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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cognitive analysis of metabolomics data for systems biology

Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most available platforms have been developed for biomedical researchers, but new NLP tools are emerging for biologists in other fields and an important example is metabolomics. NLP provides literature-based contextualization of metabolic features that decreases the time and expert-level subject knowledge required during the prioritization, identification and interpretation steps in the metabolomics data analysis pipeline. Here, we describe and demonstrate four workflows that combine metabolomics data with NLP-based literature searches of scientific databases to aid in the analysis of metabolomics data and their biological interpretation. Additionally, the four procedures can be used in isolation or consecutively, depending on the research questions. The first, used for initial metabolite annotation and prioritization, creates a list of metabolites that would be interesting for follow-up. The second workflow finds literature evidence of the activity of metabolites and metabolic pathways in governing the biological condition on a systems biology level. The third is used to identify candidate biomarkers, and the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in common. The protocol can take 1–4 h or more to complete, depending on the processing time of the various software used.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A Study of Geodesic Distance Kernel on an Integrated GPU

Graphics processing units (GPUs) are commonly used for graphics and general-purpose (GPGPU) computation. Currently, NVIDIA’s GPUs, through its CUDA framework for GPGPU programming, are ubiquitous for highperformance computing. Another class of GPUs, with a central processing unit (CPU) and a GPU integrated on the same chip, is commonly used in laptops, desktop computers, and low-power servers. While they are not designed to outperform discrete GPUs due to the power, area, and thermal constrains [1], there is a need to better understand the performance of a processor with an integrated GPU for floating-point intensive applications. The study helps us better understand the characteristics of hardware and software development tools, and the benefit of offloading such applications to an integrated GPU.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Parallel-Processed Multi-junction Perovskite Solar Cells (Final Technical Report)

This report consolidates the findings from this Department of Energy supported project, which aimed to advance the manufacturing of high-efficiency perovskite photovoltaics. To facilitate the processing of tandem devices, and perovskite single-junction and multi-junction devices more generally, the project team developed a lamination process to integrate the subcells and cells, decoupling the processing from the restrictive requirements of serial manufacturing. The lamination approach enables independent and precise tailoring of interface properties for stability and performance.

14 SOLAR ENERGY↗
DOE OSTI2021

Cloud Process Coupling and Time Integration in the E3SM Atmosphere Model

Abstract In this study, we find significant sensitivity to the choice of time step for the Energy Exascale Earth System Model's atmospheric component, leading to large decreases in the magnitude of cloud forcing when the time step is reduced to 10 s. Reducing the time step size for the microphysics increases precipitation, leading to a drying of the atmosphere and an increase in surface evaporation. This effect is amplified when the microphysics is substepped together with other cloud physics processes. Coupling the model's dynamics and physics more frequently reduces cloud fraction at lower altitudes, while producing more cloud liquid at higher altitudes. Reducing the deep convection time step also reduces low cloud mass and cloud fraction. Together, these results suggest that cloud physics in a global circulation model can depend strongly on time step and, in particular, on the frequency with which cloud‐related processes are coupled with each other and with the model dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Next-generation electronics by co-design with chalcogenide materials

As Moore’s law approaches its limits, chalcogenides offer a promising route to next-generation computing and sensing, thanks to their topological, magnetoelectric, excitonic, and spintronic properties. Yet the same traits that make them appealing, e.g., exotic properties at monolayer thickness, clean van der Waals interfaces, and strong many-body effects, also heighten sensitivity to fabrication, hindering translation into scalable devices. Progress is further constrained by fragmented knowledge across synthesis, processing, and integration, and by the lack of systematic links between fabrication parameters and performance metrics. This Perspective examines key obstacles in controlling chalcogenide heterostructures and stresses the need for an integrated co-design framework, uniting materials growth, processing, and device architecture to accelerate practical technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Thermodynamic and experimental assessment of proton conducting solid oxide fuel cells with internal methane steam reforming

