Computer Science - Computational Engineering; Finance; and Science Publications (50)


Computer Science - Computational Engineering; Finance; and Science Publications

Transmission lines are vital components in power systems. Tripping of transmission lines caused by over-temperature is a major threat to the security of system operations, so it is necessary to efficiently simulate line temperature under both normal operation conditions and foreseen fault conditions. Existing methods based on thermal-steady-state analyses cannot reflect transient temperature evolution, and thus cannot provide timing information needed for taking remedial actions. Read More

A finite element method simulation of a carbon fibre reinforced polymer block is used to analyse the nonlinearities arising from a contacting delamination gap inside the material. The ultrasonic signal is amplified and nonlinearities are analysed by delayed Time Reversal -- Nonlinear Elastic Wave Spectroscopy signal processing method. This signal processing method allows to focus the wave energy onto the receiving transducer and to modify the focused wave shape, allowing to use several different methods, including pulse inversion, for detecting the nonlinear signature of the damage. Read More

In simulation of fluid injection in fractured geothermal reservoirs, the characteristics of the physical processes are severely affected by the local occurence of connected fractures. To resolve these structurally dominated processes, there is a need to develop discretization strategies that also limit computational effort. In this paper we present an upscaling methodology for geothermal heat transport with fractures represented explicitly in the computational grid. Read More

Computations have helped elucidate the dynamics of Earth's mantle for several decades already. The numerical methods that underlie these simulations have greatly evolved within this time span, and today include dynamically changing and adaptively refined meshes, sophisticated and efficient solvers, and parallelization to large clusters of computers. At the same time, many of these methods -- discussed in detail in a previous paper in this series -- were developed and tested primarily using model problems that lack many of the complexities that are common to the realistic models our community wants to solve today. Read More

The direct numerical simulation of particulate systems offers a unique approach to study the dynamics of fluid-solid suspensions by fully resolving the submerged particles and without introducing empirical models. For the lattice Boltzmann method, different variants exist to incorporate the fluid-particle interaction into the simulation. This paper provides a detailed and systematic comparison of two different methods, namely the momentum exchange method and the partially saturated cells method by Noble and Torczynski. Read More

This paper proposes a new convex model predictive control strategy for dynamic optimal power flow between battery energy storage systems distributed in an AC microgrid. The proposed control strategy uses a new problem formulation, based on a linear d-q reference frame voltage-current model and linearised power flow approximations. This allows the optimal power flows to be solved as a convex optimisation problem, for which fast and robust solvers exist. Read More

Groups of Small and Medium Enterprises (SME) back each other and form guarantee network to obtain loan from banks. The risk over the networked enterprises may cause significant contagious damage. To dissolve such risks, we propose a hybrid feature representation, which is feeded into a gradient boosting model for credit risk assessment of guarantee network. Read More

Molecular Dynamics is an important tool for computational biologists, chemists, and materials scientists, consuming a sizable amount of supercomputing resources. Many of the investigated systems contain charged particles, which can only be simulated accurately using a long-range solver, such as PPPM. We extend the popular LAMMPS molecular dynamics code with an implementation of PPPM particularly suitable for the second generation Intel Xeon Phi. Read More

We adapt and extend a formulation for soluble surfactant transport in multiphase flows recently presented by Muradoglu & Tryggvason (JCP 274 (2014) 737-757) to the context of the Level Contour Reconstruction Method (Shin et al. IJNMF 60 (2009) 753-778) which is a hybrid method that combines the advantages of the Front-tracking and Level Set methods. Particularly close attention is paid to the formulation and numerical implementation of the surface gradients of surfactant concentration and surface tension. Read More

Three complementary methods have been implemented in the code Denovo that accelerate neutral particle transport calculations with methods that use leadership-class computers fully and effectively: a multigroup block (MG) Krylov solver, a Rayleigh quotient iteration (RQI) eigenvalue solver, and a multigrid in energy preconditioner. The multigroup Krylov solver converges more quickly than Gauss Seidel and enables energy decomposition such that Denovo can scale to hundreds of thousands of cores. The new multigrid in energy preconditioner reduces iteration count for many problem types and takes advantage of the new energy decomposition such that it can scale efficiently. Read More

