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At least 271 records · Page 15

Bimolecular Peroxy Radical (RO 2 ) Reactions and Their Relevance in Radical Initiated Oxidation of Hydrocarbons

The kinetics of peroxy radical (RO 2 ) reactions have been of long-standing interest in atmospheric and combustion chemistry. Nevertheless, the lack of kinetic studies at higher temperatures for their reactions with other radicals such as OH has precluded the inclusion of this class of reactions in detailed kinetics models developed for combustion applications. In this work, guided by the limited room temperature experimental studies on selected alkyl-peroxy radicals and literature theoretical kinetics on the prototypical CH 3 O 2 + OH system, we have performed parametric studies on the effect of uncertainties in the rate coefficients and branching ratios to potential product channels for RO 2 + OH reactions at higher temperatures. Literature kinetics models were used to simulate autoignition delays, laminar flame speeds, and speciation profiles in flow and stirred reactors for a variety of common combustion-relevant fuels. Inclusion of RO 2 + OH reactions was found to retard autoignition in fuel-lean (φ = 0.5) mixtures of ethane and dimethyl ether in air. The observed effects were noticeably more pronounced in ozone-enriched combustion of ethane and dimethyl ether. The simulations also examined the influence of ozone doping levels, pressures, and equivalence ratios for both ethane and dimethyl ether oxidation. Sensitivity and flux analyses revealed that the RO 2 + OH reaction is a significant sink of RO 2 radicals at the early stage of autoignition, affecting fuel oxidation through RO 2 ↔ QOOH, RO 2 ↔ alkene + HO 2 , or RO 2 + HO 2 ↔ ROOH + O 2 . Additionally, the kinetic stability of the trioxide formed from RO 2 + OH reactions was investigated using master equation analyses. Last, we discuss other bimolecular reactions that are missing in literature kinetics models but are relevant to hydrocarbon oxidation initiated by external radical sources (plasma-enhanced, ozone-enriched combustion, etc.). In conclusion, the present simulations provide a strong motivation for better characterizing the bimolecular kinetics of peroxy radicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A phenomenological rate of injection model for predicting fuel injection with application to mixture formation in light-duty diesel engines

Fuel injection rate laws are one of the most important pieces of information needed when modeling engine combustion with computational fluid dynamics. In this study, a simple phenomenological model of a common-rail injector was developed and calibrated for the Bosch CRI2.2 platform. The model requires three tunable parameter fits, making it relatively easy to calibrate and suitable for injector modeling when high-fidelity information about the internal injector’s geometry and electrical circuit details are not available. Each injection pulse is modeled as a sequence of up to four stages: an injection needle mechanical opening transient, a full-lift viscous flow inertial transient, a Bernoulli steady-state stage, and a needle descent transient. Parameters for each stage are obtained as polynomial fits from measured injection rate properties. The model enforces total injected mass, and the intermediate stages are only introduced if the injection pulse duration is long enough. Experimental rates of injection from two separate campaigns on the same injector were used to calibrate the model. The model was first validated against measured injection rate laws featuring pilot injections, short partially premixed combustion pulses, and conventional diesel combustion injection strategies. Then, it was employed as an input to engine computational fluid dynamics simulations, which were run to simulate experiments of mixture formation in an optically accessible light-duty diesel engine. It was found that, though simple, this model is capable of predicting both pilot and main injection pulse mass flow rates well: the simulations yielded accurate predictions of in-cylinder equivalence ratio distributions from injection strategies for both partially premixed combustion and pilot injections. Also, once calibrated, the model produced appropriate results for a wide range of injected mass and rail pressure values. Finally, it was observed that usage of such a relatively simple model can be a good choice when high-fidelity injection rate input and highly detailed information of the injector’s geometry and operation are not available, particularly as noticeable discrepancies can be present also among different experimental campaigns on similar hardware.

