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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Overview of System Integration Analysis Activities for Integrated Waste Management

Spent nuclear fuel (SNF) generated by the current fleet of commercial nuclear reactors is being stored at the reactor sites in spent fuel pools (SFPs) and in dry independent spent fuel storage installations (ISFSIs). The US Department of Energy Office of Nuclear Energy (DOE-NE) is developing an Integrated Waste Management Program (IWMP) comprising a suite of options and supporting analyses to enable future informed choices. The IWMP is organized into the following five major areas: 1) Consent-Based Siting, 2) IWM Facilities and Equipment Concepts and Development, 3) Transportation Capability Analysis and Support, 4) Information Technology Solutions and Support, and 5) System Integration Analysis and Support. This paper discusses the activities ongoing in the IWMP System Integration Analysis and Support area. Two main areas of research in system integration are data and tools development, as well as system analysis assessments. One of the tools being developed in the system integration area is the Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) tool. It is being developed as a foundational resource for DOE-NE to manage SNF data, along with several compatible analysis tools for time-dependent characterization of SNF and related systems. UNF-ST&DARDS has the unparalleled ability to track SNF through the entire back end of the fuel cycle—from the time the fuel is discharged from a reactor through its disposal in a geological repository. UNF ST&DARDS interfaces with the SCALE code system for nuclear analysis and COBRA-SFS for thermal analysis. Another main tool being developed is the Next Generation System Analysis Model (NGSAM). NGSAM is an agent-based simulation software tool expressly designed to be capable of modeling the waste management system. NGSAM has been developed to enable informed decision-making by providing the capability of analyzing various potential system options for the management of SNF and HLW. Using NGSAM, system architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analysis assessments may investigate the implications of various strategies such as different acceptance rates, acceptance queues, facility capacities and options, standardized canisters, and different assumed system operation start dates. Recently, some system analysis effort has begun to look at how the waste management system might operate for advanced reactor fuel cycles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Integral approximations to classical diffusion and smoothed particle hydrodynamics

The contribution of the paper is the approximation of a classical diffusion operator by an integral equation with a volume constraint. A particular focus is on classical diffusion problems associated with Neumann boundary conditions. By exploiting this approximation, we can also approximate other quantities such as the flux out of a domain. Our analysis of the model equation on the continuum level is closely related to the recent work on nonlocal diffusion and peridynamic mechanics. In particular, we elucidate the role of a volumetric constraint as an approximation to a classical Neumann boundary condition in the presence of physical boundary. The volume-constrained integral equation then provides the basis for accurate and robust discretization methods. An immediate application is to the understanding and improvement of the Smoothed Particle Hydrodynamics (SPH) method.

boundary conditions, smoothed particle hydrodynami↗
DOE OSTI2024

Experimental Covariance Determination for Critical Integral Experiments

Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. In general, uncertainty quantification techniques ignore correlations between experiments and shared parts. Experiments, such as the TEX (Thermal/Epithermal eXperiments) campaigns, consist of many shared parts, such as the ‘Jemima’ HEU fuel plates, which create a strong correlation in their uncertainties. While these correlations are known to exist, they are often not estimated due to the complexity of such calculations. This paper describes an intuitive method of determining the covariance for each of the experimental components, providing a correlation for each family of parts across the multiple cases examined within a benchmark. A proof-of-principle study using the TEX-HEU experimental campaign was performed and verified that the correlations can be calculated with information commonly found in the ICSBEP (International Criticality Safety Benchmark Evaluation Project) benchmarks. This study showed that the introduction of model and experimental covariances reduces the χ 2 per degree of freedom from 2.203 to 1.179, indicating that the omission causes overly pessimistic bias quantifications. This technique can be seamlessly integrated to current benchmark evaluations as well as reevaluations of legacy benchmarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗
DOE OSTI2017

Ultrathin Co 3 O 4 Layers with Large Contact Area on Carbon Fibers as High-Performance Electrode for Flexible Zinc-Air Battery Integrated with Flexible Display

