Tabulated chemistry models are widely used to simulate large-scale turbulent fires in applications including energy generation and fire safety. Tabulation via piecewise Cartesian interpolation suffers from the curse-of-dimensionality, leading to a prohibitive exponential growth in parameters and memory usage as more dimensions are considered. Artificial neural networks (ANNs) have attracted attention for constructing surrogates for chemistry models due to their ability to perform high-dimensional approximation. However, due to well-known pathologies regarding the realization of suboptimal local minima during training, in practice they do not converge and provide unreliable accuracy. Partition of unity networks (POUnets) are a recently introduced family of ANNs which preserve notions of convergence while performing high-dimensional approximation, discovering a mesh-free partition of space which may be used to perform optimal polynomial approximation. In this work, we assess their performance with respect to accuracy and model complexity in reconstructing unstructured flamelet data representative of nonadiabatic pool fire models. Our results show that POUnets can provide the desirable accuracy of classical spline-based interpolants with the low memory footprint of traditional ANNs while converging faster to significantly lower errors than ANNs. For example, we observe POUnets obtaining target accuracies in two dimensions with 40 to 50 times less memory and roughly double the compression in three dimensions. We also address the practical matter of efficiently training accurate POUnets by studying convergence over key hyperparameters, the impact of partition/basis formulation, and the sensitivity to initialization.
In this work, medium scale (30 cm diameter) methanol pool fires were simulated using the latest fire modeling suite implemented in Sierra/Fuego, a low Mach number multiphysics reacting flow code. The sensitivity of model outputs to various model parameters was studied with the objective of providing model validation. This work also assesses model performance relative to other recently published large eddy simulations (LES) of the same validation case. Two pool surface boundary conditions were simulated. The first was a prescribed fuel mass flux and the second used an algorithm to predict mass flux based on a mass and energy balance at the fuel surface. Gray gas radiation model parameters (absorption coefficients and gas radiation sources) were varied to assess radiant heat losses to the surroundings and pool surface. The radiation model was calibrated by comparing the simulated radiant fraction of the plume to experimental data. The effects of mesh resolution were also quantified starting with a grid resolution representative of engineering type fire calculations and then uniformly refining that mesh in the plume region. Simulation data were compared to experimental data collected at the University of Waterloo and the National Institute of Standards and Technology (NIST). Validation data included plume temperature, radial and axial velocities, velocity temperature turbulent correlations, velocity velocity turbulent correlations, radiant and convective heat fluxes to the pool surface, and plume radiant fraction. Additional analyses were performed in the pool boundary layer to assess simulated flame anchoring and the effect on convective heat fluxes. This work assesses the capability of the latest Fuego physics and chemistry model suite and provides additional insight into pool fire modeling for nonluminous, non-sooting flames.
All-solid-state batteries are often assumed to be safer than conventional Li-ion ones. In this work, we present the first thermodynamic models to quantitatively evaluate solid-state and Li-ion battery heat release under several failure scenarios. The solid-state battery analysis is carried out with an Li7La3Zr2O12 solid electrolyte but can be extended to other configurations using the accompanying spreadsheet. We consider solid-state batteries that include a relatively small amount of liquid electrolyte, which is often added at the cathode to reduce interfacial resistance. While the addition of small amounts of liquid electrolyte increases heat release under specific failure scenarios, it may be small enough that other considerations, such as manufacturability and performance, are more important commercially. We show that short-circuited all-solid-state batteries can reach temperatures significantly higher than conventional Li-ion, which could lead to fire through flammable packaging and/or nearby materials. Our work highlights the need for quantitative safety analyses of solid-state batteries.
This is the Sandia report from a joint NSRD project between Sandia National Labs and Savannah River National Labs. The project involved development of simulation tools and data intended to be useful for tritium operations safety assessment. Tritium is a synthetic isotope of hydrogen that has a limited lifetime, and it is found at many tritium facilities in the form of elemental gas (T2). The most serious risk of reasonable probability in an accident scenario is when the tritium is released and reacts with oxygen to form a water molecule, which is subsequently absorbed into the human body. This tritium oxide is more readily absorbed by the body and therefore represents a limiting factor for safety analysis. The abnormal condition of a fire may result in conversion of the safer T2 inventory to the more hazardous oxidized form. It is this risk that tends to govern the safety protocols. Tritium fire datasets do not exist, so prescriptive safety guidance is largely conservative and reliant on means other than testing to formulate guidelines. This can have a consequence in terms of expensive and/or unnecessary mitigation design, handling protocols, and operational activities. This issue can be addressed through added studies on the behavior of tritium under representative conditions. Due to the hazards associated with the tests, this is being approached mainly from a modeling and simulation standpoint and surrogate testing. This study largely establishes the capability to generate simulation predictions with sufficiently credible characteristics to be accepted for safety guidelines as a surrogate for actual data through a variety of testing and modeling activities.
