Publications

A Neural Network Approach to Estimate the Frequency of a Cantilever Beam with Random Multiple Damages

Natural frequency is an important parameter in the structural health monitoring (SHM) system. Any changes in this parameter indicate structural alteration due to damage. This study provides a neural network (NN) solution as an alternative to the finite element (FE) method to measure the natural frequencies of a cantilever beam with random multiple damage. It is based on a statistical dataset of a free vibration test obtained from the APDL (Ansys parametric design language) simulation using a MATLAB (matrix laboratory) script. The script can generate an unlimited number of possible damage combinations for any given parameters with the help of the Monte Carlo (MC) technique. MC helps to generate a random number of damages in random locations at each simulation. Damage conditions are controlled by three parameters including damage severity and damage size (in terms of the mean and standard deviation of damage). Moreover, the method proposes a curve-fitting equation to validate the predicted natural frequency for the first three modes obtained from the neural network model. Both methods are in good agreement with each other, having minimal errors in the range of 0.2-3% for each mode. The frequency result shows that the beam frequency is 8.6486 Hz if the area reduction is 10%, whereas it comes down to 7.2338 Hz if there is a 30% area reduction. A two-level factorial test shows that damage severity is the most impactful factor compared to the damage sizes on the frequency shift event. This indicates that damage alters the composition of the beam and has an impact on its frequency change with the assumed damage parameters. Therefore, the proposed NN model can estimate the frequency shift for various damage scenarios. It can be utilized in the vibration-based damage identification process to predict the frequency changes of the damaged beam without any computational burden.

Enhancing Seismic Displacement Prediction for Reinforced Concrete Box Girder Bridges Through Nonlinear Time History Analysis

Inelastic displacement ratios are critical parameters in the seismic design of reinforced concrete (RC) box girder bridges. Existing approaches of displacement prediction, including the Displacement Coefficient Method and the Capacity Spectrum Method, typically rely on simplified single-degree-of-freedom (SDOF) models, which do not fully account for the complex and nonlinear behavior of multi-degree-of-freedom (MDOF) bridge systems. Moreover, the AASHTO Guide Specifications apply the equal displacement rule through the inelastic displacement modification factor Rd, which may underestimate displacement demands for short-period structures. This study evaluates the accuracy of the AASHTO Rd using nonlinear time history analyses of six RC box girder bridge models subjected to 28 recorded ground motions from California. Each ground motion included two orthogonal components applied in the longitudinal and transverse direction. Both elastic and inelastic displacement demands were determined in each direction, and inelastic displacement ratios (Cμ) were computed and compared with AASHTO predictions. A new predictive equation for Cμ was developed to capture response variability. While AASHTO Rd aligns with the average behavior, it fails to provide reliable estimate across the full range of seismic conditions. A comprehensive parametric study was conducted to examine the influence of column boundary condition, column height, superstructure deck width, number of spans, and damping ratio on Cμ. While the elastic and inelastic displacement decreases with an increase in damping ratio, the result shows that Cμ increases with higher damping ratios. Accordingly, a revised amplification factor was proposed to better represent the inelastic displacement demand in MDOF bridge systems.

Guided-wave based damage detection method for various materials using piezoelectric sensors/actuators

In this study, the guided wave technique is applied to nondestructively assess the damage in various engineering materials, like alumina, laminated composites, and composite sandwiches. A combined theoretical, numerical and experimental investigation of the pulse-echo method using piezoelectric sensors and actuators is conducted. The dispersion effect of wave guides on these materials is first analyzed, and the transient propagation process of wave guides and its interaction with inside damages are then numerically simulated. The implementations of the pulse echo method are illustrated in experimental testing and damage detection of aluminum beams, carbon/epoxy laminated composite plates, and composite sandwich beams. In particular, the experimental results on damage detection of the composite sandwich beams are reported and discussed. As illustrated in this study, the pulse-echo method combined with piezoelectric material can be used effectively to locate damage in various engineering materials and structures.

Hydration Mechanism of Cement Pastes with the Addition of Dry Ice through Electrochemical Impedance Spectroscopy

The addition of dry ice as an admixture to cement pastes has many advantages such as improving the compressive strength and sequestration of CO2. However, its effect on the hydration mechanism of cement pastes is still unknown and will be investigated using electrochemical impedance spectroscopy in this paper. Based on the linear correlation of cumulative hydration heat from the isothermal calorimetry test and the logarithm of high-frequency resistivity, a modified Knudson equation is derived. Corresponding hydration kinetic parameters are calculated by applying the boundary nucleation and growth theory and kinetics model, including Avrami, geometrical contraction, and diffusion equations. The boundary area per unit volume (OvB) for the control specimen and specimens with 0.2% and 0.5% cement weight dry ice addition is 0.1171, 0.1250, and 0.1562, respectively, indicating that the dry ice addition increases the surface area of the nucleation process. In addition, the results show that the Avrami equation for monitoring the nucleation process is limited. Regarding the hydration curves, the transition from the nucleation and growth stage to the interaction of phase boundaries (I) stage is delayed by adding dry ice to the mixture.

