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At least 1,585 records · Page 88

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DOE OSTI2018

High Performance Computational Models of Synthetic Jet Actuators for Step Change Improvements in Freight Efficiency

The project presents results of a computational fluid dynamics (CFD) model developed by the Oak Ridge National Laboratory team for a synthetic jet produced by an actuator. Numerical results were compared against experimental data provided by Actasys, Inc. Three CFD packages were used for this work that are Star-CCM+, Nek5000 and OpenFOAM. A sensitivity analysis was performed with Star-CCM+ and provided more insights on how to optimize the design of the actuator. Nek5000 was used to obtain a high-resolution solution of the synthetic jet. In a exploratory stage, a CFD model of the actuator was also developed in OpenFOAM. All CFD models were able to capture the main flow features.

42 ENGINEERING↗

DOE OSTI2024

Surrogate construction via weight parameterization of residual neural networks

Surrogate model development is a critical step for uncertainty quantification or other sample-intensive tasks for complex computational models. Here, in this work, we develop a multi-output surrogate form using a class of neural networks (NNs) that employ shortcut connections, namely Residual NNs (ResNets). ResNets are known to regularize the surrogate learning problem and improve the efficiency and accuracy of the resulting surrogate. Inspired by the continuous, Neural ODE analogy, we augment ResNets with weight parameterization strategy with respect to ResNet depth. Weight-parameterized ResNets regularize the NN surrogate learning problem and allow better generalization with a drastically reduced number of learnable parameters. We demonstrate that weight-parameterized ResNets are more accurate and efficient than conventional feed-forward multi-layer perceptron networks. We also compare various options for parameterization of the weights as functions of ResNet depth. We demonstrate the results on both synthetic examples and a large scale earth system model of interest.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Aluminum Ultra-conductors for Energy-Efficient Aerospace Busbar Applications (Abstract)

In this project, we will develop aluminum ultra-conductors with graphene additives demonstrating enhanced electrical conductivity at 90 °C compared to electric grade aluminum alloy AA1100 (43% IACS at 90 °C). While ultra-conductivity has been developed in copper and copper alloys, it is yet to be reported extensively in aluminum-based materials. This project will scale initial work done at PNNL on aluminum ultra-conductors using shear-assisted processing and extrusion (ShAPETM), a novel solid phase processing technique. Ultra-conductors are an emerging class of composites, comprised of a metal substrate with small quantities of nanocrystalline additives such as graphene or carbon nanotubes that demonstrate enhanced conductivity at relevant operating temperatures. Aluminum ultra-conductors can improve efficiency and power density while reducing the demand for copper in a wide range of applications, such as power transmission cables and electric motors. Busbars are an important component in aerospace systems that require lightweight and high-current power distribution including both future electric vertical take-off and landing (eVTOL) aircrafts and current aircraft electrical systems. We will accelerate aluminum ultra-conductor composite formulation development using combinatorial synthesis and testing methods aided by process/microstructure modeling, developed previously at PNNL. Eaton will test the properties of the ShAPE aluminum ultra-conductor feedstock (used to make the busbars) in relevant operating conditions (20 – 90 °C), predict the improvement in busbar performance when manufactured with ultra-conductors over commercial conductors (such as AA1100), and perform technoeconomic analysis to evaluate the potential for commercialization of ShAPE aluminum ultra-conductors. The project is expected to have a budget of $\$375$K, with $\$300$K in federal funding and $\$75$K in-kind cost-share contribution from Eaton over a period of performance of 24 months. Of the $\$300$K of federal funds, $\$140$K is allocated for CRADA activities that generate intellectual property (IP), and the remaining $\$160$K is reserved for modeling, material testing, characterization, travel, and reporting-related activities.

36 MATERIALS SCIENCE↗

NASA NTRS2011

A Short Review of Ablative-Material Response Models and Simulation Tools

A review of the governing equations and boundary conditions used to model the response of ablative materials submitted to a high-enthalpy flow is proposed. The heritage of model-development efforts undertaken in the 1960s is extremely clear: the bases of the models used in the community are mathematically equivalent. Most of the material-response codes implement a single model in which the equation parameters may be modified to model different materials or conditions. The level of fidelity of the models implemented in design tools only slightly varies. Research and development codes are generally more advanced but often not as robust. The capabilities of each of these codes are summarized in a color-coded table along with research and development efforts currently in progress.

