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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Exascale Programming Approaches for Accelerated Climate Modeling for Energy

The Accelerated Climate Modeling for Energy (ACME) program is a leading-edge climate and Earth system model designed to address the U.S. Department of Energy (DOE) mission needs. The ACME project involves collaboration between seven National Laboratories, the National Center for Atmospheric Research, four academic institutions, and one private-sector company. The ACME project funds ongoing efforts to ensure the model continues to make efficient use of DOE Leadership Computing Facilities (LCFs) in order to best address the three driving grand challenge science questions:Water cycle: How will more realistic portrayals of features important to the water cycle (resolution, clouds, aerosols, snowpack, river routing, land use) affect river flow and associated freshwater supplies at the watershed scale?Cryosphere systems: Could a dynamical instability in the Antarctic ice sheet be triggered within the next 40 years?Biogeochemistry: What are the contributions and feedbacks from natural and managed systems to current greenhouse gas fluxes, and how will those factors and associated fluxes evolve in the future?

Norman, Matthew↗
DOE OSTI2024

Development of Data Reporting Standards for High-Temperature Gas-cooled Reactor (HTGR) Nuclear Energy University Program (NEUP) Thermal-Fluid Experiments

Since 2009, the U.S. Department of Energy (DOE) Office of Nuclear Energy's Nuclear Energy University Program (NEUP) has been at the forefront of nuclear research, specifically concentrating on advancing high-temperature gas-cooled reactor (HTGR) technologies. By Fiscal Year 2023, NEUP has authorized 35 projects dedicated to HTGR research, each contributing significantly to the enhancement of our understanding of this technology. The outcomes of these diverse projects have been disseminated through final NEUP reports, peer-reviewed journal articles, and presentations at academic conferences, forming a comprehensive tapestry of knowledge. Despite the substantial value of these findings, their dissemination has been fragmented, posing challenges for accessibility to researchers and policymakers and leading to underutilization of DOE investments. Recognizing this critical gap and its potential consequences for the future of nuclear research, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program conducted an extensive survey of completed and ongoing HTGR NEUP projects. This survey enabled the compilation of crucial data, resulting in the development of a specialized public-access database tailored for computational fluid dynamics and system code validation, specifically designed for HTGR applications. However, the data collection process revealed a significant challenge in central data organization due to individual researchers from different institutes employing varying logics and preferences for recording and documenting experimental data. Consequently, an urgent need has been identified to establish a standardized reporting format for HTGR experimental projects. Addressing this issue is essential for enhancing collaboration, maximizing the impact of DOE investments, and ensuring the seamless advancement of HTGR technologies in nuclear research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Systems, methods, and media for high dynamic range imaging using single-photon and conventional image sensor data

In accordance with some embodiments, systems, methods, and media for high dynamic range imaging using single-photon and conventional image sensor data are provided. In some embodiments, the system comprises: first detectors configured to detect a level of photons proportional to incident photon flux; second detectors configured to detect arrival of individual photons; a processor programmed to: receive, from the first detectors, first values indicative of photon flux from a scene with a first resolution; receive, from the second detectors, second values indicative of photon flux from the scene with a lower resolution; provide a first encoder of a trained machine learning model first flux values based on the first values, provide the second encoder of the model second flux values; receive, as output, values indicative of photon flux from the scene; and generate a high dynamic range image based on the third plurality of values.

Gutierrez Barragan, Felipe↗
DOE OSTI2017

Bifunctional application of lithium ferrites (Li 5 FeO 4 and LiFeO 2 ) during carbon monoxide (CO) oxidation and chemisorption processes. A catalytic, thermogravimetric and theoretical analysis

