myprojects-hg-reborn

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% Copyright 2007 by Till Tantau
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%
% DO NOT USE THIS FILE AS A TEMPLATE FOR YOUR OWN TALKS¡!!
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% Use a file in the directory solutions instead.
% They are much better suited.
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% Author, Title, etc.
  
\title[Modelling of diesel-engine exhaust nano-particle dynamics] 
{%
  Modelling of diesel-engine exhaust nanoparticle dynamics
%
}

\author[Isella, Drossinos]
{
  Lorenzo~Isella\inst{},
  Barouch Giechaskiel\inst{} 
 and
  Yannis~Drossinos\inst{}
}

\institute[]
{
  \inst{}%
  Joint Research Centre, Ispra, Italy
}

\date{JRC Exploratory Research Symposium, December 2008}


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{\Large \textbf{\textmd{\insertframetitle}}}
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% The main document

\begin{document}





\usebackgroundtemplate{\includegraphics[width=\paperwidth]{back.pdf}}


\begin{frame}
  \titlepage
\end{frame}

% \begin{frame}{Outline}
%   \tableofcontents
% \end{frame}


\section{Introduction}

\subsection{Problem Formulation}
%\vspace*{0.3cm}
\begin{frame}[c]{Motivation and Goals}
\vspace*{-0.2cm}
  \begin{itemize}
\item \textcolor{red}{Diesel-generated nanoparticles} raise concerns
  about their effects on  human health and
  environment.
\item \textcolor{red}{Legislation}  regulating diesel-vehicle particulate \textcolor{red}{mass}
  emissions (EURO1,2,3,4,\emph{etc}\dots), but particle number
  distributions may be a better metric (especially for health effects).
\item Evaluate  \textcolor{red}{effect of sampling and experimental conditions}
 on measured particle number distributions emitted from light/heavy duty vehicles $\Rightarrow$ \textcolor{red}{PMP}.
\item  Exploratory research as an experimental and theoretical study of the
 \textcolor{red}{dynamics of non-volatile (\textcolor{red}{PMP}) particles emitted from diesel
 light-duty vehicles} (emphasis on nanoparticle agglomeration).
 \item Experiments performed at the \textcolor{red}{Vehicle Emission LAboratories}
 (VELA) at Ispra.
% \item Investigation of diesel-nanoparticle aggregate structure, collisions and
%   mobility via \textcolor{red}{Langevin} simulations.
%  \item Aerosol processes: \textcolor{red}{convection, agglomeration, thermophoretic and
%  diffusional transport}
%  \item Emitted agglomerates are \textcolor{red}{fractal} objects. How
%    to estimate their fractal dimension from limited experimental information?



  \end{itemize} 
\end{frame}

\section{Overview of the Experiments}

\subsection{Exhaust-Particle Measurements}
%\vspace*{0.3cm}
\begin{frame}[t]{Experimental setup}
\vspace*{-.6cm}
\begin{center}
\includegraphics[width=8cm, height=6cm]{figure1.pdf}
\end{center}
\vspace*{-0.2cm}
\begin{itemize}
\item Temperature and particle-size distribution measurements along
  \textcolor{red}{whole} experimental manifold (\textcolor{red}{not}
  only at legislated position). 
\end{itemize}
\end{frame}


\subsection{Number Distributions}
%\vspace*{0.3cm}
\begin{frame}[t]{Inlet and outlet experimental
 number distributions:  \\ {   EURO 3 vehicle, 120km/h} }
\vspace*{-0.5cm}
\begin{center}
\rotatebox{90}{\includegraphics[width=5cm, height=8cm]{figure2_b.pdf}}
\end{center}
\vspace*{-0.6cm}
\begin{itemize}
% \item The experimental number distributions can be excellently
%   approximated with analytical lognormal distributions.
 \item \textcolor{red}{Lognormal} distribution
%\vspace*{-0.3cm}
 \beq \nonumber
 \begin{split}
 dN^{\textrm{fit}} & {} =
 \f{N_{\infty}} {\sqrt{2\pi}\log\sigma}\exp\lsq-\f{(\log d_{\rm agg}-\log\mu)^2}{2\log^2\sigma}\rsq d\log d_{\rm agg} \\
%  & {} \equiv n_q (\log d_{\rm agg}) \,  d \log d_{\rm agg}
 \end{split}
 \eeq
\vspace*{-0.2cm}
\item Compact way of representing the data: $N_{\infty}, \mu\;\; {\rm
    and}\;\; \sigma $ \textcolor{red}{unambiguously} describe the experimental data.

