Publications

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This report documents analysis to determine whether a hydrogen jet flame impinging on a tunnel ceiling structure could result in permanent damage to the Callahan tunnel in Boston, Massachusetts. This tunnel ceiling structure consists of a passive fire protective board supported by stainless steel hangers anchored to the tunnel ceiling with epoxy. Three types of fire protective boards were considered to determine whether heat from the flame could reach the stainless-steel hangers and the epoxy and cause the ceiling structure to collapse. Heat transfer analyses performed showed that the temperature remains constant where the steel hangers are attached to the passive fire protective board. According to these results, the passive fire protective board should provide adequate protection to the tunnel structure in this release scenario. Tunnel structures with similar suspended fire-resistant liner board materials should protect the integrity of the structure against the extremely low probability of an impinging hydrogen jet flame.

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HyRAM+ is a toolkit that includes fast-running models for the unconstrained (i.e., no wall interactions) dispersion and flames for non-premixed fuels. The models were developed for use with hydrogen, but the toolkit was expanded to include propane and methane in a recent release. In this work we validate the dispersion and flame models for these additional fuels, based on reported literature data. The validation efforts spanned a range of release conditions, from subsonic to underexpanded jets and flames for a range of mass flow rates. In general, the dispersion model works well for both propane and methane although the width of the jet/plume is predicted to be wider than observed in some cases. The flame model tends to over-predict the induced buoyancy for low-momentum flames, while the radiative heat flux agrees with the experimental data reasonably well, for both fuels. The models could be improved but give acceptable predictions for propane and methane behavior for the purposes of risk assessment.

In order to better understand the complex pooling and vaporization of a liquid hydrogen spill, Sandia National Laboratories is conducting a highly instrumented, controlled experiment inside their Shock Tube Facility. Simulations were run before the experiment to help with the planning of experimental conditions, including sensor placement and cross wind velocity. This paper describes the modeling used in this planning process and its main conclusions. Sierra Suite’s Fuego, an in-house computational fluid dynamics code, was used to simulate a RANS model of a liquid hydrogen spill with five crosswind velocities: 0.45, 0.89, 1.34, 1.79, and 2.24 m/s. Two pool sizes were considered: a diameter of 0.85 m and a diameter of 1.7. A grid resolution study was completed on the smaller pool size with a 1.34 m/s crosswind. A comparison of the length and height of the plume of flammable hydrogen vaporizing from the pool shows that the plume becomes longer and remains closer to the ground with increasing wind speed. The plume reaches the top of the facility only in the 0.45 m/s case. From these results, we concluded that it will be best for the spacing and location of the concentration sensors to be reconfigured for each wind speed during the experiment.

A large-scale numerical computation of five wind farms was performed as a part of the American WAKE experimeNt (AWAKEN). This high-fidelity computation used the ExaWind/AMR-Wind LES solver to simulate a 100 km × 100 km domain containing 541 turbines under unstable atmospheric conditions matching previous measurements. The turbines were represented by Joukowski and OpenFAST coupled actuator disk models. Results of this qualitative comparison illustrate the interactions of wind farms with large-scale ABL structures in the flow, as well as the extent of downstream wake penetration in the flow and blockage effects around wind farms.

The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, natural gas, and autogas systems. HyRAM+ is designed to facilitate the use of state-of-the-art models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ integrates deterministic and probabilistic models for quantifying leak sizes and rates, predicting physical effects, characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impacts on people. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards, and to provide developed models in a publicly-accessible toolkit usable by all stakeholders. This document provides a description of the methodology and models contained in HyRAM+ version 5.0. The most significant change for HyRAM+ version 5.0 from HyRAM+ version 4.1 is the ability to model blends of different fuels. HyRAM+ was previously only suitable for use with hydrogen, methane, or propane, with users having the ability to use methane as a proxy for natural gas and propane as a proxy for autogas/liquefied petroleum gas. In version 5.0, real natural gas or autogas compositions can be modeled as the fuel, or even blends of natural gas with hydrogen. These blends can be used in the standalone physics models, but not yet in the quantitative risk assessment mode of HyRAM+.

