Publication Abstract




Proceedings of the 42nd Annual Conference on Deep Foundations, 2017, New Orleans, LA, USA, (DFI)

Probabilistic Subsurface Characterization for Transmission Line Foundation Design
Peter M. Kandaris, Jogi S. Gadok and Neil T. Russo

Assessment of subsurface data for foundation design in support of long high voltage electric transmission lines is best accomplished using a probabilistic strategy since only a small portion of structure locations are typically sampled. Probabilistic approaches provide a tool to evaluate site uncertainty in a systematic and rational manner. This paper provides a case history of a risk-based design approach for a recently completed 191-mile long 69/161/345kV steel monopole transmission line traversing Central Iowa. The project owner made available limited subsurface information at project initiation, requiring the design team to obtain additional data within a constrained budget for 1067 large diameter, laterally-loaded deep drilled shaft reinforced concrete piers. The team commissioned a geologic desktop study to reduce uncertainty in subsurface evaluations and aid in selecting additional sample sites. In total, investigation programs tested approximately 15 percent of structure sites. The paper details the probabilistic approach used to estimate foundation geotechnical design parameters, with information from the various studies categorizing strata both laterally and with depth. Low-bound parameters were estimated via a statistical approach at a pre-determined reliability level. Significant savings resulted from this approach when compared to conservative deterministic processes. Project QA/QC logged subsurface soil conditions during foundation excavation, then compared as-found conditions to the conditions assumed for design. The team redesigned foundations if either a non-conservative variance in soil conditions was observed or if bedrock elevation differed significantly from design assumptions. As a result, only 22 out of 1067 foundations required modification during construction (2% variance from initial design) with negligible impact on the construction budget and schedule.


 article #2822; publication #1037 (AM-2017)