Particle damping technology has attracted extensive research and engineering application interest in the field of vibration control due to its prominent advantages, including wide working frequency bands, ease of installation, longer durability and insensitivity to extreme temperatures. To introduce particle damping technology to long-period structure seismic control, a novel multilayer compartmental particle damper (MCPD) was proposed, and a 1/20 scale test model of a typical long-period self-anchored suspension bridge with a single tower was designed and fabricated. The model was subjected to a series of shaking table tests with and without the MCPD. The results showed that the seismic responses of the flexible or semi-flexible bridge towers of long-period bridges influence the seismic responses of the main beam. The MCPD can be conveniently installed on the main beam and bridge tower and can effectively reduce the longitudinal peak displacement and the root mean square acceleration of the main beam and tower. In addition, no particle accumulation was observed during the tests. A well-designed MCPD can achieve significant damping for long-period structures under seismic excitations of different intensities. These results indicate that the application of MCPDs for seismic control of single-tower self-anchored suspension bridges and other long-period structures is viable.
The mechanical response of mutually interconnected epistyles is studied experimentally. The specimens are made of two marble blocks connected to each other with an “I”-shaped titanium connector placed in grooves sculptured on the blocks and covered with cementitious material. The specific way of connecting epistyles simulates the one used by scientists restoring the ancient “connections” of the epistyles of the Parthenon Temple. This “connection”, although designed to sustain mainly tensile loading, undertakes, also, shear load, in case of excitations imposing to the epistyles displacements normal to the connector’s axis. Attention is focused to enlighten the role of a novel design technique aiming to relieve the stress field around the connector. According to this technique, part of the connector’s web is left uncovered, forming the so-called “Relieving Space”, assisting the unconstrained deformation of the connector. Both traditional and innovative sensing techniques were employed in an effort to obtain data from the interior of the three-material-complex (marble-cementitious material-titanium). Analysis of the data indicated that the “Relieving Space” reduces the overall stiffness of the system, protecting marble in case of over-loading. Moreover, it was concluded that the innovative techniques employed provide pre-failure indicators well in advance of the catastrophic failure of the specimens.
The recycled layer in full-depth reclamation (FDR) method is a mixture of coarse aggregates and reclaimed asphalt pavement (RAP) which is stabilized by a stabilizer agent. For design and quality control of the final product in FDR method, the unconfined compressive strength of stabilized material should be known. This paper aims to develop a mathematical model for predicting the unconfined compressive strength (UCS) of soil-RAP blend stabilized with Portland cement based on multivariate adaptive regression spline (MARS). To this end, two different aggregate materials were mixed with different percentages of RAP and then stabilized by different percentages of Portland cement. For training and testing of MARS model, total of 64 experimental UCS data were employed. Predictors or independent variables in the developed model are percentage of RAP, percentage of cement, optimum moisture content, percent passing of #200 sieve, and curing time. The results demonstrate that MARS has a great ability for prediction of the UCS in case of soil-RAP blend stabilized with Portland cement (R2 is more than 0.97). Sensitivity analysis of the proposed model showed that the cement, optimum moisture content, and percent passing of #200 sieve are the most influential parameters on the UCS of FDR layer.
In a reliability-based design optimization (RBDO), computation of the failure probability (Pf) at all design points through the process may suitably be avoided at the early stages. Thus, to reduce extensive computations of RBDO, one could decouple the optimization and reliability analysis. The present work proposes a new methodology for such a decoupled approach that separates optimization and reliability analysis into two procedures which significantly improve the computational efficiency of the RBDO. This technique is based on the probabilistic sensitivity approach (PSA) on the shifted probability density function. Stochastic variables are separated into two groups of desired and non-desired variables. The three-phase procedure may be summarized as: Phase 1, apply deterministic design optimization based on mean values of random variables; Phase 2, move designs toward a reliable space using PSA and finding a primary reliable optimum point; Phase 3, applying an intelligent self-adaptive procedure based on cubic B-spline interpolation functions until the targeted failure probability is reached. An improved response surface method is used for computation of failure probability. The proposed RBDO approach could significantly reduce the number of analyses required to less than 10% of conventional methods. The computational efficacy of this approach is demonstrated by solving four benchmark truss design problems published in the structural optimization literature.
