Shear transfer across a diagonal crack in reinforced concrete strengthened with externally bonded FRP fabric

Aging concrete infrastructure in developed economies and more recently constructed concrete infrastructure in the developing world are frequently found to be deficient in structural strength relative to current needs. This can be attributed to a variety of factors including deterioration, construction defects, accidental damage, changes in understanding and failure to design for future loading requirements. Strengthening existing concrete structures can be a cost and carbon effective alternative to replacement. A competitive option for the strengthening of concrete slab-on-beam structures that are deficient in shear capacity is the U-wrapping of the down-stand beam portion of the shear span with externally bonded FRP fabric. While guidance exists for the strengthening of reinforced concrete by U-wrapping, the interaction between internal steel reinforcement, concrete and external FRP in the presence of a dominant diagonal shear crack is not well understood. An approach adopted in previous work has been to explore this interaction through conventional push-off testing. In conventional push-off testing, unlike in a beam, the shear plane is parallel to the direction of loading and perpendicular to the principal fibre orientation. This paper presents a novel push-off test variation in which the shear plane is inclined at 45° to the direction of loading and the principal fibre orientation. A variety of reinforcement ratios, FRP thicknesses and FRP end conditions are modelled. The implications of inclined cracking on debonding of FRP are investigated. The suitability and relevance of inclined push-off tests for further work in this area is also assessed. © 2013, NetComposite Limited.

Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.