Long period fiber grating, thin coating of graphene and silver nanowires, and corrosion sensing for life-cycle assessment of steel structures

This study aims to develop and validate a compact, integrated lab-on-sensor system for simultaneous measurement of strain, temperature and corrosion-induced mass loss in steel structures and concrete reinforcement elements in order to assess their life-cycle performance. The sensing system operates based on the principle of long period fiber gratings (LPFG) that are responsive to both thermal and mechanical deformation, and the change in refractive index of any medium surrounding the optical fiber. To fabricate a LPFG sensor for strain and temperature measurement, a CO2 laser aided fiber grating system was assembled. To enable mass loss measurement, a low pressure chemical vapor deposition (LPCVD) system was built to synthesize a graphene/silver nanowire composite film as flexible transparent electrode for the electroplating of a thin Fe-C layer on the curve surface of a LPFG sensor. Together with two LPFG sensors in LP06 and LP07 modes for simultaneous strain and temperature measurement, three Fe-C coated LPFG sensors were multiplexed and deployed inside three miniature, coaxial steel tubes to measure critical mass losses through the penetration of tube walls and their corresponding corrosion rates in the life cycle of an instrumented steel component. A Fe-C coated LPFG sensor was submerged in a NaCl solution and calibrated for stress corrosion cracking under three strain levels. The corrosion mechanism of the Fe-C layer was investigated and the distribution of cracks (width, length and spacing) were characterized and correlated with the wavelength change of the sensor. Thermal, loading and accelerated corrosion tests were conducted to validate the functionality, sensitivity, accuracy, and robustness of the proposed sensing system and demonstrate its feasibility in in situ applications --Abstract, page iii

Preliminary Bond Capacity Exploration between Monolayer Graphene and Cementitious Composites

This Study Aims to Explore Bond Capacity between Monolayer Graphene and Cementitious Composites for the First Time through a Pullout Test. the Low-Pressure Chemical Vapor Deposition Method Was Used to Synthesize Monolayer Graphene on the Copper Substrate to Be Embedded in the Mortar Made by the Briquette Mold. the Bond Capacity between Them Was Higher Than the Tensile Strength of the Copper Sheet with As-Grown Monolayer Graphene on the Surface Since All Specimens Failed in Fracture with Embedment Length of More Than 30 Mm. the Monolayer Graphene Enhanced the Copper Tensile Fracture Stress and Normalized Energy during the Test as the Copper Sheet Width Increased. This Short Communication Explores a New Path to Quantify the Bond between the Monolayer Graphene and the Mortar to Promote the Understanding of the Behavior of Graphene-Enhanced Cementitious Composites

Corrosion-Induced Mass Loss Measurement under Strain Conditions through Gr/AgNW-Based, Fe-C Coated LPFG Sensors

In this study, graphene/silver nanowire (Gr/AgNW)-based, Fe-C coated long period fiber gratings (LPFG) sensors were tested up to 72 hours in 3.5 w.t% NaCl solution for corrosion-induced mass loss measurement under four strain levels: 0, 500, 1000 and 1500 µ∈. The crack and interfacial bonding behaviors of laminate Fe-C and Gr/AgNW layer structures were characterized using Scanning Electron Microscopy (SEM) and electrical resistance measurement. Both optical transmission spectra and electrical impedance spectroscopy (EIS) data were simultaneously measured from each sensor. Under increasing strains, transverse cracks appeared first and were followed by longitudinal cracks on the laminate layer structures. The spacing of transverse cracks and the length of longitudinal cracks were determined by the bond strength at the weak Fe-C and Gr/AgNW interface. During corrosion tests, the shift in resonant wavelength of the Fe-C coated LPFG sensors resulted from the effects of the Fe-C layer thinning and the NaCl solution penetration through cracks on the evanescent field surrounding the LPFG sensors. Compared with the zero-strained sensor, the strain-induced cracks on the laminate layer structures initially increased and then decreased the shift in resonant wavelength in two main stages of the Fe-C corrosion process. In each corrosion stage, the Fe-C mass loss was linearly related to the shift in resonant wavelength under zero strain and with the applied strain taken into account in general cases. The general correlation equation was validated at 700 and 1200 µ∈ to a maximum error of 2.5% in comparison with 46.5% from the zero-strain correlation equation

Integrated Fiber Optic Sensors for Strain, Temperature and Corrosion-Induced Mass Loss Measurement

In this study, a fiber optic sensing system based on long period fiber gratings (LPFG) in LP06 and LP07 modes is designed, fabricated and tested for simultaneous measurements of strain, temperature and corrosion-induced mass loss. It consists of three steel tubes and several Fe-C coated LPFG sensors for long- and short-term corrosion monitoring, respectively, when deployed in proximity and parallel to a steel member. Graphene/silver nanowire (Gr/AgNW) composite was coated on the LPFG surface for efficient Fe-C electroplating due to its high optical transparency and conductivity. The sensor was subjected to both tensile strain and temperature, and submerged in 3.5 wt.% NaCl for 72 hours during corrosion tests. The results showed high accuracy and sensitivity of the integrated sensor

Synthesis and Characterization of Free-Stand Graphene/Silver Nanowire/Graphene Nano Composite as Transparent Conductive Film with Enhanced Stiffness

