Process-oriented Simulation Model Research Articles

A process-oriented simulation model for common cause failures

Abstract A process-oriented simulation model (POS-model) for common cause failures (CCF) is presented. This model consists of the following sequence of stochastic variables: time of CCF impact, number of components in the group affected by the impact, times of failure of the impacted components, time of detection of the CCF-process. As compared to the considerable number of modeling approaches that directly yield expressions for the probability of the number of failed components the POS-model seems more complicated but – thanks to a variety of interesting properties – might be useful as a complementary analytical tool. The results of a couple of applications to available field data are presented. In these exploratory examples, the adaptability of the POS-model is demonstrated and results are compared with various other modeling approaches. Finally, further planned development steps for the POS-model are addressed, primarily the optimization of parameter estimation.

From digital models to numerical analysis for mechanised tunnelling: A fully automated design-through-analysis workflow

Large infrastructure projects involving the construction of tunnels in urban areas constitute complex, integrated and multi-disciplinary systems, which require building and construction information modelling as well as computational design assessment tools for decision making during all project phases and during their complete life cycle. Even if the underlying information needed for computational analysis is stored in an information model, the translation to computational models is still cumbersome and requires significant manual work for model generation and set-up as well as excessive computing resources and time. To address these shortcomings, this paper presents a systematic summary of concepts for integrated information modelling, numerical analysis and visualisation for urban mechanized tunnelling. Our first approach “BIM-to-FEM” is characterised by a fully automated link for error-free data exchange between a standalone Tunnelling Information Model and the process-oriented simulation model for mechanized tunnelling “ekate”. In the second approach “SATBIM”, a fully automated data exchange workflow is established between a parametric multi-level information model for tunnelling and multi-level numerical models based on both Finite Element and Isogeometric Analysis, where meta models are employed for real-time design assessment. We discuss the different applications of these concepts, such as scenario-based exploration of design alternatives, real-time design assessment within a TIM based on meta-models, and the potentials of using these models for the process control during construction. Furthermore, we present two case studies where real project data has been used for the integration of information and numerical modelling. The examples in this paper indicate clear advantages of this approach compared to traditional approaches in terms of efficiency of modelling achieved by reduced user interactions and error-free information exchange, and show the benefits of multi-level model representation and real-time analysis tasks.

Assimilation of Earth Observation Data Over Cropland and Grassland Sites into a Simple GPP Model

The application of detailed process-oriented simulation models for gross primary production (GPP) estimation is constrained by the scarcity of the data needed for their parametrization. In this manuscript, we present the development and test of the assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Normalized Difference Vegetation Index (NDVI) observations into a simple process-based model driven by basic meteorological variables (i.e., global radiation, temperature, precipitation and reference evapotranspiration, all from global circulation models of the European Centre for Medium-Range Weather Forecasts). The model is run at daily time-step using meteorological forcing and provides estimates of GPP and LAI, the latter used to simulate MODIS NDVI though the coupling with the radiative transfer model PROSAIL5B. Modelled GPP is compared with the remote sensing-driven MODIS GPP product (MOD17) and the quality of both estimates are assessed against GPP from European eddy covariance flux sites over crops and grasslands. Model performances in GPP estimation (R2 = 0.67, RMSE = 2.45 gC m−2 d−1, MBE = −0.16 gC m−2 d−1) were shown to outperform those of MOD17 for the investigated sites (R2 = 0.53, RMSE = 3.15 gC m−2 d−1, MBE = −1.08 gC m−2 d−1).

Water productivity and yield analysis of groundnut using CropSyst simulation model in hyper arid partially irrigated zone of Rajasthan

CropSyst is one of the most important process-oriented simulation models largely used for field crops all over the world to study the effect of climate, soil and management practices on crop productivity. In the present study, we have calibrated and validated the CropSyst model for groundnut crop grown at farmer’s field in IGNP Stage-II of Bikaner. CropSyst model was calibrated using the experimental data of crop parameters, soil profile data and observed daily weather data of experimental site for 2012 and validated the experimental data of crop growth and yield parameters for 2013. The results of the study showed that the CropSyst model simulated the crop growth parameter data viz. green area index, seed yield, above ground biomass and N-uptake of groundnut reasonably well. The seed yield, above ground biomass and N- uptake was validated well by the model with relative error of 3.3, 2.2 and 8.4 %, respectively. The total water applied in groundnut was 728.9 and 619.6 mm in 2012 and 2013, respectively out of this 664.9 and 530.5mm consumed in evapotranspiration.