Creep Design of Epoxy Bonded Anchor System

This article presents a systematic study on creep design of epoxy bonded anchor system. First, a theoretical model for prediction of long-term performance of an anchor system is suggested assuming epoxy layer following Maxwell visco-elastic behavior, which is then validated through an ABAQUS numerical model. A close match between the ABAQUS result and the theoretical model has been reached. Next, a general-purpose methodology for estimating creep capacity of an adhesive bonded anchor system is suggested following AC58 and two creep capacity equations are reached for Model Dry Epoxy and Model Wet Epoxy bonded anchor systems. The derived creep capacity is then used to re-examine the Boston D Tunnel anchor design and a safe design is reached through the suggested method considering the anchor system's long-term creep performance. Last, the ABAQUS model is extended to include the effect of curing temperatures, which shows significant influences of curing temperature on the capacity of an epoxy bonded anchor system.

Alkali-aggregate reaction in alkali-activated cement concretes

A systematic summarization of the alkali-aggregate reaction (AAR) effect of activators and aggregates in alkaline active cement concrete has been discussed in this chapter. High calcium and low calcium alkaline-activated cement concrete have been separately summarized and the effect of AAR on these two systems are compared. Effect of activator modulus, sodium oxide does, and percentage of calcium, silica, and aluminum content of aggregates on expansion of alkaline-activated concrete are lab tested and analyzed.

Prediction of grout penetration in fractured rocks by numerical simulation

As fractures in rock significantly reduce the strength as well as the stiffness of the rock mass, grouting may be required to improve the performance of the rock mass in engineering or mining projects. During grouting, mortar of cement or other materials is injected into the rock mass so that the fractures can be filled up and the rock mass can act as an integral unit. Unlike water, grouts are usually viscous and behave as non-Newtonian fluids. Therefore, the equations describing the flow of grout are more complicated and the solutions are quite difficult to obtain. The problem is further aggravated by the fact that the fractures are mostly randomly distributed, and it is rarely possible to accurately define the fractures and the distribution patterns. In this paper, a numerical model is proposed for analyzing the grouting process. The model is based on the stochastic approach, and it can provide the depth of penetration and the fluid pressure due to the flow of grout, which is modeled as a Bingham fluid, in the fractured rock mass. Parametric studies have been carried out to investigate the effects of various factors on the depth of penetration, and a regression formula is developed for calculating the penetration depth. Experiments have been carried out and their results are used to validate the present method.Key words: stochastic fractures, fractured rock mass, grout flow, grout penetration.

Impact Mechanics and High-Energy Absorbing Materials: Review

In this paper a review of impact mechanics and high-energy absorbing materials is presented. We review different theoretical models (rigid-body dynamics, elastic, shock, and plastic wave propagation, and nonclassical or nonlocal models) and computational methods (finite-element, finite-difference, and mesh-free methods) used in impact mechanics. Some recent developments in numerical simulation of impact (e.g., peridynamics) and new design concepts proposed as high energy absorbing materials (lattice and truss structures, hybrid sandwich composites, metal foams, magnetorheological fluids, porous shape memory alloys) are discussed. Recent studies on experimental evaluation and constitutive modeling of strain rate-dependent polymer matrix composites are also presented. Impact damage on composite materials in aerospace engineering is discussed along with future research needs. A particular example for the design of a sandwich material as an impact mitigator is given in more detail. This brief review is intended to help the readers in identifying starting points for research in modeling and simulation of impact problems and in designing energy absorbing materials and structures.

Analysis of cushion systems for impact protection design of bridges against overheight vehicle collision

Based on several theoretical models of elastic and elastic–plastic impact as well as energy method, a systematic methodology for design analysis of cushion structures for impact protection of bridges against overheight vehicle collision is presented with consideration of the shear-off effect of projectiles and the nonlinear crushing behavior of sandwich cores. Three design criteria based on contact force, deflection, and energy are proposed, and the theoretical models for elastic, elastic–plastic, and after-densification impact including the shear-off effect of projectile are developed to improve the analysis and design of cushion structures against overheight vehicle impact. Realistic analysis of cushion structures is resulted from the above models, and it can be applied to design of cushion structures for the sake of bridge protection from overheight vehicle collision.

