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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The EGS Collab Project: Stimulation and Simulation

Development of Enhanced Geothermal Systems (EGS) requires accurate predictions of flow rates and temperatures at production wells over time. The concept of EGS is simple; however, complications from heterogeneity and complexity of fracture pathways may lead to channeling, short-circuiting, and premature thermal breakthrough. In the EGS Collab project, we are establishing a suite of highly monitored and well characterized intermediate-scale (~10-20 m) field test beds along with fracture stimulation and interwell flow tests to better understand processes that control formation of effective subsurface heat exchangers. EGS Collab experiments will provide a means of testing tools and concepts that could later be employed under geothermal reservoir conditions at FORGE or elsewhere. Key to the project is using numerical simulations in the experiment design and interpretation of results. Our tests will be well-controlled, in situ experiments focused on rock fracture behavior and permeability enhancement. Our pre- and post-test modeling results of each field experiment compared with detailed measurements will allow for improved model prediction and validation. We will use comprehensive instrumentation to collect high-quality and high-resolution geophysical and other fracture characterization and fluid flow data. We will analyze these data and compare them with models and field observations to further elucidate the basic relationships between stress, induced seismicity, and permeability enhancement. We will also observe and quantify other key governing parameters that impact permeability, and will attempt to understand how these parameters might change throughout the development and operation of an EGS project with the ultimate goal of enabling commercial viability of EGS. Our first set of experiments will be performed at the Sanford Underground Research Facility (SURF) in South Dakota. Our team is well underway with building the first field experiment test bed planned for this project, which is supported by the US Department of Energy’s Geothermal Technologies Office.

EGS Collab↗
DOE OSTI2018

Generation Forecasting for Small Run-of-the-River Hydroelectric Systems Using Statistical Learning Models

With an increasing interest in constructing new run-of-the-river (ROR) hydroelectric generation over the more traditional reservoir-based hydroelectric systems, there is an increasing operational challenge due to the volatility of stream flow. The Snohomish County Public Utilities District (SnoPUD) has recently invested in the construction and operation of 3 new run-of-the-river projects in Northwestern Washington along Calligan Creek, Hancock Creek, and Youngs Creek. In order to effectively plan generation dispatch, SnoPUD has expressed interest in the development of an accurate forecasting tool to predict the generation capacity for these ROR systems. The following research project aims to use statistical learning models, namely Hidden Markov Models (HMMs), to predict day-ahead generation capacities for the aforementioned ROR systems. These models are constructed using 12 years of historical stream flow data collected at the intake sites and precipitation data recorded at the National Oceanic and Atmospheric Administration (NOAA) Alpine Meadows station. Four methods of constructing the models are studied for their forecast accuracies, and are compared with the persistence model. Despite using only one set of observable variables, the HMMs are shown to have slight improvements in accuracy over the persistence model approach, which shows great optimism for future work.

13 HYDRO ENERGY↗
DOE OSTI2020

Generic, Sparse Tensor Core for Neural Networks

Sparse neural network attracts more attention for model compression, fast execution, and power reduction. The state-of-the-art designed sparse tensor core for structured and static sparsity, which did not support well for generic or dynamic sparsity. We design a sparse tensor core to support generic sparsity pruning with a novel hybrid and blocked sparse matrix storage format, HB-ELL, which saves computation and storage while keeping the most significant elements, as well as supporting dynamic sparsity for data flow in neural networks. We achieve better performance with preliminary results than the state-of- the-art on an NVIDIA GPU simulator.

Wu, Xiaolong↗
DOE OSTI2021

Methods and apparatus to detect and annotate backedges in a dataflow graph

Disclosed examples to detect and annotate backedges in data-flow graphs include: a characteristic detector to store a node characteristic identifier in memory in association with a first node of a dataflow graph; a characteristic comparator to compare the node characteristic identifier with a reference criterion; and a backedge identifier generator to generate a backedge identifier indicative of a backedge between the first node and a second node of the dataflow graph based on the comparison, the memory to store the backedge identifier in association with a connection arc between the first and second nodes.

