Verification and Validation of Pipeline Terminal Simulation Models

2014 ◽  
Author(s):  
Frank Lin ◽  
Allan Chegus ◽  
Dumitru Cernelev
Keyword(s):  
Simulation Model ◽  
Simulation Models ◽  
Difficult Problem ◽  
Verification And Validation ◽  
Optimization Software ◽  
Simulation And Optimization ◽  
Terminal Performance ◽  
Model Validity ◽  
Complex Simulation

The problem of validating a complex simulation model represents pipeline terminal performance with verifiable accuracy is a difficult problem requiring extensive testing and calibration. This paper discusses a case study of the verification and validation of a terminal simulation model. The approach to deciding model validity is presented as well as the process of verifying and validating the model including methodology and thresholds for acceptance. Ultimately the paper demonstrates the ability of commercial simulation and optimization software to work collaboratively to determine an optimal business solution.

scholarly journals Some Issues in the Testing of Computer Simulation Models

2016 ◽  
Vol 5 (1) ◽  
pp. 1-10
Author(s):  
David Murray-Smith
Keyword(s):  
Simulation Model ◽  
Model Validation ◽  
Simulation Models ◽  
Model Testing ◽  
Model Verification ◽  
Verification And Validation ◽  
Quality Data ◽  
Model Quality ◽  
Face Validation

The testing of simulation models has much in common with testing processes in other types of application involving software development. However, there are also important differences associated with the fact that simulation model testing involves two distinct aspects, which are known as verification and validation. Model validation is concerned with investigation of modelling errors and model limitations while verification involves checking that the simulation program is an accurate representation of the mathematical and logical structure of the underlying model. Success in model validation depends upon the availability of detailed information about all aspects of the system being modelled. It also may depend on the availability of high quality data from the system which can be used to compare its behaviour with that of the corresponding simulation model. Transparency, high standards of documentation and good management of simulation models and data sets are basic requirements in simulation model testing. Unlike most other areas of software testing, model validation often has subjective elements, with potentially important contributions from face- validation procedures in which experts give a subjective assessment of the fidelity of the model. Verification and validation processes are not simply applied once but must be used repeatedly throughout the model development process, with regressive testing principles being applied. Decisions about when a model is acceptable for the intended application inevitably involve some form of risk assessment. A case study concerned with the development and application of a simulation model of a hydro-turbine and electrical generator system is used to illustrate some of the issues arising in a typical control engineering application. Results from the case study suggest that it is important to bring together objective aspects of simulation model testing and the more subjective face- validation aspects in a coherent fashion. Suggestions are also made about the need for changes in approach in the teaching of simulation techniques to engineering students to give more emphasis to issues of model quality, testing and validation.

scholarly journals Simulation and Optimization of Pedestrian Regular Evacuation in Comprehensive Rail Transit Hub – A Case Study in Beijing

2020 ◽  
Vol 32 (3) ◽  
pp. 383-397
Author(s):  
Qiaochu Chen ◽  
Yan Bai ◽  
Nan Zheng
Keyword(s):  
Simulation Model ◽  
Urban Rail Transit ◽  
Model Parameters ◽  
Rail Transit ◽  
Social Force ◽  
Railway Station ◽  
Simulation And Optimization ◽  
Pedestrian Evacuation ◽  
Urban Rail

Extensive efforts have been made in pedestrian evacuation of urban rail transit systems, since there has emerged an increasing number of congestion problems. However, few studies focus on the comprehensive urban rail transit hubs. As a comprehensive interchange hub integrating urban railway and intercity railway lines, Beijing West Railway Station was taken as a case study object. The pedestrian evacuation characteristics were analysed first. Then, a social force-based simulation model of Beijing West Railway Station was constructed in PTV Viswalk. The model was applied to visually display a real evacuation process and help identify evacuation bottlenecks. The results showed that the risk points at different facilities had various causes and features. Furthermore, the simulation model could also be used to evaluate the effectiveness of different optimization measures as long as certain model parameters were changed beforehand.

