Journal home Browse Featured articles

Featured articles

  • Select all
  • RESEARCH ARTICLE
    Zhiyuan ZHANG, Xu LI, Yongkang WU, Xiaokang LI
    Frontiers of Structural and Civil Engineering, 2022, 16(12): 1501-1514. https://doi.org/10.1007/s11709-022-0893-2

    The Richards’ equation describes the flow phenomenon in unsaturated porous media and is essential to hydrology and environmental science. This study evaluated the numerical stability of two different forms of the Richards’ equation. Sensitivity analyses were performed to investigate the control parameters of the equation. The results show that the h-form Richards’ equation has better applicability for calculating variable saturation flows than the θ-form Richards’ equation. For the h-form Richards’ equation, the hydraulic conductivity of the soil in the low-suction range and the specific moisture capacity in the high-suction range primarily influenced the solution. In addition, sensitivity analyses indicated that the saturated hydraulic conductivity, initial condition, and air-entry pressure have a higher sensitivity to the simulation results than the saturated water content, rainfall intensity, and decline rate of hydraulic conductivity. Moreover, their correctness needs to be guaranteed first in numerical simulations. The research findings can provide a helpful reference for improving the reliability of numerical simulations of unsaturated flows.

  • RESEARCH ARTICLE
    Hamed BOLANDI, Xuyang LI, Talal SALEM, Vishnu Naresh BODDETI, Nizar LAJNEF
    Frontiers of Structural and Civil Engineering, 2022, 16(11): 1365-1377. https://doi.org/10.1007/s11709-022-0882-5

    Finite-element analysis (FEA) for structures has been broadly used to conduct stress analysis of various civil and mechanical engineering structures. Conventional methods, such as FEA, provide high fidelity results but require the solution of large linear systems that can be computationally intensive. Instead, Deep Learning (DL) techniques can generate results significantly faster than conventional run-time analysis. This can prove extremely valuable in real-time structural assessment applications. Our proposed method uses deep neural networks in the form of convolutional neural networks (CNN) to bypass the FEA and predict high-resolution stress distributions on loaded steel plates with variable loading and boundary conditions. The CNN was designed and trained to use the geometry, boundary conditions, and load as input to predict the stress contours. The proposed technique’s performance was compared to finite-element simulations using a partial differential equation (PDE) solver. The trained DL model can predict the stress distributions with a mean absolute error of 0.9% and an absolute peak error of 0.46% for the von Mises stress distribution. This study shows the feasibility and potential of using DL techniques to bypass FEA for stress analysis applications.

  • RESEARCH ARTICLE
    Xia YAN, Marion CHARLIER, Thomas GERNAY
    Frontiers of Structural and Civil Engineering, 2022, 16(9): 1071-1088. https://doi.org/10.1007/s11709-022-0879-0

    For open car park structures, adopting a performance-based structural fire design is often justified and allowed because the fire does not reach flashover. However, this design approach requires an accurate assessment of temperatures in structural members exposed to car fires. This paper describes a numerical study on the thermal exposure on steel framing members in open car park fires. Steel temperatures are computed by the coupling of computational fluid dynamics and finite element modeling, and by analytical models from the Eurocodes. In addition, the influence of galvanization on the steel temperature evolution is assessed. Results show that temperatures in unprotected beams and columns are influenced by the section geometry, car fire scenario, modeling approach, and use of galvanization. Galvanization slightly delays and reduces peak temperature. Regarding the different models, CFD-FEM (CFD: computational fluid dynamics, FEM: finite-element method) coupled models predict lower temperatures than the Hasemi model, because the latter conservatively assumes that the fire flame continuously touches the ceiling. Further, the Hasemi model cannot account for the effect of reduced emissivity from galvanization on the absorbed heat flux. Detailed temperature distributions obtained in the steel members can be used to complete efficient structural fire designs based on the member sections, structure layout, and use of galvanization.

  • REVIEW
    Mgboawaji Claude UJILE, Samuel Jonah ABBEY
    Frontiers of Structural and Civil Engineering, 2022, 16(7): 803-816. https://doi.org/10.1007/s11709-022-0835-z

    Construction and demolition waste (CDW) are the largest waste products in the world today and competes as a viable recycled additive material in place of natural aggregates. Due to the increase in compressive strength of different mix proportions of CDW, it is also considered for reuse in concrete and subbase construction. This study shows the effect of CDW in expansive soil stabilization. The chemical and mechanical properties of these materials have shown that they are capable of developing compressive strength properties for replacement of cement with significant reduction in carbon emission. The inherent compositional properties of recycled CDW compared in this review suggests that CDW have good filler properties in highly expansive soils. Mixtures of crushed brick and recycled aggregates characterised based on chemical properties of different replacement ratios suggests that CDW of good-quality aggregates reduces swell potential of expansive soils and increased mechanical strength in pavement construction.

  • RESEARCH ARTICLE
    Zaobao LIU, Yongchen WANG, Long LI, Xingli FANG, Junze WANG
    Frontiers of Structural and Civil Engineering, 2022, 16(4): 401-413. https://doi.org/10.1007/s11709-022-0823-3

    Real-time dynamic adjustment of the tunnel bore machine (TBM) advance rate according to the rock-machine interaction parameters is of great significance to the adaptability of TBM and its efficiency in construction. This paper proposes a real-time predictive model of TBM advance rate using the temporal convolutional network (TCN), based on TBM construction big data. The prediction model was built using an experimental database, containing 235 data sets, established from the construction data from the Jilin Water-Diversion Tunnel Project in China. The TBM operating parameters, including total thrust, cutterhead rotation, cutterhead torque and penetration rate, are selected as the input parameters of the model. The TCN model is found outperforming the recurrent neural network (RNN) and long short-term memory (LSTM) model in predicting the TBM advance rate with much smaller values of mean absolute percentage error than the latter two. The penetration rate and cutterhead torque of the current moment have significant influence on the TBM advance rate of the next moment. On the contrary, the influence of the cutterhead rotation and total thrust is moderate. The work provides a new concept of real-time prediction of the TBM performance for highly efficient tunnel construction.