Chemistry tabulation is a common approach in practical simulations of turbulent combustion at engineering scales. Linear interpolants have traditionally been used for accessing precomputed multidimensional tables but suffer from large memory requirements and discontinuous derivatives. Higher-degree interpolants address some of these restrictions but are similarly limited to relatively low-dimensional tabulation. Artificial neural networks (ANNs) can be used to overcome these limitations but cannot guarantee the same accuracy as interpolants and introduce challenges in reproducibility and reliable training. These challenges are enhanced as the physics complexity to be represented within the tabulation increases. In this manuscript, we assess the efficiency, accuracy, and memory requirements of Lagrange polynomials, tensor product B-splines, and ANNs as tabulation strategies. We analyze results in the context of nonadiabatic flamelet modeling where higher dimension counts are necessary. While ANNs do not require structuring of data, providing benefits for complex physics representation, interpolation approaches often rely on some structuring of the table. Interpolation using structured table inputs that are not directly related to the variables transported in a simulation can incur additional query costs. This is demonstrated in the present implementation of heat losses. We show that ANNs, despite being difficult to train and reproduce, can be advantageous for high-dimensional, unstructured datasets relevant to nonadiabatic flamelet models. We also demonstrate that Lagrange polynomials show significant speedup for similar accuracy compared to B-splines.
This report describes an assessment of flamelet based soot models in a laminar ethylene coflow flame with a good selection of measurements suitable for model validation. Overall flow field and temperature predictions were in good agreement with available measurements. Soot profiles were in good agreement within the flame except for near the centerline where imperfections with the acetylene-based soot-production model are expected to be greatest. The model was challenged to predict the transition between non-sooting and sooting conditions with non-negligible soot emissions predicted even down to small flow rates or flame sizes. This suggests some possible deficiency in the soot oxidation models that might alter the amount of smoke emissions from flames, though this study cannot quantify the magnitude of the effect for large fires.
This report summarizes a series of SIERRA/Fuego validation efforts of turbulent flow models on canonical wall-bounded configurations. In particular, direct numerical simulations (DNS) and large eddy simulations (LES) turbulence models are tested on a periodic channel, a periodic pipe, and an open jet for which results are compared to the velocity profiles obtained theoretically or experimentally. Velocity inlet conditions for channel and pipe flows are developed for application to practical simulations. To show this capability, LES is performed over complex terrain in the form of two natural hills and the results are compared with other flow solvers. The practical purpose of the report is to document the creation of inflow boundary conditions of fully developed turbulent flows for other LES calculations where the role of inflow turbulence is critical.
A low-Mach, unstructured, large-eddy-simulation-based, unsteady flamelet approach with a generalized heat loss combustion methodology (including soot generation and consumption mechanisms) is deployed to support a large-scale, quiescent, 5-m JP-8 pool fire validation study. The quiescent pool fire validation study deploys solution sensitivity procedures, i.e., the effect of mesh and time step refinement on capturing key fire dynamics such as fingering and puffing, as mesh resolutions approach O(1) cm. A novel design-order, discrete-ordinate-method discretization methodology is established by use of an analytical thermal/participating media radiation solution on both low-order hexahedral and tetrahedral mesh topologies in addition to quadratic hexahedral elements. The coupling between heat losses and the flamelet thermochemical state is achieved by augmenting the unsteady flamelet equation set with a heat loss source term. Soot and radiation source terms are determined using flamelet approaches for the full range of heat losses experienced in fire applications including radiative extinction. The proposed modeling and simulation paradigm are validated using pool surface radiative heat flux, maximum centerline temperature location, and puffing frequency data, all of which are predicted within 10% accuracy. Simulations demonstrate that under-resolved meshes predict an overly conservative radiative heat flux magnitude with improved comparisons as compared to a previously deployed hybrid Reynolds-averaged Navier-Stokes/eddy dissipation concept-based methodology.
