Crowd simulation has been widely used as a tool to demonstrate the behavior of passengers on public transport. A simulation model allows researchers to evaluate the platform or interior designs without involving real-world experimentation. In this paper, we propose a passenger model to measure the effect of different public transport vehicle layouts on the required time for boarding and alighting.

The living organism maintains homeostasis despite being a thermodynamically open system in constant interaction with its environment. Only a system which implements automatic control mechanisms can meet these criteria. The negative feedback loop provides a way to implement such mechanisms. While the organism is thermodynamically open, feedback loops active on the level of cells and the organism as

We propose an extension to Boltzmann BGK equation for diatomic gases. The model satisfies the H theorem and accurately recovers the compressible hydrodynamics for a diatomic gas as its macroscopic limit. The collision term is modified to account for the rotational energy and supplemented with an equation representing the evolution of the rotational energy. We demonstrate the accuracy of lattice Boltzmann

We provide a brief survey of our current developments in the simulation-based design of novel families of mesoscale porous materials using computational kinetic theory. Prospective applications on exascale computers are also briefly discussed and commented on, with reference to two specific examples of soft mesoscale materials: microfluid crystals and bi-continuous jels.

Diabetes is a metabolic disease characterized by persistent hyperglycemia, which results in serious complications such as cardiovascular disorder, neuropathy, renal failure, and retinopathy. Various anti-diabetic drugs have been developed, however, their therapeutic effect is far from satisfactory. Therefore, increasing attention has been paid to natural products, whose multi-targets characteristics

Rayleigh-Bénard convection (RBC) with anisotropic thermal diffusion inside a cylindrical cavity is investigated using the axisymmetric thermal-lattice Boltzmann method with MRT collisions. The axisymmetric approach for cylindrical geometries reduces the overall computational requirements, however, is valid for a certain range of governing non-dimensional number, here the Rayleigh number. The D2Q9 model

Hurricane evacuation is a complex dynamic process and a better understanding of the factors which influence the evacuation behavior of the coastal residents could be helpful in planning a better evacuation policy. Traditionally, the various aspects of the household evacuation decisions have been determined by post-evacuation questionnaire surveys, however, these surveys have seen a deterioration in

HIV-1 is a widespread type of the human immunodeficiency virus (HIV) which causes immune system failure. Recently, researchers found that stem cell (SC) therapy can reduce the risks associated with HIV and improve the patient's life. This article presents a mathematical model of SC therapy for the HIV-1 infection. Global stability at the endemic equilibrium point of the model is proven. Numerical solutions

The conventional lattice Boltzmann method is restricted to Cartesian grids, making it remarkably expensive for capturing thin boundary layers, and therefore impractical for most relevant problems in aerodynamics. In this paper, a finite difference approach is taken to solve the discrete-velocity Boltzmann equation in generalised curvilinear coordinates to perform fluid flow simulations with non-uniform

Acceleration of the element-by-element (EBE) kernel in matrix-vector products is essential for high-performance in unstructured implicit finite-element applications. However, the EBE kernel is not straightforward to attain high performance due to random data access with data recurrence. In this paper, we develop methods to circumvent these data races for high performance on many-core CPU architectures

The application of the optimisation problems in the daily decisions of companies is able to be used for finding the best management according to the necessities of the organisations. However, optimisation problems imply a high computational complexity, increased by the current necessity to include a massive quantity of data (Big Data), for the creation of optimisation problems to customise products

This paper introduces two new combinatorial optimization problems involving strings, namely, the Chain Alignment Problem, and a multiple version of it, the Multiple Chain Alignment Problem. For the first problem, a polynomial-time algorithm using dynamic programming is presented, and for the second one, a proof of its NP-hardness and in approximability are provided, jointly with the main ideas of three

The understanding and prediction of large wildland fire events around the world is a growing interdisciplinary research area advanced rapidly by development and use of computational models. Recent models bidirectionally couple computational fluid dynamics models including weather prediction models with modules containing algorithms representing fire spread and heat release, simulating fire-atmosphere

We present a D3Q19 lattice scheme based in MRT with central moments (MRT-CM), where the free parameters of the model are optimized to dissipate under-resolved flow structures with high wavenumbers. In Chávez-Modena et al. in Computers & Fluids 172:397-409, 2018 [1], we compared the BGK, MRT-RM and MRT-CM for the D2Q9 lattice scheme using von Neumann analyses and quantified their numerical properties

The deformation and dynamics of a single droplet in isotropic turbulence is studied using a Lattice Boltzmann diffuse interface model involving exact boundary flow conditions [1] to allow for the creation of an external turbulent flow. We focus on a small, sub-Kolmogorov droplet, whose scale is much smaller than the Kolmogorov length scale of the turbulent flow. The external flow field is obtained

