Nicholas Brake, Ph.D.
Associate Professor
We sought to improve the performance of offshore steel-concrete-steel (SCS) shells by enhancing the bond between the steel-concrete interface by using an array of welded mini steel shear studs. Laboratory experiments and finite element analysis was conducted to quantify the mode I peeling and mixed mode strength of the enhanced steel-concrete interface. A large-scale steel-concrete-steel shell was then designed using the elastic limiting strength data obtained from experimentation.
Pervious concrete is a material that allows surface water infiltration through the media to reduce flooding and surface water accumulation. Concrete is a quasi-brittle material that has a relatively large fracture process zone that influences the strength properties of the structural system.
In this research, we sought to quantify the fracture and strength size effects of two different pervious concrete mixes of high and low porosity which led to the development of a modified porosity-dependent size effect model. The equation can be used to predict the modulus of rupture of different size pervious concrete structural systems using tensile strength, size, and porosity.
According to the American Coal Ash Association, 117 million tons of coal combustion products (CCPs) were produced in the United States, while only 61 million tons were utilized in civil engineering applications. Fly ash is one of the most common CCPs, which is utilized frequently as cement replacement and has also been proven to improve the durability of the concrete substantially.
Coal bottom ash (BA), on the other hand, is a granular and porous material. BA is the incombustible material that is not burnt during the coal combustion process and is extracted at the bottom side of coal combustion furnace in thermal power plants where the coarser parts are collected. In this research, we explored the use of a pulverized ultra-fine bottom ash as a cement replacement.
This research is focused on developing a doped ferrimagnetic engineered cementitious composite (MECC) capable of efficient electromagnetic transport that has low dependency on ambient temperature and moisture fluctuations. The objective is to reduce the bulk dependency of the system on pore solution ionic conductivity and increase the influence of electrical transport with the use of ferromagnetic agents and a cocktail of short steel fibers. There is a need to optimize the pore network, pore solution, ferrimagnetic doping agents, and steel fiber to maximize magnetic permeability and minimize energy losses.
This research is focused on developing an artificial neural network to predict the stress and deflection response of a pavement system containing a sub-surface anomaly and subjected to combined environmental and mechanical loads. An extensive finite element test battery was conducted to develop a response database capable of generating a robust artificial neural network capable of predicting the critical pavement responses. Closed-form multiple linear regression models were then derived to predict the stress amplifications generated because of the sub-surface anomalies.