Simulation Of Physical Processes Research Articles

Simulation of Physical Processes in Flow-Injection System with Electrochemiluminescent Detector

Simulation of Physical Processes in Flow-Injection System with Electrochemiluminescent Detector

Process simulation and CFD calculations for the development of an innovative baled biomass-fired combustion chamber

This present work shows that the joint application of process simulation and computational fluid dynamics (CFD) is a helpful tool for the design and optimisation of complex and innovative concepts in chemical engineering practice. The application of these tools to the presented concept of a baled biomass-fired combustion chamber enables the optimisation of operation parameters such as the flue gas recirculation rate and excess air supply. Moreover numerous variations of the detailed engineering of the involved apparatuses can be simulated before realisation. The major goals comprise the maximisation of the thermal efficiency and the reduction of gaseous and particulate matter emissions. To meet these goals it is rather important to have available validated mathematical models with sharpened model parameters. Therefore the presented model approaches have been validated and refined using results from extensive combustion experiments conducted at an existing 2 MW pilot plant. Several modelling approaches are presented that especially focus on the treatment of the heterogeneous combustion and prediction of gaseous emissions such as carbon monoxide and nitrogen oxide. With validated models on a sound physical basis, process simulation and computational fluid dynamics enable a significant reduction of the development costs and the time-to-market of innovative chemical engineering concepts.

Efficient reversal of the intraprocedural flow of control in adjoint computations

Numerical simulations of physical, chemical, and economical processes play an increasingly important role in modern science and engineering. The implementation of mathematical models of real-world applications on a computer facilitates both the speed and the depth of our understanding of the behavior of the respective systems. Derivative models of the computer programs are required to make the transition from pure simulation to the highly desirable optimization of the numerical models with respect to a potentially very large number of input parameters. Such models can be generated automatically from the given numerical program by a source transformation technique known as automatic differentiation. Reversal of the control flow is especially important for the generation of adjoint derivative models. We describe an approach to the control flow reversal of structured programs motivated by the significant weakness of approaches that do not exploit the result of control-flow analysis. Our approach is used to automatically generate adjoint code for numerical programs by semantic source transformation. After a short introduction to applications and the implementation tool set, we motivate the proposed approach with a simple example. We present a novel preaccumulation algorithm for local Jacobian matrices at the level of basic blocks. The main part of the paper covers the reversal of structured control flow graphs. First we show the algorithmic steps for simple branches and loops. We give a detailed algorithm for the reversal of arbitrary combinations of loops and branches based only on the structural information in a general control flow graph. Dependencies between computations and their enclosing control flow constructs can lead to inefficient adjoint code. We formulate a set of conditions that allows for considerable efficiency gains in the adjoint code while permitting a reasonably simple modification of the reversal algorithms for specially designated control flow subgraphs. We present a sensitivity computation of an oceanographic application that illustrates the benefits of this modified approach.

Adaptive Algebraic Multigrid

Efficient numerical simulation of physical processes is constrained by our ability to solve the resulting linear systems, prompting substantial research into the development of multiscale iterative methods capable of solving these linear systems with an optimal amount of effort. Overcoming the limitations of geometric multigrid methods to simple geometries and differential equations, algebraic multigrid methods construct the multigrid hierarchy based only on the given matrix. While this allows for efficient black-box solution of the linear systems associated with discretizations of many elliptic differential equations, it also results in a lack of robustness due to unsatisfied assumptions made on the near null spaces of these matrices. This paper introduces an extension to algebraic multigrid methods that removes the need to make such assumptions by utilizing an adaptive process. Emphasis is on the principles that guide the adaptivity and their application to algebraic multigrid solution of certain symmetric positive-definite linear systems.

