Utilization of SHM Methodologies to Detect Trunnion Friction in Tainter Gates Quincy G. Alexander Research Civil Engineer Information Technology Laboratory 19 September 2017

Why Monitor Trunnion Friction Case Study Folsom Dam Spillway Gate Failure Sacramento, CA, July 1995 Gate #3 opened to maintain the flow of the river during a scheduled power plant shutdown At 2.4 feet operator felt an “unusual vibration” and heard grinding noises Gate failed releasing approximately 40,000 cfs 40% of Folsom Lake storage released Lock operator’s responsiveness reduced further damage downstream Due to the emergency action taken by the Folsom Dam operator when he noticed the failure of the gate, overtopping of Nimbus Dam was prevented and the water released from Folsom Lake was safely conveyed and attenuated.  As a result, the consequences of the gate failure were limited to the damage to the gate and the loss of stored water.  The gates were repaired at a cost of approximately $20 million.

Why Monitor Trunnion Friction Case Study-Lessons Learned Forensics revealed the cause of the malfunction to be excessive friction at the trunnion Failure initiated at a diagonal brace Caused by the corrosion at the pin-hub interface Operated nearly 40 years with no problems Failure may have been avoided with: Routine maintenance (e.g. lubrication) Protection from weathering Routine Inspections Due to the additional friction forces, the loads experienced by the trunnion pin caused increased loading in the gate struts and braces of the gate.  The gate struts are primarily compression members, but friction at the pin-hub interface induced a bending stress during gate operation. In order to better handle these loads, the struts are connected with diagonal braces that take the stress as axial loads. The resulting loads in these members exceeded the capacity of the strut-brace-connection bolts compromising the structural integrity of the gate.  As the gate was operated, the failure initiated at a diagonal brace between the lowest and second lowest struts. Increasing corrosion at the pin-hub interface raised the coefficient of friction and, therefore, the bending stress in the strut and the axial force in the brace. The capacity of the brace connection was exceeded and it failed. This caused the load to redistribute and the failure progressed, eventually buckling the struts.

Structural Health Monitoring ERDC’s view of SHM Use field observations, numerical simulations, and statistical models to: Detect damage: location, type, severity Observe degradation over time Predict future degradation and reliability We seek to provide tools, using this framework that will inform: Maintenance/Repair/Rehab decisions Operational decisions Post-emergency evaluations

Trunnion Friction Study Application of SHM paradigm to Trunnion Friction problem Trunnion friction monitoring was identified as a need by districts Low-cost Minimal instrumentation Output meaningful to operators

Trunnion Friction Study Life safety/economic justification How is damage defined What operational and environmental conditions must be considered Limitations on acquiring data Operational Evaluation Limitations….no good sensors available for this application that would allow for direct measurement of friction

Trunnion Friction Study Selecting sensor types, number, and location Data acquisition hardware Data storage Ability to normalize the data Data Acquisition

Trunnion Friction Study Identification of features that allows one to distinguish between the undamaged and damage cases Comparing measured response with observations of the degrading system Validated FEM can be used to introduce flaws and identify features Feature Extraction Externally applied moment ~3,378 kip-in Estimated moment from diagonal strain measurements ~3,606 kip-in Estimated moment 6.7% over actual Approach feasible Physical testing 1/5th scale model Big cliff bass of design Strain Measurement Numerical Model

Trunnion Friction Study Identification of features that allows one to distinguish between the undamaged and damage cases Comparing measured response with observations of the degrading system Validated FEM can be used to introduce flaws and identify features Feature Extraction Estimated moment ranged from 0.4% to 9% over actual across 10 loading scenarios Approach feasible Physical testing 1/5th scale model Big cliff bass of design Physical Model

Trunnion Friction Study Using statistical models to transform features into actual performance-level decisions Implementation of algorithms that operate on the feature to quantify damage Supervised learning, unsupervised learning/outlier detection Decision Making

Summary Trunnion friction is a major concern and is difficult to measure ERDC has developed a low-cost methodology to estimate frictional moments at trunnions Numerical and physical simulations indicate methodology may provide estimates of frictional moments within a few percent of the actual values Field demonstration pending

Questions? Quincy Alexander 601-634-2905 Quincy.G.Alexander@usace.army.mil