Lachaud, Jean↗

NASA NTRS1994

A toolbox and record for scientific models

Computational science presents a host of challenges for the field of knowledge-based software design. Scientific computation models are difficult to construct. Models constructed by one scientist are easily misapplied by other scientists to problems for which they are not well-suited. Finally, models constructed by one scientist are difficult for others to modify or extend to handle new types of problems. Construction of scientific models actually involves much more than the mechanics of building a single computational model. In the course of developing a model, a scientist will often test a candidate model against experimental data or against a priori expectations. Test results often lead to revisions of the model and a consequent need for additional testing. During a single model development session, a scientist typically examines a whole series of alternative models, each using different simplifying assumptions or modeling techniques. A useful scientific software design tool must support these aspects of the model development process as well. In particular, it should propose and carry out tests of candidate models. It should analyze test results and identify models and parts of models that must be changed. It should determine what types of changes can potentially cure a given negative test result. It should organize candidate models, test data, and test results into a coherent record of the development process. Finally, it should exploit the development record for two purposes: (1) automatically determining the applicability of a scientific model to a given problem; (2) supporting revision of a scientific model to handle a new type of problem. Existing knowledge-based software design tools must be extended in order to provide these facilities.

Ellman, Thomas↗

DOE OSTI2025

Defect Thermodynamics and Transport Properties of Proton Conducting Perovskite Electrode and Electrolyte Materials Evaluated Based on Density Functional Theory Modeling

Both electron-rich and electron-poor perovskite oxides have been used in solid oxide cell applications as electrode and electrolyte materials. The rich oxygen defect chemistry and its coupling to temperature, hydrogen-steam or oxygen-steam gas pressure, or to the applied potentials creates enormous complexities for modeling performance and degradation of the materials. Herein, density functional theory-based thermodynamic modeling was carried out to describe the defect chemistry and transport properties of the proton-conducting electrolyte BaZr1-xYxO3-δ (x≤0.1) and of the triple-conducting perovskite (La,Ba)(Fe,M)O3-δ (M=Y and Zr). The defect thermodynamics of intrinsic point defects and the hydrogen-related defect reactions were solved in integrated defect models and further used to predict the Brouwer diagram and the transport properties of the functional perovskites. For the electron-poor electrolytes BaZr0.9Y0.1O3-δ, the developed model has been used to describe the experimental transport properties in the SOC operating conditions. Specifically, the roles played by the acceptor-bound holes and the intrinsic and hydrogen point defects upon the conductivities of holes, protons, and oxygen vacancies under the hydrogen-rich and oxygen-rich conditions at various humidity levels were demonstrated. A defect modeling tool was also developed for the triple-conducting perovskite (La,Ba)(Fe,M)O3-δ (M=Y and Zr) to examine magnetic effects and hydride defects in defect equilibria.

defect thermodynamics↗

NASA NTRS2005

Computational Simulations and the Scientific Method

As scientific simulation software becomes more complicated, the scientific-software implementor's need for component tests from new model developers becomes more crucial. The community's ability to follow the basic premise of the Scientific Method requires independently repeatable experiments, and model innovators are in the best position to create these test fixtures. Scientific software developers also need to quickly judge the value of the new model, i.e., its cost-to-benefit ratio in terms of gains provided by the new model and implementation risks such as cost, time, and quality. This paper asks two questions. The first is whether other scientific software developers would find published component tests useful, and the second is whether model innovators think publishing test fixtures is a feasible approach.

Kleb, Bil↗

NASA NTRS1999

Aerodynamic Analysis of Multistage Turbomachinery Flows in Support of Aerodynamic Design

This paper summarizes the state of 3D CFD based models of the time average flow field within axial flow multistage turbomachines. Emphasis is placed on models which are compatible with the industrial design environment and those models which offer the potential of providing credible results at both design and off-design operating conditions. The need to develop models which are free of aerodynamic input from semi-empirical design systems is stressed. The accuracy of such models is shown to be dependent upon their ability to account for the unsteady flow environment in multistage turbomachinery. The relevant flow physics associated with some of the unsteady flow processes present in axial flow multistage machinery are presented along with procedures which can be used to account for them in 3D CFD simulations. Sample results are presented for both axial flow compressors and axial flow turbines which help to illustrate the enhanced predictive capabilities afforded by including these procedures in 3D CFD simulations. Finally, suggestions are given for future work on the development of time average flow models.

