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.

Exposing System and Model Disparity and Agreement Using Wavelets

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Andrew D. Atkinson ◽  
Raymond R. Hill ◽  
Joseph J. Pignatiello ◽  
G. Geoffrey Vining ◽  
Edward D. White ◽  
...  
Keyword(s):  
Development Process ◽  
Model Development ◽  
Model Verification ◽  
Verification And Validation ◽  
High Dimensional ◽  
Model Data ◽  
Accurate Representation ◽  
Model Verification And Validation ◽  
Model Development Process ◽  
Functional Output

Model verification and validation (V&V) remain a critical step in the simulation model development process. A model requires verification to ensure that it has been correctly transitioned from a conceptual form to a computerized form. A model also requires validation to substantiate the accurate representation of the system it is meant to simulate. Validation assessments are complex when the system and model both generate high-dimensional functional output. To handle this complexity, this paper reviews several wavelet-based approaches for assessing models of this type and introduces a new concept for highlighting the areas of contrast and congruity between system and model data. This concept identifies individual wavelet coefficients that correspond to the areas of discrepancy between the system and model.

scholarly journals The General Principles of the Transportation Simulation Model Development and Validation

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Simulation Model ◽  
Model Validation ◽  
Management Strategies ◽  
Model Development ◽  
Simulation Models ◽  
Model Verification ◽  
Microscopic Simulation ◽  
Calibration Methods ◽  
Transportation Simulation ◽  
Development And Validation

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.

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.

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.

Laboratory study and computer model development related to gross solids' movement in combined sewers

1996 ◽  
Vol 33 (9) ◽  
pp. 39-47 ◽  
Author(s):  
John W. Davies ◽  
Yanli Xu ◽  
David Butler
Keyword(s):  
Computer Simulation ◽  
Pipe Flow ◽  
Model Development ◽  
Simulation Models ◽  
Laboratory Studies ◽  
Pilot Model ◽  
Sewer Systems ◽  
Flow Quality ◽  
Computer Simulation Models ◽  
Theoretical Considerations

Significant problems in sewer systems are caused by gross solids, and there is a strong case for their inclusion in computer simulation models of sewer flow quality. The paper describes a project which considered methods of modelling the movement of gross solids in combined sewers. Laboratory studies provided information on advection and deposition of typical gross solids in part-full pipe flow. Theoretical considerations identified aspects of models for gross solids that should differ from those for dissolved and fine suspended pollutants. The proposed methods for gross solids were incorporated in a pilot model, and their effects on simple simulations were considered.

scholarly journals Modeling Building Stock Development

2021 ◽  
Vol 13 (2) ◽  
pp. 723
Author(s):  
Antti Kurvinen ◽  
Arto Saari ◽  
Juhani Heljo ◽  
Eero Nippala
Keyword(s):  
Model Development ◽  
Housing Demand ◽  
Quality Data ◽  
Building Stock ◽  
Test Arena ◽  
Climate Targets ◽  
Wide Range ◽  
Key Variables ◽  
The Impact

It is widely agreed that dynamics of building stocks are relatively poorly known even if it is recognized to be an important research topic. Better understanding of building stock dynamics and future development is crucial, e.g., for sustainable management of the built environment as various analyses require long-term projections of building stock development. Recognizing the uncertainty in relation to long-term modeling, we propose a transparent calculation-based QuantiSTOCK model for modeling building stock development. Our approach not only provides a tangible tool for understanding development when selected assumptions are valid but also, most importantly, allows for studying the sensitivity of results to alternative developments of the key variables. Therefore, this relatively simple modeling approach provides fruitful grounds for understanding the impact of different key variables, which is needed to facilitate meaningful debate on different housing, land use, and environment-related policies. The QuantiSTOCK model may be extended in numerous ways and lays the groundwork for modeling the future developments of building stocks. The presented model may be used in a wide range of analyses ranging from assessing housing demand at the regional level to providing input for defining sustainable pathways towards climate targets. Due to the availability of high-quality data, the Finnish building stock provided a great test arena for the model development.

