing the network structure is negligible, even in cases with a million leaves and small tensors. QuTree focuses on providing simple, high-level routines while retaining easy access to the backend to facilitate novel developments. We demonstrate the capabilities of the package by computing the eigenstates of coupled harmonic oscillator Hamiltonians and performing random circuit simulations on a virtual quantum computer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

bmdrc: Python package for quantifying phenotypes from chemical exposures with benchmark dose modeling

Though chemical exposures are known to potentially have negative impacts on health, including contributing to chronic diseases such as cancer, the quantitative contribution of risk is not fully understood for every chemical. A commonly used approach to quantify levels of risk is to measure the proportion of organisms (such as a total number of zebrafish on a plate or mice in a cage) with abnormal behavioral responses or morphology at increasing concentrations of chemical exposure. A particular challenge with processing the proportional data from these assays is the appropriate estimation of chemical concentration levels that result in malformations or acute toxicity, as these values typically vary between experimental measurements. The recommended approach by the Environmental Protection Agency (EPA) is to fit benchmark dose curves with specific filters and model fitting steps, which are crucial to properly processing the proportional data. Several tools exist for the fitting of benchmark dose response curves, but none are standalone Python libraries built to process both morphological and behavioral data as proportions with all the EPA recommended filters, filter parameters, models, and model parameters. Thus, here we present the benchmark dose response curve (bmdrc) Python library, which was built to closely follow these EPA guidelines with helpful visualizations of filters and fitted model curves, and reports for reproducibility purposes. bmdrc is open-source and has demonstrated utility as a support package to an existing web portal for information on chemicals (https://srp.pnnl.gov). Our package will support any toxicology analysis where the response is a proportional value at increasing levels of a concentration of a chemical or chemical mixture.

Superfund↗
DOE OSTI2024

PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments

This article describes PyOED, a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Specifically, PyOED aims to be a comprehensive Python toolkit for model-constrained OED. The package targets scientists and researchers interested in understanding the details of OED formulations and approaches. It is also meant to enable researchers to experiment with standard and innovative OED technologies with a wide range of test problems (e.g., simulation models). OED, inverse problems (e.g., Bayesian inversion), and data assimilation (DA) are closely related research fields, and their formulations overlap significantly. Thus, PyOED is continuously being expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators. These pieces are added such that they can be permuted to enable testing OED methods in various settings of varying complexities. The PyOED core is completely written in Python and utilizes the inherent object-oriented capabilities; however, the current version of PyOED is meant to be extensible rather than scalable. Specifically, PyOED is developed to “enable rapid development and benchmarking of OED methods with minimal coding effort and to maximize code reutilization.” This article provides a brief description of the PyOED layout and philosophy and provides a set of exemplary test cases and tutorials to demonstrate the potential of the package.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

How R Developers explain their Package Choice: A Survey

Background: Contemporary software development relies heavily on reusing already implemented functionality, usually in the form of packages. Aims: We aim to shed light on developers' preferences when selecting packages in R language. Method: To do that, we create and administer a survey to over 1000 developers who have added one of two common dataframe enhancement libraries in R to their projects: data.table or tidyr. We design a questionnaire using the Social Contagion Theory (SCT) following prior work on technology adoption and ensure that key dimensions affecting developer choice are considered. Results: Of the 1085 developers we contacted, 803 completed the survey asking them to prioritize various factors known to affect developer perceptions of package quality and to provide their background. Most developers self-identified as data scientists with two to five years of work experience. We found significant differences between the preferences of developers who chose data.table and tidyr. Surprisingly, package reputation based on easy-to-see measures, such as the number of stars on GitHub, was not an important factor for either group. Conclusions: Our findings demonstrate the inherently social nature of package adoption. They can help design future studies on how different populations of developers make decisions on which software packages to use in their projects. Finally, package developers and maintainers can benefit by better understanding the prime concerns of the users of their packages.