 
% \item Pressure fluctuations $\Rightarrow$ higher uncertainty on the 
%   number concentration $N_\infty$ (\textcolor{red}{not} on $\mu$ and $\sigma$) at inlet than outlet.
\end{itemize}
\end{frame}
  
 

\section{Dynamics along transfer tube}

\subsection{1D model for  aerosol dynamics}
  
%\vspace*{0.3cm}   
\begin{frame}[t]{Aerosol in a Tube}
\vspace*{-0.5cm}  
\begin{center}   
\resizebox{10cm}{3cm}{\input{cylinder.pdf_t}} 

%\includegraphics[width=8cm, height=4cm]{cylinder.pdf}
\end{center}
\begin{itemize}
\vspace*{-0.1cm}
\item Four different aerosol processes:
  \textcolor{darkgreen}{agglomeration},
  \textcolor{mymagenta}{diffusion},
\textcolor{Brown}{thermophoresis} and \textcolor{blue}{convection}.
%\vspace*{-0.1cm}     
\item 1D model neglecting turbulence-induced  local  particle density
   inhomogeneities. 
   \item \textcolor{red}{$n_q$} (flux-averaged axial aggregate
     concentration of size $d_q$ [$q$-mer])
 along  tube as function 
     of \textcolor{red}{residence time} \textcolor{blue}{$\tau$}  
\end{itemize} 
\vspace*{-0.1cm}
 \beq\nonumber
 \;\;\,\f{d n_q(\textcolor{blue}{\tau})}{d\textcolor{blue}{\tau}}=-\f{2(\textcolor{mymagenta}{v_{\rm dif}}+\textcolor{Brown}{v_{\rm th}})}{
   R}n_q(\textcolor{blue}{\tau})+
\f{1}{2}\sum_{i+j=q}\textcolor{darkgreen}{\mathcal{K}_{ij}}n_i(\textcolor{blue}{\tau})n_j(\textcolor{blue}{\tau}) - n_q(\textcolor{blue}{\tau})\sum_i\textcolor{darkgreen}{\mathcal{K}_{iq}}n_i(\textcolor{blue}{\tau}).
 \eeq

% \item $n_q$ the mean (flux-averaged) axial aggregate concentration of size $d_q$

        

\end{frame}

%\vspace*{0.3cm}   
\begin{frame}[t]{Time-Scales and Approximations}
%\vspace*{-0.45cm}
  \begin{itemize}
  \item Time-scales for each process: $\tau_{\rm agg}\simeq 2$s,
    $\tau_{\rm dif}\simeq 10^{3}$s, $\tau_{\rm th}\simeq 30s$ and
    $\tau_{\rm conv}\simeq 2$s.
  \end{itemize}
\vspace*{-0.5cm}
\begin{center}
\includegraphics[width=8cm, height=5.5cm]{figure7_b.pdf}
\end{center}
\vspace*{-0.5cm}
\begin{itemize}
\item Effect of the transfer tube length on number concentration:
  important for experiment \textcolor{red}{reproducibility}.
\item Different $\tau_{\rm agg}$ for a \textcolor{red}{light-duty} Euro4-5 diesel engine.
\end{itemize}


\end{frame}

 
\section{Simulation of soot aggregate formation} 
\subsection{Model for Monomer Dynamics}
%\vspace*{0.3cm}   
\begin{frame}[t]{Langevin Equation for Mesoscopic Systems}
\vspace*{-0.5cm}
\begin{center}   
\resizebox{7cm}{4.5cm}{\input{brownian.pdf_t}}

