Search NASA⌕ Search

SEARCH · Search NASA

Results for “Complex Loading”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Understanding materials microstructure and behavior at the mesoscale

Taking the mesoscale to mean length and time scales at which a material’s behavior is too complex to be understood by construction from the atomistic scale, we focus on three-dimensional characterization and modeling of mesoscale responses of polycrystals to thermal and mechanical loading. Both elastic and plastic internal structural responses are now accessible via high-energy x-ray probes. The combination of diffraction experiments and computed tomography, for example, is yielding new insights into how void formation correlates with microstructural features such as grain boundaries and higher-order junctions. The resulting large, combined data sets allow for validation of micromechanical and thermal simulations. As detectors improve in resolution, quantum efficiency, and speed of readout, data rates and data volumes present computational challenges. Spatial resolutions approach one micrometer, while data sets span a cubic millimeter. Examples are given of applications to tensile deformation of copper, grain growth in nickel and titanium, and fatigue cracks in superalloys.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Scalable Coordination and Control for Multiple Microgrids: Ten Month Progress Report

The incorporation of distributed energy resources into existing distribution systems provides make voltage and frequency regulation challenging for distribution system operators and in sufficient concentrations can destabilize the power grid. Re-configuring our distribution systems as a system of connected microgrids is one method for mitigating these instabilities. However, there is little economic reason for distribution system operators to undertake this complex upgrade of their systems. By looking beyond voltage, frequency, and power regulation for microgrids, new methods for controlling and operating microgrids can provide new functionality such as load flattening that will benefit distribution systems operators. This report details the initial research into new scalable coordination and control techniques that could be used to add this new functionality.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

EV Charging Infrastructure Energization: An Overview of Approaches for Simplifying Processes and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure and electricity. Growth in electricity demand from EV charging, coupled with growth in other sectors like data centers and electrification of other sectors, is impacting electricity infrastructure and load service request processes after two decades of relatively flat electricity demand. While most electric vehicle charging occurs at home, enroute and depot charging for medium and heavy-duty vehicles, both using high-powered EV charging, are critical to meet electric vehicle operational needs. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have expressed distress that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Large-Scale Compute-Intensive Analysis via a Combined In-situ and Co-scheduling Workflow Approach

Large-scale simulations can produce tens of terabytes of data per analysis cycle, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in situ and co-scheduling approaches for handling Petabyte-size outputs. An initial in situ step is used to reduce the amount of data to be analyzed, and to separate out the data-intensive tasks handled off-line. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.

Big data↗
DOE OSTI2020

Treatment of Problematic Reactive Metal Wastes Using GeoMelt ICV - WM2020 Conference Paper

Decommissioning of sodium-cooled reactors and fast reactor technologies has generated a number of reactive metal waste configurations that are problematic to treat and typically lack cost effective treatment methods and disposition options. As a result, Veolia Nuclear Solutions, under contract with Idaho National Laboratory (owned by the U.S. Department of Energy and managed and operated by Battelle Energy Alliance, LLC) demonstrated its GeoMelt® In-Container Vitrification (ICV)™ technology to safely convert sodium metal to a non-reactive vitrified oxide form. The demonstration project, supported by glass formulation and crucible testing, consisted of a series of ICV™ melts that processed elemental sodium into stable non-reactive glass. INL is currently implementing GeoMelt® technology as a means to safely and reliably convert radioactive reactive metal residues that contaminate sodium cooled reactor components into waste forms that comply with existing disposition pathways. Reactive metal wastes require treatment in order to remove the Resource Conservation and Recovery Act (RCRA) reactivity and ignitability characteristics to comply with land disposal restrictions. GeoMelt®, which is an alternative to other potential treatment approaches, provides a robust approach that chemically converts the reactive metals to an inert oxide while also immobilizing radionuclides in a vitrified waste form with durability equal to or better than vitrified nuclear fuel reprocessing wastes (very robust and inert waste forms). Most other treatment approaches generate hydrogen gas which is problematic. In 2016, Veolia Nuclear Solutions first demonstrated the effectiveness of the GeoMelt® ICV™ process in deactivating reactive sodium metal. Crucible, bench-scale, and engineering-scale demonstrations were conducted on several surrogate waste configurations with various ratios of sodium metal and glass-formers. Each ratio and configuration demonstrated complete deactivation of the surrogate sodium metal. Follow-on work in 2017 demonstrated the deactivation of reactive sodium by GeoMelt® ICV™ at a higher waste loading relative to previously demonstrated work performed in 2016; the higher waste loading optimized glass chemistry while enhancing the economical full-scale treatment of reactive metals. Additionally, follow-on demonstration testing in 2018 and 2019 focused on more complex shapes and other reactive-metals (mocked up Experimental Breeder Reactor II [EBR-II] subassembly, sodium filled heat exchanger, and a can containing sodium potassium alloy) which were all performed at engineering-scale. Since 2018, a 10-metric ton full-scale GeoMelt unit (GeoMelt® Richland) was designed, installed, and commissioned at Perma-Fix Northwest in Richland, Washington for the treatment of reactive metal wastes. As of September 2019, over 900 55-gallon drums containing a total of around 3,500 lb of sodium with low levels of radioactivity have been treated at GeoMelt ® Richland, with resulting glass monoliths disposed at the Nevada National Security Site (NNSS). A full-scale radiological demonstration melt on an actual EBR-II subassembly has also been performed using the full-scale melter in 2019. The GeoMelt® technology is a proven radioactive waste treatment technology capable of immobilizing radioactive wastes, including bulk rubble such as drums and other steel vessels usually without pretreatment. Utilizing the GeoMelt® technology to treat reactive metals eliminates pretreatment steps resulting from having to separate the reactive metal from steel containers or jackets as GeoMelt® can easily operate at temperatures sufficient to melt the steel and expose the reactive metal for treatment. Eliminating handling steps of reactive metals is a significant safety advantage since reactive metals are pyrophoric. The results generated as a part of the 2018-2019 demonstration program are presented in the paper.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Treatment of Problematic Reactive Metal Wastes Using the GeoMelt{sup R} In-Container Vitrification (ICV{sup TM}) Process - 20326