Many studies have evaluated the effects of additives such as nano-silica (NS), micro-silica (MS) and polymer fibers on optimizing the mechanical properties of concrete, such as compressive strength. Nowadays, with progress in cement industry provides, it has become possible to produce cement type I with strength classes of 32.5, 42.5, and 52.5 MPa. On the one hand, the microstructure of cement has changed, and modified by NS, MS, and polymers; therefore it is very important to determine the optimal percentage of each additives for those CSCs. In this study, 12 mix designs containing different percentages of MS, NS, and polymer fibers in three cement strength classes(CSCs) (32.5, 42.5, and 52.5 MPa) were designed and constructed based on the mixture method. Results indicated the sensitivity of each CSCs can be different on the NS or MS in compressive strength of concrete. Consequently, strength classes have a significant effect on the amount of MS and NS in mix design of concrete. While, polymer fibers don’t have significant effect in compressive strength considering CSCs.
The aim of this research is to assess the seismic performance of reinforced concrete columns under different axial load and transverse reinforcement ratios. These two parameters are very important as for the ductility, strength, stiffness, and energy dissipation capacity for a given reinforced concrete column. Effects of variable axial load ratio and transverse reinforcement ratio on the seismic performance of reinforced concrete columns are thoroughly analyzed. The finite element computer program Seismo-Structure was used to perform the analysis of series of reinforced concrete columns tested by the second author and other researchers. In order to reflect the reality and grasp the actual behavior of the specimens, special attention was paid to select the models for concrete, confined concrete, and steel components. Good agreements were obtained between the experimental and the analytical results either for the lateral force-drift relationships or for the damage progress prediction at different stages of the loading.
Due to an increased need in hydro-electricity, water storage, and flood protection, it is assumed that a series of new dams will be build throughout the world. The focus of this paper is on the non-probabilistic-based design of new arch-type dams by applying means of robust design optimization (RDO). This type of optimization takes into account uncertainties in the loads and in the material properties of the structure. As classical procedures of probabilistic-based optimization under uncertainties, such as RDO and reliability-based design optimization (RBDO), are in general computationally expensive and rely on estimates of the system’s response variance, we will not follow a full-probabilistic approach but work with predefined confidence levels. This leads to a bi-level optimization program where the volume of the dam is optimized under the worst combination of the uncertain parameters. As a result, robust and reliable designs are obtained and the result is independent from any assumptions on stochastic properties of the random variables in the model. The optimization of an arch-type dam is realized here by a robust optimization method under load uncertainty, where hydraulic and thermal loads are considered. The load uncertainty is modeled as an ellipsoidal expression. Comparing with any traditional deterministic optimization method, which only concerns the minimum objective value and offers a solution candidate close to limit-states, the RDO method provides a robust solution against uncertainty. To reduce the computational cost, a ranking strategy and an approximation model are further involved to do a preliminary screening. By this means, the robust design can generate an improved arch dam structure that ensures both safety and serviceability during its lifetime.
This study concerns with the design optimization of steel skeletal structures thereby utilizing both a real-life specification provisions and ready steel profiles named hot-rolled I sections. For this purpose, the enhanced genetic algorithm methodology named EGAwMP is utilized as an optimization tool. The evolutionary search mechanism of EGAwMP is constituted on the basis of generational genetic algorithm (GGA). The exploration capacity of EGAwMP is improved in a way of dividing an entire population into sub-populations and using of a radial basis neural network for dynamically adjustment of EGAwMP’s genetic operator parameters. In order to improve the exploitation capability of EGAwMP, the proposed neural network implementation is also utilized for prediction of more accurate design variables associating with a new design strategy, design codes of which are based on the provisions of LRFD_AISC V3 specification. EGAwMP is applied to determine the real-life ready steel profiles for the optimal design of skeletal structures with 105, 200, 444, and 942 members. EGAwMP accomplishes to increase the quality degrees of optimum designations Furthermore, the importance of using the real-life steel profiles and design codes is also demonstrated. Consequently, EGAwMP is suggested as a design optimization tool for the real-life steel skeletal structures.
This paper investigates a hybrid structural control system using tuned liquid dampers (TLDs) and lead-rubber bearing (LRB) systems for mitigating earthquake-induced vibrations. Furthermore, a new approach for taking into account the uncertainties associated with the steel shear buildings is proposed. In the proposed approach, the probabilistic distributions of the stiffness and yield properties of stories of a set of reference steel moment frame structures are derived through Monte-Carlo sampling. The approach is applied to steel shear buildings isolated with LRB systems. The base isolation systems are designed for different target base displacements by minimizing a relative performance index using Genetic Algorithm. Thereafter, the base-isolated structures are equipped with TLDs and a combination of the base and TLD properties is sought by which the maximum reduction occurs in the base displacement without compromising the performance of the system. In addition, the effects of TLD properties on the performance of the system are studied through a parametric study. Based on the analyses results, the base displacement can be reduced 23% by average, however, the maximum reduction can go beyond 30%.
