Environmental Simulation Models Research Articles

Telescoping strategies for improved parameter estimation of environmental simulation models

The parameters of environmental simulation models are often inferred by minimizing differences between simulated output and observed data. Heuristic global search algorithms are a popular choice for performing minimization but many algorithms yield lackluster results when computational budgets are restricted, as is often required in practice. One way for improving performance is to limit the search domain by reducing upper and lower parameter bounds. While such range reduction is typically done prior to optimization, this study examined strategies for contracting parameter bounds during optimization. Numerical experiments evaluated a set of novel “telescoping” strategies that work in conjunction with a given optimizer to scale parameter bounds in accordance with the remaining computational budget. Various telescoping functions were considered, including a linear scaling of the bounds, and four nonlinear scaling functions that more aggressively reduce parameter bounds either early or late in the optimization. Several heuristic optimizers were integrated with the selected telescoping strategies and applied to numerous optimization test functions as well as calibration problems involving four environmental simulation models. The test suite ranged from simple 2-parameter surfaces to complex 100-parameter landscapes, facilitating robust comparisons of the selected optimizers across a variety of restrictive computational budgets. All telescoping strategies generally improved the performance of the selected optimizers, relative to baseline experiments that used no bounds reduction. Performance improvements varied but were as high as 38% for a real-coded genetic algorithm (RGA), 21% for shuffled complex evolution (SCE), 16% for simulated annealing (SA), 8% for particle swarm optimization (PSO), and 7% for dynamically dimensioned search (DDS). Inter-algorithm comparisons suggest that the SCE and DDS algorithms delivered the best overall performance. SCE appears well-suited for solving low-dimensional problems using a moderate computational budget, while DDS appears better suited for solving high-dimensional problems using a restricted computational budget.

Determination of Threshold Energy Level of Monopolar Defibrillation Pulses Using the Luo–Rudy Cardiomyocyte Model

The effect of defibrillation pulses of different waveforms on the Luo–Rudy cardiomyocyte model in the Cell Electrophysiology Simulation Environment (CESE) was comparatively tested. It was established that a half-sine pulse has the minimum threshold of cell excitation energy, while an exponential pulse exhibits the maximum threshold (22% increase in comparison with the half-sine pulse). The threshold energy of the trapezoidal pulse with sloped rising and falling (waveform of the first phase of bipolar pulse in imPulse AND-P automated external defibrillators at energy levels of 150 and 180 J) was only slightly (4%) higher than the threshold energy of the half-sine pulse. The threshold energy of truncated exponential pulses, which are widely used in modern defibrillators, exceeded the threshold energy of the half-sine pulse by 10-14% (depending on the decline value). These results obtained with the Luo–Rudy model differ significantly from the results obtained using the characteristic energy method with the Blair model.

Air-vegetation-soil partitioning of toxic chemicals in environmental simulation modeling

Accumulation of airborne pollutants in vegetation is an important initial step in the uptake process of the terrestrial food web, providing direct and indirect routes by which biota and, eventually, humans are exposed to chemicals. A set of algorithms for estimating atmospheric pollutant interactions in soilvegetation- air systems is developed and tested. The model incorporates significant transport pathways with appropriate parameterization and requires a relatively limited number of meteorological input data and pollutant characteristics and vegetation parameters. Testing applications include model comparison to field data in the cases of cadmium in grass and six polycyclic aromatic hydrocarbons (PAH) in maple leaves. Results indicate that the model provides a reasonable compromise between model complexity and the ability to obtain realistic data characterizing model parameters. It is well suited for screening-level assessments; and it can also be used as a component of a management-oriented and multimedia-based environmental assessment of atmospheric pollutants. On-going work is incorporating the model algorithms into a multimedia simulation framework to provide better capabilities.