  • RESEARCH ARTICLE
    Huailei CHENG, Liping LIU, Lijun SUN
    Frontiers of Structural and Civil Engineering, 2022, 16(3): 267-280. https://doi.org/10.1007/s11709-022-0811-7

    Asphalt pavement is a key component of highway infrastructures in China and worldwide. In asphalt pavement design and condition assessment, the modulus of the asphalt mixture layer is a crucial parameter. However, this parameter varies between the laboratory and field loading modes (i.e., loading frequency, compressive or tensile loading pattern), due to the viscoelastic property and composite structure of the asphalt mixture. The present study proposes a comprehensive frequency-based approach to correlate the asphalt layer moduli obtained under two field and three laboratory loading modes. The field modes are vehicular and falling weight deflectometer (FWD) loading modes, and the laboratory ones are uniaxial compressive (UC), indirect tensile (IDT), and four-point bending (4PB) loading modes. The loading frequency is used as an intermediary parameter for correlating the asphalt layer moduli under different loading modes. The observations made at two field large-scale experimental pavements facilitate the correlation analysis. It is found that the moduli obtained via laboratory 4PB tests are pretty close to those of vehicular loading schemes, in contrast to those derived in UC, IDT, and FWD modes, which need to be adjusted. The corresponding adjustment factors are experimentally assessed. The applications of those adjustment factors are expected to ensure that the moduli measured under different loading modes are appropriately used in asphalt mixture pavement design and assessment.

  • RESEARCH ARTICLE
    Nazim Abdul NARIMAN, Raja Rizwan HUSSAIN, Ilham Ibrahim MOHAMMAD, Peyman KARAMPOUR
    Frontiers of Structural and Civil Engineering, 2019, 13(6): 1289-1300. https://doi.org/10.1007/s11709-019-0548-0

    There are many certain and uncertain design factors which have unrevealed rational effects on the generation of tensile damage and the stability of the circular tunnels during seismic actions. In this research paper, we have dedicated three certain and four uncertain design factors to quantify their rational effects using numerical simulations and the Sobol’s sensitivity indices. Main effects and interaction effects between the design factors have been determined supporting on variance-based global sensitivity analysis. The results detected that the concrete modulus of elasticity for the tunnel lining has the greatest effect on the tensile damage generation in the tunnel lining during the seismic action. In the other direction, the interactions between the concrete density and both of concrete modulus of elasticity and tunnel diameter have appreciable effects on the tensile damage. Furthermore, the tunnel diameter has the deciding effect on the stability of the tunnel structure. While the interaction between the tunnel diameter and concrete density has appreciable effect on the stability process. It is worthy to mention that Sobol’s sensitivity indices manifested strong efficiency in detecting the roles of each design factor in cooperation with the numerical simulations explaining the responses of the circular tunnel during seismic actions.

  • RESEARCH ARTICLE
    Narjes SOLTANI, Mohammad ALEMBAGHERI, Mohammad Houshmand KHANEGHAHI
    Frontiers of Structural and Civil Engineering, 2019, 13(5): 1007-1019. https://doi.org/10.1007/s11709-019-0521-y

    The probabilistic risk of arch dam failure under thermal loading is studied. The incorporated uncertainties, which are defined as random variables, are associated with the most affecting structural (material) properties of concrete and thermal loading conditions. Karaj arch dam is selected as case study. The dam is numerically modeled along with its foundation in three-dimensional space; the temperature and thermal stress distribution is investigated during the operating phase. The deterministic thermal finite element analysis of the dam is combined with the structural reliability methods in order to obtain thermal response predictions, and estimate the probability of failure in the risk analysis context. The tensile overstressing failure mode is considered for the reliability analysis. The thermal loading includes ambient air and reservoir temperature variations. The effect of solar radiation is considered by an increase in the ambient temperatures. Three reliability methods are employed: the first-order second-moment method, the first-order reliability method, and the Monte-Carlo simulation with Latin Hypercube sampling. The estimated failure probabilities are discussed and the sensitivity of random variables is investigated. Although most of the studies in this line of research are used only for academic purposes, the results of this investigation can be used for both academic and engineering purposes.

  • RESEARCH ARTICLE
    Zhenyuan LUO, Weiming YAN, Weibing XU, Qinfei ZHENG, Baoshun WANG
    Frontiers of Structural and Civil Engineering, 2019, 13(4): 751-766. https://doi.org/10.1007/s11709-018-0509-z

    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.

  • RESEARCH ARTICLE
    Y B SUDHIR SASTRY, B G KIROS, F HAILU, P R BUDARAPU
    Frontiers of Structural and Civil Engineering, 2019, 13(3): 505-514. https://doi.org/10.1007/s11709-018-0493-3

    Frequent failures due to foreign particle impacts are observed in compressor blades of the interceptor fighter MIG-23 aircraft engines in the Ethiopian air force, supplied by the Dejen Aviation Industry. In this paper, we made an attempt to identify the causes of failure and hence recommend the suitable materials to withstand the foreign particle impacts. Modal and stress analysis of one of the recently failed MIG-23 gas turbine compressor blades made up of the following Aluminum based alloys: 6061-T6, 7075-T6, and 2024-T4, has been performed, apart from the impact analysis of the rotor blades hit by a granite stone. The numerical results are correlated to the practical observations. Based on the modal, stress and impact analysis and the material properties of the three considered alloys, alloy 7075-T6 has been recommended as the blade material.