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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 289 records · Page 16

The Effects of Beta Irradiation on the Performance of ATR Fiber Probes

The use of real-time inline monitoring to track the chemical composition of slurries is recognized as a promising method to reduce the processing time of Hanford tank waste. The conversion of waste into glass suitable for long-term storage requires adherence to waste acceptance criteria and process control limits that respectively ensure safe operation of the vitrification facility and suitable glass quality. Real-time measurements of blended waste materials can ensure that the various criteria are met or can be addressed in a timely manner.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Livewire Data Platform File Standards Version 1.0

This living document describes required and recommended standards for data additions to the Livewire Data Platform (https://livewire.energy.gov/). Adherence to the standards described enables development of automated analysis and discovery tools for Livewire data and will facilitate development of future capabilities for delivering data that can be tailored to meet user needs.

33 - ADVANCED PROPULSION SYSTEMS↗

Preliminary Plan to Inform Testing of a Heat Exchanger Test Article

This report presents a preliminary plan to guide the qualification testing of advanced heat exchanger (HX) components for nuclear-to-industrial heat transfer applications. The objective is to establish a defensible, physics-based methodology that integrates computational modeling, targeted experimentation, and in-service inspection considerations to demonstrate component performance and reliability under representative reactor conditions. The analysis identifies Sodium-cooled Fast Reactor (SFR) and High-Temperature Gas-cooled Reactor (HTGR) systems as reference configurations in terms of temperature, pressure, and chemical environment. Within these operating envelopes, dominant degradation mechanisms— including creep–fatigue interaction, flow-induced vibration, corrosion, and diffusion-bond deterioration—were evaluated to define test requirements. A comprehensive computationalexperimental framework is proposed to support life prediction and qualification activities. The framework couples high-fidelity structural-mechanics, thermal-hydraulic, and fluid-structure interaction models with accelerated degradation testing to produce a traceable linkage between microstructural evolution, mechanical performance, and remaining useful life (RUL). The approach adheres to established Verification, Validation, and Uncertainty Quantification (VVUQ) standards (ASME V&V 10/20; NUREG-2152) and incorporates a digital-twin architecture for continuous model refinement through data assimilation. The plan further outlines testing methodologies, including pre-test analyses, test-loop design parameters, and sensor placement strategies that maximize information yield while maintaining mechanistic fidelity. Complementary sections describe in-service inspection (ISI), on-line monitoring (OLM), and structural-health-monitoring (SHM) techniques applicable to compact HX geometries typical of advanced reactors. Collectively, these activities establish the technical foundation for demonstrating 40-60-year equivalent service life of advanced heat exchangers in support of the U.S. Department of Energy’s Advanced Reactor and Integrated Energy Systems programs. The forthcoming phase will execute the defined pre-test analyses, initiate hardware fabrication, and implement the integrated testing campaign to validate the proposed qualification methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Luteolibacter sp. strain Populi

Luteolibacter sp. strain Populi is bacterium from the phylum Verrucomicrobiota, isolated from the rhizosphere of a black cottonwood tree, Populus trichocarpa, from the Cascade mountains in Washington. Its 6.6 Mb chromosome was completely sequenced using Oxford Nanopore long-reads and is predicted to encode 5301 proteins and 60 RNAs. The bacteria was isolated from the rhizosphere of a mature Populus trichocarpa from the Tieton riverwatershed of Washington state, USA (Lat: 46°42’9” N, Lon: 120°25 39’36” W). A rhizosphere sample (fine roots and adhering soil) was used to obtain a microbial fraction by centrifugation on Histodenz (12) and stained with 5µM Syto59 (Thermo Fisher Scientific Inc). A Cytopeia Influx cell sorter (BD, Franklin Lakes, NJ) was used to sort and array single cells (100 per plate) based on forward-side scatter and fluorescence intensity on asparagine-glucose nutrient agar (ATCC medium 184). The Luteolibacter sp. Populi genome sequence has been deposited in GenBank under the accession number CP161812. A draft genome annotated with Prokka and DRAM is available in this Narrative as Luteolibacter_sp_Prokka.240711.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of Irradiation on Corrosion Performance of Hybrid Organic/Inorganic Coatings on Austenitic Stainless Steel

