Development, validation and applications of simulation models for agroecosystems: Problems and perspectives

Transportation simulation model development allows simulating traveller’s decisions, evaluating various transportation management strategies and complex solutions. The aim of the paper is to set the general principles of the transportation simulation model development and validation. The paper contains the overview of the transportation simulation models types with the examples from the conducted projects for the Riga city. The basic steps of the simulation model development procedure: initial data preparation and analysis, transportation model development and simulation, scenarios planning and evaluation, and simulation models outcomes evaluation are considered. Simulation model verification, validation and calibration definitions are given. The basic checks for the transportation macroscopic and microscopic simulation model validation are listed. A summary of the transportation simulation model validation and calibration methods and parameters is given.

Intensive Care Units (ICUs) are specialized healthcare delivery units for patients that require the highest level of monitored care. ICUs are typically integrated into larger healthcare facilities and their operation is dependent on the operational status of other inpatient units and departments of the host facility. As patients transition between units, a lack of available beds in a requested unit may cause patients to stay in a level of care other than that which is clinically indicated, leading to unnecessary or unwarranted costs without improving medical outcomes. The simulation modeling work presented in this paper is part of a multidisciplinary research project aimed towards patient delays. We describe the design and validation of a large scale ICU simulation model that includes various inpatient units and departments of the hospital. We describe the (i) input data analysis, (ii) modeling of patient flow, and (iii) validation of the simulation model. 1

Intensive Care Units (ICUs) are specialized healthcare delivery units for patients that require the highest level of monitored care. ICUs are typically integrated into larger healthcare facilities and their operation is dependent on the operational status of other inpatient units and departments of the host facility. As patients transition between units, a lack of available beds in a requested unit may cause patients to stay in a level of care other than that which is clinically indicated, leading to unnecessary or unwarranted costs without improving medical outcomes. The simulation modeling work presented in this paper is part of a multidisciplinary research project aimed towards patient delays. We describe the design and validation of a large scale ICU simulation model that includes various inpatient units and departments of the hospital. We describe the (i) input data analysis, (ii) modeling of patient flow, and (iii) validation of the simulation model.

Development of large-scale traffic simulation models have always been challenging for transportation researchers. One of the essential steps in developing traffic simulation models, which needs lots of resources, is travel demand modeling. Therefore, proposing travel demand models that require less data than classical travel demand models is highly important, especially in large-scale networks. This paper first presents a travel demand model named as probabilistic travel demand model, then it reports the process of development, calibration and validation of Belgium traffic simulation model. The probabilistic travel demand model takes cities' population, distances between the cities, yearly vehicle-kilometer traveled, and yearly truck trips as inputs. The extracted origin-destination matrices are imported into the SUMO traffic simulator. Mesoscopic traffic simulation and the dynamic user equilibrium traffic assignment are used to build the base case model. This base case model is calibrated using the traffic count data. Al-so, the validation of the model is performed by comparing the real (extracted from Google Map API) and simulated travel times between the cities. The validation results ensure that the model is a superior representation of reality with a high level of accuracy. The model will be helpful for road authorities, planners, and decision-makers to test different scenarios, such as the im-pact of abnormal conditions or the impact of connected and autonomous vehicles on the Belgium road network.

The value of modeling and simulation for education, training, and testing in information security has been documented in several studies. In this paper, we suggest that it is important not only to include the general use of simulation in various courses of the security curriculum, but also to include the theory and development of simulation models. We describe briefly the general features of simulation models and tools for model development that we are using in computing education.A collection of educational simulation tools have been created in the OOPsim project, for developing discrete-event simulation models. The principal goal of this project is to develop newer simulation tools and approaches for education in computing. The Object Oriented Simulation Language, OOSimL, was recently developed with partial support from an NSF CPATH grant.Two object-oriented simulation models are discussed as typical examples discussed in a simulation course on security: a model of a distributed denial of service (DDoS) and a model of simple firewall system. These models were developed with educational simulation tools created in OOPsim project. We have also developed a course that emphasizes an approach to early introduction to object-oriented discrete-event simulation.The DDoS simulation model is implemented using the OOSimL simulation language. The Firewall simulation model was implemented in Java with the PsimJ2 object oriented simulation package; other models have been implemented in C++ using the Psim3 object oriented simulation package. The simulation tools and model development are very useful for educating and training students and professionals in information security, computer science, software engineering, information technology, and in other related disciplines.

This paper reports the results of a joint academic and industrial study on the development of a detailed simulation model to be used for research into advanced control strategies for civil turbofan aircraft engines. A comprehensive nonlinear dynamic model of a turbofan jet engine has been developed and validated against real industrial data. A switched, gain- scheduled, feedback control system incorporating bumpless transfer and antiwindup functionality has been designed for the engine model and implemented according to current industrial practice. Full flight envelope validation of the model has been performed with the help of Alstom Aerospace by analysing the resulting closed-loop performance properties for a range of different pilot thrust demands against the type of responses required from a real turbofan engine. In this paper, we present a detailed description of the modeling process, the various simulation issues that arise with a model of this complexity, and the validation results of the overall aero-engine system.

Validation of a simulation model is a key stage in building its credibility. It demonstrates that the model offers a reliable representation of the real system and fulfils its intended objectives. Validation is a highly discipline-dependent process. Social simulations differ from business, engineering, or physics-based simulations because usually they do not refer to an objective, well-known reality described by established, universal background theories. This causes social simulations to require a different approach to the validation process. This paper focuses on the operational validation of social simulation models and, in particular, one group of these models, namely pension models. We present the application of the model-to-model-comparison method, which involves comparing the results of two simulation models developed using different approaches and different platforms. The article discusses the rationale for using this method in the validation of social simulation models. It also presents the results of pension model validation using statistical tests and analysis of model behaviour consistency for different input parameter values.