A facile and binder-free method is developed for the in situ and horizontal growth of ultrathin mesoporous Co 3 O 4 layers on the surface of carbon fibers in the carbon cloth (ultrathin Co 3 O 4 /CC) as high-performance air electrode for the flexible Zn-air battery. In particular, the ultrathin Co 3 O 4 layers have a maximum contact area on the conductive support, facilitating the rapid electron transport and preventing the aggregation of ultrathin layers. The ultrathin feature of Co 3 O 4 layers is characterized by the transmission electron microscopy, Raman spectra, and X-ray absorption fine structure spectroscopy. Benefiting from the high utilization degree of active materials and rapid charge transport, the mass activity for oxygen reduction and evolution reactions of the ultrathin Co 3 O 4 /CC electrode is more than 10 times higher than that of the carbon cloth loaded with commercial Co 3 O 4 nanoparticles. Compared to the commercial Co 3 O 4 /CC electrode, the flexible Zn-air battery using ultrathin Co 3 O 4 /CC electrode exhibits excellent rechargeable performance and high mechanical stability. Furthermore, the flexible Zn-air battery is integrated with a flexible display unit. The whole integrated device can operate without obvious performance degradation under serious deformation and even during the cutting process, which makes it highly promising for wearable and roll-up optoelectronics.

cobalt oxides↗
DOE OSTI2017

Incorporating variability in simulations of seasonally forced phenology using integral projection models

Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography. Our derivation, which is based on the rate-summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models. We demonstrate our approach using a temperature-dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills mature pine trees. This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large-scale simulations, such as studies of altered pest distributions under climate change.

Goodsman, Devin W.↗
DOE OSTI2015

Integrated modeling applications for tokamak experiments with OMFIT

We developed one modeling framework for integrated tasks (OMFIT) is a comprehensive integrated modeling framework which will enable physics codes to interact in complicated workflows, and support scientists at all stages of the modeling cycle. The OMFIT development follows a unique bottom-up approach, where the framework design and capabilities organically evolve to support progressive integration of the components that are required to accomplish physics goals of increasing complexity. OMFIT provides a workflow for easily generating full kinetic equilibrium reconstructions that are constrained by magnetic and motional Stark effect measurements, and kinetic profile information that includes fast-ion pressure modeled by a transport code. It was found that magnetic measurements can be used to quantify the amount of anomalous fast-ion diffusion that is present in DIII-D discharges, and provide an estimate that is consistent with what would be needed for transport simulations to match the measured neutron rates. OMFIT was used to streamline edge-stability analyses, and evaluate the effect of resonant magnetic perturbation (RMP) on the pedestal stability, which have been found to be consistent with the experimental observations. Moreover, the development of a five-dimensional numerical fluid model for estimating the effects of the interaction between magnetohydrodynamic (MHD) and microturbulence, and its systematic verification against analytic models was also supported by the framework. OMFIT was used for optimizing an innovative high-harmonic fast wave system proposed for DIII-D. For a parallel refractive index n(parallel to) > 3, the conditions for strong electron-Landau damping were found to be independent of launched n(parallel to) and poloidal angle. OMFIT has been the platform of choice for developing a neural-network based approach to efficiently perform a non-linear multivariate regression of local transport fluxes as a function of local dimensionless parameters. Transport predictions for thousands of DIII-D discharges showed excellent agreement with the power balance calculations across the whole plasma radius and over a broad range of operating regimes. Concerning predictive transport simulations, the framework made possible the design and automation of a workflow that enables self-consistent predictions of kinetic profiles and the plasma equilibrium. It is found that the feedback between the transport fluxes and plasma equilibrium can significantly affect the kinetic profiles predictions. Finally, such a rich set of results provide tangible evidence of how bottom-up approaches can potentially provide a fast track to integrated modeling solutions that are functional, cost-effective, and in sync with the research effort of the community.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

An Integrated Traction Drive with a High Speed Surface Permanent Magnet External Rotor Motor for Electric Vehicles