Rheological behavior of continuous roll casting process of aluminum alloy

The rheological behavior of aluminum alloy and its influencing factors in physical simulation of continuous roll casting process were studied by using a Gleeble-1500 thermal-mechanical simulation tester with a set of special clamp system. The relationships between the flow stress and the strain rate in the deformation process of simulating roll casting experiment were obtained. The results show that four different characteristic stages exist in the temperature range of the whole rheological process. The first occurs when the temperature is higher than 600 °C, which belongs to the creep deformation stage; the second occurs when the temperature lies in the range of 500–600 °C, and it can be regarded as the high temperature and low stress level deformation stage; the third occurs when the temperature decreases to the range of 300–500 °C, it is considered to be the middle stress level deformation stage; the last occurs when the temperature is less than 300 °C and the strain rate is less than 1.00 s−1, it belongs to middle stress level deformation stage. But when the strain rate is larger than 1.00 s−1, it belongs to the high stress level deformation stage. And the relative constitutive models suitable for the four different stages of continuous roll casting process were established through multivariate linear regression analysis of the experimental data.

Analysis of a molten carbonate fuel cell: Numerical modeling and experimental validation

A detailed dynamic model incorporating geometric resolution of a molten carbonate fuel cell (MCFC) with dynamic simulation of physical and electrochemical processes in the stream-wise direction is presented. The model was developed using mass and momentum conservation, electrochemical and chemical reaction mechanisms, and heat-transfer. Results from the model are compared with data from an experimental MCFC unit. Furthermore, the model was applied to predict dynamic variations of voltage, current and temperature in an MCFC as it responds to varying load demands. The voltage was evaluated using two different approaches: one applying a model developed by Yuh and Selman [C.Y. Yuh, J.R. Selman, The polarization of molten carbonate fuel cell electrodes: I. Analysis of steady-state polarization data, J. Electrochem. Soc. 138 (1991) 3642–3648; C.Y. Yuh, J.R. Selman, The polarization of molten carbonate fuel cell electrodes: II. Characterization by AC impedance and response to current interruption, J. Electrochem. Soc. 138 (1991) 3649–3655] and another applying simplified equations using average local temperatures and pressures. The results show that both models can be used to predict voltage and dynamic response characteristics of an MCFC and the model that uses the more detailed Yuh and Selman approach can predict those accurately and consistently for a variety of operating conditions.

Definability as hypercomputational effect

The classical simulation of physical processes using standard models of computation is fraught with problems. On the other hand, attempts at modelling real-world computation with the aim of isolating its hypercomputational content have struggled to convince. We argue that a better basic understanding can be achieved through computability theoretic deconstruction of those physical phenomena most resistant to classical simulation. From this we may be able to better assess whether the hypercomputational enterprise is proleptic computer science, or of mainly philosophical interest.

Physical Simulation of Powder Injection Process in a Torpedo‐car

Through systematical physical simulation of powder injection process in a torpedo‐car, the influences of operation parameters on process variables such as uniform mixing time, powder penetration ratio and residence time are determined. The relationships between the operation parameters and the process variable are obtained using linear regression method. Finally, the optimum operation parameters for powder injection are found using multi‐objective nonlinear programming method.

Bipolar SCR ESD devices

This paper presents a review of the recent studies based on the concept of Bipolar Silicon Controlled Rectifier (BSCR) devices across a variety of BiCMOS technologies. Examples of both BSCR design and application are presented, ranging from a 0.25 μm Si–Ge process with a shallow epi-layer, up to 250 V bipolar process. The BSCR device characteristics are discussed based on both 2-D physical process and device simulation and by the test structure ESD characterization.

