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Integrating storm surge modeling with traffic data analysis to evaluate the effectiveness of hurricane evacuation
Wenrui HUANG, Kai YIN, Mahyar GHORBANZADEH, Eren OZGUVEN, Sudong XU, Linoj VIJAYAN
Front. Struct. Civ. Eng.. 2021, 15 (6): 1301-1316.
https://doi.org/10.1007/s11709-021-0765-1
An integrated storm surge modeling and traffic analysis were conducted in this study to assess the effectiveness of hurricane evacuations through a case study of Hurricane Irma. The Category 5 hurricane in 2017 caused a record evacuation with an estimated 6.8 million people relocating statewide in Florida. The Advanced Circulation (ADCIRC) model was applied to simulate storm tides during the hurricane event. Model validations indicated that simulated pressures, winds, and storm surge compared well with observations. Model simulated storm tides and winds were used to estimate the area affected by Hurricane Irma. Results showed that the storm surge and strong wind mainly affected coastal counties in south-west Florida. Only moderate storm tides (maximum about 2.5 m) and maximum wind speed about 115 mph were shown in both model simulations and Federal Emergency Management Agency (FEMA) post-hurricane assessment near the area of hurricane landfall. Storm surges did not rise to the 100-year flood elevation level. The maximum wind was much below the design wind speed of 150–170 mph (Category 5) as defined in Florida Building Code (FBC) for south Florida coastal areas. Compared with the total population of about 2.25 million in the six coastal counties affected by storm surge and Category 1–3 wind, the statewide evacuation of approximately 6.8 million people was found to be an over-evacuation due mainly to the uncertainty of hurricane path, which shifted from south-east to south-west Florida. The uncertainty of hurricane tracks made it difficult to predict the appropriate storm surge inundation zone for evacuation. Traffic data were used to analyze the evacuation traffic patterns. In south-east Florida, evacuation traffic started 4 days before the hurricane’s arrival. However, the hurricane path shifted and eventually landed in south-west Florida, which caused a high level of evacuation traffic in south-west Florida. Over-evacuation caused Evacuation Traffic Index (ETI) to increase to 200% above normal conditions in some sections of highways, which reduced the effectiveness of evacuation. Results from this study show that evacuation efficiency can be improved in the future by more accurate hurricane forecasting, better public awareness of real-time storm surge and wind as well as integrated storm surge and evacuation modeling for quick response to the uncertainty of hurricane forecasting.
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Theoretical study on the confine-stiffening effect and fractal cracking of square concrete filled steel tubes in tension loads
Meng ZHOU, Jiaji WANG, Jianguo NIE, Qingrui YUE
Front. Struct. Civ. Eng.. 2021, 15 (6): 1317-1336.
https://doi.org/10.1007/s11709-021-0763-3
Tension stress in steel-concrete composite is widely observed in engineering design. Based on an experimental program on tension performance of three square concrete-filled tubes (SCFT), the tension theory of SCFT is proposed using a mechanics-based approach. The tension stiffening effect, the confining strengthening effect and the confining stiffening effect, observed in tests of SCFTs are included in the developed tension theory model. Subsequently, simplified constitutive models of steel and concrete are proposed for the axial tension performance of SCFT. Based on the MSC.MARC software, a special fiber beam-column element is proposed to include the confining effect of SCFTs under tension and verified. The proposed analytical theory, effective formulas, and equivalent constitutive laws are extensively verified against three available tests reported in the literature on both global level (e.g., load-displacement curves) and strain level. The experimental verification proves the accuracy of the proposed theory and formulations in simulating the performance of SCFT members under tension with the capability to accurately predict the tensile strength and stiffness enhancements and realistically simulate the fractal cracking phenomenon.