Decommissioning of sodium-cooled reactors and fast reactor technologies has generated a number of reactive metal waste configurations that are problematic to treat and typically lack cost effective treatment methods and disposition options. As a result, Veolia Nuclear Solutions, under contract with Idaho National Laboratory (owned by the U.S. Department of Energy and managed and operated by Battelle Energy Alliance, LLC) demonstrated its GeoMelt{sup R} In-Container Vitrification (ICV){sup TM} technology to safely convert sodium metal to a non-reactive vitrified oxide form. The demonstration project, supported by glass formulation and crucible testing, consisted of a series of ICV{sup TM} melts that processed elemental sodium into stable non-reactive glass. INL is currently implementing GeoMelt{sup R} technology as a means to safely and reliably convert radioactive reactive metal residues that contaminate sodium cooled reactor components into waste forms that comply with existing disposition pathways. Reactive metal wastes require treatment in order to remove the Resource Conservation and Recovery Act (RCRA) reactivity and ignitability characteristics to comply with land disposal restrictions. GeoMelt{sup R}, which is an alternative to other potential treatment approaches, provides a robust approach that chemically converts the reactive metals to an inert oxide while also immobilizing radionuclides in a vitrified waste form with durability equal to or better than vitrified nuclear fuel reprocessing wastes (very robust and inert waste forms). Most other treatment approaches generate hydrogen gas which is problematic. In 2016, Veolia Nuclear Solutions first demonstrated the effectiveness of the GeoMelt{sup R} ICV{sup TM} process in deactivating reactive sodium metal. Crucible, bench-scale, and engineering-scale demonstrations were conducted on several surrogate waste configurations with various ratios of sodium metal and glass formers. Each ratio and configuration demonstrated complete deactivation of the surrogate sodium metal. Follow-on work in 2017 demonstrated the deactivation of reactive sodium by GeoMelt{sup R} ICV{sup TM} at a higher waste loading relative to previously demonstrated work performed in 2016; the higher waste loading optimized glass chemistry while enhancing the economical full-scale treatment of reactive metals. Additionally, follow-on demonstration testing in 2018 and 2019 focused on more complex shapes and other reactive-metals (mocked up Experimental Breeder Reactor II [EBR-II] subassembly, sodium filled heat exchanger, and a can containing sodium potassium alloy) which were all performed at engineering scale. Veolia Nuclear Solutions designed, installed, and commissioned in September 2018, at Perma-Fix Northwest in Richland Washington, a 10-metric ton full-scale GeoMelt unit (GeoMelt{sup R} Richland) for the treatment of reactive metal wastes. As of September 2019, over 900 55-gallon drums containing a total of around 3,500 lb of sodium with low levels of radioactivity have been treated at GeoMelt{sup R} Richland, with resulting glass monoliths disposed at the Nevada National Security Site (NNSS). A full-scale radiological demonstration melt on an actual EBR-II subassembly has also been performed using the full-scale melter in 2019. The GeoMelt{sup R} technology is a proven radioactive waste treatment technology capable of immobilizing radioactive wastes, including bulk rubble such as drums and other steel vessels usually without pretreatment. Utilizing the GeoMelt{sup R} technology to treat reactive metals eliminates pretreatment steps resulting from having to separate the reactive metal from steel containers or jackets as GeoMelt{sup R} can easily operate at temperatures sufficient to melt the steel and expose the reactive metal for treatment. Eliminating handling steps of reactive metals is a significant safety advantage since reactive metals are pyrophoric. The results generated as a part of the 2018-2019 demonstration program are presented in the paper. (authors)