A TCAD system for VLSI implementation of the CVD process using VHDL

Technology computer-aided design (TCAD) is essential for the design of modern integrated circuit fabrication processes. TCAD tools must not only model real processes accurately, to allow predictive simulation during technology research and development, but must work together as an integrated system to allow efficient exploration of new technology options and to perform numerical experiments. Cellular automata (CAs) have been applied successfully to the simulation of several physical systems and processes, and have been extensively used as VLSI architecture. This paper describes a TCAD system for the simulation of the two-dimensional (2-D) chemical vapor deposition (CVD) process. The TCAD system is fully automated and is also able to support, the hardware implementation of the corresponding CA algorithm, leading to its execution by dedicated parallel processor. The obtained simulation profiles of the CVD process are in very good qualitative agreement with experimental and simulation results found in the literature. The proposed system produces as output the corresponding VHDL code, which leads to the very large-scale integrated (VLSI) implementation of the CA algorithm. Furthermore, a user-friendly interface that enables easy and effective interaction between the user and the TCAD system has been developed. No prior knowledge of VHDL is required by the user. The produced VHDL code is synthesizable and can be used for the automated design of the corresponding VLSI system, using a commercial VLSI CAD system.

A CAD system for the construction and VLSI implementation of Cellular Automata algorithms using VHDL

Cellular Automata (CAs) are models of physical systems where space and time are discrete and interactions are only local. CAs are very effective in simulating physical systems and solving scientific problems, because they can capture the essential features of systems in which global behaviour arises from the collective effect of simple components which interact locally. CAs have been applied successfully to the simulation of several physical systems and processes, and have been extensively used as a very large-scale integrated (VLSI) architecture. We present a CAD system that builds a bridge between CAs as models of physical systems and processes, and CAs as a VLSI architecture. The inputs to our CAD system are the CA dimensionality, lattice size, local rule, and the initial and boundary conditions imposed by the particular problem. Our system produces as output the corresponding VHDL code, which leads to VLSI implementation of the CA algorithm. No prior knowledge of VHDL is required by the user. We have tested our CAD system using well-known one- and two-dimensional CAs, namely the game of life and the rule 90 CAs. The VHDL code produced in all these cases has been used for the automated design of the corresponding VLSI system, using a commercial VLSI CAD system. Simulations of the operation of these VLSI systems showed that the corresponding CA has been successfully implemented into hardware.

Observation and Numerical Simulation of Cloud Physical Processes Associated with Torrential Rain of the Meiyu Front

Cloud micro-physical structures in a precipitation system associated with the Meiyu front are observed using the balloon-borne Precipitation Particle Image Sensor at Baoshan observatory station, Shanghai during June and July 1999. The vertical distributions of various cloud particle size, number density, and mass density are retrieved from the observations. Analyses of observations show that ice-phase particles (ice crystals, graupel, snowflakes, and frozen drops) often exist in the cloud of torrential rain associated with the Meiyu front. Among the various particles, ice crystals and graupel are the most numerous, but graupel and snow have the highest mass density. Ice-phase particles coexist with liquid water droplets near the 0°C level. The graupel is similarly distributed with height as the ice crystals. Raindrops below the 0°C level are mainly from melted grauple, snowflakes and frozen drops. They may further grow larger by coalescence with smaller ones as they fall from the cloud base. Numerical simulations using the non-hydrostatic meso-scale model MM5 with the Reisner graupel explicit moisture scheme confirm the main observational results. Rain water at the lower level is mainly generated from the melting of snow and graupel falling from the upper level where snow and graupel are generated and grown from collection with cloud and rain water. Thus the mixed-phase cloud process, in which ice phase coexists and interacts with liquid phase (cloud and rain drops), plays the most important role in the formation and development of heavy convective rainfall in the Meiyu frontal system.

Color interpolation algorithms in visualizing results of numerical simulations.

The paper addresses the application of graphical replenishment (GR) color interpolation algorithms for visualizing numerical simulation of physical processes in order to enhance the information density of the graphic interpretation of these processes. The GR algorithms presented here may be successfully applied to two- and three-dimensional grids, and grids of various structures.