Volatility prediction--an essential concept in financial markets--has recently been addressed using sentiment analysis methods. We investigate the sentiment of annual disclosures of companies in stock markets to forecast volatility. We specifically explore the use of recent Information Retrieval (IR) term weighting models that are effectively extended by related terms using word embeddings. Read More

Breathing signal monitoring can provide important clues for human's physical health problems. Comparing to existing techniques that require wearable devices and special equipment, a more desirable approach is to provide contact-free and long-term breathing rate monitoring by exploiting wireless signals. In this paper, we propose TensorBeat, a system to employ channel state information (CSI) phase difference data to intelligently estimate breathing rates for multiple persons with commodity WiFi devices. Read More

This paper proposes a method of real-time voltage stability assessment for load areas, in which the proximity to voltage collapse point at each bus can be accurately evaluated. Based on the non-iterative holomorphic embedding method (HEM), the voltage of each bus for different loading levels in the load area is quickly screened out by only performing one-time power flow calculation. A power series derived by the HEM with a physical germ solution makes sure that the P-V curve is in conformity with that from conventional continuous power flow. Read More

In this paper, we propose an optimized field/circuit coupling approach for the simulation of magnetothermal transients in superconducting magnets. The approach improves the convergence of the iterative coupling scheme between a magnetothermal partial differential model and an electrical lumped-element circuit. Such a multi-physics, multi-rate and multi-scale problem requires a consistent formulation and a dedicated framework to tackle the challenging transient effects occurring at both circuit and magnet level during normal operation and in case of faults. Read More

In this paper we propose an anisotropic extension of the isotropic exponentiated Hencky en- ergy, based on logarithmic strain invariants. Unlike other elastic formulations, the isotropic exponentiated Hencky elastic energy has been derived solely on differential geometric grounds, involving the geodesic distance of the deformation gradient F to the group of rotations. We formally extend this approach towards anisotropy by defining additional anisotropic logarith- mic strain invariants with the help of suitable structural tensors and consider our findings for biomechanical applications. Read More

This paper presents a new adaptive multiscale homogenization scheme for the simulation of damage and fracture in concrete structures. A two-scale homogenization method, coupling meso-scale discrete particle models to macro- scale finite element models, is formulated into an adaptive framework. A continuum multiaxial failure criterion for concrete is calibrated on the basis of fine-scale simulations, and it serves as the adaptive criterion in the multiscale framework. Read More

In this paper, several rigorous numerical simulations were conducted to examine the relevance of mean-field micromechanical models compared to the Fast Fourier Transform full-field computation by considering spherical or ellipsoidal inclusions. To be more general, the numerical study was extended to a mixture of different kind of microstructures consisting of spheroidal shapes within the same RVE. Although the Fast Fourier Transform full field calculation is sensitive to high contrasts, calculation time, for a combination of complex microstructures, remains reasonable compared with those obtained with mean-field micromechanical models. Read More

A novel adaptive local surface refinement technique based on Locally Refined Non-Uniform Rational B-Splines (LR NURBS) is presented. LR NURBS can model complex geometries exactly and are the rational extension of LR B-splines. The local representation of the parameter space overcomes the drawback of non-existent local refinement in standard NURBS-based isogeometric analysis. Read More

Capacitive deionization (CDI) is a fast-emerging water desalination technology in which a small cell voltage of ~1 V across porous carbon electrodes removes salt from feedwaters via electrosorption. In flow-through electrode (FTE) CDI cell architecture, feedwater is pumped through macropores or laser perforated channels in porous electrodes, enabling highly compact cells with parallel flow and electric field, as well as rapid salt removal. We here present a one-dimensional model describing water desalination by FTE CDI, and a comparison to data from a custom-built experimental cell. Read More