42 ENGINEERING↗

Effects of molar expansion ratio of fuels on engine efficiency

Fuel properties have a strong impact on the efficiency of internal combustion engines. Contrary to other physical and thermochemical fuel properties, the molar expansion ratio is normally ignored. Molar expansion ratio is the ratio of number of moles of the products to the reactants. In this work, the impact of the fuel’s molar expansion ratio on engine efficiency is investigated. Findings are based on simulations of a spark ignition engine using different fuels (standard fuels and user-defined fuels) and different dilution ratios. Simulations without heat transfer and friction were performed first. The combustion then takes place at top dead center with a very short combustion duration to approach the ideal Otto cycle. The heat transfer and friction were then added step by step. From this analysis, it could be concluded that the heat loss and friction work decrease as molar expansion ratio increases. The gross indicated and brake thermal efficiencies thus increase. User-defined fuels with different molar expansion ratio, but the same physical and thermochemical properties were then employed. The simulated results showed that the brake thermal efficiency increases by around 1.15% with an increase in molar expansion ratio of 0.02 compared to a fuel with a molar expansion ratio of unity. Lastly, the simulation was also done with air and exhaust gas recirculation dilution.

42 ENGINEERING↗

A benchmark dataset for Hydrogen Combustion

The generation of reference data for deep learning models is challenging for reactive systems, and more so for combustion reactions due to the extreme conditions that create radical species and alternative spin states during the combustion process. Here, we extend intrinsic reaction coordinate (IRC) calculations with ab initio MD simulations and normal mode displacement calculations to more extensively cover the potential energy surface for 19 reaction channels for hydrogen combustion. A total of ~290,000 potential energies and ~1,270,000 nuclear force vectors are evaluated with a high quality range-separated hybrid density functional, ωB97X-V, to construct the reference data set, including transition state ensembles, for the deep learning models to study hydrogen combustion reaction.

08 HYDROGEN↗

Ducted fuel injection with Low-Net-Carbon fuels as a solution for meeting future emissions regulations

Several studies have proven how ducted fuel injection (DFI) reduces soot emissions for compression-ignition engines. Nevertheless, no comprehensive study has investigated how DFI performs over a load range in combination with low-net-carbon fuels. In this study, optical-engine experiments were performed with four different fuels—conventional diesel and three low-net-carbon fuels—at low and moderate load, to measure emissions levels and performance. The 1.7-liter single-cylinder optical engine was equipped with a high-speed camera to capture natural luminosity images of the combustion event. Conventional diesel and DFI combustion were investigated at four different dilution levels (to simulate exhaust-gas recirculation effects), from 14 to 21 mol% oxygen in the intake. At a given dilution level, with commercial diesel fuel, DFI reduced soot by 82% at medium load, and 75% at low load without increasing NO x . The results further show how DFI with dilution reduces soot and NO x without compromising engine performance or other emission types, especially when combined with low-net-carbon fuels. DFI with the oxygenated low-net-carbon blend HEA67 simultaneously reduced soot and NO x by as much as 93 % and 82 %, respectively, relative to conventional diesel combustion with commercial diesel fuel. These soot and NO x reductions occurred while lifecycle CO 2 was reduced by at least 70 % when using low-net-carbon fuels instead of conventional diesel. All emissions changes were compared with future emissions regulations for different vehicle sectors to investigate how DFI can be used to facilitate achievement of the regulations. Finally, the results show how the DFI cases fall below several future emissions regulation levels, rendering less need for aftertreatment systems and giving a possible lower cost of ownership.

