Based on the capacity models in the 2008 edition of the American Concrete Institute (ACI) Standard Building Code Requirements for Structural Concrete, a more realistic limit state function is built for reinforced concrete (RC) columns with random eccentricity. Then, we discuss the applicability of the load and resistance factors in the code, which is mainly based on reliability calibrations with a fixed eccentricity criterion. Taking the wind dominated combination as an example, representative cases are established by selecting typical values of four related design parameters. Using the load and resistance models in previous reliability calibration of the code, the probabilistic distribution of eccentricity and the statistics of column resistance are analyzed for each case. The analysis indicates that the possible eccentricity shows a scatter over a large range, and the probabilistic model of column resistance varies from case to case, which is largely different from the constant resistance model assumed in previous reliability calibration. With Monte Carlo simulation (MCS), the column reliability is calculated and obtained for different cases. The results
This paper presents a bias drift self-calibration method for micro-electromechanical systems (MEMS) gyroscopes based on noise-suppressed mode reversal without the modeling of bias drift signal. At first, the bias drift cancellation is accomplished by periodic switching between operation mode of two collinear gyroscopes and subtracting the bias error which is estimated by the rate outputs from a consecutive period interval; then a novel filtering algorithm based on improved complete ensemble empirical mode decomposition (improved complete ensemble empirical mode decomposition with adaptive noise—CEEMDAN) is applied to eliminate the noise in the calibrated signal. A set of intrinsic mode functions (IMFs) is obtained by the decomposition of the calibrated signal using improved CEEMDAN method, and the threshold denoising method is utilized; finally, the de-noised IMFs are reconstructed into the desired signal. To verify the proposed method, the hardware circuit with an embedded field-programmable gate array (FPGA) was implemented and applied in bias drift calibration for the two MEMS gyroscopes manufactured in our laboratory. The experimental results indicate that the proposed method is feasible, and it achieved a better performance than the typical mode reversal. The bias instability of the two gyroscopes decreased from 0.0066 ° / s and 0.0055 ° / s to 0.0011 ° / s ; and, benefiting from the threshold denoising based on improved CEEMDAN, the angle random walks decreased from 1.18 × 10 − 4 ° / s 1 / 2 and 2.04 × 10 − 4 ° / s 1 / 2 to 2.19 × 10 − 5 ° / s 1 / 2 , respectively.
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