This work presents the detailed design of an outer rotor motor and integrated drive for passenger electric vehicles. The motor uses non-heavy rare earth permanent magnets and operates at a top speed of 20,000rpm. In-slot ceramic heat exchangers are utilized for the cooling of the windings. The external rotor configuration of the motor leaves a significant amount of space in the stator bore, which is leveraged for the integration of the power electronics. A high speed external rotor motor creates a number of mechanical, thermal and assembly challenges and this work presents detailed thermal, mechanical and rotordynamics analysis.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Integrated Synchronization Control of Grid-Forming Inverters for Smooth Microgrid Transition

This paper develops an integrated synchronization control technique for a grid-forming inverter operating within a microgrid that can improve the microgrid's transients during microgrid transition operation. This integrated synchronization control includes the disconnection synchronization control and the reconnection synchronization control. The simulation results show that the developed synchronization control works effectively to smooth the angle change of the grid-forming inverter during microgrid transition operation. Thus, the microgrid's transients are significantly improved compared to the case without synchronization control.

control↗
DOE OSTI2022

A Blockchain Based Co-Simulation Framework for Integrating DERs to Wholesale Electricity Markets

As the number of distributed energy resources (DERs) continue to increase across energy-delivery systems, there remains a need for integrating their capabilities into traditional grid operations. In this paper, a blockchain-based solution is proposed to facilitate FERC's Order No. 2222 implementations. The presented use-case enables small-scale DERs to participate in wholesale market operations through DER aggregators, while also enabling local distribution system operators to enforce distribution system constraints in a secure and traceable manner. The presented use case is built around the Unified Testing Platform (UTP) being developed as a part of the Blockchain for Optimized Security and Energy Management (BLOSEM) project. This is a multi-lab effort intended to simplify the deployment of blockchain-powered grid solutions by enabling the integration of simulation tools, and blockchain technologies through the use of system-agnostic interfaces that provide a modular, interoperable, and reusable connectivity layer.

blockchain interoperability↗
DOE OSTI2015

Simulating and evaluating best management practices for integrated landscape management scenarios in biofuel feedstock production: Evaluating Best Management Practices for Biofuel Feedstock Production

Sound crop and land management strategies can maintain land productivity and improve the environmental sustainability of agricultural crop and feedstock production. This study evaluates the improvement of water sustainability through an integrated landscaping management strategy, where landscaping design, land management operations, crop systems, and agricultural best management practices (BMPs) play equal roles. The strategy was applied to the watershed of the South Fork Iowa River in Iowa, with a focus on implementing riparian buffers and converting low productivity land to provide cellulosic biomass while benefiting soil and water quality. The Soil and Water Assessment Tool (SWAT) was employed to simulate the impact of integrated landscape design on nutrients, suspended sediments, and flow on the watershed and subbasin scales. First, the study evaluated the representation of buffer strip as a vegetative barrier and as a riparian buffer using trapping efficiency and area ratio methods in SWAT. For the riparian buffer, the area ratio method tends to be more conservative, especially in nitrate loadings, while the trapping efficiency method generates more optimistic results. The differences between the two methods increase with buffer width. The two methods may not be comparable for the field-scale vegetative barrier simulation because of limitations in model spatial resolution. Landscape scenarios were developed to quantify water quality under (1) current land use, (2) partial land conversion to switchgrass, and (3) riparian buffer implementation. Results show that when low productivity land (15.2% of total watershed land area) is converted to grow switchgrass, suspended sediment, total nitrogen, total phosphorus, and nitrate loadings are reduced by 69.3%, 55.5%, 46.1%, and 13.4%, respectively, in the watershed surface streams. The reduction was less extensive when riparian buffer strips (30 m or 50 m) were applied to the stream network at 1.4% of total land area in the watershed. At the subbasin level, the degree of nutrient and suspended sediment reduction varies extensively, ranging from a few percent up to 55%. Results indicate that effective landscape design on current agricultural land can potentially bring marked improvements in water quality and soil erosion control while producing food and fuel feedstock in the South Fork Iowa River watershed. The concept can be integrated with other watershed management programs to improve sustainability of land, water, and the ecosystem.

