Large-scale Simulation Models Research Articles

An algorithm to estimate aircraft cruise black carbon emissions for use in developing a cruise emissions inventory

To provide accurate input parameters to the large-scale global climate simulation models, an algorithm was developed to estimate the black carbon (BC) mass emission index for engines in the commercial fleet at cruise. Using a high-dimensional model representation (HDMR) global sensitivity analysis, relevant engine specification/operation parameters were ranked, and the most important parameters were selected. Simple algebraic formulas were then constructed based on those important parameters. The algorithm takes the cruise power (alternatively, fuel flow rate), altitude, and Mach number as inputs, and calculates BC emission index for a given engine/airframe combination using the engine property parameters, such as the smoke number, available in the International Civil Aviation Organization (ICAO) engine certification databank. The algorithm can be interfaced with state-of-the-art aircraft emissions inventory development tools, and will greatly improve the global climate simulations that currently use a single fleet average value for all airplanes. Implications An algorithm to estimate the cruise condition black carbon emission index for commercial aircraft engines was developed. Using the ICAO certification data, the algorithm can evaluate the black carbon emission at given cruise altitude and speed.

Sensitivity of Evacuation Performance Estimates to Evacuee Route Choice Behavior

The objective of this paper is to illustrate the sensitivity of evacuation travel time estimates in relation to assumptions about evacuee route choice behavior. The user equilibrium (UE) assignment procedure in which evacuees are assumed to choose the shortest (or fastest) path from their origins to destinations is considered as the base case. Few studies have documented the actual route choice behavior of evacuees during a hurricane. These studies were used to develop realistic route choice behavior assumptions: the types of route choices and proportion of evacuees for those types. The impact of route choice behavior on evacuation performance, especially travel times, was then explored with a large-scale regional simulation model of the Hampton Roads, Virginia, region. The model was developed in an earlier study with real-world network data and actual evacuee behavioral data. The analysis indicates that using UE to generate average travel time estimates for evacuation planning significantly underestimates the actual evacuation travel times. The extent of underestimation of evacuation travel times depends on the total evacuation demand (a function of storm intensity) and the percentage of evacuees willing to use en route information to seek alternate routes when facing congestion. For the three en route percentages reported in the literature (30%, 50%, and 70%), the UE travel times were 58%, 42%, and 33% lower than actual travel times in a Category 1 evacuation; 94%, 71%, and 58% lower than in a Category 2 evacuation; and 90%, 69%, and 54% lower than in a Category 3 evacuation.

Export Demand Elasticity Estimation for Major U.S. Crops

Elevated prices for major U.S. commodities have renewed interest in the price sensitivity of foreign demand facing the United States. Although the elasticity of foreign demand plays an important role in discussions of U.S. farm policy, it is also a parameter that is much debated with the majority of studies in this area published over 20 years ago. We provide new estimates of the elasticity of export demand for U.S. corn, soybeans, and wheat using updated data and empirical techniques. Our estimates are useful for practical policy analysis as well as for researchers seeking to parameterize large-scale simulation models.

Parallel Model Checking for Discrete Event Simulation Models Based on Event Graphs

PDF HTML阅读 XML下载 导出引用 引用提醒 基于事件图的离散事件仿真模型并行检验方法 DOI: 10.3724/SP.J.1001.2012.04047 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(61170048); 国家教育部博士点基金(200899980004) Parallel Model Checking for Discrete Event Simulation Models Based on Event Graphs Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:非形式化仿真模型验证方法易受主观因素的影响且具有不完备性,而传统的形式化模型检验方法由于受到状态空间爆炸问题的影响,很难处理大规模的仿真模型.并行模型检验方法以其完备性、高效性已经在工业界中得到了成功的应用,但是由于涉及到形式化规约、逻辑学以及并行计算等多项技术,应用难度较大.针对上述问题,提出了基于事件图的离散事件仿真模型并行检验方法.该方法首先对事件图在模型同步方面进行了扩展,给出了扩展事件图的形式化定义、语法及语义;然后将扩展事件图模型转换到分布并行验证环境的DVE 模型,成功地将并行模型检验方法应用于仿真模型验证领域.该方法使得仿真人员无须学习新的形式化验证语言就能采用并行模型检验方法对仿真模型进行形式化验证,可降低模型并行验证的难度,从而有效提高模型验证的效率和完备性.实验结果表明了该方法的有效性,有利于扩展并行模型检验方法在仿真领域中的应用. Abstract:Informal verification methods for simulation models are vulnerable to subjective ingredients. The traditional model checking method has difficulty dealing with large-scale simulation models because of the state space explosion. The parallel model checking (PMC) method has been accepted and successfully implemented in industrial tools because of the completeness and high efficiency. Unfortunately, it is hard to use as it involves several difficulties, such as formal specifications, logics, and parallel computing. To solve the above problems, a parallel model checking method for simulation models based on event graphs is proposed in this paper. This method extends event graphs in synchronization and defines the syntax and semantics of the extended event graphs. It transforms the extended event graphs to distributed and parallel verification environment (DVE) model, and PMC method is successfully applied to simulation model verification filed. With this method, simulation participators can verify simulation models with PMC method without learning new formal modeling languages. The efficiency and completeness of simulation model verification are improved. The experimental results show the validity of this method, and the method can improve the application of PMC method in simulation field. 参考文献 相似文献 引证文献