Simulation allows to comprehensively examine the various processes and systems, and to evaluate the expected results before decision. To create reliable transportation simulation model, it should be carefully and in depth validated. The purpose of this paper is to describe the basis for the transportation microscopic simulation model validation. The paper contains the basic steps for the transportation simulation model development and validation. Various definitions for the simulation model verification, validation and calibration are considered. Validation and calibration parameters selection depends on the complexity of analysable task, initial amount and quality of input data. A summary of the transportation simulation model validation methods and parameters is presented.

Concise encyclopedia of environmental systems: Peter C. Young, ed. Pergamon Press Ltd., Oxford, England; 1993. 769 pp. (ISBN 0-08-036198-6) £155.00 hardcover

Purpose of the study.The aim is to create a technique targeted at the development of simulation skills in higher education environment, where students are competent in applying information technologies in economics. The relevance of the research lies in the fact that the existing methodological developments often focus on a specific software tool or methodology that cannot respond to all economic problems. A specialist in simulation modeling should possess integrative interdisciplinary knowledge from related scientific fields, for example, probability theory and mathematical statistics, higher mathematics, be familiar with other methods of solving economic problems: linear, nonlinear, dynamic programming, optimization; show proficiency in structural and functional analysis; be able to explore complex processes and systems comprehensively.Materials and methods.The following pedagogical approaches and teaching methods were implemented in this research: ● a systematic approach to solving complex problems based on the modelling economic objects as systems operating in a certain environment, ● activity approach to develop students’ professional competences in the process of creation, debugging and optimization of computer models of economic systems; ● problem teaching method in the framework of research and analysis of educational problems of the subject area; ● implemented interactive teaching methods; ● multimedia methods in the content of teaching materials of the discipline, including electronic manuals, educational videos, as well as multimedia presentations. The research also utilized information technologies, in which computers, communication equipment and software environments are: ● means to provide educational material to students for the transfer of knowledge; ● tools for designing, developing and conducting simulation experiments. In addition, we used the following special professional technologies, methods and tools in the process of teaching students: ● structural and functional modeling methodology; ● discrete-event approach to simulation methodology; ● special software for development and research of simulation models of economic processes and systems: Arena 15.0, AnyLogic 8.3.2.According to the requirements of the new educational standards, the student must master a sufficiently large amount of general cultural, professional and specialized competencies included in the curriculum. The application of the proposed approaches and methods allows to provide effective development of skills of simulation modeling of educational programs for bachelors of «Applied Informatics» and «Business Informatics».Results.The study created a method of teaching students the skills of simulation modeling. The research also established the model of formation of readiness of the IT specialist to the development of simulation models of economic processes and systems in higher school. We also identified important methodological conditions for the formation of professional competencies of students in the field of modeling, such as: ● application of a systematic approach to the analysis of domain problems, as well as for the synthesis of mathematical simulation models of business processes and economic systems; ● practical orientation of the content of training (selection and research in the educational process of the most characteristic, typical problems of the economy); ● integration of interdisciplinary knowledge, methods and approaches to solve complex problems.Conclusion.The method can equip students with skills of simulation modeling with various areas of practical application. First, this technique can be used by university students who are engaged in pursuing practical skills and basic system knowledge in the field of simulation. Secondly, teachers can use it, conducting courses: “Computer modeling”, “Mathematical and simulation modeling”, “Modeling of processes and systems” in the educational process of the University to improve the professional competence of students training simulation modeling. Third, the outcomes may be of interest to managers of educational programs in the areas of: “Applied Informatics”, “Business Informatics”, etc. to improve the structure and sequence of disciplines of competence-oriented curricula. Finally, the application of the proposed methodology in the educational process of the University will enhance professional expertise of young specialists and undoubtedly address the needs of potential employers.

The paper presents a new game theoretic approach towards the validation of discrete event air combat simulation models. In the approach, statistical techniques are applied for estimating game models based on simulation data. The estimation procedure is presented in cases involving games with both discrete and continuous decision variables. The validity of the simulation model is assessed by comparing the properties of the estimated games to actual practices in air combat. The approach enhances existing methods for the validation of discrete event simulation models by incorporating the inherent game setting of air combat into the analysis. The estimated games also provide a novel game theoretic perspective to simulation metamodeling which is used to facilitate simulation analysis. The utilization of the game theoretic approach is illustrated by analyzing simulation data produced with an existing air combat simulation model.

Knowledge-based method for the validation of complex simulation models

The development of simulation models can be time consuming and highly dependant on system data being widely available. When using simulation modeling to analyze future systems, system data may not be available for the system under study and simulation results are often needed within a short time frame to support early system design efforts. This paper presents a parametric estimation/generic simulation integrated environment developed to facilitate the rapid development of valid simulation models for the Orbital Space Vehicle ground processing operations.

The development of simulation models can be time consuming and highly dependant on system data being widely available. When using simulation modeling to analyze future systems, system data may not be available for the system under study and simulation results are often needed within a short time frame to support early system design efforts. This paper presents a parametric estimation/generic simulation integrated environment developed to facilitate the rapid development of valid simulation models for the Orbital Space Vehicle ground processing operations.

The objectives of this study are the development and verification of a simulation model of the partial PST (power-shift transmission) tractor based on actual field operations. The PST simulation model was verified for the asphalt driving condition, and performance was evaluated for asphalt driving, plow, and rotary tillage. In this study, the traditional, APS (Auto Power Shift) ECO, and APS power engine modes were used to analyze fuel consumption. The statistical analysis proved that the experimental and simulation results were in a linear relationship, with an accuracy of over 98%. Finally, the results suggested that users could utilize the 95-kW partial PST tractor in the APS ECO engine mode with higher fuel economy compared to the traditional and APS power modes.