Computational Modeling of Airborne Noise Demonstrated Via Benchmarks, Supersonic Jet, and Railway Barrier

In the last several years, there has been a growing demand for mobility to cope with the increasing population. All kinds of transportation have responded to this demand by expanding their networks and introducing new ideas. Rail transportation introduced the idea of high-speed trains and air transportation introduced the idea of high-speed civil transport (HSCT). In this expanding world, the noise legislation is felt to inhibit these plans. Accurate computational methods for noise prediction are in great demand. In the current research, two computational methods are developed to predict noise propagation in air. The first method is based on the finite differencing technique on generalized curvilinear coordinates and it is used to solve linear and nonlinear Euler equations. The dispersion-relation-preserving scheme is adopted for spatial discretization. For temporal integration, either the dispersion-relation-preserving scheme or the low-dispersion-and-dissipation Runge-Kutta scheme is used. Both characteristic and asymptotic nonreflective boundary conditions are studied. Ghost points are employed to satisfy the wall boundary condition. A number of benchmark problems are solved to validate different components of the present method. These include initial pulse in free space, initial pulse reflected from a flat or curved wall, time-periodic train of waves reflected from a flat wall, and oscillatory sink flow. The computed results are compared with the analytical solutions and good agreements are obtained. Using the method developed, the noise of Mach 2.1, perfectly expanded, two-dimensional supersonic jet is computed. The Reynolds-averaged Navier-Stokes equations are solved for the jet mean flow. The instability waves, which are used to excite the jet, are obtained from the solution of the compressible Rayleigh equation. Then, the linearized Euler equations are solved for jet noise. To improve computational efficiency, flow-adapted grid and a multi-block time integration technique are developed. The computations are compared with the experimental results for both the mean flow and the jet noise. Good agreement is obtained. The method proved to be fast and efficient. The second computational method is based on the boundary element technique. The Helmholtz equation is solved for the sound field around a railway noise barrier. Linear elements are used to discretize the barrier surface. Frequency-dependent grids are employed for efficiency. The train noise is represented by a point source located above the nearest rail. The source parameters are estimated from a typical field measurement of train noise spectrum. Both elevated and ground-level train decks are considered. The performance of the noise barrier at low and high frequencies is investigated. Moreover, A-weighted sound pressure levels are calculated. The computed results are successfully compared with field measurements

Medical and Biological Image Analysis

Today, technology and information communication are deeply embedded in our life. Information is present and used in many forms: electronic documents, audio, videos, photos, etc. Recent advances in technology, particularly in the computer industry and communication, have motivated organisations to replace their traditional manually stored and exchanged records with computer systems and digital documents for secure storage and smooth transmission. Medical and biological image processing is a numerical method and technique for modifying a digital image to improve or extract information. The main stages of image processing are

Mechanical properties of carbon black/poly (ε-caprolactone)-based tissue scaffolds

Carbon black (CB) spherical particles were added to poly(ε-caprolactone) (PCL) polymer to produce strong synthetic tissue scaffolds for biomedical applications. The objective of this paper is to study the mechanical behavior of CB/PCL-based nanocomposites using experimental tests, multi-scale numerical approaches, and analytical models. The mechanical properties of CB/PCL scaffolds were characterized using thermal mechanical analysis and results show a significant increase of the elastic modulus with increasing nanofiller concentration up to 7 wt%. Conversely, finite element computations were performed using a simulated microstructure, and a numerical model based on the representative volume element (RVE) was generated. Thereafter, Young's moduli were computed using a 3D numerical homogenization technique. The approach takes into consideration CB particles’ diameters, as well as their random distribution and agglomerations into PCL. Experimental results were compared with data obtained using numerical approaches and analytical models. Consistency in the results was observed, especially in the case of lower CB fractions

Evaluation of Orifice Flow Meter Accuracy under Pulsation Conditions

Orifice meter is a flow measuring device which is widely used in various industrial applications. Although the device gives accurate measurement during steady flow, measurement errors related to square root and sampling errors are unavoidable if pulsations exist. This research investigatesand improves the performance of an orifice plate flow meter under pulsation effects. A simple model for the pulsating flow through an orifice meter is presented. Square root error (SRE) is estimated. Sampling errors (SE) are reduced by proper selection of the averaging tim

