Publications

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This work will be presented at the combustion symposium in Milan, Italy.

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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. 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.

Numerical simulations were performed in 3D Cartesian coordinates to examine the post-detonation processes produced by the detonation of a 12 mm-diameter hemispherical PETN explosive charge in air. The simulations captured air dissociation by the Mach 20+ shock, chemical equilibration, and afterburning using finite-rate chemical kinetics with a skeletal chemical reaction mechanism. The Becker-Kistiakowsky-Wilson real-gas equation of state is used for the gas-phase. A simplified programmed burn model is used to seamlessly couple the detonation propagation through the explosive charge to the post-detonation reaction processes inside the fireball. Four charge sizes were considered, including diameters of 12 mm, 38 mm, 120 mm, and 1200 mm. The computed blast, shock structures, and chemical composition within the fireball agree with literature. The evolution of the flow at early times is shown to be gas dynamic driven and nearly self-similar when the time and space was scaled. The flow fields were azimuthally averaged and a mixing layer analysis was performed. The results show differences in the temperature and chemical composition with increasing charge size, implying a transition from a chemical kinetic-limited to a mixing-limited regime.

The ability to accurately predict the structure and dynamics of pool fires using computational simulations is of great interest in a wide variety of applications, including accidental and wildland fires. However, the presence of physical processes spanning a broad range of spatial and temporal scales poses a significant challenge for simulations of such fires, particularly at conditions near the transition between laminar and turbulent flow. In this study, we examine the transition to turbulence in methane pool fires using high-resolution simulations with multi-step finite rate chemistry, where adaptive mesh refinement (AMR) is used to directly resolve small-scale flow phenomena. We perform three simulations of methane pool fires, each with increasing diameter, corresponding to increasing inlet Reynolds and Richardson numbers. As the diameter increases, the flow transitions from organized vortex roll-up via the puffing instability to much more chaotic mixing associated with finger formation along the shear layer and core collapse near the inlet. These effects combine to create additional mixing close to the inlet, thereby enhancing fuel consumption and causing more rapid acceleration of the fluid above the pool. We also make comparisons between the transition to turbulence and core collapse in the present pool fires and in inert helium plumes, which are often used as surrogates for the study of buoyant reacting flows.

As large systems of Li-ion batteries are being increasingly deployed, the safety of such systems must be assessed. Due to the high cost of testing large systems, it is important to extract key safety information from any available experiments. Developing validated predictive models that can be exercised at larger scales offers an opportunity to augment experimental data In this work, experiments were conducted on packs of three Li-ion pouch cells with different heating rates and states of charge (SOC) to assess the propagation behavior of a module undergoing thermal runaway. The variable heating rates represent slow or fast heating that a module may experience in a system. As the SOC decreases, propagation slows down and eventually becomes mitigated. It was found that the SOC boundary between propagation and mitigation was higher at a heating rate of 50 °C/min than at 10 °C/min for these cells. However, due to increased pre-heating at the lower heating rate, the propagation speed increased. Simulations were conducted with a new intra-particle diffusion-limited reaction model for a range of anode particle sizes. Propagation speeds and onset times were generally well predicted, and the variability in the propagation/mitigation boundary highlighted the need for greater uncertainty quantification of the predictions.

This report documents the generation of a mechanism to predict the inclusion of carbon soot particles in a high explosive flow. The mechanism includes gasification and oxidation reactions, formation, sublimation, radiation, and agglomeration. Each part of the mechanism is derived from properties in the literature. The influence of each part of the mechanism is explored using simple, example simulations consisting of a 12 mm diameter 2,4,6-Trinitrotoluene charge detonated in ambient air. The mechanism has not been quantitatively compared to experiments. Additional efforts will be required to tune and validate it, which will require continued advancements in experimental diagnostics and simulation techniques.

This report documents the generation of a skeletal chemical reaction mechanism for use with hemispherical pentaerythritol tetranitrate charges. Skeletal mechanisms can substantially reduce computation time while maintaining accuracy. The methodology within uses faster running sample simulations to build a representative thermodynamic state space. These thermodynamic states are used with a constant-volume reactor analysis and a reaction flow analysis to remove unimportant species and reactions from a full chemical reaction mechanism. For the given test case, this results in a 6x speedup in computation time for directly comparable simulations in 2D axisymmetric simulations. We see a 30x speedup in simulations in 3D Cartesian coordainates when compared to a prior full kinetics simulation. There is strong agreement between temperature and species mass fraction profiles between the full and skeletal chemical reaction mechanisms. These methodologies can be applied to any explosive, given the availability of sample simulations.

