Huang, Qinghua;Yu, Xinping;Lv, Jun;Zhou, Jilie;Elvenia, Marischa Ray
Steel and Composite Structures
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v.45
no.3
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pp.409-423
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2022
Nowadays, there is a high demand for great structural implementation and multifunctionality with excellent mechanical properties. The porous structures reinforced by graphene platelets (GPLs) having valuable properties, such as heat resistance, lightweight, and excellent energy absorption, have been considerably used in different engineering implementations. However, stiffness of porous structures reduces significantly, due to the internal cavities, by adding GPLs into porous medium, effective mechanical properties of the porous structure considerably enhance. This paper is relating to vibration analysis of fluidconveying cantilever porous graphene platelet reinforced (GPLR) pipe with fractional viscoelastic model resting on foundations. A dynamical model of cantilever porous GPLR pipes conveying fluid and resting on a foundation is proposed, and the vibration, natural frequencies and primary resonant of such a system are explored. The pipe body is considered to be composed of GPLR viscoelastic polymeric pipe with porosity in which Halpin-Tsai scheme in conjunction with the fractional viscoelastic model is used to govern the construction relation of nanocomposite pipe. Three different porosity distributions through the pipe thickness are introduced. The harmonic concentrated force is also applied to the pipe and the excitation frequency is close to the first natural frequency. The governing equation for transverse motions of the pipe is derived by the Hamilton principle and then discretized by the Galerkin procedure. In order to obtain the frequency-response equation, the differential equation is solved with the assumption of small displacement, damping coefficient, and excitation amplitude by the multiple scale method. A parametric sensitivity analysis is carried out to reveal the influence of different parameters, such as nanocomposite pipe properties, fluid velocity and nonlinear viscoelastic foundation coefficients, on the primary resonance and linear natural frequency. Results indicate that the GPLs weight fraction porosity coefficient, fractional derivative order and the retardation time have substantial influences on the dynamic response of the system.
SETYAYUNITA, Tamaryska;WIDYORINI, Ragil;MARSOEM, Sri Nugroho;IRAWATI, Denny
Journal of the Korean Wood Science and Technology
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v.50
no.2
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pp.93-103
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2022
Currently, biofibers are used as a reinforcement in polymer composites for structural elements and construction materials instead of the synthetic fibers which cause environmental problems and are expensive. One of the chemicals with a pH close to neutral that can be potentially used as a modified fiber material is sodium chloride (NaCl). Therefore, this study aims to investigate the characteristics of a composite board made from NaCl-treated kenaf fiber. A completely randomized design method was used with consideration of two factors: the content of NaCl in the treatment solution (1 wt%, 3 wt%, and 5 wt%) and the duration of immersion of fibers in the solution (1 h, 2 h, and 3 h). The NaCl treatment was conducted by soaking the fibers in the solution for different durations. The fibers were then rinsed with water until the pH of the water reached 7 and subsequently dried inside an oven at 80℃ for 6 h. Kenaf fiber and epoxy were mixed manually with the total loading of 20 wt% based on the dry weight of the fiber. Physical and mechanical properties of the fibers were then evaluated based on JIS A 5908 particleboard standards. The results showed that increasing NaCl content in the fiber treatment solution can increase the physical and mechanical properties of the composite board. The properties of fibers treated with 5 wt% NaCl for 3 h were superior with a modulus of elasticity of 2.085 GPa, modulus of rupture of 19.77 MPa, internal bonding of 1.8 MPa, thickness swelling of 3%, and water absorption of 10.9%. The contact angle of untreated kenaf fibers was 104°, which increased to 80° and 73° on treatment with 1 wt% and 5 wt% NaCl for 3 h, respectively.
Kim, Hae-Seon;Park, Nyun-Ho;Suk, Ho-young;You, Sang-guan;Woo, Jung-Hee
Korean Journal of Environmental Agriculture
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v.41
no.1
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pp.50-54
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2022
BACKGROUND: Phyllospadix japonica Makino is a perennial plant belonging to the family Zosteraceae. This species is native to the eastern coast of the Korean Peninsula, and it is found attached to rocks on the seashore. As with all seagrass species, P. japonica is also known to play a major role in protecting the marine environment, and studies on its physiological activities suggestive of its antioxidant, antibacterial and anti-inflammatory potentials have been reported. In this study, purification and structural analysis were performed to identify the polyphenol substances derived from P. japonica. METHODS AND RESULTS: An polyphenol substance MP-1 was purified from the 70% aqueous methanol extract of P. japonica using Diaion® HP-20 column chromatography, ODS column chromatography, and medium-pressure liquid chromatography (MPLC). The purified MP-1 was identified as rosmarinic acid having a molecular weight of 360 and a molecular formula of C18H16O8 through electrospray ionization (ESI)-mass and nuclear magnetic resonance (NMR) spectroscopic analysis. CONCLUSION(S): This study highlights the processes used for the identification of the polyphenol substance derived from P. japonica. Rosmarinic acid, the polyphenol derived from P. japonica identified by this study, is a kind of bioactive substance mainly present in plants. These findings provide an important starting point and are valuable for future studies on bioactive substances in seagrass.
