Complex numerical weather prediction models incorporate a variety of physical processes, each described by multiple alternative physical schemes with specific parameters. The selection of the physical schemes and the choice of the corresponding physical parameters during model configuration can significantly impact the accuracy of model forecasts. There is no combination of physical schemes that works

This work presents a novel point interpolation algorithm that is derived from a simple weighted linear regression model. The resulting expression is similar to Inverse Distance Weighting (IDW), which is a widely adopted interpolation algorithm. The novel approach is compared to other methods on synthetic data and also over study cases related to solar radiation, surface elevation, well elevation, and

In this paper, we introduce a stable isogeometric analysis discretization of the Stokes system of equations. We use this standard constrained problem to demonstrate the flexibility and robustness of the residual minimization method on dual stable norms [16], which unlocks the extraordinary approximation power of isogeometric analysis [44]. That is, we introduce an isogeometric residual minimization

Column-level segmentation of depth images is an energy-efficient strategy to perform 3D perception in autonomous-driving systems. These systems must perform 3D perception in real time through a pipeline of multiple tasks, which benefits from proposals that prioritize low complexity and short execution time over high levels of accuracy. For many years, column-level segmentation of depth images has been

An advanced arbitrary Lagrangian–Eulerian (ALE) mixed finite element method (FEM) is developed for a cardiovascular fluid–structure interaction (FSI) problem with multiple moving interfaces arising from cardiovascular diseases (CVDs), where the aneurysm on the artery wall and the implanted stent graft are involved as multi-structural domains, interacting with the blood fluid in different regions through

Multisensor data fusion with Dempster–Shafer (D–S) theory is beneficial for context inference without any advanced information. D–S theory includes reasoning based on Dempster’s rule of combination of degrees of belief based on different pieces of evidence. Although, the computational complexity of Dempster’s rule of combination is enormous. Any change in the number of pieces of evidence or hypotheses

Due to computational cost, simulation software is confronted with the need to always use optimal building blocks — data structures, solver algorithms, parallelization schemes, and so forth — in terms of efficiency, while it typically needs to support a variety of hardware architectures. AutoPas implements the computationally most expensive molecular dynamics (MD) steps (e.g., force calculation) and

By extending the work published at ICCS 2020 [1], in this paper we propose a method to achieve cost-effective 3D printing of stiffened thin-shell objects. Our proposed method consists of three parts. The first part integrates finite element analysis, Voronoi diagram, and conformal mapping to obtain stiffener distribution. The second part combines finite element analysis with optimization calculations

The solution of large-scale combustion problems with codes such as Uintah on modern computer architectures requires the use of multithreading and GPUs to achieve performance. Uintah uses a low-Mach number approximation that requires iteratively solving a large system of linear equations. The Hypre iterative solver has solved such systems in a scalable way for Uintah, but the use of OpenMP with Hypre

The efficient solution of large sparse saddle point systems is very important in computational fluid mechanics. The discontinuous Galerkin finite element methods have become increasingly popular for incompressible flow problems but their application is limited due to high computational cost. We describe C++ programming techniques that may help to accelerate linear solvers for such problems. The approach

Stochastic Galerkin methods can be used to approximate the solution to a differential equation in the presence of uncertainties represented as stochastic inputs or parameters. The strategy is to express the resulting stochastic solution using M+1 terms of a polynomial chaos expansion and then derive and solve a deterministic, coupled system of PDEs with standard numerical techniques. Some challenges

Internal logistics systems aim at supplying the right materials at the right locations at the right time. This fact creates the need for the design of logistic-train-fleet-oriented, distributed and scalability-robust control policies ensuring deadlock-free operations. This paper presents a solution to a milk-run vehicle routing and scheduling problem subject to fuzzy pick-up and delivery transportation

Lattice Boltzmann methods are a popular mesoscopic alternative to classical computational fluid dynamics based on the macroscopic equations of continuum mechanics. Many variants of lattice Boltzmann methods have been developed that vary in complexity, accuracy, and computational cost. Extensions are available to simulate multi-phase, multi-component, turbulent, and non-Newtonian flows. In this work

The Direct Simulation Monte Carlo (DSMC) method is used to investigate the gaseous flow of monoatomic Argon in a four-sided lid-driven cavity in all the rarefaction regimes. The influence of wall movement direction and wall velocity magnitude on flow physics is studied. The Knudsen numbers selected are 0.01, 0.1, 1, 10, 20 and the Mach numbers employed are 0.03, 0.17, 0.35, and 0.70 respectively. The

