Reaction analysis and visualization of ReaxFF molecular dynamics simulations

ReaxFF MD (Reactive Force Field Molecular Dynamics) is a promising method for investigating complex chemical reactions in relatively larger scale molecular systems. The existing analysis tools for ReaxFF MD lack the capability of capturing chemical reactions directly by analyzing the simulation trajectory, which is critical in exploring reaction mechanisms. This paper presents the algorithms, implementation strategies, features, and applications of VARxMD, a tool for Visualization and Analysis of Reactive Molecular Dynamics. VARxMD is dedicated to detailed chemical reaction analysis and visualization from the trajectories obtained in ReaxFF MD simulations. The interrelationships among the atoms, bonds, fragments, species and reactions are analyzed directly from the three-dimensional (3D) coordinates and bond orders of the atoms in a trajectory, which are accomplished by determination of atomic connectivity for recognizing connected molecular fragments, perception of bond types in the connected fragments for molecules or radicals, indexing of all these molecules or radicals (chemical species) based on their 3D coordinates and recognition of bond breaking or forming in the chemical species for reactions. Consequently, detailed chemical reactions taking place between two sampled frames can be generated automatically. VARxMD is the first tool specialized for reaction analysis and visualization in ReaxFF MD simulations. Applications of VARxMD in ReaxFF MD simulations of coal and HDPE (high-density polyethylene) pyrolysis show that VARxMD provides the capabilities in exploring the reaction mechanism in large systems with complex chemical reactions involved that are difficult to access manually.     

Towards more accurate pharmacophore modeling: Multicomplex-based comprehensive pharmacophore map and most-frequent-feature pharmacophore model of CDK2

Pharmacophore modeling, including ligand- and structure-based approaches, has become an important tool in drug discovery. However, the ligand-based method often strongly depends on the training set selection, and the structure-based pharmacophore model is usually created based on apo structures or a single protein-ligand complex, which might miss some important information. In this study, multicomplex-based method has been suggested to generate a comprehensive pharmacophore map of cyclin-dependent kinase 2 (CDK2) based on a collection of 124 crystal structures of human CDK2-inhibitor complex. Our multicomplex-based comprehensive pharmacophore map contains almost all the chemical features important for CDK2-inhibitor interactions. A comparison with previously reported ligand-based pharmacophores has revealed that the ligand-based models are just a subset of our comprehensive map. Furthermore, one most-frequent-feature pharmacophore model consisting of the most frequent pharmacophore features was constructed based on the statistical frequency information provided by the comprehensive map. Validations to the most-frequent-feature model show that it can not only successfully discriminate between known CDK2 inhibitors and the molecules of focused inactive dataset, but also is capable of correctly predicting the activities of a wide variety of CDK2 inhibitors in an external active dataset. Obviously, this investigation provides some new ideas about how to develop a multicomplex-based pharmacophore model that can be used in virtual screening to discover novel potential lead compounds.     

Automating feature model refactoring: A Model transformation approach

Context: Feature model is an appropriate and indispensable tool for modeling similarities and differences among products of the Software Product Line (SPL). It not only exposes the validity of the products’ configurations in an SPL but also changes in the course of time to support new requirements of the SPL. Modifications made on the feature model in the course of time raise a number of issues. Useless enlargements of the feature model, the existence of dead features, and violated constraints in the feature model are some of the key problems that make its maintenance difficult.Objective: The initial approach to dealing with the above-mentioned problems and improving maintainability of the feature model is refactoring. Refactoring modifies software artifacts in a way that their externally visible behavior does not change.Method: We introduce a method for defining refactoring rules and executing them on the feature model. We use the ATL model transformation language to define the refactoring rules. Moreover, we provide an Alloy model to check the feature model and the safety of the refactorings that are performed on it.Results: In this research, we propose a safe framework for refactoring a feature model. This framework enables users to perform automatic and semi-automatic refactoring on the feature model.Conclusions: Automated tool support for refactoring is a key issue for adopting approaches such as utilizing feature models and integrating them into the software development process of companies. In this work, we define some of the important refactoring rules on the feature model and provide tools that enable users to add new rules using the ATL M2M language. Our framework assesses the correctness of the refactorings using the Alloy language.     

A spreadsheet-based macro manpower model

This paper describes the use of spreadsheets as a tool for macro-manpower modeling. The model defines drivers which are “output measures” for an organization. These drivers are quantified for a Base Case and for points in the future. Staffing for the various departments of the organization are defined for the Base Case. Next, estimates are made of the percent effort by department for each driver. The model also includes a number of damping factors which affect reaction of the model to changes in values of the Drivers. The model can also accommodate special features of a particular organization's manpower needs. The model is a menu-driven LOTUS 1-2-3 template which outputs estimated staffing by department, standards associated with each driver, and graphical output. The approach is presented in connection with a specific application at the Naval Training Systems Center in Orlando.     