A computational fluid dynamics code is differentiated using algorithmic differentiation (AD) in both tangent and adjoint modes. The two novelties of the present approach are (1) the adjoint code is obtained by letting the AD tool Tapenade invert the complete layer of message passing interface (MPI) communications, and (2) the adjoint code integrates time-dependent, non-linear and dissipative (hence

Web service orchestrations aim at offering value-added services that meet the increasing complex requirements of business processes. Since it becomes harder to manually check the correctness of such systems, we propose a formal method for their consistency checking by first translating OWL-S composite services and WS-BPEL orchestrator into communicating automata using an iterative process driven by

Computing grids are key enablers of computational science. Researchers from many fields (High Energy Physics, Bioinformatics, Climatology, etc.) employ grids for execution of distributed computational jobs. These computing workloads are typically data-intensive. The current state of the art approach for data access in grids is data placement: a job is scheduled to run at a specific data center, and

In this contribution, we study a stability notion for a fundamental linear one-dimensional lattice Boltzmann scheme, this notion being related to the maximum principle. We seek to characterize the parameters of the scheme that guarantee the preservation of the non-negativity of the particle distribution functions. In the context of the relative velocity schemes, we derive necessary and sufficient conditions

Understanding the impact of sea level rise on coastal areas is crucial as a large percentage of the population live on the coast. This study uses computational tools to examine how two major consequences of sea level rise: salt intrusion and an increase in water volume affect the hydrodynamics and flooding areas of a major estuary in the Iberian Peninsula. A 2D numerical model created with the software

In this work we discuss the coupling of two mesoscopic approaches for fluid dynamics, namely the lattice Boltzmann method (LB) and the multiparticle collision dynamics (MPCD) [20] to design a new class of flexible and efficient multiscale schemes based on a dual representation of the fluid observables. At variance with other commonly used multigrid methods, mostly oriented to high Reynolds and turbulent

The paper is devoted to the analysis of two parametric explicit finite-difference schemes for the linear advection equations, considered on the advection step of the splitting algorithm of the finite-difference-based single-relaxation-time lattice Boltzmann method. The schemes are constructed by the approximation of the terms with the spatial derivatives at the characteristic directions. It is demonstrated

The unprecedented increase in the number of smart connected devices invoked a plethora of diverse applications with different performance requirements stipulating various network management strategies. Ultra-reliable low-latency communication (URLLC), one of the promised 5G dimensions, is expected to enable mission-critical applications while adhering to the heterogeneity of their quality metrics.

A novel method, based on the combination of data assimilation and machine learning is introduced. The new hybrid approach is designed for a two-fold scope: (i) emulating hidden, possibly chaotic, dynamics and (ii) predicting their future states. The method consists in applying iteratively a data assimilation step, here an ensemble Kalman filter, and a neural network. Data assimilation is used to optimally

This paper presents six degrees of freedom flight simulation with mode conversion between airplane mode and helicopter mode as an application for realizing Digital Flight of the tiltrotor aircraft. The tiltrotor aircraft has the characteristics of both helicopters and propeller planes with changing the flight mode by tilting the engine nacelles. However, much less work with continuously changing these

In this paper we model influenza propagation in the Russian setting using a spatially explicit model and a detailed human agent database as its input. The aim of our research is to assess the applicability of this modeling method using influenza incidence data for the 2010–2011 epidemic outbreak in Saint Petersburg, and to demonstrate the influence of human contact patterns on the simulated influenza

The purpose of this study is to evaluate the main aspects of the mesoscale ocean circulation of the Brazilian Equatorial Margin using a ten-year hydrodynamic hindcast that successfully represented in situ and satellite observational data. The seasonality and distribution of the Amazon River Plume (ARP), as well as the volume transport of the North Brazil Current (NBC) in two cross-current sections

In our daily life, we are always facing decision making problems with different complexities and requirements. Therefore, the need to design new theories, methods and tools to solve these kinds of problems, as efficiently as possible, becomes a real challenge. In the current research, we deal with decision problems wherein value constraints are expressed on the performance ratings of the alternatives

Simultaneous occurrences of events have been a crucial and hard problem since the beginning of the research about automaton and simulation theories of discrete event systems, for more than 50 years. This article addresses some diagnosis problems in industrial processes, situations such as simultaneity of events, false positives, and partial recognition of event sequences. V-nets are presented as a