Large-Scale Computational Experiments for Complex Enterprise Systems Behaviour Prediction

Abstract This work comes as a contribution to the efforts that are undergoing within engineering systems community to account for the increased complexity of today's manufacturing or service systems. These systems are becoming more and more complicated due to the increase in the number of elements, interconnections within the system, and necessary integration with other systems. Moreover, through the emphasis on self-organization and considering the multi-stakeholders context and objectives, these systems are crossing the line towards complexity. There is a need for developing a framework to be used in modeling, analysis, and integration of systems that operate in uncertain environments, in which characteristics such as adaptation, self-organization and evolution, or in other words behavior prediction, need to be addressed. The proposed complex enterprise systems framework combines knowledge coming from complex systems science and systems engineering domains, and uses computational intelligence and agent-based systems simulation methodologies. The approach requires computational experience in manipulating large amounts of data and building large-scale simulation models. A significant result to be made possible by this research is that systems may no longer have a fixed, life-cycle long, design based on identified requirements; systems will be engineered to evolve and adapt as needed during the operational phase, while respecting their operational environment constraints.

Small-Signal Neural Models and Their Applications

This paper introduces the use of the concept of small-signal analysis, commonly used in circuit design, for understanding neural models. We show that neural models, varying in complexity from Hodgkin-Huxley to integrate and fire have similar small-signal models when their corresponding differential equations are close to the same bifurcation with respect to input current. Three applications of small-signal neural models are shown. First, some of the properties of cortical neurons described by Izhikevich are explained intuitively through small-signal analysis. Second, we use small-signal models for deriving parameters for a simple neural model (such as resonate and fire) from a more complicated but biophysically relevant one like Morris-Lecar. We show similarity in the subthreshold behavior of the simple and complicated model when they are close to a Hopf bifurcation and a saddle-node bifurcation. Hence, this is useful to correctly tune simple neural models for large-scale cortical simulations. Finaly, the biasing regime of a silicon ion channel is derived by comparing its small-signal model with a Hodgkin-Huxley-type model.

Computational models for large-scale simulations of facilitated diffusion.

The binding of site-specific transcription factors to their genomic target sites is a key step in gene regulation. While the genome is huge, transcription factors belong to the least abundant protein classes in the cell. It is therefore fascinating how short the time frame is that they require to home in on their target sites. The underlying search mechanism is called facilitated diffusion and assumes a combination of three-dimensional diffusion in the space around the DNA combined with one-dimensional random walk on it. In this review, we present the current understanding of the facilitated diffusion mechanism and identify questions that lack a clear or detailed answer. One way to investigate these questions is through stochastic simulation and, in this manuscript, we support the idea that such simulations are able to address them. Finally, we review which biological parameters need to be included in such computational models in order to obtain a detailed representation of the actual process.

Molecular mechanics modeling of azobenzene-based photoswitches

We present an extension of the generalized amber force field to allow the modeling of azobenzenes by means of classical molecular mechanics. TD-DFT calculations were employed to derive different interaction models for 4-hydroxy-4'-methyl-azobenzene, including the ground (S(0)) and S(1) excited state. For both states, partial charges and the -N = N- torsion potentials were characterized. On this basis, we pave the way to large-scale model simulations involving azobenzene molecular switches. Using the example of an isolated molecule, the mechanics of cyclic switching processes are demonstrated by classical molecular dynamics simulations.

Fluid-Based Large-Scale Bandwidth-Limited Worm Simulation Model

In this paper,based on the subnet abstraction mechanism,a fluid-based large-scale bandwidth-limited worm simulation model is proposed.In this model,the fluid simulation paradigm is leveraged to take away the huge volume of scanning traffic to reduce the requirements of computational capability and memory usage.Through extensive comparisons with the packet-level worm simulation and the measurement datasets,experiments demonstrate that the proposed simulation model is capable of high fidelity and low resource consumption,and thus,can fulfill the needs of the analysis of bandwidth-limited worm propagation characteristics and the verification of worm defense strategies.