Abdollahi, Mahdieh;Saidi, Ali Reza;Bahaadini, Reza
Structural Engineering and Mechanics
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v.84
no.4
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pp.437-452
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2022
For the first time, the higher-order shear and normal deformable plate theory (HOSNDPT) is used for the vibration and flutter analyses of the multilayer functionally graded graphene platelets reinforced composite (FG-GPLRC) plates under supersonic airflow. For modeling the supersonic airflow, the linear piston theory is adopted. In HOSNDPT, Legendre polynomials are used to approximate the components of the displacement field in the thickness direction. So, all stress and strain components are encountered. Either uniform or three kinds of non-uniform distribution of graphene platelets (GPLs) into polymer matrix are considered. The Young modulus of the FG-GPLRC plate is estimated by the modified Halpin-Tsai model, while the Poisson ratio and mass density are determined by the rule of mixtures. The Hamilton's principle is used to obtain the governing equations of motion and the associated boundary conditions of the plate. For solving the plate's equations of motion, the Galerkin approach is applied. A comparison for the natural frequencies obtained based on the present investigation and those of three-dimensional elasticity theory shows a very good agreement. The flutter boundaries for FG-GPLRC plates based on HOSNDPT are described and the effects of GPL distribution patterns, the geometrical parameters and the weight fraction of GPLs on the flutter frequencies and flutter aerodynamic pressure of the plate are studied in detail. The obtained results show that by increasing 0.5% of GPLs into polymer matrix, the flutter aerodynamic pressure increases approximately 117%, 145%, 166% and 196% for FG-O, FG-A, UD and FG-X distribution patterns, respectively.
Jian-Tao Wang;Yue Wei;Juan Wang;Yu-Wei Li;Qing Sun
Steel and Composite Structures
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v.49
no.4
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pp.441-456
/
2023
Aiming at the development trend of light weight and high strength of engineering structures, this paper experimentally investigated the seismic performance of circular-in-square high-strength concrete-filled double skin steel tubular (HCFDST) stub columns with out-of-code width-to-thickness (B/t) ratios. Typical failure mode of HCFDST stub columns appeared with the infill material crushing, steel fracture and local buckling of outer tubes as well as the inner buckling of inner tubes. Subsequently, the detailed analysis on hysteretic curves, skeleton curves and ductility, energy dissipation, stiffness degradation and lateral force reduction was conducted to reflect the influences of hollow ratios, axial compression ratios and infill types, e.g., increasing hollow ratio from 0.54 to 0.68 and 0.82 made a slight effect on bearing capacity compared to the ductility coefficients; the higher axial compression ratio (e.g., 0.3 versus 0.1) significantly reduced the average bearing capacity and ductility; the HCFDST column SCFST-6 filled with concrete obviously displayed the larger initial secant stiffness with a percentage 34.20% than the column SCFST-2 using engineered cementitious composite (ECC); increasing hollow ratios, axial compression ratios could accelerate the drop speed of stiffness degradation. The out-of-code HCFDST stub columns with reasonable design could behave favorable hysteretic performance. A theoretical model considering the tensile strength effect of ECC was thereafter established and verified to predict the moment-resisting capacity of HCFDST columns using ECC. The reported research on circular-in-square HCFDST stub columns can provide significant references to the structural application and design.
Arbuscular mycorrhizal fungi (AMF) are widespread soil endophytic fungi, forming mutualistic relationships with the vast majority of land plants. Biochar (BC) has been reported to improve soil fertility and promote plant growth. However, limited studies are available concerning the combined effects of AMF and BC on soil community structure and plant growth. In this work, a pot experiment was designed to investigate the effects of AMF and BC on the rhizosphere microbial community of Allium fistulosum L. Using Illumina high-throughput sequencing, we showed that inoculation of AMF and BC had a significant impact on soil microbial community composition, diversity, and versatility. Increases were observed in both plant growth (the plant height by 8.6%, shoot fresh weight by 12.1%) and root morphological traits (average diameter by 20.5%). The phylogenetic tree also showed differences in the fungal community composition in A. fistulosum. In addition, Linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed that 16 biomarkers were detected in the control (CK) and AMF treatment, while only 3 were detected in the AMF + BC treatment. Molecular ecological network analysis showed that the AMF + BC treatment group had a more complex network of fungal communities, as evidenced by higher average connectivity. The functional composition spectrum showed significant differences in the functional distribution of soil microbial communities among different fungal genera. The structural equation model (SEM) confirmed that AMF could improve the microbial multifunctionality by regulating the rhizosphere fungal diversity and soil properties. Our findings provide new information on the effects of AMF and biochar on plants and soil microbial communities.