This paper presents our work on developing parallel computational methods for two-phase flow on modern parallel computers, where techniques for linear solvers and nonlinear methods are studied and the standard and inexact Newton methods are investigated. A multi-stage preconditioner for two-phase flow is applied and advanced matrix processing strategies are studied. A local reordering method is developed to speed the solution of linear systems. Read More

Classical Density Functional Theory (DFT) is a statistical-mechanical framework to analyze fluids, which accounts for nanoscale fluid inhomogeneities and non-local intermolecular interactions. DFT can be applied to a wide range of interfacial phenomena, as well as problems in adsorption, colloidal science and phase transitions in fluids. Typical DFT equations are highly non-linear, stiff and contain several convolution terms. Read More

Implicit schemes have been extensively used in building physics to compute the solution of moisture diffusion problems in porous materials for improving stability conditions. Nevertheless, these schemes require important sub-iterations when treating non-linear problems. To overcome this disadvantage, this paper explores the use of improved explicit schemes, such as Dufort-Frankel, Crank-Nicolson and hyperbolisation approaches. Read More

Recent results on supercomputers show that beyond 65K cores, the efficiency of molecular dynamics simulations of interfacial systems decreases significantly. In this paper, we introduce a dynamic cutoff method (DCM) for interfacial systems of arbitrarily large size. The idea consists in adopting a cutoff-based method in which the cutoff is cho- sen on a particle-by-particle basis, according to the distance from the interface. Read More

This book addresses the scientific domains of operations research, information science and statistics with a focus on engineering applications. The purpose of this book is to report on the implications of the loop equations formulation of the state estimation procedure of the network systems, for the purpose of the implementation of Decision Support (DS) systems for the operational control of the network systems. In general an operational DS comprises a series of standalone applications from which the mathematical modeling and simulation of the distribution systems and the managing of the uncertainty in the decision-making process are essential in order to obtain efficient control and monitoring of the distribution systems. Read More

This article provides an introduction to and review of the field of computer-aided molecular design (CAMD). It is intended to be approachable for the absolute beginner as well as useful to the seasoned CAMD practitioner. We begin by discussing various quantitative structure-property relationships (QSPRs) which have been demonstrated to work well with CAMD problems. Read More

In this paper a procedure for the static identification and reconstruction of concentrated damage distribution in beam-like structures, implemented in a dedicated software, is presented. The proposed damage identification strategy relies on the solution of an optimisation problem, by means of a genetic algorithm, which exploits the closed form solution based on the distribution theory of multi-cracked beams subjected to static loads. Precisely, the adoption of the latter closed-form solution allows a straightforward evolution of an initial random population of chromosomes, representing different damage distributions along the beam axis, towards the fittest and selected as the sought solution. Read More

Bound-to-Bound Data Collaboration (B2BDC) provides a natural framework for addressing both forward and inverse uncertainty quantification problems. In this approach, QOI (quantity of interest) models are constrained by related experimental observations with interval uncertainty. A collection of such models and observations is termed a dataset and carves out a feasible region in the parameter space. Read More

We are concerned with finite element modeling of geometrically non-linear laminated glass beams consisting of stiff elastic glass layers connected with compliant polymeric interlayer of temperature-sensitive viscoelastic behavior. In particular, four layerwise theories are introduced in this paper, which differ in the non-linear beam formulation used at the layer level (von K\'{a}rm\'{a}n/Reissner) and in constitutive assumptions used for interlayer (viscoelastic solid with time-independent bulk modulus/Poisson ratio). We show that all formulations deliver practically identical responses for simply-supported and fixed-end three-layer beams. Read More

In this paper, we study a day ahead double energy auction in a distribution system involving dispatchable generation units, renewable generation units supported by battery storage systems(BSSs), fixed loads, price responsive loads, and supply from the Whole Sale Market(WSM) at Locational Marginal Price(LMP). The auction is implemented within a Distribution System Operator (DSO) premises using Mixed Integer Linear Programming (MIP). The proposed auction is cleared at the Distribution LMP (DLMP) and is observed to be weakly budget balanced if no penalty is applied for DSO's deviation from originally committed supply from the WSM. Read More

