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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

UMass 2-Body WEC Techno-Economic Assessment

The University of Massachusetts (UMass) is developing a 2-body wave energy converter (WEC) device that is converting mechanical power into electricity using a mechanical motion rectifier that allows the system to couple to a flywheel. UMass has completed numerical modeling, wave tank testing, and PTO sub-system testing and needed assistance in developing a techno-economic model to enable optimization of their topology, comparison to a generic heaving point absorber topology, and guide the next steps in their development efforts. The core objective was to develop a techno-economic approach and modeling tool that allows benchmarking of the two topologies across a wide range of scales to evaluate their respective competitiveness in different application spaces. This data includes the final report as well as a supporting spreadsheet containing the data produced for this report.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Power market models for the clean energy transition: State of the art and future research needs

As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero-carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Viscosity Meaurement Technique for Metal Fuels

Metallic fuels have exceptional transient behavior, excellent thermal conductivity, and a more straightforward reprocessing path, which does not separate out pure plutonium from the process stream. Fabrication of fuel containing minor actinides and rare earth (RE) elements for irradiation tests, for instance, U-20Pu-3Am-2Np-1.0RE-15Zr samples at the Idaho National Laboratory, is generally done by melt casting in an inert atmosphere. For the design of a casting system and further scale up development, computational modeling of the casting process is needed to provide information on melt flow and solidification for process optimization. Therefore, there is a need for melt viscosity data, the most important melt property that controls the melt flow. The goal of the project was to develop a measurement technique that uses fully sealed melt sample with no Americium vapor loss to determine the viscosity of metallic melts and at temperatures relevant to the casting process. The specific objectives of the project were to: develop mathematical models to establish the principle of the measurement method, design and build a viscosity measurement prototype system based on the established principle, and calibrate the system and quantify the uncertainty range. The result of the project indicates that the oscillation cup technique is applicable for melt viscosity measurement. Detailed mathematical models of innovative sample ampoule designs were developed to not only determine melt viscosity, but also melt density under certain designs. Measurement uncertainties were analyzed and quantified. The result of this project can be used as the initial step toward the eventual goal of establishing a viscosity measurement system for radioactive melts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Multiscale thermal properties prediction in the Multiphysics Object Oriented Simulation Environment (MOOSE) via a general Boltzmann solver [Poster]

The project objectives were: (1) Engineering-scale fuel performance modeling relies on accurate thermal properties; (2) Thermal properties are inherently multi-scale, arising from atomistic processes and interactions with a material’s microstructure; (3) Heat transport in solids via conduction occurs through transport and scattering of electrons and phonons; (4) Use the Boltzmann transport equation (BTE) to predict the macroscopic behavior of a materials system in terms of the microscopic dynamics of its heat carriers; and (5) This project establishes a new MOOSE (Multiphysics Object Oriented Simulation Environment) module, Boltzmann, dedicated to phonon and thermal electron transport.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Model Package Report: Central Plateau Vadose Zone Geoframework Version 1.0

The purpose of the Central Plateau Vadose Zone (CPVZ) Geoframework model (GFM) is to provide a reasonable, consistent, and defensible three-dimensional (3D) representation of the vadose zone beneath the Central Plateau at the Hanford Site to support the Composite Analysis (CA) vadose zone contaminant fate and transport models. The GFM is a 3D representation of the subsurface geologic structure. From this 3D geologic model, exported results in the form of point, surface, and/or volumes are used as inputs to populate and assemble the various numerical model architectures, providing a 3D-layered grid that is consistent with the GFM. The objective of this report is to define the process used to produce a hydrostratigraphic model for the vadose zone beneath the Hanford Site Central Plateau and the corresponding CA domain.

58 GEOSCIENCES↗
DOE OSTI2020

Report of the Atmosphere to Electrons Land-Based Mesoscale-to-Microscale Coupling Project (FY2020)

