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Development trend of urban design in “digital age”: Pan-dimensionality and individual-ubiquity
Jianguo WANG
Front. Struct. Civ. Eng.. 2021, 15 (3): 569-575.
https://doi.org/10.1007/s11709-021-0735-7
The wave of “digital age” featuring digital information is coming. Digital technology is profoundly changing the societal development direction and evolution paths. It also has significant bearing on production modes, social interactions and lifestyles. With regard to urban design, a system of knowledge about the creation and adaptation of material space forms that integrate humanities, art, technology and materials, digital technology has provided it with a brand-new and revolutionary scientific impetus for its evolution. The result of this evolution is “digital urban design paradigm based on human-computer interaction”, i.e., the urban development is moving toward “pan-dimensionality” and “individual ubiquity”. The future of urban design will construct a new approach to urban research and engineering, which is more complex, capable of accommodating and compatible with multiple goals of “instrumental rationality” and “value rationality”. Such a new approach shall be led by the probabilistic theory of “gray scale thinking”, reflecting quaternary synergetic view of “scientific rationality, ecological rationality, cultural rationality and technical rationality” to realize the cognitive progress of “engineering for the benefit of mankind”.
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Fatigue shear performance of concrete beams reinforced with hybrid (glass-fiber-reinforced polymer+ steel) rebars and stirrups
Peng ZHU, Jiajing XU, Wenjun QU
Front. Struct. Civ. Eng.. 2021, 15 (3): 576-594.
https://doi.org/10.1007/s11709-021-0728-6
Reinforced concrete beams consisting of both steel and glass-fiber-reinforced polymer rebars exhibit excellent strength, serviceability, and durability. However, the fatigue shear performance of such beams is unclear. Therefore, beams with hybrid longitudinal bars and hybrid stirrups were designed, and fatigue shear tests were performed. For specimens that failed by fatigue shear, all the glass-fiber-reinforced polymer stirrups and some steel stirrups fractured at the critical diagonal crack. For the specimen that failed by the static test after 8 million fatigue cycles, the static capacity after fatigue did not significantly decrease compared with the calculated value. The initial fatigue level has a greater influence on the crack development and fatigue life than the fatigue level in the later phase. The fatigue strength of the glass-fiber-reinforced polymer stirrups in the specimens was considerably lower than that of the axial tension tests on the glass-fiber-reinforced polymer bar in air and beam-hinge tests on the glass-fiber-reinforced polymer bar, and the failure modes were different. Glass-fiber-reinforced polymer stirrups were subjected to fatigue tension and shear, and failed owing to shear.
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Parametric equations for notch stress concentration factors of rib–deck welds under bending loading
Qiudong WANG, Bohai JI, Zhongqiu FU, Yue YAO
Front. Struct. Civ. Eng.. 2021, 15 (3): 595-608.
https://doi.org/10.1007/s11709-021-0720-1
The effective notch stress approach for evaluating the fatigue strength of rib–deck welds requires notch stress concentration factors obtained from complex finite element analysis. To improve the efficiency of the approach, the notch stress concentration factors for three typical fatigue-cracking modes (i.e., root–toe, root–deck, and toe–deck cracking modes) were thoroughly investigated in this study. First, we developed a model for investigating the effective notch stress in rib–deck welds. Then, we performed a parametric analysis to investigate the effects of multiple geometric parameters of a rib–deck weld on the notch stress concentration factors. On this basis, the multiple linear stepwise regression analysis was performed to obtain the optimal regression functions for predicting the notch stress concentration factors. Finally, we employed the proposed formulas in a case study. The notch stress concentration factors estimated from the developed formulas show agree well with the finite element analysis results. The results of the case study demonstrate the feasibility and reliability of the proposed formulas. It also shows that the fatigue design curve of FAT225 seems to be conservative for evaluating the fatigue strength of rib–deck welds.
