Eng

Steel shear tab connections connect beams to columns and girders. While extended shear tab (EST) connections have been studied for stability and strength, their impact on the lateral torsional buckling (LTB) capacity of I-beams has not been explored. To address this research gap, the present study uses finite element (FE) modelling to examine how EST connection details affect the LTB capacity of I-beams. Several parameters, such as shear tab thickness, bolt configurations, unbraced beam length, bolt distance from the supporting member, and stabilizer plates, are examined. Results show that steel stabilizer plates can significantly improve LTB resistance of laterally unsupported I-beams with EST connections, by up to 61% compared to unstiffened connections. However, beams connected through unstiffened ESTs, regardless of whether a single or double vertical bolt arrangement is used, may exhibit substantially lower LTB strengths than those predicted by CSA S16-19 and ANSI/AISC 360-22, particularly in deeper sections. Finally, an alternative connection configuration employing a standard channel section in place of the conventional shear tab plate is also investigated. FE analysis shows that this channel-based detail can improve the LTB capacity of I-beams by about 27% for the W410X54 beam section, compared to standard shear tab connections.

This study investigates flood-induced dynamic responses of bridge piers and local scour around pile-group foundations, using the Jangwani Bridge in Tanzania as a case study. Separate fluid–structure interaction and coupled hydrodynamic–sediment transport scour models were developed for the bridge pier and pile-group foundation, respectively, to examine hydrodynamic forces, displacements, stresses, and scour evolution under different pier cross sections, approach-flow velocities, water levels, and pile diameters. The results show that the short-duration hydrodynamic response of bridge piers to the initial flood impact is distinctly transient and comprises three stages: initial impact, damped oscillation, and quasi-steady flow-past response. Under representative conditions, the peak transient impact force is 1.61–2.93 times the quasi-steady hydrodynamic load. Pier cross-sectional shape significantly affects the structural response, with the circular section exhibiting lower peak impact force and maximum principal stress than the square and rectangular sections. The fluid–structure interaction coefficient ranges from 0.98 to 1.41, indicating that the mean force predicted with fluid–structure interaction exceeds that for a rigid pier in most cases. Local scour around pile-group foundations develops rapidly at first, followed by slower growth toward the end of the 3000 s simulations. The scour hole is concentrated mainly near the upstream front-row piles, whereas the downstream rear-row piles experience less scour because of shielding. Under the selected reference condition and local perturbations, approach-flow velocity has the greatest effect on maximum scour depth, followed by water level and pile diameter. These findings provide a basis for flood-resilient bridge-substructure design, foundation scour protection, and construction-stage safety management in floodplains.

Multivariate control charts combine a monitoring statistic, a control limit, and a sequential signaling rule. This study evaluates the incremental contribution of principal component analysis (PCA) features to a learned score chart based on lagged measurements. Each chart is calibrated using independent healthy trajectories and a rule requiring three consecutive exceedances, under a common nominal run-level alarm criterion. The charts are compared in two simulation case studies—an eight-channel autoregressive (AR) benchmark with ten repeated fitting experiments and a Tennessee Eastman Process (TEP) dataset—using healthy-run alarm rates, detection proportions, and a mean capped signal delay. This delay criterion is measured in post-change samples and penalizes faults undetected within the monitoring horizon. In the AR case, adding residual energy Q to the model using raw lags reduced the mean capped signal delay from 45.0 to 41.2 samples; the full PCA–ML and multivariate exponentially weighted moving average (MEWMA) charts had mean capped delays of 41.5 and 36.1 samples, respectively. In the TEP case, excluding three provider-flagged faults, mean capped delays were 78.6 samples for raw-lag learning, 27.2 for lags plus Q, 29.5 for full PCA–ML, and 16.8 for MEWMA. Realized healthy-run alarm rates differed across procedures. Family-level analyses relate the AR results to fault-direction geometry. Measurement noise increased alarm rates, and covariance regularization affected the TEP MEWMA response to noise. The findings support a comparator-specific benefit from residual features, without establishing general superiority, detection of fault mechanisms absent from supervised training, or performance on operating-plant data.