This work uses accelerating rate calorimetry to evaluate the impact of cell chemistry, state of charge, cell capacity, and ultimately cell energy density on the total energy release and peak heating rates observed during thermal runaway of Li-ion batteries. While the traditional focus has been using calorimetry to compare different chemistries in cells of similar sizes, this work seeks to better understand how applicable small cell data is to understand the thermal runaway behavior of large cells as well as determine if thermal runaway behaviors can be more generally tied to aspects of lithium-ion cells such as total stored energy and specific energy. We have found a strong linear correlation between the total enthalpy of the thermal runaway process and the stored energy of the cell, apparently independent of cell size and state of charge. We have also shown that peak heating rates and peak temperatures reached during thermal runaway events are more closely tied to specific energy, increasing exponentially in the case of peak heating rates.
Energy storage using lithium-ion cells dominates consumer electronics and is rapidly becoming predominant in electric vehicles and grid-scale energy storage, but the high energy densities attained lead to the potential for release of this stored chemical energy. This article introduces some of the paths by which this energy might be unintentionally released, relating cell material properties to the physical processes associated with this potential release. The selected paths focus on the anode–electrolyte and cathode–electrolyte interactions that are of typical concern for current and near-future systems. Relevant material processes include bulk phase transformations, bulk diffusion, surface reactions, transport limitations across insulating passivation layers, and the potential for more complex material structures to enhance safety. We also discuss the development, parameterization, and application of predictive models for this energy release and give examples of the application of these models to gain further insight into the development of safer energy storage systems.
Thermal runaway of Li-ion batteries is a risk that is magnified when stacks of lithium-ion cells are used for large scale energy storage. When limits of propagation can be identified so that systems can be designed to prevent large scale cascading failure even if a failure does occur, these systems will be safer. The prediction of cell-to-cell failure propagation and the propagation limits in lithium-ion cell stacks were studied to better understand and identify safe designs. A thermal-runaway model was considered based on recent developments in thermochemical source terms. Propagating failure was characterized by temperatures above which calorimetry data is available. Results showed high temperature propagating failure predictions are too rapid unless an intra-particle diffusion limit is included, introducing a Damköhler number limiter into the rate expression. This new model form was evaluated against cell-to-cell failure propagation where the end cell of a stack is forced into thermal runaway through a nail-induced short circuit. Limits of propagation for this configuration are identified. Results showed cell-to-cell propagation predictions are consistent with measurements over a range of cell states of charge and with the introduction of metal plates between cells to add system heat capacity representative of structural members. This consistency extends from scenarios where propagation occurs through scenarios where propagation is prevented.
The heat generated during a single cell failure within a high energy battery system can force adjacent cells into thermal runaway, creating a cascading propagation effect through the entire system. This work examines the response of modules of stacked pouch cells after thermal runaway is induced in a single cell. The prevention of cascading propagation is explored on cells with reduced states of charge and stacks with metal plates between cells. Reduced states of charge and metal plates both reduce the energy stored relative to the heat capacity, and the results show how cascading propagation may be slowed and mitigated as this varies. These propagation limits are correlated with the stored energy density. Results show significant delays between thermal runaway in adjacent cells, which are analyzed to determine intercell contact resistances and to assess how much heat energy is transmitted to cells before they undergo thermal runaway. A propagating failure of even a small pack may stretch over several minutes including delays as each cell is heated to the point of thermal runaway. This delay is described with two new parameters in the form of gap-crossing and cell-crossing time to grade the propensity of propagation from cell to cell.