Comparative study of nitrate leaching models on a regional scale

In Europe and North America the application of high levels of manure and fertilisers on agricultural land has led to high levels of nitrate concentrations in groundwater, in particular on sandy soils. For the evaluation of the development of the quality of groundwater a sound quantitative basis is needed. In this paper a comparison has been made between observations of nitrate concentrations in the upper groundwater and predictions of nitrate leaching models. Observations of nitrate concentrations in the upper groundwater at three different locations in regions with mainly sandy soils in the eastern and northern part of the Netherlands were used to test the performance of the simulation models to predict nitrate leaching to the upper groundwater. Four different types of simulation models of different levels of complexity and input data requirement were tested. These models are ANIMO (dynamic complex process oriented model), MM-WSV (meta-model), WOG (simple process oriented model) and NURP (semi-empiric model). The performance of the different simulation models was evaluated using statistical criteria. The dynamic complex process oriented ANIMO model showed the best model performance. The MM-WSV meta-model was the second best model, whilst the simple process oriented WOG model produced the worst model performance. The best model performance showed the dynamic complex process oriented ANIMO model in predicting the nitrate concentrations in the upper groundwater of the Klooster catchment. The good performance of the ANIMO model for this catchment can be explained by the additional information about the use of manure and fertilisers at farm level in this study area. The ANIMO model may be a good tool to predict nitrate concentrations in the upper groundwater on a regional scale. However, the use of a detailed process oriented simulation model requires a comprehensive set of input data. If such a comprehensive data-set is not available the MM-WSV model (meta-model) proves to be a good alternative. The WOG and NURP models are suitable for long term (>8years) predictions of average nitrate concentrations in the upper groundwater on a regional scale.

Simulation Method to Improve Hospital Service Quality

This article presents the results of a simulation model designed to reduce patient waiting time in the emergency department of a hospital in the United Arab Emirates. The process-oriented simulation model shows how the resources in the hospital are inter-related. The model depicts the hospital operating system and its performance and management issues with regards to allocation of human and material resources. Based on results of the simulation, optimized response surfaces are developed to explain patient waiting time and the total time a patient spends in the hospital for treatment. Results of the study can be used by hospital management to reduce patient waiting time and improve service quality by using a mix of operational strategies and resource allocations.

Parallelized computational modeling of pile–soil interactions in mechanized tunneling

The construction of tunnels in soft ground causes short and long term ground deformations resulting from the disturbance of the virgin stress state of the soil and the changing pore water conditions. In particular in urban tunneling, in each stage of the construction process, interactions between the construction process, the soil and existing building infrastructure need to be evaluated to limit the risk of damage on existing buildings and to decide on appropriate mitigation measures. Besides conventional tunneling, mechanized tunneling is a well established and flexible technology in particular in urban areas, which allows for tunnel advances in a wide range of soils and difficult conditions. The paper presents a finite element model for the simulation of interactions between mechanized tunnel construction, the surrounding soil and existing buildings resting on pile foundations in the framework of a process-oriented simulation model for mechanized tunneling. The performance of the model is demonstrated by means of selected prototype analyses. As a consequence of the high computational demand connected with this type of spatio-temporal simulations, problem specific parallelization techniques are investigated to increase the numerical efficiency of the numerical analyses.

ICDE-results on complete common cause failures in the light of results obtained with the POS model

Abstract Since April 1998, the OECD Nuclear Energy Agency (NEA) is operating the International Common Cause Data Exchange (ICDE) project. The objectives of this exchange comprise, to collect and analyze CCF events, to generate insights into root causes and derive preventing approaches, to strengthen experience feedback and, last but not least, to facilitate quantification. For a large number of about 1000ICDE events the fractions of complete CCFs have been displayed as a function of the degree of redundancy. Complete CCFs are relevant to PSA as in these cases the respective function fails and in many cases significant contributions to core damage can be expected. From the point of view of quantitative CCF modeling, the theoretical theoretical approach to of the empirically available complete CCF fractions represents a major challenge. The large number of events have been collected in the ICDE project for nine different types of components in nuclear power plants from ten different countries. Obviously, these components are operated under different conditions and technical specifications. Therefore, an approach is chosen which is based on low information distributions of the model parameters to account for the large variation throughout the component populations. The Process Oriented Simulation Model (POS) has been selected to carry out an analysis of complete CCFs. The consistency between the theoretical approach – considering its simplicity – and the data observed is satisfactory.

