Experimental Study on Bearing Capacity of Alkaline Activated Granular Asphalt Concrete Columns on Soft Soils

At present, the research work on recycled concrete is still relatively slow and backward, and many problems are not studied in detail enough. It only stays at the material level, and there is no in-depth research on the performance of recycled concrete structures. The purpose of this paper is to study the automatic testing system of ceramsite concrete bearing capacity based on genetic algorithm. A prediction model for the flexural and shear resistance of RC beams after high temperature, and the bearing capacity of RC columns after high temperature, based on BP neural network and GA-BP neural network, was established to prove the effectiveness and efficiency of the automatic test system based on ceramsite concrete bearing capacity accuracy. The overall structure of the system is analyzed, and the following conclusions are obtained: Compared with the BP neural network prediction model, the flexural and shear bearing capacity of the RC beam based on the GA-BP neural network after high temperature and the axial compression of the RC column after high temperature are analyzed. The relative error, absolute error, average error and root mean square of the predicted data obtained by the bias bearing capacity prediction model and the theoretical calculation value are smaller.

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“…The building block hypothesis suggests that genetic algorithms can find the best solution in the world 13,14 .…”

Section: Research On the Methods Of Bearing Capacity Automatic Test S...mentioning

confidence: 99%

Automatic testing system for ceramsite concrete bearing capacity based on genetic algorithm

Liu

Xue

Zhao

et al. 2023

International Conference on Computer Application and Information Security (ICCAIS 2022)

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“…Soil stabilization must be done both physically and chemically to raise the mechanical strength of the soil. Another type of mechanical soil enhancement is stone columns [9]. In addition to employing plant medium, slope erosion may be controlled with a versatile kind of slope protection known as riprap structures.…”

Section: Introductionmentioning

confidence: 99%

Slope Reinforcement Model Scale Test With X-Block

et al. 2022

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This study aims to determine the material composition and dimensions of X-block, develop a slope reinforcement model using X-block, evaluate the mechanical behavior of slopes that are reinforced with rock-bound by X-block, and analyze the performance of slope reinforcement using X-block. This research was conducted at Hasanuddin University's soil mechanics and civil engineering structure laboratory. The model scale test was employed in this study. The geometrical speciation of the test box is 150 cm in length, 60 cm in width, and 100 cm in height. The X-block model was produced using concrete with a FC of 25 MPa. The X-block was divided into two types: X-block type 1 and X-block type 2. Tensile strength testing is performed on the X-block. The slopes are made of clay soil and have a slope angle of 70 degrees. The loading test was conducted in three stages: without block, with X-block type 1, and with X-block type 2. The loading test uses a hydraulic pump equipped with a load cell and LVDT. The tensile strength of X-block type 1 is 2.56 MPa, whereas X-block type 2 has a tensile strength of 4.35 MPa. The development of the type X-block design, which is used as a retaining wall material, has shown that it can effectively withstand landslides on the slopes under consideration. The slope safety factor rose dramatically after being reinforced with type X-blocks, reaching 2.73 for both X-block type 1 and X-block type 2. Doi: 10.28991/CEJ-2022-08-03-014 Full Text: PDF

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“…To meet the aggregate needs in an area by bringing in the aggregate from other places which of course will increase the unit price of road construction costs [12,13]. To overcome this, it is necessary to carry out technical engineering in the use of materials so that local substandard materials or industrial waste materials can be optimized for use on road pavements, both in asphalt mixtures and for road foundation layers [14,15].…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Asphalt Mixed Using Mountain Stone

et al. 2021

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Aggregate is the main thing in asphalt mixtures with a percentage of about 70% to 80%. The aggregate used should meet the Indonesian National Standard (SNI) before being used in the asphalt mixture. East Kalimantan Province is one of the provinces in Indonesia which always brings in aggregates from outside the region for road construction. This study aims to analyze the modulus of stiffness of the AC-WC mixture using local aggregate of East Kalimantan Province and petroleum bitumen grade 60/70 as a binder due to water immersion. This research is experimental in the laboratory. The variation of the petroleum bitumen content used was 4.5, 5.0, 5.5, 6.0 and 6.5%. Water immersion was carried out at the age of 3, 5 and 7 days. The results showed that at 3 days of immersion, the resilient modulus values obtained at petroleum bitumen content of 4.5, 5.0, 5.5, 6.0 and 6.5% were 421.0, 506.0, 872.5, 747.0 and 648.5 MPa, respectively. At 5 days immersion, the resilient modulus values obtained were 383.5, 386.0, 915.5, 561.0 and 555.5 MPa, respectively. Whereas for the 7 days immersion, the resilient modulus were 290.5, 425.5, 1369.0, 547.5 and 525.0 MPa, respectively. It can be seen that water immersion greatly affects the stiffness modulus of the asphalt mixture. This stiffness will cause the asphalt mixture to be easily damaged or cracked. This can be caused by the influence of the sub-standard aggregates used, namely Senoni stone and Mahakam sand. Doi: 10.28991/cej-2021-03091652 Full Text: PDF

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Experimental Study on Bearing Capacity of Alkaline Activated Granular Asphalt Concrete Columns on Soft Soils

Cited by 9 publications

References 17 publications

Automatic testing system for ceramsite concrete bearing capacity based on genetic algorithm

Automatic testing system for ceramsite concrete bearing capacity based on genetic algorithm

Slope Reinforcement Model Scale Test With X-Block

Characteristics of Asphalt Mixed Using Mountain Stone

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