Concrete Values Research Articles

Potensi Limbah Fly Ash PLTU Anggrek, Gorontalo Utara sebagai Bahan Substitusi Semen Pada Beton

Accumulation of coal ash waste (fly ash) is a dangerous toxic material (B3) which light and fine so it easily flies in the air. This problem is urgent to be resolved because the production continues to increase in quantity and can cause air and water pollution. Currently, coal waste is used to make bricks, but research needs to be done on its potential as a concrete mixture and even as a cement substitute. Currently, coal waste is used to make bricks, but research necessery on its potential as a concrete mixture and even as a cement substitute. Therefore this research can be an alternative solution to the coal ash waste problem in Gorontalo Province. Research on the use of coal ash as a concrete mixture using crushed stone aggregate and sand from the quarry PT. CMP, Bonda Raya, South Suwawa To obtain a granular distribution that meets the requirements, the proportions used for crushed stone measuring 1-2 cm and measuring 2-3 cm are 65% and 35% respectively. Meanwhile, to obtain a combined gradation of fine and coarse aggregate that meets the requirements, percentages of 55% and 45% are used respectively. Based on the research results, the normal compressive strength value of concrete is 28.827 MPa. The compressive strength of fly ash variations of 5%, 10%, 15%, and 20% is 25,069 MPa, 27,442 MPa, 23,096 MPa, and 20,934 MPa. The compressive strength of fly ash variations is lower than normal concrete. The optimum compressive strength value for fly ash substitution for cement with a 10% variation is 27.442 MPa.

Quantifying Resource Nexus: Virtual Water Flows, Water Stress Indices, and Unsustainable Import Fraction in South Korea’s Grain Trade Landscape

This study delves into the intricate dynamics of South Korea’s grain production and trade, specifically scrutinizing water resource management and sustainability trends from 1991 to 2022. The primary objective was to assess the temporal evolution of South Korea’s agricultural virtual water trade in maize, soybeans and wheat. Employing the virtual water flows assessment method, water stress index, and an unsustainable import fraction (UIF) analysis, this research aimed to uncover key patterns and dynamics within the agricultural grain trade landscape. Utilizing comprehensive datasets encompassing grain trade, as well as water and land footprint data, this study assessed the intricate interplay between agricultural production, trade, and resource utilization. Results showed a reduction in local production for soybeans and a slight increase in domestic wheat production over the study period. In addition, the study revealed an overall increase in the virtual water imports associated with grain crops, with maize exhibiting the steepest upward trend in comparison with the other grains (wheat and soybeans). Furthermore, the study demonstrated that the import of maize contributed the highest amount of water and land savings, implying that this grain crop had the most significant impact on conserving local water and land resources. Environmental impact assessments, including water stress indices and the unsustainable import fractions, contributed to a comprehensive understanding of grain trade sustainability with concrete result values and insights, highlighting the intricate interplay of international grain trade and local water resource conservation in South Korea. By scrutinizing the virtual land and water dimensions of grain trade, this research offers valuable insights for policymakers and researchers striving to navigate the nexus of agriculture, trade, and resource management. The findings hold significance in the context of ensuring food security, optimizing resource allocation, and fostering sustainable agricultural practices in a dynamically evolving global landscape.

The Effect of Fineness Modulus of Fine Aggregate on Concrete Compressive Strength