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Compressive behavior and microstructure of concrete mixed with natural seawater and sea sand
Qinghai XIE, Jianzhuang XIAO, Kaijian ZHANG, Zhongling ZONG
Front. Struct. Civ. Eng.. 2021, 15 (6): 1347-1357.
https://doi.org/10.1007/s11709-021-0780-2
Noncorrosive reinforcement materials facilitate producing structural concrete with seawater and sea sand. This study investigated the properties of seawater and sea sand concrete (SSC), considering the curing age (3, 7, 14, 21, 28, 60, and 150 d) and strength grade (C30, C40, and C60). The compressive behavior of SSC was obtained by compressive tests and digital image correction (DIC) technique. Scanning electron microscope (SEM) and X-ray powder diffraction (XRD) methods were applied to understand the microstructure and hydration products of cement in SSC. Results revealed a 30% decrease in compressive strength for C30 and C40 SSC from 60 to 150 d, and a less than 5% decrease for C60 from 28 to 150 d. DIC results revealed significant cracking and crushing from 80% to 100% of compressive strength. SEM images showed a more compact microstructure in higher strength SSC. XRD patterns identified Friedel’s salt phase due to the chlorides brought by seawater and sea sand. The findings in this study can provide more insights into the microstructure of SSC along with its short- and long-term compressive behavior.
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Chloride ingress and macro-cell corrosion of steel in concrete made with recycled brick aggregate
Tarek Uddin MOHAMMED, Mahfuzur RAHMAN, Ahmed SABBIR, Mohammad Mehedi HASAN, Abdullah Al MAMUN
Front. Struct. Civ. Eng.. 2021, 15 (6): 1358-1371.
https://doi.org/10.1007/s11709-021-0769-x
An investigation on chloride ingress and macro-cell corrosion of steel bars in concrete made with recycled brick aggregate (RBA) was carried out. As control cases, virgin brick aggregate (BA) and stone aggregate (SA) were also investigated. Both cylindrical and cracked prism specimens were studied for 16 different cases. The prism specimens were made with a segmented steel bar providing electrical connection from outside of the specimens to measure macro-cell corrosion current continuously under seawater splash exposure for a period of 30 d using a data logger. Cylindrical specimens were submerged in 3% NaCl solution at a temperature of 40°C to investigate chloride ingress in concrete made with RBA, BA, and SA after 120 and 180 d. Half-cell potential, corrosion area, and depths of corrosion were also investigated. The chloride ingress as well as corrosion of steel bars in concrete made with the different types of aggregate is ordered as RBA > BA > SA.
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Effect of different high viscosity modifiers on rheological properties of high viscosity asphalt
Peipei KONG, Gang XU, Xianhua CHEN, Xiangdong SHI, Jie ZHOU
Front. Struct. Civ. Eng.. 2021, 15 (6): 1390-1399.
https://doi.org/10.1007/s11709-021-0775-z
High viscosity asphalt (HVA) has been a great success as a drainage pavement material. However, the larger porosity of drainage asphalt mixtures weakens the cohesion and adhesion and leads to premature rutting, water damage, spalling and cracking. The purpose of this study was to investigate the rheological properties of HVA prepared using different high viscosity modifiers through conventional tests, Brookfield viscosity tests, dynamic shear rheometer tests and bending beam rheometer tests. The conventional performance results demonstrated SBS + rubber asphalt (SRA-1/2) exhibited excellent elastic recovery and low-temperature flexibility. The 60°C dynamic viscosity results indicated TPS + rubber asphalt (TRA) had the excellent adhesion. The rotational viscosity results and rheological results indicated that SRA-2 not only exhibited excellent temperature stability and workability, as well as excellent resistance to deformation and rutting resistance, but also exhibited excellent low-temperature cracking resistance and relaxation performance. Based on rheological results, the PG classification of HVA was 16% rubber + asphalt for PG76-22, 20% rubber + asphalt for PG88-22, TRA and SRA-1/2 for PG88-28. From comprehensive evaluation of the viscosity, temperature stability and sensitivity, as well as high/low temperature performance of HVA, SRA-2 was found to be more suited to the requirements of drainage asphalt pavement materials.
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Destructive and non-destructive evaluation of concrete for optimum sand to aggregate volume ratio
Tarek Uddin MOHAMMED, Aziz Hasan MAHMOOD, Mohammad Zunaied-Bin-HARUN, Jamil Ahmed JOY, Md. Asif AHMED
Front. Struct. Civ. Eng.. 2021, 15 (6): 1400-1414.
