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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Challenges in Rotor Aerodynamic Modeling for Non-Uniform Inflow Conditions

Within an international collaboration framework, the accuracy of rotor aerodynamic models used for design load calculations of wind turbines is being assessed. Where the use of high-fidelity computation fluid dynamics (CFD) and mid-fidelity free-vortex wake (FVW) models has become commonplace within the wind energy community, these still fail to meet the requirements in terms of execution time and computational cost needed for design load calculations. The fast but engineering fidelity blade-element/momentum (BEM) method can therefore still be considered the industry workhorse for design load simulations. At the same time, upscaling of wind turbine rotors makes inflow non-uniformities (e.g. shear, veer, turbulence) more important. The objective of this work is to assess model accuracy in non-uniform inflow conditions, which violate several BEM assumptions. Thereto a comparison in turbulent inflow has been executed including a wide variety of codes, focusing on the DanAero field measurements, where a 2.3-MW turbine was equipped with, among other sensors, a pressure measurement apparatus. The results indicate that, although average load patterns are in good agreement, this does not hold for the unsteady loads that drive fatigue damage and aero-elastic stability. A simplified comparison round in vertical shear was initiated to investigate the observed differences in a more controlled manner. A consistent offset in load amplitude was observed between CFD and free-vortex codes on the one hand and BEM-type codes on the other hand. To shed more light on the observations, dedicated efforts are ongoing to pinpoint the cause for these differences, in the end leading to guidelines for an improved BEM implementation.

17 WIND ENERGY↗
DOE OSTI2026

OC6 Phase Ia - Nonlinear hydrodynamic loading validation dataset

Two validation campaigns were examined within the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) Phase 1 project to examine the modeling tools' underprediction of loads and motion of a floating wind semisubmersible (semi) at their surge and pitch natural frequencies. These campaigns were performed at the Maritime Research Institute Netherlands (MARIN) in 2017 and 2018. The load cases (LC) considered include: LC1 – Load measurements across semi under current loading; LC2 - Load measurements across semi under forced surge oscillation; LC3 – Load measurements across semi under wave loading, while held fixed; LC4 – Free-decay motion measurements in surge, pitch, and heave; and LC5 – Motion measurements under wave loading. Details on the results from the OC6 Phase Ia project can be found in the reference, “OC6 Phase 1: Investigating the underprediction of low-frequency hydrodynamic loads and responses of floating wind turbines”, J Phys: Conf Series 1618 032033.

17 WIND ENERGY↗
DOE OSTI2017

Modeling fiber reinforced polymer (FRP) coating in retrofitting concrete walls against explosive loads

One of the issues considered in the design and dynamic resistance of structures (as seismic or explosive) is the use of materials which cause reduction in the force applied on the structure. With regard to the fact that greater loading is on the wall of concrete structures, the use of materials that reduce explosive force on the structure wall are among explosive force reduction methods.One of the viscose and damping materials of polymers is FRP, and in this study the FLAC3D software is used to evaluate the effect of this material on reducing force implemented on the walls and hence reduction of wall movement due to explosion. The concrete wall along with the FRP layer is modeled under dynamic loading. The effect of damping coefficient, number of FRP layers and concrete wall thickness has been evaluated.

42 ENGINEERING↗
DOE OSTI2020

Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics

For multilayer materials in thin substrate systems, interfacial failure is one of the most challenges. The traction-separation relations (TSR) quantitatively describe the mechanical behavior of a material interface undergoing openings, which is critical to understand and predict interfacial failures under complex loadings. However, existing theoretical models have limitations on enough complexity and flexibility to well learn the real-world TSR from experimental observations. A neural network can fit well along with the loading paths but often fails to obey the laws of physics, due to a lack of experimental data and understanding of the hidden physical mechanism. In this paper, we propose a thermodynamic consistent neural network (TCNN) approach to build a data-driven model of the TSR with sparse experimental data. The TCNN leverages recent advances in physics-informed neural networks (PINN) that encode prior physical information into the loss function and efficiently train the neural networks using automatic differentiation. We investigate three thermodynamic consistent principles, i.e., positive energy dissipation, steepest energy dissipation gradient, and energy conservative loading path. All of them are mathematically formulated and embedded into a neural network model with a novel defined loss function. A real-world experiment demonstrates the superior performance of TCNN, and we find that TCNN provides an accurate prediction of the whole TSR surface and significantly reduces the violated prediction against the laws of physics.