33 ADVANCED PROPULSION SYSTEMS↗

Analysis of direct and indirect noise in a next-generation aviation gas turbine combustor

A large-eddy simulation (LES) of a next-generation combustor is performed to examine effects of this combustor concepts on direct and indirect combustion noise characteristics. Direct noise is computed considering the unsteady heat release predictions while entropy fluctuations in the downstream part of the combustor are used to estimate indirect noise through the transfer function of the outlet nozzle. A low-order acoustic reconstruction technique, which utilizes the Green’s function of the configuration, is developed to compute the acoustics inside the combustor. Comparisons to experimental results are reported, showing the reasonable accuracy of the LES and combustion noise computations. The direct noise spectrum peaks at frequencies around 3 kHz because of the fast timescales associated with the chemical reactions inside the combustor. In addition, the indirect noise is dominant at low frequencies, i.e., less than 400 Hz, because of the characteristics of the entropy spectrum at the outlet nozzle. Further, compared to a conventional rich-quench-lean (RQL) combustor configuration, significant differences in the acoustics are observed, and are explained by two specific technological novelties. Firstly, the direct noise spectrum peaks at significantly higher frequencies due to the combustor’s compactness. Secondly, the entropy inhomogeneties downstream of the combustion region are an order of magnitude smaller in amplitude due to the lack of dilution with cold air. This leads to a significant reduction in the indirect noise amplitude at low frequencies, where it is the dominant source of noise. These results suggest opportunities for advanced combustion technologies to achieve substantial reductions in combustion-related noise.

42 ENGINEERING↗

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. Here, in order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

42 ENGINEERING↗

Application of a Comprehensive Lagrangian–Eulerian Spark-Ignition Model to Different Operating Conditions

Increasing engine efficiency is essential to reducing emissions, which is a priority for automakers. Unconventional modes such as boosted and highly dilute operation have the potential to increase engine efficiency but suffer from stability concerns and cyclic variability. To aid engineers in designing ignition systems that reduce cyclic variability in such engine operation modes, reliable and accurate spark-ignition models are necessary. Here, in this article, a Lagrangian–Eulerian spark-ignition (LESI) model is used to simulate electrical discharge, spark channel elongation, and ignition in inert or reacting crossflow within a combustion vessel, at different pressures, flow speeds, and dilution rates. First the model formulation is briefly revisited. Then, the experimental and simulations setups are presented. The results showcase the model’s ability to predict the secondary circuit voltage, current, and power signals, in addition to the spark channel elongation, for the inert cases, or flame front growth, for the reacting cases. The results also compare simulation spark channel and flame growth plots to experimental Schlieren images at different instants in time. This work serves to highlight LESI’s ability to predict the characteristics of discharge and ignition across a variety of operating conditions.

42 ENGINEERING↗

Computational fluid dynamics modeling and analysis of silica nanoparticle synthesis in a flame spray pyrolysis reactor

Flame Spray Pyrolysis (FSP) is a method for large-scale production of nanoparticles and nanoscale powders employed in a wide range of industrial applications. Particle size and morphology are complex functions of the physicochemical phenomena occurring in the FSP reactor. An extensive study of FSP-related phenomena can be utilized to develop effective strategies for achieving desired particle size/morphology and scaling up the overall yield of an FSP system. In this work, a computational fluid dynamics (CFD) model of an FSP reactor is developed to simulate the coupling of key phenomena involved in the particle synthesis process: liquid spray breakup and evaporation, mixing, combustion, and particle formation/growth of silica nanoparticles. Herein, the particle sizes and their distributions from the CFD simulations are validated against experimental data. Subsequently, the simulations are utilized to investigate the impact of process parameters on the resultant flame dynamics and particle growth. Firstly, the CFD results show that the particle sizes are strongly correlated with the precursor concentration in the solvent. At lower precursor concentrations, the spread of the distribution is relatively insensitive to the value of the concentration. At higher concentrations, the spread is higher as the collision probability between particles is higher. Secondly, increasing the pilot flow rate increases the length of the pilot flames impacting the local ignition location of the spray flame. Lastly, it is shown that the dispersion gas flow rate strongly influences the spray flame shape. This shape can be used for control of particle growth as it helps determine the regions of high temperature and the residence time of the particles in the high temperature region enabling the design and process optimization of the FSP reactor.

