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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Intelligent load pattern modeling and denoising using improved variational mode decomposition for various calendar periods

This paper proposes a novel approach to identify the load patterns considering calendar impact and denoising process, which advances the state of art of load identification and load forecasting to a more flexible and adaptive extent by revealing the correlation between load profile and the substantial influence factors. With the rapid development and the promising application of energy intemet and grid modernization, the accurate load modeling and forecasting especially by load pattern modeling (LPM) have become more and more critical to observe and estimate load profile so as to optimize the operation efficiency of the power grid. Traditional methods mostly focus on the static LPM itself which are unable to account the non-linear and highly dynamic load fluctuations in order to balance the demand of the power grid during various calendar period (VCP) scheduling. In this paper, a load pattern modeling method for power grid considering the impact of typical calendar effects is proposed using a combination of improved variational mode decomposition (IVMD) and deep belief network (DBN) algorithm. Firstly, an index of load curve curvature (LCC) is proposed to improve the selection of value K in the conventional VMD algorithm. The value K of the intrinsic modality is determined by adopting LCC to better quantify the average instantaneous frequency of the modal decomposition of the VMD and to reduce the elevated stochasticity of k. Secondly, an optimization formulation is developed based on adaptive segmented loop decomposition of the typical correlation coefficient to suppress the edge effect in VMD decomposition, which would enable the reconstructed curve to incorporate the variabilities from the initial data. Finally, the IVMD and DBN algorithms are jointly implemented to optimize the accuracy of VCP load pattern modeling curve regression. Numerical examples have been performed with the results proving that the proposed method significantly outperforms the state-of-art in reducing the modeling error of VCP load curve, improving the overall forecasting accuracy, and reducing load dispatching cost.

deep belief network↗
DOE OSTI2022

Comparisons of Nodal diffusion and whole-core transport methods for multiple cycles of a small Light water reacto

As part of a cooperative research and development agreement between the US department of Energy's Oak Ridge National Laboratory and Holtec International subsidiary SMR LLC, core simulator models of the SMR-160, a light water-cooled and -moderated, natural circulation, small modular reactor, were developed and compared. The model results indicate pin-by-pin power histories, critical boron concentration, and other key performance indicators useful for developing multi-cycle core loading patterns. One model uses industry standard nodal methods with a simple thermal-hydraulics solution, and the other uses an advanced deterministic neutronics solver with a coupled subchannel calculation. The goals of the comparison are to provide the reactor designer with a detailed and coupled core physics reference solution, inform the reactor designer of nodal model best practices based on the code-to-code comparison, and set up a workflow for performing subsequent detailed core simulator calculations. The results of this work will be used in the development of coupled neutronic, thermal hydraulic, and fuel performance models for advanced analysis of the SMR-160. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.

Computer Science↗
DOE OSTI2016

Impact of Uncertainty from Load-Based Reserves and Renewables on Dispatch Costs and Emissions

Aggregations of controllable loads are considered to be a fast-responding, cost-efficient, and environmental-friendly candidate for power system ancillary services. Unlike conventional service providers, the potential capacity from the aggregation is highly affected by factors like ambient conditions and load usage patterns. Previous work modeled aggregations of controllable loads (such as air conditioners) as thermal batteries, which are capable of providing reserves but with uncertain capacity. A stochastic optimal power flow problem was formulated to manage this uncertainty, as well as uncertainty in renewable generation. In this paper, we explore how the types and levels of uncertainty, generation reserve costs, and controllable load capacity affect the dispatch solution, operational costs, and CO2 emissions. We also compare the results of two methods for solving the stochastic optimization problem, namely the probabilistically robust method and analytical reformulation assuming Gaussian distributions. Case studies are conducted on a modified IEEE 9-bus system with renewables, controllable loads, and congestion. We find that different types and levels of uncertainty have significant impacts on dispatch and emissions. More controllable loads and less conservative solution methodologies lead to lower costs and emissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

