Publications

Abstract not provided.

Abstract not provided.

Abstract not provided.

Wind energy is stochastic in nature; the prediction of aerodynamic quantities and loads relevant to wind energy applications involves modeling the interaction of a range of physics over many scales for many different cases. These predictions require a range of model fidelity, as predictive models that include the interaction of atmospheric and wind turbine wake physics can take weeks to solve on institutional high performance computing systems. In order to quantify the uncertainty in predictions of wind energy quantities with multiple models, researchers at Sandia National Laboratories have applied Multilevel-Multifidelity methods. A demonstration study was completed using simulations of a NREL 5MW rotor in an atmospheric boundary layer with wake interaction. The flow was simulated with two models of disparate fidelity; an actuator line wind plant large-eddy scale model, Nalu, using several mesh resolutions in combination with a lower fidelity model, OpenFAST. Uncertainties in the flow conditions and actuator forces were propagated through the model using Monte Carlo sampling to estimate the velocity defect in the wake and forces on the rotor. Coarse-mesh simulations were leveraged along with the lower-fidelity flow model to reduce the variance of the estimator, and the resulting Multilevel-Multifidelity strategy demonstrated a substantial improvement in estimator efficiency compared to the standard Monte Carlo method.

Abstract not provided.

Abstract not provided.

The Alternative Fuels Risk Assessment Models (A1tRAM) toolkit combines Quantitative Risk Assessment (QRA) with simulations of unignited dispersion, ignited turbulent diffusion flames, and indoor accumulation with delayed ignition of fuels. The models of the physical phenomena need to be validated for each of the fuels in the toolkit. This report shows the validation for methane which is being used as a surrogate for natural gas. For the unignited dispersion model, seven previously published experiments from credible sources were used to validate. The validation looked at gas concentrations with respect to the distance from the release point. Four of these were underexpanded jets (i.e. release velocity equal to or greater than local speed of sound) and the other three subsonic releases. The methane plume model in AltRAM matched both varieties well, with higher accuracy for the underexpanded releases. For the jet flame model, we compared the heat flux and thermal radiation data reported from five separate turbulent jet flame experiments to the quantities calculated by A1tRAM. Four of the five datasets were for underexpanded diffusion jets flames. While the results still match well enough to give a good estimate of what is occurring, the error is higher than what was seen with the plume model. For the underexpanded flames A1tRAM provided reasonable approximations, which would lead to conservative risk assessments. Some modeling errors can be attributed to environmental effects (i.e. wind) since most large scale flame experiments are conducted outdoors. A1tRAM has been shown to be a reasonably accurate tool for calculating the concentration or flame properties of natural gas releases. Improvements could still be made for the plume of subsonic releases and radiative heat fluxes to reduce the conservative nature of these predictions. These models can provide valuable information for the risk assessment of natural gas infrastructure.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Power production of the turbines at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at the Texas Tech University’s National Wind Institute Research Center was measured experimentally and simulated for neutral atmospheric boundary layer operating conditions. Two V27 wind turbines were aligned in series with the dominant wind direction, and the upwind turbine was yawed to investigate the impact of wake steering on the downwind turbine. Two conditions were investigated, including that of the leading turbine operating alone and both turbines operating in series. The field measurements include meteorological evaluation tower (MET) data and light detection and ranging (lidar) data. Computations were performed by coupling large eddy simulations (LES) in the three-dimensional, transient code Nalu-Wind with engineering actuator line models of the turbines from OpenFAST. The simulations consist of a coarse precursor without the turbines to set up an atmospheric boundary layer inflow followed by a simulation with refinement near the turbines. Good agreement between simulations and field data are shown. These results demonstrate that Nalu-Wind holds the promise for the prediction of wind plant power and loads for a range of yaw conditions.

Spontaneous Raman scattering images of liquid and near liquid methane released through 1 and 1.25 mm diameter orifices were taken using a pulsed planar laser sheet. The methane back pressure was varied between 2 and 6 bar_abs with methane temperatures between 130 and 220 K. Analysis of the Raman images resulted in the planar concentration and temperature fields of the methane jets. The measured methane concentration was compared with empirical relationships for warm gas releases and found to be in agreement in terms of centerline concentration decay rate, self-similarity, and half-width decay rate. Comparisons were then made for anticipated real-world CNG and LNG releases showing similar extents of flammable mass for the two fuel options. Measured images were compared to a cold gas release model, which showed good agreement over the range of methane release temperatures, pressures, and nozzle sizes. The collected measurements provide validation of this cold release model which will be used to model additional scenarios and inform LNG safety codes and standards.

Abstract not provided.

DOE has identified consistent safety, codes, and standards as a critical need for the deployment of hydrogen technologies, with key barriers related to the availability and implementation of technical information in the development of regulations, codes, and standards. Advances in codes and standards have been enabled by risk-informed approaches to create and implement revisions to codes, such as National Fire Protection Association (NFPA) 2, NFPA 55, and International Organization for Standardization (ISO) Technical Specification (TS)-19880-1. This project provides the technical basis for these revisions, enabling the assessment of the safety of hydrogen fuel cell systems and infrastructure using QRA and physics-based models of hydrogen behavior. The risk and behavior tools that are developed in this project are motivated by, shared directly with, and used by the committees revising relevant codes and standards, thus forming the scientific basis to ensure that code requirements are consistent, logical, and defensible.