Method to Control Manufacturing Cell by Driving Simulation Model

2014 ◽  
Vol 8 (4) ◽  
pp. 539-549 ◽  
Author(s):  
Hironori Hibino ◽  
Keyword(s):  
Simulation Model ◽  
Manufacturing System ◽  
Simulation Models ◽  
Driving Simulation ◽  
Manufacturing Cell ◽  
Manufacturing Management ◽  
Execution Phase ◽  
Manufacturing Engineering ◽  
Wiring System

In this paper, a method to Control a Manufacturing Cell by Driving Simulation Models (CMC-DSM) is proposed. The purposes of CMC-DSM is not only to directly operate the manufacturing cell while controlling and monitoring the manufacturing cell based on a simulation model in the manufacturing system execution phase, but also to support the manufacturing engineering processes based on the simulation model. In the manufacturing engineering processes, the simulation model is mixed and synchronized with real equipment and management applications in the case where parts of equipment and manufacturing management applications are not provided in the manufacturing cell. In the manufacturing system execution phase, when the simulation model acts in response to manufacturing system behaviors, the manufacturing system is controlled by synchronizing the simulation model behaviors. In this paper, the Environment required to Control a Manufacturing Cell by Driving Simulation Models (E-CMC-DSM) is proposed. The necessary functions for E-CMC-DSM are defined and developed. E-CMC-DSM consists of a simulator developed to drive simulation models (EMU), a soft-wiring system developed in this study, and a semi-standard industrial network middleware. The validation of ECMC-DSM was carried out through a case study.

Study of industrially applied methods for verification, validation and uncertainty quantification of simulator models

2015 ◽  
Vol 06 (02) ◽  
pp. 1550014 ◽  
Author(s):  
Magnus Eek ◽  
Sogol Kharrazi ◽  
Hampus Gavel ◽  
Johan Ölvander
Keyword(s):  
Uncertainty Quantification ◽  
Simulation Models ◽  
Verification And Validation ◽  
Credibility Assessment ◽  
Driving Simulators ◽  
Exploratory Case Study ◽  
Aircraft System ◽  
National Road ◽  
Further Development

To better utilize the potential of system simulation models and simulators, industrially applicable methods for Verification, Validation and Uncertainty Quantification (VV&UQ) are crucial. This paper presents an exploratory case study of VV&UQ techniques applied on models integrated in aircraft system simulators at Saab Aeronautics and in driving simulators at the Swedish National Road and Transport Research Institute (VTI). Results show that a large number of Verification and Validation (V&V) techniques are applied, some of which are promising for further development and use in simulator credibility assessment. Regarding the application of UQ, a large gap between academia and this part of industry has been identified, and simplified methods are needed. The applicability of the NASA Credibility Assessment Scale (CAS) at the studied organizations is also evaluated and it can be concluded that the CAS is considered to be a usable tool for achieving a uniform level of V&V for all models included in a simulator, although its implementation at the studied organizations requires tailoring and coordination.

Westinghouse Waste Simulation and Optimization Software Tool

2013 ◽  
Author(s):  
Kim Mennicken ◽  
Jörg Aign
Keyword(s):  
Waste Management ◽  
Dynamic Simulation ◽  
Waste Treatment ◽  
Software Tool ◽  
Simulation Models ◽  
Project Planning ◽  
Waste Stream ◽  
Management Activity ◽  
Optimization Software ◽  
Simulation And Optimization

Applications for dynamic simulation can be found in virtually all areas of process engineering. The tangible benefits of using dynamic simulation can be seen in tighter design, smoother start-ups and optimized operation. Thus, proper implementation of dynamic simulation can deliver substantial benefits. These benefits are typically derived from improved process understanding. Simulation gives confidence in evidence based decisions and enables users to try out lots of ‘what if’ scenarios until one is sure that a decision is the right one. In radioactive waste treatment tasks different kinds of waste with different volumes and properties have to be treated, e.g. from NPP operation or D&D activities. Finding a commercially and technically optimized waste treatment concept is a time consuming and difficult task. The Westinghouse Waste Simulation and Optimization Software Tool will enable the user to quickly generate reliable simulation models of various process applications based on equipment modules. These modules can be built with ease and be integrated into the simulation model. This capability ensures that this tool is applicable to typical waste treatment tasks. The identified waste streams and the selected treatment methods are the basis of the simulation and optimization software. After implementing suitable equipment data into the model, process requirements and waste treatment data are fed into the simulation to finally generate primary simulation results. A sensitivity analysis of automated optimization features of the software generates the lowest possible lifecycle cost for the simulated waste stream. In combination with proven waste management equipments and integrated waste management solutions, this tool provides reliable qualitative results that lead to an effective planning and minimizes the total project planning risk of any waste management activity. It is thus the ideal tool for designing a waste treatment facility in an optimum manner, taking account of the detailed waste stream and specific requirements.