Concrete is the major material used for most civil engineering constructions like buildings, bridges, culvert, rigid road pavement, dam spillway and so on. Concrete is made from a mixture of cement, fine aggregate (sand), coarse aggregate (granite or gravel), and water. The fineness modulus is one of the physical properties of fine aggregates (sand). The Fineness Modulus (FM) of fine aggregates (sand) is obtained from the grading size distribution test as summation of percentage cumulative retained by series of sieves and divided the sum by 100. The fineness modulus of sand differs for each sand quarry. The purpose of this research is to analyze the effect of fineness modulus of fine aggregate (sand) from three different sand quarries on concrete compressive strength. The sand for the study were taken from three quarries (Ayegun, Akufo and Awotan) in Ibadan, Oyo state, Nigeria. The specimens of concrete used in the form of the cube measuring 150x150x150 mm amounted to 36 specimens. The compressive strength of concrete (fc’) targeted is 21 N/mm2 with W/C ratio 0.5. Concrete mix ratio of 1:2:4 was batched by weight. The results showed that the fineness modulus of sand strongly influence the compressive strength of concrete. The classification of sand type is differentiated based on the results of fineness modulus test on each sand sample. Sand fineness modulus (FM) of Ayegun quarry is 2.64 called medium sand (zone 2). Sand fineness modulus of Akufo quarry is 2.35 called mild sand (zone 3), and, sand fineness modulus of Awotan quarry is 1.57 called fine sand (zone 4). Concrete compressive strength values of Ayegun, Akufo and Awotan quarries sand were 21.3 N/mm2, 22.4 N/mm2, and 20.5 N/mm2, respectively. The value of sand fineness modulus does not affect the increase in the concrete compressive strength. The best classification of fine aggregate to increase concrete compressive strength is mild sand (Akufo quarry) and all the sand samples meet the planned concrete compressive strength of 21 N/mm2.

Fracture toughness determination for epoxy-based polymer concrete mixtures: Applicability of different rectangular beam and circular disc specimens

The purpose of this study was to examine the potential impact of the testing procedure, the shape of the test sample, loading method and sample size on the KIc value of polymer concrete (PC) materials. The research involved experimental investigations using five different testing techniques and specimen types, namely the single edge notched beam (SENB), short bend beam (SBB), semi-circular bend (SCB), edge notch disc bend (ENDB), and center cracked Brazilian disc (CCBD). A typical PC mixture made of mineral silicious aggregate, ML506 epoxy resin, chopped E-glass, and foundry sand filler. Despite the difference in the shape and loading type of the tested samples, the KIc data obtained from all groups of specimens are in good agreement with together and with the SENB proposed by RILEM. Depending on the test type, the KIc value varied from 1.43 to 1.74 MPa.m0.5 and the discrepancy between the data was mainly attributed to the type of loading (compression or bending) and the crack type (center crack or edge crack). The T-stress affects the fracture toughness for different testing samples and configurations. The lowest fracture toughness corresponds to the CCBD specimen (the center cracked disc loaded diametrically). The other test samples with edge cracks and loaded by a three-point bend setup showed KIc = 1.7 - 1.74 MPa.m0.5. Moreover, the fracture toughness data for PC mixtures can be achieved by utilizing sub-sized samples like SBB (for smaller amounts of PC material) instead of larger beam samples (i.e., SENB).

Effect of variations in concrete quality on the crack width in rigid pavement

Cracks pose a significant issue in rigid pavement, leading to substantial damage. The manual mixing and casting of road pavement concrete underscore the importance of concrete quality as a critical parameter. This study investigates crack behavior by varying concrete quality. Loading is performed statically using line loads, shedding light on the impact of concrete quality on crack development. The concrete to be used has a quality fc' of 15 MPa, 25 MPa, and 35 MPa. The fine aggregate used in this study was Lumajang black sand, while the coarse aggregate used was machine crushed stone, and Portland Composite Cement (PCC) was used in all concrete mixes. The reinforcing steel used had a quality fy of 480 MPa, with a reinforcement ratio of ρ=0.010, which was converted to 5-D16 reinforcement. The subgrade density used to support the specimens had a CBR value of 10 %. Specimen dimensions were 2×0.6×0.2 m for length, width, and thickness. Pavement plates, 30 cm thick, were placed on leveled subgrade soil in a steel box set to achieve a 6 % CBR reading. Hydraulic jacks, monitored by a load cell, applied monotonic static loading with 2 kN intervals, reaching a maximum load of 200 kN. Steel tension and plate settlement were measured using a tension sensor and Linear Variable Differential Transformer (LVDT), respectively. A data logger recorded readings, and crack widths were captured by a digital microscope with 0.01 mm accuracy. Experimental results show that low concrete compressive strength values result in larger crack widths, and vice versa. Cracks also occur at earlier loading of concrete quality fc' 15 MPa. In addition, experiments show that the reinforcement stress value has a significant influence on crack width in specimens with low concrete quality

