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If leadership and collaboration require identifying direction, discovering alignment, collaborating across difference, and building trust among people to increase commitment, then effective communication is critical to both effective leadership and collaboration. Professional communications are strengthened by establishing clear connections, losing the fear of vulnerability, listening and responding to the messages received from others, and allowing spontaneous interaction to replace the prescribed and expected. The key is using one’s whole self to tell the most important stories and to listen deeply to the stories of others.
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Two Day Professional Short Course
(Available for Corporate Training)
Verification and Validation in Scientific Computing
About the Course
Engineering systems must increasingly rely on computational simulation for predicted performance, reliability, and safety. Computational analysts, designers, decision makers, and project managers who rely on simulation must have practical techniques and methods for assessing simulation credibility. This short course presents modern terminology and effective procedures for verification of numerical simulations, validation of mathematical models, and uncertainty quantification of nondeterministic simulations. The techniques presented in this course are applicable to a wide range of engineering and science applications, including fluid dynamics, heat transfer, solid mechanics, and structural dynamics. The mathematical models considered are given in terms of partial differential or integral equations, formulated as initial and boundary value problems. The computer codes that implement the mathematical models can use any type of numerical method (e.g., finite volume, finite element) and can be developed by commercial, corporate, government, or research organizations. A framework is provided for incorporating a wide range of error and uncertainty sources identified during model formulation and development, verification activities, and validation processes with the goal of estimating the total prediction uncertainty of the simulation. While the focus of the course is on modeling and computational simulation, experimentalists will benefit from a detailed discussion of techniques for designing and conducting high quality validation experiments. Application examples are primarily taken from the fields of fluid dynamics and heat transfer, but the techniques and procedures apply to all application areas in engineering and science. The course closely follows the course instructors’ book, Verification and Validation in Scientific Computing, Cambridge University Press (2010).
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“Curiosity keeps us moving forward, exploring, experimenting, opening new doors”
- Walt Disney
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