Experimental Study on the Mechanics and Impact Resistance of Multiphase Lightweight Aggregate Concrete

Meng, Jian; Xu, Ziling; Liu, Zeli; Chen, Song; Wang, Chen; Zhao, Ben Y.; Zhou, Anning

doi:10.3390/su14159606

Cited by 8 publications

(6 citation statements)

References 31 publications

(32 reference statements)

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“…This phase is characterized by a steeper damage curve, indicating a considerable increase in damage to the cement mortar. Eventually, as D(N) reaches 1, the curve tends to smooth, indicating complete destruction of the cement mortar [45,62,63]. ) . ]…”

Section: Impact Damage Analysismentioning

confidence: 99%

“…The Swedish physicist Waloddi Weibull first proposed the Weibull distribution model in 1939, which is widely used in reliability assessment research on engineering materials as a data processing method for life tests [42][43][44][45]. Tingting Zhang et al [46] used a two-parameter Weibull model to study the effect of high-performance polypropylene fibers on the impact resistance of recycled aggregate concrete.…”

Section: Introductionmentioning

confidence: 99%

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Experimental Study on the Durability Performance of Sustainable Mortar with Partial Replacement of Natural Aggregates by Fiber-Reinforced Agricultural Waste Walnut Shells

Peng,

Qiu,

Yang

et al. 2024

Sustainability

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Through the recovery and reuse of agricultural waste, the extraction and consumption of natural aggregates can be reduced to realize the sustainable development of the construction industry. Therefore, this paper utilizes the inexpensive, surplus, clean, and environmentally friendly waste agricultural material walnut shell to partially replace the fine aggregates in mortar to prepare environmentally friendly mortar. Considering the decrease in mortar performance after mixing walnut shells, basalt fibers of different lengths (3 mm, 6 mm, and 9 mm) and different dosages (0.1%, 0.2%, and 0.3%) were mixed in the mortar. The reinforcing effect of basalt fibers on walnut shell mortar was investigated by mechanical property tests, impact resistance tests, and freeze–thaw cycle tests. The damage prediction model was established based on the Weibull model and gray model (GM (1,1) model), and the model accuracy was analyzed. The experimental results showed that after adding basalt fibers, the compressive strength, split tensile strength, and flexural strength of the specimens with a length of 6 mm and a doping amount of 0.2% increased by 13.98%, 48.15%, and 43.75%, respectively, and the fibers effectively improved the defects inside the walnut shell mortar. The R²s in the Weibull model were greater than 87.38%, and the average relative error between the predicted life of the impacts and the measured values was greater than 87.38%. The average relative errors in the GM (1,1) model ranged from 0.81% to 2.19%, and the accuracy analyses were all of the first order.

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Section: Impact Damage Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Durability Performance of Sustainable Mortar with Partial Replacement of Natural Aggregates by Fiber-Reinforced Agricultural Waste Walnut Shells

Peng,

Qiu,

Yang

et al. 2024

Sustainability

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“…Element killing algorithm (*MAT_ADD_EROSION) in LS-DYNA is used to simulate the damage of bridge piers impacted by rockfalls [22]. To make the FE simulation result close to the actual impact result, the maximum principal strain of 0.1 is set as the condition of mesh killing.…”

Section: Damage Characteristicmentioning

confidence: 99%

Durability Assessment Method of Hollow Thin-Walled Bridge Piers under Rockfall Impact Based on Damage Response Surface