Maximum output discrepancy computation for convolutional neural network compression

Network compression methods minimize the number of network parameters and computation costs while maintaining desired network performance. However, the safety assurance of many compression methods is based on a large amount of experimental data, whereas unforeseen incidents beyond the experiment data may result in unsafe consequences. In this work, we developed a discrepancy computation method for two convolutional neural networks by giving a concrete value to characterize the maximum output difference between the two networks after compression. Using Imagestar-based reachability analysis, we propose a novel method to merge the two networks to compute the difference. We illustrate reachability computation for each layer in the merged network, such as the convolution, max pooling, fully connected, and ReLU layers. We apply our method to a numerical example to prove its correctness. Furthermore, we implement our developed methods on the VGG16 model with the Quantization Aware Training (QAT) compression method; the results show that our approach can efficiently compute the accurate maximum output discrepancy between the original neural network and the compressed neural network.

Inovasi Teknologi Beton Self Compacting Concrete Terhadap Panjang Pengaliran (L-Flow) Dengan Variasi Umur Perawatan Beton

The aim of this research is to analyze the effect of adding hyperplasticizer and retarder on the compressive strength of self-compacting concrete. Fine aggregate and coarse aggregate from the Jenneberang River, Kab. Gowa. The concrete mix design uses a trial and error mix design for self-compacting concrete by making visual observations, so that the physical conditions of the mixture appear to be sufficient to produce a good mix. The stages of this research, by finding a comparison of the slump flow values ​​of the self-compacting Concrete concrete, then making test objects, after that curing the test objects using the water curing method for 28 days, then testing the compressive strength of the self-compacting Concrete concrete to produce comparison to the compressive strength of normal(conventional) concrete. The results of this research show that self-compacting concrete has a compressive strength value of 46.25 Mpa compared to normal concrete of 45.02 Mpa, an increase of 2.73% compared to normal concrete. And the slump value of normal concrete is 8 - 13 cm, while the slump flow of self-compacting concrete is 63 - 84.9 cm, with a time range between 2.53 - 3.46 seconds, able to reach a diameter of 500 mm on the segregation board.

Testing concolic execution through consistency checks

Symbolic execution is a well-known software testing technique that evaluates how a program runs when considering a symbolic input, i.e., an input that can initially assume any concrete value admissible for its data type. The dynamic twist of this technique is dubbed concolic execution and has been demonstrated to be a practical technique for testing even complex real-world programs. Unfortunately, developing concolic engines is hard. Indeed, an engine has to correctly instrument the program to build accurate symbolic expressions, which represent the program computation. Furthermore, to reason over such expressions, it has to interact with an SMT solver. Hence, several implementation bugs may emerge within the different layers of an engine.In this article, we consider the problem of testing concolic engines. In particular, we propose several testing strategies whose main intuition is to exploit the concrete state kept by the executor to identify inconsistencies within the symbolic state. We integrated our strategies into three state-of-the-art concolic executors (SymCC, SymQEMU, and Fuzzolic, respectively) and then performed several experiments to show that our ideas can find bugs in these frameworks. Overall, our approach was able to discover more than 12 bugs across these engines.

