Two-dimensional Test Research Articles

Statistical Learning for Anomaly Detection in Cloud Server Systems: A Multi-Order Markov Chain Framework

As a major strategy to ensure the safety of IT infrastructure, anomaly detection plays a more important role in cloud computing platform which hosts the entire applications and data. On top of the classic Markov chain model, we proposed in this paper a feasible multi-order Markov chain based framework for anomaly detection. In this approach, both the high-order Markov chain and multivariate time series are adopted to compose a scheme described in algorithms along with the training procedure in the form of statistical learning framework. To curb time and space complexity, the algorithms are designed and implemented with non-zero value table and logarithm values in initial and transition matrices. For validation, the series of system calls and the corresponding return values are extracted from classic Defense Advanced Research Projects Agency (DARPA) intrusion detection evaluation data set to form a two-dimensional test input set. The testing results show that the multi-order approach is able to produce more effective indicators: in addition to the absolute values given by an individual single-order model, the changes in ranking positions of outputs from different-order ones also correlate closely with abnormal behaviours.

River computations: artificial backwater from the momentum advection scheme

ABSTRACTThe established method for determining dike heights and dimensioning river training structures is to assess the resulting backwater by numerical modelling. The common consensus is that bottom friction determines the backwater and that momentum advection only has a local effect. We demonstrate that the numerical/artificial backwater contribution from the momentum advection approximation can be of the same order of magnitude as the bottom friction contribution, depending on the advection scheme. This is realized using a one-dimensional analysis and verified using a set of one- and two-dimensional test problems including a wavy bed case, flow over emerged and submerged groynes and finally an actual river. We compare first- and second-order accurate advection schemes and compute their artificial contribution to the backwater, for a range of practically-feasible grid resolutions. The tests demonstrate that the conservation/constancy properties of the scheme determine the size of this contribution, rather than the order of the scheme.

Groundwater flow and heat transport for systems undergoing freeze-thaw: Intercomparison of numerical simulators for 2D test cases

Abstract In high-elevation, boreal and arctic regions, hydrological processes and associated water bodies can be strongly influenced by the distribution of permafrost. Recent field and modeling studies indicate that a fully-coupled multidimensional thermo-hydraulic approach is required to accurately model the evolution of these permafrost-impacted landscapes and groundwater systems. However, the relatively new and complex numerical codes being developed for coupled non-linear freeze-thaw systems require verification. This issue is addressed by means of an intercomparison of thirteen numerical codes for two-dimensional test cases with several performance metrics (PMs). These codes comprise a wide range of numerical approaches, spatial and temporal discretization strategies, and computational efficiencies. Results suggest that the codes provide robust results for the test cases considered and that minor discrepancies are explained by computational precision. However, larger discrepancies are observed for some PMs resulting from differences in the governing equations, discretization issues, or in the freezing curve used by some codes.

An HLLC Riemann solver for resistive relativistic magnetohydrodynamics

We present a new approximate Riemann solver for the augmented system of equations of resistive relativistic magnetohydrodynamics (RRMHD) that belongs to the family of Harten-Lax-van Leer contact wave (HLLC) solvers. In HLLC solvers, the solution is approximated by two constant states flanked by two shocks separated by a contact wave. The accuracy of the new approximate solver is calibrated through one- and two-dimensional test problems.

A conservative numerical scheme for modeling nonlinear acoustic propagation in thermoviscous homogeneous media

A nonlinear system of partial differential equations capable of describing the nonlinear propagation and attenuation of finite amplitude perturbations in thermoviscous media is presented. This system constitutes a full nonlinear wave model that has been formulated in the conservation form. Initially, this model is investigated analytically in the inviscid limit where it has been found that the resulting flux function fulfills the Lax–Wendroff theorem, and the scheme can match the solutions of the Westervelt and Burgers equations numerically. Here, high-order numerical descriptions of strongly nonlinear wave propagations become of great interest. For that matter we consider finite difference formulations of the weighted essentially non-oscillatory (WENO) schemes associated with explicit strong stability preserving Runge–Kutta (SSP-RK) time integration methods. Although this strategy is known to be computationally demanding, it is found to be effective when implemented to be solved in graphical processing units (GPUs). As we consider wave propagations in unbounded domains, perfectly matching layers (PML) have been also considered in this work. The proposed system model is validated and illustrated by using one- and two-dimensional benchmark test cases proposed in the literature for nonlinear acoustic propagation in homogeneous thermoviscous media.

