989 resultados para Term Splitting Algorithm
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A numerical scheme is presented for the solution of the Euler equations of compressible flow of a real gas in a single spatial coordinate. This includes flow in a duct of variable cross-section, as well as flow with slab, cylindrical or spherical symmetry, as well as the case of an ideal gas, and can be useful when testing codes for the two-dimensional equations governing compressible flow of a real gas. The resulting scheme requires an average of the flow variables across the interface between cells, and this average is chosen to be the arithmetic mean for computational efficiency, which is in contrast to the usual “square root” averages found in this type of scheme. The scheme is applied with success to five problems with either slab or cylindrical symmetry and for a number of equations of state. The results compare favourably with the results from other schemes.
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In order to use the finite element method for solving fluid-rock interaction problems in pore-fluid saturated hydrothermal/sedimentary basins effectively and efficiently, we have presented, in this paper, the new concept and numerical algorithms to deal with the fundamental issues associated with the fluid-rock interaction problems. These fundamental issues are often overlooked by some purely numerical modelers. (1) Since the fluid-rock interaction problem involves heterogeneous chemical reactions between reactive aqueous chemical species in the pore-fluid and solid minerals in the rock masses, it is necessary to develop the new concept of the generalized concentration of a solid mineral, so that two types of reactive mass transport equations, namely, the conventional mass transport equation for the aqueous chemical species in the pore-fluid and the degenerated mass transport equation for the solid minerals in the rock mass, can be solved simultaneously in computation. (2) Since the reaction area between the pore-fluid and mineral surfaces is basically a function of the generalized concentration of the solid mineral, there is a definite need to appropriately consider the dependence of the dissolution rate of a dissolving mineral on its generalized concentration in the numerical analysis. (3) Considering the direct consequence of the porosity evolution with time in the transient analysis of fluid-rock interaction problems; we have proposed the term splitting algorithm and the concept of the equivalent source/sink terms in mass transport equations so that the problem of variable mesh Peclet number and Courant number has been successfully converted into the problem of constant mesh Peclet and Courant numbers. The numerical results from an application example have demonstrated the usefulness of the proposed concepts and the robustness of the proposed numerical algorithms in dealing with fluid-rock interaction problems in pore-fluid saturated hydrothermal/sedimentary basins. (C) 2001 Elsevier Science B.V. All rights reserved.
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Consider the problem of scheduling a set of sporadic tasks on a multiprocessor system to meet deadlines using a task-splitting scheduling algorithm. Task-splitting (also called semi-partitioning) scheduling algorithms assign most tasks to just one processor but a few tasks are assigned to two or more processors, and they are dispatched in a way that ensures that a task never executes on two or more processors simultaneously. A particular type of task-splitting algorithms, called slot-based task-splitting dispatching, is of particular interest because of its ability to schedule tasks with high processor utilizations. Unfortunately, no slot-based task-splitting algorithm has been implemented in a real operating system so far. In this paper we discuss and propose some modifications to the slot-based task-splitting algorithm driven by implementation concerns, and we report the first implementation of this family of algorithms in a real operating system running Linux kernel version 2.6.34. We have also conducted an extensive range of experiments on a 4-core multicore desktop PC running task-sets with utilizations of up to 88%. The results show that the behavior of our implementation is in line with the theoretical framework behind it.
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We present a novel numerical algorithm for the simulation of seismic wave propagation in porous media, which is particularly suitable for the accurate modelling of surface wave-type phenomena. The differential equations of motion are based on Biot's theory of poro-elasticity and solved with a pseudospectral approach using Fourier and Chebyshev methods to compute the spatial derivatives along the horizontal and vertical directions, respectively. The time solver is a splitting algorithm that accounts for the stiffness of the differential equations. Due to the Chebyshev operator the grid spacing in the vertical direction is non-uniform and characterized by a denser spatial sampling in the vicinity of interfaces, which allows for a numerically stable and accurate evaluation of higher order surface wave modes. We stretch the grid in the vertical direction to increase the minimum grid spacing and reduce the computational cost. The free-surface boundary conditions are implemented with a characteristics approach, where the characteristic variables are evaluated at zero viscosity. The same procedure is used to model seismic wave propagation at the interface between a fluid and porous medium. In this case, each medium is represented by a different grid and the two grids are combined through a domain-decomposition method. This wavefield decomposition method accounts for the discontinuity of variables and is crucial for an accurate interface treatment. We simulate seismic wave propagation with open-pore and sealed-pore boundary conditions and verify the validity and accuracy of the algorithm by comparing the numerical simulations to analytical solutions based on zero viscosity obtained with the Cagniard-de Hoop method. Finally, we illustrate the suitability of our algorithm for more complex models of porous media involving viscous pore fluids and strongly heterogeneous distributions of the elastic and hydraulic material properties.