A cellular automaton methodology for the simulation of integrated circuit fabrication processes

This paper presents a methodology for the simulation of physical processes with local interactions using cellular automata. Such processes are common in integrated circuit fabrication, and their simulation presents one of the most difficult problems in developing technology computer aided design (TCAD) systems. The simulated integrated circuit fabrication processes considered are lithography, oxidation, and deposition processes. The proposed methodology establishes the ability to capture the essential features of these integrated circuit fabrication processes and to translate them into a suitable form, in order to obtain an effective cellular automaton model, for each process. Several numerical experiments were carried out, in this work, using the cellular automaton algorithms obtained, and their results were found to be in very good agreement with published experimental results. Furthermore, cellular automaton algorithms exploit the inherent parallelism of the cellular automaton model and run fast on serial computers.

Simulation of Sand Production in Unconsolidated Heavy Oil Reservoirs

Abstract Previous research on sand production prediction focused on when sand will be produced during depletion based on some mechanics analyses, but the amount of sand production was ignored. Recently, more and more researchers are focussing on the simulation of heavy oil sand production processes. For an unconsolidated heavy oil reservoir which employs sand production to enhance production, the amount of sand production is of great importance, because too much sand production may cause near wellbore instability, while too little sand production may not maximize well productivity. In view of this, based on both fluid flow modelling and reservoir mechanics concepts, a coupled heavy oil/sand particulate flow/reservoir elasto-plastic deformation model is used to simulate sand production, oil production, and reservoir deformation. With this model, we can determine an optimum flow rate which will not cause near wellbore instability while maximizing well productivity. Introduction Heavy oil sand production as an important production enhancement measure has been used in the primary development of heavy oil reservoirs in Canada for a long time. The production of sand may lead to the change of formation flow-related parameters such as permeability, porosity and mechanical parameters such as cohesion, and it also causes near wellbore stress redistribution. Thus, sand production is a very complicated process involving both fluid flow and geomechanical problems. In order to simulate the effect of sand production and productivity enhancement, simulation of the physical process needs to be done. Because of the long history of cold production, the simulation of cold production is becoming mature and a lot of excellent work has been done by experts in Canada and elsewhere around the world(1–5). Wang(1) developed a model to predict sand production in a heavy oil reservoir in Frog Lake at Lloydminster, Canada. It is believed that reservoir depletion induces stress concentrations around the wellbore, and large drawdown causes a foamy oil zone, in which large drawdown and seepage forces are created which causes sand production. A fully coupled geomechanical, foamy oil flow model was developed. Sand production is assumed to start when the effective radial stress is equal to the tensile strength. Later Wang(2) developed a coupled reservoir-geomechanical model to simulate the enhanced production phenomena in both heavy oil reservoirs (Northwestern Canada) and conventional oil reservoirs (North Sea). It is believed that the production enhancement is contributed:by the reservoir porosity and permeability improvement after a large amount of sand is produced, andby the higher mobility of the fluid due to the movement of the sand particles. Once the reservoir formation yields plastically, loose sand particles can be generated. Sand production has been postulated as a critical condition when the effective radial stress reaches the tensile strength or when the plastic strain reaches the critical plastic strain. Recently, Papamichos et al.(3) and Stavropoulou et al.(4) also provided their model to simulate sand production. Later Papamichos et al.(5) applied successfully this model to interpret sand production from a North Sea reservoir.

Shadowing breakdown and large errors in dynamical simulations of physical systems.

Simulations play a crucial role in the modern study of physical systems. A major open question for long dynamical simulations of physical processes is the role of discretization and truncation errors in the outcome. A general mechanism is described that can cause extremely small noise inputs to result in errors in simulation statistics that are several orders of magnitude larger. A scaling law for the size of such errors in terms of the noise level and properties of the dynamics is given. This result brings into question trajectory averages that are computed for systems with particular dynamical behaviors, in particular, systems that exhibit fluctuating Lyapunov exponents or unstable dimension variability.

Accelerating Convergence in Stochastic Particle Dispersion Simulation Codes

Recent work in adaptive importance sampling is applied to Markov chain models for Monte Carlo simulations. When this technique is incorporated into the simulation of physical processes, it can give orders-of-magnitude improvement in convergence times relative to standard approaches. We review the related methodology and illustrate its application.