The CO oxidation and subsequent CO 2 chemisorption processes were evaluated using two lithium ferrites, Li 5 FeO 4 and LiFeO 2 , as possible catalytic and captor materials. The analysis of the bifunctional process was dynamic and isothermally evaluated using catalytic and thermogravimetric techniques, while solid final products were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and temperature programmed desorption (TPD). These experiments were performed using a CO-O 2 mixture or only CO as gas flows. In addition, different ab initio thermodynamic calculations were performed to elucidate the theoretical viability of these processes. Thermogravimetric and catalytic results clearly showed that both lithium ferrites were able to perform the CO oxidation and CO 2 chemical capture. The efficiency and reaction mechanism varied as a function of the lithium ferrite (Li 5 FeO 4 or LiFeO 2 ), gas mixture and temperature. As it would be expected, Li 5 FeO 4 sample presented better chemisorption properties than LiFeO 2 , regardless the gas mixture employed (CO or CO+O 2 ). Moreover, catalytic tests showed that the reaction process was produced even in the oxygen absence. Here, in such a case, both lithium ferrites released the oxygen necessary for the oxidation process with a consequent iron reduction, as it was observed by XRD. Based on the obtained experimental and theoretical results, reaction mechanisms were proposed for each lithium ferrite into this bifunctional process. Finally, the best catalytic behavior was obtained with the Li 5 FeO 4 -CO-O 2 system, where high CO conversions (50–75%) were observed between 500–650 °C and T > 800 °C. Also according to TGA results, this system at T > 700 °C presented the highest ability for capture the CO 2 previously formed during the CO oxidation process (~45%).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

A tri-level distribution locational marginal price-based demand response framework

Here, in this paper, we propose a tri-level, nested, two-stage price-based demand response (PBDR) framework that considers distribution locational marginal price (DLMP) as DR enabler between load-serving entities (LSE), demand response providers (DRPs), and customers in the day-ahead distribution market. It enables LSE and customer interactions by using multiple DRPs, positioned in-between, and independently optimizes their objectives. The problem is formulated using linear power flow with approximated power losses and its application in DLMP as DR pricing. The tri-level problem is solved using a nested reformulation & decomposition (R&D) method and tested on the real Indian-108 bus distribution system under various dynamic pricings. Further, the temporal–spatial variations in DLMPs are assessed using fairness criteria. Numerical analyses demonstrate that DLMP applications can effectively improve economic efficiency, and transparency in DR programs valuation with a favorable fairness margin. The results show that DLMP as DR pricing signal induces (0-2) % variation in DLMP for DR participation up to 10 %. Further, it gives over 90 % fairness over temporal–spatial variation for all the customers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

The role of vascular niche and endothelial cells in organogenesis and regeneration

Highlights: • The vascular niche creates a permissive environment that realize developmental or regenerative programs. • The proximity between endothelium and cells of organs suggests a role of endothelial cells in the organs maturation. • Organs provide cues shaping vascular network structure. The term vascular niche indicate the physical and biochemical microenvironment around blood vessel where endothelial cells, pericytes, and smooth muscle cells organize themselves to form blood vessels and release molecules involved in the recruitment of hematopoietic stem cells, endothelial progenitor cells and mesenchymal stem cells. The vascular niche creates a permissive environment that enables different cell types to realize their developmental or regenerative programs. In this context, the proximity between the endothelium and the new-forming cellular components of organs suggests an essential role of endothelial cells in the organs maturation. Dynamic interactions between specific organ endothelial cells and different cellular conponents are crucial for different organ morphogenesis and function. Conversely, organs provide cues shaping vascular network structure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Dynamics of soft Nanomaterials captured by transmission electron microscopy in liquid water

In this paper we present in situ transmission electron microscopy (TEM) of soft, synthetic nanoparticles with a comparative analysis using conventional TEM methods. This comparison is made with the simple aim of describing what is an unprecedented example of in situ imaging by TEM. However, we contend the technique will quickly become essential in the characterization of analogous systems, especially where dynamics are of interest in the solvated state. In this case, particles were studied which were obtained from the direct polymerization of an oxaliplatin analog, designed for an ongoing program in novel chemotherapeutic delivery systems. The resulting nanoparticles provided sufficient contrast for facile imaging in situ, and point toward key design parameters that enable this new characterization approach for organic nanomaterials. We describe the preparation of the synthetic micellar nanoparticles to- gether with their characterization in liquid water.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2024