Accurate models of thermal runaway in lithium-ion batteries require quantitative knowledge of heat release during thermochemical processes. A capability to predict at least some aspects of heat release for a wide variety of candidate materials a priori is desirable. This work establishes a framework for predicting staged heat release from basic thermodynamic properties for layered metal-oxide cathodes. Available enthalpies relevant to thermal decomposition of layered metal-oxide cathodes are reviewed and assembled in this work to predict potential heat release in the presence of alkyl-carbonate electrolytes with varying state of charge. Cathode delithiation leads to a less stable metal oxide subject to phase transformations including oxygen release when heated. We recommend reaction enthalpies and show the thermal consequences of metal-oxide phase changes and solvent oxidation within the battery are of comparable magnitudes. Heats of reaction are related in this work to typical observations reported in the literature for species characterization and calorimetry. The methods and assembled databases of formation and reaction enthalpies in this work lay groundwork a new generation of thermal runaway models based on fundamental material thermodynamics, capable of predicting accurate maximum cell temperatures and hence cascading cell-to-cell propagation rates.
Lithium-ion battery safety is prerequisite for applications from consumer electronics to grid energy storage. Cell and component-level calorimetry studies are central to safety evaluations. Qualitative empirical comparisons have been indispensable in understanding decomposition behavior. More systematic calorimetry studies along with more comprehensive measurements and reporting can lead to more quantitative mechanistic understanding. This mechanistic understanding can facilitate improved designs and predictions for scenarios that are difficult to access experimentally, such as system-level failures. Recommendations are made to improve usability of calorimetry results in mechanistic understanding. From our perspective, this path leads to a more mature science of battery safety.
Heat release that leads to thermal runaway of lithium-ion batteries begins with decomposition reactions associated with lithiated graphite. We broadly review the observed phenomena related to lithiated graphite electrodes and develop a comprehensive model that predicts with a single parameter set and with reasonable accuracy measurements over the available temperature range with a range of graphite particle sizes. The model developed in this work uses a standardized total heat release and takes advantage of a revised dependence of reaction rates and the tunneling barrier on specific surface area. The reaction extent is limited by inadequate electrolyte or lithium. Calorimetry measurements show that heat release from the reaction between lithiated graphite and electrolyte accelerates above ~200°C, and the model addresses this without introducing additional chemical reactions. This method assumes that the electron-tunneling barrier through the solid electrolyte interphase (SEI) grows initially and then becomes constant at some critical magnitude, which allows the reaction to accelerate as the temperature rises by means of its activation energy. Phenomena that could result in the upper limit on the tunneling barrier are discussed. The model predictions with two candidate activation energies are evaluated through comparisons to calorimetry data, and recommendations are made for optimal parameters.
This study addresses predicting the internal thermochemical state in buoyant fire plumes using largeeddy simulations (LES) with a tabular flamelet library for the underlying flame chemistry. Buoyant fire plumes are characterized by moderate turbulent mixing, soot growth and oxidation and radiation transport. Soot moments, mixture fraction and enthalpy evolve in the LES with soot source terms given by the non-adiabatic flamelet library. Participating media radiation transport is predicted using the discrete ordinates method with source terms also from the flamelet library, and the LES subgrid-scale modeling is based on a one-equation kinetic-energy sub-filter model. This library is generated with flamelet states that include unsteady heat loss through extinction nominally representing radiative quenching. We describe the performance of this model both in the context of a laminar coflow configuration where extensive measurements are available and in buoyant turbulent fire plumes where measurements are more global.
ODT (one-dimensional turbulence) simulations of particle-carrier gas interactions are performed in the jet flow configuration. Particles with different diameters are injected onto the centerline of a turbulent air jet. The particles are passive and do not impact the fluid phase. Their radial dispersion and axial velocities are obtained as functions of axial position. The time and length scales of the jet are varied through control of the jet exit velocity and nozzle diameter. Dispersion data at long times of flight for the nozzle diameter (7 mm), particle diameters (60 and 90 µm), and Reynolds numbers (10, 000–30, 000) are analyzed to obtain the Lagrangian particle dispersivity. Flow statistics of the ODT particle model are compared to experimental measurements. It is shown that the particle tracking method is capable of yielding Lagrangian prediction of the dispersive transport of particles in a round jet. In this paper, three particle-eddy interaction models (Type-I, -C, and -IC) are presented to examine the details of particle dispersion and particle-eddy interaction in jet flow.
A 1-m diameter methane fire plume has been studied using a large eddy simulation (LES) methodology. Eddy dissipation concept (EDC) and steady flamelet combustion models were used to describe interactions between buoyancy-induced turbulence and gas-phase combustion. Detailed comparisons with experimental data showed that the simulation is sensitive to the combustion model and mesh resolution. In particular, any excessive mixing results in a wider and more diffusive plume. As mesh resolution increases, the current simulations demonstrate a tendency toward excessive mixing.