A Hybrid Demand Response Simulator Version 1.0

A hybrid demand response simulator is developed to test different control algorithms for centralized and distributed demand response (DR) programs in a small distribution power grid. The HDRS is designed to model a wide variety of DR services such as peak having, load shifting, arbitrage, spinning reserves, load following, regulation, emergency load shedding, etc. The HDRS does not model the dynamic behaviors of the loads, rather, it simulates the load scheduling and dispatch process. The load models include TCAs (water heaters, air conditioners, refrigerators, freezers, etc) and non-TCAs (lighting, washer, dishwasher, etc.) The ambient temperature changes, thermal resistance, capacitance, and the unit control logics can be modeled for TCA loads. The use patterns of the non-TCA can be modeled by probability of use and probabilistic durations. Some of the communication network characteristics, such as delays and errors, can also be modeled. Most importantly, because the simulator is modular and greatly simplified the thermal models for TCA loads, it is very easy and fast to be used to test and validate different control algorithms in a simulated environment.

Lu, Ning↗
DOE OSTI2013

Simulation of Wind Turbine Performance and Loading Patterns using a Coupled Meso-scale/Micro-scale Flow Analysis Model

HELIOS simulations were conducted for the WPS-30 turbine from the Sexbierum experimental site. The MMCI module was used to include the effects of the atmospheric boundary layer using the strategy described in the methodology section. In Figure 1 , the thrust and power variation for the WRF/Helios (Meso-scale/micro-scale simulation) is compared with measured power and stand-alone Helios computations (uniform inflow). The unsteady variations in power and thrust caused by the turbulent inflow conditions is clearly evident from these figures. Note that the mean hub height velocity could not be exactly matched to the uniform inflow values of 8 m/s because of constraints in adjusting the geostrophic wind and roughness length in Meso-scale WRF simulations. The offset in mean power and thrust notable in the figures are because of the small difference in the mean wind speed. Nonetheless, these results provide proof-of-concept of the integrated Meso-scale/Micro-scale simulation capability developed as part of this work. To further substantiate the effects of turbulent inflow, flow visualizations (iso-surfaces of vorticity overlaid on contours of velocity magnitude) are shown in Figure 2 . Meandering of the vortex wake and eventual breakdown are observed in the flow visualizations. Vortex breakdown is observed to occur between 1.5 and 2.5 diameter distance from the turbine. In uniform inflow (not shown here), the vortex wake persists to much longer distance of about 5 diameters before beginning to breakdown. It is expected that the vortex breakdown will be strongly correlated with the turbulence intensity of the inflow. The capability developed herein provides enabling technology for analyzing and characterizing such effects.

17 WIND ENERGY↗
DOE OSTI2021

Periodicity Analysis of Earthquake Occurrence and Hypocenter Depth Near Parkfield, California, 1994–2002 Versus 2006–2014

In central California, periodic earthquake occurrence suggests a relationship with annual hydrological, atmospheric, thermal, and tidal loadings. Here, in catalogs of declustered earthquakes within 100 km from Parkfield, CA, we study a semiannual periodicity for the monthly number of ≤7.2-km-deep earthquakes and the monthly median hypocenter depth over 1994–2002 and 2006–2014. Peak-trough months in fitted periodic components differ between time spans and event populations. Deeper earthquakes present no semiannual and a weak annual periodicity. Although modeled pore pressure shows a Spring peak, when added to the elastic Coulomb stress from surface hydrospheric loads, it fails to predict a 6-month periodicity for 2006–2014. In 1994–2002, the pore-pressure amplitude appears to be of same order as the elastic stress and may have had a stronger effect. In 2006–2014, we did not find load model parameters explaining the observed pattern or apparent changes following the 2003 San Simeon and 2004 Parkfield earthquakes.