Optimal Control of SOEC-Based Hydrogen Production Systems for Demand Response Using Deep Reinforcement Learning in Smart Grids

Solid oxide electrolysis cell (SOEC) hydrogen production technology can range in size from small, appliance-size equipment to large-scale, central production facilities that can be tied directly to renewable or non-greenhouse-gas-emitting forms of electricity production, making it an ideal resource for demand response (DR). The SOEC hydrogen production system is a complex integrated system that encompasses fluid dynamics, electrical dynamics, and electrochemical and thermal dynamics, all of which involve non-linearity and non-convexity. Proper control of the SOEC hydrogen production system is crucial to enable its participation in the DR program. Here, to overcome the difficulty of designing an explicit control law for such nonlinear systems with nonconvex optimization features in DR applications, deep reinforcement learning (DRL) is explored to achieve the optimal control of the SOEC system for DR participation. Specifically, a twin delayed deterministic policy gradient (TD3) control framework is applied to achieve optimal response performance during DR events by considering power tracking error and hydrogen production efficiency with a suitable reward function. Two case studies with grid connections for tracking different DR commands were investigated. The first case study involved operating conditions reaching the boundaries, while the second involved operating conditions within the boundaries. The results showed that the proposed DRL-based control for SOEC can track the DR signal in a timely manner while maintaining high energy efficiency.

08 HYDROGEN↗
DOE OSTI2012

Ethanol Distribution, Dispensing, and Use: Analysis of a Portion of the Biomass-to-Biofuels Supply Chain Using System Dynamics

The Energy Independence and Security Act of 2007 targets use of 36 billion gallons of biofuels per year by 2022. Achieving this may require substantial changes to current transportation fuel systems for distribution, dispensing, and use in vehicles. The U.S. Department of Energy and the National Renewable Energy Laboratory designed a system dynamics approach to help focus government action by determining what supply chain changes would have the greatest potential to accelerate biofuels deployment. The National Renewable Energy Laboratory developed the Biomass Scenario Model, a system dynamics model which represents the primary system effects and dependencies in the biomass-to-biofuels supply chain. The model provides a framework for developing scenarios and conducting biofuels policy analysis. This paper focuses on the downstream portion of the supply chain-represented in the distribution logistics, dispensing station, and fuel utilization, and vehicle modules of the Biomass Scenario Model. This model initially focused on ethanol, but has since been expanded to include other biofuels. Some portions of this system are represented dynamically with major interactions and feedbacks, especially those related to a dispensing station owner's decision whether to offer ethanol fuel and a consumer's choice whether to purchase that fuel. Other portions of the system are modeled with little or no dynamics; the vehicle choices of consumers are represented as discrete scenarios. This paper explores conditions needed to sustain an ethanol fuel market and identifies implications of these findings for program and policy goals. A large, economically sustainable ethanol fuel market (or other biofuel market) requires low end-user fuel price relative to gasoline and sufficient producer payment, which are difficult to achieve simultaneously. Other requirements (different for ethanol vs. other biofuel markets) include the need for infrastructure for distribution and dispensing and widespread use of high ethanol blends in flexible-fuel vehicles.

02 PETROLEUM↗
DOE OSTI2014

Load Balancing Scientific Applications

The largest supercomputers have millions of independent processors, and concurrency levels are rapidly increasing. For ideal efficiency, developers of the simulations that run on these machines must ensure that computational work is evenly balanced among processors. Assigning work evenly is challenging because many large modern parallel codes simulate behavior of physical systems that evolve over time, and their workloads change over time. Furthermore, the cost of imbalanced load increases with scale because most large-scale scientific simulations today use a Single Program Multiple Data (SPMD) parallel programming model, and an increasing number of processors will wait for the slowest one at the synchronization points. To address load imbalance, many large-scale parallel applications use dynamic load balance algorithms to redistribute work evenly. The research objective of this dissertation is to develop methods to decide when and how to load balance the application, and to balance it effectively and affordably. We measure and evaluate the computational load of the application, and develop strategies to decide when and how to correct the imbalance. Depending on the simulation, a fast, local load balance algorithm may be suitable, or a more sophisticated and expensive algorithm may be required. We developed a model for comparison of load balance algorithms for a specific state of the simulation that enables the selection of a balancing algorithm that will minimize overall runtime.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: Coordinate Multiscale FeCrAl Modeling