As-grown graphene via chemical vapor deposition (CVD) has potential defects, cracks, and disordered grain boundaries induced by the synthesis and transfer process. Graphene/silver nanowire/graphene (Gr/AgNW/Gr) sandwich composite has been proposed to overcome these drawbacks significantly as the AgNW network can provide extra connections on graphene layers to enhance the stiffness and electrical conductivity. However, the existing substrate (polyethylene terephthalate (PET), glass, silicon, and so on) for composite production limits its application and mechanics behavior study. In this work, a vacuum annealing method is proposed and validated to synthesize the free-stand Gr/AgNW/Gr nanocomposite film on transmission electron microscopy (TEM) grids. AgNW average spacing, optical transmittance, and electrical conductivity are characterized and correlated with different AgNW concentrations. Atomic force microscope (AFM) indentation on the free-stand composite indicates that the AgNW network can increase the composite film stiffness by approximately 460% with the AgNW concentration higher than 0.6 mg/mL. Raman spectroscopy shows the existence of a graphene layer and the disturbance of the AgNW network. The proposed method provides a robust way to synthesize free-stand Gr/AgNW/Gr nanocomposite and the characterization results can be utilized to optimize the nanocomposite design for future applications

Synthesis and Characterization of Free-Stand Graphene/Silver Nanowire/Graphene Nano Composite as Transparent Conductive Film with Enhanced Stiffness

As-grown graphene via chemical vapor deposition (CVD) has potential defects, cracks, and disordered grain boundaries induced by the synthesis and transfer process. Graphene/silver nanowire/graphene (Gr/AgNW/Gr) sandwich composite has been proposed to overcome these drawbacks significantly as the AgNW network can provide extra connections on graphene layers to enhance the stiffness and electrical conductivity. However, the existing substrate (polyethylene terephthalate (PET), glass, silicon, and so on) for composite production limits its application and mechanics behavior study. In this work, a vacuum annealing method is proposed and validated to synthesize the free-stand Gr/AgNW/Gr nanocomposite film on transmission electron microscopy (TEM) grids. AgNW average spacing, optical transmittance, and electrical conductivity are characterized and correlated with different AgNW concentrations. Atomic force microscope (AFM) indentation on the free-stand composite indicates that the AgNW network can increase the composite film stiffness by approximately 460% with the AgNW concentration higher than 0.6 mg/mL. Raman spectroscopy shows the existence of a graphene layer and the disturbance of the AgNW network. The proposed method provides a robust way to synthesize free-stand Gr/AgNW/Gr nanocomposite and the characterization results can be utilized to optimize the nanocomposite design for future applications

VoxelFormer: Bird's-Eye-View Feature Generation based on Dual-view Attention for Multi-view 3D Object Detection

In recent years, transformer-based detectors have demonstrated remarkable performance in 2D visual perception tasks. However, their performance in multi-view 3D object detection remains inferior to the state-of-the-art (SOTA) of convolutional neural network based detectors. In this work, we investigate this issue from the perspective of bird's-eye-view (BEV) feature generation. Specifically, we examine the BEV feature generation method employed by the transformer-based SOTA, BEVFormer, and identify its two limitations: (i) it only generates attention weights from BEV, which precludes the use of lidar points for supervision, and (ii) it aggregates camera view features to the BEV through deformable sampling, which only selects a small subset of features and fails to exploit all information. To overcome these limitations, we propose a novel BEV feature generation method, dual-view attention, which generates attention weights from both the BEV and camera view. This method encodes all camera features into the BEV feature. By combining dual-view attention with the BEVFormer architecture, we build a new detector named VoxelFormer. Extensive experiments are conducted on the nuScenes benchmark to verify the superiority of dual-view attention and VoxelForer. We observe that even only adopting 3 encoders and 1 historical frame during training, VoxelFormer still outperforms BEVFormer significantly. When trained in the same setting, VoxelFormer can surpass BEVFormer by 4.9% NDS point. Code is available at: https://github.com/Lizhuoling/VoxelFormer-public.git

Smart Rock Technology for Real-Time Monitoring of Bridge Scour and Riprap Effectiveness -- Design Guidelines and Visualization Tools

This study aims to further develop and demonstrate the recently-proposed smart rock technology for scour depth and protection effectiveness monitoring. A smart rock is one or two stacked magnets encased in a concrete sphere with a specially-designed rotational mechanism. Design guidelines, rotational mechanisms, remote measurement tools and localization algorithms of smart rocks were developed and validated at three bridge sites. The effect of steel reinforcement in bridge piers/deck on the orientation of gravity-controlled magnets was negligible. The localization accuracy with a single smart rock met a general requirement of less than 0.5 m in engineering applications. The spherical smart rock placed directly on the riverbed of the Roubidoux Creek successfully demonstrated its movement to the bottom of scour hole during the December 27, 2015, flood. Those deployed in the Waddell Creek and the Gasconade River were washed away and thus replaced with smart rocks embedded in deposits such that their top is in flush with the riverbed for improved stability under water current. For rip-rap effectiveness monitoring, polyhedral smart rocks are recommended to increase their interlock with other natural rocks