AnyLogic, ExtendSim and Simulink Overview Comparison of Structural and Simulation Modelling Systems

Compositional Simulation of Well Performance for Fractured and Multiple Fractured Horizontal Wells in Stratified Gas Condensate Reservoirs. Introduction The work for this paper has been carried out to improve development concepts in gas condensate reservoirs in the North Sea. While early North Sea oil fields were characterized by very large dimensions, thick homogeneous layers, and high permeabilities, newer discoveries have not been as blessed. Fields in the Haltenbanken area, such as Asgard have large extensions and reserves, but are found in deeper water and deep formations, characterized by hot reservoir temperatures of more than 300 degrees Fahrenheit, pressures from 7,500 to 13,000 psi, and most importantly, in heterogeneous, low permeable rocks. The need to make these high cost discoveries economic and accurate prediction of reservoir performance is more important than ever. In this context, the application of advanced well technologies such as multi-laterals and hydraulic fracturing takes on more significance. The primary advantages of fracturing are increasing productivity from low permeable rocks and improving the connectivity of the well in stratified formations (Abou-Sayed et. al. (1)). In gas condensate reservoirs, however, fracturing has additional advantages: stimulation reduces pressure drawdown and thus leads to less liquid dropout. Non-Darcy effects are minimized and the well will suffer less productivity reduction once liquid blocking occurs (Setari et. al. (2)). Simulation models developed for these applications differ from conventional approaches. The correct representation of geological features is normally the main gridding criterion. In fractured well simulation, however, the size and aspect ratio of the grid cells have a strong influence in predicting the flow behavior for different well types, fluid compositions, and recovery processes correctly. The goal of this paper is to determine practical simulation guidelines in modeling fractured well productivity in gas condensate fields. Analytical Methods Several analytical methods are available to predict the productivity and performance for vertical fractured wells. New models for horizontal wells have been developed by Babu/Odeh and Joshi, and for multiple fracture wells by Babu, Horne and Temeng, and others. Some of them have now the capability to model stratified reservoirs. The complex equations in these methods can be handled easily with the new faster PCs. Programs such as MEPFRAC/HYFRAC, a Mobil internal analytical software, can predict the productivity in time of multiple fractured wells with different fracture sizes in a stratified reservoir in only a few minutes. Unfortunately, different analytical models were found to have individual restrictions. One limitation of all analytical models is in the definition of fluids because they permit only one set of PVT data and no compositional modeling at all. Therefore, most of the methods are only highly accurate for dry gas or almost incompressible fluids but cannot model gas condensate characteristics. In most cases, simulation and analytical model results agree only during certain flow periods depending on the assumptions used in the analytical model. Another limitation is that either uniform flux or infinite conductivity descriptions are applied in the individual methods. After comparing the benefits of a number of analytical models with simulation results, our conclusion is that no analytical method is available to predict fractured well productivity reductions due to liquid effects in gas-condensate systems with sufficient detail. The only complete tool to predict this is fully-compositional simulation. Even a black oil representation is inadequate when finely-gridded models are used, since incorrect predictions result if improper fluid models are selected. See Coats and Hwang. Simulation of Fractured Wells in Coarse-Grid Gas Condensate Models Fracture representation in coarse simulation models depends on the selection of well productivity corrections derived from analytical techniques or locally fine gridded simulations. The necessary correction depends upon the timeframe, or flow regime, which needs to be treated most accurately. Figure 1 illustrates the timeframes and flow regimes for one example and the drainage patterns along fractures for infinite flow and uniform-pressure fracture systems. The flow periods begin with linear flow in the fracture and progress to pseudo-radial flow as the drainage area increases. P. 175