Zhang, Jiaxin↗
DOE OSTI2018

Electric Power Distribution System Model Simplification Using Segment Substitution

Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). In contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.

Reiman, Andrew P. (ORCID:0000000302042960)↗
DOE OSTI2021

Pipeline Structural Stability Under Nuclear Blast Pressure Loading

This report documents a set of simplified models to predict pipeline collapse under nuclear pressure loading. After a review of pipeline design literature, a set of simple expressions have been selected to represent an approximation of the threshold pressure for failure from cross- sectional yielding, cross-section buckling, and longitudinal buckling. These expressions provide a first-order approximation on load levels needed to achieve collapse. As a demonstration, the collapse pressure for a set of representative pipelines are calculated. Estimated pressure fields are also computed for a set of nuclear detonations, providing estimates of the ground range limit for pipeline collapse.

42 ENGINEERING↗
DOE OSTI2025

ComStock Measure Documentation: Thermostat and Lighting Control for Load Shedding

This report describes the modeling methodology for an upgrade package of two end-use savings shape measures - Thermostat Control for Load Shedding and Lighting Control for Load Shedding - and briefly introduces key results. The package combines thermostat control for load shedding and lighting control for load shedding measures to reduce the HVAC and lighting load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then relaxes the thermostat setpoints and dims the lighting level from the original schedules during the peak window to reduce the peak demand. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 3%-10% daily peak demand reduction performance for applicable buildings, and 0.97% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

HyPerPy (Hydrogen Extraction and Parabolic Trough Plant Performance Models using Python) [SWR-21-53]

The HyPerPy package consists of three scripts: 1) Model for Hydrogen Tracking in Parabolic Trough Power Plants, 2) Model for Receiver Performance, and 3) Model for Hydrogen Extraction Process. The power plant model (1) tracks hydrogen generation and transport within the circulating heat transfer fluid (HTF) of the power plant. This script is a transient, initial value simulation, in which the hydrogen concentration in the circulating HTF is 0 moles per cubic meter everywhere at time 0 seconds. Hydrogen concentration is calculated at discrete locations within the circulating HTF with 4-second time resolution. During each time step, the change in hydrogen concentration due to hydrogen generation and permeation is calculated for each location according to the local HTF temperature, vessel or piping properties, hydrogen concentration and partial pressure. This model predicts hourly hydrogen concentrations for typical operating days in the spring, summer, fall, and winter seasons. Data is used to create hourly mappings of hydrogen concentrations for a typical operating year. The receiver model (2) uses a 1-hour time step to estimate getter loading and annulus pressure. For each time step, the model uses HTF and ambient temperature data to estimate absorber tube, bellows, and getter temperatures for the time step. In addition, the model uses hourly HTF hydrogen concentrations that are generated by the power plant model (1), and annulus hydrogen pressure from the previous time step. With these data, the model calculates the moles of hydrogen permeating across the absorber tube and bellows during the time step. The net change in moles hydrogen is added or subtracted from the getter loading for the previous time step, and the hydrogen pressure is re-calculated based on getter loading and temperature. The model uses this algorithm to simulate hydrogen permeation and loading 24 hours per day, 365 days per year using seasonal temperature data. The model repeats these calculations for 25 years to create a mapping of receiver getter loading and annulus hydrogen pressure for four seasons of each year. The model for hydrogen extraction (3) estimates hydrogen extraction rates for a specific separation module configuration. The rate depends primarily on membrane area, vacuum pump performance, headspace gas flowrate to the membrane, and headspace gas hydrogen partial pressure. This model has two versions. The steady-state version predicts hydrogen extraction rates when the module is operating in separation mode. The dynamic version predicts hydrogen transfer through the membrane when the module is operating in sensor mode. The steady-state version is used with the plant model (1) to predict hydrogen partial pressures in the power plant when the extraction process is operating.