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

Tunable Porosity in Fused Filament 3D-Printed Blends of Intrinsically Porous Polymer and Thermoplastic Aliphatic Polyesters Polycaprolactone and Polylactic Acid

Future advances and usage of all-organic polymeric materials with permanent void spaces and high surface areas, in applications such as separations or as supports, depends heavily on the development of processing techniques to produce complex geometry objects. Here, the high free volume glassy microporous polymer PIM-1 was fabricated, as a major component in a polymer blend, into complex and customizable 3D objects by fused filament fabrication (FFF). PIM-1 was found to be compatible with polycaprolactone (PCL) and polylactic acid (PLA) and thus could be processed by extrusion into filaments with high loadings of PIM-1 (50% by mass). Ternary PCL/PLA/PIM-1 composite filaments provided an optimal balance of durability and melt flow characteristics for consistent FFF 3D printing of intricate structures. As printed, the micropores of PIM-1 were blocked and inaccessible to N2 during sorption experiments; however, the ternary composite structures displayed significant meso- and macroporosity and nanostructured phase separation. Postprinting immersion in 3-chloro-1-propanol was identified to selectively remove PCL within the composites, re-expose the characteristic micropores of PIM-1, and retain the macrostructure of the printed object. After postprinting treatments, specific surface areas by the Brunauer–Emmett–Teller method (as high as 460 m2 g–1) were found to directly correlate with the PCL content originally present. In conclusion, the extrusion-based processing methodology provides a new approach for production of intrinsically porous polymer objects in custom and complex shapes by reinforcement with thermoplastics (PCL and PLA).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identification of crystal plasticity model parameters by multi-objective optimization integrating microstructural evolution and mechanical data

Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.

42 ENGINEERING↗
DOE OSTI2023

Bayesian optimal experimental design for constitutive model calibration

Computational simulation is increasingly relied upon for high/consequence engineering decisions, which necessitates a high confidence in the calibration of and predictions from complex material models. However, the calibration and validation of material models is often a discrete, multi-stage process that is decoupled from material characterization activities, which means the data collected does not always align with the data that is needed. To address this issue, an integrated workflow for delivering an enhanced characterization and calibration procedure—Interlaced Characterization and Calibration (ICC)—is introduced and demonstrated. Further, this framework leverages Bayesian optimal experimental design (BOED), which creates a line of communication between model calibration needs and data collection capabilities in order to optimize the information content gathered from the experiments for model calibration. Eventually, the ICC framework will be used in quasi real-time to actively control experiments of complex specimens for the calibration of a high-fidelity material model. This work presents the critical first piece of algorithm development and a demonstration in determining the optimal load path of a cruciform specimen with simulated data. Calibration results, obtained via Bayesian inference, from the integrated ICC approach are compared to calibrations performed by choosing the load path a priori based on human intuition, as is traditionally done. The calibration results are communicated through parameter uncertainties which are propagated to the model output space (i.e. stress–strain). In these exemplar problems, data generated within the ICC framework resulted in calibrated model parameters with reduced measures of uncertainty compared to the traditional approaches.