Since the events at the Fukushima-Daiichi nuclear power plant in March 2011 significant research has unfolded at national laboratories, universities and other institutions into alternative materials that have potential enhanced ac- cident tolerance when compared to traditional UO2 fuel zircaloy clad fuel rods. One of the potential replacement claddings are iron-chromium-alunimum (FeCrAl) alloys due to their increased oxidation resistance [1–4] and higher strength [1, 2]. While the oxidation characteristics of FeCrAl are a benefit for accident tolerance, the thermal neu- tron absorption cross section of FeCrAl is about ten times that of Zircaloy. This neutronic penalty necessitates thinner cladding. This allows for slightly larger pellets to give the same cold gap width in the rod. However, the slight increase in pellet diameter is not sufficient to compensate for the neutronic penalty and enriching the fuel beyond the current 5% limit appears to be necessary [5]. Current estimates indicate that this neutronic penalty will impose an increase in fuel cost of 15-35% [1, 2]. In addition to the neutronic disadvantage, it is anticipated that tritium release to the coolant will be larger because the permeability of hydrogen in FeCrAl is about 100 times higher than in Zircaloy [6]. Also, radiation-induced hardening and embrittlement of FeCrAl need to be fully characterized experimentally [7]. Due to the aggressive development schedule for inserting some of the potential materials into lead test assemblies or rods by 2022 [8] multiscale multiphysics modeling approaches have been used to provide insight into these the use of FeCrAl as a cladding material. The purpose of this letter report is to highlight the multiscale modeling effort for iron-chromium-alunimum (FeCrAl) cladding alloys as part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program through its Accident Tolerant Fuel (ATF) High Impact Problem (HIP). The approach taken throughout the HIP is to utilize lower length scale approaches (e.g., density functional theory, cluster dynamics, rate theory, phase field, and Visco-Plastic- Self-Consistent (VPSC)) to develop more physically informed models at the engineering scale for use in the BISON [9] fuel performance code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Rattlesnake User's Manual

Rattlesnake is a combined-environments, multiple input/multiple output control system for dynamic excitation of structures under test. It provides capabilities to control multiple responses on the part using multiple exciters using various control strategies. Rattlesnake is written in the Python programming language to facilitate multiple input/multiple output vibration research by allowing users to prescribe custom control laws to the controller. Rattlesnake can target multiple hardware devices, or even perform synthetic control to simulate a test virtually. Rattlesnake has been used to execute control problems with up to 200 response channels and 12 drives. This document describes the functionality, architecture, and usage of the Rattlesnake controller to perform combined environments testing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Rattlesnake User's Manual (V.3)

Rattlesnake is a combined-environments, multiple input/multiple output control system for dynamic excitation of structures under test. It provides capabilities to control multiple responses on the part using multiple exciters using various control strategies. Rattlesnake is written in the Python programming language to facilitate multiple input/multiple output vibration research by allowing users to prescribe custom control laws to the controller. Rattlesnake can target multiple hardware devices, or even perform synthetic control to simulate a test virtually. Rattlesnake has been used to execute control problems with up to 200 response channels and 24 shaker drives. This document describes the functionality, architecture, and usage of the Rattlesnake controller to perform combined environments testing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Performance improvement and human resources transition management in D and D projects - 15440