As deployment of large-scale Li-Ion battery modules is contemplated, there is a need to understand the propensity for thermal runaway in individual cells and the large-scale thermal failure at the pack level. Sources of thermal energy can lead to runaway including short circuits (internal or external), exothermic processes from overcharge of imbalanced cells, the external environment, and other factors. With battery modules consisting of hundreds or even thousands of cells, it will be necessary to design tolerance to local heat release, regardless of the source. This work presents a chemistry-independent framework for analyzing and modeling thermal runaway that will be demonstrated by applying it to thermal runaway (ignition) and cascading failure (propagation).
Turbulent fluctuations of the scalar dissipation rate have a major impact on extinction in non-premixed combustion. Recently, an unsteady extinction criterion has been developed (Hewson, 2013) that predicts extinction dependent on the duration and the magnitude of dissipation rate fluctuations exceeding a critical quenching value; this quantity is referred to as the dissipation impulse. The magnitude of the dissipation impulse corresponding to unsteady extinction is related to the difficulty with which a flamelet is exintguished, based on the steady-state S-curve. In this paper we evaluate this new extinction criterion for more realistic dissipation rates by evolving a stochastic Ornstein-Uhlenbeck process for the dissipation rate. A comparison between unsteady flamelet evolution using this dissipation rate and the extinction criterion exhibit good agreement. The rate of predicted extinction is examined over a range of Damköhler and Reynolds numbers and over a range of the extinction difficulty. The results suggest that the rate of extinction is proportional to the average dissipation rate and the area under the dissipation rate probability density function exceeding the steady-state quenching value. It is also inversely related to the actual probability that this steady-state quenching dissipation rate is observed and the difficulty of extinction associated with the distance between the upper and middle branches of the S-curve.
The suitability of crude and purified struvite (MgNH4PO4), a major precipitate in wastewater streams, was investigated for renewable replacement of conventional nitrogen and phosphate resources for cultivation of microalgae. Bovine effluent wastewater stone, the source of crude struvite, was characterized for soluble N/P, trace metals, and biochemical components and compared to the purified mineral. Cultivation trials using struvite as a major nutrient source were conducted using two microalgae production strains, Nannochloropsis salina and Phaeodactylum tricornutum, in both lab and outdoor pilot-scale raceways in a variety of seasonal conditions. Both crude and purified struvite-based media were found to result in biomass productivities at least as high as established media formulations (maximum outdoor co-culture yield ~20±4gAFDW/m2/day). Analysis of nutrient uptake by the alga suggest that struvite provides increased nutrient utilization efficiency, and that crude struvite satisfies the trace metals requirement and results in increased pigment productivity for both microalgae strains.
Alkaline flocculation holds great potential as a low-cost harvesting method for marine microalgae biomass production. Alkaline flocculation is induced by an increase in pH and is related to precipitation of calcium and magnesium salts. In this study, we used the diatom Phaeodactylum tricornutum as model organism to study alkaline flocculation of marine microalgae cultured in seawater medium. Flocculation started when pH was increased to 10 and flocculation efficiency reached 90% when pH was 10.5, which was consistent with precipitation modeling for brucite or Mg(OH)2. Compared to freshwater species, more magnesium is needed to achieve flocculation (>7.5mM). Zeta potential measurements suggest that brucite precipitation caused flocculation by charge neutralization. When calcium concentration was 12.5mM, flocculation was also observed at a pH of 10. Zeta potential remained negative up to pH 11.5, suggesting that precipitated calcite caused flocculation by a sweeping coagulation mechanism.
We present a detailed set of measurements from a piloted, sooting, turbulent C 2 H 4 - fueled diffusion flame. Hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (CARS) is used to monitor temperature and oxygen, while laser-induced incandescence (LII) is applied for imaging of the soot volume fraction in the challenging jet-flame environment at Reynolds number, Re = 20,000. Single-laser shot results are used to map the mean and rms statistics, as well as probability densities. LII data from the soot-growth region of the flame are used to benchmark the soot source term for one-dimensional turbulence (ODT) modeling of this turbulent flame. The ODT code is then used to predict temperature and oxygen fluctuations higher in the soot oxidation region higher in the flame.
