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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

NEAMS Software V&V Plan for the MARMOT Software

In order to ensure the accuracy and quality of the microstructure based materials models being developed in conjunction with MARMOT simulations, MARMOT must undergo exhaustive verification and validation. Only after this process can we confidently rely on the MARMOT code to predict the microstructure evolution within the fuel. Therefore, in this report we lay out a V&V plan for the MARMOT code, highlighting where existing data could be used and where new data is required.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

IEA Wind Task 26. Wind Technology, Cost and Performance Trends in Denmark, Germany, Ireland, Norway, the European Union, and the United States. 2007 - 2012

This report builds from a similar previous analysis (Schwabe et al., 2011) exploring the differences in cost of wind energy in 2008 among countries participating in IEA Wind Task 26 at that time. The levelized cost of energy (LCOE) is a widely recognized metric for understanding how technology, capital investment, operations, and financing impact the life-cycle cost of building and operating a wind plant. Schwabe et al. (2011) apply a spreadsheet-based cash flow model developed by the Energy Research Centre of the Netherlands (ECN) to estimate LCOE. This model is a detailed, discounted cash flow model used to represent the various cost structures in each of the participating countries from the perspective of a financial investor in a domestic wind energy project. This model is used for the present analysis as well, and comparisons are made for those countries who contributed to both reports, Denmark, Germany, and the United States.

17 WIND ENERGY↗
DOE OSTI2022

A Demonstration of Intelligent Container Surveillance Using Stationary and Mobile Camera Platforms

Surveillance of nuclear material storage containers is required to ensure that the container safety boundary is maintained during the service life of the container. As many of these container types are the first and only containment barrier to release protecting the worker, public, and environment, it is imperative to develop robust surveillance tools to characterize container degradation. Machine learning (ML) techniques have matured quickly in the past decade and are slowly becoming a routine application in data analysis. While more popular architectures have been developed with different applications in mind, these can be easily translated to container surveillance requirements. In this study, we developed a ML model based on the Detectron2 framework to identify slip lid containers and common exterior container defects, primarily dents. Commercial-off-the-shelf cameras are combined into a stationary camera array or are mounted to a robotic arm to provide more mobility for positioning needs. Results from the model evaluations on the images indicate that the stationary camera arrays outperform the accuracy of the mobile camera systems for both individual camera and composite image detections. Overall, however, the detection accuracies of the systems fell short of 50% and were less than satisfactory. Future efforts to improve the system involve focusing on a single camera deployable solution that combines a controllable light source that eliminates one of the biggest environmental factors that influence ML model detection performance. Additional training set collection is planned to build a more robust model that enables accurate detection from a wider range of imaging conditions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Toward a Generalizable Framework of Disturbance Ecology Through Crowdsourced Science

Disturbances fundamentally alter ecosystem functions, yet predicting their impacts remains a key scientific challenge. While the study of disturbances is ubiquitous across many ecological disciplines, there is no agreed-upon, cross-disciplinary foundation for discussing or quantifying the complexity of disturbances, and no consistent terminology or methodologies exist. This inconsistency presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can destabilize ecosystem responses. By harvesting the expertise of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we identified an essential limitation in disturbance ecology: the word ‘disturbance’ is used interchangeably to refer to both the events that cause, and the consequences of, ecological change, despite fundamental distinctions between the two meanings. In response, we developed a generalizable framework of ecosystem disturbances, providing a well-defined lexicon for understanding disturbances across perspectives and scales. The framework results from ideas that resonate across multiple scientific disciplines and provides a baseline standard to compare disturbances across fields. This framework can be supplemented by discipline-specific variables to provide maximum benefit to both inter- and intra-disciplinary research. To support future syntheses and meta-analyses of disturbance research, we also encourage researchers to be explicit in how they define disturbance drivers and impacts, and we recommend minimum reporting standards that are applicable regardless of scale. Finally, we discuss the primary factors we considered when developing a baseline framework and propose four future directions to advance our interdisciplinary understanding of disturbances and their social-ecological impacts: integrating across ecological scales, understanding disturbance interactions, establishing baselines and trajectories, and developing process-based models and ecological forecasting initiatives. Our experience through this process motivates us to encourage the wider scientific community to continue to explore new approaches for leveraging Open Science principles in generating creative and multidisciplinary ideas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Machine Learning Analysis of Hydrologic Exchange Flows and Transit Time Distributions in a Large Regulated River

Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. High-resolution numerical models were often used to resolve the spatial and temporal variations of exchange flows, which are computationally expensive. In this study, we adopt Random Forest (RF) and Extreme Gradient Boosting (XGB) approaches for deriving reduced order models of hydrologic exchange flows and associated transit time distributions, with integrated field observations (e.g., bathymetry) and hydrodynamic simulation data (e.g., river velocity, depth). The setup allows an improved understanding of the influences of various physical, spatial, and temporal factors on the hydrologic exchange flows and transit times. The predictors also contain those derived using hybrid clustering, leveraging our previous work on river corridor system hydromorphic classification. The machine learning-based predictive models are developed and validated along the Columbia River Corridor, and the results show that the top parameters are the thickness of the top geological formation layer, the flow regime, river velocity, and river depth; the RF and XGB models can achieve 70% to 80% accuracy and therefore are effective alternatives to the computational demanding numerical models of exchange flows and transit time distributions. Each machine learning model with its favorable configuration and setup have been evaluated. The transferability of the models to other river reaches and larger scales, which mostly depends on data availability, is also discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Operating Hardware Impact on the Heat Transfer Properties of Windows

Despite significant advancements in fenestration technology in the last two decades, the thermal transmittance of fenestration products is still significantly higher than that of walls. This corresponds to 60% of the total energy loss of a modern building envelope through the windows. Hence, further development and improvements of fenestration products are necessary. Increasingly stringent codes and standards for fenestration stimulate industry to work on improved solutions. Thus, it is crucial that assessment techniques are able to account for innovations accurately. The thermal effects of non-continuous hardware in window frames are currently ignored by international rating procedures. A preliminary investigation conducted by our team showed significant performance degradation in two of the three out-opening casement profiles caused by the presence of operating hardware. Frames with the structure made of vinyl and fiberglass consist of many air cavities that are penetrated by operating hardware made of highly conductive materials. In these frames, in order to have an accurate assessment, it may be required to employ three-dimensional modeling due to the convective nature of heat transfer within the cavities. However, in this study, we demonstrate that the three-dimensional (3D) effects of non-continuous hardware can be approximated accurately with simpler two-dimensional (2D) simulations. We then develop a simplified model based on weighted average capable of replacing the time- and computation-intensive 3D simulations with 2D simulations and validate it against market available frames and their corresponding hardware. Validation results show that our approximation technique results in discrepancies lower than 0.05 W/(m2K), or 3% of the total thermal transmittance. Thus, we conclude that simplified 2D simulation models may be used for predicting hardware impact in window frames with reasonable accuracy. As windows and glazing structures are becoming ever better thermally insulated, it is becoming even more important to be able to model the impact of the operating hardware on the total thermal performance in order to design the best windows possible and not let the operating hardware ruin an otherwise well-proven design, which is hence addressed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Monitoring the Morphology of M87* in 2009-2017 with the Event Horizon Telescope

The Event Horizon Telescope (EHT) has recently delivered the first resolved images of M87*, the supermassive black hole in the center of the M87 galaxy. These images were produced using 230 GHz observations performed in 2017 April. Additional observations are required to investigate the persistence of the primary image feature—a ring with azimuthal brightness asymmetry—and to quantify the image variability on event horizon scales. To address this need, we analyze M87* data collected with prototype EHT arrays in 2009, 2011, 2012, and 2013. While these observations do not contain enough information to produce images, they are sufficient to constrain simple geometric models. We develop a modeling approach based on the framework utilized for the 2017 EHT data analysis and validate our procedures using synthetic data. Applying the same approach to the observational data sets, we find the M87* morphology in 2009–2017 to be consistent with a persistent asymmetric ring of ∼40 μas diameter. The position angle of the peak intensity varies in time. In particular, we find a significant difference between the position angle measured in 2013 and 2017. These variations are in broad agreement with predictions of a subset of general relativistic magnetohydrodynamic simulations. We show that quantifying the variability across multiple observational epochs has the potential to constrain the physical properties of the source, such as the accretion state or the black hole spin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE

A multi-species linearized collision operator based on the model developed by Sugama et al. has been implemented in the nonlinear gyrokinetic code, GENE. Such a model conserves particles, momentum, and energy to machine precision, and is shown to have negative definite free energy dissipation characteristics, satisfying Boltzmann’s H-theorem, including for realistic mass ratio. Finite Larmor Radius (FLR) effects have also been implemented into the local version of the code. For the global version of the code, the collision operator has been developed to allow for block-structured velocity space grids, allowing for computationally tractable collisional global simulations. The validity of the collision operator has been demonstrated by relaxation and conservation tests, as well as appropriate benchmarks. The newly implemented operator shall be used in future simulations to study magnetically confined fusion plasma turbulence and transport in more extreme regions with higher collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2011