ChoFleming, Jr., Kermin E.↗
DOE OSTI2022

Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception: Preprint

This paper puts forth a system architecture for an infrastructure-based cooperative perception (CP) fusion engine, to provide a complete state-space digital representation, with measurable accuracy, to support a wide-range of applications. The architecture includes the inputs, functional flow, data standardization recommendations, outputs and supported applications. The CP engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure (IRI), that complements and accelerates connected and automated vehicle (CAV) technology. that the CP acquires and fuses information from sensors (radar, LiDAR, and cameras), and CAVs to intelligently perceive roadway traffic states of all moving objects, create a complete three-dimensional digital representation of that state-space, and communicate it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications for CAVs as examples. The IRI approach, as opposed to a vehicle centric approach, is found to be more scalable in that it can deployed to the roughly 300,000 signalized intersections more readily than the over 300 million vehicles in the US, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and GHG reduction.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

HIGH-LOW FIDELITY THERMAL HYDRAULIC COUPLING USING AI/MACHINE LEARNING ALGORITHMS

The primary goal of the US Department of Energy (DOE) office of Nuclear Energy Integrated Energy Systems (IES) program is to develop the tools and framework for coupling multi-scale and multi-physical thermal and electrical energy usage and storage systems. High- and low-fidelity (high–low) coupling is a key feature of multi-scale, multi-component systems and has been an important focus of research in the nuclear energy community for the past two decades. An essential feature of demonstrating the capability to couple high-fidelity and low-fidelity systems for real-time applications are surrogate/reduced order models (ROM). For the purposes of this study, surrogate models are essentially Blackbox models, typically developed using supervised Machine learning (ML) algorithms. The surrogate models can be used to mimic the response of high-fidelity models to represent large historical datasets and coupled with more general low-fidelity system models distributed as Functional Mock-up Interface (FMI) or Functional Mock-up Units (FMU) modules. The example is demonstrated with Spallation Neutron Source (SNS) First Target Station flow loop data. The flow loop is a liquid mercury loop with a pump, piping, heat exchange, and internal heat generation in the target window. This work elucidates some of the potential benefits and future needs of developing tools for high–low system coupling of energy systems.

Williams, Wesley↗
DOE OSTI2022

A next-generation toolset for the life-cycle analysis of electricity use

This works presents an overview--including background, data flow, and case study--of a tool for analyzing impacts utilizing the electricity baseline provided by ElectricityLCI and the impact-modeling techniques of Grid Mix Explorer (along with air and water quality) as a part of a next-generation LCA analytical framework.

Davis, Tyler↗
DOE OSTI2023

Analyzing Hardware and Software Common Cause Failures in Digital Instrumentation and Control Systems using Dual Error Propagation Method

This paper develops a methodology for quantifying software common cause failures (CCFs) in digital instrumentation and control (I&C) systems of nuclear power plants. To support the transition of analog I&C systems to digital in nuclear power plants, probabilistic risk assessment (PRA) techniques are used. The hardware components of the I&C systems have reliability databases that can be used in the PRA studies. However, the failure data for redundant software components of the systems is sparse. Failure of components constitutes a CCF, wherein two or more components or systems fail due to a single shared cause and coupling mechanism. This paper proposes a quantification approach that can simultaneously model hardware and software components, incorporate the CCFs of software systems in the models, and bridge the gap between the failure quantification of models and the development of CCF parametric databases. We demonstrate the dual error propagation method (DEPM) by developing I&C systems failure models for a representative digital reactor trip system. The DEPM models are built to simulate the control and data flows within the systems and can accommodate failure states. By expanding DEPM to software CCFs, we generated alpha factor parameter estimates for each of the modeled error propagation mechanisms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Methods and apparatus to detect and annotate backedges in a dataflow graph

Disclosed examples to detect and annotate backedges in data-flow graphs include: a characteristic detector to store a node characteristic identifier in memory in association with a first node of a dataflow graph; a characteristic comparator to compare the node characteristic identifier with a reference criterion; and a backedge identifier generator to generate a backedge identifier indicative of a backedge between the first node and a second node of the dataflow graph based on the comparison, the memory to store the backedge identifier in association with a connection arc between the first and second nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Experimental Technetium Release from Simulated Salt-stone Cementitious Waste Form - 18419