The objective of this work is to investigate the efficacy of using calibration strategies from Uncertainty Quantification (UQ) to determine model coefficients for LES. As the target methods are for engineering LES, uncertainty from numerical aspects of the model must also be quantified. 15 The ultimate goal of this research thread is to generate a cost versus accuracy curve for LES such that the cost could be minimized given an accuracy prescribed by an engineering need. Realization of this goal would enable LES to serve as a predictive simulation tool within the engineering design process.
In this study, Chlorella zofingiensis harvesting by dissolved air flotation (DAF) was critically evaluated with regard to algal concentration, culture conditions, type and dosage of coagulants, and recycle ratio. Harvesting efficiency increased with coagulant dosage and leveled off at 81%, 86%, 91%, and 87% when chitosan, Al3+, Fe3+, and cetyl trimethylammonium bromide (CTAB) were used at dosages of 70, 180, 250, and 500mgg-1, respectively. The DAF efficiency-coagulant dosage relationship changed with algal culture conditions. Evaluation of the influence of the initial algal concentration and recycle ratio revealed that, under conditions typical for algal harvesting, it is possible that the number of bubbles is insufficient. A DAF algal harvesting model was developed to explain this observation by introducing mass-based floc size distributions and a bubble limitation into the white water blanket model. The model revealed the importance of coagulation to increase floc-bubble collision and attachment, and the preferential interaction of bubbles with larger flocs, which limited the availability of bubbles to the smaller sized flocs. The harvesting efficiencies predicted by the model agree reasonably with experimental data obtained at different Al3+ dosages, algal concentrations, and recycle ratios. Based on this modeling, critical parameters for efficient algal harvesting were identified. Biotechnol.
Lagrangian particle dispersion is studied using the one-dimensional turbulence (ODT) model in homogeneous decaying turbulence configurations. The ODT model has been widely and successfully applied to a number of reacting and nonreacting flow configurations, but only limited application has been made to multiphase flows. We present a version of the particle implementation and interaction with the stochastic and instantaneous ODT eddy events. The model is characterized by comparison to experimental data of particle dispersion for a range of intrinsic particle time scales and body forces. Particle dispersion, velocity, and integral time scale results are presented. Moreover, the particle implementation introduces a single model parameter β p , and sensitivity to this parameter and behavior of the model are discussed. Good agreement is found with experimental data and the ODT model is able to capture the particle inertial and trajectory crossing effects. Our results serve as a validation case of the multiphase implementations of ODT for extensions to other flow configurations.
Particles in non - isothermal turbulent flow are subject to a stochastic environment tha t produces a distribution of particle time - temperature histories. This distribution is a function of the dispersion of the non - isothermal (continuous) gas phase and the distribution of particles relative to that gas phase. In this work we extend the one - dimensional turbulence (ODT) model to predict the joint dispersion of a dispersed particle phase and a continuous phase. The ODT model predicts the turbulent evolution of continuous scalar fields with a model for the cascade of fluctuations to smaller sc ales (the 'triplet map') at a rate that is a function of the fully resolved one - dimens ional velocity field . Stochastic triplet maps also drive Lagrangian particle dispersion with finite Stokes number s including inertial and eddy trajectory - crossing effect s included. Two distinct approaches to this coupling between triplet maps and particle dispersion are developed and implemented along with a hybrid approach. An 'instantaneous' particle displacement model matches the tracer particle limit and provide s an accurate description of particle dispersion. A 'continuous' particle displacement m odel translates triplet maps into a continuous velocity field to which particles respond. Particles can alter the turbulence, and modifications to the stochastic rate expr ession are developed for two - way coupling between particles and the continuous phase. Each aspect of model development is evaluated in canonical flows (homogeneous turbulence, free - shear flows and wall - bounded flows) for which quality measurements are ava ilable. ODT simulations of non - isothermal flows provide statistics for particle heating. These simulations show the significance of accurately predicting the joint statistics of particle and fluid dispersion . Inhomogeneous turbulence coupled with the in fluence of the mean flow fields on particles of varying properties alter s particle dispersion. The joint particle - temperature dispersion leads to a distribution of temperature histories predicted by the ODT . Predictions are shown for the lower moments an d the full distributions of the particle positions, particle - observed gas temperatures and particle temperatures. An analysis of the time scales affecting particle - temperature interactions covers Lagrangian integral time scales based on temperature autoco rrelations, rates of temperature change associated with particle motion relative to the temperature field and rates of diffusional change of temperatures. These latter two time scales have not been investigated previously; they are shown to be strongly in termittent having peaked distributions with long tails. The logarithm of the absolute value of these time scales exhibits a distribution closer to normal. A cknowledgements This work is supported by the Defense Threat Reduction Agency (DTRA) under their Counter - Weapons of Mass Destruction Basic Research Program in the area of Chemical and Biological Agent Defeat under award number HDTRA1 - 11 - 4503I to Sandia National Laboratories. The authors would like to express their appreciation for the guidance provi ded by Dr. Suhithi Peiris to this project and to the Science to Defeat Weapons of Mass Destruction program.