58 GEOSCIENCES↗
DOE OSTI2023

A simple, validated approach for design of two-dimensional periodic particle patterns via acoustophoresis

Two-dimensional patterning of microparticles enables a wide range of functional materials, including patterned energy storage electrodes, flexible electronics, and sensor arrays. Particle patterning via acoustics offers an attractive path to generate a wide variety of 2D periodic patterns that introduce tailorable hierarchical porosity, useful for controlling surface area, transport distances, and other properties. This method is most effective with micron scale particles and patterns of tens to hundreds of microns. To enable systematic exploration of the broad design space for such patterns, this work develops a model of 2D and 3D assembly of particles at high loadings and validates the obtained patterns against both experiments and more computationally intensive modeling techniques. Using this simple model, connections are mapped between input parameters (like actuation conditions, particle volume fraction, material properties) and output geometrical features (like void size and shape, pattern connectivity, and surface area) so that they can be tailored to given applications. The utility of this simple model is illustrated by predicting and then experimentally demonstrating new hierarchical patterns resulting from multiple waves of different frequencies interacting. These multiscale patterns offer the potential to lift the limits on surface area, diffusion distances, and other features.

42 ENGINEERING↗
DOE OSTI2021

Characterizing patterns and variability of building electric load profiles in time and frequency domains

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. Furthermore, the commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Novel Method for Controlling Crud Deposition in Nuclear Reactors Using Optimization Algorithms and Deep Neural Network Based Surrogate Models

This work presents the use of a high-fidelity neural network surrogate model within a Modular Optimization Framework for treatment of crud deposition as a constraint within light-water reactor core loading pattern optimization. The neural network was utilized for the treatment of crud constraints within the context of an advanced genetic algorithm applied to the core design problem. This proof-of-concept study shows that loading pattern optimization aided by a neural network surrogate model can optimize the manner in which crud distributes within a nuclear reactor without impacting operational parameters such as enrichment or cycle length. Several analysis methods were investigated. Analysis found that the surrogate model and genetic algorithm successfully minimized the deviation from a uniform crud distribution against a population of solutions from a reference optimization in which the crud distribution was not optimized. Strong evidence is presented that shows boron deposition in crud can be optimized through the loading pattern. This proof-of-concept study shows that the methods employed provide a powerful tool for mitigating the effects of crud deposition in nuclear reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

WE-A-17A-05: Differences in Applicator Configuration and Dwell Loading Between Standard and Image-Guided Tandem and Ring (T and R) HDR Brachytherapy

Purpose: To investigate differences in: (i) relative location of the tandem and the ring compared to a rigid standard applicator model; and (ii) relative loading and changes in loading pattern between standard and image-guided planning. Methods: All T and R insertions performed in 2013 in our institution under CT- or MR-guidance were analyzed. Standard plans were generated using library applicator models with a fixed relationship between ring and tandem, standardized uniform dwell loading and normalization to point A. The graphic plans and the associated standard-plan dwell configurations were compared: the rings were rigidly registered, and the residual tandem shift, rotation and maximum distance between plan tandem dwell and corresponding model tandem dwell were calculated. The normalization ratio (NR = the ratio of graphic versus standard-plan total reference air kerma [TRAK]), the general loading difference (GLD = the difference between graphic and standard ratios of the tandem versus the ring TRAK), and the percent standard deviation (SD% = SD/mean) of the tandem and the ring TRAK for the graphic plan (all standard-plans SD% = 0) were calculated. Results: 71 T and R were analyzed. Residual tandem shift, rotation and maximum corresponding dwell distance were 1.2±0.8mm (0.4±0.4mm lateral, 0.9±0.8mm craniocaudal, 0.4±0.3mm anterior-posterior), 2.3±1.9deg and 3.4±2.3mm. NR was 0.86±0.11 indicating a lower overall loading of the graphic compared to the standard plans. GLD was -0.12±0.16 indicating a modest increased ring loading relative to the tandem in the graphic plans. SD% was 2.1±1.6% for tandem and 2.8±1.9% for ring, indicating small deviations from uniform loading. Conclusion: Variability in the relative locations of the tandem and the ring necessitates the independent registration of each component model for accurate digitization. Our clinical experience suggests that graphically planned T and R results on average in a lower total dose to the patient, and in an increased relative loading of the ring component.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Damage of prismatic lithium‐ion cells subject to bending: Test, model, and detection