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Modeling limit force capacities of high force to volume lead extrusion dampers
V. VISHNUPRIYA, Geoffrey. W. RODGERS, J. Geoffrey CHASE
Front. Struct. Civ. Eng.. 2021, 15 (3): 609-622.
https://doi.org/10.1007/s11709-021-0724-x
Lead extrusion dampers are supplemental energy-dissipation devices that are used to mitigate seismic structural damage. Small volumetric sizes and high force capacities define high-force-to-volume (HF2V) devices, which can absorb significant response energy without sacrificial damage. However, the design of such devices for specific force capacities has proven difficult based on the complexities of their internal reaction mechanisms, leading to the adoption of empirical approaches. This study developed upper- and lower-bound force capacity estimates from analytical mechanics based on direct and indirect metal extrusion for guiding design. The derived equations are strictly functions of HF2V device geometric parameters, lead material properties, and extrusion mechanics. The upper-bound estimates from direct and indirect extrusion are denoted as (FUB,1, FUB,2) and (FUB,3, FUB,4), respectively, and the lower-bound estimates are denoted as (FLB, FLB,1) based on the combination of extrusion and friction forces. The proposed models were validated by comparing the predicted bounds to experimental force capacity data from 15 experimental HF2V device tests. The experimental device forces all lie above the lower-bound estimates (FLB, FLB,1) and below the upper-bound estimates (FUB,1, FUB,2, FUB,4). Overall, the (FLB, FUB,2) pair provides wider bounds and the (FLB,1, FUB,4/FUB,1) pair provides narrower bounds. The (FLB,1, FUB,1) pair has a mean lower-bound gap of 36%, meaning the lower bound was 74% of the actual device force on average. The mean upper-bound gap was 33%. The bulge area and cylinder diameter of HF2V devices are key parameters affecting device forces. These relatively tight bounds provide useful mechanics-based predictive design guides for ensuring that device forces are within the targeted design range after manufacturing.
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Progressive failure analysis of notched composite plate by utilizing macro mechanics approach
Seyed M. N. GHOREISHI, Mahdi FAKOOR, Ahmad AZIZI
Front. Struct. Civ. Eng.. 2021, 15 (3): 623-642.
https://doi.org/10.1007/s11709-021-0726-8
In this study, gradual and sudden reduction methods were combined to simulate a progressive failure in notched composite plates using a macro mechanics approach. Using the presented method, a progressive failure is simulated based on a linear softening law prior to a catastrophic failure, and thereafter, sudden reduction methods are employed for modeling a progressive failure. This combination method significantly reduces the computational cost and is also capable of simultaneously predicting the first and last ply failures (LPFs) in composite plates. The proposed method is intended to predict the first ply failure (FPF), LPF, and dominant failure modes of carbon/epoxy and glass/epoxy notched composite plates. In addition, the effects of mechanical properties and different stacking sequences on the propagation of damage in notched composite plates were studied. The results of the presented method were compared with experimental data previously reported in the literature. By comparing the numerical and experimental data, it is revealed that the proposed method can accurately simulate the failure propagation in notched composite plates at a low computational cost.
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Characterization of 3D microstructure, thermal conductivity, and heat flow of cement-based foam using imaging technique
Farnaz BATOOL, Muhammad Saad KHAN, Vivek BINDIGANAVILE
Front. Struct. Civ. Eng.. 2021, 15 (3): 643-651.
https://doi.org/10.1007/s11709-021-0709-9
This study presents the results of the 3D microstructure, thermal conductivity, and heat flow in cement-based foams and examines their changes with a range of densities. Images were captured using X-ray micro computed tomography (micro-CT) imaging technique on cement-based foam samples prepared with densities of 400, 600, and 800 kg/m3. These images were later simulated and quantified using 3D data visualization and analysis software. Based on the analysis, the pore volume of 11000 µm3 was determined across the three densities, leading to optimal results. However, distinct pore diameters of 15 µm for 800 kg/m3, and 20 µm for 600 and 400 kg/m3 were found to be optimum. Most of the pores were spherical, with only 10% appearing elongated or fractured. In addition, a difference of 15% was observed between the 2D and 3D porosity results. Moreover, a difference of 5% was noticed between the experimentally measured thermal conductivity and the numerically predicted value and this variation was constant across the three cast densities. The 3D model showed that heat flows through the cement paste solids and with an increase in porosity this flow reduces.