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The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, methane, and propane systems. HyRAM+ is designed to facilitate the use of state-of-the-art models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impacts on people. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards, and to provide developed models in a publicly-accessible toolkit usable by all stakeholders. This document provides a description of the methodology and models contained in HyRAM+ version 4.1. The two most significant changes for HyRAM+ version 4.1 from HyRAM+ version 4.0 are direct incorporation of unconfined overpressure into the QRA calculations and modification of the models for cryogenic liquid flow through an orifice. In QRA mode, the user no longer needs to input peak overpressure and impulse values that were calculated separately; rather, the unconfined overpressure is estimated for the given system inputs, leak size, and occupant location. The orifice flow model now solves for the maximum mass flux through the orifice at constant entropy while conserving energy, which does not require a direct speed of sound calculation. This does not affect the mass flow for all-gaseous releases; the method results in the same speed of sound for choked flow. However, this method does result in a higher (and more realistic) mass flow rate for a given leak size for liquid releases than was previously calculated.

Nalu-Wind is part of the ExaWind code suite.

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The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, methane, and propane infrastructure and transportation systems. HyRAM+ is designed to facilitate the use of state-of-the-art science and engineering models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ includes generic probabilities for equipment failures, probabilistic models for the impact of heat flux on humans and structures, and experimentally validated first-order models of release and flame physics. HyRAM+ integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impact on people and structures. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards. HyRAM+ is a research software in active development and thus the models and data may change. This report will be updated at appropriate developmental intervals. This document provides a description of the methodology and models contained in HyRAM+ version 4.0. The most significant change for HyRAM+ version 4.0 from HyRAM version 3.1 is the incorporation of other alternative fuels, namely methane (as a proxy for natural gas) and propane into the toolkit. This change necessitated significant changes to the installable graphical user interface as well as changes to the back-end Python models. A second major change is the inclusion of physics models for the overpressure associated with the delayed ignition of an unconfined jet/plume of flammable gas.

The complexity and associated uncertainties involved with atmospheric-turbine-wake interactions produce challenges for accurate wind farm predictions of generator power and other important quantities of interest (QoIs), even with state-of-the-art high-fidelity atmospheric and turbine models. A comprehensive computational study was undertaken with consideration of simulation methodology, parameter selection, and mesh refinement on atmospheric, turbine, and wake QoIs to identify capability gaps in the validation process. For neutral atmospheric boundary layer conditions, the massively parallel large eddy simulation (LES) code Nalu-Wind was used to produce high-fidelity computations for experimental validation using high-quality meteorological, turbine, and wake measurement data collected at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at Texas Tech University's National Wind Institute. The wake analysis showed the simulated lidar model implemented in Nalu-Wind was successful at capturing wake profile trends observed in the experimental lidar data.

Liquefied petroleum gas (LPG) is a viable, cleaner alternative to traditional diesel fuel used in busses and other heavy-duty vehicles and could play a role in helping the US meet its lower emission goals. While the LPG industry has focused efforts on developing vehicles and fueling infrastructure, we must also establish safe parameters for maintenance facilities which are servicing LPG fueled vehicles. Current safety standards aid in the design of maintenance facilities, but additional quantitative analysis is needed to prove safeguards are adequate and suggest improvements where needed. In this report we aim to quantify the amount of flammable mass associated with propane releases from vehicle mounted fuel vessels within enclosed garages. Furthermore, we seek to qualify harm mitigation with variable ventilations and facility layout. To accomplish this we leverage validated computational resources at Sandia National Laboratories to simulate various release scenarios representative of real world vehicles and maintenance facilities. Flow solvers are used to predict the dynamics of fuel systems as well as the evolution of propane during release events. From our simulated results we observe that both inflow and outflow ventilation locations play a critical role in reducing flammable cloud size and potential overpressure values during a possible combustion event.