Policy evaluation problems in multi-agent reinforcement learning (MARL) have attracted growing interest recently. In this setting, agents collaborate to learn the value of a given policy with private local rewards and jointly observed state-action pairs. However, existing fully decentralized algorithms treat each agent equally, without considering the communication structure of the agents over a given

Like any other scientific discipline, the High Performance Computing community suffers under the publish or perish paradigm. As a result, a significant portion of novel algorithm designs and hardware-optimized implementations never make it into production code but are instead abandoned once they served the purpose of yielding (another) publication. At the same time, community software packages driving

We enable large-scale high-fidelity finite-element seismic response simulations of important structures, that are expected to contribute towards improvement in seismic design verification, by reducing cost of the nonlinear dynamic unstructured low-order implicit finite-element method. Most of the computational cost of this method is involved in the element-by-element (EBE) method, which is a typical

Swarm intelligence enables simulation and exploration of different phenomena. In this work, it is designed a multiple swarm particles simulation algorithm (MSPSA), based on classical swarm particle interactions extended to a scenario with more than one swarm. It explicitly presents a mathematical and statistical analysis of experimental results. This MSPSA was applied to the simulation of the coffee

The present paper develops a fast method to simulate the solidification structure of continuous billets with Cellular Automaton (CA) model. Traditional solution of the CA model on single CPU takes a long time for the massive datasets and complicated calculations, making it unrealistic to optimize the parameters through numerical simulation. In this paper, a parallel method based on Graphics Processing

Hierarchical zeolites containing both micropores and mesopores are valuable catalysts for facilitating reactions of large molecules. Furan acylation by fatty acids is a promising reaction for valorizing biomass, and the self-pillared pentasil (SPP) zeolite was found to perform particularly well for this reaction. To better understand the distribution of molecules in hierarchical zeolites at the elevated

Using density functional theory in combination with Green's functional formalism we study the quantum transport through molecular junctions containing pyrimidine units characterized by a permanent dipole moment. The presence of the pyrimidine rings results in the enhanced current through the junctions for both polarities of the applied voltage. In addition, these systems show clear current rectification

In this paper, we investigate the demand-flexibility of large-collections of electric vehicles (EVs) by scheduling their demand to flatten the electricity duck curve that emerge as a result of growing solar power production. The scheduling problem is investigated in a bi-objective setting and an additional objective function related to the amount of charge provided to EVs is also analyzed. The first

Performance evaluation is crucial to understanding the behavior of scientific workflows. In this study, we target an emerging type of workflow, called in situ workflows. These workflows tightly couple components such as simulation and analysis to improve overall workflow performance. To understand the tradeoffs of various configurable parameters for coupling these heterogeneous tasks, namely simulation

This paper presents neural network regression models for predicting the nonlinear static and linearized dynamic reaction forces of spiral grooved gas journal bearings. The partial differential equations (PDEs) are sampled, based on a full factorial and randomly spaced parameter set. Feed-forward neural network (FNN) architectures are developed for modeling the PDEs and therefore replacing the time-consuming

Port state control inspection is seen as the safety net to guard marine safety, protect the marine environment, and guarantee decent onboard working and living conditions for seafarers. A substandard ship can be detained in an inspection if serious deficiencies are found onboard. Ship detention is regarded to be a severe result in port state control inspection, however, developing accurate prediction

This paper presents an approach of generation of 3D parallel tiled code implementing an Optimal Binary Search Tree (OBST) algorithm. We demonstrate that the features of data dependences available in the code implementing Knuth's OBST algorithm allow us to generate only 2D tiled code. We suggest a way of transformation of Knuth's OBST algorithm to a modified one exposing dependences allowing us to generate

The alkaline-earth metal hydrides and their corresponding ions are heteronuclear molecules that are essential in many fields especially in astrophysics and spectroscopy such as sunspots, stars, nebulae, the interstellar medium and chemical engineering. They are important systems in spectroscopy due to their visible bands which emerge in the absorption spectrum of sun. Due to the importance of hydride

Effectual allocation of resources with fault tolerance is one of the important targets in any computational grid environment to accomplish the task execution on time. In this paper, a Fault Tolerant Hybrid Resource allocation Model (FTHRM) has been proposed to minimize the turnaround time for the batch of tasks while ensuring fault tolerance in a dynamic grid environment. The model uses the prior reservation