The effects of gamma radiation on the performance of two corrosion-resistant coatings applied to stainless-steel 304L (SS304L) surfaces are presented. Specifically, the ability of the coatings to mitigate corrosion of SS304L surfaces as a function of the dose received (0–1300 Mrad) and dose rate (176 compared to 1054 rad/s) is evaluated using electrochemical methods, spectroscopy, and microscopy. Coating A, an organic/inorganic hybrid coating consisting of a two-part silica ceramic component and a polymer linker was evaluated in comparison to Coating B, which utilized Coating A as a topcoat for a commercial, off-the-shelf, Zn-rich primer. Post irradiation, Coating A demonstrated some corrosion protection following exposure to low levels of gamma radiation, but coating degradation occurred with an increased exposure dose and resulted in isolated regions of corrosion initiation. For Coating B, greater corrosion resistance was observed compared to Coating A due to the sacrificial nature of the Zn at elevated doses of gamma radiation. No effect of the dose rate (for the single dose examined) was observed for either coating. It is proposed for Coating B that as the polymer coating thermally degrades above 250 °C (bond scission of the polymer occurs), the remaining Zinc layer adhered to the SS304L post-irradiation enables enhanced corrosion resistance as compared to Coating A, which displays solely polymer degradation. The results presented herein establish an understanding of coating behavior with radiation exposure, specifically the relationship between corrosion coating performance and radiation dose, and can inform ageing and lifetime management for various applications.

degradation↗

Experimental Validation of a Modular All-Electric Power Take-Off Topology for Wave Energy Converter Enabling Marine Renewable Energy Interconnection

Power electronic converters are an enabling technology for the emerging marine energy applications, such as using ocean waves to produce electricity. This paper outlines the power take-off system and its key components used in a wave energy converter offering modularity and scalability to generate power efficiently. The proposed power take-off system was implemented based on a modular multilevel converter and could be deployed to convert any alternating current electrical energy to a different alternating current for interconnection to grid or non-grid applications. Examples of widespread deployment are supplying electricity to coastal communities or producing clean drinking water. The analysis using both the simulation tests and laboratory experiments verified the design objectives and basic functionality of the developed power take-off system. An acceptable response using a field programmable gate array-based controlled laboratory testbench was achieved, complying with guidelines specified in the prevalent industry standards. Seamless operation during steady-state and transients for the studied wave energy converter was achieved as supported by the obtained results. The key findings of this work were experimentally examined under different load conditions, direct current bus voltage fluctuations, and generator speed–torque regulation. The ability of the power take-off system to generate high-power quality of the waveforms, e.g., against adhering to the IEEE 519-2022 standard for total harmonic distortion limits, is also confirmed.

Engineering↗

Advances in Electrospun Poly(ε-caprolactone)-Based Nanofibrous Scaffolds for Tissue Engineering

Tissue engineering has great potential for the restoration of damaged tissue due to injury or disease. During tissue development, scaffolds provide structural support for cell growth. To grow healthy tissue, the principal components of such scaffolds must be biocompatible and nontoxic. Poly(ε-caprolactone) (PCL) is a biopolymer that has been used as a key component of composite scaffolds for tissue engineering applications due to its mechanical strength and biodegradability. However, PCL alone can have low cell adherence and wettability. Blends of biomaterials can be incorporated to achieve synergistic scaffold properties for tissue engineering. Electrospun PCL-based scaffolds consist of single or blended-composition nanofibers and nanofibers with multi-layered internal architectures (i.e., core-shell nanofibers or multi-layered nanofibers). Nanofiber diameter, composition, and mechanical properties, biocompatibility, and drug-loading capacity are among the tunable properties of electrospun PCL-based scaffolds. Scaffold properties including wettability, mechanical strength, and biocompatibility have been further enhanced with scaffold layering, surface modification, and coating techniques. In this article, we review nanofibrous electrospun PCL-based scaffold fabrication and the applications of PCL-based scaffolds in tissue engineering as reported in the recent literature.