Operating proton conducting solid oxide fuel cells (H-SOFCs) with hydrocarbon as fuel remains a challenge because of the instability of the anode and electrolyte materials in a CO 2 /H 2 O-containing atmosphere and the catalytic activity and coking resistance of the anode for direct oxidation of hydrocarbons. Therefore, in this paper, the steam reforming of methane (SRM, an endothermic process) is integrated into the H-SOFCs (fuel cell process, an exothermic process) for internally converting hydrocarbon to hydrogen and increasing energy efficiency of H-SOFCs. Moreover, a proton-conducting zirconate oxide (BaZr 0.8 Y 0.2 O 3 , BZY), which is stable in a CO 2 /H 2 O-containing atmosphere, is applied as an electrolyte and anode material of H-SOFCs. The operation of BZY-based H-SOFCs with internal SRM is assessed by thermodynamic calculation and experiments for the first time. The catalytic activity and coking resistance of the Ni-BZY anode for SRM are investigated thermodynamically and experimentally. Finally, the results demonstrate that the Ni-BZY anode possesses reasonable catalytic activity as well as good coking resistance for SRM at a temperature as low as 550 °C. Then, the electrochemical performance and durability of H-SOFCs operated with internal SRM are comprehensively studied from 550 °C to 700 °C.

25 ENERGY STORAGE↗
DOE OSTI2024

Integrated top-down process and voxel-based microstructure modeling for Ti-6Al-4V in laser wire direct energy deposition process

Laser-wire metal additive manufacturing (AM) is one of the ideal direct energy deposition (DED) processes for creating large-scale parts with a medium level of complexity. However, the DED process involves complex thermal signatures and wide length scales making the fabrication of realistic AM components and part qualification often reliant on experimental trial-and-error optimization. While experimental measurements over the full volume of a part are valuable and necessary, measuring the entire area of a part is significantly laborious and practically infeasible, particularly for large parts in terms of cost and rapid qualification. Therefore, in this work, we developed an effective thermal and microstructure modeling framework based on the Johnson–Mehl-Avrami-Kolmogorov (JMAK) and Koistinen & Marburger (KM) models through a top-down approach that considers plate distortion-affected thermal profiles. A voxel-by-voxel simulation method is used to predict individual phase fractions of Ti-6Al-4 V. The predicted results were validated through detailed metallurgical measurements. A combined voxel-by-voxel approach with a sparse data reconstruction technique produced a near-perfect reconstruction of the original data. This approach anticipates a significant reduction in data points and computation time and resources. Lastly, we conclude with potential extensions of this work to other modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fire as a fundamental ecological process: Research advances and frontiers

Fire is a powerful ecological and evolutionary force that regulates organismal traits, population sizes, species interactions, community composition, carbon and nutrient cycling and ecosystem function. It also presents a rapidly growing societal challenge, due to both increasingly destructive wildfires and fire exclusion in fire–dependent ecosystems. As an ecological process, fire integrates complex feedbacks among biological, social and geophysical processes, requiring coordination across several fields and scales of study. Here, we describe the diversity of ways in which fire operates as a fundamental ecological and evolutionary process on Earth. We explore research priorities in six categories of fire ecology: (a) characteristics of fire regimes, (b) changing fire regimes, (c) fire effects on above–ground ecology, (d) fire effects on below–ground ecology, (e) fire behaviour and (f) fire ecology modelling. We identify three emergent themes: the need to study fire across temporal scales, to assess the mechanisms underlying a variety of ecological feedbacks involving fire and to improve representation of fire in a range of modelling contexts. As fire regimes and our relationships with fire continue to change, prioritizing these research areas will facilitate understanding of the ecological causes and consequences of future fires and rethinking fire management alternatives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Multiscale Modeling of Carbon Fiber Reinforced Polymer (CFRP) for Integrated Computational Materials Engineering Process