42 ENGINEERING↗
DOE OSTI2022

Grid impact analysis using controller-hardware-in-the-loop for high-power vehicle charging stations

A controller-hardware-in-the-loop (CHIL) architecture for the evaluation of grid impacts arising from high-power vehicle charging stations is presented in this paper. Unlike simulation-based studies, the proposed method can be used to capture the interactions of the grid and the charging load along with charger controllers in real time. The proposed method can be used to evaluate the impact of charging load on the grid in terms of voltage variations and line congestion. The proposed CHIL platform allows for de-risking the vehicle charging station deployment by simulating the complex interactions among all the components of a vehicle charging station - i.e., the grid, vehicle, and charger controller - in a realistic manner before using the charging station in a grid. Further, the proposed CHIL approach can be used to evaluate the voltage regulation causalities of the vehicle charging station. Experimental results are presented in the paper to illustrate the applicability of the proposed method in a laboratory environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Self-Assembly of Supramolecular Thin Films: Role of Small Molecule and Solvent Vapor Annealing

Block copolymer (BCP)-based supramolecules offer a versatile platform to generate hierarchically assembled nanostructures with inherent functions. However, the multicomponent supramolecular system is complex, and there is a limited understanding of the self-assembly process which is critical for precise control of the nanostructure. As such, the effect of small molecule loading and the solvent annealing condition on thin films of supramolecules on flat and patterned substrates were investigated here. There is a superposition between the effect of the small molecule loading and solvent annealing condition that can be used to control the assembly rate, grain size, and feature size. The final film features are a result of the kinetic pathway taken during the assembly process. On patterned substrates with linear or circular trenches, the assembly is not driven by incommensurability as is commonly seen in BCP thin films but rather by the kinetic pathway. The present study offers insight into the importance of systematic studies in the kinetic process in self-assembly of multicomponent systems.

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

The Viscoplastic Behavior of Natural Hydrate‐Bearing Sandy‐Silts Under Uniaxial Strain Compression ( K 0 Loading)

Abstract The in‐situ stress state and geomechanical properties of hydrate‐bearing sediments impact hydrate formation and gas production strategies. We explore the uniaxial strain compression and stress evolution of natural hydrate‐bearing sandy‐silts from Green Canyon Block 955 in the deep‐water Gulf of Mexico. We performed constant rate of strain uniaxial strain experiments, interrupted by periods where we held the axial stress constant, to explore the vertical deformation and the evolution of the ratio of lateral to axial effective stress ( K 0 ) with time. The hydrate‐bearing sandy‐silt is stiffer and has a larger K 0 than the equivalent hydrate‐free sediment upon loading. During stress holds, the void ratio decreases sigmoidally with the log of time, and K 0 converges to isotropic conditions. We interpret that during loading, the hydrate bears the load and deforms. With time, the hydrate redistributes the load and K 0 increases. We used a viscoelastic model to describe the behavior. The model accurately captures deformation and K 0 trends but does not reproduce all the complex interactions of the hydrate with the porous skeleton. We anticipate that viscous effects within hydrate sediments will impact reservoir compression and stresses during production (hours to days), result in isotropic stress state over geological timescales, and explain the creeping movement in submarine landslides.

58 GEOSCIENCES↗
DOE OSTI2018

Equation of state, phase stability, and phase transformations of uranium-6 wt.% niobium under high pressure and temperature

In-situ time-of-flight neutron diffraction experiments were conducted on the uranium-niobium alloy with 6 wt. % Nb (U–6Nb) at pressures up to 4.7 GPa and temperatures up to 1073 K. Upon static compression at room temperature, the monoclinic structure of U–6Nb (α" U–6Nb) remains stable up to the highest experimental pressure. Based on the pressure-volume measurements at room temperature, the least-squares fit using the finite-strain equation of state (EOS) yields an isothermal bulk modulus of B 0 = 127±2 GPa for the α"-phase of U–6Nb. The calculated zero-pressure bulk sound speed from this EOS is 2.706±0.022 km/s, which is in good agreement with the linear extrapolation of the previous Hugoniot data above 12 GPa for α" U–6Nb, indicating that the dynamic response under those shock-loading conditions is consistent with the stabilization of the initial monoclinic phase of U-6Nb. Upon heating at ambient and high pressures, the metastable α" U–6Nb exhibits complex transformation paths leading to the diffusional phase decomposition, which are sensitive to applied pressure, stress state, and temperature-time path. These findings provide new insight into the behavior of atypical systems such as U-Nb and suggest that the different U-Nb phases are separated by rather small energies and hence highly sensitive to compositional, thermal, and mechanical perturbations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Transmission Expansion Planning Test System for AC/DC Hybrid Grid With High Variable Renewable Energy Penetration