42 ENGINEERING↗

Numerical and boundary condition effects on the prediction of detonation engine behavior using detailed numerical simulations

High-fidelity numerical simulations of an experimental rotating detonation engine with discrete fuel/air injection were conducted. A series of configurations with different feed-plenum pressures but with constant equivalence ratio were studied. Detailed chemical kinetics for the hydrogen/air system is used. A resolution study for the full rotating detonation engine (RDE) system simulation is also conducted. Two kinds of boundary conditions, a total pressure boundary and a constant mass flow rate boundary, are used to assess the effects of the inlet boundary. As mass flow rate is increased, the total pressure boundary causes more error in the axial pressure distribution while the constant mass flow rate gives a better solution for all cases ran. The simulations confirm experimental findings, and reproduce qualitative as well as some of the quantitative trends. These results demonstrate that a) fuel-air mixing is highly non-uniform within the detonation chamber, leading to variations in local equivalence ratio, b) the fuel and oxidizer injectors experience significant backflow as the detonation wave passes over, but recover at different rates which further augments the inefficiencies in mixing, and c) parasitic combustion in the mixing region makes the detonation wave weak by extending the reaction zone across the wave.

33 ADVANCED PROPULSION SYSTEMS↗

A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation

As the use of combustion engine vehicles plays a deciding role in global warming, we can observe a trend to replace them with electric vehicles (EV) driven by new environmentally conscious policies and increasing technological capabilities. With improvements in driving range and reduction in prices come new challenges that may hamper the progress towards complete battery driven transportation. A major challenge for the increasing EV adoption is the planning of extensions to existing infrastructure or the inclusion of new infrastructure components in the planning process. This demands increasingly complex planning tools that can simulate the interplay between different stakeholders in modern transportation scenarios such as EVs, charging stations, energy providers, and general transportation participants. Simulation platforms for agent-based modeling in transportation have been developed as effective interactive tools that allow planners to explore different trade-offs across different scenarios with the ability to simulate the impact of policy or infrastructure decisions on the different stakeholders in the simulation. This article surveys several of the major simulation platforms that include modern EV-based forms of transportation and allow the simulation of relevant infrastructure components alongside the well established transportation simulations. These tools allow researchers to analyze expected traffic flow, identify possible charging station locations based on area demand, predict electrical grid demand, and more. Here this survey intends to make it easier for researchers to identify and apply a simulation platform in the context of supporting the increasing electrification of the transportation sector, enabling more efficient simulation and planning capabilities in this domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Experimental Combustion and Flame Characterization of a Chemical Looping-Based Oxidative Dehydrogenation Byproduct Fuel Mixture Containing High CO2 Dilution

Abstract This study investigates the combustion performance of a CO2-rich fuel mixture containing ethane and methane as active species using a constant volume combustion chamber. This fuel is obtained as a byproduct of a chemical looping-based oxidative dehydrogenation (Cl-ODH) process ethylene production. The byproduct gas mixture has 40.79% CO2, 39.49% ethane, and 4.88% methane by weight with other minor compounds. Using this fuel for energy extraction would improve the process efficiency of the ethane to ethylene conversion. After initial combustion modeling, the gas fuel mixture was reduced to just the major species: CO2, ethane, and methane. The mixture was then tested for flammability limits and combustion performance under spark-ignition conditions. Effects of ambient conditions like temperatures between 300 and 400 K with initial pressures from 1 to 10 bar were tested. The effects of stoichiometry were tested to understand flame velocities and heat release. The fuel mixture showed an overall reduced flame velocity compared to gasoline. Instability in combustion was believed to be caused by the dissociation of ethane under elevated conditions. At higher pressures, the flame produces lower cumulative heat release. Simulations were also performed using a model tuned to replicate the operations of the combustion chamber used in the experiments. Heat release and unburnt fuel mass data were calculated to identify the discrepancies in the combustion completeness at elevated pressures. The effects of CO2 quenching the flame coupled with the increased dissociation of the fuel species can lead to up to more than 75% of the fuel mixture being unburnt. Data from this study were used to modify a small-scale spark-ignition engine to use this fuel and produce usable energy.