N6-methyladenosine (m6A) modifications are one the most frequently occurring RNA post transcriptional modifications. These modifications perform vital roles in different biological processes, including, localization and translation of proteins, X chromosome inactivation, cell stability, microRNA regulation, and reprogramming etc. Any abnormal change in m6A sites may lead to several abnormalities, including

We propose a physics-informed echo state network (ESN) to predict the evolution of chaotic systems. Compared to conventional ESNs, the physics-informed ESNs are trained to solve supervised learning tasks while ensuring that their predictions do not violate physical laws. This is achieved by introducing an additional loss function during the training, which is based on the system's governing equations

Agent-based modeling is a relatively new approach to model complex systems composed of agents whose behavior is described using simple rules. As a consequence of the agent interactions emerges a complex global behavioral pattern not explicitly programmed. In the last decade, an increasing number of metaheuristic techniques have been reported in the literature where authors claim their novelty and their

Vehicular Ad hoc NETworks (VANET) allow communications between vehicles using their own connection infrastructure. There are several advantages and applications in using this technology and one of most significant is road safety. As in most other networks, it is not only important to guarantee the transport but also the security of information. Security in VANET is a big challenge because there are

In this numerical study, the supersonic combustion of ethylene in three model combustor configurations namely, baseline (no cavity), square cavity and inclined cavity are investigated. To this end, 3D, compressible, turbulent, non-reacting (with fuel injection) and reacting flow calculations using single step and 10-step chemical kinetics in conjunction with a one equation turbulence model have been

High-throughput RNA sequencing technologies (RNA-Seq) have recently started being used as a tool for helping diagnose rare genetic disorders, as they can indicate abnormal gene expression counts — a telltale sign of genetic pathology. Existing solutions either require a large number of samples or do not provide proper statistical significance testing. We present a Bayesian model (OutPyR) for identifying

Privacy is an important issue on any open system, in particular for connected vehicles. These vehicles send continuously messages containing their locations in order to cooperate with their neighbors about what is happening on roads. Privacy protection is highly required to deploy C-ITS (Cooperative Intelligent Transport Systems) in order to avoid tracking drivers. For this reason, vehicles change

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

Based on the forecast of the future prospect of the car network function, the paper analyzes the traffic characteristics of the future networked vehicles and the traffic characteristics of the emergency vehicles in the network environment. Then in order to better investigate the characteristics of Internet of Vehicles, MCD model (into which introduced the brake light) is improved by considering the

We provide a new approach for the efficient matrix-free application of the transpose of the Jacobian for the spectral element method for the adjoint-based solution of partial differential equation (PDE) constrained optimization. This results in optimizations of nonlinear PDEs using explicit integrators where the integration of the adjoint problem is not more expensive than the forward simulation. Solving

The Meta-heuristic algorithm has become an effective solution to global optimization problems. Recently, a new meta-heuristic algorithm called sine-cosine algorithm (SCA) search algorithm is proposed, which uses the characteristics of sine-cosine trigonometric function in mathematical formulas to solve the optimal solution of the problem to be optimized. This paper presents a new variant of the SCA

In this paper, a novel adaptive procedure for step size selection for fractional differential equations is presented. The new adaptive approach is based on the implementation of a single numerical method and uses two numerical approximations, obtained at two successive steps, to advance the computation. We define a step size selection function that allows to adapt the size of the step according to

Mechanisms for remote execution of computational tasks enable a distributed system to effectively utilize all available resources. This ability is essential to attaining the objectives of high availability, system reliability, and graceful degradation and directly contribute to flexibility, adaptability, and incremental growth. As part of a national fabric of Distributed High Throughput Computing (dHTC)

A global-search method which applies the concept of genetic algorithm (GA) with gradient-based optimizer is proposed for the problem of experimental data analysis from spectroscopic ellipsometry on thin films. The method is applied to evaluate the data obtained for samples with different structure complexity, starting with transparent monolayers (SiO2, HfO2) on a substrate, through absorbing film (diamond-like

Increased availability and access to medical image data has enabled more quantitative approaches to clinical diagnosis, prognosis, and treatment planning for congenital heart disease. Here we present an overview of long-term clinical management of congenital heart disease and its intersection with novel computational and data science approaches to discovering biomarkers of functional and prognostic

Each successive generation of computer architecture has brought new challenges to achieving high performance mathematical solvers, necessitating development and analysis of new algorithms, which are then embodied in software libraries. These libraries hide architectural details from applications, allowing them to achieve a level of portability across platforms from desktops to world-class high performance