Glatzmaier, Gregory↗
DOE OSTI2021

Comparison of Deterministic and Statistical Models for Water Quality Compliance Forecasting in the San Joaquin River Basin, California

Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Optimization of Advanced Steels for Cyclic Operation through an Integration of Material Testing, Modeling and Novel Component Test Validation

The efforts in this project were focused in three primary objectives, provided below: • To develop the needed microstructural processing and performance relationships and associated material models for specific constituents in fabricated weldments (such as the parent material, heat affected zone regions and weld metal), • Apply these metallurgical relationships through modeling of a welded pressure bearing power plant component subjected to cyclic operational conditions under both mechanical and thermal loading, and • Validate the model through novel structural feature and component tests. An attempt was made to optimize the heat treatment schedule to reduce or eliminate the presence of boron nitride (BN) in the matrix of the Grade 92 material. BN has been shown to be a primary nucleation source for creep damage. Proper evaluation of material behavior, and as assessed in this research, included the influence of geometric notches (such as those from poor fabrication or design) and metallurgical notches (such as weldments or poorly processed parent material). Better practice methodologies were implemented in the theoretical design of a high-temperature, critical component for cyclic operation. It was demonstrated that vessel testing can be reliably performed and provides a critical link between standard testing, structural assessment and validation. While the goal of an improved Grade 92 steel was not achieved in this project, there is considerable value in applying the documented testing and assessment methodologies to assess material and/or component behavior. This is especially true for materials and/or designs which are expected to be subjected to flexible operating modes. Design of a cycling state of the art thick wall steam header for long term operation with a state of the art ferritic steel was a task in this project. Implementation of that task showed how many factors including plant operating mode, creep strength, creep ductility, fatigue strength, and resistance to crack growth should be considered and evaluated to properly design high temperature components for long term service (200,000 operating hours or more) in a modern Fossil energy power plant. The current ASME non-nuclear boiler design code does not mandate this level of complex analysis nor does it provide all the metallurgical and mechanical properties data needed to perform this kind of design analysis.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

FIREFLY: heat load and particle exhaust approximations for rapid evaluation of divertor designs

The divertor in a magnetic confinement fusion reactor is an essential component for power dissipation and particle removal. The FIREFLY package for rapid evaluation of divertor designs is presented as an extension of the FLARE code for field line reconstruction from a flux tube mesh. First, divertor loads are approximated with a simplified heat transport model. Neutralized particles are then sampled from the resulting load distribution, and the EIRENE code is used to track molecules and atoms in a plasma background while accounting for dissociation, charge exchange and ionization. Particles are removed on pumping surfaces in order to estimate the exhaust efficiency for a given divertor geometry. Optimization of the divertor geometry for more efficient particle exhaust is explored by using W7-X as an example, and the sensitivity to model parameters for the plasma background in the proxy calculations is evaluated.

mesh generation, magnetic field lines, scrape-off ↗
DOE OSTI2016

A mobile test facility based on a magnetic cumulative generator to study the stability of the power plants under impact of lightning currents

The report presents the results of the development and field testing of a mobile test facility based on a helical magnetic cumulative generator (MCGTF). The system is designed for full-scale modeling of lightning currents to study the safety of power plants of any type, including nuclear power plants. Advanced technologies of high-energy physics for solving both engineering and applied problems underlie this pilot project. The energy from the magnetic cumulative generator (MCG) is transferred to a high-impedance load with high efficiency of more than 50% using pulse transformer coupling. Modeling of the dynamics of the MEG that operates in a circuit with lumped parameters allows one to apply the law of inductance output during operation of the MCG, thus providing the required front of the current pulse in the load without using any switches. The results of field testing of the MCGTF are presented for both the ground loop and the model load. The ground loop generates a load resistance of 2–4 Ω. In the tests, the ohmic resistance of the model load is 10 Ω. It is shown that the current pulse parameters recorded in the resistive-inductive load are close to the calculated values.