scholarly journals Micro-mechanical investigation of railway ballast behavior under cyclic loading in a box test using DEM: effects of elastic layers and ballast types

2019 ◽  
Vol 21 (4) ◽  
Author(s):  
Nishant Kumar ◽  
Bettina Suhr ◽  
Stefan Marschnig ◽  
Peter Dietmaier ◽  
Christof Marte ◽  
...  
Keyword(s):  
Cyclic Loading ◽  
Early Stage ◽  
Damage Model ◽  
Simulation Models ◽  
Railway Track ◽  
Maintenance Cost ◽  
Particle Movement ◽  
Railway Ballast ◽  
Elastic Layers ◽  
The Impact

Abstract Ballasted tracks are the commonly used railway track systems with constant demands for reducing maintenance cost and improved performance. Elastic layers are increasingly used for improving ballasted tracks. In order to better understand the effects of elastic layers, physical understanding at the ballast particle level is crucial. Here, discrete element method (DEM) is used to investigate the effects of elastic layers – under sleeper pad ($$\text {USP}$$USP) at the sleeper/ballast interface and under ballast mat ($$\text {UBM}$$UBM) at the ballast/bottom interface – on micro-mechanical behavior of railway ballast. In the DEM model, the Conical Damage Model (CDM) is used for contact modelling. This model was calibrated in Suhr et al. (Granul Matter 20(4):70, 2018) for the simulation of two different types of ballast. The CDM model accounts for particle edge breakage, which is an important phenomenon especially at the early stage of a tamping cycle, and thus essential, when investigating the impact of elastic layers in the ballast bed. DEM results confirm that during cyclic loading, $$\text {USP}$$USP reduces the edge breakage at the sleeper/ballast interface. On the other hand, $$\text {UBM}$$UBM shows higher particle movement throughout the ballast bed. Both the edge breakage and particle movement in the ballast bed are found to influence the sleeper settlement. Micro-mechanical investigations show that the force chain in deeper regions of the ballast bed is less affected by $$\text {USP}$$USP for the two types of ballast. Conversely, dense lateral forces near to the box bottom were seen with $$\text {UBM}$$UBM. The findings are in good (qualitative) agreement with the experimental observations. Thus, DEM simulations can aid to better understand the micro-macro phenomena for railway ballast. This can help to improve the track components and track design based on simulation models taking into account the physical behavior of ballast. Graphical Abstract

scholarly journals Assessing asset monitoring levels for maintenance operations

2015 ◽  
Vol 26 (5) ◽  
pp. 632-659 ◽  
Author(s):  
Abdullah A Alabdulkarim ◽  
Peter Ball ◽  
Ashutosh Tiwari
Keyword(s):  
Asset Management ◽  
Business Models ◽  
Discrete Event ◽  
Dynamic Modelling ◽  
Simulation Models ◽  
Content Type ◽  
Event Simulation ◽  
Product Service ◽  
Asset Monitoring ◽  
The Impact

Purpose – Asset management has recently gained significance due to emerging business models such as Product Service Systems where the sale of asset use, rather than the sale of the asset itself, is applied. This leaves the responsibility of the maintenance tasks to fall on the shoulders of the manufacturer/supplier to provide high asset availability. The use of asset monitoring assists in providing high availability but the level of monitoring and maintenance needs to be assessed for cost effectiveness. There is a lack of available tools and understanding of their value in assessing monitoring levels. The paper aims to discuss these issues. Design/methodology/approach – This research aims to develop a dynamic modelling approach using Discrete Event Simulation (DES) to assess such maintenance systems in order to provide a better understanding of the behaviour of complex maintenance operations. Interviews were conducted and literature was analysed to gather modelling requirements. Generic models were created, followed by simulation models, to examine how maintenance operation systems behave regarding different levels of asset monitoring. Findings – This research indicates that DES discerns varying levels of complexity of maintenance operations but that more sophisticated asset monitoring levels will not necessarily result in a higher asset performance. The paper shows that it is possible to assess the impact of monitoring levels as well as make other changes to system operation that may be more or less effective. Practical implications – The proposed tool supports the maintenance operations decision makers to select the appropriate asset monitoring level that suits their operational needs. Originality/value – A novel DES approach was developed to assess asset monitoring levels for maintenance operations. In applying this quantitative approach, it was demonstrated that higher asset monitoring levels do not necessarily result in higher asset availability. The work provides a means of evaluating the constraints in the system that an asset is part of rather than focusing on the asset in isolation.