Test systems are important tools and benchmark for power system research. Currently, there is a lack of standard test systems for modern transmission expansion planning (TEP) research, especially under high variable renewable energy (VRE) penetrations. This article describes a 38-bus test system named the HRP-38 system dedicated to TEP. “HRP” stands for high renewable penetration. The objective of establishing such a system is to provide a consistent platform for different TEP methods to be tested and compared. The test system considers high VRE penetration of more than 30% energy share, which will be an important feature in many power systems in the future. Both AC and DC candidate lines are given to provide sufficient transmission planning alternatives. The complexity of the test system is well balanced considering calculation tractability and the ability to test the performance of the TEP planning model. The network topology, generation mix and load characteristics are described in detail. Year-round time series of VRE (wind power and PV) output and load curves for each bus are provided to facilitate a detailed evaluation of the transmission grid configuration under high VRE penetration. Finally, four benchmark results with different optimization settings are provided for the HRP-38 system.

AC/DC hybrid↗
DOE OSTI2015

Large-scale compute-intensive analysis via a combined in-situ and co-scheduling workflow approach, In: SC '15 Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

Large-scale simulations can produce hundreds of terabytes to petabytes of data, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in-situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in-situ and co-scheduling approaches for handling petabyte-scale outputs. We compare different analysis set-ups ranging from purely off-line, to purely in-situ to in-situ/co-scheduling. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.

Computer Science↗
DOE OSTI2018

Advancing the Fork detector for quantitative spent nuclear fuel verification

The Fork detector is widely used by the safeguards inspectorate of the European Atomic Energy Community (EURATOM) and the International Atomic Energy Agency (IAEA) to verify spent nuclear fuel. Fork measurements are routinely performed for safeguards prior to dry storage cask loading. Additionally, spent fuel verification will be required at the facilities where encapsulation is performed for acceptance in the final repositories planned in Sweden and Finland. The use of the Fork detector as a quantitative instrument has not been prevalent due to the complexity of correlating the measured neutron and gamma ray signals with fuel inventories and operator declarations. A spent fuel data analysis module based on the ORIGEN burnup code was recently implemented to provide automated real-time analysis of Fork detector data. This module allows quantitative predictions of expected neutron count rates and gamma units as measured by the Fork detectors using safeguards declarations and available reactor operating data. This study describes field testing of the Fork data analysis module using data acquired from 339 assemblies measured during routine dry cask loading inspection campaigns in Europe. Assemblies include both uranium oxide and mixed-oxide fuel assemblies. More recent measurements of 50 spent fuel assemblies at the Swedish Central Interim Storage Facility for Spent Nuclear Fuel are also analyzed. An evaluation of uncertainties in the Fork measurement data is performed to quantify the ability of the data analysis module to verify operator declarations and to develop quantitative go/no-go criteria for safeguards verification measurements during cask loading or encapsulation operations. The goal of this approach is to provide safeguards inspectors with reliable real-time data analysis tools to rapidly identify discrepancies in operator declarations and to detect potential partial defects in spent fuel assemblies with improved reliability and minimal false positive alarms. Finally, the results are summarized, and sources and magnitudes of uncertainties are identified, and the impact of analysis uncertainties on the ability to confirm operator declarations is quantified.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens of thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.

25 ENERGY STORAGE↗
DOE OSTI2020

A Data-Driven Nonparametric Approach for Probabilistic Load-Margin Assessment Considering Wind Power Penetration

A modern power system is characterized by an increasing penetration of wind power, which results in large uncertainties in its states. These uncertainties must be quantified properly; otherwise, the system security may be threatened. Facing this challenge, here we propose a cost-effective, data-driven approach to assessing a power system's load margin probabilistically. Using actual wind data, a kernel density estimator is applied to infer the nonparametric wind speed distributions, which are further merged into the framework of a vine copula. The latter enables us to simulate complex multivariate and highly dependent model inputs with a variety of bivariate copulae that precisely represent the tail dependence in the correlated samples. Furthermore, to reduce the prohibitive computational time of traditional Monte-Carlo simulations that process a large amount of samples, we propose to use a nonparametric, Gaussian-process-emulator-based reduced-order model to replace the original complicated continuation power-flow model through a Bayesian-learning framework. To accelerate the convergence rate of this Bayesian algorithm, a truncated polynomial chaos surrogate, which serves as a highly efficient, parametric Bayesian prior, is developed. This emulator allows us to execute the time-consuming continuation power-flow solver at the sampled values with a negligible computational cost. Results of simulations that are performed on several test systems reveal the impressive performance of the proposed method in the probabilistic load-margin assessment.

17 WIND ENERGY↗