The Effects of Heterogeneities on Seismic Wave Propagation in the Climax Stock

The Comprehensive Nuclear Test-Ban Treaty requires the ability to detect low-yield (less than 150kton) nuclear events. This kind of monitoring can only be done seismically on a regional scale (within 2000km). At this level, it is difficult to distinguish between low-yield nuclear events and non-nuclear events of similar magnitude. In order to confidently identify a nuclear event, a more detailed understanding of nuclear seismic sources is needed. In particular, it is important to know the effects of local geology on the seismic signal. This study focuses on P-wave velocity in heterogeneous granitoid. The Source Physics Experiment (SPE) is currently performing low-yield tests with chemical explosives at the Nevada National Security Site (NNSS). The exact test site was chosen to be in the Climax Stock, a cretaceous granodiorite and quartz-monzonite pluton located in Area 15 of the NNSS. It has been used in the past for the Hard Hat and Pile Driver nuclear tests, which provided legacy data that can be used to simulate wave propagation. The Climax Stock was originally chosen as the site of the SPE partly because of its assumed homogeneity. It has since been discovered that the area of the stock where the SPE tests are being performed contains a perched water table. In addition, the stock is known to contain an extensive network of faults, joints, and fractures, but the exact effect of these structural features on seismic wave velocity is not fully understood. The SPE tests are designed to seismically capture the explosion phenomena from the near- to the far-field transition of the seismic waveform. In the first SPE experiment, 100kg of chemical explosives were set off at a depth of 55m. The blast was recorded with an array of sensors and diagnostics, including accelerometers, geophones, rotational sensors, short-period and broadband seismic sensors, Continuous Reflectometry for Radius vs. Time Experiment, Time of Arrival, Velocity of Detonation, and infrasound sensors. The focus of this study is two-fold: (1) the geophone array that was focused over the SPE shot and (2) a high-resolution seismic profile that was recently acquired at the field site. The geophone array was placed radially around the SPE shot in five directions with 100m spacing and out to a distance of 2 km. The high-resolution profile was about 475m in length with station and shot spacing of 5m using a 7000lb mini-vibe as a source. In both data sets, the first arrivals will be used to develop velocity models. For the geophone array, 1-D P-wave velocity models will be developed to determine an average apparent velocity of the Climax Stock. The high-resolution data will be used to develop a 2-D P-wave velocity model along the seismic profile. This is in an effort to elucidate the water table in more detail and provide additional information on the near-surface structure. These results will be used in the overall modeling effort to fully characterize the test bed and develop a physics-based model to simulate seismic energy from the SPE events.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

A Learning-based Supervisory Control Architecture for Electric Vehicle Charging System Paired with Energy Storages

A Machine Learning-based predictive model is developed for optimal dispatching energy storage system integrated with Electric Vehicle battery charger. The model is effectively trained using transfer learning algorithm and successfully validated via measurement data to achieve high fidelity and accuracy. The study findings provide possibilities for future development of the presented approach to implement computational heavy predictive algorithms with multi-step predictions in emerging modular bidirectional charger topologies to realize vehicle-to-grid (V2G) technology. The online tuning can be explored using the new measurements obtained during the operation, henceforth, enhancing the controller performance for integrating multiple DERs into distribution power networks that shows huge interest for the utilities and regulatory agencies. Multiple operation scenatios have been evaluated and simulation results are discussed to verify intended performance of the proposed control solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Recovering New Type of Sources by Off-Site Source Recovery Project for WIPP Disposal - 16604