Li¹,

Liu²,

Yang³

2022

Preprint

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Continuous rigid frame bridges across valleys are often at the risk of rockfalls caused by heavy rainfalls, earthquakes and debris flows in a mountainous country. Hollow thin-walled bridge piers (HTWBP) in valleys are exposed to the threat of the impact of accidental rockfalls. In the current research, ANSYS/LS-DYNA is used to establish a high-precision rockfall-HTWBP model. The rockfall-HTWBP model is verified against a scaled impact test of a previous research. A mesh independence test is also performed to obtained an appropriate mesh size. Based on the rockfall-HTWBP model, the impact force, damage and dynamic response characteristics of HTWBP under the rockfall impact are studied. In addition, a damage assessment criteria is proposed based on the response surface model combined with Central Composite Design method and Box-Behnken Design method. The main conclusions are as follows: 1）The impact force of rockfall has a substantial impulse characteristic, and the duration of the impulse load is approximately 0.01s. 2）The impacted surface of the pier is dominated by the final elliptic damage with the conical and strip damage areas as the symmetry axis. The cross-sectional damage mode is compression failure in the impact area and shear failure at the corner. 3）The maximum displacement occurs in the middle height of the pier. The maximum displacement increases with impact height, impact velocity and rockfall diameter and decreases with the uniaxial compressive strength of the concrete. 4) The initial impact velocity and diameter of the rockfall are the most significant parameters affecting the damage indices. In addition, a damage assessment method with a damage zoning diagram based on the response surface method is established for the fast assessment of the damage level of impacted HTWBP.

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“…Moving towards sustainable structures is the goal of all civilizations worldwide, which is being investigated by many researchers. Thus, many research studies seek to improve the current construction materials and develop new sustainable ones, particularly lightweight concrete [1][2][3][4][5][6][7]. The failure of concrete elements in shear is brittle, which could result in a catastrophic disaster.…”

Section: Introductionmentioning

confidence: 99%

“…After the first onset of cracking, stress distribution becomes complex while being affected by a combination of several parameters and mechanisms. In the late '90s, the ASCE-ACI Committee 445 reported significant shear transfer mechanisms as follows: (1) shear in the uncracked compression zone of the element; (2) shear in the cracking interface due to aggregate interlock as well as the surface roughness along inclined cracks; (3) dowel action of the longitudinal reinforcement; (4) residual tensile stresses across inclined cracks; and (5) arch mechanism.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Shear Strength of Light-Weight and Normal-Weight Concretes through Artificial Intelligence

2022

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The strength of concrete elements under shear is a complex phenomenon, which is induced by several effective variables and governing mechanisms. Thus, each parameter’s importance depends on the values of the effective parameters and the governing mechanism. In addition, the new concrete types, including lightweight concrete and fibered concrete, add to the complexity, which is why machine learning (ML) techniques are ideal to simulate this behavior due to their ability to handle fuzzy, inaccurate, and even incomplete data. Thus, this study aims to predict the shear strength of both normal-weight and light-weight concrete beams using three well-known machine learning approaches, namely evolutionary polynomial regression (EPR), artificial neural network (ANN) and genetic programming (GP). The methodology started with collecting a dataset of about 1700 shear test results and dividing it into training and testing subsets. Then, the three considered (ML) approaches were trained using the training subset to develop three predictive models. The prediction accuracy of each developed model was evaluated using the testing subset. Finally, the accuracies of the developed models were compared with the current international design codes (ACI, EC2 & JSCE) to evaluate the success of this research in terms of enhancing the prediction accuracy. The results showed that the prediction accuracies of the developed models were 68%, 83% & 76.5% for GP, ANN & EPR, respectively, and 56%, 40% & 62% for ACI, EC2 & JSCE, in that order. Hence, the results indicated that the accuracy of the worst (ML) model is better than those of design codes, and the ANN model is the most accurate one.

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Experimental Study on the Mechanics and Impact Resistance of Multiphase Lightweight Aggregate Concrete

Cited by 8 publications

References 31 publications

Experimental Study on the Durability Performance of Sustainable Mortar with Partial Replacement of Natural Aggregates by Fiber-Reinforced Agricultural Waste Walnut Shells

Experimental Study on the Durability Performance of Sustainable Mortar with Partial Replacement of Natural Aggregates by Fiber-Reinforced Agricultural Waste Walnut Shells

Durability Assessment Method of Hollow Thin-Walled Bridge Piers under Rockfall Impact Based on Damage Response Surface

Evaluating Shear Strength of Light-Weight and Normal-Weight Concretes through Artificial Intelligence

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