This paper presents a novel algorithm for uncertainty quantification of water distribution system measurement data including nodal demands/consumptions as well as real pressure and flow measurements. This procedure, referred to as Confidence Limit Analysis (CLA), is concerned with a deployment of a Least Squares (LS) state estimator based on the loop corrective flows and the variation of nodal demands as independent variables. The confidence limits obtained for the nodal pressures and the inflows/outflows of a water network are determined with the novel algorithm called Error Maximization (EM) method and are evaluated with respect to two other more established CLA algorithms based on an Experimental Sensitivity Matrix (ESM) and on the sensitivity matrix method obtained with the LS nodal heads equations state estimator. Read More

For time integration of transient eddy current problems commonly implicit time integration methods are used, where in every time step one or several nonlinear systems of equations have to be linearized with the Newton-Raphson method due to ferromagnetic materials involved. In this paper, a generalized Schur-complement is applied to the magnetic vector potential formulation, which converts a differential-algebraic equation system of index 1 into a system of ordinary differential equations (ODE) with reduced stiffness. For the time integration of this ODE system of equations, the explicit Euler method is applied. Read More

We present OpenRBC, a coarse-grained molecular dynamics code, which is capable of performing an unprecedented in silico experiment --- simulating an entire mammal red blood cell lipid bilayer and cytoskeleton as modeled by 4 million mesoscopic particles --- using a single shared memory commodity workstation. To achieve this, we invented an adaptive spatial-searching algorithm to accelerate the computation of short-range pairwise interactions in an extremely sparse 3D space. The algorithm is based on a Voronoi partitioning of the point cloud of coarse-grained particles, and is continuously updated over the course of the simulation. Read More

This paper presents several test cases intended to be benchmarks for numerical schemes for single-phase fluid flow in fractured porous media. A number of solution strategies are compared, including a vertex and a cell-centered finite volume method, a non-conforming embedded discrete fracture model, a primal and a dual extended finite element formulation, and a mortar discrete fracture model. The proposed benchmarks test the schemes by increasing the difficulties in terms of network geometry, e. Read More

The paper derives and analyses the (semi-)discrete dispersion relation of the Parareal parallel-in-time integration method. It investigates Parareal's wave propagation characteristics with the aim to better understand what causes the well documented stability problems for hyperbolic equations. The analysis shows that the instability is caused by convergence of the amplification factor to the exact value from above for medium to high wave numbers. Read More

A high-resolution finite volume method approach to incorporating time-dependent slip across rectangular subfaults when modeling general fault geometry is presented. The fault slip is induced by a modification of the Riemann problem to the linear elasticity equations across cell interfaces aligned with the subfaults. This is illustrated in the context of the high-resolution wave-propagation algorithms that are implemented in the open source Clawpack software (www. Read More

Here, we present the concept of an open virtual prototyping framework for maritime systems and operations that enables its users to develop re-usable component or subsystem models, and combine them in full-system simulations for prototyping, verification, training, and performance studies. This framework consists of a set of guidelines for model coupling, high-level and low-level coupling interfaces to guarantee interoperability, a full-system simulation software, and example models and demonstrators. We discuss the requirements for such a framework, address the challenges and the possibilities in fulfilling them, and aim to give a list of best practices for modular and efficient virtual prototyping and full-system simulation. Read More

A review of the properties that bond the particles under Lennard Jones Potential allow to states properties and conditions for building evolutive algorithms using the CB lattice with other different lattices. The new lattice is called CB lattice and it is based on small cubes. A set of propositions states convergence and optimal conditions over the CB lattice for an evolutionary algorithm. Read More

Motif finding in DNA, RNA and proteins plays an important role in life science research. Recent patents concerning motif finding in the biomolecular data are recorded in the DNA Patent Database which serves as a resource for policy makers and members of the general public interested in fields like genomics, genetics and biotechnology. In this paper we present a computational approach to mining for RNA tertiary motifs in genomic sequences. Read More