Abstract The mechanically induced internal short circuit (ISC) is one of the major safety concerns of lithium‐ion batteries. Mechanical abuse tests are often performed to evaluate the integrity and safety of lithium‐ion batteries under mechanical loadings. Except for the widely explored compression‐dominated indentation tests, bending is another typical real‐world loading condition that is tension‐dominated. To investigate the mechanical damage and ISC behavior of batteries under bending, we carried out controlled three‐point bending tests in four progressive steps on prismatic battery cells with maximum deflections ranging from 38% to 76% of the cell thickness. None of the tested cells experienced an ISC. We then conducted 3D X‐ray computed tomography (CT) scanning on the bent cells after unloading. X‐ray CT images showed three out of the four tested cells have extensive cracking in the electrode layers at the bottom side (opposite to the loading head). This indicates that cracking does not necessarily lead to an ISC under bending. Electrochemical impedance spectroscopy was also measured on the bent cells and substantial changes were observed. Both the bulk resistance and charge‐transfer resistance increased significantly after bending, which could influence the battery performance and lifespan. We then developed a detailed finite (FE) element model to further investigate the mechanical deformation and failure mechanisms. The FE model successfully predicts the load–displacement response and reproduces the deformation patterns. The findings and the FE model developed in the present study provide useful insights and tools for the battery structure and crash safety design. image

25 ENERGY STORAGE↗
DOE OSTI2023

Differences In High Burnup Fuel Management Strategies to Minimize FFRD and Increase Economic Viability

The nuclear industry is pursuing approval of an increase in the length of the pressurized water reactor (PWR) cycle from 18 months to 24 months to reduce reactor downtime and enhance the economic competitiveness of nuclear energy. Such an increase in reactor cycle length will require that the maximum rod average burnup exceeds the current regulatory limit of 62 GWd/MTU, and it could peak at approximately 75 GWd/MTU, posing potential reactor safety and performance concerns. One such concern is that fuel fragmentation, relocation, and dispersal (FFRD) could occur during a severe loss-of coolant accident (LOCA) in which a fuel rod balloons and bursts, and pulverized fuel fragments are dispersed throughout the reactor’s primary coolant system. Previous analyses have identified which reactor operating conditions leave the core more susceptible to FFRD and have shown that FFRD susceptibility is strongly linked to fuel rod burnup and linear heat rate (LHR) history. The work described in this report uses an optimization strategy known as parallel simulated annealing (PSA) and a coarse mesh Purdue Advanced Reactor Core Simulator (PARCS) reactor physics model to develop two core fuel loading patterns, each with a different optimization objective. One core optimization maximized the core’s cycle length while still respecting regulatory limits on the radial peaking factor and soluble boron concentration with a peak rod average burnup of 75 GWd/MTU. The second optimization was aimed at minimizing FFRD susceptibility while still targeting a 24-month cycle length and respecting regulatory limits. PARCS model predictions were verified using the high-fidelity Virtual Environment for Reactor Applications (VERA). The two core designs were compared to highlight core design strategies to minimize FFRD susceptibility and to maximize economic viability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Joint Estimation of Behind-the-Meter Solar Generation in a Community

Distribution grid planning, control, and optimization require accurate estimation of solar photovoltaic (PV) generation and electric load in the system. Most of the small residential solar PV systems are installed behind-the-meter making only the net load readings available to the utilities. This paper presents an unsupervised framework for joint disaggregation of the net load readings of a group of customers into the solar PV generation and electric load. Our algorithm synergistically combines a physical PV system performance model for individual solar PV generation estimation with a statistical model for joint load estimation. The electric loads for a group of customers are estimated jointly by a mixed hidden Markov model (MHMM) which enables modeling the general load consumption behavior present in all customers while acknowledging the individual differences. At the same time, the model can capture the change in load patterns over a time period by the hidden Markov states. The proposed algorithm is also capable of estimating the key technical parameters of the solar PV systems. Our proposed method is evaluated using the net load, electric load, and solar PV generation data gathered from residential customers located in Austin, Texas. Testing results show that our proposed method reduces the mean squared error of state-of-the-art net-load disaggregation algorithms by 67%.