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Prediction of hydro-suction dredging depth using data-driven methods
Amin MAHDAVI-MEYMAND, Mohammad ZOUNEMAT-KERMANI, Kourosh QADERI
Front. Struct. Civ. Eng.. 2021, 15 (3): 652-664.
https://doi.org/10.1007/s11709-021-0719-7
In this study, data-driven methods (DDMs) including different kinds of group method of data handling (GMDH) hybrid models with particle swarm optimization (PSO) and Henry gas solubility optimization (HGSO) methods, and simple equations methods were applied to simulate the maximum hydro-suction dredging depth (hs). Sixty-seven experiments were conducted under different hydraulic conditions to measure the hs. Also, 33 data samples from three previous studies were used. The model input variables consisted of pipeline diameter (d), the distance between the pipe inlet and sediment level (Z), the velocity of flow passing through the pipeline (u0), the water head (H), and the medium size of particles (D50). Data-driven simulation results indicated that the HGSO algorithm accurately trains the GMDH methods better than the PSO algorithm, whereas the PSO algorithm trained simple simulation equations more precisely. Among all used DDMs, the integrative GMDH-HGSO algorithm provided the highest accuracy (RMSE = 7.086 mm). The results also showed that the integrative GMDHs enhance the accuracy of polynomial GMDHs by ~14.65% (based on the RMSE).
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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related uncertainties
Ahmad SHARAFATI, Masoud HAGHBIN, Mohammadamin TORABI, Zaher Mundher YASEEN
Front. Struct. Civ. Eng.. 2021, 15 (3): 665-681.
https://doi.org/10.1007/s11709-021-0713-0
The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (Rtest = 0.923) and minimum root mean square error value (RMSEtest = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.
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Probabilistic analysis of secant piles with random geometric imperfections
Yi YANG, Dalong JIN, Xinggao LI, Weilin SU, Xuyang WANG
Front. Struct. Civ. Eng.. 2021, 15 (3): 682-695.
https://doi.org/10.1007/s11709-021-0703-2
The failure to achieve minimum design overlap between secant piles compromises the ability of a structure to perform as designed, resulting in water leakage or even ground collapse. To establish a more realistic simulation and provide guidelines for designing a safe and cost-effective secant-pile wall, a three-dimensional model of a secant pile, considering the geometric imperfections of the diameter and direction of the borehole, is introduced. An ultrasonic cross-hole test was performed during the construction of secant piles in a launching shaft in Beijing, China. Based on the test results, the statistical characteristics of the pile diameters and orientation parameters were obtained. By taking the pile diameter D, inclination angle β, and azimuth angle α as random variables, Monte Carlo simulations were performed to discuss the influence of different design parameters on the probability density functions of the overlap of secant piles. The obtained results show that the randomness of the inclination angle and pile diameter can be well described by a normal distribution, whereas the azimuth angle is more consistent with a uniform distribution. The integrity of the secant-pile wall can be overestimated without considering the uncertainty of geometric imperfections. The failure of the secant-pile wall increases substantially with increasing spatial variability in drilling inclination and diameter. A design flowchart for pile spacing under the target safety level is proposed to help engineers design a safe and economical pile wall.
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Data-driven approach to solve vertical drain under time-dependent loading
Trong NGHIA-NGUYEN, Mamoru KIKUMOTO, Samir KHATIR, Salisa CHAIYAPUT, H. NGUYEN-XUAN, Thanh CUONG-LE
Front. Struct. Civ. Eng.. 2021, 15 (3): 696-711.
https://doi.org/10.1007/s11709-021-0727-7
Currently, the vertical drain consolidation problem is solved by numerous analytical solutions, such as time-dependent solutions and linear or parabolic radial drainage in the smear zone, and no artificial intelligence (AI) approach has been applied. Thus, in this study, a new hybrid model based on deep neural networks (DNNs), particle swarm optimization (PSO), and genetic algorithms (GAs) is proposed to solve this problem. The DNN can effectively simulate any sophisticated equation, and the PSO and GA can optimize the selected DNN and improve the performance of the prediction model. In the present study, analytical solutions to vertical drains in the literature are incorporated into the DNN–PSO and DNN–GA prediction models with three different radial drainage patterns in the smear zone under time-dependent loading. The verification performed with analytical solutions and measurements from three full-scale embankment tests revealed promising applications of the proposed approach.
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Surficial stability analysis of soil slope under seepage based on a novel failure mode
Jifeng LIAN, Jiujiang WU
Front. Struct. Civ. Eng.. 2021, 15 (3): 712-726.
https://doi.org/10.1007/s11709-021-0729-5
Normally, the edge effects of surficial landslides are not considered in the infinite slope method for surficial stability analysis of soil slopes. In this study, the limit stress state and discrimination equation of an infinite slope under saturated seepage flow were analyzed based on the Mohr-Coulomb strength criterion. Therefore, a novel failure mode involving three sliding zones (upper tension zone, middle shear sliding zone, and lower compression zone) was proposed. Accordingly, based on the limit equilibrium analysis, a semi-analytical framework considering the edge effect for the surficial stability of a soil slope under downslope seepage was established. Subsequently, the new failure mode was verified via a numerical finite element analysis based on the reduced strength theory with ABAQUS and some simplified methods using SLIDE software. The results obtained by the new failure mode agree well with those obtained by the numerical analysis and traditional simplified methods, and can be efficiently used to assess the surficial stability of soil slopes under rainwater seepage. Finally, an evaluation of the infinite slope method was performed using the semi-analytical method proposed in this study. The results show that the infinite slope tends to be conservative because the edge effect is neglected, particularly when the ratio of surficial slope length to depth is relatively small.
