Engineers recognized with national award

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Engineers recognized with national award

Engineers_SEK_KPL_PhotoEngineers Steve Kelly and Pat Lee have been recognized by the American Statistical Association (ASA) with the 2014 Statistics in Chemistry Award. The award recognizes outstanding collaborative endeavors between statisticians and chemists for their innovative use of statistics to solve a problem in chemistry and the impact of the solution.
Kelly and Lee co-authored a paper with colleagues from the Pacific Northwest National Laboratory (PNNL) that summarized small-scale tank mixing and waste transfer test results. Their work involved studying the process for mixing and transferring radioactive waste from storage tanks to the Waste Treatment Plant, where it will be converted to a safer, stable glass waste form. The work consisted of developing models based on small-scale test data to enable predicting mixing and transfer performance at full scale.

“Working with PNNL’s Applied Statistics and Computational Modeling group was an excellent experience,” Kelly said. “They helped us understand what is important for model optimization and how to identify parameters not significantly adding to the correlation.”

“This work was a collaborative effort between disciplines from beginning to end,” Lee said. “We worked closely with statisticians to design a set of experiments that could be modeled and included the variables we considered important to scaling the mixing and transfer process.”

Regarding the paper and corresponding research, the ASA wrote, “The process scale-up problem addressed in their work is one that is common, yet remains challenging for statisticians, engineers and scientists. In the statistical literature, little-to-no published work exists on this important topic. Their unique scale-up modeling and overall approach is important with many potential applications in a wide array of industries and technical disciplines. By combining the principles of statistics and engineering, the honorees created improved models and gained a better understanding of the system.”