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  1. Chemics-Reactors: A Preliminary Python Program for Implementing Network Models of Multiphase Reactors

    We discuss the design and implementation of a preliminary software package written in Python 3 that is intended to represent complex multiphase reactors as networks of ideal continuous stirred tank reactors. This software also implements statistical design of experiments, uncertainty quantification, and global sensitivity analysis. These advanced features can provide important qualitative and quantitative insights into the effect of operating conditions and model parameters on predicted reactor performance. We demonstrate the utility of the program by modeling the vapor phase catalytic upgrading of bio-oil in a bubbling fluidized bed reactor.
  2. Low-Order Modeling of Internal Heat Transfer in Biomass Particle Pyrolysis

    We present a computationally efficient, one-dimensional simulation methodology for biomass particle heating under conditions typical of fast pyrolysis. Our methodology is based on identifying the rate limiting geometric and structural factors for conductive heat transport in biomass particle models with realistic morphology to develop low-order approximations that behave appropriately. Comparisons of transient temperature trends predicted by our one-dimensional method with three-dimensional simulations of woody biomass particles reveal good agreement, if the appropriate equivalent spherical diameter and bulk thermal properties are used. We conclude that, for particle sizes and heating regimes typical of fast pyrolysis, it is possible to simulate biomassmore » particle heating with reasonable accuracy and minimal computational overhead, even when variable size, aspherical shape, anisotropic conductivity, and complex, species-specific internal pore geometry are incorporated.« less
  3. Simulating Biomass Fast Pyrolysis at the Single Particle Scale

    Simulating fast pyrolysis at the scale of single particles allows for the investigation of the impacts of feedstock-specific parameters such as particle size, shape, and species of origin. For this reason particle-scale modeling has emerged as an important tool for understanding how variations in feedstock properties affect the outcomes of pyrolysis processes. The origins of feedstock properties are largely dictated by the composition and hierarchical structure of biomass, from the microstructural porosity to the external morphology of milled particles. These properties may be accounted for in simulations of fast pyrolysis by several different computational approaches depending on the level ofmore » structural and chemical complexity included in the model. The predictive utility of particle-scale simulations of fast pyrolysis can still be enhanced substantially by advancements in several areas. Most notably, considerable progress would be facilitated by the development of pyrolysis kinetic schemes that are decoupled from transport phenomena, predict product evolution from whole-biomass with increased chemical speciation, and are still tractable with present-day computational resources.« less
  4. Low-order modeling of internal heat transfer in biomass particle pyrolysis

    We present a computationally efficient, one-dimensional simulation methodology for biomass particle heating under conditions typical of fast pyrolysis. Our methodology is based on identifying the rate limiting geometric and structural factors for conductive heat transport in biomass particle models with realistic morphology to develop low-order approximations that behave appropriately. Comparisons of transient temperature trends predicted by our one-dimensional method with three-dimensional simulations of woody biomass particles reveal good agreement, if the appropriate equivalent spherical diameter and bulk thermal properties are used. Here, we conclude that, for particle sizes and heating regimes typical of fast pyrolysis, it is possible to simulatemore » biomass particle heating with reasonable accuracy and minimal computational overhead, even when variable size, aspherical shape, anisotropic conductivity, and complex, species-specific internal pore geometry are incorporated.« less
  5. Application of Wavelet-Based Methods for Accelerating Multi-Time-Scale Simulation of Bistable Heterogeneous Catalysis

    Here, we report results from a numerical study of multi-time-scale bistable dynamics for CO oxidation on a catalytic surface in a flowing, well-mixed gas stream. The problem is posed in terms of surface and gas-phase submodels that dynamically interact in the presence of stochastic perturbations, reflecting the impact of molecular-scale fluctuations on the surface and turbulence in the gas. Wavelet-based methods are used to encode and characterize the temporal dynamics produced by each submodel and detect the onset of sudden state shifts (bifurcations) caused by nonlinear kinetics. When impending state shifts are detected, a more accurate but computationally expensive integrationmore » scheme can be used. This appears to make it possible, at least in some cases, to decrease the net computational burden associated with simulating multi-time-scale, nonlinear reacting systems by limiting the amount of time in which the more expensive integration schemes are required. Critical to achieving this is being able to detect unstable temporal transitions such as the bistable shifts in the example problem considered here. Lastly, our results indicate that a unique wavelet-based algorithm based on the Lipschitz exponent is capable of making such detections, even under noisy conditions, and may find applications in critical transition detection problems beyond catalysis.« less
  6. Nanostructure and burning mode of light-duty diesel particulate with conventional diesel, biodiesel, and intermediate blends