Polymer Science↗

Scientific machine learning for closure models in multiscale problems: A review

Here, closure problems are omnipresent when simulating multiscale systems, where some quantities and processes cannot be fully prescribed despite their effects on the simulation's accuracy. Recently, scientific machine learning approaches have been proposed as a way to tackle the closure problem, combining traditional (physics-based) modeling with data-driven (machine-learned) techniques, typically through enriching differential equations with neural networks. This paper reviews the different reduced model forms, distinguished by the degree to which they include known physics, and the different objectives of a priori and a posteriori learning. The importance of adhering to physical laws (such as symmetries and conservation laws) in choosing the reduced model form and choosing the learning method is discussed. The effect of spatial and temporal discretization and recent trends toward discretization-invariant models are reviewed. In addition, we make the connections between closure problems and several other research disciplines: inverse problems, Mori-Zwanzig theory, and multi-fidelity methods. In conclusion, much progress has been made with scientific machine learning approaches for solving closure problems, but many challenges remain. In particular, the generalizability and interpretability of learned models is a major issue that needs to be addressed further.

97 MATHEMATICS AND COMPUTING↗

Developing A Custom-Built Metal Aerosol Processing Chamber: Analysis of Aerosol Coagulation at Low Humidities

We have developed an intermediate size (906 L) aerosol processing chamber, and this work reports on the design and initial characterization of dry aerosol experiments. Specifically, we are determining wall-loss and coagulation correction factors using the observed size distribution measurements for surrogates of common aerosol classes: sodium chloride, sucrose, and biomass burning aerosol smoke. Results show that, on average, sodium chloride, sucrose, and smoke wall-loss rates converge to similar values on relatively short time scales (< 1 h). The fitted coagulation correction factor, W C -1 , for smoke particles (1.23 ± 0.312), indicates that on average they adhere to each other more than sodium chloride (0.969 ± 0.524) and sucrose (1.16 ± 1.38). The relative uncertainty is high for the coagulation correction, but it is consistent with our Monte Carlo error analysis. This study lays the foundation for future experiments at elevated humidity and supersaturation conditions to characterize the influence of particle shape on coagulation and cloud parameters.

54 ENVIRONMENTAL SCIENCES↗

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

Preferred Practices Through a Project Template

In the realm of scientific software development, adherence to best practices is often advocated. However, implementing these can be challenging due to differing opinions. Certain aspects, such as software licenses and naming conventions, are typically left to the discretion of the development team. Our team has established a set of preferred practices, informed by, but not limited to, widely accepted best practices. These preferred practices are derived from our understanding of the specific contexts and user needs we cater to. To facilitate the dissemination of these practices among our team and foster standardization with collaborating domain scientists, we have created a project template for Python projects. This template serves as a platform for discussing the implementation of various decisions. This paper will succinctly delineate the components that constitute an effective project template and elucidate the advantages of consolidating preferred practices in such a manner.

Zhang, Chen↗

Recorder trace files of 91 built-in tests from three widely-used I/O libraries (Dec 24, 2024)

This dataset contains the Recorder trace files of 91 built-in tests from three widely-used I/O libraries. It was utilized in our IPDPS'25 paper, "VerifyIO: Verifying Adherence to Parallel I/O Consistency Semantics". The dataset can be used to reproduce the results presented in the paper and to conduct additional analyses