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A numerical simulation study was performed to examine the post-detonation reaction processes produced by the detonation of a 12 mm diameter hemispherical pentaerythritol tetranitrate (PETN) explosive charge. The simulations used a finite rate detailed chemical reaction model consisting of 59 species and 368 reactions to capture post-detonation reaction processes including air dissociation from Mach 19+ shock waves that initially break out of the PETN charge, reactions within the detonation products during expansion, and afterburning when the detonation products mix with the shock heated air. The multi-species and thermodynamically complete Becker-Kistiakowsky-Wilson real-gas equation of state is used for the gaseous phase to allow for the mixing of reactive species. A recent simplified reactive burn model is used to propagate the detonation through the charge and allow for detailed post-detonation reaction processes. The computed blast, shock structures, and mole fractions of species within the detonation products agree well with experimental measurements. A comparison of the simulation results to equilibrium calculations indicates that the assumption of a local equilibrium is fairly accurate until the detonation products rapidly cool to temperatures in the range of 1500-1900 K by expansion waves. Below this range, the computed results show mole fractions that are nearly chemically frozen within the detonation products for a significant portion of expansion. These results are consistent with the freeze out approximation used in the blast modeling community.

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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.

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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, nonsooting flames.

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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.

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Propagating thermal runaway events are a significant threat to utility-scale storage installations. A propagating thermal runaway event is a cascading series of failures in which energy released from a failed cell triggers subsequent failures in nearby cells. Without intervention, propagation can turn an otherwise manageable single cell failure into a full system conflagration. This study presents a method of mitigating the severity of propagating thermal runaway events in utility-scale storage systems by leveraging the capabilities of a module-interfaced power conversion architecture. The method involves strategic depletion of storage modules to delay or arrest propagation, reducing the total thermal energy released in the failure event. The feasibility of the method is assessed through simulations of propagating thermal runaway events in a 160 kW/80 kWh energy storage system.

Propagating thermal runaway events are a significant threat to utility-scale storage installations. A propagating thermal runaway event is a cascading series of failures in which energy released from a failed cell triggers subsequent failures in nearby cells. Without intervention, propagation can turn an otherwise manageable single cell failure into a full system conflagration. This study presents a method of mitigating the severity of propagating thermal runaway events in utility-scale storage systems by leveraging the capabilities of a module-interfaced power conversion architecture. The method involves strategic depletion of storage modules to delay or arrest propagation, reducing the total thermal energy released in the failure event. The feasibility of the method is assessed through simulations of propagating thermal runaway events in a 160 kW/80 kWh energy storage system.

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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.

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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.

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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.

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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.

Thermal runaway of lithium-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. This work addresses the prediction of cell-to-cell failure propagation and the propagation limits in lithium-ion cell stacks to better understand and identify safe designs. A thermal-runaway model is presented based on recent developments in thermochemical source terms. It is noted that propagating failure is characterized by temperatures above which calorimetry data is available. Results show 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 is 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 show 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.

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Battery based energy storage systems are becoming a critical part of a modernized, resilient power system. However, batteries have a unique combination of hazards that can make design and engineering of battery systems difficult. This report presents a systematic hazard analysis of a hypothetical, grid scale lithium-ion battery powerplant to produce sociotechnical "design objectives" for system safety. We applied system's theoretic process analysis (STPA) for the hazard analysis which is broken into four steps: purpose definition, modeling the safety control structure, identifying unsafe control actions, and identifying loss scenarios. The purpose of the analysis was defined as to prevent event outcomes that can result in loss of battery assets due to fires and explosions, loss of health or life due to battery fires and explosions, and loss of energy storage services due to non- operational battery assets. The STPA analysis resulted in identification of six loss scenarios, and their constituent unsafe control actions, which were used to define a series of design objectives that can be applied to reduce the likelihood and severity of thermal events in battery systems. These design objectives, in all or any subset, can be utilized by utilities and other industry stakeholders as "design requirements" in their storage request for proposals (RFPs) and for evaluation of proposals. Further, these design objectives can help to protect firefighters and bring a system back to full functionality after a thermal event. We also comment on the hazards of flow battery technologies.

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.