Malviya Thakur, Addi↗
DOE OSTI2021

The utility of Bayesian data reconciliation for separations

Data reconciliation methods for separation processes typically rely on classical statistical approaches to generate estimates of true mass flow rates from measurements. Knowledge regarding the uncertainty of these estimates has value in decision making, but is often not acquired. Bayesian approaches intrinsically quantify uncertainty; however, literature for Bayesian data reconciliation of separation processes is scarce. This publication outlines two Bayesian data reconciliation models and provides details for how the models were implemented for the BayesMassBal (V 1.0.0) software package written in R. To demonstrate the advantages of this approach for data reconciliation, the models were first applied to simulated data and then compared to a classical model through a Monte Carlo experiment. In this example, the Bayesian models were found to provide more accurate estimates of the simulated data, while also providing quantitative information on the estimate uncertainty. To demonstrate the use of the technique in a practical problem, the models were also applied to real data collected from a pilot-scale rare earth solvent extraction process. Here, this publication provides a small window into how Bayesian methods can be used for data reconciliation, but findings suggest Bayesian data reconciliation models for separation processes have distinct advantages over classical alternatives.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Catalight─An Open-Source Automated Photocatalytic Reactor Package Illustrated through Plasmonic Acetylene Hydrogenation

An open-source and modular Python package, Catalight, is developed and demonstrated to automate (photo)catalysis measurements. (Photo)catalysis experiments require studying several parameters to evaluate performance, including the temperature, gas flow rate and composition, illumination power, and spectral profile. Catalight orchestrates measurements over this complicated parameter space and systematically stores, analyzes, and visualizes the results. To showcase the capabilities of Catalight, we perform an automated apparent activation barrier measurement of acetylene hydrogenation over a plasmonic AuPd catalyst on an Al 2 O 3 support, simultaneously varying laser power, wavelength, and temperature in a multiday experiment controlled by a simple Python script. Our chemical results unexpectedly show an increased activation barrier upon light excitation, contrary to previous findings for other plasmonic reactions and catalysts. We show that the reaction rate order with respect to both acetylene and hydrogen remains unchanged upon illumination, suggesting that molecular surface coverage is not changed by light. By analyzing the inhomogeneity of the laser-induced heating, we attribute these results to a partial photothermal effect combined with a photochemical/hot electron-driven mechanism. In conclusion, our findings highlight the capabilities of a new experiment automation tool; explore the photocatalytic mechanism for an industrially relevant reaction; and identify systematic sources of error in canonical photocatalysis experimental procedures.

Catalysts↗
DOE OSTI2023

Replacement of Legacy Analytical Codes at the Advanced Test Reactor

For each operating cycle of the Advanced Test Reactor (ATR) at Idaho National Laboratory, a Core Safety Assurance Package (CSAP) is necessary to demonstrate compliance with the safety basis approved by the United State Department of Energy (DOE). Certain computer codes are used in CSAP development, most of them developed in-house. This work describes replacement of a large set of these codes and updates previous work. Replacement of legacy codes is necessary due to computer hardware failure but also has generally improved user-friendliness.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Replacement of Legacy Analytical Codes at the Advanced Test Reactor

For each operating cycle of the Advanced Test Reactor (ATR) at Idaho National Laboratory, a Core Safety Assurance Package (CSAP) is necessary to demonstrate compliance with the safety basis approved by the United State Department of Energy (DOE). Certain computer codes are used in CSAP development, most of them developed in-house. This work describes replacement of a large set of these codes and updates previous work. Replacement of legacy codes is necessary due to computer hardware failure but also has generally improved user-friendliness.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay

In recent years, machine learning (ML) models have been used to improve physical parameterizations of general circulation models (GCMs). A significant challenge of integrating ML models into GCMs is the online instability when they are coupled for long‐term simulation. We present a new strategy that demonstrates robust online stability when the physical parameterization package of an atmospheric GCM is replaced by a deep ML model. The method uses experience replay with a multistep training scheme of the ML model in which the model's own output at the previous time step is used in the training. Predicted physics tendencies in the replay buffer with the most recent errors in the training iterations are reused, making the ML model learn from its own errors. The training method reduces the gap between the offline and online environments of the ML model. The method is used to train the ML model as the physical parameterization of the Community Atmosphere Model (CAM5) with training data from the Multi‐scale Modeling Framework high resolution simulations. Three 6‐year online simulations of the CAM5 are carried out by using the ML physics package. The simulated spatial distributions of precipitation, surface temperature and zonally averaged atmospheric fields demonstrate overall better accuracy than that of the standard CAM5 and benchmark model even without the use of additional physical constraints or tuning. This work is the first to demonstrate a solution to address the online instability problem in climate modeling with ML physics by using experience replay.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluation of Hydrogen Gas Generation and Permeation in the 9979 Type AF Shipping Package