The Process-Oriented Simulation (POS) model for common cause failures: recent progress

AbstractA common-cause failure (CCF) model based on stochastic simulation has been developed to complement the established approaches and to overcome some of their shortcomings. Reflecting the models proximity to the CCF process it was called Process Oriented Simulation (POS) Model. In recent years, some progress has been made to render the POS model fit for practical applications comprising the development of parameter estimates and a number of test applications in areas where results were already available – especially from CCF benchmarks – and comparison can provide insights in strong and weak points of the different approaches. In this paper, a detailed description of the POS model is provided together with the approach to parameter estimation and representative test applications. It is concluded, that the POS model has a number of strengths – especially the feature to provide reasonable extrapolation to CCF groups with high degrees of redundancy – and thus a considerable potential to complement the insights obtained from existing modeling.

Simulation of crop-weed competition : Models and their applications

Competition between crops and weeds is a complex phenomenon. Comprehensive, process-oriented simulation models which treat competition in a mechanistic rather than an empirical fashion, can offer insight into relationships among competition, crop and weed density, relative time of emergence, various morphological and physiological traits, and resource levels. They can also be used for prediction as part of a Systems approach to weed management. This paper reviews the features of a number of recent simulation models of crop-weed competition, the species for which they have been parameterized, and their applications. To date, these models have been used primarily to predict crop yield losses due to weed competition. Their ability to simulate weed seed production in response to the environment has not been exploited. The next step is to link simulation models of crop-weed competition to weed population dynamics models, in order to improve our ability to predict the effect of various weed management strategies over time. Advantages and drawbacks of a modeling approach to weed management problems are discussed.

A simulation-based approach to software performance modeling

Quantitative performance analysis of software systems should be integrated in the early stages of the development process. We propose a simulation-based performance modeling of software architectures specified in UML. We propose an algorithm for deriving a simulation model from annotated UML software architectures. We introduce the annotation for some UML diagrams, i.e., Use Case, Activity and Deployment diagrams, to describe system performance parameters. Then we show how to derive a process-oriented simulation model by automatically extracting information from the UML diagrams. Simulation provides performance results that are reported into the UML diagrams as tagged values. The proposed methodology has been implemented into a prototype tool called UML-?. The proposed methodology will be illustrated on a simple case study.

Evaluation of process controller fault tolerance using simulation

The paper presents a study of several alternatives of a fault-tolerant process controller design. We compare controller architectures based on different amount of hardware redundancy with those using time redundancy. The system behaviour is evaluated by means of a process-oriented simulation model enabling software injection of faults. As an overall measure of controller design quality (which includes both performance and reliability) we use the numerical error of the output. The results obtained on the model are used to show the dependence of the output error upon the relative speed of computation and upon the rate of faults damaging the data. Thus for every set of parameters, a system configuration which gives the best results, can be determined.

Comparison of N and C dynamics in two Norway spruce stands using a process oriented simulation model

Nitrogen and carbon dynamics of two Norway spruce stands were compared using a dynamic soil-plant simulation model (SOILN). The objectives were to evaluate differences in properties between the two stands and to explore the consequences on C and N dynamics. The young stand (25 years old) was located in south-west Sweden (Skogaby) growing on a loamy sand soil. The old stand (70 years old) was growing on a sandy soil in western Denmark (Klosterhede). Differences in specific rates of processes between the two sites were estimated in terms of parameter values derived by calibration of the model. Differences in daily flow rates and pathways of N and C were examined and budget components were simulated over a six year period. Simulations showed that the different stands had different specific rates for growth, allocation, litter fall and N uptake resulting in higher N uptake in the younger trees whereas growth was more similar. The soil carbon balance was positive and soil C/N ratio increased for the young stand. For the old stand the soil carbon balance was negative and the C/N ratio decreased. The soil mineral N levels were much lower in the younger stand which was explained by a higher plant uptake of organic N. At both sites the average pools and fluxes over the years were fairly well simulated indicating that N leaching predictions on average might be reliable.