Guaranteeing the quality of multidimensional analysis in data warehouses of simulation results: Application to pesticide transfer data produced by the MACRO model

Currently, the vital impact of environmental pollution on economic, social and health dimensions has been recognized. The need for theoretical and implementation frameworks for the acquisition, modeling and analysis of environmental data as well as tools to conceive and validate scenarios is becoming increasingly important. For these reasons, different environmental simulation models have been developed. Researchers and stakeholders need efficient tools to store, display, compare and analyze data that are produced by simulation models. One common way to manage simulation results is to use text files; however, text files make it difficult to explore the data. Spreadsheet tools (e.g., OpenOffice, MS Excel) can help to display and analyze model results, but they are not suitable for very large volumes of information. Recently, some studies have shown the feasibility of using Data Warehouse (DW) and On-Line Analytical Processing (OLAP) technologies to store model results and to facilitate model visualization, analysis and comparisons. These technologies allow model users to easily produce graphical reports and charts. In this paper, we address the analysis of pesticide transfer simulation results by warehousing and OLAPing data, for which the data results from the MACRO simulation model. This model simulates hydrological transfers of pesticides at the plot scale. We demonstrate how the simulation results can be managed using DW technologies. We also demonstrate how the use of integrity constraints can improve OLAP analysis. These constraints are used to maintain the quality of the warehoused data as well as to maintain the aggregations and queries, which will lead to better analysis, conclusions and decisions.

Adequacy of wireless sensor network models in simulation environments

The paper gives the analysis of existing tools for wireless sensor networks (WSN) simulation and verification of the obtained models. The objective of the research is verification of the WSN model obtained in simulation environment OMNET ++. Each of the analyzed simulation systems of wireless sensor networks allows: -increasing the WSN development efficiency; -conducting an experiment without real deployment of sensor network; -carrying out researches of WSN; -significant costs reduction for network development and deployment. The model adequacy depends on the purpose of modeling and accepted criteria. WSN simulation models development based on the simulation system OMNET++ provides adequate models. This is confirmed by the obtained results

The Three-dimensional Urban Growth Simulating Based on Cellular Automata

Research of urban growth has focused on the two-dimensional flat space,while the development of the modern city is three-dimensional.So the development and changes of the modern urban space could not be accurately described by two-dimensional method.Therefore,the research of three-dimensional urban growth has great significance to the future development of the city.Based on the theory of self-organization in urban development,the urban growth simulating model using three-dimensional cellular automata(3DCA) which proposed by Bengguigui was improved.The center distance parameter and the traffic distance parameter were added to the model.And new three-dimensional urban growth models were set up: the center distance model and the transport distance model.The two establishment steps of the model are as follows: Firstly,described the calculation methods and the economic interpretations of all the model parameters.Secondly,gave the potential development function of three-dimensional urban growth and the transition rules of the cellular state.The three-dimensional urban growth simulating experiments based on the given models was developed by NetLogo 3D.NetLogo 3D is a programmable modeling environment for natural and social phenomena simulation,which could show simulating results both in two dimension and three dimension view.The experiment results show that the three-dimensional urban growth simulating with the models proposed in this paper is more approximate to the reality city extension progress than Bengguigui's model,and also prove that the urban development is a self-organized process.

BlockSim++: 연속시스템의 계층적 모델링 및 시뮬레이션을 위한 블록기반 경량 프레임워크

본 논문은 실용 엔지니어를 위해서 일반미분방정식으로 표현될 수 있는 연속시스템의 계층적인 모델 개발을 위한 모델링 기법 및 객체지향언어 기반의 경량 시뮬레이션 구축 환경을 제안하였다. 제안된 블록 기반 모델링 형식론은 단위 모델의 동적인 행위를 나타내는 기본블록 모델과 모델들의 계층적인 구조를 나타내는 결합블록 모델 형식론으로 이루어져 있다. 이러한 수학적 모델의 시뮬레이터를 객체지향 언어로 구현하기 위한 시뮬레이션구축 프레임워크인 BlockSim++를 제안하였다. 제안된 프레임워크는 재사용성을 제공하며, 수학적 모델을 쉽게 구현할 수 있게 하고, 또한 외부 응용 소프트웨어와도 쉽게 결합할 수 있는 인터페이스를 제공한다. 간단한 하이브리드 모델링 시뮬레이션 예시를 통해 제안된 모델링 형식론과 시뮬레이션 프레임워크를 이용하여 그 유용성을 입증하였다. This paper proposes for practical engineers a lightweight modeling and simulation environment for continuous system models specified in ordinary differential equations, which are time-domain specification of such systems. We propose a block-oriented specification formalism that has two levels: one for atomic behavior and the other the structure of models. Also we provide with a simulation framework, called BlockSim++, which make models specified in the block-oriented formalism be easily translated in object-oriented program that runs with the proposed simulation framework. The proposed formalism and framework has advantage of reuse such that it can be easily integrated into application programs and heterogeneous simulators. We illustrates the usefulness of the proposed framework by a simple hybrid modeling simulation example.