%\includegraphics[width=8cm, height=4cm]{cylinder.pdf}
\end{center}
%\vspace*{-0.15cm}
\begin{itemize}
\item  \textcolor{red}{3D} system of interacting monomers, each
  obeying
%\vspace*{-0.2cm} 
\begin{equation}
  \label{eq:Langevin} \nonumber
  m_1\ddot{\bf r}_i=\textcolor{red}{{\bf F}_i}-\beta_1 m_1\dot{\bf r}_i+ 
  {\bf W}_i(t).
\end{equation}
\vspace*{-0.55cm}  
\item Force acting on i-th monomer from \textcolor{red}{pairwise} monomer-monomer interaction potential
\vspace*{-0.25cm}  
\begin{equation} \nonumber
  \label{eq:potential_pairwise}
  {\bf F}_i=-\nabla_{{\bf r}_i} U_i=-\f{\nabla_{{\bf r}_i}}{2}\lro\s_{j\neq i}u(r_{ij})\rro.
\end{equation}
\end{itemize}
\end{frame}

 

\subsection{Interaction Potential}
%\vspace*{0.3cm}   
\begin{frame}[t]{Monomer-Monomer Interaction Potential}
%\vspace*{-0.5cm}
%  \begin{block}{General Features}
%\vspace*{-0.4cm}
    \begin{itemize}
    \item \textcolor{red}{Repulsion} at short  separations $r\le\sigma$
      (hard-core repulsion) and \textcolor{red}{attraction} for separations above
      $\sigma$ 
      (sticking upon collision).
\item Simulations performed  with two \textcolor{red}{radial} interaction potentials:  integrated Lennard-Jones
  potential  (model for the attractive part of \textcolor{red}{Van der Waals}
  interaction between two spheres,  $\sim r^{-6}$ for $r\gg\sigma$) and with a short-ranged
  \textcolor{red}{model potential}.        
%\begin{itemize}
%\item Potential used in the simulations:
\end{itemize}
\vspace*{-.5cm} 
\begin{figure}  
\includegraphics[height=5cm, width=9cm]{presentation_potential.pdf} 
%\caption{show an example picture}
\end{figure}

     

\end{frame}



  

%\vspace*{0.3cm}   
\begin{frame}[t]{Distribution of Aggregate Morphologies} 
\vspace*{-0.5cm}
\begin{figure}
\includegraphics[height=3.5cm, width=0.43\columnwidth]{final2.png}
\vspace*{0.1cm} 
\includegraphics[height=3.5cm, width=0.43\columnwidth]{50_monomers_neighbor1_bis.png} 
%\caption{show an example picture}
\end{figure} 

\vspace{-0.5cm}

\begin{figure}
\includegraphics[height=3.5cm, width=0.43\columnwidth]{50_monomers_neighbor2_bis.png} 
\vspace*{0.1cm} 
\includegraphics[height=3.5cm, width=0.43\columnwidth]{50_monomers_neighbor3_bis.png} 
%\caption{show an example picture}
\end{figure} 
\end{frame}




\subsection{Determination of the Fractal Dimension}
\begin{frame}
\begin{figure}
\includegraphics[height=5cm, width=5cm]{camera.jpeg} 
%\caption{show an example picture}
\end{figure}
\end{frame}


\section{Conclusions}
%\vspace*{0.3cm}   
\begin{frame}[t]{Final Remarks}
  \begin{itemize}
  \item Simplified 1D model for soot solid nanoparticles (PMP
    recommendation) $\Rightarrow$ runs on any up-to-date PC within hours.
\item  Determination of characteristic time-scales.
\item Different role of agglomeration for Euro4-5 vehicles.
\item Modelling  complements the experimental information on soot
  aggregates $\Rightarrow$  theoretical investigation on aggregate
  structure, mobility and collisional properties.   
  \end{itemize}
\end{frame}

   

\end{document}