Pengaruh Abu Serbuk Kayu Kulim dan Serbuk Tempurung Kelapa terhadap Kuat Tekan Beton

This research combines kulim wood dust and coconut shell powder as a substitute for concrete materials. Ash from kulim sawdust has silicca properties. Meanwhile, coconut shell powder can be mixed in concrete. This study aims to determine the effect of using kulim sawdust ash as a partial substitution of cement and coconut shell powder waste as a partial substitution of fine aggregate on compressive strength and to determine the ideal proportion of the percentage variation of added ingredients. Concrete planning uses an experimental method that refers to SNI 03-2834-2000, SNI 03-1974-1990 and the Unisla Concrete Practicum Guidebook. With a total sample of 12 test objects with the quality plan K-225. The results of the normal concrete compressive strength test with an N code of 19.55 MPa. The results of testing the compressive strength of concrete with added materials with code A1 are 19.29 MPa. The results of testing the compressive strength of concrete with added materials with code B1 are 18.84 Mpa. The results of testing the compressive strength of concrete with added materials with code C1 are 18.46 MPa. Based on the results of the study it was concluded that the added ingredients of kulim wood powder ash and coconut shell powder did not significantly affect the compressive strength of concrete and the higher the added material value the lower the concrete compressive strength value and the lower the added material value, the higher the concrete compressive strength value.

Application of Quantifier Elimination in Epidemiology.

An application of a novel method of a quantifier elimination in epidemiology was presented in this paper. We investigated the existence of the endemic equilibrium for the SEIRS model by QE method and gave a short review of the epidemic prediction models for covid-19. A new method for quantifier elimination for the theory of real closed fields. Obtained value of a reproduction number and endemic equilibrium for the SEIRS model by QEAnalysis of the SEIR model with the concrete values through the example of Severe Acute Respiratory Syndrome (SARS) (a critical value of a transmission rate is evaluated in the example). The main result of this paper is the obtained value of the endemic equilibrium for the SEIRS model (similar result is obtained for the SEIR model). Also, we have analysed the SEIR model through the examle of SARS and we reviewed several epidemic prediction models for covid-19.

Mechanical characterization of fiber-reinforced rubberized recycled concrete

Dumping non-biodegradable wastes, such as construction and demolition waste (CDW) and scrap tires, is causing significant environmental problems. Thus, this study used recycled coarse aggregate (RCA) and crumb rubber (CR) procured from CDW and scrap tires as a partial replacement of natural aggregates. 30% natural coarse aggregate (NCA) was replaced by RCA, and 0, 5, 10 and 15% natural fine aggregate (NFA) was replaced by CR. Besides these, 0.5% polypropylene (PP) fiber was incorporated into the concrete mixtures. Different physical and mechanical properties of rubberized recycled concrete (R2C) and fiber-reinforced rubberized recycled concrete (FR2C) were investigated. Microstructural analysis, chemical analysis, failure modes, and cost-effectiveness were also evaluated. Simplified regression equations have been proposed to predict various mechanical properties of R2C and FR2C mixtures. The inclusion of RCA, CR, and fiber decreased the slump value of the fresh concrete up to 69.7%. The compressive strength decreased with an increase in CR percentage, but it increased by including fiber content. Though all the R2C and FR2C specimens exhibited lower tensile and flexural strength, a marginal reduction was found in FR2C specimens containing up to 5% CR content, which was only 3.3% and 6.8% lesser compared to the control samples. The surface resistivity test revealed that the chloride ion penetrability may be very low for all the combinations of R2C and FR2C specimens. By raising the percentage of CR, the UPV decreased, but the addition of PP fiber slightly increased the value. The cost analysis results pointed out that both the R2C and FR2C combinations saved more energy (up to 2.22 times) and decreased fuel consumption (up to 20.2%). Finally, the present study will aid in advancing sustainable fiber-reinforced rubberized recycled concrete.