The 9979 Type AF Shipping Packaging is a cost-effective radioactive material package designed by Savannah River National Laboratory (SRNL) that consists of two primary components: a foamed outer drum for structural protection and an inner containment drum. The packaging was designed to transport Highly Enriched Uranium (HEU), Low Enriched Uranium (LEU), and other isotopes not exceeding a Type A quantity. These contents have the potential to generate flammable hydrogen gas during transport due to the degradation of hydrogenous materials (e.g. water vapor, plastics, etc) by high-energy alpha radiation. Since 10 CFR 71.43(h) prohibits the incorporation of packaging features explicitly designed for continuous venting, alternative justification was required to demonstrate that the requirements of 10 CFR 71.43(d) for negligible reactions between packaging components and contents were satisfied. An analysis was performed to demonstrate that the potential for hydrogen gas generation over a one-year period was limited by the effects of permeation through the packaging materials. The rate of hydrogen collection was evaluated for both the inner containment drum and the outer structural drum under 10 CFR 71.71 Normal Conditions of Transport (NCT). The analysis concludes that the Lower Flammability Limit (LFL) for hydrogen gas will not be reached in a one-year shipping period assuming a minimum void volume is maintained within the drum.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

ftmsRanalysis: An R package for exploratory data analysis and interactive visualization of FT-MS data

The high-resolution and mass accuracy of Fourier transform mass spectrometry (FT-MS) has made it an increasingly popular technique for discerning the composition of soil, plant and aquatic samples containing complex mixtures of proteins, carbohydrates, lipids, lignins, hydrocarbons, phytochemicals and other compounds. Thus, there is a growing demand for informatics tools to analyze FT-MS data that will aid investigators seeking to understand the availability of carbon compounds to biotic and abiotic oxidation and to compare fundamental chemical properties of complex samples across groups. We present ftmsRanalysis, an R package which provides an extensive collection of data formatting and processing, filtering, visualization, and sample and group comparison functionalities. The package provides a suite of plotting methods and enables expedient, flexible and interactive visualization of complex datasets through functions which link to a powerful and interactive visualization user interface, Trelliscope. Example analysis using FT-MS data from a soil microbiology study demonstrates the core functionality of the package and highlights the capabilities for producing interactive visualizations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Cask RT-100 Type B(U) Self-Certification for DOT 7A, Type A Nuclear Waste Transportation - 20098

The purpose of this Type A certification is to diversify the use of the RT-100 cask by allowing the end user to transport either Type A or Type B radioactive waste in accordance with the handling procedures for each waste category. The project's scope included the development of a matrix that contains all applicable requirements for a Type A package from the Code of Federal Regulations (CFR), Title 49 for the Department of Transportation (DOT) with a justification for each requirement. Moreover, the scope included the writing of conditions and restrictions list for the transportation of Type A nuclear waste, the writing of a compliance statement, and the design and fabrication of a Type A placard to be permanently placed on the RT-100 cask. Type A packages are self-certified by the end user using one of three methods as permitted by 49 CFR 173.461, either by performance of tests with prototypes or samples of the specimens representing the packaging, or reference to a previous satisfactory demonstration of compliance of a sufficiently similar nature, or calculations or reasoned evaluation using reliable and conservative procedures and parameters. Since the RT-100 cask was licensed by the Nuclear Regulatory Commission (NRC) as a Type B cask, Robatel relied on the method of reference to a previous satisfactory demonstration of compliance of a sufficiently similar nature for Type A certification. This method was determined to be acceptable, since Type B packages are evaluated for more demanding transport conditions than those required for Type A packages. This paper presents Robatel's process for certifying the RT-100 cask for Type A shipments, an overview of the DOT regulations related to Type A packages, and the documents that were generated for the end user. This paper is concluded with a discussion on the advantages of having the option to transport both Type A and Type B nuclear waste, and possible future projects to further improve the operation of the cask when making Type A shipments. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Benchmarking MELCOR's NAC Package to ABCOVE Tests AB5 and AB6

This report presents analyses of the AB5 and AB6 ABCOVE sodium spray fire experiments with the MELCOR code. This code simulates the progression of accident events for analysis and auditing purposes of nuclear facilities during accident conditions. Historically, the ABCOVE experiments have contributed to the validation of aerosol physics and related phenomena. Given advancements in sodium-cooled reactor designs, characterization of the sodium spray combustion may further the review and validation of newly incorporated sodium properties and physics packages, namely, the sodium equations of state (EOS) and the sodium combustion (NAC) package within MELCOR. By analyzing the AB5 and AB6 experiments with and without the NAC package, sodium specificity for spray combustion and aerosol formation as well as speciation of the combustion products are reviewed with the new packages. This effort provides code users with a demonstration of the current code capabilities. This report provides the current best practices for the NAC package as well as a discussion of any issues observed while performing the presented analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