behind-the-meter solar generation↗
DOE OSTI2019

Full-core analysis for FeCrAl enhanced accident tolerant fuel in boiling water reactors

The impact of replacing Zircaloy with FeCrAl, a candidate enhanced accident-tolerant fuel cladding material, was evaluated for 10 × 10 boiling water reactor fuel bundles. Results from a series of full-core parametric studies estimated that replacing UO 2 /Zircaloy with UO 2 /FeCrAl would require an average enrichment increase of 0.6% 235 U throughout the fuel lattice with the cladding and channel box thicknesses halved and fuel pellet diameter increased. Full-core results indicated that UO 2 /FeCrAl models with these geometric/enrichment specifications matched the base UO 2 /Zircaloy cycle length of 527 effective full power days. Optimization studies of the full-core design established loading and control blade patterns for both Zircaloy and FeCrAl models. A side study was conducted modeling a hybrid fuel bundle consisting of FeCrAl cladding and a SiC/Ni/Cr channel box. By halving the cladding thickness, the enrichment level required was less than that of the Zircaloy base case design after performing loading pattern optimization of the hybrid bundle core. Lastly, the thermomechanical performance of a Zircaloy-cladded fuel rod was compared to that of a FeCrAl system. Results from this analysis show that, if starting from the same fuel-cladding gap thickness, a FeCrAl-clad fuel rod operates with a greater average fuel centerline temperature, comparable axial elongation and radial displacement, and longer time to gap closure compared to a Zircaloy-clad fuel rod. Furthermore, this fuel performance analysis was primarily based on the commercial Kanthal APMT FeCrAl alloy but also used available data for the C35M FeCrAl alloy developed at Oak Ridge National Laboratory.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Criticality safety analysis of spent fuel storage or handling disposals using burnup credit - loading curve calculation - 14445

MILLENNIUM and REEL SAS Companies have shared their own experience to develop a neutron and criticality calculations chain in order to perform isotopic composition predictions of spent fuel after irradiation in a reactor and criticality analysis of fuel storages taking into account burnup credit. The whole calculation sequence is divided into three steps, all calling SCALE 6.1.2 modules. The first two steps are dedicated to the evaluation of isotopic compositions of burnt fuel. As transport and depletion calculations in three dimensions appears to be way too long for the whole core (about several months), dealing with each fuel assembly one by one is the alternative solution MILLENNIUM and REEL SAS commonly chose to study. Therefore, the first step aims at determining the axial burnup profile of a given fuel assembly using a 3-D model with infinite reflections on lateral axes. The T6-depl sequence of TRITON module coupling KENO-VI and ORIGEN-S was used in this step. Sensitivity studies confirmed that addition of the 8 closest neighbors of the studied fuel assembly in the model has an insignificant impact on the axial burnup profile. However, fuel assemblies in the peripheral zone of the core must be treated separately with a model including the nearest fuel assemblies and the effect of peripheral water. Then, the second phase evaluates the isotopic compositions of each fuel assemblies at the center of the active height with a 2-D model under conservative core conditions. The T-depl sequence of the TRITON module coupling NEWT to ORIGEN-S is called in this step. Each fuel assembly must be studied separately to consider loading pattern changes occurring at each cycle. An infinite model with reflections on lateral axes is used and the closest neighbors of the fuel assembly are limited to 2 pins - which is around the size of the neutrons mean free path in the core. This is an innovative physical trick aiming at compensating for a limited computing power. Finally, isotopic compositions calculated are combined with the axial burnup profile of the first step to extrapolate the concentrations along the whole active length. Data can then be added in any criticality model, such as a spent fuel pit or any disposal handling fuel assemblies. Criticality analyses of burnt fissile material using burnup credit can be managed within a reasonable amount of time, on condition that sufficient proofs of code qualification for the studied range of parameters are provided, especially on fission products isotopic compositions calculation. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