Turbulent premixed flame model based on a recent dispersion model

A model of turbulent premixed combustion is formulated based on a recent dispersion model and on earlier flame models. The dispersion model accounts for the effect of velocity correlation on turbulent dispersion without using parameters that are explicitly dependent on time or space. The earlier flame models are used as a basis for formulating an appropriate chemical source term. The resulting model is more general than the earlier models.The proposed model and one of the earlier models are validated against various experimental flames. It is shown that the proposed model is more accurate and requires less calibration. Furthermore, the proposed model is tested successfully against general criteria for premixed combustion modeling formulated in earlier works. It is therefore concluded that the dispersion model is a useful tool for premixed combustion modeling.     

APROMORE: An advanced process model repository

Business process models are becoming available in large numbers due to their widespread use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: how can it be ensured that the proper process model is always available to the interested stakeholder? On the other hand, the richness of a large set of process models also offers opportunities, for example with respect to the re-use of existing model parts for new models. This paper describes the functionality and architecture of an advanced process model repository, named APROMORE. This tool brings together a rich set of features for the analysis, management and usage of large sets of process models, drawing from state-of-the art research in the field of process modeling. A prototype of the platform is presented in this paper, demonstrating its feasibility, as well as an outlook on the further development of APROMORE.     

A finite difference model for air pollution simulation

A 3-D model for atmospheric pollutant transport is proposed considering a set of coupled convection–diffusion–reaction equations. The convective phenomenon is mainly produced by a wind field obtained from a 3-D mass consistent model. In particular, the modelling of oxidation and hydrolysis of sulphur and nitrogen oxides released to the surface layer is carried out by using a linear module of chemical reactions. The dry deposition process, represented by the so-called deposition velocity, is introduced as a boundary condition. Moreover, the wet deposition is included in the source term of the governing equations using the washout coefficient. Before obtaining a numerical solution, the problem is transformed using a terrain conformal coordinate system. This allows to work with a simpler domain in order to build a mesh that provides finite difference schemes with high spatial accuracy. The convection–diffusion–reaction equations are solved with a high order accurate time-stepping discretization scheme which is constructed following the technique of Lax and Wendroff. Finally, the model is tested with a numerical experiment in La Palma Island (Canary Islands).     

基于智能集成策略的烧结块残硫软测量模型

针对铅锌冶炼烧结过程烧结块残硫估计问题,提出了一个基于智能集成策略的软测量模型,主要包括数学模型、专家规则模型和智能协调器几部分.其中数学模型通过物料平衡方程计算烧结块残硫,方程中的部分不可解参数由神经网络估计给出.专家规则模型对残硫与主要影响因素之间的关系进行了描述.基于模糊逻辑的智能协调器根据生产条件的情况综合各模型的输出作为估计结果.工业实际数据验证表明,智能集成模型的残硫估计误差平均值仅为7.5%,而且真实反映了烧结块残硫的变化趋势,可以为生产操作提供有益的指导.     

Digital marbling: a multiscale fluid model

This paper presents a multiscale fluid model based on mesoscale dynamics and viscous fluid equations as a generic tool for digital marbling purposes. The model uses an averaging technique on the adaptation of a stochastic mesoscale model to obtain the effect of fluctuations at different levels. It allows various user controls to simulate complex flow behaviors as in traditional marbling techniques, as well as laminar and turbulent flows. Material transport is based on an improved advection solution to be able to match the highly detailed, sharp fluid interfaces in marbling patterns. In the transport model, two reaction models are introduced to create different effects and to simulate density fluctuations.     

A mathematical model for foreign body reactions in 2D

The foreign body reactions are commonly referred to the network of immune and inflammatory reactions of human or animals to foreign objects placed in tissues. They are basic biological processes, and are also highly relevant to bioengineering applications in implants, as fibrotic tissue formations surrounding medical implants have been found to substantially reduce the effectiveness of devices. Despite of intensive research on determining the mechanisms governing such complex responses, few mechanistic mathematical models have been developed to study such foreign body reactions. This study focuses on a kinetics-based predictive tool in order to analyze outcomes of multiple interactive complex reactions of various cells/proteins and biochemical processes and to understand transient behavior during the entire period (up to several months). A computational model in two spatial dimensions is constructed to investigate the time dynamics as well as spatial variation of foreign body reaction kinetics. The simulation results have been consistent with experimental data and the model can facilitate quantitative insights for study of foreign body reaction process in general.     