Progress toward predictions of the statistics of particle time-temperature histories is presented. These predictions are to be made using Lagrangian particle models within the one-dimensional turbulence (ODT) model. In the present reporting period we have further characterized the performance, behavior and capabilities of the particle dispersion models that were added to the ODT model in the first period. We have also extended the capabilities in two manners. First we provide alternate implementations of the particle transport process within ODT; within this context the original implementation is referred to as the type-I and the new implementations are referred to as the type-C and type-IC interactions. Second we have developed and implemented models for two-way coupling between the particle and fluid phase. This allows us to predict the reduced rate of turbulent mixing associated with particle dissipation of energy and similar phenomena. Work in characterizing these capabilities has taken place in homogeneous decaying turbulence, in free shear layers, in jets and in channel flow with walls, and selected results are presented.
This document summarizes a three year Laboratory Directed Research and Development (LDRD) program effort to improve our understanding of algal flocculation with a key to overcoming harvesting as a techno-economic barrier to algal biofuels. Flocculation is limited by the concentrations of deprotonated functional groups on the algal cell surface. Favorable charged groups on the surfaces of precipitates that form in solution and the interaction of both with ions in the water can favor flocculation. Measurements of algae cell-surface functional groups are reported and related to the quantity of flocculant required. Deprotonation of surface groups and complexation of surface groups with ions from the growth media are predicted in the context of PHREEQC. The understanding of surface chemistry is linked to boundaries of effective flocculation. We show that the phase-space of effective flocculation can be expanded by more frequent alga-alga or floc-floc collisions. The collision frequency is dependent on the floc structure, described in the fractal sense. The fractal floc structure is shown to depend on the rate of shear mixing. We present both experimental measurements of the floc structure variation and simulations using LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). Both show a densification of the flocs with increasing shear. The LAMMPS results show a combined change in the fractal dimension and a change in the coordination number leading to stronger flocs.
Expert panels comprised of subject matter experts identified at the U.S. National Laboratories (SNL, ANL, INL, ORNL, LBL, and BNL), universities (University of Wisconsin and Ohio State University), international agencies (IRSN, CEA, JAEA, KAERI, and JRC-IE) and private consultation companies (Radiation Effects Consulting) were assembled to perform a gap analysis for sodium fast reactor licensing. Expert-opinion elicitation was performed to qualitatively assess the current state of sodium fast reactor technologies. Five independent gap analyses were performed resulting in the following topical reports: (1) Accident Initiators and Sequences (i.e., Initiators/Sequences Technology Gap Analysis), (2) Sodium Technology Phenomena (i.e., Advanced Burner Reactor Sodium Technology Gap Analysis), (3) Fuels and Materials (i.e., Sodium Fast Reactor Fuels and Materials: Research Needs), (4) Source Term Characterization (i.e., Advanced Sodium Fast Reactor Accident Source Terms: Research Needs), and (5) Computer Codes and Models (i.e., Sodium Fast Reactor Gaps Analysis of Computer Codes and Models for Accident Analysis and Reactor Safety). Volume II of the Sodium Research Plan consolidates the five gap analysis reports produced by each expert panel, wherein the importance of the identified phenomena and necessities of further experimental research and code development were addressed. The findings from these five reports comprised the basis for the analysis in Sodium Fast Reactor Research Plan Volume I.