ESTIMATING WITHIN-HOUSEHOLD CONTACT NETWORKS FROM EGOCENTRIC DATA.

Acute respiratory diseases are transmitted over networks of social contacts. Large-scale simulation models are used to predict epidemic dynamics and evaluate the impact of various interventions, but the contact behavior in these models is based on simplistic and strong assumptions which are not informed by survey data. These assumptions are also used for estimating transmission measures such as the basic reproductive number and secondary attack rates. Development of methodology to infer contact networks from survey data could improve these models and estimation methods. We contribute to this area by developing a model of within-household social contacts and using it to analyze the Belgian POLYMOD data set, which contains detailed diaries of social contacts in a 24-hour period. We model dependency in contact behavior through a latent variable indicating which household members are at home. We estimate age-specific probabilities of being at home and age-specific probabilities of contact conditional on two members being at home. Our results differ from the standard random mixing assumption. In addition, we find that the probability that all members contact each other on a given day is fairly low: 0.49 for households with two 0-5 year olds and two 19-35 year olds, and 0.36 for households with two 12-18 year olds and two 36+ year olds. We find higher contact rates in households with 2-3 members, helping explain the higher influenza secondary attack rates found in households of this size.

A Comparative Study of the Probabilistic-Collocation and Experimental-Design Methods for Petroleum-Reservoir Uncertainty Quantification

Summary Reservoir modeling and simulation are subject to significant uncertainty, which usually arises from heterogeneity of the geological formation and deficiency of measured data. Uncertainty quantification, thus, plays an important role in reservoir simulation. In order to perform accurate uncertainty analysis, a large number of simulations are often required. However, it is usually prohibitive to do so because even a single simulation of practical large-scale simulation models may be quite time consuming. Therefore, efficient approaches for uncertainty quantification are a necessity. The experimental-design (ED) method is applied widely in the petroleum industry for assessing uncertainties in reservoir production and economic appraisal. However, a key disadvantage of this approach is that it does not take into account the full probability-density functions (PDFs) of the input random parameters consistently—that is, the full PDFs are not used for sampling and design but used only during post-processing, and there is an inherent assumption that the distributions of these parameters are uniform (during sampling), which is rarely the case in reality. In this paper, we propose an approach to deal with arbitrary input probability distributions using the probabilistic-collocation method (PCM). Orthogonal polynomials for arbitrary distributions are first constructed numerically, and then PCM is used for uncertainty propagation. As a result, PCM can be applied efficiently for any arbitrary numerical or analytical distribution of the input parameters. It can be shown that PCM provides optimal convergence rates for linear models, whereas no such guarantees are provided by ED. The approach is also applicable to discrete distributions. PCM and ED are compared on a few synthetic and realistic reservoir models. Different types of PDFs are considered for a number of reservoir parameters. Results indicate that, while the computational efforts are greatly reduced compared to Monte Carlo (MC) simulation, PCM is able to accurately quantify uncertainty of various reservoir performance parameters. Results also reveal that PCM is more robust, more accurate, and more efficient than ED for uncertainty analysis.

Modeling and Control of Diabetes: Towards the Artificial Pancreas

AbstractThe paper offers a survey of some major simulation and control issues associated with the development of an Artificial Pancreas. The main topics include the role of large-scale simulation models used to carry out in silico trials, the discussion of the specific features of the glucose control problem, the layered architecture of the artificial pancreas, and the controller tuning strategies adopted to achieve individualization of the glucose control algorithm.

LUCI: A facility at DUSEL for large-scale experimental study of geologic carbon sequestration

LUCI, the Laboratory for Underground CO2 Investigations, is an experimental facility being planned for the DUSEL underground laboratory in South Dakota, USA. It is designed to study vertical flow of CO2 in porous media over length scales representative of leakage scenarios in geologic carbon sequestration. The plan for LUCI is a set of three vertical column pressure vessels, each of which is ~500 m long and ~1 m in diameter. The vessels will be filled with brine and sand or sedimentary rock. Each vessel will have an inner column to simulate a well for deployment of down-hole logging tools. The experiments are configured to simulate CO2 leakage by releasing CO2 into the bottoms of the columns. The scale of the LUCI facility will permit measurements to study CO2 flow over pressure and temperature variations that span supercritical to subcritical gas conditions. It will enable observation or inference of a variety of relevant processes such as buoyancy-driven flow in porous media, JouleThomson cooling, thermal exchange, viscous fingering, residual trapping, and CO2 dissolution. Experiments are also planned for reactive flow of CO2 and acidified brines in caprock sediments and well cements, and for CO2-enhanced methanogenesis in organic-rich shales. A comprehensive suite of geophysical logging instruments will be deployed to monitor experimental conditions as well as provide data to quantify vertical resolution of sensor technologies. The experimental observations from LUCI will generate fundamental new understanding of the processes governing CO2 trapping and vertical migration, and will provide valuable data to calibrate and validate large-scale model simulations. © 2010 Elsevier Ltd. All rights reserved