Experiments are being conducted to evaluate the early release of technetium (Tc) from fresh salt-stone waste forms using dynamic flow-through tests. Salt-stone is a chemically reducing, grout-based waste form used by the U.S. Department of Energy (DOE) to dispose of low-activity salt solutions arising from high-level radioactive waste tank closure activities at the Savannah River Site (SRS). A key safety function of salt-stone is maintaining a low-flow, chemically reducing environment that will attenuate the release of redox-sensitive radioelements such as Tc. Salt-stone also provides a physical barrier due to its low intrinsic permeability, which limits both water and oxygen ingress. These release experiments, conducted to support the U.S. Nuclear Regulatory Commission's monitoring role during tank closure, are designed to provide independent information on how well salt-stone will perform its safety function. The dynamic leach tests were conducted in a Hassler-type core-holder permeameter system that allows an accelerated flow rate of simulated SRS groundwater through an intact cylinder of salt-stone spiked with Tc-99 at a concentration of approximately 2,100 Bq/g (3 ppm). The first salt-stone specimen to be tested (Specimen 2) was prepared with Grade 100 ground granulated blast-furnace slag and aged for 119 days in a temperature-controlled, low-oxygen, high-humidity environment. Before test completion, 9.5 pore volumes (PV) of simulated SRS groundwater were passed through the salt-stone cylinder. After a few PV, apparent saturated hydraulic conductivity (K{sub sat}) values calculated from flow data reached a steady-state value of approximately 1.0 x 10{sup -9} cm/s, which is within the range of previously reported data. Tc-99 concentrations in leachate peaked early during the leach test at 2.0 x 10{sup -7} M and then declined to approximately 4 x 10{sup -8} M after 9.5 PV. The leachate Tc-99 concentration after elution of 9.5 PV is broadly consistent with a Tc solution concentration controlled by the solubility of reduced Tc solids. The range of Tc-99 concentrations is similar to the range reported for a column test that was sponsored by DOE, but the time pattern of release differs. The second salt-stone specimen tested (Specimen 3) was aged for 372 days and it further differed from the first specimen in that its Grade 100 slag component had been finely ground using a mortar and pestle in an attempt to make it more reactive. This second test yielded Tc release behavior broadly similar to that observed during the first test, except that the early Tc peak (at 1.2 x 10{sup -6} M) was six times higher and the concentration after 6.7 PV (8.8 x 10{sup -8} M) was approximately two times higher than in the first test. In addition, the steady-state K{sub sat} was an order of magnitude lower than that of the first specimen. During the second test, the injection pump was intentionally turned off for a period of 11 days (i.e., approximate residence time for 1 PV) and a Tc spike was observed when pumping resumed, suggesting that longer residence times may promote higher Tc effluent concentrations. During a second intentional shut-down of the pump for 25 days (approximate residence time for 2 PV), another Tc spike was observed. An unplanned excursion to higher confining pressure physically affected the specimen, temporarily lowering the apparent K{sub sat} followed by a subsequent increase in both K{sub sat} and Tc effluent concentration. One hypothesis is that the transient spike in confining pressure and resulting salt-stone compression and later decompression may have induced Tc release from otherwise inactive pores. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Commissioning of Robotic Inspection and Automated Analysis System for Assay of Gas Diffusion Piping - 19500