Application of an Interactive Water Simulation Model in urban water management: a case study in Amsterdam

2014 ◽  
Vol 70 (11) ◽  
pp. 1729-1739 ◽  
Author(s):  
J. G. Leskens ◽  
M. Brugnach ◽  
A. Y. Hoekstra
Keyword(s):  
Water Management ◽  
Simulation Model ◽  
Simulation Models ◽  
Decision Makers ◽  
Urban Water ◽  
Urban Water Management ◽  
Current Water ◽  
Water Simulation ◽  
Computation Algorithms

Water simulation models are available to support decision-makers in urban water management. To use current water simulation models, special expertise is required. Therefore, model information is prepared prior to work sessions, in which decision-makers weigh different solutions. However, this model information quickly becomes outdated when new suggestions for solutions arise and are therefore limited in use. We suggest that new model techniques, i.e. fast and flexible computation algorithms and realistic visualizations, allow this problem to be solved by using simulation models during work sessions. A new Interactive Water Simulation Model was applied for two case study areas in Amsterdam and was used in two workshops. In these workshops, the Interactive Water Simulation Model was positively received. It included non-specialist participants in the process of suggesting and selecting possible solutions and made them part of the accompanying discussions and negotiations. It also provided the opportunity to evaluate and enhance possible solutions more often within the time horizon of a decision-making process. Several preconditions proved to be important for successfully applying the Interactive Water Simulation Model, such as the willingness of the stakeholders to participate and the preparation of different general main solutions that can be used for further iterations during a work session.

Verification and Validation of Simulation Models

2010 ◽  
pp. 58-74
Author(s):  
Sattar J. Aboud ◽  
Mohammad Al Fayoumi ◽  
Mohamed Alnuaimi
Keyword(s):  
Model Development ◽  
Simulation Models ◽  
Model Verification ◽  
Verification And Validation ◽  
Validation And Verification ◽  
Model Validity ◽  
Security Models ◽  
Real Model ◽  
Data Validity ◽  
The Impact

Unfortunately, cost and time are always restraints; the impact of simulation models to study the dynamic system performance is always rising. Also, with admiration of raising the network security models, the complexity of real model applications is rising too. As a result, the complexity of simulation models applications is also rising and the necessary demand for designing a suitable verification and validation systems to ensure the system reliability and integrality is very important. The key requirement to study the system integrity is to verify the system accuracy and to validate its legality regarding to prespecified applications causes and validly principles. This needs different plans, and application phases of simulation models to be properly identified, and the output of every part is properly documented. This chapter discusses validation and verification of simulation models. The different approaches to deciding model validity are presented; how model validation and verification relate to the model development process are discussed; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity; superior verification and validation technique for simulation models relied on a multistage approach are described; ways to document results are given; and a recommended procedure is presented.

scholarly journals Rapid-cycle systems modeling to support evidence-informed decision-making during system-wide implementation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
R. Christopher Sheldrick ◽  
Gracelyn Cruden ◽  
Ana J. Schaefer ◽  
Thomas I. Mackie
Keyword(s):  
Simulation Model ◽  
Simulation Modeling ◽  
Implementation Strategy ◽  
Simulation Models ◽  
Illustrative Case ◽  
Systems Modeling ◽  
Cycle Systems ◽  
Analytic Strategy ◽  
Group Interviews