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El proyecto fin de carrera de herramienta de apoyo a la docencia en Sistemas Operativos quiere ayudar al alumno a entender el funcionamiento de un planificador a corto plazo. Lo hace mediante una representación gráfica de procesos que ocupan o el procesador o distintas unidades de entrada/salida mientras transcurre el tiempo. El tiempo está dividido en ciclos de reloj de un procesador, a lo que a continuación se referirá como unidades de tiempo. Los procesos están definidos por su nombre, la instante de entrada que entran al sistema, su prioridad y la secuencia de unidades de tiempo en el procesador y unidades de entrada/salida que necesitan para terminar su trabajo. El alumno puede configurar el sistema a su gusto en cuanto al número y comportamiento de las unidades de entrada/salida. Puede definir que una unidad solo permita acceso exclusivo a los procesos, es decir que solo un proceso puede ocuparla simultáneamente, o que permita el acceso múltiple a sus recursos. El alumno puede construir un planificador a corto plazo propio, integrarlo en el sistema y ver cómo se comporta. Se debe usar la interfaz Java proporcionada para su construcción. La aplicación muestra datos estadísticos como por ejemplo la eficiencia del sistema (el tiempo activo de la CPU dividido por el tiempo total de la simulación), tiempos de espera de los procesos, etc. Se calcula después de cada unidad de tiempo para que el alumno pueda ver el momento exacto donde la simulación tomó un giro inesperado. La aplicación está compuesta por un motor de simulación que contiene toda la lógica y un conjunto de clases que forman la interfaz gráfica que se presenta al usuario. Estos dos componentes pueden ser reemplazados siempre y cuando se mantenga la definición de sus conectores igual. La aplicación la he hecho de manejo muy simple e interfaz fácil de comprender para que el alumno pueda dedicar todo su tiempo a probar distintas configuraciones y situaciones y así entender mejor la asignatura. ABSTRACT. The project is called “Tool to Support Teaching of the Subject Operating Systems” and is an application that aims to help students understand on a deeper level the inner workings of how an operating system handles multiple processes in need of CPU time by the means of a short-term planning algorithm. It does so with a graphical representation of the processes that occupy the CPU and different input/output devices as time passes by. Time is divided in CPU cycles, from now on referred to as time units. The processes are defined by their name, the moment they enter the system, their priority and the sequence of time units they need to finish their job. The student can configure the system by changing the number and behavior of the input/output devices. He or she can define whether a device should only allow exclusive access, i.e. only one process can occupy it at any given time, or if it should allow multiple processes to access its resources. The student can build a planning algorithm of his or her own and easily integrate it into the system to see how it behaves. The provided Java interface and the programming language Java should be used to build it. The application shows statistical data, e.g. the efficiency of the system (active CPU time divided by total simulation time) and time spent by the processes waiting in queues. The data are calculated after passing each time unit in order for the student to see the exact moment where the simulation took an unexpected turn. The application is comprised of a simulation motor, which handles all the logic, and a set of classes, which is the graphical user interface. These two parts can be replaced individually if the definition of the connecting interfaces stays the same. I have made the application to be very easy to use and with an easy to understand user interface so the student can spend all of his or her time trying out different configurations and scenarios in order to understand the subject better.
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Thesis (Ph.D.)--University of Washington, 2016-06
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Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year
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In this paper a method for solving the Short Term Transmission Network Expansion Planning (STTNEP) problem is presented. The STTNEP is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In this work we present a constructive heuristic algorithm to find a solution of the STTNEP of excellent quality. In each step of the algorithm a sensitivity index is used to add a circuit (transmission line or transformer) to the system. This sensitivity index is obtained solving the STTNEP problem considering as a continuous variable the number of circuits to be added (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an interior points method that uses a combination of the multiple predictor corrector and multiple centrality corrections methods, both belonging to the family of higher order interior points method (HOIPM). Tests were carried out using a modified Carver system and the results presented show the good performance of both the constructive heuristic algorithm to solve the STTNEP problem and the HOIPM used in each step.
