The objective of this study is to evaluate the performance of the artificial neural network (ANN) approach for predicting interlayer conditions and layer modulus of a multi-layered flexible pavement structure. To achieve this goal, two ANN based back-calculation models were proposed to predict the interlayer conditions and layer modulus of the pavement structure. The corresponding database built with ANSYS based finite element method computations for four types of a structure subjected to falling weight deflectometer load. In addition, two proposed ANN models were verified by comparing the results of ANN models with the results of PADAL and double multiple regression models. The measured pavement deflection basin data was used for the verifications. The comparing results concluded that there are no significant differences between the results estimated by ANN and double multiple regression models. PADAL modeling results were not accurate due to the inability to reflect the real pavement structure because pavement structure was not completely continuous. The prediction and verification results concluded that the proposed back-calculation model developed with ANN could be used to accurately predict layer modulus and interlayer conditions. In addition, the back-calculation model avoided the back-calculation errors by considering the interlayer condition, which was barely considered by former models reported in the published studies.
The main purpose of the present study is to enhance high-level noisy data by a wavelet-based iterative filtering algorithm for identification of natural frequencies during ambient wind vibrational tests on a petrochemical process tower. Most of denoising methods fail to filter such noise properly. Both the signal-to-noise ratio and the peak signal-to-noise ratio are small. Multiresolution-based one-step and variational-based filtering methods fail to denoise properly with thresholds obtained by theoretical or empirical method. Due to the fact that it is impossible to completely denoise such high-level noisy data, the enhancing approach is used to improve the data quality, which is the main novelty from the application point of view here. For this iterative method, a simple computational approach is proposed to estimate the dynamic threshold values. Hence, different thresholds can be obtained for different recorded signals in one ambient test. This is in contrast to commonly used approaches recommending one global threshold estimated mainly by an empirical method. After the enhancements, modal frequencies are directly detected by the cross wavelet transform (XWT), the spectral power density and autocorrelation of wavelet coefficients. Estimated frequencies are then compared with those of an undamaged-model, simulated by the finite element method.
Many studies on the mixture design of fly ash and slag ternary blended concrete have been conducted. However, these previous studies did not consider the effects of climate change, such as acceleration in the deterioration of durability, on mixture design. This study presents a procedure for the optimal mixture design of ternary blended concrete considering climate change and durability. First, the costs of CO2 emissions and material are calculated based on the concrete mixture and unit prices. Total cost is equal to the sum of material cost and CO2 emissions cost, and is set as the objective function of the optimization. Second, strength, slump, carbonation, and chloride ingress models are used to evaluate concrete properties. The effect of different climate change scenarios on carbonation and chloride ingress is considered. A genetic algorithm is used to find the optimal mixture considering various constraints. Third, illustrative examples are shown for mixture design of ternary blended concrete. The analysis results show that for ternary blended concrete exposed to an atmospheric environment, a rich mix is necessary to meet the challenge of climate change, and for ternary blended concrete exposed to a marine environment, the impact of climate change on mixture design is marginal.
This work presents a numerical simulation of ballistic penetration and high velocity impact behavior of plain and reinforced concrete slabs. In this paper, we focus on the comparison of the performance of the plain and reinforced concrete slabs of unconfined compressive strength 41 MPa under ballistic impact. The concrete slab has dimensions of 675 mm × 675 mm × 200 mm, and is meshed with 8-node hexahedron solid elements in the impact and outer zones. The ogive-nosed projectile is considered as rigid element that has a mass of 0.386 kg and a length of 152 mm. The applied velocities vary between 540 and 731 m/s. 6 mm of steel reinforcement bars were used in the reinforced concrete slabs. The constitutive material modeling of the concrete and steel reinforcement bars was performed using the Johnson-Holmquist-2 damage and the Johnson-Cook plasticity material models, respectively. The analysis was conducted using the commercial finite element package Abaqus/Explicit. Damage diameters and residual velocities obtained by the numerical model were compared with the experimental results and effect of steel reinforcement and projectile diameter were studies. The validation showed good agreement between the numerical and experimental results. The added steel reinforcements to the concrete samples were found efficient in terms of ballistic resistance comparing to the plain concrete sample.
It is remarkable, the recent advances concerning the development of numerical modeling frameworks to simulate the infill panels’ seismic behavior. However, there is a lack of experimental data of their mechanical properties, which are of full importance to calibrate the numerical models. The primary objective of this paper is to present an extensive experimental campaign of mechanical characterization tests of infill masonry walls made with three different types of masonry units: lightweight vertical hollow concrete blocks and hollow clay bricks. Four different types of experimental tests were carried out, namely: compression strength tests, diagonal tensile strength tests, and flexural strength tests parallel and perpendicular to the horizontal bed joints. A total amount of 80 tests were carried out and are reported in the present paper. The second objective of this study was to compare the mechanical properties of as-built and existing infill walls. The results presented and discussed herein, will be in terms of strain-stress curves and damages observed within the tests. It was observed a fragile behavior in the panels made with hollow clay horizontal bricks, without propagation of cracks. The plaster increased the flexural strength by 57%.
