A Practical Guide to Surface Kinetic Monte Carlo Simulations

This review article is intended as a practical guide for newcomers to the field of kinetic Monte Carlo (KMC) simulations, and specifically to lattice KMC simulations as prevalently used for surface and interface applications. We will provide worked out examples using the kmos code, where we highlight the central approximations made in implementing a KMC model as well as possible pitfalls. This includes the mapping of the problem onto a lattice and the derivation of rate constant expressions for various elementary processes. Example KMC models will be presented within the application areas surface diffusion, crystal growth and heterogeneous catalysis, covering both transient and steady-state kinetics as well as the preparation of various initial states of the system. We highlight the sensitivity of KMC models to the elementary processes included, as well as to possible errors in the rate constants. For catalysis models in particular, a recurrent challenge is the occurrence of processes at very different timescales, e.g. fast diffusion processes and slow chemical reactions. We demonstrate how to overcome this timescale disparity problem using recently developed acceleration algorithms. Finally, we will discuss how to account for lateral interactions between the species adsorbed to the lattice, which can play an important role in all application areas covered here.Comment: This document is the final Author's version of a manuscript that has been peer reviewed and accepted for publication in Frontiers in Chemistry. To access the final edited and published work see https://www.frontiersin.org/articles/10.3389/fchem.2019.00202/abstrac

An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms

This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Industrial marketing planning is a typical example of an unstructured decision making problem due to the large number of variables to consider and the uncertainty imposed on those variables. Although abundant studies identified barriers and facilitators of effective industrial marketing planning in practice, the literature still lacks practical tools and methods that marketing managers can use for the task. This paper applies fuzzy cognitive maps (FCM) to industrial marketing planning. In particular, agent based inference method is proposed to overcome dynamic relationships, time lags, and reusability issues of FCM evaluation. MACOM simulator also is developed to help marketing managers conduct what-if scenarios to see the impacts of possible changes on the variables defined in an FCM that represents industrial marketing planning problem. The simulator is applied to an industrial marketing planning problem for a global software service company in South Korea. This study has practical implication as it supports marketing managers for industrial marketing planning that has large number of variables and their cause–effect relationships. It also contributes to FCM theory by providing an agent based method for the inference of FCM. Finally, MACOM also provides academics in the industrial marketing management discipline with a tool for developing and pre-verifying a conceptual model based on qualitative knowledge of marketing practitioners.Ministry of Education, Science and Technology (Korea

High-efficiency silicon solar-cell design and practical barriers

A numerical evaluation technique is used to study the impact of practical barriers, such as heavy doping effects (Auger recombination, band gap narrowing), surface recombination, shadowing losses and minority-carrier lifetime (Tau), on a high efficiency silicon solar cell performance. Considering a high Tau of 1 ms, efficiency of a silicon solar cell of the hypothetical case is estimated to be around 29%. This is comparable with (detailed balance limit) maximum efficiency of a p-n junction solar cell of 30%. Value of Tau is varied from 1 second to 20 micro. Heavy doping effects, and realizable values of surface recombination velocities and shadowing, are then considered in succession and their influence on cell efficiency is evaluated and quantified. These practical barriers cause the cell efficiency to reduce from the maximum value of 29% to the experimentally achieved value of about 19%. Improvement in open circuit voltage V sub oc is required to achieve cell efficiency greater than 20%. Increased value of Tau reduces reverse saturation current and, hence, improves V sub oc. Control of surface recombination losses becomes critical at higher V sub oc. Substantial improvement in Tau and considerable reduction in surface recombination velocities is essential to achieve cell efficiencies greater than 20%