bioenergy production↗
DOE OSTI2021

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗
DOE OSTI2021

Mocking the u-plane integral

Abstract The u -plane integral is the contribution of the Coulomb branch to correlation functions of $${\mathcal {N}}=2$$ N = 2 gauge theory on a compact four-manifold. We consider the u -plane integral for correlators of point and surface observables of topologically twisted theories with gauge group $$\mathrm{SU}(2)$$ SU ( 2 ) , for an arbitrary four-manifold with $$(b_1,b_2^+)=(0,1)$$ ( b 1 , b 2 + ) = ( 0 , 1 ) . The u -plane contribution equals the full correlator in the absence of Seiberg–Witten contributions at strong coupling, and coincides with the mathematically defined Donaldson invariants in such cases. We demonstrate that the u -plane correlators are efficiently determined using mock modular forms for point observables, and Appell–Lerch sums for surface observables. We use these results to discuss the asymptotic behavior of correlators as function of the number of observables. Our findings suggest that the vev of exponentiated point and surface observables is an entire function of the fugacities.

Mathematics↗
DOE OSTI2014

An integrated assessment of location-dependent scaling for microalgae biofuel production facilities

Successful development of a large-scale microalgae-based biofuels industry requires comprehensive analysis and understanding of the feedstock supply chain—from facility siting and design through processing and upgrading of the feedstock to a fuel product. The evolution from pilot-scale production facilities to energy-scale operations presents many multi-disciplinary challenges, including a sustainable supply of water and nutrients, operational and infrastructure logistics, and economic competitiveness with petroleum-based fuels. These challenges are partially addressed by applying the Integrated Assessment Framework (IAF) – an integrated multi-scale modeling, analysis, and data management suite – to address key issues in developing and operating an open-pond microalgae production facility. This is done by analyzing how variability and uncertainty over space and through time affect feedstock production rates, and determining the site-specific “optimum” facility scale to minimize capital and operational expenses. This approach explicitly and systematically assesses the interdependence of biofuel production potential, associated resource requirements, and production system design trade-offs. To provide a baseline analysis, the IAF was applied in this paper to a set of sites in the southeastern U.S. with the potential to cumulatively produce 5 billion gallons per year. Finally, the results indicate costs can be reduced by scaling downstream processing capabilities to fit site-specific growing conditions, available and economically viable resources, and specific microalgal strains.

09 BIOMASS FUELS↗
DOE OSTI2020

Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma

Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potentialroles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Hu, Yingwei↗
DOE OSTI2023

Recent advances in integrated hydrologic models: Integration of new domains

Over the past several decades, hydrologic models have advanced from independent models of the surface and subsurface to integrated models that can capture the terrestrial hydrologic cycle within one framework. In recent years, these coupled frameworks have seen the inclusion of biogeochemical processes, ecohydrology, sedimentation and erosion, cold region hydrology, anthropogenic activities, and atmospheric processes. This expansion is the result of increased computational, data, and modeling capabilities and capacities, as well as improved understanding of the processes that drive these integrated systems. Here, in this study, we review these recent advances to integrate new processes and systems into existing terrestrial hydrologic models and highlight the significant challenges and opportunities that remain. We identify that with so many models currently available and in development, selecting the most appropriate model is difficult, and we suggest a path for new or novice modelers to find the most appropriate code based on their needs. In addition, data required to parameterize and calibrate these models can often constrain their applicability and usefulness. However, advances in environmental sensors and measurement technology, in addition to data assimilation of non-traditional data (e.g. remote sensing, qualitative data) are providing new ways of addressing this issue. As we expand hydrologic models to integrate more processes and systems, our computational demands also increase. Recent and emerging advances in computational platforms, including cloud and quantum computing, in addition to the use of machine learning to capture some processes, will continue to support the use of increasingly larger and more complex, process-based models. Finally, we highlight that it is critical to develop state-of-the-science models that are accessible to all model users, not just those applied for research and development. We encourage continued development of diverse modeling platforms, considering the user needs, data availability, and computational resources.

54 ENVIRONMENTAL SCIENCES↗