Method of relaxed streamline upwinding for hyperbolic conservation laws

In this work a new finite element based Method of Relaxed Streamline Upwinding is proposed to solve hyperbolic conservation laws. Formulation of the proposed scheme is based on relaxation system which replaces hyperbolic conservation laws by semi-linear system with stiff source term also called as relaxation term. The advantage of the semi-linear system is that the nonlinearity in the convection term is pushed towards the source term on right hand side which can be handled with ease. Six symmetric discrete velocity models are introduced in two dimensions which symmetrically spread foot of the characteristics in all four quadrants thereby taking information symmetrically from all directions. Proposed scheme gives exact diffusion vectors which are very simple. Moreover, the formulation is easily extendable from scalar to vector conservation laws. Various test cases are solved for Burgers equation (with convex and non-convex flux functions), Euler equations and shallow water equations in one and two dimensions which demonstrate the robustness and accuracy of the proposed scheme. New test cases are proposed for Burgers equation, Euler and shallow water equations. Exact solution is given for two-dimensional Burgers test case which involves normal discontinuity and series of oblique discontinuities. Error analysis of the proposed scheme shows optimal convergence rate. Moreover, spectral stability analysis gives implicit expression of critical time step.

Adjoint-Based Two-Step Optimization Method Using Proper Orthogonal Decomposition and Domain Decomposition

A modified two-step method for aerodynamic shape optimization is proposed, where proper orthogonal decomposition and automatic domain-decomposition techniques are adopted to accelerate flow and adjoint solutions in the second-step optimization. As the first step in this method, the initial optimization is first performed by a genetic algorithm coupled with a kriging model. Next, a reduced-order model is set up via proper orthogonal decomposition with the reuse of ready-made flow snapshots in the first-step optimization. A proper-orthogonal-decomposition Petrov-Galerkin method is investigated to provide fast flow predictions in the second-step optimization. With the assistance of an error estimation method and an automatic domain-decomposition method that are presented in this paper, the sensitive domain in the computational grid is split out. To improve the accuracy, predictions provided by proper orthogonal decomposition in the sensitive domain are further corrected by computational fluid dynamics modifications. Meanwhile, in order to accelerate gradient solutions, the adjoint equation of this proper orthogonal decomposition and domain-decomposition-based flow analysis method is derived and discussed. The optimization results of a two-dimensional airfoil design test and a three-dimensional wing design test highlight the efficiency of the proposed method when compared with results of either a gradient-free optimization method or a traditional two-step method.

The Shifted Proper Orthogonal Decomposition: A Mode Decomposition for Multiple Transport Phenomena

Transport-dominated phenomena provide a challenge for common mode-based model reduction approaches. We present a model reduction method, which is suited for these kinds of systems. It extends the proper orthogonal decomposition (POD) by introducing time-dependent shifts of the snapshot matrix. The approach, called shifted proper orthogonal decomposition (sPOD), features a determination of the multiple transport velocities and a separation of these. One- and two-dimensional test examples reveal the good performance of the sPOD for transport-dominated phenomena and its superiority in comparison to the POD.

Research on the grinding performance of high pressure sintering SiCp/Al matrix composites

The two-dimensional vertical grinding test equipment was used to grind SiCp/Al composites which were prepared by high pressure sintering method. The SEM observation of grinding morphology showed that grinding damage can be prevented by SiC particles reinforcement, 60% volume fraction of SiC particles of SiCp/Al composite can hinder grinding depth and grinding performance was improved with the sintering pressure and temperature increasing. In addition, some scratches and exfoliated pits of SiC particles were observed on the surface of 60% volume SiCp/Al composite as the increase of grinding grain, while the depth of these scratches was shallower, there was no large area exfoliated pits of SiC reinforcements.<br>

A Conservative Interface Sharpening Lattice Boltzmann Model

A lattice Boltzmann model for the propagation and sharpening of phase boundaries that arise in applications such as multiphase flow is presented. The sharpening is accomplished through an artificial compression term that acts in the vicinity of the interface and in the direction of its surface normal. This term is embedded into the moments of the two-relaxation-time discrete velocity Boltzmann partial differential equation, which is discretized in space and time to yield a second order algorithm. Stringent one- and two-dimensional tests for sharp propagating fronts are performed. The proposed model is shown to conserve the phase field to machine precision and allows narrow interfaces to advect correctly with the flow field with minimal lattice pinning and facetting.

