Verification & Validation of Models and Simulations Combo Course (Virtual Classroom)

The modeling process itself introduces participants to uncertainties due to a variety of factors and approximations made during modeling simulations. The techniques in this series of courses will give the learner the techniques and procedures for verification of numerical simulations, validation of mathematical models, and uncertainty quantification for assessing the credibility and total uncertainty of the predicted performance, reliability, and safety of engineering systems. Combined participants will make more effective, risk-informed decisions for models and simulations. 

This official ASME learning path consists of two courses:

Course 1: Verification and Validation in Scientific Computing 

In ASME’s Verification and Validation in Scientific Computing course, learn modern terminology, practical techniques, and procedures for verification of numerical simulations, validation of mathematical models, and uncertainty quantification for assessing the credibility of the predicted performance, reliability, and safety of engineering systems.

• Schedule: this course commences at 10:30 AM and ends at 3:30 PM Eastern each day, with breaks scheduled throughout.

Course 2: Probabilistic and Uncertainty Quantification Methods for Model Verification & Validation 

Learn effective procedures and the systematic way to predict uncertainties in models in ASME’s Uncertainty Quantification Methods for Model Verification & Validation course.

• Schedule: This course runs from 9:30 AM and 1:30 PM and 2 PM – 6 PM Eastern each day, with breaks scheduled throughout.

Who should attend?

This course benefits model developers, computational analysts, code developers, experimentalists, and software engineers. Managers directing this work and project engineers relying on computational simulations for decision-making will also find this course to be beneficial. The course will discuss the responsibilities of organizations and individuals serving in various positions where computational simulation software, mathematical models, and simulation results are produced. An undergraduate or advanced degree in engineering or the physical sciences is recommended. Training and experience in computational simulation or experimental testing is also helpful.

This course is essential for engineers, scientists, and technical managers concerned with managing uncertainties in model predictions used to make decisions in the engineering design and evaluation process. Please visit the individual course pages for detailed information.

These ASME Virtual Classroom courses are held live with an instructor on our online learning platform. Certificate of completion will be issued to registrants who successfully attend and complete the course