A Phase-field Model for Computer Simulation of Lamellar Structure Formation in y-TiAI

In the present paper, a phase-field model is developed to simulate the formation and evolution of lamellar microstructure in γ-TiAl alloys. The mechanism of formation of TiAl lamellae proposed by Denquin and Naka is incorporated into the model. The model describes the formation and evolution of the face-centered cubic (fcc) stacking lamellar zone followed by the subsequent appearance and growth of the γ-phase, involving both the chemical composition change by atom transfer and the ordering of the fcc lattice. The thermodynamics of the model system and the interaction between the displacive and diffusional transformations are described by a non-equilibrium free energy formulated as a function of concentration and structural order parameter fields. The long-range elastic interactions, arising from the lattice misfit between the α, fcc (A1) and the various orientation variants of the γ-phase are taken into account by incorporating of the elastic strain energy into the total free energy. Simulation studies based on the model successfully predicted some essential features of the lamellar structure. It is found that the formation and evolution of the lamellar structure are predominantly controlled by the minimization of the elastic energy of the interfaces between the different fcc stacking groups, low-symmetry product phase γ and the high-symmetry α-phase, as well as between the various orientation variants of the product phase.

Molecular dynamics simulation of ionic liquids: The effect of electronic polarizability

An electronically polarizable model has been developed for the ionic liquid 1-ethyl-3-methylimidazolium nitrate (EMIM+/NO3-), Molecular dynamics simulation studies were then performed on both the polarizable and nonpolarizable versions of the model. Comparisons of shear viscosity and diffusion constants at 400 K show that the effects of polarizability are quite substantial and the polarizable model results are in better agreement with the experimental values.

Diamond machining of silicon: A review of advances in molecular dynamics simulation

Molecular dynamics (MD) simulation has enhanced our understanding about ductile-regime machining of brittle materials such as silicon and germanium. In particular, MD simulation has helped understand the occurrence of brittle–ductile transition due to the high-pressure phase transformation (HPPT), which induces Herzfeld–Mott transition. In this paper, relevant MD simulation studies in conjunction with experimental studies are reviewed with a focus on (i) the importance of machining variables: undeformed chip thickness, feed rate, depth of cut, geometry of the cutting tool in influencing the state of the deviatoric stresses to cause HPPT in silicon, (ii) the influence of material properties: role of fracture toughness and hardness, crystal structure and anisotropy of the material, and (iii) phenomenological understanding of the wear of diamond cutting tools, which are all non-trivial for cost-effective manufacturing of silicon. The ongoing developmental work on potential energy functions is reviewed to identify opportunities for overcoming the current limitations of MD simulations. Potential research areas relating to how MD simulation might help improve existing manufacturing technologies are identified which may be of particular interest to early stage researchers.

Offshore wind turbine simulation: multibody drive train. Bacl-to-back NPC (Neutral Point Clamped) converters: Fractional-order control

This paper is on offshore wind energy conversion systems installed on the deep water and equipped with back-to-back neutral point clamped full-power converter, permanent magnet synchronous generator with an AC link. The model for the drive train is a five-mass model which incorporates the dynamic of the structure and the tower in order to emulate the effect of the moving surface. A three-level converter and a four-level converter are the two options with a fractional-order control strategy considered to equip the conversion system. Simulation studies are carried out to assess the quality of the energy injected into the electric grid. Finally, conclusions are presented. (C) 2014 Elsevier Ltd. All rights reserved.

Agent Based Evacuation Simulation Using Leader-Follower Model

Agent based simulation is a widely developing area in artificial intelligence.The simulation studies are extensively used in different areas of disaster management. This work deals with the study of an agent based evacuation simulation which is being done to handle the various evacuation behaviors.Various emergent behaviors of agents are addressed here. Dynamic grouping behaviors of agents are studied. Collision detection and obstacle avoidances are also incorporated in this approach.Evacuation is studied with single exits and multiple exits and efficiency is measured in terms of evacuation rate, collision rate etc.Net logo is the tool used which helps in the efficient modeling of scenarios in evacuation

First structural analysis of a naphthalene-based poly(ether ketone): Crystal and molecular simulation from X-ray powder data and diffraction modeling

Polycondensation of 2,6-dihydroxynaphthalene with 4,4'-bis(4"-fluorobenzoyl)biphenyl affords a novel, semicrystalline poly(ether ketone) with a melting point of 406 degreesC and glass transition temperature (onset) of 168 degreesC. Molecular modeling and diffraction-simulation studies of this polymer, coupled with data from the single-crystal structure of an oligomer model, have enabled the crystal and molecular structure of the polymer to be determined from X-ray powder data. This structure-the first for any naphthalene-containing poly(ether ketone)-is fully ordered, in monoclinic space group P2(1)/b, with two chains per unit cell. Rietveld refinement against the experimental powder data gave a final agreement factor (R-wp) of 6.7%.

Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study

We investigated the effect of morphological differences on neuronal firing behavior within the hippocampal CA3 pyramidal cell family by using three-dimensional reconstructions of dendritic morphology in computational simulations of electrophysiology. In this paper, we report for the first time that differences in dendritic structure within the same morphological class can have a dramatic influence on the firing rate and firing mode (spiking versus bursting and type of bursting). Our method consisted of converting morphological measurements from three-dimensional neuroanatomical data of CA3 pyramidal cells into a computational simulator format. In the simulation, active channels were distributed evenly across the cells so that the electrophysiological differences observed in the neurons would only be due to morphological differences. We found that differences in the size of the dendritic tree of CA3 pyramidal cells had a significant qualitative and quantitative effect on the electrophysiological response. Cells with larger dendritic trees: (1) had a lower burst rate, but a higher spike rate within a burst, (2) had higher thresholds for transitions from quiescent to bursting and from bursting to regular spiking and (3) tended to burst with a plateau. Dendritic tree size alone did not account for all the differences in electrophysiological responses. Differences in apical branching, such as the distribution of branch points and terminations per branch order, appear to effect the duration of a burst. These results highlight the importance of considering the contribution of morphology in electrophysiological and simulation studies.

Molecular dynamics simulation insight into the mechanism of phenol adsorption at low coverages from aqueous solutions on microporous carbons

MD simulation studies showing the influence of porosity and carbon surface oxidation on phenol adsorption from aqueous solutions on carbons are reported. Based on a realistic model of activated carbon, three carbon structures with gradually changed microporosity were created. Next, a different number of surface oxygen groups was introduced. The pores with diameters around 0.6 nm are optimal for phenol adsorption and after the introduction of surface oxygen functionalities, adsorption of phenol decreases (in accordance with experimental data) for all studied models. This decrease is caused by a pore blocking effect due to the saturation of surface oxygen groups by highly hydrogen-bounded water molecules.

Towards data warehousing and mining of protein unfolding simulation data

OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles : a simulation study

Generalized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three different statistical principles - marginal likelihood, extended likelihood, Bayesian analysis-via simulation studies. Real data on contact wrestling are used for illustration.

Computational studies to understand the role of social learning in team familiarity and its effects on team performance

This paper concerns social learning modes and their effects on team performance. Social learning, such as by observing others' actions and their outcomes, allows members of a team to learn what other members know. Knowing what other members know can reduce task communication and co-ordination overhead, which helps the team to perform faster since members can devote their attention to their tasks. This paper describes agent-based simulation studies using a computational model that implements different social learning modes as parameters that can be controlled in the simulations. The results show that social learning from both direct and indirect observations positively contributes to learning about what others know, but the value of social learning is sensitive to prior familiarity such that minimum thresholds of team familiarity are needed to realise the benefits of social learning. This threshold increases with task complexity. These findings clarify the level of influence that sociality has on social learning and sets up a formal framework by which to conduct studies on how social context influences learning and group performance.

Modelling daylight for preserving identity : simulation of daylight levels for successful intervention in historic buildings

Historical listed buildings have their own unique cultural identity, which is one of the criteria used by decision mechanisms for their statutory protection. The identity of many of these buildings is often related to their tangible features/components, such as period characteristics (geometry, size, colour, form, and shape), materials and construction. Daylight is one of the in/tangible elements that have contributed to the distinctiveness of many historical buildings, yet when constructing preservation schemes of historical buildings, daylight is rarely introduced or considered as one of the components that shape the character of buildings. One of the reasons is the limited number of credible simulation studies that identify such interrelationships. As many of these buildings were originally designed to accommodate different activities to today's requirements, maintaining the quality of daylight that originally contributed to their visual identity can be a very challenging task, especially if the building is to be adapted to accommodate a different activity. In this paper we will discuss the conflict between maintaining the original visual identity of historical buildings and meeting the visual requirements of restored buildings. The paper discusses the visual performance of a traditional bathhouse (Hammam) in the city of Bursa in Turkey. The change in the visual performance of the selected case study will be discussed in terms of daylight conditions. The paper explores the possibility of maintaining the original daylight conditions of renovated historical buildings while meeting the visual requirements of the new use.

Experimental and simulation study of the impact of increased photovoltaic integration with the grid

The abundance, availability, and climate-friendly characteristics of solar photovoltaic (PV) energy encourage nations around the globe to adopt it to assist in overcoming global warming as well as build a sustainable society for the future. The intermittent nature of solar energy generation and the associated power electronic inverters with connected consumer loads creates a number of potential challenges in integrating large-scale PV into the grid that affects power quality of the distribution networks. This paper investigates the impacts of varying PV integration into the grid through experimental and simulation studies. Initially, several experiments were conducted with varying PV penetration and load conditions using the Renewable Energy Integration Facility at CSIRO, Newcastle, Australia. Later, a simulation model was developed that mimics the experimental facility used at CSIRO to investigate the adverse impacts on integrating large-scale PV into the grid using the power system simulation software PSS Sincal. Experimental and simulation analyses clearly indicate that integration of PV into the grid causes power quality issues such as voltage instability, harmonic injection, and low power factor into the networks and the level of these impacts increases with the increase of PV penetration. © 2014 AIP Publishing LLC.

A Framework for the Automation of Discrete-Event Simulation Experiments

Simulation is an important resource for researchers in diverse fields. However, many researchers have found flaws in the methodology of published simulation studies and have described the state of the simulation community as being in a crisis of credibility. This work describes the project of the Simulation Automation Framework for Experiments (SAFE), which addresses the issues that undermine credibility by automating the workflow in the execution of simulation studies. Automation reduces the number of opportunities for users to introduce error in the scientific process thereby improvingthe credibility of the final results. Automation also eases the job of simulation users and allows them to focus on the design of models and the analysis of results rather than on the complexities of the workflow.