Browsing by Subject "Monte-Carlo simulation"
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Item A comprehensive study of cholesterol in biomembranes using computer simulations(2011-05) Dai, Jian; Huang, Juyang; Park, Soyeun; Sanati, Mahdi; Khare, RajeshSeveral methods were applied to study the effects of cholesterol on multi-component lipid bilayers. The goal is to investigate the validity of the "Umbrella Effect" via simulations and experiments. The Umbrella Model is a hypothesis proposed based on previous structural and thermodynamical studies of lipid membranes containing cholesterol. DPPC is the most widely studied phospholipid in the simulation community. It has a large polar headgroup (which consists of a positively charged choline group and a negatively charged phosphate group), a glycerol group and two long saturated hydrocarbon chains. On the other hand, cholesterol has a relatively large carbon-ring body, compared to its small hydrophilic hydroxyl group. When a binary mixture of DPPC/cholesterol is placed in an aqueous environment, it has been suggested that cholesterol is always trying to find a “shield” to protect it from extensive contact with water, and this shield is most likely to be provided by the headgroups of phospholipids. This hypothesis is termed the “Umbrella Model”. Monte Carlo (MC) simulations will be used to study the phase transitions of multi-component lipid mixtures and molecular dynamics (MD) simulations will be used to test the Umbrella Model in direct and indirect ways, and to interpret the experimental data. Melittin is the most studied antimicrobial peptide, it can cause cell death by damaging cell membranes. Melittin interacts differently with various membrane components, such as cholesterol and negatively-charged phospholipid, both of which have been shown to reduce melittin's lytic effect against the membrane. Several model systems were constructed and simulated, different effects were observed and the possible mechanisms were discussed.Item Effect of cumulative seismic damage and corrosion on life-cycle cost of reinforced concrete bridges(2009-05-15) Kumar, RameshBridge design should take into account not only safety and functionality, but also the cost effectiveness of investments throughout a bridge life-cycle. This work presents a probabilistic approach to compute the life-cycle cost (LCC) of corroding reinforced concrete (RC) bridges in earthquake prone regions. The approach is developed by combining cumulative seismic damage and damage associated to corrosion due to environmental conditions. Cumulative seismic damage is obtained from a low-cycle fatigue analysis. Chloride-induced corrosion of steel reinforcement is computed based on Fick?s second law of diffusion. The proposed methodology accounts for the uncertainties in the ground motion parameters, the distance from source, the seismic demand on the bridge, and the corrosion initiation time. The statistics of the accumulated damage and the cost of repairs throughout the bridge life-cycle are obtained by Monte-Carlo simulation. As an illustration of the proposed approach, the effect of design parameters on the life-cycle cost of an example RC bridge is studied. The results are shown to be valuable in better estimating the condition of existing bridges (i.e., total accumulated damage at any given time) and, therefore, can help schedule inspection and maintenance programs. In addition, by taking into consideration the deterioration process over a bridge life-cycle, it is possible to make an estimate of the optimum design parameters by minimizing, for example, the expected cost throughout the life of the structure.Item In-Jet Tracking Efficiency Analysis for the STAR Time Projection Chamber in Polarized Proton-Proton Collisions at sqrt(s) = 200GeV(2012-07-16) Huo, LiaoyuanAs one of the major mid-rapidity tracking devices of the STAR detector at the Relativistic Heavy-Ion Collider (RHIC), the Time Projection Chamber (TPC) plays an important role in measuring trajectory and energy of high energy charged particles in polarized proton-proton collision experiments. TPC's in-jet tracking efficiency represents the largest systematic uncertainty on jet energy scale at high transverse momentum, whose measurement contributes to the understanding of the spin structure of protons. The objective of this analysis is to get a better estimation of this systematic uncertainty, through methods of pure Monte-Carlo simulation and real- data embedding, in which simulated tracks are embedded into real-data events. Be- sides, simulated tracks are also embedded into Monte-Carlo events, to make a strict comparison for the uncertainty estimation. The result indicates that the unexplained part of the systematic uncertainty is reduced to 3.3%, from a previous quoted value of 5%. This analysis also suggests that future analysis, such as embedding jets into zero-bias real data and analysis with much higher event statistics, will benefit the understanding of the systematic uncertainty of the in-jet TPC tracking efficiency.Item Polymer nanocomposite foams : fabrication, characterization, and modeling(2012-12) Kim, Yongha; Li, Wei, doctor of mechanical engineering; Chen, Jonathan Y.; Djurdjanovic, Dragan; Ferreira, Paulo; Koo, Joseph H.Polymer nanocomposite foams have attracted tremendous interests due to their multifunctional properties in addition to the inherited lightweight benefit of being foamed materials. Polymer nanocomposite foams using high performance polymer and bio-degradable polymer with carbon nanotubes were fabricated, and the effects of foam density and pore size on properties were characterized. Electrical conductivity modeling of polymer nanocomposite foams was conducted to investigate the effects of density and pore size. High performance polymer Polyetherimide (PEI) and multi-walled carbon nanotube (MWCNT) nanocomposites and their foams were fabricated using solvent-casting and solid-state foaming under different foaming conditions. Addition of MWCNTs has little effect on the storage modulus of the nanocomposites. High glass transition temperature of PEI matrix was maintained in the PEI/MWCNT nanocomposites and foams. Volume electrical conductivities of the nanocomposite foams beyond the percolation threshold were within the range of electro-dissipative materials according to the ANSI/ESD standard, which indicates that these lightweight materials could be suitable for electro-static dissipation applications with high temperature requirements. Biodegradable Polylactic acid (PLA) and MWCNT nanocomposites and their foams were fabricated using melt-blending and solid-state foaming under different foaming conditions. Addition of MWCNTs increased the storage modulus of PLA/MWCNT composites. By foaming, the glass transition temperature increased. Volume electrical conductivities of foams with MWCNT contents beyond the percolation threshold were again within the range of electro-dissipative materials according to the ANSI/ESD standard. The foams with a saturation pressure of 2 MPa and foaming temperature of 100 °C showed a weight reduction of 90% without the sacrifice of electrical conductivity. This result is promising in terms of multi-functionality and material saving. At a given CNT loading expressed as volume percent, the electrical conductivity increased significantly as porosity increased. A Monte-Carlo simulation model was developed to understand and predict the electrical conductivity of polymer/MWCNT nanocomposite foams. Two different foam morphologies were considered, designated as Case 1: volume expansion without nanotube rearrangement, and Case 2: nanotube aggregation in cell walls. Simulation results from unfoamed nanocomposites and the Case 1 model were validated with experimental data. The results were in good agreement with those from PEI/MWCNT nanocomposites and their foams, which had a similar microstructure as modeled in Case 1. Porosity effects on electrical conductivity were investigated for both Case 1 and Case 2 models. There was no porosity effect on electrical conductivity at a given volume percent CNT loading for Case 1. However, for Case 2 the electrical conductivity increased as porosity increased. Pore size effect was investigated using the Case 2 model. As pore size increased, the electrical conductivity also increased. Electrical conductivity prediction of foamed polymer nanocomposites using FEM was performed. The results obtained from FEM were compared with those from the Monte-Carlo simulation method. Feasibility of using FEM to predict the electrical conductivity of foamed polymer nanocomposites was discussed. FEM was able to predict the electrical conductivity of polymer nanocomposite foams represented by the Case 2 model with various porosities. However, it could not capture the pore size effect in the electrical conductivity prediction. The FEM simulation can be utilized to predict the electrical conductivity of Case 2 foams when the percolation threshold is determined by Monte-Carlo simulation to save the computational time. This has only been verified when the pore size is small in the range of a few micrometers.