Signature-Free Asynchronous Binary Byzantine Consensus with t<<n/3, O(n²) Messages, and O(1) Expected Time

International audienceThis paper is on broadcast and agreement in asynchronous message-passing systems made up of n processes, and where up to t processes may have a Byzantine Behavior. Its first contribution is a powerful , yet simple, all-to-all broadcast communication abstraction suited to binary values. This abstraction, which copes with up to t < n/3 Byzantine processes, allows each process to broadcast a binary value, and obtain a set of values such that (1) no value broadcast only by Byzantine processes can belong to the set of a correct process, and (2) if the set obtained by a correct process contains a single value v, then the set obtained by any correct process contains v. The second contribution of the paper is a new round-based asynchronous consensus algorithm that copes with up to t < n/3 Byzantine processes. This algorithm is based on the previous binary broadcast abstraction and a weak common coin. In addition of being signature-free and optimal with respect to the value of t, this consensus algorithm has several noteworthy properties: the expected number of rounds to decide is constant; each round is composed of a constant number of communication steps and involves O(n²) messages; each message is composed of a round number plus a constant number of bits. Moreover , the algorithm tolerates message reordering by the adversary (i.e., the Byzantine processes)

Stabilization of the transmission Schrodinger equation with boundary time-varying delay

We consider a system of transmission of the Schrodinger equation with Neumann feedback control that contains a&nbsp;time-varying delay term and that acts on the exterior boundary. Using a suitable energy function and a suitable Lyapunov functionnal, we prove under appropriate assumptions that the solutions decay exponentially. Keywords: Schrodinger equation, transmission problem, time-varying delay, exponential stability, boundary stabilization. ¨ MSC: 35Q93, 93D15 REFERENCES [1] Allag, I., &amp; Rebiai, S. (2014). Well-posedness, regularity and exact controllability for the problem of transmission of the Schrödinger equation. Quarterly of Applied Mathematics, 72(1), 93-108.‏. Search in Google Scholar&nbsp;&nbsp; Digital Object Identifier MathSciNet [2] Bayili, G., Aissa, A. B., &amp; Nicaise, S. (2020). Same decay rate of second order evolution equations with or without delay. Systems &amp; Control Letters, 141, 104700.‏. 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Adaptive traffic lights based on traffic flow prediction using machine learning models

Traffic congestion prediction is one of the essential components of intelligent transport systems (ITS). This is due to the rapid growth of population and, consequently, the high number of vehicles in cities. Nowadays, the problem of traffic congestion attracts more and more attention from researchers in the field of ITS. Traffic congestion can be predicted in advance by analyzing traffic flow data. In this article, we used machine learning algorithms such as linear regression, random forest regressor, decision tree regressor, gradient boosting regressor, and K-neighbor regressor to predict traffic flow and reduce traffic congestion at intersections. We used the public roads dataset from the UK national road traffic to test our models. All machine learning algorithms obtained good performance metrics, indicating that they are valid for implementation in smart traffic light systems. Next, we implemented an adaptive traffic light system based on a random forest regressor model, which adjusts the timing of green and red lights depending on the road width, traffic density, types of vehicles, and expected traffic. Simulations of the proposed system show a 30.8% reduction in traffic congestion, thus justifying its effectiveness and the interest of deploying it to regulate the signaling problem in intersections

Dynamic thermal model for proton-exchange membrane fuel cell

In this paper, a mathematical model is developed to simulate the transient phenomena in a polymer electrolyte membrane fuel cell (PEMFC) system. Large transient changes are expected for practical application such as transportation vehicles due to acceleration and deceleration. Simple models are usually unable to capture these transient dynamics. For control purposes, a fuel cell model must include the dynamics of flow and pressure in the anode and cathode channels and mass/heat transfer transients. The proposed model can predict the transient response of cell voltage, temperature of the cell, hydrogen/oxygen out flow rates and cathode and anode channel pressures under sudden change in load current. It is implemented in SIMULINK environment. The model is tested by simulating a transportation-size fuel cell with 85 kW maximum power output. Results for maximum power and multi-step input current that simulate start up-shut down cycle are shown. The predicted power, pressure and temperature are matching the published data for the fuel cell. The model will be very useful for the optimal design and real-time control of PEM fuel cell systems in practical automotive or stationary applications