Modelling, verification and validation

Text Box: Simulation modelling, verification, validation and quality management One-day course Introduction A model yielding erroneous predictions may entail serious consequences, not least in terms of cost, safety and legal liability. This course details best-practice techniques for minimising the opportunity for error in a generic engineering analysis process. The course begins by carefully reviewing the modelling and analysis process and identifying the potential sources of error arising at each stage. A simulation process invariably commences by describing the object to be analysed, followed by an idealisation of the problem characteristics. The idealisation assumptions made at this stage will directly impact the validity of the model and need to be clearly identified. Moreover, the model data needs to be of sufficient accuracy to deliver the required solution accuracy. Techniques to estimate the required accuracy of models and data will be discussed. Computational modelling is the next step in the simulation process, whereby the idealised model is converted into an approximate numerical model in analysis software. Numerical accuracy and solution error are discussed along with best-practice techniques for minimising them. Model verification is discussed in the context of determining the degree to which the computational model is an accurate representation of the mathematical model Model validation is discussed in the context of determining the degree to which the simulation model is an accurate representation of the object behaviour from the perspective of its intended use. Real-world examples of the consequences of inadequate verification and validation of simulation models will be presented. Finally the course introduces and explains, in the context of computational modelling, the basic requirements of Quality Management System ISO 9001 and NAFEMS QSS 001 (a supplement to ISO 9001 for engineering simulation). This section of the material focuses on gaining an understanding of the concepts of ISO 9001 and QSS 001 quality models, and their practical application in managing an engineering simulation project. The development of engineering simulation procedures suitable for implementation into a quality management system will be discussed and examples provided. Formal quality certification requirements will be briefly discussed along with issues relating to the effects of an implemented quality system on simulation product quality, and on the working practices and culture of the organisation. Course content Introduction Simulation modelling, verification, validation and quality management The simulation process Object Mathematical domain Computational domain Discrete solution Continuous solution Behaviour Behavioural domain Object Parameters Behaviour Mathematical domain Idealisation error Data error Error estimation and treatment Computational domain Approximation error Calculation error Error estimation and treatment Model verification Verification requirements Approaches to model verification Verification procedures Model validation Validation requirements Approaches to model validation Validation procedures Quality system ISO 9001 and NAFEMS QSS ISO 9000 family of standards Quality management principles Process based quality management NAFEMS QSS 001 Quality requirements Quality management system Management responsibility Resource management Product realisation Measurement, analysis and improvement Quality management of simulation projects Simulation project management Human and computer resources Simulation procedures Conclusions Simulation quality management in practice Design, implementation and maintenance of the management system Certification and audit of the management system * Partial accreditation

Presenter: Jonathan Smith

Duration: One day

Synopsis

Simulation models need to be fit for their intended use.

This course identifies the common sources of error, uncertainty and mistakes that inevitably arise in the modelling process, and discusses best practice techniques for modelling, verification and validation in the context of systematic simulation management .