Quantifying uncertainty in remotely sensed land cover maps

Remotely sensed land cover maps are increasingly used as inputs into environmental simulation models whose outputs inform decisions and policy-making. Risks associated with these decisions are dependent on model output uncertainty, which is in turn affected by the uncertainty of land cover inputs. This article presents a method of quantifying the uncertainty that results from potential mis-classification in remotely sensed land cover maps. In addition to quantifying uncertainty in the classification of individual pixels in the map, we also address the important case where land cover maps have been upscaled to a coarser grid to suit the users’ needs and are reported as proportions of land cover type. The approach is Bayesian and incorporates several layers of modelling but is straightforward to implement. First, we incorporate data in the confusion matrix derived from an independent field survey, and discuss the appropriate way to model such data. Second, we account for spatial correlation in the true land cover map, using the remotely sensed map as a prior. Third, spatial correlation in the mis-classification characteristics is induced by modelling their variance. The result is that we are able to simulate posterior means and variances for individual sites and the entire map using a simple Monte Carlo algorithm. The method is applied to the Land Cover Map 2000 for the region of England and Wales, a map used as an input into a current dynamic carbon flux model.

A Distributed Parallel Simulation Environment for Interoperability and Reusability of Models in Military Applications

Interoperability and reusability of models are main concerns in military simulation. In order to improve the interoperability and reusability of models, the model shall be separated with a particular simulation engine, and the modelling framework of models as well as the architecture of the simulation engine should be standardized. This paper describes the architecture and operational concept of simulation environment which has been developed to enhance interoperability an d reusability of models. We named this environment adaptive distributed parallel Simulation environment for Interoperable and reusable models (AddSIM). We suggested a modelling framework to promote model development, portability and interoperability with other models. Also, we proposed a layered architecture to modularise critical capabilities including kernel layer, tool/application layer, support/service layer and external interface. This means that models can be developed independently of a simulation engine and interfaced with it using API. To validate the application feasibility of AddSIM, we set up an anti-air missile engagement situation and performed simulation. In military simulation, it is expected that reusability and interoperability of models will be enhanced by using proposed AddSIM. Defence Science Journal, 2012, 62(6), pp.412-419 , DOI:http://dx.doi.org/10.14429/dsj.62.1477

A Study of the Myocardium Cell Membrane Using the Luo-Rudy Model

The Cell Electrophysiology Simulation Environment (CESE) modeling medium was used to study parameters of the myocardium cell membrane. The parameters of the model were experimentally tested using rectangular electric pulses. The growth of the transmembrane potential with respect to the resting potential increased the specific resistance, specific capacitance, and time constant τ m of the cell membrane. Comparative analysis revealed that the Weiss–Lapicque model provided most adequate description of reaction to rectangular defibrillation electric pulses.

Multicriteria generalization (MCG): a decision-making framework for formalizing multiscale environmental data reduction

Environmental simulation models need automated geographic data reduction methods to optimize the use of high-resolution data in complex environmental models. Advanced map generalization methods have been developed for multiscale geographic data representation. In the case of map generalization, positional, geometric and topological constraints are focused on to improve map legibility and communication of geographic semantics. In the context of environmental modelling, in addition to the spatial criteria, domain criteria and constraints also need to be considered. Currently, due to the absence of domain-specific generalization methods, modellers resort to ad hoc methods of manual digitization or use cartographic methods available in off-the-shelf software. Such manual methods are not feasible solutions when large data sets are to be processed, thus limiting modellers to the single-scale representations. Automated map generalization methods can rarely be used with confidence because simplified data sets may violate domain semantics and may also result in suboptimal model performance. For best modelling results, it is necessary to prioritize domain criteria and constraints during data generalization. Modellers should also be able to automate the generalization techniques and explore the trade-off between model efficiency and model simulation quality for alternative versions of input geographic data at different geographic scales. Based on our long-term research with experts in the analytic element method of groundwater modelling, we developed the multicriteria generalization (MCG) framework as a constraint-based approach to automated geographic data reduction. The MCG framework is based on the spatial multicriteria decision-making paradigm since multiscale data modelling is too complex to be fully automated and should be driven by modellers at each stage. Apart from a detailed discussion of the theoretical aspects of the MCG framework, we discuss two groundwater data modelling experiments that demonstrate how MCG is not just a framework for automated data reduction, but an approach for systematically exploring model performance at multiple geographic scales. Experimental results clearly indicate the benefits of MCG-based data reduction and encourage us to continue expanding the scope of and implement MCG for multiple application domains.