In this work, a multiscale modeling framework for CFRP is introduced to study hierarchical structure of CFRP. Four distinct scales are defined: nanoscale, microscale, mesoscale, and macroscale. Information at lower scales can be passed to higher scale, which is beneficial for studying effect of constituents on macroscale part’s mechanical property. This bottom-up modeling approach enables better understanding of CFRP from finest details. Current study focuses on microscale and mesoscale. Representative volume element is used at microscale and mesoscale to model material’s properties. At microscale, unidirection CFRP (UD) RVE is used to study properties of UD. The UD RVE can be modeled with different volumetric fraction to encounter non-uniform fiber distribution in CFRP part. Such consideration is important in modeling uncertainties at microscale level. Currently, we identified volumetric fraction as the only uncertainty parameters in UD RVE. To measure effective material properties of UD RVE, periodic boundary conditions (PBC) are applied to UD RVE to ensure convergence of obtained properties. Properties of UD is directly used at mesoscale woven RVE modeling, where each yarn is assumed to have same properties as UD. Within woven RVE, there can be many potential uncertainties parameters to consider for a physical modeling of CFRP. Currently, we will consider fiber misalignment within yarn and angle between wrap and weft yarns. PBC is applied to woven RVE to calculate its effective material properties. The effect of uncertainties are investigated quantitatively by Gaussian process. Preliminary results of UD and Woven study are analyzed for efficacy of the RVE modeling. This work is considered as the foundation for future multiscale modeling framework development for ICME project.

Composite, ICME, Multiscale Modeling↗
DOE OSTI2019

Integrating Smart Plug and Process Load Controls into Energy Management Information System Platforms: A Landscaping Study

Plug and process loads (PPLs) already represent a significant fraction of total energy use in commercial buildings and their contribution is expected to increase in the future. Although plug-in devices are typically not monitored or controlled, new wireless technologies are being developed that can provide these functions. These 'smart' outlets collect data from connected devices and transmit it to cloud services for energy measurement, tracking, and control purposes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Potential Integration Between Residual Biogenic Process Resources and Green Hydrogen [Slides]

This presentation highlights previously published analysis on the use of off-gases from biomass pyrolysis processes towards energy utilities. The potential for use of pyrolysis off-gases in existing steam reformers for green hydrogen production is assessed. Impacts on various operations within a steam reforming system (with natural gas as the primary base feed) from the introduction of pyrolysis off-gases in various proportions are quantified to assess the feasibility of reusing existing industrial facilities with renewably sourced gases.

09 BIOMASS FUELS↗
DOE OSTI2017

INTEGRATION OF COST MODELS AND PROCESS SIMULATION TOOLS FOR OPTIMUM COMPOSITE MANUFACTURING PROCESS

Manufacturing cost of resin transfer molded composite parts is significantly influenced by the cycle time, which is strongly related to the time for both filling and curing of the resin in the mold. The time for filling can be optimized by various injection strategies, and by suitably reducing the length of the resin flow distance during the injection. The curing time can be reduced by the usage of faster curing resins, but it requires a high pressure injection equipment, which is capital intensive. Predictive manufacturing simulation tools that are being developed recently for composite materials are able to provide various scenarios of processing conditions virtually well in advance of manufacturing the parts. In the present study, we integrate the cost models with process simulation tools to study the influence of various parameters such as injection strategies, injection pressure, compression control to minimize high pressure injection, resin curing rate, and demold time on the manufacturing cost as affected by the annual part volume. A representative automotive component was selected for the study and the results are presented in this paper

42 ENGINEERING↗
DOE OSTI2025

Embedded Sensing in Additive Manufacturing Metal and Polymer Parts: A Comparative Study of Integration Techniques and Structural Health Monitoring Performance

This study presents a comparative evaluation of post-process sensor integration in additively manufactured (AM) metal and the in-situ process for polymer structures for structural health monitoring (SHM), with an emphasis on embedded sensors. Geometrically identical specimens were fabricated using copper via metal fused filament fabrication (FFF) and PLA via polymer FFF, with piezoelectric transducers (PZTs) inserted into internal cavities to assess the influence of material and placement on sensing fidelity. Mechanical testing under compressive and point loads generated signals that were transformed into time–frequency spectrograms using a Short-Time Fourier Transform (STFT) framework. An engineered RGB representation was developed, combining global amplitude scaling with an amplitude-envelope encoding to enhance contrast and highlight subtle wave features. These spectrograms served as inputs to convolutional neural networks (CNNs) for classification of load conditions and detection of damage-related features. Results showed reliable recognition in both copper and PLA specimens, with CNN classification accuracies exceeding 95%. Embedded PZTs were especially effective in PLA, where signal damping and environmental sensitivity often hinder surface-mounted sensors. This work demonstrates the advantages of embedded sensing in AM structures, particularly when paired with spectrogram-based feature engineering and CNN modeling, advancing real-time SHM for aerospace, energy, and defense applications.

