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My Story: John L. Swanson—ANS member since 1978
. . . and in 2019, on his 90th birthday.
Swanson in 1951, the year of his college graduation . . .
My pre-college years were spent in a rural suburb of Tacoma, Wash. In 1947, I enrolled in Reed College, a small liberal arts school in Portland, Ore.; I majored in chemistry and graduated in 1951. While at Reed, I met and married a young lady with whom I would raise 3 children and spend the next 68 years of my life—almost all of them in Richland, Wash., where I still live.
I was fortunate to have a job each of my “college summers” that provided enough money to cover my college costs for the next year; I don’t think that is possible these days. My job was in the kitchen/dining hall of a salmon cannery in Alaska. Room and board were provided and the cannery was in an isolated location, so I could save almost every dollar of my salary.
Jagjit Singh Matharu, Vidya Devi
Nuclear Science and Engineering | Volume 193 | Number 3 | March 2019 | Pages 314-324
Technical Paper | doi.org/10.1080/00295639.2018.1538280
Articles are hosted by Taylor and Francis Online.
This paper presents a novel approach for uncertainty propagation of neutron-induced activation cross-section measurement using unscented transformation (UT). Generally, the first-order sensitivity analysis (sandwich formula) method is used for uncertainty propagation in cross-section measurement. It is based on a linear approximation of Taylor series expansion of the function of input parameters and gives satisfactory results for smooth nonlinear functions having relatively small uncertainties. On the contrary, the UT technique is completely defined by the moments of random process and hence produces better results for error propagation in the nonlinear case with large uncertainties. The UT method is easier to implement and gives results as accurate as the sandwich formula and Monte Carlo techniques. This work examines the application of the UT method in nuclear science as an alternate to the sandwich formula and Monte Carlo methods.