    The nanostructure of diesel particulates has been shown to impact its oxidation rate and burnout trajectory. Additionally, this nanostructure can evolve during the oxidation process, furthering its influence on the burnout process. For this paper, exhaust particulates were generated on a light-duty diesel engine with conventional diesel fuel, biodiesel, and intermediate blends of the two at a single load-speed point. Despite the singular engine platform and operating point, the different fuels created particulates with varied nanostructure, thereby greatly expanding the window for observing nanostructure evolution and oxidation. The physical and chemical properties of the particulates in the nascent state andmore » at partial oxidation states were measured in a laboratory reactor and by high-resolution transmission electron microscopy as a function of the degree of oxidation in O 2. X-ray photoacoustic spectroscopy analysis, thermal desorption, and solvent extraction of the nascent particulate samples reveal a significant organic content in the biodiesel-derived particulates, likely accounting for differences in the nanostructure. This study reports the nanoscale structural changes in the particulate with biofuel blend level and during O 2 oxidation as observed by high-resolution transmission electron microscopy and quantitated by fringe analysis and Brunnauer–Emmet–Teller total surface area measurements. It was observed that initial fuel-related differences in the lamella lengths, spacing, and curvature disappear when the particulate reaches approximately 50% burnout. Specifically, the initial ordered, fullerenic, and amorphous nanostructures converge during the oxidation process and the surface areas of these particulates appear to grow through these complex changes in internal particle structure. The specific surface area, measured at several points along the burnout trajectory, did not match the shrinking core projection and in contrast suggested that internal porosity was increasing. Thus, the appropriate burnout model for these particulates is significantly different from the standard shrinking core assumption, which does not account for any internal structure. Finally, an alternative burnout model is supported by high-resolution transmission electron microscopy image analysis.« less
    Cited by 1
  7. COMPARISON OF PARALLEL AND SERIES HYBRID POWERTRAINS FOR TRANSIT BUS APPLICATION

    The fuel economy and emissions of both conventional and hybrid buses equipped with emissions aftertreatment were evaluated via computational simulation for six representative city bus drive cycles. Both series and parallel configurations for the hybrid case were studied. The simulation results indicate that series hybrid buses have the greatest overall advantage in fuel economy. The series and parallel hybrid buses were predicted to produce similar CO and HC tailpipe emissions but were also predicted to have reduced NOx tailpipe emissions compared to the conventional bus in higher speed cycles. For the New York bus cycle (NYBC), which has the lowestmore » average speed among the cycles evaluated, the series bus tailpipe emissions were somewhat higher than they were for the conventional bus, while the parallel hybrid bus had significantly lower tailpipe emissions. All three bus powertrains were found to require periodic active DPF regeneration to maintain PM control. Plug-in operation of series hybrid buses appears to offer significant fuel economy benefits and is easily employed due to the relatively large battery capacity that is typical of the series hybrid configuration.« less
  8. Simulations of the Fuel Economy and Emissions of Hybrid Transit Buses over Planned Local Routes

    We present simulated fuel economy and emissions city transit buses powered by conventional diesel engines and diesel-hybrid electric powertrains of varying size. Six representative city drive cycles were included in the study. In addition, we included previously published aftertreatment device models for control of CO, HC, NOx, and particulate matter (PM) emissions. Our results reveal that bus hybridization can significantly enhance fuel economy by reducing engine idling time, reducing demands for accessory loads, exploiting regenerative braking, and shifting engine operation to speeds and loads with higher fuel efficiency. Increased hybridization also tends to monotonically reduce engine-out emissions, but trends inmore » the tailpipe (post-aftertreatment) emissions involve more complex interactions that significantly depend on motor size and drive cycle details.« less
  9. Coupling DAEM and CFD for simulating biomass fast pyrolysis in fluidized beds

    We report results from computational simulations of an experimental, lab-scale bubbling bed biomass pyrolysis reactor that include a distributed activation energy model (DAEM) for the kinetics. In this study, we utilized multiphase computational fluid dynamics (CFD) to account for the turbulent hydrodynamics, and this was combined with the DAEM kinetics in a multi-component, multi-step reaction network. Our results indicate that it is possible to numerically integrate the coupled CFD–DAEM system without significantly increasing computational overhead. It is also clear, however, that reactor operating conditions, reaction kinetics, and multiphase flow dynamics all have major impacts on the pyrolysis products exiting themore » reactor. We find that, with the same pre-exponential factors and mean activation energies, inclusion of distributed activation energies in the kinetics can shift the predicted average value of the exit vapor-phase tar flux and its statistical distribution, compared to single-valued activation-energy kinetics. Perhaps the most interesting observed trend is that increasing the diversity of the DAEM activation energies appears to increase the mean tar yield, all else being equal. As a result, these findings imply that accurate resolution of the reaction activation energy distributions will be important for optimizing biomass pyrolysis processes.« less
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"Daw, C. Stuart"

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