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Multi-Objective Optimization of Fuel Consumption and NOx Emissions using a Stochastic Reactor Model
Abstract
The 0D DI-SRM with tabulated chemistry is successfully applied for a multi-objective optimization of fuel consumption and NO x emissions in a direct injection Diesel engine. The approach highlighted its strength to account for physical and chemical effects in a 0D model framework with a lesser extent of computational costs. The optimization results show that increasing compression ratio has the highest potential for reducing fuel consumption especially at part load conditions. Increasing the EGR rate is most effective in reducing the NO x emissions of all operating points. The average optimization time is 30h on three cores of an Intel i7-7820HQ CPU. Multi-Objective Optimization with 0D DI-SRM The specific fuel consumption (ISFC) and NO x emissions (sNO x) shall be minimized for each operating point by tuning the parameters in Table 2. The constraints are 200bar peak cylinder pressure (PCP) and 1000K turbine inlet temperature (TIT). The optimization results are shown in Figure 3 and Figure 4. The relative change of the given property compared to the base case is depicted in percent. The compression ratio is found to be most effective for improving fuel consumption. Especially part load operating points show the highest potential regarding increased compression ratio. The EGR rate is the most effective parameter to reduce the NO x emissions for all operating points. Full load operating points show only a minor potential for improving ISFC and sNO x since they are limited by PCP and TIT. [1] Matrisciano A., Franken T., Perlman C., Borg A.
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A novel 0-D Probability Density Function (PDF) based approach for the modelling of Diesel combustion using tabulated chemistry is presented. The Direct Injection Stochastic Reactor Model (DI-SRM) by Pasternak et al. has been extended with a progress variable based framework allowing the use of a pre-calculated auto-ignition table. Auto-ignition is tabulated through adiabatic constant pressure reactor calculations. The tabulated chemistry based implementation has been assessed against the previously presented DI-SRM version by Pasternak et al. where chemical reactions are solved online. The chemical mechanism used in this work for both, online chemistry run and table generation, is an extended version of the scheme presented by Nawdial et al. The main fuel species are n-decane, α-methylnaphthalene and methyl-decanoate giving a size of 463 species and 7600 reactions. A single-injection part-load heavy-duty Diesel engine case with 28 % EGR fueled with regular Diesel is investigated with both tabulated and online chemistry. Comparisons between the two approaches are presented by means of overall engine performance and engine-out emission predictions and in equivalence ratio-temperature space. The new implementation delivers reasonably good agreement with the online chemistry one. The methodology presented in this paper allows for the use of detailed chemistry in the DI-SRM with high computational efficiency and thus facilitates the use of the DI-SRM in the engine development process.
Probability density function (PDF) methods offer compelling advantages for modeling chemically reacting turbulent flows. In particular, they provide an elegant and effective resolution to the closure problems that arise from averaging or filtering the highly nonlinear chemical source terms, and terms that correspond to other one-point physical processes (e.g., radiative emission) in the instantaneous governing equations. This review is limited to transported PDF methods, where one models and solves an equation that governs the evolution of the one-point, one-time PDF for a set of variables that determines the local thermochemical and/or hydrodynamic state of a reacting system. Progress over the previous 20–25 years (roughly since Pope's seminal paper [24]) is covered, with emphasis on developments over the past decade. For clarity and concreteness, two current mainstream approaches are adopted as baselines: composition PDF and velocity–composition PDF methods for low-Mach-number reacting ideal-gas mixtures, with standard closure models for key physical processes (e.g., mixing models), and consistent hybrid Lagrangian particle/Eulerian mesh numerical solution algorithms. Alternative formulations, other flow regimes, additional physics, advanced models, and alternative solution algorithms are introduced and discussed with respect to these baselines. Important developments that are discussed include velocity–composition–frequency PDF's, PDF-based methods as subfilter-scale models for large-eddy simulation (filtered density function methods), PDF-based modeling of thermal radiation heat transfer and turbulence–radiation interactions, PDF-based models for soot and liquid fuel sprays, and Eulerian field methods for solving modeled PDF transport equations. Examples of applications to canonical systems, laboratory-scale flames, and practical combustion devices are provided to emphasize key points. An attempt has been made throughout to strike a balance between rigor and accessibility, between breadth and depth of coverage, and between fundamental physics and practical relevance. It is hoped that this review will contribute to broadening the accessibility of PDF methods and to dispelling misconceptions about PDF methods. Although PDF methods have been applied primarily to reacting ideal-gas mixtures using single-turbulence-scale models, multiple-physics, multiple-scale information is readily incorporated. And while most applications to date have been to laboratory-scale nonpremixed flames, PDF methods can be, and have been, applied to high-Damköhler-number systems as well as to low-to-moderate-Damköhler-number systems, to premixed systems as well as to nonpremixed and partially premixed systems, and to practical combustion devices as well as to laboratory-scale flames. It is anticipated that PDF-based methods will be adopted even more broadly through the 21st century to address important combustion-related energy and environmental issues.
Simulation of the Diesel Engine Combustion Process Using the Stochastic Reactor Model
- M Pasternak
Pasternak M. (2016) Simulation of the Diesel Engine Combustion Process Using the Stochastic Reactor Model. PhD Thesis,
Logos Verlag Berlin, ISBN 978-3-8325-4310-5.