Although somewhat arbitrary, models can be categorized as being analytical, and/or simulation models. Analytical models are those models for which the mathematical expression can be solved in or closed form. Numerical models are those for which solutions are obtained using numerical analysis techniques, usually evaluated using a computer. Numerical models include analytical models which are implemented on a computer for ease in obtaining solutions (and generating results in graphical form) for a variety of alternative conditions. Numerical sonar models generally include analytical submodels which describe the various physical phenomena implicit in the prototype, such as spherical spreading with range and absorption loss with frequency. Numerical models also include those models for which closed-form, analytical solutions to the equations cannot be found for the conditions of interest, and, hence, require techniques to obtain solutions. Simulation Models are those models which include in some sense the dynamics of the prototype being modeled. This includes models which represent dynamic systems that produce outputs which unfold in time in response to time-varying inputs or parameters. It includes models which produce statistical realizations of the response of a system to random inputs or with randomly varying parameters, as in time series generation models for use in single or multiple Monte Carlo simulations. It is noted that simulation models can be constructed from analytical or models which produce closed-form or numerically-derived solutions, respectively, to individual stimuli; however, when the analytical or models are implemented for a contiguous sequence of dynamic stimuli, they become simulation models. Since simulation models are usually sufficiently complex to require implementation on a computer, they generally can be considered a subset within the model category.

In this paper authors propose the approach for investigation of photonic switches performance metrics in modern all-optical networks. The approach includes photonic switches analytical and simulation modeling. The analytical model of the $$4\times 4$$ -photonic switch is based on the M/M/1/4 queuing model using so-called probability translation matrix method that allows to investigate functioning of the system in transient mode. The analytical expressions of such performance metrics as a loss probability, a buffer size and a transient time are obtained. A comparison of analytical and simulation modeling results was carried out. The analysis show that the steady-state loss probability obtained in results of analytical modeling is greater than the analogous parameter obtained in results of simulation modelling by 8%. The study of simulation models of $$4\times 4$$ and $$16\times 16$$ -photonic switches show that the buffer size of these systems does not exceed one packet. Analysis of the $$16\times 16$$ -photonic switch buffer show that the buffer size of the first cascade is four times larger than the buffer of the second cascade. The results of the investigation show that the proposed type of photonic switches can be used in the high-performance all-optical network designed to transmit information from the ground module to tethered high-altitude unmanned module and vice versa.

Dual-3D hybrid fire simulation for modelling steel structures in fire with column failure

This paper analyses the effects of job release policies, priority scheduling rules and setup times on the performance of a dynamic job shop in a sequence dependent setup time environment. Two job release policies namely, immediate job release and job release based on a specified work-in-process are investigated. A simulation model of a realistic manufacturing system is developed for detailed analysis. The dynamic total work content method is adopted to assign the due dates of jobs. Six priority rules are applied for prioritizing jobs for processing on machines. Several performance criteria are considered for analyzing the system performance. The simulation results are used to conduct statistical tests. Analytical models have been formulated to represent the simulation model for post-simulation studies. These models are found to yield a satisfactory estimation of the system outputs.

Cognitive radio (CR) is currently one of the most promising information transmission technologies to deal with the problem of spectrum scarcity and spectrum underutilization in wireless communications. CR networks aim to enhance spectrum efficiency to meet the ever-increasing demands of end users. The principle is to provide the opportunity for unlicensed users (secondary users, SUs) to temporarily and dynamically access the unused or sparsely used bandwidth while ensuring that it never interferes or degrades the performance of the incumbent license holders, commonly called primary users (PUs). This raises several challenges to be addressed in CR networks and performance of secondary users is one of the critical issues tackled in this paper. That is, we propose to devise CR networks as a retrial queueing system where PUs have preemptive priority over SUs. To calculate performance measures of the devised model under quite general assumptions about the model parameters, analytical methods are known to require hard calculations and the obtained results are generally not exploitable. For this reason, simulation modeling becomes the last resort to assess the dependability indicators. To this extend, we build the simulation model of the queueing system using Timed Stochastic Colored Petri Nets. Various useful results will be hence drawn while varying network conditions. Both exponential and Erlang distributions are considered for modeling service time of SUs. The obtained results with restrictive assumptions fit the analytical outcomes experienced for quite similar queuing models, which demonstrate the effectiveness of the proposed STCPN simulation model.