Abstract Background To “model and simulate change” is an accepted strategy to support implementation at scale. Much like a power analysis can inform decisions about study design, simulation models offer an analytic strategy to synthesize evidence that informs decisions regarding implementation of evidence-based interventions. However, simulation modeling is under-utilized in implementation science. To realize the potential of simulation modeling as an implementation strategy, additional methods are required to assist stakeholders to use models to examine underlying assumptions, consider alternative strategies, and anticipate downstream consequences of implementation. To this end, we propose Rapid-cycle Systems Modeling (RCSM)—a form of group modeling designed to promote engagement with evidence to support implementation. To demonstrate its utility, we provide an illustrative case study with mid-level administrators developing system-wide interventions that aim to identify and treat trauma among children entering foster care. Methods RCSM is an iterative method that includes three steps per cycle: (1) identify and prioritize stakeholder questions, (2) develop or refine a simulation model, and (3) engage in dialogue regarding model relevance, insights, and utility for implementation. For the case study, 31 key informants were engaged in step 1, a prior simulation model was adapted for step 2, and six member-checking group interviews (n = 16) were conducted for step 3. Results Step 1 engaged qualitative methods to identify and prioritize stakeholder questions, specifically identifying a set of inter-related decisions to promote implementing trauma-informed screening. In step 2, the research team created a presentation to communicate key findings from the simulation model that addressed decisions about programmatic reach, optimal screening thresholds to balance demand for treatment with supply, capacity to start-up and sustain screening, and availability of downstream capacity to provide treatment for those with indicated need. In step 3, member-checking group interviews with stakeholders documented the relevance of the model results to implementation decisions, insight regarding opportunities to improve system performance, and potential to inform conversations regarding anticipated implications of implementation choices. Conclusions By embedding simulation modeling in a process of stakeholder engagement, RCSM offers guidance to realize the potential of modeling not only as an analytic strategy, but also as an implementation strategy.

A pattern-based validation method for the credibility evaluation of simulation models

SIMULATION ◽  
2019 ◽  
Vol 96 (2) ◽  
pp. 151-167
Author(s):  
Yuanjun Laili ◽  
Lin Zhang ◽  
Yongliang Luo
Keyword(s):  
Simulation Model ◽  
Dynamic Models ◽  
Reference Data ◽  
Model Performance ◽  
Simulation Models ◽  
Validation Method ◽  
Evaluation Procedures ◽  
Serial Data ◽  
Multi Agent

Measuring the credibility of a simulation model has always been challenging due to its growing uncertainty and complexity. During the past decades, plenty of metrics and evaluation procedures have been developed for evaluating different sorts of simulation models. Most of the existing research focuses on the direct comparison of numerical results with a group of reference data. However, it is sometimes unsuitable for evolving dynamic models such as the multi-agent models. With the same condition, both the practical system and the simulation model perform highly dynamic actions. The credibility of the model with insufficient information, non-stationary states and changing environment is unable to acquire through a direct pair comparison. This paper presents a pattern-based validation method to complementarily extract hidden patterns that exist in both a simulation model and its reference data, and assess the model performance in a different aspect. Firstly, multi-dimensional perceptually important points strategy is modified to find the patterns exist in time-serial data. Afterward, a pattern organizing topology is applied to automatically depict required pattern from reference data and assess the performance of the corresponding simulation model. The extensive case study on three simulation models shows the effectiveness of the proposed method.

scholarly journals Train Vehicle Structure Design from the Perspective of Evacuation

2019 ◽  
Vol 32 (1) ◽  
Author(s):  
Hanzhao Qiu ◽  
Weining Fang
Keyword(s):  
Simulation Model ◽  
Dynamic Process ◽  
Simulation Models ◽  
Structure Design ◽  
Small Sample ◽  
Time Warping ◽  
Evacuation Simulation ◽  
Vehicle Structure ◽  
Dynamic Time

Abstract The safety of trains, a highly efficient mode of transportation, has attracted significant attention. In the vehicle structure design of a train, the evaluation of the passenger evacuation time is necessary. The establishment of a simulation model is the fastest, most convenient, and practical way to achieve this goal. However, few scholars have focused on the reliability of a passenger train evacuation simulation model. This paper proposes a new validation method based on dynamic time warping and multidimensional scaling. The proposed method validates the dynamic process of a simulation model, provides statistical results, and can be used for small-sample scenarios such as a train evacuation scenario. The results of a case study indicate that the proposed method is an effective and quantitative approach to the validation of simulation models in a dynamic process. Thus, this paper describes the influence of the train structure size on an evacuation based on the results of simulation experiments. The structural size factors include the door width, aisle width, and seat pitch. The experiment results indicate that a wide aisle and reasonable seat pitch can promote a proper evacuation. In addition, a normal train door width has no effect on an evacuation.

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