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The HyRAM software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM is designed to facilitate the use of state-of-the-art science and engineering models to conduct robust, repeatable assessments of hydrogen safety, hazards, and risk. HyRAM includes generic probabilities for hydrogen equipment failures, probabilistic models for the impact of heat flux on humans and structures, and experimentally validated first-order models of hydrogen release and flame physics. HyRAM integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing hydrogen hazards (thermal effects from jet res, overpressure effects from deflagrations), and assessing impact on people and structures. HyRAM is developed at Sandia National Laboratories for the U.S. Department of Energy to increase access to technical data about hydrogen safety and to enable the use of that data to support development and revision of national and international codes and standards. HyRAM is a research software in active development and thus the models and data may change. This report will be updated at appropriate developmental intervals. This document provides a description of the methodology and models contained in HyRAM version 3.1. There have been several impactful updates since version 3.0. HyRAM 3.1 contains a correction to use the volume fraction for two-phase speed of sound calculations; this only affects cryogenic releases in which two-phase ow (vapor and liquid) is predicted in the orifice. Other changes include clarifications that inputs for tank pressure should be given in absolute pressure, not gauge pressure. Additionally, the interface now rejects invalid inputs to probability distributions, and the less accurate single-point radiative source model selection was removed from the interface.

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The Hydrogen Risk Assessment Model Plus (HyRAM+) toolkit combines quantitative risk assessment with simulations of unignited dispersion, ignited turbulent diffusion flames, and indoor accumulation with delayed ignition of fuels. HyRAM+ is differentiated from HyRAM in that it includes models and leak data for other alternate 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 propane which is being used as a surrogate for autogas, which is a mixture of propane and butane and used in internal combustion engines in vehicles. For flame length comparisons, five previously published experiments from peer reviewed journals were used to validate our models. The validation looked at flame lengths and flame widths with respect to different leak diameters, mass flow rates, and source pressures. Most of the sources included more than one set of experimental data, which were collected using different methods (CCD cameras, IR visualization etc.). In general, HyRAM+ overpredicts the flame lengths by around 65%. For heat and radiation models, we compared the heat flux and radiation data reported from two different sources to the values calculated by HyRAM+. For higher mass flow rates, the HyRAM+ calculated flame length results gave a better estimate of what is found in the experiments (65% error), but a higher error (85%) is observed between the HyRAM+ calculated lengths and the experimental flame lengthsfor lower mass flows. Some differences can be attributed to outdoor environmental effects (i.e. wind speed) and uncertainties in jet flame shapes. The propane flame trajectory is predicted for a high Reynolds number case with Re = 12,500 and a low Reynolds number case where Re = 2,000. The Re=12,500 case which is momentum dominated matches well with the experimental flame trajectory, but the agreement for the bouancy driven low Reynolds number case is not as good. Dispersion modeling for unignited propane was also analyzed. We compared the mole fraction, mixture fraction, mean velocity, concentration half width, and inverse mass concentration over an axial distance from different credible journals to the values calculated by HyRAM+. The results display good agreement but generally, HyRAM+ predicts a wider profile for mole fraction and mixture fraction experiments. Overall, HyRAM+’s results are reasonable for predicting the flame length, heat flux, flame trajectory, and dispersion for propane and can be used in risk analyses

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The availability of repair garage infrastructure for hydrogen fuel cell vehicles is becoming increasingly important for future industry growth. Ventilation requirements for hydrogen fuel cell vehicles can affect both retrofitted and purpose-built repair garages and the costs associated with these requirements can be significant. A hazard and operability (HAZOP) study was performed to identify risk-significant scenarios related to light-duty hydrogen vehicles in a repair garage. Detailed simulations and modeling were performed using appropriate computational tools to estimate the location, behavior, and severity of hydrogen release based on key HAZOP scenarios. Here, this work compares current fire code requirements to an alternate ventilation strategy to further reduce potential hazardous conditions. Modeling shows that position, direction, and velocity of ventilation have a significant impact on the amount of instantaneous flammable mass in the domain.

In this study, large eddy simulations (LES) of offshore boundary layers near the Nantucket coast are performed using Nalu-Wind. The marine boundary layer conditions are chosen to match the predominantly unstable and neutral conditions measured by the Cape Wind platform. The appropriate domain, resolution, and boundary condition settings required for the LES are established through this work. Differences between stable and unstable cases are found in the wind speed profiles, averaged statistics, and wind spectra, and explained in terms of stratification effects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2020-5996C.