Simulation modeling is an important step of a simulation study. It concerns with the creation of an efficient simulation model as accurate as needed to mimic the behavior of the underlying system and to reproduce useful observations for subsequent analysis. This introductory article discusses three main simulation modeling methods: discrete‐event simulation, continuous simulation, and agent‐based simulation. In particular, three discrete‐event simulation modeling paradigms are introduced: event scheduling, process interaction, and activity scanning. Several modeling issues are exemplified by a simple single‐server queueing system and a slightly more complex multiple‐server finite capacity queueing system with impatient customers. Continuous simulation is briefly discussed to draw the differences between discrete‐event and continuous simulations. Simulating emergent behavior as a common purpose of agent‐based simulation is demonstrated by a classic game of life model and a variation model. Monte‐Carlo simulation and other simulation modeling formalisms are briefly highlighted.

Performance simulation of software for Multiprocessor System-on-a-Chips (MPSoC) suffers from poor tool support. Cycle accurate simulation at Instruction Set Simulation level is too slow and inefficient for any design of realistic size. Behavioral simulation, though useful for functional analysis at high level, does not provide any performance information that is crucial for design and analysis of MPSoC implementations. As a consequence, designers are often reduced to manually annotate performance information onto behavioral models, which contributes further to inefficiency and inaccuracy. In this paper, we use structural performance models to provide fast and accurate simulation of software for MPSoC. We generate structural models automatically using GCC with accurate performance annotation while considering optimizations for instruction selection, branch prediction, and pipeline interlock. Our structural models are able to simulate at several orders of magnitude faster than ISS and provide less than 1% error on performance estimation. These models allow realistic MPSoC design space explorations based on performance characteristics with simulation speed comparable to behavioral simulation. We validate our simulation models with several benchmarks and demonstrate our approach with a design case study of an MPEG-2 decoder.

Analytical water quality model for biochemical oxygen demand simulation in River Gomti of Ganga Basin, India

<div class="htmlview paragraph">The simulation model presented in this report is capable of analytically predicting the dynamic responses of the unibody passenger car during a rear-end barrier impact. A 5 degree-of-freedom system consisting of a rigid barrier mass, four vehicle masses, and seven nonlinear resistances represents the vehicle impacting the barrier, or vice versa. Five equations of motion are derived and ten initial conditions are specified for the model to define an initial-value problem. Due to the complexities of force-deformation characteristics of the resistances, the solution is derived by a numerical method. A computer program in PL/I for the IBM 360/65 is developed to perform the solution. Output data are available in both numeric and graphic forms. The simulation results are in good agreement with the results of the actual barrier test. Examples of application are given to demonstrate the usefulness of the simulation model in investigating various problems of practical interest.</div>

Problem statement. Tests and intended use of rocket and space technology facilities are accompanied by monitoring of their technical condition and monitoring of various natural and man-made processes, for which various radio telemetry systems are being developed. An important task at the present stage of the development of the test base is the development and implementation of approaches to optimize the structure and composition of radio telemetry systems, as well as the characteristics of its components for the requirements of a specific flight test, including taking into account the many changing characteristics of the radio channel, depending on the type of test object, the dynamic parameters of its trajectory, the conditions of a particular test site and even the time of year. Under such conditions, simulation modeling is a tool necessary to assess the condition of a non-stationary radio channel of a radio telemetry system, to select the optimal characteristics of the radio channel equipment, as well as to conduct research on the effectiveness of certain technical solutions in the creation and further improvement of digital radio channel equipment. Goal. To consider the existing models of radio channels of communication systems and identify their main disadvantages, to develop a mathematical simulation model of a new-generation radio telemetry system with advantages over existing models, and to determine the prospects for its improvement. Results. The disadvantages of existing models of radio channels of communication systems have been identified. A new generation simulation mathematical model of a radio telemetry system has been developed, which has such advantages over existing models as accounting for the error of synchronization systems, accounting for signal attenuation due to the polarization mismatch of the transmitting and receiving antennas, accounting for the rotation of the signal source around the longitudinal axis, accounting for the movement of the signal source and receiver. The model takes into account the signal structure used, its encoding methods, digital signal processing algorithms, principles for increasing noise immunity with spaced reception, estimating the power of diffusely scattered and reflected radiation components from the underlying surface, and the model takes into account for losses caused by the influence of plasma generated by the movement of high-speed objects in dense atmospheric layers. The software implementation of the model makes it possible to calculate the reliability of receiving information (the probability of bit and packet errors, bandwidth, reception reliability), determine the optimal placement of measuring (receiving) points of various bases in accordance with the described criterion, determine the requirements for individual characteristics of the radio telemetry system, ensuring the achievement of the required information content of the system and the reliability of receiving information transmitted from the test facility, if necessary, add additional parameters and functionality to the program. Further improvement of the developed simulation model is seen in deeper consideration of the effect on the passage of the telemetric signal of the plasma envelope surrounding the test object upon entry into the dense layers of the atmosphere. Practical significance. The results can be used in the development and defining characteristics of new-generation radio telemetry systems to ensure flight tests of rocket and space technology facilities, and to conduct research on the effectiveness of certain technical solutions.