Performance Modeling of Desiccant Wheels: 1 — Model Development

2008 ◽  
Author(s):  
Chaoqin Zhai ◽  
David H. Archer ◽  
John C. Fischer
Keyword(s):  
Model Development ◽  
Axial Direction ◽  
Performance Model ◽  
Design Parameters ◽  
Residual Water ◽  
One Dimensional ◽  
Operating Variables ◽  
Steady State Operation ◽  
Rotary Speed ◽  
The Impact

This paper presents the development of an equation based model to simulate the combined heat and mass transfer in the desiccant wheels. The performance model is one dimensional in the axial direction. It applies a lumped formulation in the thickness direction of the desiccant and the substrate. The boundary conditions of this problem represent the inlet outside/process and building exhaust/regeneration air conditions as well as the adiabatic condition of the two ends of the desiccant composite. The solutions of this model are iterated until the wheel reaches periodic steady state operation. The modeling results are obtained as the changes of the outside/process and building exhaust/regeneration air conditions along the wheel depth and the wheel rotation. This performance model relates the wheel’s design parameters, such as the wheel dimension, the channel size and the desiccant properties, and the wheel’s operating variables, such as the rotary speed and the regeneration air flowrate, to its operating performance. The impact of some practical issues, such as wheel purge, residual water in the desiccant and the wheel supporting structure, on the wheel performance has also been investigated.

scholarly journals A Synoptic Weather Typing Approach to Simulate Daily Rainfall and Extremes in Ontario, Canada: Potential for Climate Change Projections

2010 ◽  
Vol 49 (5) ◽  
pp. 845-866 ◽  
Author(s):  
Chad Shouquan Cheng ◽  
Guilong Li ◽  
Qian Li ◽  
Heather Auld
Keyword(s):  
Model Development ◽  
Daily Rainfall ◽  
Simulation Models ◽  
Rainfall Simulation ◽  
Rainfall Events ◽  
Logit Regression ◽  
Synoptic Weather ◽  
Weather Typing ◽  
Synoptic Weather Typing ◽  
Cumulative Logit

Abstract An automated synoptic weather typing and stepwise cumulative logit/nonlinear regression analyses were employed to simulate the occurrence and quantity of daily rainfall events. The synoptic weather typing was developed using principal component analysis, an average linkage clustering procedure, and discriminant function analysis to identify the weather types most likely to be associated with daily rainfall events for the four selected river basins in Ontario. Within-weather-type daily rainfall simulation models comprise a two-step process: (i) cumulative logit regression to predict the occurrence of daily rainfall events, and (ii) using probability of the logit regression, a nonlinear regression procedure to simulate daily rainfall quantities. The rainfall simulation models were validated using an independent dataset, and the results showed that the models were successful at replicating the occurrence and quantity of daily rainfall events. For example, the relative operating characteristics score is greater than 0.97 for rainfall events with daily rainfall ≥10 or ≥25 mm, for both model development and validation. For evaluation of daily rainfall quantity simulation models, four correctness classifications of excellent, good, fair, and poor were defined, based on the difference between daily rainfall observations and model simulations. Across four selected river basins, the percentage of excellent and good simulations for model development ranged from 62% to 84% (of 20 individuals, 16 cases ≥ 70%, 7 cases ≥ 80%); the corresponding percentage for model validation ranged from 50% to 76% (of 20 individuals, 15 cases ≥ 60%, 6 cases ≥ 70%).

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