Robotic, in-pipe, nondestructive assay (NDA) is a revolutionary and important means for measuring, analyzing, and reporting radioactive holdup deposits in enrichment piping. This innovation promises vast advantages for efficiency, safety, and cost savings. Payoff, however, lies in utilization much more than innovation. Crossing that threshold from a technical capability to an everyday tool occurs only after rigorous commissioning, adoption, and infusion. This must meet the highest standard, and there can be no compromise. Certification of a new NDA technology must meet the highest standards for quality, safety, and efficacy. Prior to this work, there was no precedent of procedure and method for certification of a robotic methodology for this purpose. The best of robotics had not certified NDA. The best of NDA had not certified robotics. Hence, a great deal of discovery, resourcefulness, and collaboration contributed to this success. This paper chronicles the first-of-kind chartering, co-development, testing, documentation, and site integration that certified this trailblazing in-pipe, robotic NDA. Commissioning had to demonstrate and certify end-to-end NDA automation from robot traversal to computer analysis to report generation of contaminated process piping at the Portsmouth, Ohio gaseous diffusion facility. This was a rigorous campaign of tests, evaluations, and documentation. Highlights included multiple tests in four elevated pipes exercised the gamut of NDA and robotic capabilities. Each of the four test pipes presented a unique loading of U-235. The tests demonstrated operations in both 30- inch and 42-inch diameter pipes with varying lengths and terminated by a variety of valves and fittings. Tests in a fifth pipe at floor level demonstrated deployment and applicability for pipes at this ground height and robot recognition of another fitting type. All operations, calibration, deployment, auto-reporting, and analysis were handled by Portsmouth site personnel. These tests concluded a series of component-level acceptance tests which certified all constituent technologies and operational features. Test metrics included comparison of reported to ground truth results and assessment of data quality from quality assurance and replicate measurement comparison. Beyond the radiometry associated with any NDA method, this unique commissioning path exercised and evaluated all the robotic features that are intrinsic to automation. These include odometry, geometric modeling, autonomy, remote launch and recovery, and end-to-end data flow. Each of these required verification and certification. These evaluations were first-of-kind for the decommissioning community, requiring innovation and resourcefulness in their own right. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Transition to a Thorium-based Fuel Cycle - Choices, Challenges, and Options

The Charter for the Evaluation and Screening (E and S) of Nuclear Fuel Cycle Options requested by the US Department of Energy calls for the identification of promising fuel cycle options to help guide the future directions of research and development in this area. The final report for this study, which was produced by various national laboratory and industry experts, collected the expansive set of fuel cycle options into 40 evaluation groups (EGs). In support of this study, detailed steady-state physics and mass flow data for each of these groups were compiled into a set of Fuel Cycle Data Packages (FCDPs). The data in the FCDPs were then used to quantify the nine criteria detailed in the study to identify the most promising EGs. In addition to supporting the E and S study, data from these FCDPs can be used to benchmark fuel cycle simulation tools for equilibrium calculations. Once benchmarked, their dynamic modeling capabilities can support the continuing effort to determine the most effective approaches for transitioning to proposed advanced future fuel cycles. While steady-state conditions can be calculated directly in some cases, fuel cycle simulation tools allow for the transition scenarios to be simultaneously optimized on multiple parameters such as the fissile material availability, the amount of desirable material in storage, and the time required for transition. In addition to fuel cycle simulations where material availability is considered and is often a constraint to achieving transition, determining the technology needs to enable a transition to take place is also a key consideration (e.g., what technology is needed, when it is needed, and whether it is needed only during the transition and not for the equilibrium fuel cycle). This paper evaluates the material and technology issues and challenges associated with a transition from a uranium-based fuel cycle (such as that operating in the US today, represented by EG01) to a thorium-based fuel cycle, recognizing that thorium requires fissile material to start up. Based on the findings of the E and S report, the two most promising thorium fuel cycle options are considered in this report: (1) EG26, a thermal spectrum molten salt reactor (MSR), and (2) EG28, represented by a sodium fast reactor (SFR, fast spectrum) and a resource-renewable boiling water reactor (RBWR, intermediate spectrum). (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Co-Simulation of PSS/E, OpenDSS, and PSCAD for Power Systems Stability Analysis With Inverter-Based Resources: Preprint

The increasing penetration of inverter-based resources (IBRs) is reshaping the dynamic behavior of power systems. IEEE standard 1547-2018 suggests that distributed energy resources (DERs) should provide grid services such as voltage and frequency supports. On the other hand, dynamic events caused by IBRs such as sub-synchronous oscillation have been reported. These developments necessitate improvement in the current modeling capabilities to better understand the interdependencies within power systems. These include interactions between transmission and distribution systems, among IBRs themselves, and between IBRs and conventional resources. In this paper, we present a co-simulation model integrating PSS/E, OpenDSS, and PSCAD to analyze IBR impacts on the stability of transmission and distribution systems. A key challenge in developing a co-simulation model is ensuring interoperability among different simulators (interfacing and data flow) while maintaining accurate results. Using the developed model, we simulate the impact of IBRs on power systems in two test cases: 1) fault ride through (FRT) capability during a generation trip contingency; 2) IBR-induced sub-synchronous oscillation. The results show the effectiveness of the co-simulation model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1984

Comparison of viscous-shock-layer heating analysis with Shuttle flight data in slip flow regime