Energy & Fuels↗

Considerations for the temperature stratification in a pre-burn constant-volume combustion chamber

In recent years, the Engine Combustion Network (ECN) has developed as a worldwide reference for understanding and describing engine combustion processes, successfully bringing together experimental and numerical efforts. Since experiments and numerical simulations both target the same boundary conditions, an accurate characterization of the stratified environment that is inevitably present in experimental facilities is required. The difference between the core-, and pressure-derived bulk-temperature of pre-burn combustion vessels has been addressed in various previous publications. Additionally, thermocouple measurements have provided initial data on the boundary layer close to the injector nozzle, showing a transition to reduced ambient temperatures. The conditions at the start of fuel injection influence physicochemical properties of a fuel spray, including near nozzle mixing, heat release computations, and combustion parameters. To address the temperature stratification in more detail, thermocouple measurements at larger distances from the spray axis have been conducted. Both the temperature field prior to the pre-combustion event that preconditions the high-temperature, high-pressure ambient, as well as the stratification at the moment of fuel injection were studied. To reveal the cold boundary layer near the injector with a better spatial resolution, Rayleigh scattering experiments and thermocouple measurements at various distances close to the nozzle have been carried out. The impact of the boundary layers and temperature stratification are illustrated and quantified using numerical simulations at Spray A conditions. Next to a reference simulation with a uniform temperature field, six different stratified temperature distributions have been generated. These distributions were based on the mean experimental temperature superimposed by a randomized variance, again derived from the experiments. The results showed that an asymmetric flame structure arises in the computed results when the temperature stratification input is used. In these predictions, first-stage ignition is advanced by 24 $\mu$s , while second-stage ignition is delayed by 11 $\mu$s. At the same time a lift-off length difference between the top and the bottom of up to 1.1 mm is observed. Furthermore, the lift-off length is less stable over time. Given the shown dependency, the temperature data is made available along with the vessel geometry data as a recommended basis for future numerical simulations.

42 ENGINEERING↗

Multidimensional Numerical Modeling of Combustion Dynamics in a Non-Premixed Rotating Detonation Engine With Adaptive Mesh Refinement

In the present work, a novel computational fluid dynamics (CFD) methodology was developed to simulate full-scale non-premixed rotating detonation engines (RDEs). A unique feature of the modeling approach was the incorporation of adaptive mesh refinement (AMR) to achieve a good trade-off between model accuracy and computational expense. Here, unsteady Reynolds-averaged Navier–Stokes (RANS) simulations were performed for an Air Force Research Laboratory (AFRL) non-premixed RDE configuration with hydrogen as fuel and air as the oxidizer. The finite-rate chemistry model, along with a ten-species detailed kinetic mechanism, was employed to describe the H 2 -Air combustion chemistry. Three distinct operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel/air mass flowrates. For all conditions, the capability of the model to capture essential detonation wave dynamics was assessed. An exhaustive verification and validation study was performed against experimental data in terms of a number of waves, wave frequency, wave height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model was demonstrated to accurately predict the sensitivity of these wave characteristics to the operating conditions, both qualitatively and quantitatively. A comprehensive heat release analysis was also conducted to quantify detonative versus deflagrative burning for the three simulated cases. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

42 ENGINEERING↗

Vapor–liquid equilibrium estimation of n-alkane/nitrogen mixtures using neural networks

Understanding fluid phase behavior, like VLE, in high P&T conditions is crucial for developing high-fidelity simulations of chemically reacting flows in liquid-fueled combustion systems and also forms an integral part of the design-modeling of the control processes in chemical industries. Two data-driven models have been proposed here in this study, each of which was competent in estimating VLE for the Type III binary systems of C 10 /N 2 and C 12 /N 2 , at pressures ranging up to 50–60 MPa. Both models showed better performance in predicting equilibrium pressure as compared to VLE modeled using PR-EOS. A modified model has also been proposed, capable of estimating the full phase envelope for the binary systems of C 10 /N 2 and C 12 /N 2 across a wide range of temperatures, and thus exhibit the mixture critical pressure at the concerned temperature. The diverse applicability of the proposed network architecture was further exhibited while estimating the VLE of a ternary system of C 1 /C 10 /N 2 .

