Response spectrum devices for active learning in earthquake engineering education
Richard K. Slocum,
Rachel K. Adams,
Kamilah Buker,
David S. Hurwitz,
H. Benjamin Mason,
Christopher E. Parrish,
Michael H. Scott
Affiliations
Richard K. Slocum
School of Civil and Construction Engineering, Oregon State University, 101 Kearney Hall, Corvallis, OR 97331, USA
Rachel K. Adams
School of Civil and Construction Engineering, Oregon State University, 101 Kearney Hall, Corvallis, OR 97331, USA
Kamilah Buker
School of Civil and Construction Engineering, Oregon State University, 101 Kearney Hall, Corvallis, OR 97331, USA
David S. Hurwitz
School of Civil and Construction Engineering, Oregon State University, 101 Kearney Hall, Corvallis, OR 97331, USA
H. Benjamin Mason
Honors College, Oregon State University, 450 Learning Innovation Center, Corvallis, OR 97331, USA; School of Civil and Construction Engineering, Oregon State University, 101 Kearney Hall, Corvallis, OR 97331, USA
Christopher E. Parrish
School of Civil and Construction Engineering, Oregon State University, 101 Kearney Hall, Corvallis, OR 97331, USA
Michael H. Scott
School of Civil and Construction Engineering, Oregon State University, 101 Kearney Hall, Corvallis, OR 97331, USA; Corresponding author.
Structural and geotechnical engineers regularly use response spectra to assess the response of civil infrastructure to earthquakes; however, the underlying concepts of response spectra are often difficult for civil engineering students to grasp. Hardware specifications for two low cost response spectrum devices (RSDs) facilitate an inductive approach for teaching response spectrum concepts to students. The RSDs, which consist of wooden masses, compression springs, and accelerometers, can be excited manually or on a portable shake table to show the effects of mass and stiffness on the dynamic response of structures subjected to earthquake ground motion. Auxiliary Python scripts record real time accelerometer data, enabling students to compare the observed RSD response to numerical computations. Keywords: Earthquake engineering, Structural dynamics, Inductive learning, Desktop Learning Modules