Comparison of STS-2 Shuttle flight heating data along the windward centerline has been made with two-dimensional nonequilibrium viscous shock-layer solutions obtained with shock and wall-slip conditions at an altitude range of 90 to 110 km. The shock slip condition used is the modified Rankine-Hugoniot relations of Cheng as used by Davis, and the wall-slip conditions are based on the first order consideration derived from kinetic theory as given by Scott and Hendricks. The results indicate that the calculated heating distributions with slip boundary conditions agree better with the flight data than those without slip conditions. The agreement improves when the accommodation coefficient or freestream density is decreased to one-half, suggesting the possibility of less than full accommodation for the tile surface and (or) an overestimate of freestream density using the Jacchia-Roberts model. Heating reduction due to the slip effect becomes very pronounced as the flow becomes more rarefied, and the effect is more significant for the stagnation region than the aft region of the vehicle.

Shinn, J. L.↗
NASA NTRS2003

Testing of RANS Turbulence Models for Stratified Flows Based on DNS Data

In most geophysical flows, turbulence occurs at the smallest scales and one of the two most important additional physical phenomena to account for is strati cation (the other being rotation). In this paper, the main objective is to investigate proposed changes to RANS turbulence models which include the effects of stratifi- cation more explicitly. These proposed changes were developed using a DNS database on strati ed and sheared homogenous turbulence developed by Shih et al. (2000) and are described more fully in Ferziger et al. (2003). The data generated by Shih, et al. (2000) (hereinafter referred to as SKFR) are used to study the parameters in the k- model as a function of the turbulent Froude number, Frk. A modified version of the standard k- model based on the local turbulent Froude number is proposed. The proposed model is applied to a stratified open channel flow, a test case that differs significantly from the flows from which the modified parameters were derived. The turbulence modeling and results are discussed in the next two sections followed by suggestions for future work.

Venayagamoorthy, S. K.↗
DOE OSTI2021

Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

This study explores the usefulness of machine learning classifiers for modeling freight mode choice. We investigate eight commonly used machine learning classifiers, namely Naïve Bayes, Support Vector Machine, Artificial Neural Network, K-Nearest Neighbors, Classification and Regression Tree, Random Forest, Boosting and Bagging, along with the classical Multinomial Logit model. US 2012 Commodity Flow Survey data are used as the primary data source; we augment it with spatial attributes from secondary data sources. The performance of the classifiers is compared based on prediction accuracy results. The current research also examines the role of sample size and training-testing data split ratios on the predictive ability of the various approaches. In addition, the importance of variables is estimated to determine how the variables influence freight mode choice. The results show that the tree-based ensemble classifiers perform the best. Specifically, Random Forest produces the most accurate predictions, closely followed by Boosting and Bagging. With regard to variable importance, shipment characteristics, such as shipment distance, industry classification of the shipper and shipment size, are the most significant factors for freight mode choice decisions.

42 ENGINEERING↗
DOE OSTI2021

Critical analysis of velocimetry methods for particulate flows from synthetic data

Particle tracking methods that extract high-fidelity particle velocity data from high speed video of particle laden flows is a common experimental technique applied to chemical processes. These measurements are used to better understand the motion of particles and fluids in complex systems and create data against which computational models are validated. However, the methods, codes, and experimental setups all have limitations. It is imperative that practitioners verify the methods and their implementation as well as understand the limitations of experimental setups. This work focuses on quantifying the visible depth of field in a high particle concentration fluidized bed. Following a precedent set by the particle imaging velocimetry community, a particle velocity field is manufactured using a computational fluid dynamics and discrete element method simulation. Photo realistic high-speed videos are rendered based on the simulated data using the three-dimensional creation software Blender. Particle velocities are extracted from the synthetic high-speed videos using three variants of Particle Tracking Velocimetry and Optical Flow Velocimetry methodologies. Here, the tracked results are then compared to the known solution, quantifying the error associated with the assumed visible depth. The results indicate that at depth of one particle diameter, all three particle tracking codes give accurate measurements, largely within 5%. However, the error increases when the full bed video measurements are compared to the known solution at one particle diameter, i.e., mimicking a validation study. Finally, for some statistics the constant depth assumption only increases the error slightly, for others significantly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