Effects of phosphate addition on the removal of disinfection by-product formation potentials by biological activated carbon filtration

In drinking water treatment plants (DWTPs), the widely used biological activated carbon filters (BACFs), as the last barrier before disinfection, can remove dissolved organic matter (DOM) known as precursors of disinfection by-products (DBPs). Whether phosphate addition can improve water purification and DBP control of BACFs is still...

Damage pattern recognition for corroded beams strengthened by CFRP anchorage system based on acoustic emission techniques

This study presents a damage pattern recognition approach for corroded steel beams strengthened by CFRP anchorage system based on acoustic emission clustering analysis. The proposed method includes four steps: acoustic emission signal acquisition, feature extraction, clustering analysis, and damage pattern recognition. Four corroded beams...

Damage Mode Identification of CFRP-Strengthened Beam Based on Acoustic Emission Technique

Externally bonded (EB) carbon fiber reinforced polymer (CFRP) is widely used in structural strengthening and retrofitting. Premature debonding of the FRP severely limits the efficiency of CFRP utilization. The application of CRRP anchorage system offers a solution to the debonding problem. However, the understanding of damage mode identification...

A hybrid methodology for structural damage detection uniting FEM and 1D-CNNs: Demonstration on typical high-pile wharf: Demonstration on typical high-pile wharf

Vibration-based structural damage detection (SDD) has been a subject of intense research in structural health monitoring (SHM) for large civil engineering structures over the decades. The performance of the conventional SDD approaches predominantly relies on the rational choices of the damage feature and classifier. Hand-crafted features or...

Sparse Bayesian deep learning for dynamic system identification

This paper proposes a sparse Bayesian treatment of deep neural networks (DNNs) for system identification. Although DNNs show impressive approximation ability in various fields, several challenges still exist for system identification problems. First, DNNs are known to be too complex that they can easily overfit the training data. Second, the...

Coupled effects of corrosion damage and sustained loading on the flexural behavior of RC beams strengthened with CFRP anchorage system

This paper presents the results of an experimental study on the flexural behavior of carbon fibre reinforced polymer (CFRP) anchorage system strengthened reinforced concrete (RC) beams under the coupled effects of corrosion damage and sustained loading. The test beams were subjected to combined accelerated corrosion in 5% NaCl solution and...

Fractal characteristics and damage evaluation of corroded beams under four-point bending tests based on acoustic emission techniques

This study investigated the relationship between the acoustic emission (AE) signals parameter sequence fractal characteristics and the damage evolution information of corroded reinforced concrete (RC) beams under four-point bending. Strength deterioration behavior and AE data can be obtained by coupling the four-point bending test and the AE...

Effects of biological activated carbon filter running time on disinfection by-product precursor removal

Biological activated carbon (BAC) filtration is usually considered to be able to decrease formation potentials (FPs) of disinfection by-products (DBPs) in drinking water treatment plant (DWTP). However, BAC filters with long running time may release microbial metabolites to effluents and therefore increase FPs of nitrogenous DBPs with high...

Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee

This paper presents a deep reinforcement learning (DRL) algorithm for orientation estimation using inertial sensors combined with a magnetometer. Lyapunov’s method in control theory is employed to prove the convergence of orientation estimation errors. The estimator gains and a Lyapunov function are parametrised by deep neural networks and...

Data driven discovery of cyber physical systems

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction...

Hydrostatic analyses of uprighting processes of a capsized and damaged ship