EMUSIM: an integrated emulation and simulation environment for modeling, evaluation, and validation of performance of Cloud computing applications

SUMMARYCloud computing allows the deployment and delivery of application services for users worldwide. Software as a Service providers with limited upfront budget can take advantage of Cloud computing and lease the required capacity in a pay‐as‐you‐go basis, which also enables flexible and dynamic resource allocation according to service demand. One key challenge potential Cloud customers have before renting resources is to know how their services will behave in a set of resources and the costs involved when growing and shrinking their resource pool. Most of the studies in this area rely on simulation‐based experiments, which consider simplified modeling of applications and computing environment. In order to better predict service's behavior on Cloud platforms, we developed an integrated architecture that is based on both simulation and emulation. The proposed architecture, named EMUSIM, automatically extracts information from application behavior via emulation and then uses this information to generate the corresponding simulation model. We performed experiments using an image processing application as a case study and found that EMUSIM was able to accurately model such application via emulation and use the model to supply information about its potential performance in a Cloud provider. We also discuss our experience using EMUSIM for deploying applications in a real public Cloud provider. EMUSIM is based on an open source software stack and therefore it can be extended for analysis behavior of several other applications. Copyright © 2012 John Wiley & Sons, Ltd.

Implementation and validation of simplified heat pump model in IDA-ICE energy simulation environment

Heating and cooling of buildings are responsible for a large percentage of world energy consumption. Today, ground source heat pumps offer one of the most energy efficient technologies to provide heating and cooling by using the renewable heat source of the building's surrounding ground volume. Primarily in Northern Europe these systems are becoming a common heating/cooling technology. Some currently available building simulation programs like TRNSYS or EnergyPlus have the ability to model them. In this paper a parameter estimation study of a water-to-water heat pump model, implemented in IDA-ICE simulation environment, is presented and validated using experimental data. The model is based on performance maps: user-supplied data files containing catalogue data for the delivered energy and power absorbed are based on the entering load and source temperatures. The simulation results show that, if the input parameters (e.g. heat pump typology and control operation) are known, the simulated heat-pump model corresponds closely with the experimental operation. The maximum absolute mean deviation in the predicted values is equal to 5.09, 0.94, and 5.06%, respectively, for COP, condenser water temperature, and power delivered by the heat pump in heating operation.

Jointly mapping hydraulic conductivity and porosity by assimilating concentration data via ensemble Kalman filter

Summary Real-time data from on-line sensors offer the possibility to update environmental simulation models in real-time. Information from on-line sensors concerning contaminant concentrations in groundwater allow for the real-time characterization and control of a contaminant plume. In this paper it is proposed to use the CPU-efficient Ensemble Kalman Filter (EnKF) method, a data assimilation algorithm, for jointly updating the flow and transport parameters (hydraulic conductivity and porosity) and state variables (piezometric head and concentration) of a groundwater flow and contaminant transport problem. A synthetic experiment is used to demonstrate the capability of the EnKF to estimate hydraulic conductivity and porosity by assimilating dynamic head and multiple concentration data in a transient flow and transport model. In this work the worth of hydraulic conductivity, porosity, piezometric head, and concentration data is analyzed in the context of aquifer characterization and prediction uncertainty reduction. The results indicate that the characterization of the hydraulic conductivity and porosity fields is continuously improved as more data are assimilated. Also, groundwater flow and mass transport predictions are improved as more and different types of data are assimilated. The beneficial impact of accounting for multiple concentration data is patent.