Using of rubber asphalt can both promote the recycling of waste tires and improve the performance of asphalt pavement. However, the segregation of rubber asphalt caused by the poor storage stability always appears during its application. Storage stability of asphalt and rubber is related to the compatibility and also influenced by rubber content. In this study, molecular models of different rubbers and chemical fractions of asphalt were built to perform the molecular dynamics simulation. The solubility parameter and binding energy between rubber and asphalt were obtained to evaluate the compatibility between rubber and asphalt as well as the influence of rubber content on compatibility. Results show that all three kinds of rubber are commendably compatible with asphalt, where the compatibility between asphalt and cis-polybutadiene rubber (BR) is the best, followed by styrene-butadiene rubber (SBR), and natural rubber (NR) is the worst. The optimum rubber contents for BR asphalt, SBR asphalt, and NR asphalt were determined as 15%, 15%, and 20%, respectively. In addition, the upper limits of rubber contents were found as between 25% and 30%, between 20% and 25%, and between 25% and 30%, respectively.
Modeling and prediction of bed loads is an important but difficult issue in river engineering. The introduced empirical equations due to restricted applicability even in similar conditions provide different accuracies with each other and measured data. In this paper, three different artificial neural networks (ANNs) including multilayer percepterons, radial based function (RBF), and generalized feed forward neural network using five dominant parameters of bed load transport formulas for the Main Fork Red River in Idaho-USA were developed. The optimum models were found through 102 data sets of flow discharge, flow velocity, water surface slopes, flow depth, and mean grain size. The deficiency of empirical equations for this river by conducted comparison between measured and predicted values was approved where the ANN models presented more consistence and closer estimation to observed data. The coefficient of determination between measured and predicted values for empirical equations varied from 0.10 to 0.21 against the 0.93 to 0.98 in ANN models. The accuracy performance of all models was evaluated and interpreted using different statistical error criteria, analytical graphs and confusion matrixes. Although the ANN models predicted compatible outputs but the RBF with 79% correct classification rate corresponding to 0.191 network error was outperform than others.
This paper examines the structural response of reinforced concrete flat slabs, provided with fully-embedded shear-heads, through detailed three-dimensional nonlinear numerical simulations and parametric assessments using concrete damage plasticity models. Validations of the adopted nonlinear finite element procedures are carried out against experimental results from three test series. After gaining confidence in the ability of the numerical models to predict closely the full inelastic response and failure modes, numerical investigations are carried out in order to examine the influence of key material and geometric parameters. The results of these numerical assessments enable the identification of three modes of failure as a function of the interaction between the shear-head and surrounding concrete. Based on the findings, coupled with results from previous studies, analytical models are proposed for predicting the rotational response as well as the ultimate strength of such slab systems. Practical recommendations are also provided for the design of shear-heads in RC slabs, including the embedment length and section size. The analytical expressions proposed in this paper, based on a wide-ranging parametric assessment, are shown to offer a more reliable design approach in comparison with existing methods for all types of shear-heads, and are suitable for direct practical application.
The contact form of rock-concrete has a crucial influence on the failure characteristics of the stability of rock-concrete engineering. To study the influence of contact surface on the mechanical properties of rock-concrete composite specimens under compressive loads, the two different contact forms of rock-concrete composite specimens are designed, the mechanical properties of these two different specimens are analyzed under triaxial compressive condition, and analysis comparison on the stress-strain curves and failure forms of the two specimens is carried out. The influence of contact surface constraint on the mechanical properties of rock-concrete composite specimens is obtained. Results show that the stress and strain of rock-concrete composite specimens with contact surface constraint are obviously higher than those without. Averagely, compared with composite specimens without the contact surface, the existence of contact surface constraint can increase the axial peak stress of composite specimens by 24% and the axial peak strain by 16%. According to the characteristics of the fracture surface, the theory of microcrack development is used to explain the contact surface constraint of rock-concrete composite specimens, which explains the difference of mechanical properties between the two rock-concrete composite specimens in the experiment. Research results cannot only enrich the research content of the mechanics of rock contact, but also can serve as a valuable reference for the understanding of the corresponding mechanics mechanism of other similar composite specimens.
The development of a miniature triaxial apparatus is presented. In conjunction with an X-ray micro-tomography (termed as X-ray μCT hereafter) facility and advanced image processing techniques, this apparatus can be used for in situ investigation of the micro-scale mechanical behavior of granular soils under shear. The apparatus allows for triaxial testing of a miniature dry sample with a size of 8mm×16mm (diameter × height). In situ triaxial testing of a 0.4–0.8 mm Leighton Buzzard sand (LBS) under a constant confining pressure of 500 kPa is presented. The evolutions of local porosities (i.e., the porosities of regions associated with individual particles), particle kinematics (i.e., particle translation and particle rotation) of the sample during the shear are quantitatively studied using image processing and analysis techniques. Meanwhile, a novel method is presented to quantify the volumetric strain distribution of the sample based on the results of local porosities and particle tracking. It is found that the sample, with nearly homogenous initial local porosities, starts to exhibit obvious inhomogeneity of local porosities and localization of particle kinematics and volumetric strain around the peak of deviatoric stress. In the post-peak shear stage, large local porosities and volumetric dilation mainly occur in a localized band. The developed triaxial apparatus, in its combined use of X-ray μCT imaging techniques, is a powerful tool to investigate the micro-scale mechanical behavior of granular soils.