With the scoping experimental results, initial computational model development is underway. Coupling the experimental program with the computational modern analysis will develop the expertise and capability needed to identify, investigate, and assess key metal fires issues.
A joint temperature/soot laser-based optical diagnostic was developed for the determination of the joint temperature/soot probability density function (PDF) for hydrocarbon-fueled meter-scale turbulent pool fires. This Laboratory Directed Research and Development (LDRD) effort was in support of the Advanced Simulation and Computing (ASC) program which seeks to produce computational models for the simulation of fire environments for risk assessment and analysis. The development of this laser-based optical diagnostic is motivated by the need for highly-resolved spatio-temporal information for which traditional diagnostic probes, such as thermocouples, are ill-suited. The in-flame gas temperature is determined from the shape of the nitrogen Coherent Anti-Stokes Raman Scattering (CARS) signature and the soot volume fraction is extracted from the intensity of the Laser-Induced Incandescence (LII) image of the CARS probed region. The current state of the diagnostic will be discussed including the uncertainty and physical limits of the measurements as well as the future applications of this probe.
The potential for liquid aluminum to dissolve an iridium solid is examined. Substantial uncertainties exist in material properties, and the available data for the iridium solubility and iridium diffusivity are discussed. The dissolution rate is expressed in terms of the regression velocity of the solid iridium when exposed to the solvent (aluminum). The temperature has the strongest influence in the dissolution rate. This dependence comes primarily from the solubility of iridium in aluminum and secondarily from the temperature dependence of the diffusion coefficient. This dissolution mass flux is geometry dependent and results are provided for simplified geometries at constant temperatures. For situations where there is negligible convective flow, simple time-dependent diffusion solutions are provided. Correlations for mass transfer are also given for natural convection and forced convection. These estimates suggest that dissolution of iridium can be significant for temperatures well below the melting temperature of iridium, but the uncertainties in actual rates are large because of uncertainties in the physical parameters and in the details of the relevant geometries.
This report documents the results of a Phenomena Identification and Ranking Table (PIRT) exercise performed at Sandia National Laboratories (SNL) as well as the experimental and modeling program that have been designed based on the PIRT results. A PIRT exercise is a structured and facilitated expert elicitation process. In this case, the expert panel was comprised of nine recognized fire science and aerosol experts. The objective of a PIRT exercise is to identify phenomena associated with the intended application and to then rank the current state of knowledge relative to each identified phenomenon. In this particular PIRT exercise the intended application was sodium fire modeling related to sodium-cooled advanced reactors. The panel was presented with two specific fire scenarios, each based on a hypothetical sodium leak in an Advanced Breeder Test Reactor (ABTR) design. For both scenarios the figure of merit was the ability to predict the thermal and aerosol insult to nearby equipment (i.e. heat exchangers and other electrical equipment). When identifying phenomena of interest, and in particular when ranking phenomena importance and the adequacy of existing modeling tools and data, the panel was asked to subjectively weigh these factors in the context of the specified figure of merit. Given each scenario, the panel identified all those related phenomena that are of potential interest to an assessment of the scenario using fire modeling tools to evaluate the figure of merit. Each phenomenon is then ranked relative to its importance in predicting the figure of merit. Each phenomenon is then further ranked for the existing state of knowledge with respect to the ability of existing modeling tools to predict that phenomena, the underlying base of data associated with the phenomena, and the potential for developing new data to support improvements to the existing modeling tools. For this PIRT two hypothetical sodium leak scenarios were evaluated for the ABTR design. The first scenario was a leak in the hot side of the intermediate heat transport system (IHTS) resulting in a sodium pool fire. The second scenario was a leak in the cold side of the IHTS resulting in a sodium spray fire.
Public safety and acceptance is extremely important for the nuclear power renaissance to get started. The Advanced Burner Reactor and other potential designs utilize liquid sodium as a primary coolant which provides distinct challenges to the nuclear power industry. Fire is a dominant contributor to total nuclear plant risk events for current generation nuclear power plants. Utilizing past experience to develop suitable safety systems and procedures will minimize the chance of sodium leaks and the associated consequences in the next generation. An advanced understanding of metal fire behavior in regards to the new designs will benefit both science and industry. This report presents an extensive literature review that captures past experiences, new advanced reactor designs, and the current state-of-knowledge related to liquid sodium combustion behavior.