Testing and analytical modeling of two-dimensional geotextile tube dewatering process

Geotextile tubes are used to dewater slurries, sediments, and wastes. With their extensive use for dewatering, the desire to maximize both dewatering rate and sediment retention has led to the use of chemical accelerants, which have become a standard practice in geotextile tube dewatering projects. A variety of test methods are currently used to evaluate geotextile tube performance, ranging from small-scale Falling Head Tests (FHTs), medium-scale Hanging Bag Tests (HBTs), and Geotextile-tube Demonstration Tests (GDTs), to full-scale pilot tests. However, few studies have compared the results from different dewatering tests and fewer have developed proper correlations between test methods. In this study, a recently developed pressurized two-dimensional dewatering test (P2DT) is used to analyze the dewatering process in geotextile tubes in both the radial and axial directions. In this study, P2DT and GDT tests were performed on Tully slurry at different solids concentrations conditioned with chemical accelerants and under different pressures. The P2DT results, along with analytical modeling, are then used to predict the dewatering behavior of GDTs based on P2DT, where the predictions were within 8%. Based on the results, a framework for predicting the dewatering behavior of full-scale tests using an analytical model generated from P2DT is presented.

Cross-Level Detection Framework for Attacks on Cyber-Physical Systems

Anomaly detection is critical in thwarting malicious attacks on Cyber-Physical Systems. This work presents a novel inference engine that integrates two heterogeneous anomaly detectors, working at different levels of the system architecture, in order to produce a cross-level detector more effective than either one separately. The macro- or process-level detector uses a bank of observers of the physical plant that estimate the state of the process suspected to be under attack, specifically for its sensor to be compromised, from data gathered by available networked sensors. The estimates are then combined using a consensus algorithm to determine if the suspect sensor is reporting false readings. The micro-level detector uses time-sampled side-channel power measurements of an integrated circuit on the suspect sensor. By comparing power measurements against those from a known good state, differences indicate the code running inside has been altered. The cross-level detector performs a two-dimensional Neyman-Pearson hypothesis test that declares the presence of an attack on the sensor node. The cross-level detector is shown to be more accurate and less latent than its constituent parts. Detection was tested against a range of False Data Injection attacks on a hardware prototype and the detector performance was measured experimentally. The cross-level detector on average achieved a 93% rate of correct detection, compared with 72 and 85% for the macro- and micro-level detectors, respectively; and a 50% reduction in latency compared to the macro-level detector.

Improvement of computational efficiency of circular function-based gas kinetic scheme by using Jacobian-free Newton–Krylov method

The gas-kinetic BGK scheme is a promising method for simulation of inviscid and viscous flows. Different from conventional Navier–Stokes (N-S) solvers, it evaluates the inviscid and viscous fluxes simultaneously by reconstructing the local solution of BGK Boltzmann equation at the cell interface. Due to its inherently superior dissipation property, it usually gives accurate and robust numerical results. However, a notable drawback of the BGK-type scheme is the low computational efficiency. Recently, aimed at reducing the computational effort, a circular function-based BGK (CBGK) scheme was developed. Nevertheless, it is still time consuming because the original scheme used an explicit way in the time integration as in most existing BGK schemes and the convergence speed can be slow. To improve the computational efficiency, an implicit CBGK scheme is developed in this paper by incorporating the Jacobian-free Newton–Krylov (JFNK) method into the scheme. Particularly, the generalized minimal residual (GMRES) approach is employed to iteratively solve the large linear equation system. With the help of the Jacobian-free approach, a faster convergence speed can be achieved without explicitly computing and storing the flux Jacobian, which is usually a large and sparse matrix. In order to reduce the number of GMRES iterations, the preconditioning is also adopted and the Lower-Upper symmetric Gauss-Seidel (LUSGS) scheme is employed as a preconditioner. For validation of the present CBGK-JFNK method, several two-dimensional inviscid and viscous test cases are investigated. The numerical results show that the needed computational time is significantly reduced as compared with the original explicit CBGK scheme and the CBGK-LUSGS method.