"Reduced to Near Nothingness": Don DeLillo's Ethico-Political Project in Cosmopolis

Abstract: A drama of personal failure lies at the heart of Don DeLillo's novel Cosmopolis (2003), as currency trader Eric Packer's misguided strategy of borrowing enormous sums of yen backfires when the currency fails to depreciate. DeLillo treats Packer as a point of contact between the concrete world and abstract value, and Packer desires, accordingly, to become a piece of abstract data. Yet failure undermines Packer's fantasies of abstraction and forces upon him an awareness of his constitutive openness to alterity. It is through Packer's failure that DeLillo weaves into Cosmopolis an ethico-political project that aligns his novelistic art with Emmanuel Levinas's philosophy—a project that plays out on both a narrative and a formal level.

Influence of fine aggregate types for the achievement of concrete quality

Fine aggregates in the form of sand are granulated materials, which generally measure between 0.0625 to 2 millimeters. Sand as a fine aggregate mixed with cement and water becomes a concrete mixture that has a role in the strength of construction. This study aims to determine how much influence the fine aggregates or sand of four different mining sites have on the compressive strength of concrete. The method used is an experiment, based on the results of laboratory tests of compressive strength tests at the age of concrete 7, 14 and 28 days for fc’25 or 25 MPa quality concrete with a mix of designs for fine aggregates from Leles sand, Kuyamut sand, Cikamiri sand, and Cilopang sand, Garut Regency West Java Province Indonesia. The aggregates tested include moisture content, sludge content, organic content, dry saturation, waand ter absorption affects the quality of concrete and improves quality strength with the same treatment for laboratory testing. The results of the analysis with 28 days of concrete compressive strength testing obtained the achievement of the highest concrete strength, namely with Cilopang sand 27 MPa, allowed by Kuyamut sand 26 Mpa, Leles sand 25 MPa and Cikamiri sand 23 MPa. Based on the results of concrete strength testing for up to 28 days, there are three sources of fine aggregates that can reach a minimum of fc’ 25, and there is one sand source that has a compressive strength value of concrete.

AN ALTERNATIVE ARCHITECTURE GRADUATE COURSE CONDUCTED THROUGH DISTANCE EDUCATION AND ITS IMPACTS ON STUDENT LEARNING PROCESS

A multidisciplinary atelier course conducted through distance education in Kocaeli University Faculty of Architecture Graduate Program in 2020/21 Fall Semester is analyzed in this article concerning the impacts of the alternative and versatile methods followed during the course process on student learning achievement. The aim is to reveal the new pedagogical visions and contributions that the methods of this course can provide to student learning and instructor intervention in architecture graduate education. During the course, the stages of determining the workshop groups, discussing the activities with the groups, and developing suggestions, conducting discussions in the distance education environment on the students' study subjects and activity plans, and delivering the final report based on the activity week process and the products obtained were carried out. The required data, including the evidence of actual learning achievement in this course, is derived from a catechetical survey with 12 students who took the course, while the final statements and inferences of the study are based on the achievements and critics of these students about the course. The results obtained from this survey are reciprocally evaluated with the learning achievement targets that are placed in the course syllabus at the beginning of the semester with concrete numerical values to observe the level of achievement of these learning targets. The learning achievements that students gained most apart from the determined learning achievement targets of the course are the development of presentation abilities of students, the provision of exchange of ideas with students from different departments and with the lecturers apart from their thesis advisors, and the possibility of following the processes of different work items. The findings of this study express that the program and the methods of this course can be instructive for implementing new approaches in post-pandemic distance and face-to-face education of architecture in graduate programs.

Assessing the influence of sugarcane bagasse ash for the production of eco-friendly concrete: Experimental and machine learning approaches