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In this paper, a method for solving the short term transmission network expansion planning problem is presented. This is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In order to And a solution of excellent quality for this problem, a constructive heuristic algorithm is presented in this paper. In each step of the algorithm, a sensitivity index is used to add a circuit (transmission line or transformer) or a capacitor bank (fixed or variable) to the system. This sensitivity index is obtained solving the problem considering the numbers of circuits and capacitors banks to be added (relaxed problem), as continuous variables. The relaxed problem is a large and complex nonlinear programming and was solved through a higher order interior point method. The paper shows results of several tests that were performed using three well-known electric energy systems in order to show the possibility and the advantages of using the AC model. ©2007 IEEE.
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In this paper, the short term transmission network expansion planning (STTNEP) is solved through a specialized genetic algorithm (SGA). A complete AC model of the transmission network is used, which permits the formulation of an integrated power system transmission network expansion planning problem (real and reactive power planning). The characteristics of the proposed SGA to solve the STTNEP problem are detailed and an interior point method is employed to solve nonlinear programming problems during the solution steps of the SGA. Results of tests carried out with two electrical energy systems show the capabilities of the SGA and also the viability of using the AC model to solve the STTNEP problem. © 2009 IEEE.
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The GLAaS algorithm for pretreatment intensity modulation radiation therapy absolute dose verification based on the use of amorphous silicon detectors, as described in Nicolini et al. [G. Nicolini, A. Fogliata, E. Vanetti, A. Clivio, and L. Cozzi, Med. Phys. 33, 2839-2851 (2006)], was tested under a variety of experimental conditions to investigate its robustness, the possibility of using it in different clinics and its performance. GLAaS was therefore tested on a low-energy Varian Clinac (6 MV) equipped with an amorphous silicon Portal Vision PV-aS500 with electronic readout IAS2 and on a high-energy Clinac (6 and 15 MV) equipped with a PV-aS1000 and IAS3 electronics. Tests were performed for three calibration conditions: A: adding buildup on the top of the cassette such that SDD-SSD = d(max) and comparing measurements with corresponding doses computed at d(max), B: without adding any buildup on the top of the cassette and considering only the intrinsic water-equivalent thickness of the electronic portal imaging devices device (0.8 cm), and C: without adding any buildup on the top of the cassette but comparing measurements against doses computed at d(max). This procedure is similar to that usually applied when in vivo dosimetry is performed with solid state diodes without sufficient buildup material. Quantitatively, the gamma index (gamma), as described by Low et al. [D. A. Low, W. B. Harms, S. Mutic, and J. A. Purdy, Med. Phys. 25, 656-660 (1998)], was assessed. The gamma index was computed for a distance to agreement (DTA) of 3 mm. The dose difference deltaD was considered as 2%, 3%, and 4%. As a measure of the quality of results, the fraction of field area with gamma larger than 1 (%FA) was scored. Results over a set of 50 test samples (including fields from head and neck, breast, prostate, anal canal, and brain cases) and from the long-term routine usage, demonstrated the robustness and stability of GLAaS. In general, the mean values of %FA remain below 3% for deltaD equal or larger than 3%, while they are slightly larger for deltaD = 2% with %FA in the range from 3% to 8%. Since its introduction in routine practice, 1453 fields have been verified with GLAaS at the authors' institute (6 MV beam). Using a DTA of 3 mm and a deltaD of 4% the authors obtained %FA = 0.9 +/- 1.1 for the entire data set while, stratifying according to the dose calculation algorithm, they observed: %FA = 0.7 +/- 0.9 for fields computed with the analytical anisotropic algorithm and %FA = 2.4 +/- 1.3 for pencil-beam based fields with a statistically significant difference between the two groups. If data are stratified according to field splitting, they observed %FA = 0.8 +/- 1.0 for split fields and 1.0 +/- 1.2 for nonsplit fields without any significant difference.