Introduction of a new platform for parameter estimation of kinetically complex environmental systems

A modeling framework (ReKinSim - Reaction Kinetics Simulator) is introduced, within which biogeochemical reactions in environmental systems can be described and inversely fitted to experimental data. Three key features of this simulation environment are: (1) a generic mathematical tool for solving sets of unlimited, arbitrary, non-linear ordinary differential equations; (2) no limitation to the number or type of reactions or other influential dynamics (e.g., isotope fractionation or small-scale mass-transfer limitations); (3) an easy to use and flexible module for nonlinear data-fitting. It allows users to easily define any kinetic model by a set of biogeochemical reactions relevant to the experimental application and to obtain the values of the kinetic parameters by fitting of the model to data. By allowing users to include the environmentally related processes and solving them along with the chemical kinetics, ReKinSim helps the user to elucidate the extent that these processes are controlled by factors other than kinetics. The novelty of the presented program primary lays in its unique combination of flexibility, computational efficiency and user-friendliness. ReKinSim's usability is showcased by four case studies of varying complexity, and compared against a set of currently available modeling tools.     

An algorithm based on collision theory for the lattice Boltzmann simulation of isothermal mass diffusion with chemical reaction

The lattice Boltzmann method (LBM) provides a framework for the simulation of mass transport and chemical reaction in complex geometries when accurate pointwise mesoscopic-scale solutions are sought. Herein, an algorithm based on collision theory to determine the rate of chemical reaction during the collision step in LBM is proposed. The model is validated against three isothermal problems with simple analytical solutions: a batch reactor with homogeneous chemical reactions of first and second-order and a cylindrical pore with one-dimensional mass diffusion and surface (heterogeneous) chemical reaction. The results of the LBM simulations agree to within 1% when compared to the analytical solutions, presenting a promising opportunity for the simulation of detailed chemical reaction mechanisms.     

含有时间幂次项的灰色预测模型病态特性

为了准确揭示含时间幂次项灰色预测模型的解在系统原始特征序列存在微小扰动下的变化规律,对该模型背景值和时间幂系数在不同取值下的系数矩阵谱条件数值进行分类计算.研究结果表明,一般情况下该模型不存在严重病态性.研究结论认为,在系统建模预测过程中,该模型的预测值不会因系统原始特征序列存在一定误差而产生显著振荡现象.     

A simulation model for risk analysis of toxic chemical storage

With the increasing complexity of chemical plants and the growing public concern for the safe manufacture, transport, and disposal of these chemicals, there exist a need to assist decision-makers in project evaluation with regard to risk.

Extensive work has been done in risk analysis area related to nuclear industry. The amount of research and applications of risk analysis methodology in chemical industry is seriously lacking. Direct application of some of the risk analysis techniques used for nuclear risk studies is not always appropriate to the chemical industry.

The use of simulation models to overcome some of the problems of direct application of probabilistic risk assessment (PRA) methodologies is evaluated in this paper. A simulation model is developed for a toxic chemical storage risk analysis problem. The results of the simulation model are compared to the results of using standard fault tree methodology.     

Exploring airport traffic capability using Petri net based model

The first part of the paper introduces a novel tool for modeling and simulation of discrete event system. This tool called GPenSIM is a Petri net based simulator and offers significant benefits to model builders such as flexibility to include diverse libraries, ease of extending the models, and ease of programming. The second part of the paper presents a case study on modeling and optimization of airport traffic management; this study is to explore air traffic management capability of Evenes airport in Norway. The case study shows that with GPenSIM, modeling and simulation problems of large industrial discrete event systems can be done. Future research directions are discussed as well.     

Application of a Galerkin finite element method to atmospheric transport problems

Numerical simulation of the movement of a contaminant within the atmosphere presents difficulties due to (a) The multi-dimensionality of the problem; (b) The fact that the horizontal transport is usually convection dominated; (c) The boundary conditions are mixed; (d) Both slow and fast atmospheric chemical reactions can be important. In this study, numerical experiments using a Crank-Nicolson Galerkin finite element method to solve the time-dependent partial differential equations demonstrate the applicability and accuracy of this method for the variety of conditions encountered in atmospheric pollutant modeling. The Crank-Nicolson Galerkin method using piecewise linear, piecewise cubic Hermite polynomials, and upwind finite elements is shown to accurately model the pure convection of initial wave forms. Numerical results studying the interactions of convection, diffusion, chemical reaction, pollutant removal, and the effects of contaminant emission source strength, source location and multiple sources are also presented.     

A mathematical model for foreign body reactions in 2D

The foreign body reactions are commonly referred to a network of immune and inflammatory reactions of human or animals in response to foreign objects being placed in tissues. They are basic biological processes, and are also highly relevant to bioengineering applications in implants, as fibrotic tissue formations surrounding medical implants have been found to substantially reduce the effectiveness of devices. Despite the intensive research on determining the mechanisms governing such complex responses, few mechanistic mathematical models have been developed to study such foreign body reactions. This study focuses on a kinetics-based predictive tool to analyse the outcomes of multiple interactive complex reactions of various cells/proteins and biochemical processes and to understand transient behaviour during the entire period (up to several months). A computational model in two spatial dimensions is constructed to investigate the time dynamics as well as the spatial variation of foreign body reaction kinetics. The simulation results have been consistent with the experimental data and the model can facilitate quantitative insights into the study of foreign body reaction process, in general.