Fatigue Test and Analysis on Subframe in Fuel Cell Car

The work environment and the feature of the subframe have been discussed though the fatigue test on the subframe of original design. Fatigue simulation environment of the original subframe was established and analyzed under assistance of optimization software. After comparative analysis with test environment, the construction of the fatigue simulation environment model was considered more reasonable. Meanwhile, fatigue simulation analysis, under the original simulation model, was conducted on the subframe of new materials. After a comparative analysis with general steel subframe, it was concluded that fatigue life of new subframe was greatly improved while the lightweight.

Dynamic Simulation of Aircraft Environmental Control System Based on Flowmaster

The mathematical model and calculation method of three-wheel environmental control system with the highpressure water separation are developed in this paper. The component models are created based on the Flowmaster software platform, and the environmental control system simulation model is established using these component models. The dynamical response of environmental control system is simulated.With the simulation results, a general idea of the dynamical characteristic of the environmental control system can be determined. Then the aircraft cabin temperature control method is developed, which uses expert proportional–integral–derivative to design a coolingpack temperature controller and temperature control table based on fuzzy theory to design the cabin-zone temperature controller. Simulation of this control system is performed based on the established dynamic simulation platform, and the simulation results show that this method has good control effect.

동남권 신공항 건설에 대한 포괄적 환경영향평가 기법의 적용

The need and importance of developing and utilizing the oceans, not only as sources of renewable energy and mineral resources, but also as countermeasures to global warming such as for CCS (carbon capture and storage), have continued to increase, especially in countries with limited land areas and resources. Therefore, it is necessary to assess the sustainability of an ocean utilization technology or system not only from an economic point of view but also from an ecological one. For this purpose, it might be effective to develop a comprehensive evaluation method and/or index, by which the assessment of and decisions about a technology and system can be made more objectively. It would also be useful to have an environmental simulation model, which was developed and reported in a previous research. The aim of this study was to modify a reasonable and quantitative index, with which a comprehensive evaluation system can be established, to assess environmental sustainability and risk.

CASL virtual reactor predictive simulation: Grid-to-Rod Fretting wear

Grid-to-Rod Fretting (GTRF) wear is currently one of the main causes of fuel rod leaking in pressurized water reactors. The Consortium for Advanced Simulation of Light Water Reactors (CASL) has identified GTRF as one of the Challenge Problems that drive the requirement for the development and application of a modeling and simulation computational environment for predictive simulation of light water reactors. This paper presents fretting wear simulation methodology currently employed by Westinghouse, a CASL industrial partner, to address GTRF. The required advancements in the computational and materials science modeling areas to develop a predictive simulation environment by CASL to address GTRF are outlined.

Neural Predictive Controller Based Diesel Injection Management System for Emission Minimisation

Rapid growth in production of automobiles has increased emissions. Automotive control engineers use innovative control techniques to meet the upcoming emission standards. This paper proposes a novel method of employing artificial neural network (ANN) based predictive controller design. The controller predicts the injection duration based on the inputs from various sensors. The results are then evaluated over a simulated engine model developed in AMESim (Advanced Modelling Environment for Simulation), which ensures a green design process with almost negligible carbon foot print. The results obtained are encouraging and promotes the use of neural predictive control. Implementation of the controller will lead to emission reduction.

SNMP-based acquisition system for DiffServ parameters

Modern communication networks cannot get along without quality of service (QoS) assurance. QoS-support mechanisms offer preferential treatment for specific traffic classes that is required especially by real-time network applications. Unfortunately current QoS technologies have certain disadvantages and limitations and therefore they are not always able to guarantee the required QoS level. This paper introduces a quality of service support system that improves the most often used quality of service support technology called Differentiated Services (DiffServ). The system proposed utilizes the Simple Network Management Protocol (SNMP) for the acquisition of configuration information from the edge router of the DiffServ domain. This information is subsequently used to control the allocation of network resources within the QoS assurance process. In order to evaluate this system we used the OPNET Modeler simulation environment where we built a simulation scenario able to interact with real network components. For this purpose we implemented the SNMP protocol into the OPNET Modeler and used it for acquisition of management information, stored in the Management Information Base (MIB) of the network node. The paper describes in details the improved QoS-support mechanism and the simulation model able to cosimulate the behavior of both real and virtual network elements.