The overall goal of the Mesoscale-to-Microscale Coupling (MMC) project is to improve coupling between mesoscale and microscale simulations via improved guidance and new strategies for setting up simulations and for the development of new tools that can be used across the community. Including the mesoscale forcing is critical to modeling the full energy transfer across scales in the atmosphere. The project-specific objectives include: 1) To apply rigorous verification and validation (V&V) techniques to the new modeling tools that are developed as part of the project to ensure the accuracy of our codes and results and to develop estimates of the relative uncertainty. 2) To improve computational performance of the coupled MMC models through the development of methods that can be used to reduce turbulence spin-up time and hence the size of computational domains. 3) To improve representation of the surface layer in microscale models to enhance simulations of hub-height wind speed. 4) To develop guidance for the community describing the best ways to couple mesoscale and microscale models, including specific spatial scales at which the handoff to the microscale model should occur. 5) To prepare documentation and a suite of software tools that can be used across the community. And 6) To transition MMC research to the offshore environment. Major progress was made in each of these areas during FY20. The land-based portion of the project is reported herein, while the offshore portion will be reported separately. The team continued to advance the MMC tools and methodologies as well as to document their performance in journal papers and conference presentations, although several planned conferences were cancelled due to the COVID-19 pandemic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Event-to-Video Conversion for Overhead Object Detection

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such as object detection. In this paper, we investigate the viability of event streams for overhead object detection. We demonstrate that across a number of standard modeling approaches, there is a significant gap in performance between dense event representations and corresponding RGB frames. We establish that this gap is, in part, due to a lack of overlap between the event representations and the pre-training data that the object detectors were initially trained on through a number of experiments. Then, apply an off-the-shelf event-to-video conversion tool that converts event streams into gray-scale video to close this gap. We demonstrate that this approach results in a large performance increase, outperforming even event-specific object detection techniques on our overhead target task. These results suggest that better aligning event representations with existing large pre-trained models may result in greater short-term performance gains compared to end-to-end event-specific architectural improvements.

machine learning (ML), computer vision, Neuromorph↗
DOE OSTI2016

SU-F-T-355: Evaluation of Knowledge-Based Planning Model for the Cervical Cancer Radiotherapy

Purpose: The Varian RapidPlan™ is a commercial knowledge-based optimization process which uses a set of clinically used treatment plans to train a model that can predict individualized dose-volume objectives. The purpose of this study is to evaluate the performance of RapidPlan to generate intensity modulated radiation therapy (IMRT) plans for cervical cancer. Methods: Totally 70 IMRT plans for cervical cancer with varying clinical and physiological indications were enrolled in this study. These patients were all previously treated in our institution. There were two prescription levels usually used in our institution: 45Gy/25 fractions and 50.4Gy/28 fractions. 50 of these plans were selected to train the RapidPlan model for predicting dose-volume constraints. After model training, this model was validated with 10 plans from training pool(internal validation) and additional other 20 new plans(external validation). All plans used for the validation were re-optimized with the original beam configuration and the generated priorities from RapidPlan were manually adjusted to ensure that re-optimized DVH located in the range of the model prediction. DVH quantitative analysis was performed to compare the RapidPlan generated and the original manual optimized plans. Results: For all the validation cases, RapidPlan based plans (RapidPlan) showed similar or superior results compared to the manual optimized ones. RapidPlan increased the result of D98% and homogeneity in both two validations. For organs at risk, the RapidPlan decreased mean doses of bladder by 1.25Gy/1.13Gy (internal/external validation) on average, with p=0.12/p<0.01. The mean dose of rectum and bowel were also decreased by an average of 2.64Gy/0.83Gy and 0.66Gy/1.05Gy,with p<0.01/ p<0.01and p=0.04/<0.01 for the internal/external validation, respectively. Conclusion: The RapidPlan model based cervical cancer plans shows ability to systematically improve the IMRT plan quality. It suggests that RapidPlan has great potential to make the treatment planning process more efficient.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Proposed mechanistic description of dose-dependent BDE-47 urinary elimination in mice using a physiologically based pharmacokinetic model

Polybrominated diphenyl ethers (PBDEs) have been used in a wide variety of consumer applications as additive flame retardants. In North America, scientists have noted continuing increases in the levels of PBDE congeners measured in human serum. Some recent studies have found that PBDEs are associated with adverse health effects in humans, in experimental animals, and wildlife. This laboratory previously demonstrated that urinary elimination of 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47) is saturable at high doses in mice; however, this dose-dependent urinary elimination has not been observed in adult rats or immature mice. Thus, the primary objective of this study was to examine the mechanism of urinary elimination of BDE-47 in adult mice using a physiologically based pharmacokinetic (PBPK) model. To support this objective, additional laboratory data were collected to evaluate the predictions of the PBPK model using novel information from adult multi-drug resistance 1a/b knockout mice. Using the PBPK model, the roles of mouse major urinary protein (a blood protein carrier) and P-glycoprotein (an apical membrane transporter in proximal tubule cells in the kidneys, brain, intestines, and liver) were investigated in BDE-47 elimination. The resulting model and new data supported the major role of m-MUP in excretion of BDE-47 in the urine of adult mice, and a lesser role of P-gp as a transporter of BDE-47 in mice. This work expands the knowledge of BDE-47 kinetics between species and provides information for determining the relevancy of these data for human risk assessment purposes. - Highlights: • We report the first study on PBPK model on flame retardant in mice for BDE-47. • We examine mechanism of urinary elimination of BDE-47 in mice using a PBPK model. • We investigated roles of m-MUP and P-gp as transporters in urinary elimination.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A Spatiotemporal Prediction Model for Regional Scheduling of Shared Bicycles Based on the INLA Method