Use of a network of long-term experiments for analysis of soil carbon dynamics and global change: the North American model

Soils contain a large proportion of the carbon (C) in the terrestrial biosphere, yet the role of soils as a sink or a source of net atmospheric C flux is uncertain. In agricultural systems, soil C is highly influenced by management practices and there is considerable interest in adapting management systems to promote soil C sequestration, thereby helping to mitigate atmospheric CO2 increases. Long-term field experimental sites represent a unique source of information on soil C dynamics, and networks of such sites provide a key ingredient for making large-scale assessments of soil C change across ranges in climate and soil conditions and management regimes. Currently, there are collaborative efforts to develop such site networks in Australia, Europe, and North America. A network of long-term experiments in North America was established to provide baseline information on the effects of management (i.e. tillage, crop rotations, fertilisation, organic amendments) on soil organic matter. Historical data on soils, primary productivity, climate, and management were synthesised by scientists from the individual field sites, representing a total of 35 long-term field experiments. An additional cross-site soil sampling campaign was carried out to provide uniform comparisons of soil C and nitrogen (N), both within and across sites. Long-term field experiments are a principle component necessary for regional assessments of soil C dynamics. We describe a general methodology for combining long-term data with process-oriented simulation models and regional-level, spatially resolved databases. Such analyses are needed to assess past and present changes in soil C at regional to global scales and to make projections of the potential impacts of changes in climate, CO2, and landuse patterns on soil C in agroecosystems.

Soil behavior under field conditions: differences in perception and their effects on research

Soil behavior can be considered from different levels of perception: by the user, by experts and by specialists. The most comprehensive and effective characterization of soil behavior is likely obtained when these three levels are considered together as is illustrated in six case studies. Soil behavior is determined by interacting physical, chemical and biological processes of natural and man-induced origin. Three procedures for characterizing soil behavior are discussed: (1) monitoring of soil processes in situ; (2) monitoring the effects of soil processes as expressed on the soil surface, and (3) prediction of soil behavior for actual and potential environmental conditions by process oriented simulation modelling. A case is made to combine real-time monitoring and simulation modelling for predictions of soil behavior over periods for which extended weather forecasts are available. Heterogeneous field conditions require application of special techniques that account for soil horizons and patterns of heterogenity to be characterized with morphological techniques. Electronic techniques allow widespread generation of continuous monitoring data crucial for calibration and validation of process-oriented simulation models, and for updating expert knowledge. Modern remote sensing techniques, using satellites, airplanes and handheld equipment, allow detailed characterization of conditions at the soil surface or of the crop cover, reflecting soil conditions within the rootzone. A research approach is advocated, based on a critical problem-analysis and on quantitative ground-truth data. Some problems can be solved by expert knowledge, whereas others require additional measurements or simulations.

A SLAM Based Computer Simulation Model of a Meat Processing Plant

ABSTRACT SYSTEM modeling is an effective and proven aid to decision making in business and industry. It is a powerful tool for analyzing complex production systems. In this research a process-oriented simulation model of an existing meat processing plant based in SLAM is developed and presented. Simulation model is capable of simulating virtually all the processing activities and provides the snapshot view of the entire plant at any given time. The predicted operating statistics and results are used to analyze the plant's performance. This work provides a clearer and better understanding of the meat processing plant and could serve as a basis for on-going research.

A process oriented simulation model specification and documentation language

AbstractWe present a language for specifying and documenting discrete event simulation models, designed to facilitate communication during model design, implementation and maintenance. The systems from which models are developed are viewed as collections of communicating elements. Each element is specified separately in a module consisting of attributes, axioms and a scenario. The model's specification consists of each model element's specification and some systemwide attributes and axioms. Synchronization among model elements (model dynamics) is specified within the model elements rather than globally. Each language control structure has a monitor associated with it. Appropriate changes are made in the model's state in response to a monitor's sensing an attribute change. The language contains a library of specifications for common simulation model entities such as the priority queue. The syntax and semantics of the language are presented through examples. Examples of a library specification and a model specification are included.