Iowa State University
United States of America
Dr. Mark Bryden is the founding director of the Simulation, Modeling and Decision Science program at the U.S. Department of Energy’s Ames Laboratory and is a professor of mechanical engineering at Iowa State University. Dr. Bryden’s research is focused on the federation of information from disparate sources (e.g., models, data, and other information elements) to create detailed models of engineered, human, and natural systems that enable engineering decision making for these complex systems. Dr. Bryden has published more than 180 peer-reviewed articles and co-authored the textbook Combustion Engineering. He has founded two successful startups based on his research work, and he has founded the nonprofit ETHOS, a community of 150+ researchers focused on meeting the needs for clean village energy in the developing world. He has received three patents, three R&D 100 awards, two Regional Excellence in Technology Transfer awards, and a National Excellence in Technology Transfer award. In 2013 he and his coauthors received the ASME Melville Medal. The Melville Medal was first awarded in 1927 and is the highest honor for the best original technical paper published in the ASME Transactions in the past two years. His professional experience includes three years as an engineer and 11 years as a manager at Westinghouse Electric in Idaho Falls, Idaho, and Pittsburgh, Pennsylvania. In addition, for more than 15 years Professor Bryden has worked on energy systems for the poor in a number of developing countries. Most recently he has worked in Mali, one of the poorest countries in the world, where he led an effort to develop the technology, infrastructure, and in-country support network needed to provide household lighting to remote off-grid villages.
Dr. Bryden’s research interests are broad but fit well under the umbrella of integrated computational environments and engineering decision making. Today one of the most critical issues in modeling and engineering is how to use the models and computing capabilities we have to improve our engineered products and processes. We have many powerful engineering modeling tools, but in many cases we cannot bring the full power of these tools to bear on engineering problems. Computational time, differing vocabularies between various disciplines, and the disparate nature of model creation all create barriers to the use of detailed model sets in engineering decision making. The challenge is that nearly all engineered products and processes are holistic systems composed of interdependent parts. Each of these parts is commonly analyzed with a separate model or set of models, and in many cases the interaction between the models is as important as the models themselves to the behavior and performance of the engineered product. Because of this, we need to be able to readily integrate the models and information required to create robust computational systems that accurately represent the fidelity and diversity of built, social, and natural systems. Within this area Dr. Bryden has worked on model integration, linking physical and virtual systems, visualization, and optimization. Although these tools can be applied in many areas, the primary applications that Dr. Bryden is examining are in the areas of energy, environment, and sustainability. This includes developing an integrated environmental model to address the sustainability of crop residue removal for bioenergy applications, developing an open source integration framework for interacting with CAD and analysis software, and developing tools to model and understand the impact of various energy system interventions in the developing world.
N. A. MacCarty and K. M. Bryden, “A Generalized Heat-Transfer Model for Shielded-Fire Household Cookstoves,” Energy for Sustainable Development, 33:96-107 (2016)
S. Suram and K. M. Bryden, “Integrating a Reduced-Order Model Server into the Engineering Design Process,” Advances in Engineering Software, 90:169–182 (2015)
P. E. Antonelli, K. M. Bryden, and R. LeSar, “A Model-to-Model Interface for Concurrent Multiscale Simulations,” Computational Materials Science, 123:244-251 (2016) [Editors Choice]