https://doi.org/10.1007/s11709-021-0779-8
Aggregates are the biggest contributor to concrete volume and are a crucial parameter in dictating its mechanical properties. As such, a detailed experimental investigation was carried out to evaluate the effect of sand-to-aggregate volume ratio (s/a) on the mechanical properties of concrete utilizing both destructive and non-destructive testing (employing UPV (ultrasonic pulse velocity) measurements). For investigation, standard cylindrical concrete samples were made with different s/a (0.36, 0.40, 0.44, 0.48, 0.52, and 0.56), cement content (340 and 450 kg/m3), water-to-cement ratio (0.45 and 0.50), and maximum aggregate size (12 and 19 mm). The effect of these design parameters on the 7, 14, and 28 d compressive strength, tensile strength, elastic modulus, and UPV of concrete were assessed. The careful analysis demonstrates that aggregate proportions and size need to be optimized for formulating mix designs; optimum ratios of s/a were found to be 0.40 and 0.44 for the maximum aggregate size of 12 and 19 mm, respectively, irrespective of the W/C (water-to-cement) and cement content.
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Influence of steel corrosion on axial and eccentric compression behavior of coral aggregate concrete column
Bo DA, Yan CHEN, Hongfa YU, Haiyan MA, Bo YU, Da CHEN, Xiao CHEN, Zhangyu WU, Jianbo GUO
Front. Struct. Civ. Eng.. 2021, 15 (6): 1415-1425.
https://doi.org/10.1007/s11709-021-0786-9
To study the behavior of coral aggregate concrete (CAC) column under axial and eccentric compression, the compression behavior of CAC column with different types of steel and initial eccentricity (ei) were tested, and the deformation behavior and ultimate bearing capacity (Nu) were studied. The results showed that as the ei increases, the Nu of CAC column decreases nonlinearly. Besides, the steel corrosion in CAC column is severe, which reduces the steel section and steel strength, and decreases the Nu of CAC column. The durability of CAC structures can be improved by using new organic coated steel. Considering the influence of steel corrosion and interfacial bond deterioration, the calculation models of Nu under axial and eccentric compression were presented.
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Estimation of optimum design of structural systems via machine learning
Gebrail BEKDAŞ, Melda YÜCEL, Sinan Melih NIGDELI
Front. Struct. Civ. Eng.. 2021, 15 (6): 1441-1452.
https://doi.org/10.1007/s11709-021-0774-0
Three different structural engineering designs were investigated to determine optimum design variables, and then to estimate design parameters and the main objective function of designs directly, speedily, and effectively. Two different optimization operations were carried out: One used the harmony search (HS) algorithm, combining different ranges of both HS parameters and iteration with population numbers. The other used an estimation application that was done via artificial neural networks (ANN) to find out the estimated values of parameters. To explore the estimation success of ANN models, different test cases were proposed for the three structural designs. Outcomes of the study suggest that ANN estimation for structures is an effective, successful, and speedy tool to forecast and determine the real optimum results for any design model.
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A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced composite plates using modal kinetic energy
Huy Q. LE, Tam T. TRUONG, D. DINH-CONG, T. NGUYEN-THOI
Front. Struct. Civ. Eng.. 2021, 15 (6): 1453-1479.
https://doi.org/10.1007/s11709-021-0767-z
This paper proposes a new Deep Feed-forward Neural Network (DFNN) approach for damage detection in functionally graded carbon nanotube-reinforced composite (FG-CNTRC) plates. In the proposed approach, the DFNN model is developed based on a data set containing 20 000 samples of damage scenarios, obtained via finite element (FE) simulation, of the FG-CNTRC plates. The elemental modal kinetic energy (MKE) values, calculated from natural frequencies and translational nodal displacements of the structures, are utilized as input of the DFNN model while the damage locations and corresponding severities are considered as output. The state-of-the art Exponential Linear Units (ELU) activation function and the Adamax algorithm are employed to train the DFNN model. Additionally, in order to enhance the performance of the DFNN model, the mini-batch and early-stopping techniques are applied to the training process. A trial-and-error procedure is implemented to determine suitable parameters of the network such as the number of hidden layers and the number of neurons in each layer. The accuracy and capability of the proposed DFNN model are illustrated through two distinct configurations of the CNT-fibers constituting the FG-CNTRC plates including uniform distribution (UD) and functionally graded-V distribution (FG-VD). Furthermore, the performance and stability of the DFNN model with the consideration of noise effects on the input data are also investigated. Obtained results indicate that the proposed DFNN model is able to give sufficiently accurate damage detection outcomes for the FG-CNTRC plates for both cases of noise-free and noise-influenced data.
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