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Assessment of glass fiber-reinforced polyester pipe powder in soil improvement
Baki BAĞRIAÇIK, Ahmet BEYCIOĞLU, Szymon TOPOLINSKI, Emre AKMAZ, Sedat SERT, Esra Deniz GÜNER
Front. Struct. Civ. Eng.. 2021, 15 (3): 742-753.
https://doi.org/10.1007/s11709-021-0732-x
This study investigates the use of glass fiber-reinforced polyester (GRP) pipe powder (PP) for improving the bearing capacity of sandy soils. After a series of direct share tests, the optimum PP addition for improving the bearing capacity of soils was found to be 12%. Then, using the optimum PP addition, the bearing capacity of the soil was estimated through a series of loading tests on a shallow foundation model placed in a test box. The bearing capacity of sandy soil was improved by up to 30.7%. The ratio of the depth of the PP-reinforced soil to the diameter of the foundation model (H/D) of 1.25 could sufficiently strengthen sandy soil when the optimum PP ratio was used. Microstructural analyses showed that the increase in the bearing capacity can be attributed to the chopped fibers in the PP and their multiaxial distribution in the soil. Besides improving the engineering properties of soils, using PP as an additive in soils would reduce the accumulation of the industrial waste, thus providing a twofold benefit.
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Influence of construction-induced damage on the degradation of freeze–thawed lightweight cellular concrete
Xin LIU, Liye ZHANG, Zhiwei SHAO, Yunqiang SHI, Lizhi SUN
Front. Struct. Civ. Eng.. 2021, 15 (3): 781-792.
https://doi.org/10.1007/s11709-021-0733-9
During the construction of lightweight cellular concrete (LCC), material damage frequently occurs, causing the degradation and deterioration of the mechanical performance, durability, and subgrade quality of LCC. The construction-induced damage can be more significant than those from the service environment of LCC, such as freeze–thaw (F–T) action in cold regions. However, the effect of construction-induced damage on LCC during F–T cycles is often ignored and the deterioration mechanisms are not yet clarified. In this study, we investigated the factors causing damage during construction using a sample preparation method established to simulate the damage in the laboratory setting. We conducted F–T cycle tests and microstructural characterization to study the effect of microstructural damage on the overall strength of LCC with different water contents under F–T actions. We established the relationship between the pore-area ratio and F–T cycle times, pore-area ratio, and strength, as well as the F–T cycle times and strength under different damage forms. The damage evolution is provided with the rationality of the damage equation, verified by comparing the measured and predicted damage variables. This study would serve as a guide for the construction and performance of LCC in cold regions.
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Service life prediction of fly ash concrete using an artificial neural network
Yasmina KELLOUCHE, Mohamed GHRICI, Bakhta BOUKHATEM
Front. Struct. Civ. Eng.. 2021, 15 (3): 793-805.
https://doi.org/10.1007/s11709-021-0717-9
Carbonation is one of the most aggressive phenomena affecting reinforced concrete structures and causing their degradation over time. Once reinforcement is altered by carbonation, the structure will no longer fulfill service requirements. For this purpose, the present work estimates the lifetime of fly ash concrete by developing a carbonation depth prediction model that uses an artificial neural network technique. A collection of 300 data points was made from experimental results available in the published literature. Backpropagation training of a three-layer perceptron was selected for the calculation of weights and biases of the network to reach the desired performance. Six parameters affecting carbonation were used as input neurons: binder content, fly ash substitution rate, water/binder ratio, CO2 concentration, relative humidity, and concrete age. Moreover, experimental validation carried out for the developed model shows that the artificial neural network has strong potential as a feasible tool to accurately predict the carbonation depth of fly ash concrete. Finally, a mathematical formula is proposed that can be used to successfully estimate the service life of fly ash concrete.
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