A neural network approach for the blind deconvolution of turbulent flows

We present a single-layer feed-forward artificial neural network architecture trained through a supervised learning approach for the deconvolution of flow variables from their coarse-grained computations such as those encountered in large eddy simulations. We stress that the deconvolution procedure proposed in this investigation is blind, i.e. the deconvolved field is computed without any pre-existing information about the filtering procedure or kernel. This may be conceptually contrasted to the celebrated approximate deconvolution approaches where a filter shape is predefined for an iterative deconvolution process. We demonstrate that the proposed blind deconvolution network performs exceptionally well in the a priori testing of two-dimensional Kraichnan, three-dimensional Kolmogorov and compressible stratified turbulence test cases, and shows promise in forming the backbone of a physics-augmented data-driven closure for the Navier–Stokes equations.

Nonreflecting outlet boundary conditions for incompressible flows using SPH

In this paper we implement a simple strategy, based on Jin and Braza’s method, to deal with nonreflecting outlet boundary conditions for incompressible Navier-Stokes flows using the method of smoothed particle hydrodynamics (SPH). The outflow boundary conditions are implemented using an outflow zone downstream of the outlet, where particles are moved using an outgoing wave equation for the velocity field so that feedback noise from the outlet boundary is greatly reduced. For unidirectional flow across the outlet, this condition reduces to Orlanski’s wave equation. The performance of the method is demonstrated through several two-dimensional test problems, including unsteady, plane Poiseuille flow, flow between two inclined plates, the Kelvin–Helmholtz instability in a channel, and flow in a constricted conduit, and in three-dimensions for turbulent flow in a 90° section of a curved square pipe. The results show that spurious waves incident from the outlet are effectively absorbed and that steady-state laminar flows can be maintained for much longer times compared to periodic boundary conditions. In addition, time-dependent anisotropies in the flow, like fluid recirculations, are convected across the outlet in a very stable and accurate manner.

A cargo-sorting DNA robot.

Two critical challenges in the design and synthesis of molecular robots are modularity and algorithm simplicity. We demonstrate three modular building blocks for a DNA robot that performs cargo sorting at the molecular level. A simple algorithm encoding recognition between cargos and their destinations allows for a simple robot design: a single-stranded DNA with one leg and two foot domains for walking, and one arm and one hand domain for picking up and dropping off cargos. The robot explores a two-dimensional testing ground on the surface of DNA origami, picks up multiple cargos of two types that are initially at unordered locations, and delivers them to specified destinations until all molecules are sorted into two distinct piles. The robot is designed to perform a random walk without any energy supply. Exploiting this feature, a single robot can repeatedly sort multiple cargos. Localization on DNA origami allows for distinct cargo-sorting tasks to take place simultaneously in one test tube or for multiple robots to collectively perform the same task.

Mechanical characteristics of the maxillary sinus Schneiderian membrane ex vivo.

It has been speculated that certain Schneiderian membrane thickness (SMT) might be more prone to perforation. This investigation was aimed at studying the mechanical characteristics of the Schneiderian membrane under one- and two-dimensional tests and their correlation to the histological SMT in human samples. Sixteen Schneiderian membranes were collected from 11 cadaver heads treated with Thiel's embalming method. The samples were processed and analyzed clinically and histologically. One-dimensional maximum elongation until perforation and two-dimensional resistance to ball penetration were performed after the biopsy. Data was analyzed by using the Wilcoxon rank test and the Spearman's rank correlation. The histological SMT was 1.36±0.42mm, whereas the clinical thickness was 0.27±0.21mm, yielding statistical significance (p=0.000). The resistance under ball penetration was 0.59±0.43N and the mean maximum elongation in the one-dimension test 11.19±7.14mm. Expressed in percentage, the mean stretch was 241.36±227.97% (range 31.5 up to 947%). A weak positive correlation was found between the ball penetration test and the SMT (r=0.10, p=0.711), while a weak negative correlation was found between stretching test and the SMT (r=-0.021, p=0.94). Mechanical tests seem to indicate that SMT might not significantly predispose to Schneiderian membrane perforation. Hence, other anatomical and operator's factors should be considered of surpassing importance. Thinner SM might be more prone to perforation when detaching it from the maxillary sinus antrum; however, a thick membrane is not prevented to tear, as their resistance under elastic forces is not higher than thinner ones.