Lattice differential operators are known to preserve key properties of their analytical counterpart, such as isotropy, fundamental vector identities due to the symmetries of the discrete kinetic lattice. Here, we present the idea of discrete lattice operators derived on a body-centered-cubic (BCC) lattice. These operators show quite a high degree of accuracy and isotropy as compared to the earlier

The phenomenon of explosive synchronization, which originates from hypersensitivity to small perturbation caused by some form of frustration prevailed in various physical and biological systems, has been shown to lead events of cascading failure of the power grid to chronic pain or epileptic seizure in the brain. Furthermore, networks provide a powerful model to understand and predict the properties

Large-scale simulations of blood flow that resolve the 3D deformation of each comprising cell are increasingly popular owing to algorithmic developments in conjunction with advances in compute capability. Among different approaches for modeling cell-resolved hemodynamics, fluid structure interaction (FSI) algorithms based on the immersed boundary method are frequently employed for coupling separate

While distributed computing infrastructures can provide infrastructure-level techniques for managing energy consumption, application-level energy consumption models have also been developed to support energy-efficient scheduling and resource provisioning algorithms. In this work, we analyze the accuracy of a widely-used application-level model that has been developed and used in the context of scientific

This paper proposes a novel optimization algorithm, called Diffusion Algorithm Based on P Systems (DAPS), for continuous global optimization. This algorithm utilizes four different search strategies and a P system to explore the search space and find the global minima. These search strategies mimic the diffusion phenomena and a hybrid membrane structure inspired by chloroplasts and mitochondria is

Cryptocurrencies have become a prominent investment tool recently with increasing interest in them and their relationships with stock and foreign exchange markets. We analyze here the cross-correlations of price changes of different cryptocurrencies using Random Matrix Theory and extract community structures by constructing minimum spanning trees, finding their eigenvalues contrast sharply with universal

Since Shahshahani and Landgrebe published their seminal paper (Shahshahani and Landgrebe, 1994) [1] in 1994, the study on semi-supervised learning (SSL) developed fast and has already become one of the main streams of machine learning (ML) research. However, there are still some areas or problems where the capability of SSL remains seriously limited. Firstly, according to our observation, almost all

One of the key ideas in realizing human-like intelligence is to understand enough information-processing mechanisms in the human brain. Brain Informatics is a rapidly expanding interdisciplinary field to systematically utilize brain-related data, information, and knowledge coming from the entire research process for deeply brain investigation. In the past few years, a data-centric conceptual brain

We address multiple aspects of the numerical modeling of turbulence and mixing. Fundamental issues of thermodynamics related to nonuniqueness of solutions of the fluid Euler are addressed here. Recent developments of Front Tracking, a part of this analysis, is reviewed as well. The work presented is the result of multiple collaboration teams, and includes in some cases announcements of results yet

We address the link between the controllability or observability of a stochastic complex system and concepts of information theory. We show that the most influential degrees of freedom can be detected without acting on the system, by measuring the time-delayed multi-information. Numerical and analytical results support this claim, which is developed in the case of a simple stochastic model on a graph

We develop a spatio-temporal model to forecast sensor output at five locations in North East England. The signal is described using coupled dynamic linear models, with spatial effects specified by a Gaussian process. Data streams are analysed using a stochastic algorithm, known as iterated batch importance sampling (IBIS), which sequentially propagates a discrete approximation of the parameter posterior

Portfolio allocation and risk management make use of correlation matrices and heavily rely on the choice of a proper correlation matrix to be used. In this regard, one important question is related to the choice of the proper sample period to be used to estimate a stable correlation matrix. This paper addresses this question and proposes a new methodology to estimate the correlation matrix which doesn’t

Deterministic equivalent models reformulate optimization problems from a computational perspective. Nonetheless, these models become computationally intractable quickly when the number of stages increase. In this context, a framework to reduce the size of scenario tree and multistage stochastic optimization problems is proposed. Scenario trees are generated using the Knuth transformation for a more

For a considerable time, researchers have focused on defining different measures capable to characterizing the importance of vertices in networks. One type of these networks, the cities, are complex systems that generate large quantity of information. These data are an important part of the characteristics of the urban network itself. Because of this, it is crucial to have a classification system,

Cardiovascular disease (CVD) affects more than 90 million adults in the United States. In recent years, computational hemodynamic models have helped improve our understanding of CVD progression; however, such research workflows can be challenging and unintuitive to operate. We thus developed Harvis, a software platform with a flexible GUI for performing vascular simulations and a VR-capable interface

We study the diffusivity of a small particle immersed in a square box filled with a non-ideal multicomponent fluid in the presence of thermal fluctuations. Our approach is based on the numerical integration of fluctuating lattice Boltzmann models (LBM) for multicomponent mixtures. At changing the wettability on the particle's surface, we measure the mean square displacement (MSD) and compare with the

