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A room using carbon black mortar slabs (CBMS) as the electrical floor heating element has been built in our lab. Studies showed that an electrical power of about 123.8 W/m2 resulted in the indoor temperature rise of 10 °C within 330 min. Temperature distribution along the height of the room was uniform. Temperature rise was slightly higher if floor tiles rather than the wood flooring was used. In the process of heating, self-heating of CBMS has consumed more than 30% of the generated heat by Joule effect, which was advantageous for the stability of the thermal state. The indoor air absorbed over 50% of the generated heat. Results derived from repeated tests show that the electrical power of the CBMS system was stable during several cycles of heating. Further, the procedure and power consumption for the system to maintain a certain indoor temperature were studied. Continuous tests for 72 h has shown that the higher the indoor controlled temperature was, the longer the working time and the shorter the rest time in every cycle of heating were required. Accordingly, the power consumption to maintain the heat state increased with the controlled temperature increasing.

Electrical emission (EM) signals, which are generated from the concrete specimens under three-point bending tests, were conducted. It is shown that electrical emission phenomena are related to cracking of the specimens, cohesive failure, contact-separation etc. The simultaneous appearance of electric emission signals and visible cracks during the flexure loading of beams was also observed.

The external penalty function methods transform the basic optimization problem into alternative formulations such that numberical solutions are sought by solving a sequence of unconstrained minimization problem. This paper uses the external penalty function method to solve constrained optimal control problems for optimization design of underground reinforced concrete penstock. Through establishing the cost of construction of underground penstock as objective function and strength, stability and deformation as constrain conditions, hence we have solved the minimum cost constrained optimal control problems and gained the minimum cost. Due to the optimized design, the rate of reinforcement rebar decreased 15%

Infrared thermal imaging technology is one new method of the modern non-destructive testing. Expanding the qualitative analysis to quantitative characterization is hot and difficult of the infrared thermal imaging technology, that is to say, expanding assessing whether damage and judging injury location to structural integrity evaluation. The key lies in the extraction and description of the infrared thermal imaging characteristics parameters. This paper did fractal study on the experimental samples of infrared thermal imaging, including infrared thermal imaging graphics processing, fractal dimension calculation, realization of calculation program and gray, network and scale and so on, which is the foundation for further study on concrete structure damage and fracture or fracture criterion and the experimental calibration.

Due to the characteristic of the intuitivism of image, Ultrasonic tomography technology in non-destructive testing of concrete structure is attached importance. The combination of Wavelet and Neural Networks will constructs a kind of wavelet neural network, which can be used to study the segmentation method of Ultrasonic CT color image. Instead of the traditional Sigmoid function, Wavelet basis function can organically fuse the good time-frequency domain feature and the adaptive advantage of neural network, and overcome the limitations of the slow convergence rate and easily felling into the local minimum of BP neural network.

Carbon fiber reinforced concrete (CFRC) is an intrinsically smart material that can sense not only compressive or tensile stress, but also temperature. The thermal self-monitoring ability is associated with the Seebeck effect. An experimental study was made to examine the relationship between the temperature differential (ΔT) and thermoelectric force (TEF)—its sensitivity and repeatability, its response time and the influence of ambient temperature (Ta) on TEF. The results show that TEF is proportional to ΔT over a wide range of temperature, and the thermal self-monitoring CFRC possesses high sensitivity and good repeatability. The Ta has no influence on TEF. Although the response time of CFRC is not fast enough because of its low heat conductivity, it can be used as a thermal sensor embedded in massive concrete structures, such as water dams and bridges, where the temperature changes slowly.