The HyRAM software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM is designed to facilitate the use of state-of-the-art science and engineering models to conduct robust, repeatable assessments of hydrogen safety, hazards, and risk. HyRAM includes generic probabilities for hydrogen equipment failures, probabilistic models for the impact of heat flux on humans and structures, and computationally and experimentally validated first-order models of hydrogen release and flame physics. HyRAM integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing hydrogen hazards (thermal effects from jet fires, overpressure effects from deflagrations), and assessing impact on people and structures. HyRAM is developed at Sandia National Laboratories for the U.S. Department of Energy to increase access to technical data about hydrogen safety and to enable the use of that data to support development and revision of national and international codes and standards. HyRAM is a research software in active development and thus the models and data may change. This report will be updated at appropriate developmental intervals. This document provides a description of the methodology and models contained in the HyRAM version 3.0. HyRAM 3.0 includes the new ability to model cryogenic hydrogen releases from liquid hydrogen systems, using a different property calculation method and different equations of state. Other changes include modifications to the ignition probability calculations, component leak frequency calculations, and addition of default impulse data.

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Previous research has revealed the need for a validation study that considers several wake quantities and code types so that decisions on the trade-off between accuracy and computational cost can be well informed and appropriate to the intended application. In addition to guiding code choice and setup, rigorous model validation exercises are needed to identify weaknesses and strengths of specific models and guide future improvements. Here, we consider 13 approaches to simulating wakes observed with a nacelle-mounted lidar at the Scaled Wind Technology Facility (SWiFT) under varying atmospheric conditions. We find that some of the main challenges in wind turbine wake modeling are related to simulating the inflow. In the neutral benchmark, model performance tracked as expected with model fidelity, with large-eddy simulations performing the best. In the more challenging stable case, steady-state Reynolds-averaged Navier–Stokes simulations were found to outperform other model alternatives because they provide the ability to more easily prescribe noncanonical inflows and their low cost allows for simulations to be repeated as needed. Dynamic measurements were only available for the unstable benchmark at a single downstream distance. These dynamic analyses revealed that differences in the performance of time-stepping models come largely from differences in wake meandering. This highlights the need for more validation exercises that take into account wake dynamics and are able to identify where these differences come from: mesh setup, inflow, turbulence models, or wake-meandering parameterizations. In addition to model validation findings, we summarize lessons learned and provide recommendations for future benchmark exercises.

Turbulent mixing in pilot-scale cultivation systems influences the productivity of photoautotrophic cultures. We studied turbulent mixing by applying particle image velocimetry and acoustic doppler velocimetry to pilot-scale, flat-panel photobioreactor, and open-channel raceway. Mixing energy inputs were varied from 0.1 to 2.1 W·m−3. The experimental results were used to quantify turbulence and to validate computational fluid dynamics models, from which Lagrangian representations of the fluid motion in these reactors were derived. The results of this investigation demonstrated that differences in mixing energy input do not significantly impact the structure of turbulence and the light/dark cycling frequencies experienced by photoautotrophic cells within the reactors. The experimental and computational results of our research demonstrated that well-mixed conditions exist in pilot-scale, flat-panel photobioreactors and open-channel raceways, even for relatively low mixing energy inputs.

Milestone Description: Enhance Nalu-Wind's actuator disc model through hardening, documenting, stress-testing, verifying, and validating. Existing workflows will be improved by reducing the data output stream, and by making the analysis capabilities more modular and generally better. These model capabilities are needed by other A2e areas, namely Wake Dynamics, AWAKEN, and VV&UQ.

The availability of repair garage infrastructure for hydrogen fuel cell vehicles is becoming increasingly important for future industry growth. Ventilation requirements for hydrogen fuel cell vehicles can affect both retrofitted and purpose-built repair garages and the costs associated with these requirements can be significant. A hazard and operability study (HAZOP) was performed to identify key risk-significant scenarios related to hydrogen vehicles in a repair garage. Detailed simulations and modeling were performed using appropriate computational tools to estimate the location, behavior, and severity of hydrogen release based on key HAZOP scenarios. This work compares current fire code requirements to an alternate ventilation strategy to further reduce potentially hazardous conditions. Overall, the amount of flammable mass of hydrogen at any one time in the simulation is low compared to the total mass of hydrogen released, due to the low flow rate of a low pressure release. It is shown that position, direction, and velocity of ventilation have a significant impact on the amount of instantaneous flammable mass in the domain.

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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.

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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.

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