The gravitational force has been considered as one of the most important factors leading to composition variation of multicomponent chemical species mixture in many industrial processes and natural phenomena. This has been largely studied through experimental and numerical modeling, especially in chemical processes and petroleum reservoir engineering. The modeling and simulation of dynamical process

Network dismantling aims to find the minimal set of nodes that, if removed, will break the network into small components with their largest one limited to a certain threshold. This problem underlies many practical applications in various areas, such as bioinformatics, transportation and the Internet. There are two major kinds of network dismantling methods, i.e. centrality measure based methods and

In this paper, a new traffic model is presented which characterizes spatial changes in traffic density to smoothly align the traffic flow with forward conditions. This alignment is a function of the difference in velocities so there is no change in flow when the velocities are the same. The commonly employed Payne-Witham (PW) model aligns traffic with a constant speed (velocity) regardless of the transitions

This paper investigates the behavior and synchronization of a network of reaction–diffusion neural dynamics models using a highly efficient numerical method. In fact, the dynamical modeling, behavior analysis and controlled synchronization of a network of FitzHugh–Nagumo (FHN) neurons which promising the understanding of cognitive processing are studied by considering the unidirectional gap junctions

Molecular dynamics (MD) simulations accelerated by high-performance computing (HPC) methods are powerful tools to investigate and extract the microscopic mechanisms characterizing the properties of soft materials such as self-assembled nanoparticles, virus capsids, confined electrolytes, and polymeric fluids. In this paper, we extend the idea developed in our earlier work of integrating machine learning

We present a Weak Constraint Gaussian Process (WCGP) model to integrate noisy inputs into the classical Gaussian Process (GP) predictive distribution. This model follows a Data Assimilation approach (i.e. by considering information provided by observed values of a noisy input in a time window). Due to the increased number of states processed from real applications and the time complexity of GP algorithms

Chip multicore processors (CMPs) constitute the architecture of choice for a wide spectrum of computing systems, ranging from power-efficient mobile devices to high-performance server platforms. Despite their benefits, the contention that appears when multiple applications compete for the use of shared resources among cores, such as the last-level cache (LLC), may lead to substantial performance degradation

The instance of the epistemic uncertainty quantification concerning the estimation of the approximation error norm is analyzed using the ensemble of numerical solutions obtained via independent numerical algorithms. The analysis is based on the geometry considerations: the triangle inequality and the diameter of the ensemble related with the measure concentration phenomenon in spaces of great dimension

Optimisation problems usually take the form of having a single or multiple objectives with a set of constraints. The model itself concerns a single problem for which the best possible solution is sought. Problems are usually static in the sense that they do not consider changes over time in a cumulative manner. Dynamic optimisation problems to incorporate changes. However, these are memoryless in that

Many believe that the future of innovation lies in simulation. However, as computers are becoming ever more powerful, so does the hyperbole used to discuss their potential in modelling across a vast range of domains, from subatomic physics to chemistry, climate science, epidemiology, economics and cosmology. As we are about to enter the era of quantum and exascale computing, machine learning and artificial

Many problems in science and engineering can be formulated as optimization problems, subject to complex nonlinear constraints. The solutions of highly nonlinear problems usually require sophisticated optimization algorithms, and traditional algorithms may struggle to deal with such problems. A current trend is to use nature-inspired algorithms due to their flexibility and effectiveness. However, there

We discuss how computational data science and agent-based modeling, are shedding new light on the age-old issue of human conflict. While social science approaches focus on individual cases, the recent proliferation of empirical data and complex systems thinking has opened up a computational approach based on identifying common statistical patterns and building generative but minimal agent-based models

This paper presents tackling of a hard optimization problem of computational linguistics, specifically automatic multi-document text summarization, using grid computing. The main challenge of multi-document summarization is to extract the most relevant and unique information effectively and efficiently from a set of topic-related documents, constrained to a specified length. In the Big Data/Text era

This paper tackles the slowness issue of the well-known expectation-maximization (EM) algorithm in the context of Gaussian mixture models. To cope with this slowness problem, an Exact Line Search scheme is proposed. It is based on exact computation of the step size required to jump, for a given search direction, towards the final solution. Computing this exact step size is easily done by only rooting

Electrophoreticdeposition (EPD) coating is one of the key processes in automotive manufacturing. Here, car bodies are moved through a tank of paint in which electrically charged paint particles lead to a successive increase of the paint film thickness on the car body. This paint film is used to protect the car body from corrosion. However, in order to properly protect the car body from corrosion, it