In the present paper, the effect of recycled aggregates on the rheological and mechanical properties of self-consolidating concrete is investigated experimentally and numerically. Hence, the specimen with two types of recycled aggregates, i.e., known and unknown resistance origins, are utilized for the studied specimens. The experiments in this study are designed using the Box-Behnken method, which is one of the response surface methods. Input variables in mixtures include silica fume in the range of 5-15% as a percentage substitute for cement weight and recycled coarse and fine aggregates in the range of 0-50% for both series of recycled materials as a substitute for natural materials. The studied responses are slump flow, V funnel, compressive strength, tensile strength, and durability. The results indicate that the increase in the amount of recycled aggregates reduces the rheological and mechanical properties of the mixtures, while silica fume effectively improves the mechanical properties. In addition, the results demonstrate that the fine recycled aggregates affect the total response of the concrete significantly. The results of tensile and compressive strengths indicate that the mixtures including 50% recycled materials with known resistance origin demonstrate better responses up to 8 and 10% compared to the materials with unknown resistance origins, respectively. Recycled materials with a specific resistance origin also show better results than recycled materials with an unknown resistance origin. Durability test results represent those concretes containing recycled coarse aggregates have lower strength compared to recycled fine aggregates. Also, a series of mathematical relationships for all the responses are presented using variance analysis to predict mixtures' rheological and mechanical properties.
This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.
Jianhui Hu;Wujun Chen;Chengjun Gao;Yibei Zhang;Yonglin Chen;Pujin Wang
Structural Engineering and Mechanics
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v.90
no.6
/
pp.543-549
/
2024
The utilization of the fabric materials for lightweight building structures has attracted considerable attention due to the multiple functions and high strength-to-weight ratio. The mechanical properties of the fabric materials evolve with the loading cycle, especially for the Poisson's ratio that requires the full cyclic strain to determine the accurate values. The digital image correlation method has been justified but needs to meet the flexibility and complexity requirements of the fabric materials. This paper thus proposes a modified digital image correlation method to quantify the Poisson's ratio of fabric materials. To obtain the accurate Poisson's ratio of fabric materials in the cyclic experiments using non-contact measuring method, a speckle generation of the digital image correlation method is implemented to obtain the strain distribution and strain characteristics. The uniaxial cyclic experiments for the fabric materials are carried out in the warp, weft and 45° directions. The digital image correlation photos are taken when the material properties become stable in the cyclic loading. The results show that the strain distributions are non-uniform and dependent on the specimen directions. The reliable Poisson's ratios of the fabric materials in the warp, weft and 45° directions are 0.016, 1.2 and 2.6. The strain asymmetry at the maximum strain position is related with the weaving architecture. These observations and results are indispensable to understand the Poisson's ratios of fabric materials and to guide the proper analysis of the large-span membrane structures.
An expansive soil in 4970 special railway line in Dangyang City, China, has encountered a series of landslides due to the expansion characteristics of expansive soil over the past 50 years. Thereafter, a sheet-pile retaining structure was adopted to fortify the expansive soil slope after a comprehensive discussion. In order to evaluate the efficacy of engineering measure of sheet-pile retaining structure, the field test was carried out to investigate the lateral pressure and pile bending moment subjected to construction and service conditions, and the local daily rainfall was also recorded. It took more than 500 days to carry out the field investigation, and the general change laws of lateral pressure and pile bending moment versus local daily rainfall were obtained. The results show that the effect of rainfall on the moisture content of backfill behind the wall decreases with depth. The performance of sheet-pile retaining structure is sensitive to the intensity of rainfall. The arching effect is reduced significantly by employing a series of sheet behind piles. The lateral pressure behind the sheet exhibits a single-peak distribution. The turning point of the horizontal swelling pressure distribution is correlated with the self-weight pressure distribution of soil and the variation of soil moisture content. The measured pile bending moment is approximately 44% of the ultimate pile capacity, which indicates that the sheet-pile retaining structure is in a stable service condition with enough safety reserve.
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