42 ENGINEERING↗
DOE OSTI2025

Electrical Load Forecasting Over Multihop Smart Metering Networks With Federated Learning

Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) record household energy data. Traditional machine learning (ML) methods are often employed for load forecasting, but require data sharing, which raises data privacy concerns. Federated learning (FL) can address this issue by running distributed ML models at local SMs without data exchange. However, current FL-based approaches struggle to achieve efficient load forecasting due to imbalanced data distribution across heterogeneous SMs. Here, this article presents a novel personalized FL (PFL) method for high-quality load forecasting in metering networks. A meta-learning-based strategy is developed to address data heterogeneity at local SMs in the collaborative training of local load forecasting models. Moreover, to minimize the load forecasting delays in our PFL model, we study a new latency optimization problem based on optimal resource allocation at SMs. A theoretical convergence analysis is also conducted to provide insights into FL design for federated load forecasting. Extensive simulations from real-world datasets show that our method outperforms existing approaches regarding better load forecasting and reduced operational latency costs.

Rahman, Ratun [Univ. of Alabama, Huntsville, AL (U↗
DOE OSTI2025

Experimental Validation of a Module Cell Cracking Model

The What's Cracking app can predict how changes in crystalline silicon photovoltaic (PV) module materials, design, and mounting affect its susceptibility for cell fracture under uniform loading. This work has experimentally validated the app. A set of commercial crystalline silicon PV modules was obtained for this study. The modules were uniformly loaded at three different mounting points, and their subsequent cell fractures were recorded. A large sample size allowed for the development of an experimental statistical model for cell fracture. Here, the comparison of the experiment to predictions from the app is in excellent agreement. Both experimental and modeling results also elucidate how moving the module mounting points toward the center of the module increases the probability of cell fracture.

14 SOLAR ENERGY↗
DOE OSTI2017

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters

Next-generation power networks will contain large numbers of grid-connected inverters satisfying a significant fraction of system load. Since each inverter model has a relatively large number of dynamic states, it is impractical to analyze complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model with lumped parameters for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. We show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as any individual inverter in the system. Numerical simulations validate the reduced-order model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Material Model Testing in the DYNA3D Code: Material Models 1 through 5