Characterization of pervious concrete through image based micromechanical modeling

Pervious concrete has been widely used in parking lots and airport fields. However, past experience has shown durability and strength of the pervious concrete remains a challenge for adopting them in wider applications, as the binding material proportion is low and the use of fine aggregates is nearly zero. When loading in compression, the failure appears first in the weak concrete zone induced by the random distribution of voids. The process continues until the failure of the whole specimen occurs. Thus, the position, size and shape distribution of voids in the pervious concrete microstructure control the overall behavior of the material. In this work, the influence of the distribution of voids on the strength, stiffness, and permeability of pervious concrete microstructure is studied by 2D image analysis and finite element modeling. The position and size distribution of the microstructure voids are first summarized through Fast Fourier Transformation (FFT) analysis. A finite element analysis is then conducted on the microstructure models regenerated through the derived microstructure characteristics using ANSYS Parametric Design Language (APDL). The effect of the sample size of 2D microstructures is studied by varying the section size and a possible representative volume element (RVE) is therefore found. Predicted stress-strain plots are generated for the 2D specimen under compressive load and the obtained results, including stiffness, strength and permeability are compared with the results from the experiments conducted following ASTM standards. The comparison between models and physical experiments showed around or above 90% accuracy, which validates the suggested micromechanical analysis method of the previous concrete composite.

Optimization and experimental research on treelike joints based on generative design and powder bed fusion

Optimization and intelligent construction are of particular interest and important to improve the traditional design and manufacturing methods of cast steel joints. The optimal design, intelligent construction, and experimental research of treelike joints are conducted is this study based on generative design and laser power bed fusion (L-PBF) technology. First, the principle of generative design is comprehensively discussed in accordance of the Audze space-filling criteria. This method is applied to the optimal design of the treelike cast steel joint for Jinming Campus Museum of Henan University. Second, static behaviors of the generative design joints are compared with those of other joints obtained via parametric design through ANSYS version 2022R1 (64-bit) software. Finally, instead of traditional casting, all joints are produced using the L-PBF technology, and the manufactured 316L stainless steel joints are subjected to experimental research and finite element analysis. Results showed the minimum mass, optimal static behaviors, and evenly distributed stress of the generative design joint, thereby indicating that the generative design can effectively optimize treelike cast steel joints. The failure mode of 316Lstainless steel joints obtained via the L-PBF technology is similar to that of traditional cast steel joints but with higher yield load and ultimate bearing capacity. Therefore, employing the generative design and L-PBF technology in the optimization and intelligent construction of cast steel joints is effective and feasible.

Strength-based differential tolerable settlement limits of bridges

Based on realistic modeling of 44 bridges in national bridge inventory using its actual layout and dimensions, a theoretical framework is defined to calculate the tolerable differential settlement limits based on the over-bending moment or over-shear force generated by settlements and the moment or shear capacity of the bridge. First, the derived over-bending moment or over-shear force is validated through literature results. Second, the differential settlement limits of bridges are derived from the bridge strength capacities. Finally, based on the established differential settlement limits, the relationship of bridge differential settlement limits with its span length, number of spans, bridge skew, and the bridge type is discussed and compared with American Association of State Highway and Transportation Officials specification (2010). A statistics-based differential settlement limit criterion is also suggested for steel and pre-stressed concrete bridges and compared with the field survey results. From the research outcomes, it is concluded that extra caution is needed when implementing the 0.4% differential settlement limits of bridge foundations in American Association of State Highway and Transportation Officials.

Effects of overheight truck impacts on intermediate diaphragms in prestressed concrete bridge girders

This paper studies the capacity of prestressed concrete bridge girders to withstand overheight truck impacts. The numerical model of the bridge was validated with the existing experimental data in the literature. The elastic-plastic modeling of concrete damage and quasi-static impact simulation of the bridge were considered. Parametric studies were then conducted with respect to the spacing and depth of intermediate diaphragms as well as girder types from which the role of intermediate diaphragms in protection and enhancement of prestressed concrete bridge girders from truck impacts is obtained. From the simulation results, it was concluded that the optimum spacing of intermediate diaphragms (that is, 25.0 ft [7.62 m]) is consistent with the results reported for previous studies. The depth of intermediate diaphragms should be extended to the top edge of the bottom flange of girders to provide maximum impact protection. Wide flanges in girders increase the bending stiffness and reduce the horizontal deflection and correspondingly decrease damage areas. However, deep webs in girders introduce a large rotation with respect to the deck, and thus increase the deflection under the truck impact. Design guidelines for typical parameters for intermediate diaphragms in prestressed concrete bridges are provided. The numerical finite-element parametric study provides a better understanding of placement and size of intermediate diaphragms in prestressed concrete bridges and their role in protecting girders from overheight truck impacts.