The prevalence of flammable carbon-based composite airframe materials and their use in high-temperature nuclear weapon re-entry systems requires analysts to address the abnormal thermal environment hazards associated with composite material fires. These fires tend to burn very differently than conventional fuel fires, usually burning less intensely, but much longer. This could lead to challenges in understanding margins in classic safety themes. The technical challenges in modeling the phenomena associated with these new types of fires are considerable, but new models have been developed. Their predictions have been compared with well-documented measurements of a vertical porous burner fire, known as a "wall fire" (a "wall-fire" validation simulation is reflected in the figures below). These measurements were conducted at FMGlobal, a mutual insurance company with a strong fire risk management program, as part of an ongoing collaboration between Sandia and FMGlobal. To date, the "wall-fire" scenario has been set up and initial model assessments with grid refinement studies have been conducted focusing on mesh resolutions suitable for full weapon system simulations. This work will continue with further verification and validation tasks assessing the predictions of the new model. Future work will address specific aspects of the wall models that are lacking in their predictive ability.

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.

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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.

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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.

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Progress towards next-generation internal combustion engine technologies is dramatically hindered by the complexity of both simulating and measuring key processes, such as thermal stratification and soot formation, in an operating prototype. In general, spectroscopic methods for in-operando probing become limitingly complex at the high pressures and temperature encountered in such systems, and numerical methods for simulating device performance become computationally expensive due to the turbulent flow field, detailed chemistry, and range of important length-scales involved. This report presents parallel experimental and theoretical advances to conquer these limitations. We report the development of high pressure and high temperature ultrafast coherent anti-Stokes Raman spectroscopy measurements, up to a pressure and temperature regime relevant to engine conditions. This report also presents theoretical results using a stochastic one-dimensional turbulence (ODT) model providing insight into the local thermochemical state and its consequences by resolving the full range of reaction-diffusion scales in a stochastic model.

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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.

The surface area dependence of the decomposition reaction between lithiated graphites and electrolytes for temperatures above 100◦C up to ~200◦C is explored through comparison of model predictions to published calorimetry data. The initial rate of the reaction is found to scale super-linearly with the particle surface area. Initial reaction rates are suggested to scale with edge area, which has also been measured to scale super-linearly with particle area. As in previous modeling studies, this work assumes that electron tunneling through the solid electrolyte interphase (SEI) limits the rate of the reaction between lithium and electrolyte. Comparison of model predictions to calorimetry data indicates that the development of the tunneling barrier is not linear with BET surface area; rather, the tunneling barrier correlates best with the square root of specific surface area. This result suggests that tunneling though the SEI may be controlled by defects with linear characteristics. The effect of activation energy on the tunneling-limited reaction is also investigated. The modified area dependence results in a model that predicts with reasonable accuracy the range of observed heat-release rates in the important temperature range from 100◦C to 200◦C where transition to thermal runaway typically occurs at the cell level.

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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.

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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.

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We present a detailed set of measurements from a piloted, sooting, turbulent C2H4-fueled jet 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. A new dual-detection channel CARS instrument provides the enhanced dynamic range required in this highly intermittent and turbulent environment. LII measurements are made across a wide field of view requiring us to account for spatial variation in the soot-volume-fraction response of the instrument. Single-laser-shot results are used to illustrate the mean and rms statistics, as well as probability densities of all three measured quantities. LII data from the soot-growth region of the jet 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, oxygen and soot fluctuations within the soot oxidation region higher in the flame.

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.

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.

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.

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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 (>7.5 mM). Zeta potential measurements suggest that brucite precipitation caused flocculation by charge neutralization. When calcium concentration was 12.5 mM, flocculation was also observed at a pH of 10. Furthermore, zeta potential remained negative up to pH 11.5, suggesting that precipitated calcite caused flocculation by a sweeping coagulation mechanism.

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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.

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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.

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Particles in non-isothermal turbulent flow are subject to a stochastic environment that 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 scales (the ‘triplet map’) at a rate that is a function of the fully resolved one-dimensional velocity field. Stochastic triplet maps also drive Lagrangian particle dispersion with finite Stokes numbers including inertial and eddy trajectory-crossing effects 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 provides an accurate description of particle dispersion. A ‘continuous’ particle displacement model translates triplet maps into a continuous velocity field to which particles respond. Particles can alter the turbulence, and modifications to the stochastic rate expression 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 available. 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 influence of the mean flow fields on particles of varying properties alters 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 and 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 autocorrelations, 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 intermittent having peaked distributions with long tails. The logarithm of the absolute value of these time scales exhibits a distribution closer to normal.

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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.

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