97 MATHEMATICS AND COMPUTING↗

High-Accuracy Simulations to Model Pyrometallurgical Processes in a Secondary Lead Reverberatory Furnace

The US manufacturing industry produces about 1.3 million tons of refined lead each year using secondary sources consisting mainly of lead batteries. ORNL is partnering with Gopher resource, the second largest lead recycling company in the United States, and GTI, to develop a high-fidelity CFD model of a directly fired, reverberatory-style, secondary lead furnace. These High Performance Computing (HPC) simulations are aimed to use first principles modeling for combustion and melting processes of the secondary lead feed while accounting for complex interphase interactions between the gas, solid charge (lead) material, slag, and metal phases. Through validation against operating plant data, this effort will enable significant improvements in design, operational parameters, and energy efficiency, thus improving productivity and refractory lifetime of secondary lead melting furnaces. Estimated savings/reduction of, at least, 1 trillion BTU, 1 million ton/year of greenhouse gas emissions, and $\$50$ million/year to the US lead industry can be expected. ORNL resources and expertise in high-performance computing and multicomponent, multiphase flows were utilized to realize this goal while advancing the understanding of the smelting and melting processes occurring within the furnace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermal radiation analysis of a pressurized oxy-coal combustor with discrete ordinate model

Concerns over climate change have led to numerous efforts in developing low-carbon energy technologies. Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Pressure strongly impacts thermal radiation, leading to a substantial difference in heat transfer between POC and conventional atmospheric pressure combustion. A good understanding of thermal radiation in POC is needed to aid new combustor development. The present work is a step in this direction, initiating a systematic analysis of thermal radiation and heat transfer in a pilot-scale POC combustor, which has been developed at Washington University in St. Louis (WUSTL). In a POC process, pulverized coal is burned under elevated pressure and O2-CO2 environment. Few researchers have investigated the thermal radiation of pressurized oxy-combustion. This work adopted the discrete ordinate model to simulate the radiation of a 1-D cylinder with predetermined conditions (temperature, pressure, gas compositions) to predict the influence of radiative properties of flue gas on the radiation in the combustor.

Li, Lei↗

Detonation structure in the presence of mixture stratification using reaction-resolved simulations

Many investigations of detonation-based combustors have identified reactant mixture inhomogeneity as having a leading-order impact on wave dynamics and combustion efficiency. To examine this phenomenon in a simplified context, an array of two- and three-dimensional channel detonation simulations are conducted in the present work. The reactant mixture consists of stratified fuel and air, wherein the randomly distributed equivalence ratio field features a characteristic stratification length scale. Detailed chemical kinetics are implemented in an adaptive mesh refinement solution framework where the region near the shock front is resolved with Ο (100) cells per representative ZND induction length. The results show that in comparison to baseline cases with uniform reactant mixtures, reactant stratification has a marked impact on the detonation structure. Increasing the stratification length scale increases the size and irregularity of the detonation cells, yielding larger variations in wave speed. Triple point collisions in fuel-rich regions lead to local wave speeds above the notional mean CJ speed, but wave passage through inert regions causes the local wave speed and strength to diminish. Further, conditional statistics show that increasing the stratification length scale increases the variance in pressure and temperature in the primary reaction zone, as well as the variance in heat release over a range of mixture conditions. In addition to the reactant mixture, the impact of the boundary condition behind the detonation is also investigated. The results show that an inflow boundary condition acts to over-drive the wave, leading to higher peak pressures, smaller detonation cells, and increased reactant consumption. On the other hand, cases with a wall behind the wave exhibit weaker waves with lower peak pressures and heat release rates, as well as greater variance in conditional quantities. Comparisons between complementary two- and three-dimensional simulations show reasonable qualitative agreement in wave structure, speed, and conditional statistics.

42 ENGINEERING↗