Investigating progressive collapse of tall structures under beam removal scenarios after earthquake is a complex subject because the earthquake damage acts as an initial condition for the subsequent scenario. An investigation is performed here on a 10 story steel moment resisting structure designed to meet the life safety level of performance when different beam removal scenarios after earthquake are considered. To this end, the structure is first subjected to the design earthquake simulated by Tabas earthquake acceleration. The beam removal scenarios are then considered at different locations assuming that both ends connections of the beam to columns are simultaneously detached from the columns; thus the removed beam falls on the underneath floor with an impact. This imposes considerable loads to the structure leading to a progressive collapse in all the scenarios considered. The results also show that the upper stories are much more vulnerable under such scenarios than the lower stories. Hence, more attention shall be paid to the beam-to-column connections of the upper stories during the process of design and construction.
Modulus is one of the main parameters during the design of asphalt pavement structure, the newest specifications of China gives the dynamic moduli ranges of commonly used asphalt mixtures with base asphalt (BA) or styrene-butadiene-styrene modified asphalt (SBS MA), while the moduli ranges of mixtures with carbon black modified asphalt (CB MA) are not recommended. To investigate the CB effect on the dynamic moduli of CB MA mixtures, one commonly used asphalt mixture (AC-20) was designed with BA, SBS MA, and CB MA, respectively. Then, the uniaxial compression dynamic modulus tests were conducted at different temperatures and loading frequencies, the master curves of asphalt mixtures were analyzed based on the time-temperature equivalence principle. The results show that with increasing loading frequency, the temperature dependence of dynamic moduli of all asphalt mixtures tend to be less obvious. Both SBS and CB can decrease the temperature sensitivity of asphalt mixture, the SBS MA mixture has the lowest temperature sensitivity, followed by CB MA and BA mixture. In addition, CB and SBS can obviously improve the dynamic modulus of the BA mixture, enhance the anti-deformation performance of pavement structure, and the improvement effect of CB is almost the same with SBS.
In this paper, an empirical model based on self-evolving neural network is proposed for predicting the flexural behavior of ferrocement elements. The model is meant to serve as a simple but reliable tool for estimating the moment capacity of ferrocement members. The proposed model is trained and validated using experimental data obtained from the literature. The data consists of information regarding flexural tests on ferrocement specimens which include moment capacity and cross-sectional dimensions of specimens, concrete cube compressive strength, tensile strength and volume fraction of wire mesh. Comparisons of predictions of the proposed models with experimental data indicated that the models are capable of accurately estimating the moment capacity of ferrocement members. The proposed models also make better predictions compared to methods such as the plastic analysis method and the mechanism approach. Further comparisons with other data mining techniques including the back-propagation network, the adaptive spline, and the Kriging regression models indicated that the proposed models are superior in terms prediction accuracy despite being much simpler models. The performance of the proposed models was also found to be comparable to the GEP-based surrogate model.
This article presents an experimental and numerical investigation on the strength and performance of intermediate length rack column sections with C-stitches under axial compression. The test program consisted of 10 axial concentric compression tests on columns with and without C-stitches under pin end conditions for two different geometric lengths. Finite element (FE) models were developed using commercial FE package ABAQUS considering material and geometric nonlinearities as well as initial geometric imperfections. The elastic buckling properties of the section were calculated using readily available linear elastic buckling analysis tools based on Generalized Beam Theory (GBT) and Finite Strip Method (FSM). Obtained FE results were compared with those obtained experimentally, and once verified the developed FE modeling technique was used to carry out a parametric study to examine changes in structural response due to variations in length, depth and spacing of C-stitches. Observed influences of C-stitches on the behavior and resistance of the considered columns were carefully analyzed, and key design aspects are presented herein.
Cracks at the crest of slopes frequently occur during earthquakes. Such cracks result from limited tension strength of the soil. A tension cut-off in Mohr-Coulomb shear strength can represent this limited strength. Presented is an extension of variational analysis of slope stability with a tension crack considering seismicity. Both translational and rotational failure mechanisms are included in a pseudo-static analysis of slope stability. Developed is a closed-form to assess the seismic stability of slopes with zero tensile strength. The results indicate that the presence of the tension crack has significant effects on the seismic stability of slopes, i.e., leading to small value of the yield acceleration. Considering soil tension strength in seismic slope analysis may lead to overestimation on the stability, as much as 50% for vertical slopes. Imposing tension crack results in transit of the critical failure mode to a straight line from a log-spiral, except for flat slopes with small soil cohesion. Under seismic conditions, large cohesion may increase the depth of crack, moving it closer to the slope.