Wang, Chen [Lawrence Livermore National Laboratory↗

Regulations for Bat Protection in Mexico's Wind Farms

Wind energy development has expanded the fastest globally among all renewable sources during the last 20 years. However, wind farms have documented adverse impacts on bats, including mortality from collisions with turbine blades and disruptions to habitat and behavior. As the world's sixth most attractive economy for renewables, with 70 operating wind farms, Mexico and its bats now face escalating threats from the country's burgeoning wind industry. Despite this rapid growth, few studies have analyzed Mexico's regulatory framework to prevent, evaluate, and mitigate wind farm effects on bats. In this study, we reviewed Mexican laws and treaties that facilitate wind farm permitting, construction, operation, and decommissioning, and searched for guidelines that specifically address bat conservation. We found eight international pacts that promote wind power adoption along with three relevant articles in Mexico's Constitution. The General Law of Ecological Balance and Environmental Protection proved most pertinent for impact management. Supplementary guidelines from the Ministry of Environment and Natural Resources offer general strategies for evaluating wind farm impacts on bats, but adherence remains voluntary. Given expanding wind power investments across Mexico, we highlight the need for more stringent national standards that require preventative and corrective measures to protect bat populations. Tighter legislation and enforcement offer pathways toward environmentally sustainable wind energy development in Mexico.

17 WIND ENERGY↗

Assess The Water Resistance And Thermal Performance Of Pre-flashing Methods When Adding Continuous Insulation During Re-siding (AIRS)

Retrofitting existing buildings by adding continuous insulation during re-siding projects has become a popular method for enhancing energy efficiency, especially given the aging building stock and stricter energy codes. When properly integrated with existing window systems, continuous insulation can significantly improve thermal performance, but it also presents challenges related to water resistance and building envelope integrity. Research indicates that the interface between windows and wall assemblies is critical as improper installation or sealing can lead to water intrusion, materials deterioration, and energy loss. Moreover, studies show that fully integrating the windows with the insulation layer can reduce window heat loss by up to 40%, emphasizing the importance of optimizing window placement and sealing during retrofitting to ensure both energy efficiency and structural performance. In this study, we conducted experimental tests to evaluate the water penetration and thermal performance of two window types: an aluminum window with a 2-inch installation fin and a wood window, representing typical mid-20th century designs. Using the Heat, Air, and Humidity (HAM) chamber at Oak Ridge National Laboratory (ORNL), we assessed bulk water penetration and performed COMSOL analysis for thermal flux and examined the effectiveness of different pre-flashing methods, i.e., standard self-adhered flashing tape and high-performance flashing tape with low-expansion foam, to enhance water resistance. The results indicate that applying proper flashing techniques and moisture management strategies can mitigate these risks, improving the overall performance and durability of retrofitted buildings. Additionally, proper sealing during retrofitting is essential, as improper installation can lead to moisture issues that compromise both energy efficiency and structural integrity.

Shen, Zhenglai [ORNL]↗

Measuring Impact: Evaluating Thermal Zoning Simplification on Energy Efficiency Measures Analysis

Building Energy Modeling (BEM) is a versatile tool for designing, retrofitting, ensuring code compliance, obtaining certifications, qualifying for incentives, and enabling real-time building control. However, capturing all the details of building geometry for thermal zoning can be time-consuming, costly, and sometimes computationally challenging. As a result, modelers have been applying zoning simplification based on factors such as space functions and internal loads, as well as relying on their experience and judgment while adhering to zoning rules outlined in industry standards. Despite the prevalence of this common practice, a notable gap exists in the literature regarding studies quantifying the influence of simplified thermal zoning on the evaluation of Energy Efficiency Measures (EEMs). Recognizing this gap, this paper seeks to contribute to the field by enhancing the understanding of how the simplification of thermal zoning influences the evaluation of EEMs against a baseline design. The study utilized a medium office prototype model with a detailed floor plan featuring over 20 zones per floor covering diverse functional spaces with varying internal loads and occupancy schedules. A standard thermal zoning strategy outlined in ASHRAE Standard 90.1 Appendix G was employed as the simplified zoning method. This strategy condenses the zoning into a core zone and four perimeter zones per floor. It was compared with the detailed zoning approach, which involves one zone per space. Common Energy EEMs, such as enhanced envelope, high-efficiency appliances and equipment, and HVAC controls, were individually implemented and evaluated. The results indicate that the performance comparison between the two zoning methods varies depending on the type of measures considered. Basic measures, such as adding wall insulation, demonstrate similar energy impacts, while advanced HVAC control measures, such as static pressure reset, exhibit a more substantial difference that cannot be overlooked.

