Implementation of the Semi Empirical Kinetic Soot Model within Chemistry Tabulation Framework for Efficient Emissions Predictions in Diesel Engines

Soot prediction for diesel engines is a very important aspect of internal combustion engine emissions research, especially nowadays with very strict emission norms. Computational Fluid Dynamics (CFD) is often used in this research and optimisation of CFD models in terms of a trade-off between accuracy and computational efficiency is essential. This is especially true in the industrial environment where good predictivity is necessary for engine optimisation, but computational power is limited. To investigate soot emissions for Diesel engines, in this work CFD is coupled with chemistry tabulation framework and semi-empirical soot model. The Flamelet Generated Manifold (FGM) combustion model precomputes chemistry using detailed calculations of the 0D homogeneous reactor and then stores the species mass fractions in the table, based on six look-up variables: pressure, temperature, mixture fraction, mixture fraction variance, progress variable and progress variable variance. Data is then retrieved during online CFD simulation, enabling fast execution times while keeping the accuracy of the direct chemistry calculation. In this work, the theory behind the model is discussed as well as implementation in commercial CFD code. Also, soot modelling in the framework of tabulated chemistry is investigated: mathematical model and implementation of the kinetic soot model on the tabulation side is described, and 0D simulation results are used for verification. Then, the model is validated using real-life engine geometry under different operating conditions, where better agreement with experimental measurements is achieved, compared to the standard implementation of the kinetic soot model on the CFD side

Applying a Tabulated Chemistry Approach for the Calculation of Combustion and Emissions in Diesel Engines

It is generally acknowledged, that more details of the chemical reactions occurring in the flame front should be accounted for in the CFD simulations, but with increasing the number of species and reactions involved the associated CPU cost grows quickly beyond practical engineering time limits. Aim of this work is to increase computation efficiency by using a tabulation technique, without losing any accuracy. In order to achieve these goals, dedicated software solution for the generation of CFD look-up tables for advanced combustion models, is applied. Simulations were run for real life Diesel engine, for 5 different EGR levels. FGM results are showing very good match with measurements and direct calculation of the chemical reactions. The runtime for CFD simulations, including chemistry pre-processing, does only mildly increase with the number of species used in the reaction mechanism; simulations with 1000+ species have been realized within 20 hrs on 8 CPU cores

Time-optimal path planning in dynamic flows using level set equations: theory and schemes

We develop an accurate partial differential equation-based methodology that predicts the time-optimal paths of autonomous vehicles navigating in any continuous, strong, and dynamic ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-optimal path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-optimal paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.United States. Office of Naval Research (Grant N00014-09-1-0676 (Science of Autonomy - A-MISSION))United States. Office of Naval Research (Grant N00014-12-1-0944 (ONR6.2))Natural Sciences and Engineering Research Council of Canada (Postgraduate Fellowship

Generalized Huygens principle with pulsed-beam wavelets

Huygens' principle has a well-known problem with back-propagation due to the spherical nature of the secondary wavelets. We solve this by analytically continuing the surface of integration. If the surface is a sphere of radius $R$, this is done by complexifying $R$ to $R+ia$. The resulting complex sphere is shown to be a real bundle of disks with radius $a$ tangent to the sphere. Huygens' "secondary source points" are thus replaced by disks, and his spherical wavelets by well-focused pulsed beams propagating outward. This solves the back-propagation problem. The extended Huygens principle is a completeness relation for pulsed beams, giving a representation of a general radiation field as a superposition of such beams. Furthermore, it naturally yields a very efficient way to compute radiation fields because all pulsed beams missing a given observer can be ignored. Increasing $a$ sharpens the focus of the pulsed beams, which in turn raises the compression of the representation.Comment: 49 pages, 14 figure

Differential Adaptation of Human Gut Microbiota to Bariatric Surgery–Induced Weight Loss: Links With Metabolic and Low-Grade Inflammation Markers

International audienceOBJECTIVE Obesity alters gut microbiota ecology and associates with low-grade inflammation in humans. Roux-en-Y gastric bypass (RYGB) surgery is one of the most efficient procedures for the treatment of morbid obesity resulting in drastic weight loss and improvement of metabolic and inflammatory status. We analyzed the impact of RYGB on the modifications of gut microbiota and examined links with adaptations associated with this procedure. RESEARCH DESIGN AND METHODS Gut microbiota was profiled from fecal samples by real-time quantitative PCR in 13 lean control subjects and in 30 obese individuals (with seven type 2 diabetics) explored before (M0), 3 months (M3), and 6 months (M6) after RYGB. RESULTS Four major findings are highlighted: 1) Bacteroides/Prevotella group was lower in obese subjects than in control subjects at MO and increased at M3. It was negatively correlated with corpulence, but the correlation depended highly on caloric intake; 2) Escherichia coli species increased at M3 and inversely correlated with fat mass and leptin levels independently of changes in food intake; 3) lactic acid bacteria including Lacto-bacillus/Leuconostoc/Pediococcus group and Bifidobacterium genus decreased at M3; and 4) Faecalibacterium prausnitzii species was lower in subjects with diabetes and associated negatively with inflammatory markers at MO and throughout the follow-up after surgery independently of changes in food intake. CONCLUSIONS These results suggest that components of the dominant gut microbiota rapidly adapt in a starvation-like situation induced by RYGB while the F. prausnitzii species is directly linked to the reduction in low-grade inflammation state in obesity and diabetes independently of calorie intake. Diabetes 59:3049-3057, 201