Power generation and other nuclear facilities production is mainly characterized by stable working environment, with continuous efforts for improvement based on previous achievements, constant workload, foreseeable and established organizational hierarchy; and generation of cash. In contrary to normal production - when phasing down the facility for final shutdown, decommissioning and dismantling - one has to manage a new, highly dynamic working environment, with decreasing workload, new skills required; and consumption of cash. The key to successful transition is to recognize the need for establishing an explicit performance improvement program with an effective change management process in order to address this profound evolution as early as possible in the project. AREVA owns and operates large nuclear material processing facilities. This includes the responsibility for their end of life up to final Decommissioning and Dismantling (D and D). Faced with this transitional challenge, AREVA took example from well-known management methods (Lean Management, 6 Sigma, TPM...) successfully applied by the non-nuclear production industry with the corresponding philosophy of Operational Excellence. These methods were adapted to the specifics of nuclear decommissioning projects. Furthermore, specific computerized tools were developed to assist managers in implementing measures for re-deploying, re-training and re-qualifying personnel as well as re-organizing the work structure while maintaining safety and social consensus. Significant improvements in the dismantling works as well as in the management of generated waste were achieved early after start of the implementation of the performance improvement programs. (authors)

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

Enabling Dynamic Probabilistic Risk Assessment of Physical Security Using EMRALD and MAAP (Presentation)

The optimization of physical security in nuclear power plants requires sophisticated methodologies that integrate operator actions and plant behavior through advanced simulation tools. Idaho National Laboratory has developed the Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF) methodology, an approach that integrates force-on-force simulations, dynamic probabilistic risk assessment, and thermal hydraulics modeling to enhance security planning while reducing costs. A reduced order model for thermal hydraulic simulations performed by the Modular Accident Analysis Program (MAAP) was developed to evaluate reactor core behavior during attack scenarios. MAAP simulations are computationally intensive and must be run in a secure environment, complicating analysis and validation. By pre-computed scenario outcomes for a small number of modified parameters, the reduced order model significantly decreases the computational cost and enables offsite review of the results.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

The modern temperature-accelerated dynamics approach

Accelerated molecular dynamics (AMD) is a class of MD-based methods used to simulate atomistic systems in which the metastable state-to-state evolution is slow compared with thermal vibrations. Temperature-accelerated dynamics (TAD) is a particularly efficient AMD procedure in which the predicted evolution is hastened by elevating the temperature of the system and then recovering the correct state-to-state dynamics at the temperature of interest. TAD has been used to study various materials applications, often revealing surprising behavior beyond the reach of direct MD. This success has inspired several algorithmic performance enhancements, as well as the analysis of its mathematical framework. Recently, these enhancements have leveraged parallel programming techniques to enhance both the spatial and temporal scaling of the traditional approach. Here, we review the ongoing evolution of the modern TAD method and introduce the latest development: speculatively parallel TAD.

36 MATERIALS SCIENCE↗
DOE OSTI2011

X-Band Photoinjector Beam Dynamics

SLAC is studying the feasibility of using an X-band RF photocathode gun to produce low emittance bunches for applications such as a mono-energetic MeV {gamma} ray source (in collaboration with LLNL) and a photoinjector for a compact FEL. Beam dynamics studies are being done for a configuration consisting of a 5.5-cell X-band gun followed by several 53-cell high-gradient X-band accelerator structures. A fully 3D program, ImpactT, is used to track particles taking into account space charge forces, short-range longitudinal and transverse wakefields, and the 3D rf fields in the structures, including the quadrupole component of the couplers. The effect of misalignments of the various elements, including the drive-laser, gun, solenoid and accelerator structures, are evaluated. This paper presents these results and estimates of the expected bunch emittance vs cathode gradient, and the effects of mixing between the fundamental and off-frequency longitudinal modes. An X-band gun at SLAC has been shown to operate reliably with a 200 MV/m acceleration gradient at the cathode, which is nearly twice the 115 MV/m acceleration gradient in the LCLS gun. The higher gradient should roughly balance the space charge related transverse emittance growth for the same bunch charge but provide a 3-4 times shorter bunch length. The shorter length would make the subsequent bunch compression easier and allow for a more effective use of emittance exchange. Such a gun can also be used with an X-band linac to produce a compact FEL or g ray source that would require rf sources of only one frequency for beam generation and acceleration. The feasibility of using an X-band rf photocathode gun and accelerator structures to generate high quality electron beams for compact FELs and g ray sources is being studied at SLAC. Results from the X-band photoinjector beam dynamics studies are reported in this paper.

43 PARTICLE ACCELERATORS↗