This report describes the computation of gradients by algorithmic differentiation for statistically optimum beamforming operations. Especially the derivation of complex-valued functions is a key component of this approach. Therefore the real-valued algorithmic differentiation is extended via the complex-valued chain rule. Read More

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, or migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. Read More

This paper presents a non-parametric approach for segmenting trees from airborne LiDAR data in deciduous forests. Based on the LiDAR point cloud, the approach collects crown information such as steepness and height on-the-fly to delineate crown boundaries, and most importantly, does not require a priori assumptions of crown shape and size. The approach segments trees iteratively starting from the tallest within a given area to the smallest until all trees have been segmented. Read More

This paper presents a distributed approach that scales up to segment tree crowns within a LiDAR point cloud representing an arbitrarily large forested area. The approach uses a single-processor tree segmentation algorithm as a building block in order to process the data delivered in the shape of tiles in parallel. The distributed processing is performed in a master-slave manner, in which the master maintains the global map of the tiles and coordinates the slaves that segment tree crowns within and across the boundaries of the tiles. Read More

Airborne LiDAR point cloud of a forest contains three dimensional data, from which vertical stand structure (including information about under-story trees) can be derived. This paper presents a segmentation approach for multi-story stands that strips the point cloud to its canopy layers, identifies individual tree segments within each layer using a DSM-based tree identification method as a building block, and combines the segments of immediate layers in order to fix potential over-segmentation of tree crowns across the layers. We introduce local layering that analyzes the vertical distributions of LiDAR points within their local neighborhoods in order to locally determine the height thresholds for layering the canopy. Read More

Electro-quasistatic field problems involving nonlinear materials are commonly discretized in space using finite elements. In this paper, it is proposed to solve the resulting system of ordinary differential equations by an explicit Runge-Kutta-Chebyshev time-integration scheme. This mitigates the need for Newton-Raphson iterations, as they are necessary within fully implicit time integration schemes. Read More

In this work we continue the investigation of different approaches to conception and modeling of composite materials. The global method we focus on, is called 'stochastic homogenization'. In this approach, the classical deterministic \emph{homogenization} techniques and procedures are used to compute the macroscopic parameters of a composite starting from its microscopic properties. Read More

This paper presents three different constitutive approaches to model thin rotation-free shells based on the Kirchhoff-Love hypothesis. One approach is based on numerical integration through the shell thickness while the other two approaches do not need any numerical integration and so they are computationally more efficient. The formulation is designed for large deformations and allows for geometrical and material nonlinearities, which makes it very suitable for the modeling of soft tissues. Read More

We develop a framework to uncover and analyze dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive data sets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high frequency oscillations (HFOs) from a big database of rat EEG recordings. Read More

When comparing measurements to numerical simulations of moisture transfer through porous materials a rush of the experimental moisture front is commonly observed in several works shown in the literature, with transient models that consider only the diffusion process. Thus, to overcome the discrepancies between the experimental and the numerical models, this paper proposes to include the moisture advection transfer in the governing equation. To solve the advection-diffusion differential equation, it is first proposed two efficient numerical schemes and their efficiencies are investigated for both linear and nonlinear cases. Read More

The immersed boundary (IB) method is an approach to fluid-structure interaction (FSI) that uses a Lagrangian description of the structural deformations, stresses, and forces along with an Eulerian description of the momentum, viscosity, and incompressibility of the fluid-structure system. Originally, the IB method for FSI described the immersed structure using systems of elastic fibers discretized as collections of points connected by springs and beams. Extensions of the classical IB method also have been introduced, including approaches that use finite element (FE) methods for the structural elasticity. Read More

Reconstructing brain activity through electroencephalography requires a boundary value problem (BVP) solver to take a proposed distribution of current dipoles within the brain and compute the resulting electrostatic potential on the scalp. This article proposes the use of sequential kriging optimization to identify different optimal BVP solver parameters for dipoles located in isolated sections of the brain by considering the cumulative impact of randomly oriented dipoles within a chosen isolated section. We attempt preemptive termination of parametrizations suggested during the sequential kriging optimization which, given the results to that point, seem unlikely to produce high quality solutions. Read More