We consider an inventory system for continuous decaying items with stochastic lead time and Poisson demand. Shortage is allowed and all the unsatisfied demands are backlogged. Moreover, replenishment is one for one. Our objective is to minimize the long-run total expected cost of the system. Firstly, we have developed the mathematical model with deterministic lead time. Since the stochastic lead time makes the model complex especially when lead time has complicated probability distribution and it is difficult to prove convexity of the objective function, we have applied simulation modeling approach. The simulation model has no limitation on lead time or any other parameters. The simulation model is validated by comparing its outputs and analytical model's results for the deterministic lead time case. Furthermore, we use optimizer module of the applied software to find near optimal solutions for a number of examples with stochastic lead time.

This article presents results obtained on the development of a pseudo-random sequence generator for simulation modeling of queueing system (QS) with second-order hyperexponential input distribution. In the scientific literature on GPSS WORLD, including web resources, the authors did not find any data in this subject area. The GPSS WORLD library includes many generators of various distribution laws, but there are no generators for such important composite distributions according to the queuing theory. It is known that the hyperexponential distribution concept provides a wide range of changes in the random variable variation coefficient from unity to an arbitrarily large value. Due to the fact that the variation coefficients of arrival and service intervals play an important role in estimating the delay of queue claims in queuing systems, thus this distribution concept plays a special role in modeling of QS. For a hyperexponential distribution of the second order, the authors previously obtained numerical-analytical results based on the Lindley integral equation spectral solution method. The article describes a developed algorythm and a program on GPSS WORLD to simulate the functioning of QS with hyperexponential input distribution incl. description of operation of logical switches. The difference between analytical and simulation modeling of the two-phase representation of a given distribution concept is explained on the example of the developed model. The adequacy of the obtained results was confirmed by comparing the simulation results with the results of numerical simulation in the Mathcad environment.

Test-driven simulation modelling: A case study using agent-based maritime search-operation simulation

A production line is an important class of manufacturing system when large quantities of identical or similar products are to be produced. The performance of a production line is highly influenced by machine failures. When a machine fails, it is then be unavailable during a certain amount of time required to repair it. Analysis of production lines divides into three types: analytical, approximation and simulation models. The analytical and approximation models have assumptions, which make these models unrealistic such as reliable workstations, certain processing distribution, the first workstation cannot be starved and the last workstation cannot be blocked. The main problems in production lines treatment are the calculation of throughput and average levels of buffers because of the great size of state space. An analytical model is reviewed to clarify the limitations to use such treatment in real production lines. Simulation modeling of production lines is considered very important for designers interested in: Workload Allocation Problem (WAP), Server Allocation Problem (SAP), and Buffer Allocation Problem (BAP). This paper studies and analyzes the performance keys, which effect on production lines. A simulation model is developed by using ARENA software and used to analyze and test several bottlenecks that are causing severe congestions in different areas on the production line and could resolve all of these bottlenecks. In this paper, an actual cement production line is used as a case study. After a simulation time of 13 days, a simulation results show the line bottlenecks, workstations utilization, buffer capacities and the line production rate. The outputs clarify redesign of allocation of buffers, which verify an optimum size could be made; it might be taken into consideration when designers implement such lines. Finally modified better workstations utilization, buffer capacities and the line production rate with an increase about 15% of the production rate and economizing of 37 % from buffer capacities