Additive Manufacturing and Mechanical Performance of Trifurcated Steel Joints for Architecturally Exposed Steel Structures

Additive Manufacturing (AM) technology has unique advantages in producing complex joints in architecturally exposed steel structures. This article focuses on the process of manufacturing and investigating the mechanical properties of a reduced scale model of a trifurcated joint using Selective Laser Melting (SLM) method and mechanical tests, respectively. The orthogonal test method was used to optimize the main AM process parameters. Then the trifurcated steel joint was printed using the optimal process parameters and treated by solid solution and aging treatment. To investigate the mechanical performance of the printed joint, an axial compression test and complimentary finite element analyses were carried out. Failure processes and failure mechanisms of the trifurcated steel joint were discussed in detail. The research results show that the preferred process parameters for printing 316L stainless steel powder are: scanning power 150 W, scanning speed 700 mm/s, and scanning pitch 0.09 mm. Using these AM parameters, trifurcated steel joints with good surface quality, geometrical accuracy and tensile strength are obtained after heat treatment. Our mechanical tests and Finite element analyses results indicate that the failure mechanism in the AM trifurcated joint are similar to those of cast steel joints. Based on these results, we conclude that the AM technology serves as a promising new way for the fabrication of joints with complex geometries.

Effect of Prestress on Bridge–Vehicle Interactions

Prestress applied on bridges affects the dynamic interaction between bridges and vehicles traveling over them. In this paper, the prestressed bridge is modeled as a beam subjected to eccentric prestress force at the two ends, and a half-vehicle model with four degrees-of-freedom is used to represent the vehicle passing the bridge. A new bridge–vehicle interaction model considering the effect of prestress with eccentricity is developed through the principle of virtual work. The correctness and accuracy of the model are validated with literature results. Based on the developed model, numerical simulations have been conducted using Newmark's β method to study the effects of vehicle speed, eccentricity and amplitude of the prestress, and presence of multiple vehicles. It is shown that prestress has an important effect on the maximum vertical acceleration of vehicles, which may provide a good index for detecting the change of prestress. It is also interesting to find that the later-entering vehicle on the prestressed bridge will largely reduce the maximum vertical acceleration of the vehicle ahead of it.

DYNAMIC ANALYSIS OF NEGATIVE STIFFNESS NOISE ABSORBER WITH MAGNET

Bond strength of PCC pavement repairs using metakaolin-based geopolymer mortar

In order to use geopolymer mortar as a pavement repair material, a splitting test and a slant shear test are performed to characterize the bond strength of the geopolymer and conventional cement mortar interfaces. Effect of curing time, degradation of the cement mortar under different acid conditions on the bond strength of geopolymer with conventional cement mortar, and comparison of the metakaolin geopolymer with other pavement repair materials are analyzed. It was found that curing time affects the interface bond strength greatly. Metakaolin geopolymer reaches 80% of its 28 day strength in 3 days curing, but shows low strength in 24 h curing. Curing temperature affects the strength of metakaolin geopolymer, however metakaolin geopolymer cured in ambient temperature and the bond strength of 3 days curing through splitting and slant shear tests reaches 3.63 MPa and 16.32 MPa, respectively. Degradation of cement mortar negatively affects the bond strength of geopolymer and conventional cement mortar. Possibility of using metakaolin geopolymer as a repair material is discussed by comparison of this experimental result with these of other repair materials.

Deep learning-based structural health monitoring through the infusion of optical photos and vibration data

This paper reports an investigation of deep learning techniques in structural damage identification that can overcome the limitations of traditional visual inspection. First, a vibration-based deep learning model is established to locate the damage in a beam and a truss structure. Then an optical photo-based model is established and used to classify different defects. Based on the satisfactory outcomes of these two models, a new structural health monitoring technique is proposed through the infusion of optical photos and vibration data. Vibration signals and true structural images for a truss are used to demonstrate the capability of the proposed method. It was found that the infusion of vibration data and optical photos can enhance damage identification significantly and overcome the drawbacks in the existing deep learning models due to incomplete vibration signals or blurred optical photo inputs.