FEA Simulation of Free-Bending – a Preforming Step in the Hydroforming Process Chain

High-strength steel and aluminum alloys are essential for developing innovative, lightly-weighted space frame concepts. The intended design is built from car body parts with high geometrical complexity and reduced material-thickness.Over the past few years, many complex car body parts have been produced using hydroforming. To increase the accuracy of hydroforming in relation to prospective car concepts, the virtual manufacturing of forming becomes more important. As a part of process digitalization, it is necessary to develop a simulation model for the hydroforming process chain. The preforming of longitudinal welded tubes is therefore implemented by the use of three-dimensional free-bending. This technique is able to reproduce complex deflection curves in combination with innovative low-thickness material design for hydroforming processes.As a first step to the complete process simulation, the content of this paper deals with the development of a finite element simulation model for the free-bending process with 6 degrees of freedom. A mandrel built from spherical segments connected by a steel rope is located inside of the tube to prevent geometrical instability. Critical parameters for the result of the bending process are therefore evaluated and optimized. The simulation model is verified by surface measurements of a two-dimensional bending test.

Simulation of bubbly flows with special numerical treatments of the semi-conservative and fully conservative two-fluid model

Bubbly flows are found in a large number of chemical engineering applications. For the computational fluid dynamics (CFD) simulations of such multi-phase flows, both physical models and numerical treatment are crucial to obtain robust and accurate results. In this numerical study, we investigate the two-fluid model (TFM) under challenging conditions such as phase segregation and inversion. For the phase segregation, a singular problem arises in the phase momentum and the two-phase k-ε equations when one phase fraction approaches zero. Another numerical issue is the accurate calculation of the drag coefficient, e.g., during the phase inversion. To address the singular problem, previous studies used a non-conservative formulation after dividing by the phase fraction; in our approach, we present a robust methodology for semi-conservative and fully conservative formulations. A special numerical treatment is introduced to the phase momentum equations and the turbulence equations, which avoids the singular problem in case of phase segregation. Concerning the drag force, two novel methods, the linear and the hyperbolic blending method, respectively, are presented to obtain accurate results. For testing the new numerical treatment, the analytical solution of a two-dimensional test case is first compared with the results predicted using a semi-conservative and a fully conservative formulation. The second test case investigated is a bubble column with different superficial velocities. The results from three-dimensional simulations using the novel formulations show good agreement with the literature data. Especially when phase segregation occurs, the semi-conservative and the fully conservative formulations using the two-phase k-ε model formulation converge.

An efficient flamelet progress-variable method for modeling non-premixed flames in weak electric fields

Combustion stabilization and enhancement of the flammability limits are mandatory objectives to improve nowadays combustion chambers. At this purpose, the use of an electric field in the flame region provides a solution which is, at the same time, easy to implement and effective to modify the flame structure. The present work describes an efficient flamelet progress-variable approach developed to model the fluid dynamics of flames immersed in an electric field. The main feature of this model is that it can use complex ionization mechanisms without increasing the computational cost of the simulation. The model is based on the assumption that the combustion process is not directly influenced by the electric field and has been tested using two chemi-ionization mechanisms of different complexity in order to examine its behavior with and without the presence of heavy anions in the mixture. Using a one- and a two-dimensional numerical test cases, the present approach has been able to reproduce all the major aspects encountered when a flame is subject to an imposed electric field and the main effects of the different chemical mechanisms. Moreover, the proposed model is shown to produce a large reduction in the computational cost, being able to shorten the time needed to perform a simulation up to 40 times.