MODELLING AEROSOL DYNAMICS : A STOCHASTIC ALGORITHM

2001 ◽  
Vol 32 ◽  
pp. 1037-1038
Author(s):  
E. DEBRY ◽  
B. JOURDAIN ◽  
B. SPORTISSE
Keyword(s):  
Stochastic Algorithm ◽  
Aerosol Dynamics

Modeling Aerosol Dynamics: A Stochastic Algorithm

2002 ◽  
pp. 308-318
Author(s):  
Edouard Debry ◽  
Benjamin Jourdain ◽  
Bruno Sportisse
Keyword(s):  
Stochastic Algorithm ◽  
Aerosol Dynamics

Comparison of soot models for reacting sprays in diesel engine-like conditions

2021 ◽  
pp. 095440702110154
Author(s):  
Pavan Prakash Duvvuri ◽  
Rajesh Kumar Shrivastava ◽  
Sheshadri Sreedhara
Keyword(s):  
Experimental Data ◽  
Volume Fraction ◽  
Soot Volume Fraction ◽  
Modeling Framework ◽  
Aerosol Dynamics ◽  
Significant Difference ◽  
Polycyclic Aromatic ◽  
Order Of Magnitude ◽  
Detailed Kinetics ◽  
Soot Model

Stringent emission legislations and growing health concerns have contributed to the evolution of soot modeling in diesel engines from simple empirical relations to methods involving detailed kinetics and complex aerosol dynamics. In this paper, four different soot models have been evaluated for the high temperature, high pressure combusting dodecane spray cases of engine combustion network (ECN) spray A which mimics engine-relevant conditions. The soot models considered include an empirical, a multistep, a method of moments based, and a discrete sectional method soot model. Two experimental cases with ambient oxygen volume of 21% and 15% have been modeled. A good agreement between simulations and experiments for vapor penetration and heat release rate has been obtained. Quasi-steady soot volume fraction contours for the four soot models have been compared with experiments. Contours of the species and source terms involved in soot modeling have also been compared for a better understanding of soot processes. The empirical soot model results in higher magnitude and spread of soot due to a lack of modeling framework for oxidation through OH species. Among the four models studied, the multistep soot model has been observed to provide the most promising agreement with the experimental data in terms of distribution of soot and location of peak soot volume fraction. Due to a two-way coupling of soot models, the detailed models predict an upstream location for soot as compared to the multi-step soot model which is one way coupled. A significant difference (of an order of magnitude) in the concentration of PAH (polycyclic aromatic hydrocarbons) precursor between multistep and detailed soot models has been observed because of precursor consumption due to the coupling of detailed soot models with chemical kinetics. It is recommended that kinetic schemes, especially those concerning PAH, be validated with experimental data with a kinetics-coupled soot model.

scholarly journals Improving Computational Efficiency in Crowded Task Allocation Games with Coupled Constraints

2019 ◽  
Vol 9 (10) ◽  
pp. 2117
Author(s):  
Ming Chong Lim ◽  
Han-Lim Choi
Keyword(s):  
Task Allocation ◽  
Random Sampling ◽  
Scheduling Algorithm ◽  
Stochastic Algorithm ◽  
Speed Of Convergence ◽  
Temporal Dependence ◽  
Real World Applications ◽  
Coupled Constraints ◽  
Multi Agent ◽  
Feasible Solutions

Multi-agent task allocation is a well-studied field with many proven algorithms. In real-world applications, many tasks have complicated coupled relationships that affect the feasibility of some algorithms. In this paper, we leverage on the properties of potential games and introduce a scheduling algorithm to provide feasible solutions in allocation scenarios with complicated spatial and temporal dependence. Additionally, we propose the use of random sampling in a Distributed Stochastic Algorithm to enhance speed of convergence. We demonstrate the feasibility of such an approach in a simulated disaster relief operation and show that feasibly good results can be obtained when the confirmation and sample size requirements are properly selected.

Nanoparticle Mass Transfer From Lung Airways to Systemic Regions—Part II: Multi-Compartmental Modeling

2013 ◽  
Vol 135 (12) ◽  
Author(s):  
Arun V. Kolanjiyil ◽  
Clement Kleinstreuer
Keyword(s):  
Mass Transfer ◽  
Model Parameters ◽  
Computationally Efficient ◽  
Nanoparticle Deposition ◽  
Aerosol Dynamics ◽  
Multicompartmental Model ◽  
Quantitative Results ◽  
Species Extrapolation ◽  
Critical Insight ◽  
Lung Airways

This is the second article of a two-part paper, combining high-resolution computer simulation results of inhaled nanoparticle deposition in a human airway model (Kolanjiyil and Kleinstreuer, 2013, “Nanoparticle Mass Transfer From Lung Airways to Systemic Regions—Part I: Whole-Lung Aerosol Dynamics,” ASME J. Biomech. Eng., 135(12), p. 121003) with a new multicompartmental model for insoluble nanoparticle barrier mass transfer into systemic regions. Specifically, it allows for the prediction of temporal nanoparticle accumulation in the blood and lymphatic systems and in organs. The multicompartmental model parameters were determined from experimental retention and clearance data in rat lungs and then the validated model was applied to humans based on pharmacokinetic cross-species extrapolation. This hybrid simulator is a computationally efficient tool to predict the nanoparticle kinetics in the human body. The study provides critical insight into nanomaterial deposition and distribution from the lungs to systemic regions. The quantitative results are useful in diverse fields such as toxicology for exposure-risk analysis of ubiquitous nanomaterial and pharmacology for nanodrug development and targeting.

The aerosol dynamics of H2O–H2SO4–HNO3 mixtures in aircraft wakes. A modeling study

1999 ◽  
Vol 1 (24) ◽  
pp. 5503-5509 ◽  
Author(s):  
Götz Gleitsmann ◽  
Reinhard Zellner
Keyword(s):  
Aerosol Dynamics ◽  
Modeling Study

A new weighted fraction Monte Carlo method for particle coagulation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiao Jiang ◽  
Tat Leung Chan
Keyword(s):  
Monte Carlo ◽  
Design Methodology ◽  
Computational Cost ◽  
Particle Coagulation ◽  
Content Type ◽  
Aerosol Dynamics ◽  
Stochastic Error ◽  
Adjustable Weight ◽  
Initial Distributions ◽  
Coagulation Kernel

Purpose The purpose of this study is to investigate the aerosol dynamics of the particle coagulation process using a newly developed weighted fraction Monte Carlo (WFMC) method. Design/methodology/approach The weighted numerical particles are adopted in a similar manner to the multi-Monte Carlo (MMC) method, with the addition of a new fraction function (α). Probabilistic removal is also introduced to maintain a constant number scheme. Findings Three typical cases with constant kernel, free-molecular coagulation kernel and different initial distributions for particle coagulation are simulated and validated. The results show an excellent agreement between the Monte Carlo (MC) method and the corresponding analytical solutions or sectional method results. Further numerical results show that the critical stochastic error in the newly proposed WFMC method is significantly reduced when compared with the traditional MMC method for higher-order moments with only a slight increase in computational cost. The particle size distribution is also found to extend for the larger size regime with the WFMC method, which is traditionally insufficient in the classical direct simulation MC and MMC methods. The effects of different fraction functions on the weight function are also investigated. Originality Value Stochastic error is inevitable in MC simulations of aerosol dynamics. To minimize this critical stochastic error, many algorithms, such as MMC method, have been proposed. However, the weight of the numerical particles is not adjustable. This newly developed algorithm with an adjustable weight of the numerical particles can provide improved stochastic error reduction.

Sign in / Sign up

Export Citation Format

Share Document