In the present contribution, operational modal analysis in conjunction with bees optimization algorithm are utilized to update the finite element model of a solar power plant structure. The physical parameters which required to be updated are uncertain parameters including geometry, material properties and boundary conditions of the aforementioned structure. To determine these uncertain parameters, local and global sensitivity analyses are performed to increase the solution accuracy. An objective function is determined using the sum of the squared errors between the natural frequencies calculated by finite element method and operational modal analysis, which is optimized using bees optimization algorithm. The natural frequencies of the solar power plant structure are estimated by multi-setup stochastic subspace identification method which is considered as a strong and efficient method in operational modal analysis. The proposed algorithm is efficiently implemented on the solar power plant structure located in Shahid Chamran university of Ahvaz, Iran, to update parameters of its finite element model. Moreover, computed natural frequencies by numerical method are compared with those of the operational modal analysis. The results indicate that, bees optimization algorithm leads accurate results with fast convergence.
Steel and steel-concrete composite girders are two types of girders commonly used for long-span bridges. However, practice has shown that the two types of girders have some drawbacks. For steel girders, the orthotropic steel deck (OSD) is vulnerable to fatigue cracking and the asphalt overlay is susceptible to damage such as rutting and pot holes. While for steel-concrete composite girders, the concrete deck is generally thick and heavy, and the deck is prone to cracking because of its low tensile strength and high creep. Thus, to improve the serviceability and durability of girders for long-span bridges, three new types of steel-UHPC lightweight composite bridge girders are proposed, where UHPC denotes ultra-high performance concrete. The first two types consist of an OSD and a thin UHPC layer while the third type consists of a steel beam and a UHPC waffle deck. Due to excellent mechanical behaviors and impressive durability of UHPC, the steel-UHPC composite girders have the advantages of light weight, high strength, low creep coefficient, low risk of cracking, and excellent durability, making them competitive alternatives for long-span bridges. To date, the proposed steel-UHPC composite girders have been applied to 14 real bridges in China. It is expected that the application of the new steel-UHPC composite girders on long-span bridges will have a promising future.
This paper proposes a new type of steel-concrete composite deck, which is composed of orthotropic steel deck (OSD) with T-shaped ribs, concrete plate and studs connecting OSD and concrete plate. The OSD can act as framework for concrete plate and contribute to load bearing capacity at the same time, which could save construction time. Compared with conventional OSD system, this new type of composite bridge deck can also improve fatigue performance.Considering that this type of composite deck is not yet applied in practical engineering and its mechanical performance is not revealed in previous literatures, two full-scale specimens were designed and manufactured in this research. The mechanical performance, particularly, bending capacity in positive and negative region was carefully tested and analyzed. The load-deflection curve, load-slip relation, strain distribution in concrete and steel were obtained. The test results showed that the plastic performance of this kind of composite bridge deck was satisfying and the bending capacity was high.
This study examines the properties of fiber-reinforced reactive powder concrete (FR-RPC). Steel fibers, glass fibers, and steel-glass hybrid fibers were used to prepare the FR-RPC. The non-fibrous reactive powder concrete (NF-RPC) was prepared as a reference mix. The proportion of fibers by volume for all FR-RPC mixes was 1.5%. Steel fibers of 13 mm length and 0.2 mm diameter were used to prepare the steel fiber-reinforced RPC (SFR-RPC). Glass fibers of 13 mm length and 1.3 mm diameter were used to prepare the glass fiber-reinforced RPC (GFR-RPC). The hybrid fiber-reinforced RPC (HFR-RPC) was prepared by mixing 0.9% steel fibers and 0.6% glass fibers. Compressive strength, axial load-axial deformation behavior, modulus of elasticity, indirect tensile strength, and shear strength of the RPC mixes were investigated. The results showed that SFR-RPC achieved higher compressive strength, indirect tensile strength and shear strength than NF-RPC, GFR-RPC, and HFR-RPC. Although the compressive strengths of GFR-RPC and HFR-RPC were slightly lower than the compressive strength of NF-RPC, the shear strengths of GFR-RPC and HFR-RPC were higher than that of NF-RPC.