OSRP uses two types of eligible packaging configurations for Cm-244 and Cf-252 disposal to WIPP: an S-100 drum and a 12'' Pipe Overpack (POC) drum. Both types of packaging are WIPP accepted configurations for Contact Handled (CH) waste, which offer different advantages and disadvantages when used in the case of the two isotopes. The S-100 is a poly-shielded type A, 55 gallon drum, containing a 6'' diameter POC. The 12'' POC drum is a type A, 55 gallon drum without the internal poly-shield and with a pipe component of 12'' diameter. The S-100 drum presents the advantage of poly-shielding which is very important for neutron sources, such as the Cf-252, or Cm-244Be, at the expense of reduced internal volume. The 12'' POC drum presents a larger pipe component accommodating many more sources, like Cm-244 alpha emitters or shielded Cf-252, for which the CH dose rate is not an issue. All the sources prepared for disposal to WIPP are required to be special form, as defined in 49 CFR 173.403. When OSRP recovers normal form sources, these can be packaged in a field closable DOT certified Special Form Capsule (SFC) model II or model III, thus becoming special form. These capsules are then packaged in the type-A containers. The difference between the two types of packaging is that the 12'' POC can hold more sources, or a mix of sources and capsules at the expense of less shielding. This becomes important when the TRU content criteria of 100 nCi/g of TRU waste has to be met for the drums that are packaged for WIPP disposal. Measured neutron dose rates for Cm-244 packaged in S-100 agree reasonably well with calculated dose rates based on the models developed with MCNP. Future work will include validating the model for Cm-244 packaged in 12'' POC. A 1:1 ratio of neutron to gamma is expected for Cm-244Be dose rates packaged in S-100 drums. For Cf-252 packaged in S-100 and 12'' POC, the contribution of Cf-250 to the total emission neutron rate had to be taken into account due to the increasing role of Cf-250 as sources age. The uncertainty in the measurement of Cf-252 neutron dose rate for S-100 drum was quite high due to a high neutron background. A larger Cf- 252 source needs to be used for measurements in the future, in order to fully validate the model developed. A better agreement for measured versus calculated rate was obtained for a Cf-252 packaged in 12'' POC. For the WIPP disposal of these sources, OSRP will use the best packaging configuration for these isotopes in order to minimize the dose rate and maximize the TRU content. The S-100 packaging will be used for Cf-252 and Cm-244Be sources, when neutron dose reduction by the poly-shielding is important. Neutron dose rates will be estimated using the new MCNP correlations.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

A new model for active nucleation site density in boiling systems

A new model for active nucleation site density in boiling systems has been developed. The model is based on parametric analysis of existing experimental data and is a function of wall superheat, pressure, and contact angle. The model is applicable for a wide pressure range - from 0.101 MPa to 19.8 MPa. Preliminary studies of temperature dependency of the contact angle have also been performed. The new model is intended to improve the predictions of the interfacial area concentration in two-fluid models and the wall temperature in subcooled boiling simulations. Validation activities have shown that the active nucleation site density predicted by the new model is in a good agreement with various published experimental data, and have demonstrated the achieved improvements as compared to existing models. (authors)

42 ENGINEERING↗
DOE OSTI2016

Testing of LWR Surveillance Materials from the High Fluence UCSB ATR-2 Irradiation

The reactor pressure vessel (RPV) in a light water reactor (LWR) represents the first line of defense against a release of radiation in case of an accident. Thus, regulations that govern the operation of commercial nuclear power plants require conservative margins of fracture toughness, both during normal operation and under accident scenarios. In the unirradiated condition, the RPV has sufficient fracture toughness such that failure is implausible under any postulated condition, including pressurized thermal shock (PTS) in pressurized water reactors (PWR). In the irradiated condition, however, the fracture toughness of the RPV may be severely degraded, with the degree of toughness loss dependent on the radiation sensitivity of the materials. Of the many significant issues discussed regarding irradiation effects, the issue considered to have the most impact on the current regulatory process is that associated with effects of neutron irradiation on RPV steels at high fluence, for long irradiation times, and as affected by neutron flux. As also stated in a companion paper by Odette, et. al., the primary objective of the DOE-sponsored Light Water Reactor Sustainability (LWRS) Program RPV task is to develop robust predictions of transition temperature shifts (TTS) at high fluence (φt) to at least 10{sup 20} n/cm{sup 2} (>1 MeV) pertinent to plant operation of some pressurized water reactors (PWR) for 80 full power years. While understanding of copper-enriched precipitates (CRPs) have been fully developed, the discovery and experimental verification of 'late blooming' Mn-Ni-enriched precipitates (MNPs) with little to no copper for nucleation has stimulated research efforts to understand the evolution of these phases. The new and existing databases will be combined to support development of physically based models of TTS for high fluence-low flux (φ < 10 {sup 11}n/cm{sup 2}-s) conditions, beyond the existing surveillance database, to neutron fluences of at least 10{sup 20} n/cm{sup 2} (>1 MeV). The RPV task of the LWRS Program has worked with various organizations to obtain archival surveillance materials from commercial nuclear power plants to allow for comparisons of the irradiation-induced microstructural features from reactor surveillance materials with those from similar alloys irradiated under high flux conditions in test reactors, such as the UCSB ATR-2 experiment conducted at the Advanced Test Reactor (ATR) at the Idaho National Laboratory (INL). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Hierarchical Conceptual Model Event and Activity Domains for Forecasting State-Sponsored Civil Nuclear Power Activities