Dynamic actions on bridge slabs due to heavy vehicle impact on roadside barriers

The use of roadside safety barriers in Italy has changed in recent years: the number of installed devices has increased, and so have their stiffness and resistance. These changes were necessary because early barrier design was inadequate to contain and redirect heavy vehicles. The change in barrier design led to an increase in stiffness and resistance; consequently, the action transferred to the structure by the device increased. The need for resistance on the bridge slabs can be too high because the peculiar action of the roadside barriers was not adequately taken into account in the oldest bridge design codes. In addition, characterizing the actions transferred to the bridge slab is difficult because of the dynamic nature of vehicle impacts on roadside barriers. Given the impossibility of performing a full-scale laboratory test for every bridge deck, the use of computational mechanics applied to dynamic impact/interaction problems is one of the best ways to establish these actions in the project phase. Research was conducted into the use of a three-dimensional finite element model of the bridge slab-barrier-vehicle system to perform a numerical simulation of the impact, according to the procedure used for the roadside barrier homologation crash test, described in the European Standard EN 1317

Ab-initio molecular dynamics simulation of hydrogen diffusion in α\alpha-iron

First-principles atomistic molecular dynamics simulation in the micro-canonical and canonical ensembles has been used to study the diffusion of interstitial hydrogen in $\alpha$-iron. Hydrogen to Iron ratios between $\theta=1/16 and 1/2 have been considered by locating interstitial hydrogen atoms at random positions in a$2 \times 2 \times 2$ supercell. We find that the average optimum absorption site and the barrier for diffusion depend on the concentration of interestitials. Iron Debye temperature decreases monotonically for increasing concentration of interstitial hydrogen, proving that iron-iron interatomic potential is significantly weakened in the presence of a large number of diffusing hydrogen atoms

Electromagnetic propagation through non-dissipative and dissipative barriers : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Physics at Massey University, Palmerston North, New Zealand

A Matlab simulation was developed to help visualise and investigate electromagnetic tunnelling through particular non-dissipative and dissipative barriers within a waveguide. The theory behind the simulation is based on a transmission line model that accurately predicts experimental results and is shown to be equivalent to previous numerical and quantum tunnelling models. A few useful speeds referring to electromagnetic waves have been defined and utilised to calculate die speeds at which different incident time signals penetrate electromagnetic barriers. Due to bandwidth restrictions, the created incident time signals had wavepacket properties. The importance of resampling an oscillating signal at the appropriate frequency to avoid aliasing has been recognised. The definition and creation of matched signals that can penetrate long barriers yet remain a single pulse have been investigated. Such signals will have no practical application since the attenuation will deem the transmitted signals immeasurable. However, the speeds through these larger barrier lengths will have a smaller uncertainty since the time delays are longer. Most of the signal distortion depends only on the barrier interfaces rather than the barrier length. Penetration through dissipative barriers gives speeds below the vacuum speed of light for all barrier lengths investigated. Faster than light speeds are however predicted for penetration through non-dissipative barriers greater than about 4cm

BarrierPoint: sampled simulation of multi-threaded applications

Sampling is a well-known technique to speed up architectural simulation of long-running workloads while maintaining accurate performance predictions. A number of sampling techniques have recently been developed that extend well- known single-threaded techniques to allow sampled simulation of multi-threaded applications. Unfortunately, prior work is limited to non-synchronizing applications (e.g., server throughput workloads); requires the functional simulation of the entire application using a detailed cache hierarchy which limits the overall simulation speedup potential; leads to different units of work across different processor architectures which complicates performance analysis; or, requires massive machine resources to achieve reasonable simulation speedups. In this work, we propose BarrierPoint, a sampling methodology to accelerate simulation by leveraging globally synchronizing barriers in multi-threaded applications. BarrierPoint collects microarchitecture-independent code and data signatures to determine the most representative inter-barrier regions, called barrierpoints. BarrierPoint estimates total application execution time (and other performance metrics of interest) through detailed simulation of these barrierpoints only, leading to substantial simulation speedups. Barrierpoints can be simulated in parallel, use fewer simulation resources, and define fixed units of work to be used in performance comparisons across processor architectures. Our evaluation of BarrierPoint using NPB and Parsec benchmarks reports average simulation speedups of 24.7x (and up to 866.6x) with an average simulation error of 0.9% and 2.9% at most. On average, BarrierPoint reduces the number of simulation machine resources needed by 78x