Adamczyk, John J.↗

NASA NTRSDate not supplied

Recent Updates to the Object Reentry Survival Analysis Tool (ORSAT) Version 7.1

The Object Reentry Survival Analysis Tool (ORSAT) code is maintained and used by the NASA Orbital Debris Program Office (ODPO) and has been under continuous development and improvement since the mid-1990s. ORSAT is an object-oriented reentry simulation tool; it models a satellite as a collection of discrete components that follow independent trajectories upon the breakup of the parent object. Version 7.1 of the tool incorporates five years of new thermal and aerodynamic model development, multi-processor parametric study capability, codebase upgrades, and numerous bug-fixes. The thermal demise model was completely rewritten using a forward-time/central-space numerical stencil and incorporating a new pyrolysis model for fiber-reinforced plastic (FRP) materials. New aerodynamic and aeroheating models for hollow cylinders and hollow square prisms were developed using a combination of flow simulations in the direct simulation Monte Carlo (DSMC) Analysis Code (DAC) and Data Parallel Line Relaxation (DPLR) code and free-flight tests in the University of Texas at San Antonio’s Hypersonic Wind Tunnel. The latest version also incorporates a mechanical, strength-based demise model for FRP materials. Minor improvements include an update to the Fortran 2018 codebase; improved integration and speed with the Python-based, multi-core, parametric study tool, AutoORSAT; and fixes for many minor bugs. This new version of ORSAT will enable more accurate reentry risk assessments for modern satellites. This paper presents an overview of these changes and a summary of the verification and validation performed on the final code.

Benton R. Greene↗

NASA NTRSDate not supplied

Recent Updates to the Object Reentry Survival Analysis Tool (ORSAT) Version 7.1

Benton R. Greene↗

DOE OSTI2016

Forecasting climate change impacts on plant populations over large spatial extents

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Measured and estimated performance of a fleet of shaded photovoltaic systems with string and module-level inverters

Shade obstructions can significantly impact the performance of photovoltaic (PV) systems. Although there are many models for partially shaded PV arrays, there is a lack of information available regarding their accuracy and uncertainty when compared with actual field performance. This work assesses the recorded performance of 46 residential PV systems, equipped with either string-level or module-level inverters, under a variety of shading conditions. We compare their energy production data to annual PV performance predictions, with a focus on the practical models developed here for National Renewable Energy Laboratory's system advisor model software. This includes assessment of shade extent on each PV system by using traditional onsite surveys and newer 3D obstruction modelling. The electrical impact of shade is modelled by either a nonlinear performance model or assumption of linear impact with shade extent, depending on the inverter type. When applied to the fleet of residential PV systems, performance is predicted with median annual bias errors of 2.5% or less, for systems with up to 20% estimated shading loss. The partial shade models are not found to add appreciable uncertainty to annual predictions of energy production for this fleet of systems but do introduce a monthly root-mean-square error of approximately 4%-9% due to seasonal effects. Here the use of a detailed 3D model results in similar or improved accuracy over site survey methods, indicating that, with proper description of shade obstructions, modelling of partially shaded PV arrays can be done completely remotely, potentially saving time and cost.

14 SOLAR ENERGY↗

DOE OSTI2021

Influence of tower shadow on downwind flexible rotors: Field tests and simulations

Abstract As wind turbine rotors become larger, the blades become more flexible, requiring extra stiffness and cost to avoid the risk of tower strike. Wind turbines in a downwind configuration have a reduced risk of tower strike because the rotor thrust acts away from the tower. However, downwind blades pass through the wake of the tower, and the resulting load variation may contribute to blade fatigue. To date, there have been no field tests to quantify this tower shadow effect on unsteady blade moments. The present study reports on the first field testing of a flexible, downwind, coned rotor and compares the experimental data against simulations run in OpenFAST. The tower shadow effect is simulated using the conventional Powles model and a new Eames model (developed herein), which includes the influence of upstream turbulence. Both models reasonably predict the blade root out‐of‐plane bending moment data and the tower shadow dip magnitude when compared to field test data in Region 3. Tower shadow was found to increase the short‐term Damage Equivalent Loads (DELs) by less than 10% compared to other effects (gravity, shear, and turbulence), and the predictions were consistent with experiments. These results indicate that the tower shadow effect can be reasonably modeled with the simpler Powles model and that the tower shadow effect can be small compared to the effect of turbulence. However, long‐term fatigue due to tower shadow should be included in detailed structural analysis and design of the rotor and the tower.