Streamflow trends in Europe: evidence from a dataset of near-natural catchments

Abstract. Streamflow observations from near-natural catchments are of paramount importance for detection and attribution studies, evaluation of large-scale model simulations, and assessment of water management, adaptation and policy options. This study investigates streamflow trends in a newly-assembled, consolidated dataset of near-natural streamflow records from 441 small catchments in 15 countries across Europe. The period 1962–2004 provided the best spatial coverage, but analyses were also carried out for longer time periods (with fewer stations), starting in 1932, 1942 and 1952. Trends were calculated by the slopes of the Kendall-Theil robust line for standardized annual and monthly streamflow, as well as for summer low flow magnitude and timing. A regionally coherent picture of annual streamflow trends emerged, with negative trends in southern and eastern regions, and generally positive trends elsewhere. Trends in monthly streamflow for 1962–2004 elucidated potential causes for these changes, as well as for changes in hydrological regimes across Europe. Positive trends were found in the winter months in most catchments. A marked shift towards negative trends was observed in April, gradually spreading across Europe to reach a maximum extent in August. Low flows have decreased in most regions where the lowest mean monthly flow occurs in summer, but vary for catchments which have flow minima in winter and secondary low flows in summer. The study largely confirms findings from national and regional scale trend analyses, but clearly adds to these by confirming that these tendencies are part of coherent patterns of change, which cover a much larger region. The broad, continental-scale patterns of change are mostly congruent with the hydrological responses expected from future climatic changes, as projected by climate models. The patterns observed could hence provide a valuable benchmark for a number of different studies and model simulations.

An Interval-Based Metamodeling Approach to Simulate Material Handling in Semiconductor Wafer Fabs

In this paper, we propose a new efficient metamodeling approach as a simulation platform to estimate the performance of automated material handling systems (AMHS) in a much shorter execution time. Our new mechanism is based on imprecise probabilities, in which the simulation model parameters are represented as intervals to incorporate unknown dependency relationships as total uncertainties. The interval-based metamodel provides reasonably accurate and fast estimates of the performance measures of interest. The performance measures from the interval-based simulation are represented as intervals that enclose the traditional real-valued simulation estimates. Using the SEMATECH virtual fab as a test bed, the metamodel of the wafer fab AMHS is implemented in JSim, a java-based discrete-event simulation environment, and the results are compared to the detailed large-scale simulation model to investigate the validity of the proposed approach.

Simulation of Exclusive Truck Facilities on Urban Freeways

This paper assesses the impact of exclusive truck facilities on urban freeway performance. A large-scale regional microscopic traffic simulation model is developed for morning and afternoon peak hours and is used to model two alternative truckway configurations in the Greater Toronto Area, including a truck-only highway and a truck lane conversion on Highway 401. Demand inputs to the microsimulation model are generated by a regional transportation demand model that provides origin-destination matrices for light, medium, and heavy trucks and passenger cars. Plug-ins are developed to represent a truck-only lane in the simulation environment. The simulation model is successfully calibrated to reflect observed road counts and to produce realistic congestion patterns. The effect of infrastructure changes on travel distances, travel times, exclusive truck lane usage, and travel speeds is assessed. Microscopic simulation allows queuing formation/dissipation and bottlenecks to be represented and allows for separate analysis of truck and car performance. Addition of a 4-lane truck-only highway results in greater travel time improvements for trucks, and it sometimes results in shifting of traffic bottlenecks on Highway 401 to downstream locations. Conversion of a freeway lane on Highway 401 results in increased congestion for passenger cars, but improved travel speeds for trucks. Both scenarios show truck facility usage ranges from 100 to 800 trucks per hour per direction.