Dock-less bicycle-sharing programs have been widely accepted as an efficient mode to benefit health and reduce congestions. And modeling and prediction has always been a core proposition in the field of transportation. Most of the existing demand prediction models for shared bikes take regions as research objects; therefore, a POI-based method can be a beneficial complement to existing research, including zone-level, OD-level, and station-level techniques. Point of interest (POI) is the location description of spatial entities, which can reflect the cycling route characteristics for both commuting and noncommuting trips to a certain extent, and is also the main generating point and attraction point of shared-bike travel flow. In this study, we make an effort to model a POI-level cycling demand with a Bayesian hierarchical method. The proposed model combines the integrated nested Laplace approximation (INLA) and random partial differential equation (SPDE) to cope with the huge computation in the modeling process. In particular, we have adopted the dock-less bicycle-sharing rental records of Mobike as a case study to validate our method; the study area was one of the fastest growing urban districts in Shanghai in August 2016. The operation results show that the method can help better understand, measure, and characterize spatiotemporal patterns of bike-share ridership at the POI level and quantify the impact of the spatiotemporal effect on bicycle-sharing use.

Yu, Zhuoran↗
DOE OSTI2014

Recent Progress Validating the HADES Model of LLNL's HEAF MicroCT Measurements

This report compares recent HADES calculations of x-ray linear attenuation coefficients to previous MicroCT measurements made at Lawrence Livermore National Laboratory’s High Energy Applications Facility (HEAF). The chief objective is to investigate what impact recent changes in HADES modeling have on validation results. We find that these changes have no obvious effect on the overall accuracy of the model. Detailed comparisons between recent and previous results are presented.

42 ENGINEERING↗
DOE OSTI2013

Influence of Sea Ice on Arctic Marine Sulfur Biogeochemistry in the Community Climate System Model

Global climate models (GCMs) have not effectively considered how responses of arctic marine ecosystems to a warming climate will influence the global climate system. A key response of arctic marine ecosystems that may substantially influence energy exchange in the Arctic is a change in dimethylsulfide (DMS) emissions, because DMS emissions influence cloud albedo. This response is closely tied to sea ice through its impacts on marine ecosystem carbon and sulfur cycling, and the ice-albedo feedback implicated in accelerated arctic warming. To reduce the uncertainty in predictions from coupled climate simulations, important model components of the climate system, such as feedbacks between arctic marine biogeochemistry and climate, need to be reasonably and realistically modeled. This research first involved model development to improve the representation of marine sulfur biogeochemistry simulations to understand/diagnose the control of sea-ice-related processes on the variability of DMS dynamics. This study will help build GCM predictions that quantify the relative current and possible future influences of arctic marine ecosystems on the global climate system. Our overall research objective was to improve arctic marine biogeochemistry in the Community Climate System Model (CCSM, now CESM). Working closely with the Climate Ocean Sea Ice Model (COSIM) team at Los Alamos National Laboratory (LANL), we added 1 sea-ice algae and arctic DMS production and related biogeochemistry to the global Parallel Ocean Program model (POP) coupled to the LANL sea ice model (CICE). Both CICE and POP are core components of CESM. Our specific research objectives were: 1) Develop a state-of-the-art ice-ocean DMS model for application in climate models, using observations to constrain the most crucial parameters; 2) Improve the global marine sulfur model used in CESM by including DMS biogeochemistry in the Arctic; and 3) Assess how sea ice influences DMS dynamics in the arctic marine environment and predict how it will do so in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Structure and Process of Managing the UO2 Dry In-Pile Fracture Test Irradiation Experiment

The management and structure of a novel research and development (R&D) project can be hard to navigate. This is especially true when it involves nuclear fuel. Familiarity with institutional safety and procedural requirements, a well defined scope, and accurate cost estimates can all help ensure successful project management from start to finish. The Dry In-Pile Fracture Test (DRIFT) experiments performed at the Transient Test Reactor Facility are an excellent example of managing an R&D project within its scope and budget constraints. The objective of the DRIFT test was to develop fracture propagation data in a manner consistent with light-water reactors to validate and improve the fracture propagation models of uranium oxide fuels in the MOOSE (Multiphysics Object-Oriented Simulation Environment)-BISON-Marmot code framework [1].