additive manufacturing↗
DOE OSTI2018

Demonstration of Chemical Decladding and Disposition Options for Non-Al Clad Fuels in H-Canyon

Aqueous disposition of non-Al clad fuels was studied in order to determine if H-Canyon would be a viable disposition option for this type of L-Basin fuel. A review of the L-Basin fuel types and its condition was done suggesting two major cladding types, Zircaloy and 304L stainless steel needed to be studied. Dissolution flowsheets options were reviewed. Sulfex and Zirflex processes were chosen as best for H-Canyon integration. Both process flowsheets were demonstrated on a lab scale to determine decladding rate, and off-gas and waste production. The resulting data suggested decladding in H-Canyon was an option but dissolver corrosion as well as off-gas and waste generation needed to be addressed. Small scale dissolution in a hot cell of smaller damaged fuel is a viable option with the flowsheets tested.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Modular Biomass Gasification for Co-Production of Hydrogen and Power

The overall goal of this project was to demonstrate a novel process-intensified and modular Combined Hydrogen, Heat and Power (CH 2 P) production technology, targeting commercial scales of 5-to-10-megawatt electric (MWe) equivalent of hydrogen (H 2 ). The process technology integrates a novel adaptation of the steam-iron process to produce high purity H 2 from gasification of biomass and biomass blends with a compression-ready carbon dioxide (CO 2 ) stream, enabling significant progress towards achieving $1 per kilogram (kg) cost for clean H 2 .

08 HYDROGEN↗
DOE OSTI2021

Rapidly ramp cryogenic air separation unit without loss of O2 product purity—application for low-carbon fossil-fuel plants

The rapid integration of intermittent renewable sources into the electricity grid is driving the need for low-carbon, fossil-fuel power plant capable of rapid ramping. Therefore, a cryogenic air separation unit (ASU) as part of low-carbon, fossil-fuel power plant should be capable of rapid ramping. However, highly integrated and nonlinear processes of the ASU would significantly restrict this rapid ramping. To overcome this fundamental issue, we study the basic dynamic process of a state-of-the-art double-column ASU. A flow-driven dynamic model was established in Aspen Plus Dynamics, assuming perfect flow controls, to capture the basic dynamics of ramping ASU. We find the vapor-liquid counter-current flow structure in the low-pressure column is critical to the air separation when rapidly ramping the ASU. This flow structure is established based on a complicated heat integration process. It is simplified as an apparent counter-current heat transfer process in this work, which greatly reduces the complexity for studying the dynamics of ASU. For keeping this basic flow structure, the heat integration is maintained as its heat duty follows the ASU load, through several basic feed-forward and feed-back controllers on the critical stream flowrates. Moreover, we find a fundamental issue of mismatched dynamics in the low-pressure column, resulting in a significant loss of O2 product purity when rapidly ramping down the ASU and an obvious fluctuation of O2 product purity. Based on these explorations, we propose a basic control method for rapidly ramping the ASU without loss of O2 product purity. Results show the ASU basic dynamic process successfully ramps at a rate up to 10%/min (40-100% load) while maintaining the O2 product purity within 95.2-95.6 mol%.

Cheng, Mao↗
DOE OSTI2023

Oak Ridge National Laboratory Security by Design: A Plant Design and Component-Based Approach to Technical Solutions to Insider and Outsider Threat

Security costs for nuclear reactors have been shown to rise over the lifecycle of a nuclear facility as new threats, security weaknesses, and the generic threat profile of the plant location change over time. This paper conducts a review of the technological gaps that currently exist in Security by Design (SeBD) based on the literature available and attempts to close those gaps through proposing technological constructs and processes that can integrate safety and security in the design process of a plant, with a primary focus on SMR technology. Under the new modular and mass manufacturing regime, where plant designs attempt to reduce costs with potential economies of scale and modular construction, the current SeBD definitions focusing on state level regulators are not considered adequate since the licensing stage is often too late in the design process to integrate the true cost savings of SeBD. Thus, this paper attempts to remedy the current logic in order to allow for continuous implementation of security alongside the development of the safety concept for the plant. If adopted within the design process the establishment of this type of technology will allow for a technological ecosystem to evolve that will imbed security concepts into the physical design of the components of the plant.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