Surface wavelets: a multiresolution signal processing tool for 3D computational modelling

AbstractIn this paper, we provide an introduction to wavelet representations for complex surfaces (surface wavelets), with the goal of demonstrating their potential for 3D scientific and engineering computing applications. Surface wavelets were originally developed for representing geometric objects in a multiresolution format in computer graphics. These wavelets share all of the major advantages of conventional wavelets, in that they provide an analysis tool for studying data, functions and operators at different scales. However, unlike conventional wavelets, which are restricted to uniform grids, surface wavelets have the power to perform signal processing operations on complex meshes, such as those encountered in finite element modelling. This motivates the study of surface wavelets as an efficient representation for the modelling and simulation of physical processes. We show how surface wavelets can be applied to partial differential equations, stated either in integral form or in differential form. We analyse and implement the wavelet approach for a model 3D potential problem using a surface wavelet basis with linear interpolating properties. We show both theoretically and experimentally that an O(h) convergence rate, hn being the mesh size, can be obtained by retaining only O((logN) 7/2N) entries in the discrete operator matrix, where N is the number of unknowns. The principles described here may also be extended to volumetric discretizations. Copyright © 2001 John Wiley & Sons, Ltd.

Model study of Lakes Shinji and Nakaumi — a coupled coastal lagoon system

To understand the physical and biological processes that occur in Lakes Shinji and Nakaumi, a coastal lagoon system, a hydrodynamic–ecological coupled model was applied. The model was run to hindcast these processes from March 1, 1995 to the end of September 1995. The simulation of physical processes suggests that the meteorologically induced sea level variation and a large episodic amount of freshwater discharge effectively caused the water exchange between the open sea and this lagoon system. The simulated results of the biological processes using the ecological model show good agreement with field data except for the phosphate concentration in the bottom water. It was also found that the microbiological processes in the water column, as well as in the sediment, contribute largely to the formation of oxygen-depleted water in the bottom layer. It was also clarified from the simulation that the two species of benthic bivalve, which have dense populations in this lagoon system, play important roles on removing organic particulate matter and nutrients from the system.

AquaFarm: simulation and decision support for aquaculture facility design and management planning

Development and application of a software product for aquaculture facility design and management planning are described (AquaFarm, Oregon State University©). AquaFarm provides: (1) simulation of physical, chemical, and biological unit processes; (2) simulation of facility and fish culture management; (3) compilation of facility resource and enterprise budgets; and (4) a graphical user interface and data management capabilities. These analytical tools are combined into an interactive, decision support system for the simulation, analysis, and evaluation of alternative design and management strategies. The quantitative methods and models used in AquaFarm are primarily adapted from the aquaculture science and engineering literature and mechanistic in nature. In addition, new methods have been developed and empirically based simplifications implemented as required to construct a comprehensive, practically oriented, system level, aquaculture simulator. In the use of AquaFarm, aquaculture production facilities can be of any design and management intensity, for purposes of broodfish maturation, egg incubation, and/or growout of finfish or crustaceans in cage, single pass, serial reuse, water recirculation, or solar-algae pond systems. The user has total control over all facility and management specifications, including site climate and water supplies, components and configurations of fish culture systems, fish and facility management strategies, unit costs of budget items, and production species and objectives (target fish weights/states and numbers at given future dates). In addition, parameters of unit process models are accessible to the user, including species-specific parameters of fish performance models. Based on these given specifications, aquaculture facilities are simulated, resource requirements and enterprise budgets compiled, and operation and management schedules determined so that fish production objectives are achieved. When facility requirements or production objectives are found to be operationally or economically unacceptable, desired results are obtained through iterative design refinement. Facility performance is reported to the user as management schedules, summary reports, enterprise budgets, and tabular and graphical compilations of time-series data for unit process, fish, and water quality variables. Application of AquaFarm to various types of aquaculture systems is demonstrated. AquaFarm is applicable to a range of aquaculture interests, including education, development, and production.