Development of a Large-Scale Traffic Simulation Model for Hurricane Evacuation—Methodology and Lessons Learned

This paper focuses on traffic modeling of large-scale hurricane evacuation networks. Several research efforts to date have addressed the evacuation problem from a local perspective. The largest network found in the open literature on microscopic simulation of evacuation operations was of an area 45 miles long and 15 miles wide. The current study models 10 cities with a total length of approximately 2,000 miles of roadway including freeways, arterials, and local streets in two regions in Virginia--the Hampton Roads region and the city of Richmond. This research accomplished the following objectives: (1) estimate the traffic performance of evacuation routes and other major arterial streets; (2) locate the major bottlenecks, congestion, or other operational difficulties in the network; (3) estimate the total network evacuation time; and 4) recommend amendments to the traffic control plan to improve the traffic performance. The simulation results led to the following conclusions: (1) for a category 4 storm with high hotel occupancy, almost all vehicles (99%) were able to exit the network by the end of 27 h; (2) traffic demand on I-64 exceeded capacity for the section between I-64/Fort Eustis Blvd. and I-64/I-295 interchanges, significantly reducing the speed of evacuating vehicles; (3) the reversed lanes can carry more vehicles than their current assigned demand; and (4) for a category 3 storm, the throughput values for different evacuation routes are nearly the same with or without lane reversal. The modeling lessons learned from this research are also documented in the paper. For the network model development, geographic information system maps and a text processing scripting language (e.g., PERL) are shown to be useful tools. Parallel processing is recommended, especially for conducting statistical analysis of output data, given the enormously high run times (25-30 h in the current research) for the detailed simulations. The limitations of microscopic simulation in handling large-scale networks are identified and remedies are suggested.

Dielectric Constants of Simple Liquids: Stockmayer and Ellipsoidal Fluids

Coarse-grained models of molecular interactions are of interest because they convey the essence of molecular interactions in simple and easy to understand form. However, coarse-grained models fail to adequately predict some material properties, such as the failure of the Stockmayer model to reproduce the dielectric behavior of highly polar liquids. We examine the behavior of the Stockmayer fluid over a range of dipole densities that covers known organic solvents, as well as that of an ellipsoidal Stockmayer-like fluid, using NVT rigid-body Monte Carlo simulations. Both fluids are examined under different electrostatic boundary conditions and ensemble sizes. While the Stockmayer model predicts that liquids of similar dipole density to acetonitrile would be ferroelectric and have a dielectric constant far higher than shown by experiment, the ellipsoidal model provides a better accounting of dielectric behavior. This result bodes well for the use of coarse-grained solvent models for large-scale simulations.

Parallelization of a Commercial Streamline Simulator and Performance on Practical Models

SummaryWe present the parallelization of a commercial streamline simulator to multicore architectures based on the OpenMP programming model and its performance on various field examples. This work is a continuation of recent work by Gerritsen et al. (2009) in which a research streamline simulator was extended to parallel execution.We identified that the streamline-transport step represents approximately 40-80% of the total run time. It is exactly this step that is straightforward to parallelize owing to the independent solution of each streamline that is at the heart of streamline simulation. Because we are working with an existing large serial code, we used specialty software to quickly and easily identify variables that required particular handling for implementing the parallel extension. Minimal rewrite to existing code was required to extend the streamline-transport step to OpenMP. As part of this work, we also parallelized additional run-time code, including the gravity-line solver and some simple routines required for constructing the pressure matrix. Overall, the run-time fraction of code parallelized ranged from 0.50 to 0.83, depending on the transport physics being considered.We tested our parallel simulator on a variety of large models including SPE 10, Forties-a UK oil/water model, Judy Creek-a Canadian waterflood/water-alternating-gas (WAG) model, and a South American black-oil model. We noted overall speedup factors from 1.8 to 3.3x for eight threads. In terms of real time, this implies that large-scale streamline simulation models as tested here can be simulated in less than 4 hours. We found speedup results to be reasonable when compared with Amdahl's ideal scaling law. Beyond eight threads, we observed minimal speedups because of memory bandwidth limits on our test machine.

Modeling Low Climate Stabilization with E3MG:1 Towards a ‘New Economics’ Approach to Simulating Energy-Environment-Economy System Dynamics

The literature on climate stabilization modeling largely refers to either energy-system or inter-temporal computable general equilibrium/optimal growth models. We contribute with a different perspective by deploying a large-scale macro-econometric hybrid simulation model of the global energy-environment-economy (E3MG) adopting a “New Economics” approach. We use E3MG to assess the implications of a low-stabilization target of 400ppm CO2 equivalent by 2100, assuming both fiscal instruments and regulation. We assert that if governments adopt more stringent climate targets for rapid and early decarbonization, such actions are likely to induce more investment and increased technological change in favor of low-carbon alternatives. Contrary to the conventional view on the economics of climate change, a transition towards a low-carbon society as modeled with E3MG leads to macroeconomic benefits, especially in conditions of unemployment, with GDP slightly above a reference scenario, depending on use of tax or auction revenues. In addition, more stringent action can lead to higher benefits.