The Scientific Computing and Imaging (SCI) Institute at the University of Utah evolved from the SCI research group, started in 1994 by Professors Chris Johnson and Rob MacLeod. Over time, research centers funded by the National Institutes of Health, Department of Energy, and State of Utah significantly spurred growth, and SCI became a permanent interdisciplinary research institute in 2000. The SCI

We introduce the steady-state two-relaxation-time (TRT) Lattice Boltzmann method. Owing to the symmetry argument, the bulk system and the closure equations are all expressed in terms of the equilibrium and non-equilibrium unknowns with the half discrete velocity set. The local mass-conservation solvability condition is adjusted to match the stationary, but also the quasi-stationary, solutions of the

High-Performance Computing (HPC) research, from hardware and software to the end applications, provides remarkable computing power to help scientists solve complex problems in science, engineering, or even daily business. Over the last decades, Message Passing Interface (MPI) libraries have been powering numerous scientific applications, such as weather forecasting, earthquake simulations, physic,

A growing gap between progress in biological knowledge and improved health outcomes inspired the new discipline of translational medicine, in which the application of new knowledge is an explicit part of a research plan. Abramson and Parashar argue that a similar gap between complex computational technologies and ever-more-challenging applications demands an analogous discipline of translational computer

Computational geoscience is an established field for better understanding and protecting our planet. It covers a wide range of different fields that are closely related to Earth systems. As a popular research area that largely relies on high performance computing, the efficient translation of novel techniques from computer science to practical geoscience solutions has emerged as an important and challenging

This paper overviews the enablers and phases for translational cyberinfrastructure for data-driven applications. In particular, it summarizes the translational process of and the lessons learned from the development of the NSF WIFIRE cyberinfrastructure. WIFIRE is an end-to-end cyberinfrastructure for real-time data fusion and data-driven simulation, prediction, and visualization of wildfire behavior

Environmental disasters such as flash floods are becoming more and more prevalent and carry an increasing burden to human civilization. They are usually unpredictable, fast in development and extend across large geographical areas. The consequences of such disasters can be reduced through better monitoring, for example using mobile sensing platforms that can give timely and accurate information to

This study is inspired by a challenging dynamic Dial-a-Ride Problem (DARP) encountered in a mobility service operated by the company Padam.1 . Customers ask for a transportation service either in advance or in real-time and get an immediate answer about whether their requests are accepted or rejected. The main goal is to maximize the number of accepted requests during the service while respecting maximum

In this paper, the application of Free Element Method (FREM) is extended to the transient nonlinear heat conduction problems, and the characteristics of anisotropic, heterogeneous, temperature-dependent thermophysical properties and heat generation are also involved. In order to improve the efficiency during the nonlinear iterations, an alternating iteration strategy, FREM-ROM, is proposed, in which

This paper presents the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction

Translational research (TR) has been extensively used in the health science domain, where results from laboratory research are translated to human studies and where evidence-based practices are adopted in real-world settings to reach broad communities. In computer science, much research stops at the result publication and dissemination stage without moving to the evaluation in real settings at scale

Prediction of drug effects on the heart still represents a challenge in drug development, given potential adverse outcomes. Computer modelling and simulations of the human heart offer a powerful technology to augment existing animal and clinical methodologies. Here we describe the translation process that led to the development and uptake of Virtual Assay, a user-friendly software to perform in silico

The MPICH project is an example of translational research in computer science before that term was well known or even coined. The project began in 1992 as an effort to develop a portable, high-performance implementation of the emerging Message-Passing Interface (MPI) Standard. It has enabled the widespread adoption of MPI as a way to write scalable parallel applications on systems of all sizes including

Wireless communication protocols are often used in critical applications, e.g., urban water supply networks or healthcare monitoring within the Internet of Things. It is essential that control software and protocols for such systems are verified to be both robust and reliable. The effects on the hardware caused by environmental conditions and the choice of parameters used by the protocol are among

The notion of stable storage is very important in the area of fault tolerance. We are interested in the implementation of the concept of stable storage in mobile ad hoc environment. In this paper, we present the design and comparison of two solutions for implementing stable storage in mobile ad hoc networks (MANET) environment. One is based on the principle of data replication and the other on the

Small cells is a promising technique to improve the spectral efficiency or quality-of-service (QoS) of a cellular network as it reduces the distance between the user and the base station (MBS). It has been proposed for indoor as well as outdoor users. For the outdoor scenario, the backhaul (the link from a small cell to the core network) of the small cell has always been a challenging issue. Different