This report is the first volume in an effort to study the material model implementations in DYNA3D, using the latest developmental version of the code. Input files were derived from a template supplied by Jerry Lin to perform an equation-of-state study. Most of the simulations use 10 cubes, each 1 cm on a side with a density of 8.03 (steel). Each of the cubes tests a different aspect of the material model. The first three cubes are testing normal stresses and normal strains (uniaxial stresses and strains) placed on the cube parallel to the x-axis, y-axis and z-axis, respectively. The x (or y or z) = 1 face of the cube is moved along the x-axis (or y-axis or z-axis) to test the model, while the opposite side remains in the x (or y or z) = 0 plane. For some of the tests, the nodes are free to move perpendicular to the applied strain to allow the cross-sectional area of the cube to change in response to being placed under pressure or tension (to test Poisson’s Ratio), while in others the nodes are frozen to eliminate dynamic effects resulting from the code. The cube is placed in tension along the axis being tested and then released, followed by a cycle of compression and release. This tension/compression cycle is repeated 3 more times. The additional cycles allow for the model to be tested under different loads. For these calculations, the amount by which the cube is stretched and compressed is varied from cycle to cycle to allow testing of model features. Cubes number 4 and 5 are intended to test xy shear stresses/strains. This is done by sliding one face of the cube in its plane parallel to the axis of interest. For example, for cube 4, the upper face of the cube is slid in the y=1 plane in a direction parallel to the x-axis (so there are no changes in the y and z coordinates of the points in the plane) and then returned to its starting position. This preserves the volume of the cube, so there is no change in density or pressure. The cycle is repeated 8 times. For cube 5, the plane of the cube satisfying x=1 is slid in this plane in a direction parallel to the y-axis and then returned to its starting position. This preserves the volume of the cube, so there is no change in density or pressure. The cycle is repeated 8 times. Cubes number 6 through 9 repeat these tests for yz shear stresses/strains (Cubes 6 and 7) and zx shear stresses and strains (Cubes 8 and 9). For reasons discussed in the next paragraph, it is unclear if these tests represent a state of pure shear stress and shear strain in the code. Application of shear stresses and strains should not, in general, result in the appearance of normal stresses and strains in Cubes 4 - 9. In the infinitesimal limit, this result might be obtained. However, DYNA3D is a finite deformation code and in the real deformations used in the code, this result is not achieved and the individual components of the normal stresses and strains are non-zero during the cycling. However, the sums of the normal strains are zero in these tests and, except in the case of thermally dependent models, so are the sums of the normal stresses. Cube 10 tests the response of the material model to a hydrostatic loading of the cube. The load curve used for the first three tests is used again and applied to each of the 8 nodes in a manner causing the cube to be either compressed or expanded. This compression/tension cycle is repeated 4 times. The additional cycles allow for the model to be tested under different loads. The amount by which the cube is stretched and compressed is varied from cycle to cycle to allow testing of model features. This document will discuss the testing of Material Models 1 through 5. Relevant results from the test cubes will be discussed. A discussion of the results from all 10 test cubes will be presented only if necessary.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Improving the accuracy of energy baseline models for commercial buildings with occupancy data

More than 80% of energy is consumed during operation phase of a building's life cycle, so energy efficiency retrofit for existing buildings is considered a promising way to reduce energy use in buildings. The investment strategies of retrofit depend on the ability to quantify energy savings by “measurement and verification” (M&V), which compares actual energy consumption to how much energy would have been used without retrofit (called the “baseline” of energy use). Although numerous models exist for predicting baseline of energy use, a critical limitation is that occupancy has not been included as a variable. However, occupancy rate is essential for energy consumption and was emphasized by previous studies. This study develops a new baseline model which is built upon the Lawrence Berkeley National Laboratory (LBNL) model but includes the use of building occupancy data. The study also proposes metrics to quantify the accuracy of prediction and the impacts of variables. However, the results show that including occupancy data does not significantly improve the accuracy of the baseline model, especially for HVAC load. The reasons are discussed further. In addition, sensitivity analysis is conducted to show the influence of parameters in baseline models. To conclude, the results from this study can help us understand the influence of occupancy on energy use, improve energy baseline prediction by including the occupancy factor, reduce risks of M&V and facilitate investment strategies of energy efficiency retrofit.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Battery Equivalent Model for Residential HVAC

Flexible loads, especially heating, ventilation, and air-conditioning (HVAC) systems can be used to provide a battery-like service to the power grid by varying their demand up and down over a baseline. Recent work has reported that the round-trip efficiency for providing grid services with HVAC systems can be close to 1. Inspired by this promising result, in this work, we rigorously develop a battery equivalent model (BEM) for residential HVAC systems. Relying only on typically available data, the proposed BEM will bridge the observability and controllability gaps between utility companies and customers. The proposed BEM will enable the utility companies to manage the flexible HVAC devices as easy as charging/discharging the conventional energy storage devices. Validated physics-based models are used to train the BEM, whose prediction accuracy is illustrated through a simulation study.

Dong, Jin↗