In FY20, the Savannah River National Laboratory and the Sanghani Center for Artificial Intelligence and Data Analytics (Virginia Tech) entered a collaboration funded by the Department of Energy’s Office of Defense Nuclear Nonproliferation Research and Development to develop a machine learning based modeling pipeline to extract proliferation events of interest from open data sources. The prototype modeling pipeline that was developed relies on the use of time dependent word embedding models to identify contextual shifts in key words and phrases that act as indicators of events of interest. The FY20- 21 efforts were focused on a narrow topical domain of forecasting “fissile core fabrication” at the Savannah River Site prior to its official announcement in 2018. In FY22, the research team was funded to continue development of the modeling pipeline by applying it to the problem of forecasting new, and/or significant changes to existing, civil nuclear power reactors around the world. In this effort, the development will focus on proving applicability to a broader topical domain and in data environments that may contain more sparse information, relative to the United States. In this report, the worldwide landscape of civil nuclear reactors is outlined, the timeline of interest is defined, and a hierarchical conceptual model is established to identify the activity domains of interest and the event domains of interest. This preliminary effort will guide the curation of a glossary of key terms for data acquisition, as well as the downstream modeling efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Electro-Oxidation of Methane on Platinum under Ambient Conditions

Herein, we investigate the electrochemical conversion of methane to CO 2 on platinum electrodes under ambient conditions. Through a combination of experimentation, density functional theory (DFT) calculations, and ab initio kinetic modeling, we have developed an improved understanding of the reaction mechanism and the factors that determine catalyst activity. We hypothesized that the rate-determining methane activation step is thermochemical (i.e., CH 4 (g) → CH 3 * + H * ) as opposed to electrochemical based on a fitted barrier of approximately 0.96 eV that possesses minimal potential dependence. We developed a simple kinetic model based on the assumption of thermochemical methane activation as the rate-determining step, and the results match well with experimental data. Namely, the magnitude of the maximum current density and the electrode potential at which it is realized agree with our ab initio kinetic model. Finally, we expanded our kinetic model to include other transition metals via a descriptor-based analysis and found platinum to be the most active catalyst for the oxidation of methane, which is in line with previously published experimental observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Gray-Box Modeling for Distribution Systems with Inverter-Based Resources

In this paper, we develop a novel gray-box modeling approach for distribution systems with inverter-based resources (IBRs). The proposed gray-box modeling method aims to improve estimation accuracy by taking advantages of both physics-based (white-box) and data-driven (black-box) modeling approaches. To this end, the gray-box modeling framework is constructed by encoding prior physical knowledge of the system into a whitebox model and then embedding the output variables of the white-box model into the input vector of a black-box model. Especially, the white-box modeling component is constructed alongside the equivalent network model simplified with Kron reduction. Furthermore, case studies demonstrate that our graybox modeling approach effectively improves estimation accuracy compared to purely physics-based or data-driven methods.

Zhang, Junhui↗
DOE OSTI2023

Deep-Learning-Based Koopman Modeling for Online Control Synthesis of Nonlinear Power System Transient Dynamics

Power system stability and control have become more challenging due to the increasing uncertainty associated with renewable generation. Here, the performance of conventional control is highly driven by the physics-based offline-developed dynamic models that can deviate from the actual system characteristics under different operating conditions and/or configurations. Data-driven approaches based on online measurements can be a better solution to addressing these issues by capturing real-time operation conditions. This article describes a novel fully data-driven probabilistic framework to derive a linear representation of postcontingency grid dynamics and online prescribe control based on the derived model to enhance transient stability. The complex nonlinear power system dynamics is approximated by a linear model by using multiple neural network modules that infer distributions of the observations and introducing a Koopman layer to sample possible Koopman linear models from the inferred distributions. The trained model features linearity that can be easily incorporated into the existing linear control design paradigm and ease the controller design process. The effectiveness of Koopman-based control designs is validated through comparative case studies, which demonstrate increased prediction accuracy and control performance when applied to a power system with heterogeneous generator dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

The effect of capturing the correct turbulence dissipation rate in BHR

In this manuscript, we discuss the shortcoming of a quasi-equilibrium assumption made in the BHR closure model. Turbulence closure models generally assume fully developed turbulence, which is not applicable to 1) non-equilibrium turbulence (e.g. change in mean pressure gradient) or 2) laminar-turbulence transition flows. Based on DNS data, we show that the current BHR dissipation equation [modeled based on the fully developed turbulence phenomenology] does not capture important features of nonequilibrium flows. To demonstrate our thesis, we use the BHR equations to predict a non-equilibrium flow both with the BHR dissipation and the dissipation from DNS. We find that the prediction can be substantially improved, both qualitatively and quantitatively, with the correct dissipation rate. We conclude that a new set of nonequilibrium phenomenological assumptions must be used to develop a new model equation for the dissipation to accurately predict the turbulence time scale used by other models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