Xie, Jiarong↗

PVDeg: Enhancing Usability and AI-Driven Multi-Mechanism Degradation Modeling

PVDeg version 0.7.0, released in December 2025, introduced major enhancements to improve usability and performance. This update reorganized tutorials and tool notebooks to create a more intuitive experience, enabling users to easily follow and adapt workflows for their specific analyses. In addition to structural improvements, both the notebooks and core logic underwent significant optimization for efficiency, robustness, and style. These refinements were supported by new testing frameworks built on nbval and pytest, adherence to PEP8 standards, and extensive code refactoring, which collectively simplify onboarding for new developers. Looking ahead, version 0.8.0 will deliver advanced AI-driven capabilities. The primary focus is to further develop and automate the degradation workflow, designed to analyze PV module degradation across diverse locations and system configurations. By integrating large language models (LLMs) to scan literature and compile a comprehensive database of materials and degradation rates, this feature will enable modeling of multiple materials and mechanisms within a single, streamlined workflow. Users will be able to evaluate degradation impacts on different system architectures under varying environmental conditions, facilitating informed decisions on bill-of-materials optimization for specific deployment scenarios. These advancements position PVDeg as a powerful, user-friendly tool for accelerating PV reliability research and system design.

14 SOLAR ENERGY↗

Women in Nuclear Security: The United Arab Emirates Story

Historically in the United Arab Emirates, security personnel stationed at nuclear sites were typically men with military or policing backgrounds. Although these groups bring important, transferrable skills and experience to the nuclear security mission, some Emirati stakeholders recognize the increased benefit of a greater diversity of voices and backgrounds within the nuclear security team hierarchy. By recruiting from a wider range of disciplines and encouraging gender diversity, the security team could develop broader insight into security challenges, and a greater variety of perspectives could bring forth more innovative solutions. When aligning a diverse, multinational workforce with a common mission, all members of a security organization must fundamentally change their individual approaches to the work; the entire staff must be on the same page. This can be particularly challenging for some people who find it difficult to transition from a framework of beliefs because of past experiences based on prescriptive, exclusionary, hierarchical thought. Also, national cultural values are learned early, held deeply, and change slowly over the course of generations, and inherent biases rooted in these values can create barriers to the collective progress of a team. Creating a more open, diverse, and transparent culture for the team by accepting a unique, egalitarian, professional nuclear security culture that all members adhere to can be a challenging task for some. In this article, I share my experiences related to professional roadblocks, personal challenges, and lessons learned, particularly those regarding the empowerment of women in science and engineering, while developing and establishing the United Arab Emirates nuclear security program. I also discuss the support (and underrepresentation) of women, including those currently in critical leadership positions, and their careers in nuclear security.

Barakah Nuclear Power Plant↗

Testing convolutional neural network based deep learning systems: a statistical metamorphic approach

Machine learning technology spans many areas and today plays a significant role in addressing a wide range of problems in critical domains,i.e., healthcare, autonomous driving, finance, manufacturing, cybersecurity,etc. Metamorphic testing (MT) is considered a simple but very powerful approach in testing such computationally complex systems for which either an oracle is not available or is available but difficult to apply. Conventional metamorphic testing techniques have certain limitations in verifying deep learning-based models (i.e., convolutional neural networks (CNNs)) that have a stochastic nature (because of randomly initializing the network weights) in their training. In this article, we attempt to address this problem by using a statistical metamorphic testing (SMT) technique that does not require software testers to worry about fixing the random seeds (to get deterministic results) to verify the metamorphic relations (MRs). We propose seven MRs combined with different statistical methods to statistically verify whether the program under test adheres to the relation(s) specified in the MR(s). We further use mutation testing techniques to show the usefulness of the proposed approach in the healthcare space and test two CNN-based deep learning models (used for pneumonia detection among patients). The empirical results show that our proposed approach uncovers 85.71% of the implementation faults in the classifiers under test (CUT). Furthermore, we also propose an MRs minimization algorithm for the CUT, thus saving computational costs and organizational testing resources.

Computer Science↗