Simpson, Juliet G.↗

DOE OSTI2021

A hierarchical gray-box dynamic modeling methodology for direct-expansion cooling systems to support control stability analysis; Méthodologie de modélisation dynamique hiérarchique de type boîte grise pour les systèmes de refroidissement à détente directe afin de soutenir l'analyse de stabilité de la commande

In this paper, a gray-box dynamic modeling approach for direct-expansion cooling systems is presented. The overall approach incorporates a multi-stage training procedure that consists of 1) identification of component sub-models from quasi-steady-state performance data, 2) system model integration with estimation of refrigerant charge and 3) fine tuning of thermal capacitances of the evaporator and condenser to capture the system dynamic responses. Compared to traditional physics-based models, the proposed modeling approach has advantages including reduced engineering efforts in the model development phase, improved computational efficiency and enhanced prediction accuracy. The modeling method was validated using a 3-ton variable-speed heat pump and proved to be capable of accurately predicting the system transient behaviors over a wide range of operating conditions. The established dynamic model was then applied for control stability analysis, with a specific goal of determining a proper control execution time step. The case study results showed that the stable control execution time step could change significantly, from 3 sec to 19 sec, as the operating conditions and control settings vary, and a proper selection of the execution time step is critical to ensure stable and reliable operations.

42 ENGINEERING↗

DOE OSTI2022

Reverse scaling of a bonded-sphere DEM model: Formulation and application to lignocellulosic biomass microstructures

We explore scaling laws for adapting a bonded-sphere discrete element method (BS-DEM) model developed for woody structural mechanics at the millimeter scale to model the mechanics of realistic lignocellulosic biomass microstructures. Two scaling approaches, i.e., the reverse coarse graining (RCG) and equivalent bulk behavior (EBB), are proposed based on the classical mechanics principles and assessed in the single-particle compression and rectangular cuboid block tension tests. The EBB approach is recommended for BS-DEM models with general 3D geometries and is applied to simulate the microindentation test on a realistic microscale pinewood specimen. Simulations are performed to elucidate the impact of specimen thickness and loading position on the specimen’s force–deformation behavior. Furthermore, the range of Young’s modulus obtained from the calibrated BS-DEM simulations can match the experimental measurements. This is the first-of-its-kind study that has explored scale-bridging modeling approaches in biomass micromechanics and has proposed solutions based on BS-DEM models in the microscale.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

High-Fidelity Models and Fast EMT Simulation Algorithms for Isolated Multi-port Autonomous Reconfigurable Solar power plant (MARS)

The integration of hybrid photovoltaic (PV) and energy storage system (ESS) based plants has become a promising way of solving the intermittency of PV plants and providing frequency support to the power grid. The multi-port autonomous reconfigurable solar power plant (MARS) can integrate the PV systems and ESSs to an ac grid and dc lines. The proposed isolated MARS incorporates an isolated converter that connects to the PV arrays and is based on the dual active bridge (DAB) converter. The high frequency switching in the DAB and the means to control the DAB converter using delays between switching signals lead to the need for a small timestep in simulations. Moreover, several hundreds of modules that include a DAB converter are present in the MARS. The small timestep and the presence of several hundreds of modules lead to a significant rise in the overall simulation time. To address this issue, simulation algorithms like numerical stiffness-based hybrid discretization and the hysteresis relaxation technique are applied to the switched system model of isolated MARS. Additionally, an event-driven interpolating method is introduced to help increase the minimum timestep to simulate the conventional DAB converter model while maintaining high accuracy in the simulation results. The developed model is validated by comparison with its reference model built in the PSCAD/EMTDC and MATLAB software environments using library components.

Xia, Qian↗

DOE OSTI2017

An agent based model for joint placement of PV panels and green roofs

Photovoltaic panels generate electricity directly from sunlight, making them a favored renewable technology. Green roofs are rooftops covered with vegetation, which provide a variety of benefits, namely, reducing stormwater runoff, improving air quality, and biodiversity. Green roofs are capable of improving the efficiency of Photovoltaic panels, as shown by the recent studies. Optimal placement of Photovoltaic panels and green roofs is a challenging problem due to the complications imposed by uncertainties associated with future climate conditions, specifically due to climate change. An agent based model to optimally place Photovoltaic panels and green roofs is developed in this study. We propose a tabu search metaheuristic algorithm to solve the developed model. Then, a real-world case for a mid-sized city in the U.S. is solved as a case study for the model. We further conduct numerical analysis and provide insights.

Li, Xueping↗

DOE OSTI2017

ACME Priority Metrics (A-PRIME)

A-PRIME, is a collection of scripts designed to provide Accelerated Climate Model for Energy (ACME) model developers and analysts with a variety of analysis of the model needed to determine if the model is producing the desired results, depending on the goals of the simulation. The software is csh scripts based at the top level to enable scientist to provide the input parameters. Within the scripts, the csh scripts calls code to perform the postprocessing of the raw data analysis and create plots for visual assessment.

Evans, KatherineJ.↗