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Brown dwarf disks with ALMA

We present Atacama Large Millimeter/submillimeter Array continuum and spectral line data at 0.89 mm and 3.2 mm for three disks surrounding young brown dwarfs and very low mass stars in the Taurus star forming region. Dust thermal emission is detected and spatially resolved for all the three disks, while CO(J = 3-2) emission is seen in two disks. We analyze the continuum visibilities and constrain the disks' physical structure in dust. The results of our analysis show that the disks are relatively large; the smallest one has an outer radius of about 70 AU. The inferred disk radii, radial profiles of the dust surface density, and disk to central object mass ratios lie within the ranges found for disks around more massive young stars. We derive from our observations the wavelength dependence of the millimeter dust opacity. In all the three disks, data are consistent with the presence of grains with at least millimeter sizes, as also found for disks around young stars, and confirm that the early stages of the solid growth toward planetesimals occur also around very low-mass objects. We discuss the implications of our findings on models of solids evolution in protoplanetary disks, the main mechanisms proposed for the formation of brown dwarfs and very low-mass stars, as well as the potential of finding rocky and giant planets around very low-mass objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

MITR RELAP5 Model Validations at Steady States and Transients

The Massachusetts Institute of Technology Reactor (MITR-II) is a 6 MW university research reactor designed primarily for experiments using neuron beams and in-core irradiation facilities, and education. The objective of this study is to validate the MITR RELAP5 model, which includes the reactor core, primary coolant loop, secondary coolant loop and heat exchanger models. Two sets of operational data were collected for validation. Steady-state data for 1 MW, 3 MW, 5.5 MW was obtained in the first test. The continuous startup transient data and the cooling tower outlet coolant temperature reduction obtained during the second test. The five steady-state conditions and two transient conditions were calculated by the RELAP5. The reactor power and cooling tower outlet temperature were used as boundary conditions while the reactor core inlet temperature and outlet temperature were calculated. A comparison was made between the modeling results and the temperature measurements. The results show that the MITR RELAP5 modeling results are in good agreement with measurement data for both steady-state and transient conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2025

Pressure Gain, Stability, and Operability of Methane/Syngas Based RDEs Under Steady and Transient Conditions (Final Project Report)

The scope of this work addresses key issues associated with losses associated with the detonation wave and other processes internal to the RDE operation, as well as it develops modeling tools for the evaluation of these losses and exhaust emissions in RDEs. The main challenge in studying RDEs is that RDE performance is highly reliant on the specifics of the design so much so that simple/canonical systems alone cannot provide useful engineering information, but practical RDE designs are sufficiently complex and involve extreme operational environments that detailed access either experimentally (laser diagnostics, for instance) or computationally (direct numerical simulations) are as yet to become practical. To overcome this challenge, we have conducted a combined experimental/simulation/analytical study investigating key phenomena that control the characteristics of operation of RDEs. As a result, the study has developed tools and methods that can be used to evaluate performance and design approaches using reduced-physics models, with the assumptions validated using detailed simulations, and the model prediction tested using experimental observations. The specific objectives of the research were: (1) Develop and demonstrate a low-loss fully axial injection concept, taking advantage of stratification effects to alter the detonation structure and position the wave favorably within the combustor; (2) Obtain stability and operability characteristics of an RDE across operating conditions to aid in the development of operability and performance rules for the operations of other systems; and (3) Develop quantitative metrics for performance gain as well as quantitative description of the loss mechanisms through a combination of diagnostics development, reduced-order modeling, and detailed simulations. The work conducted here has made contribution on design of low-loss inlets that has broad application within the power generation industry for use with pressure gain combustion. The operability and stability of different designs, while focusing on axial air inlet designs, has been analyzed. The effect of nozzle and injection conditions was studied. Models and simulations of exhaust emissions, focusing on NOx emission has been developed and used to investigate how operation of the RDE affect NOx production using Lagrangian analysis of RDE simulations. This work has built on previous programs, with the goal of further understanding operation of RDEs and elevate the readiness of design consideration. In addition, a suite of diagnostic and modeling tools have been developed to obtain quantitative metrics on performance based on measurements, which can be readily transferred to other experimental configurations.

08 HYDROGEN↗