The innovative utilization of sugarcane bagasse ash (SCBA) in producing lightweight concrete (LWC) needs to be explored experimentally and quantification with machine learning approaches. Therefore, this study aims to investigate fresh, mechanical and microstructural characteristics and machine learning modeling of incorporating SCBA as a partial substitute of cement. In this investigation, OPC was replaced partially by the weight of SCBA in the proportion of 0 %, 5 %, 10 %, 15 %, and 20 %. The influences of SCBA on the fresh characteristics of concrete were investigated through tests of the slump, compacting factor, Kelly ball, k-slump, density, and air content. In addition, for hardened properties compressive, splitting tensile, flexural strength, and static modulus of elasticity were tested at 7 and 28 days. Furthermore, a microstructural characteristic was carried out for varying content of SCBA. Different machine learning (ML) predictive models were performed utilizing artificial neural network (ANN) and random forest (RF), to predict the fresh and mechanical attributes of the LWC. It was noticed that the workability value of fresh concrete was enhanced almost by 40 % to 50 % with the incorporation of SCBA content. The hardened test results revealed that a mixture having SCBA up to 10 % content SCBA resulted in nearly 10 % to 30 % better performance to satisfy the requirement of LWC. Regarding the sustainability assessment, the less embodied CO2 (eCO2) is produced in SCBA mixes, whereas it is also economically beneficial to produce SCBA mixes. Models' efficacy was evaluated including mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination (R2). The maximum R2 and minimum RMSE came across for RF (0.989 and 1.393, respectively) which provides the well estimation of the model.

Impact of calcium content and pH value on MICP crack healing of geopolymer concrete

In recent years, microbial-induced carbonate precipitation (MICP) is becoming a popular method of soil stabilisation and concrete crack healing. In MICP, calcium is a necessary reactant, and pH value is a crucial factor for living bacteria. Both parameters (i.e., calcium and pH) are adjustable for geopolymer concrete mix design. Given the attractive potential for future applications of geopolymer concrete, understanding the impact of calcium content and pH value of MICP crack healing in geopolymer concrete mix design is of great importance. In this study, it was found that high calcium content in geopolymer concrete mix design is helpful to improve the healing effect. When CaO% in mix design increases from 7.5 % to 18.3 %, the healing degree increases. When Na2O% increases from 4.4 % to 11.6 %, the pH value of geopolymer concrete is improved by around 1, and it was also found that the impact of pH value depends on the way healing is implemented. In the case where bacteria were applied from outside of the healing surface cracks, the effect of pH value was almost negligible. However, when bacteria were used for internal healing, the lower pH value of the geopolymer mix design was beneficial for bacteria to provide a more suitable environment for bacterial activity and thus generate healing products. Therefore, the adjustment of calcium content and pH value in the geopolymer mix design can enhance the effectiveness of MICP crack healing for geopolymer concrete.

Quality and safety aspects of semi-finished meat and chopped by-products made for public consumption

In the current market conditions, quality has become a determining element for satisfying consumer requirements. A special place is occupied by the manufacture of products with high organoleptic characteristics and which have a long sales perspective, without changing the quality of the product. The researches were carried out on semi-finished meat and chopped by-products - Cighiri, ("Homemade Cighiri"), manufactured by two local producers (Sample I and Mostra II) and collected from the consumer network in a refrigerated state. The organoleptic characteristics studied in the samples taken in the study demonstrated qualitative sensory indices, physico-chemical indices evaluated in semi-finished meat products and shredded by-products - Cighiri, presented concrete values and corresponding to the samples of homemade Cighiri taken in the study, the results are compliant and correspond to the requirements regulations in force Government decision 624/2020, for these products. The microbiological parameters determined at homemade Cighiri, taken in the study, demonstrated results that tell us about the absence of pathogenic microorganisms and, also about the sanitation, compliance and safety of meat products made for public consumption.

PENGARUH NILAI SLUMP PADA KUAT TEKAN BETON DENGAN CAMPURAN AIR PAYAU

Concrete is a combination of constituent materials which consists of hydraulic cement (portland cement), coarse aggregate, fine aggregate, water, and additives. Generally, the use of concrete starts from the bottom construction to the top construction. In use in under construction, concrete will be in a variety of environments, one of which is an aggressive environment such as brackish water. This study aims to determine the ratio of the compressive strength of concrete and the split tensile strength of concrete in a mixture of brackish water and the concrete's compressive strength at various slump values (25–50 mm), 75–100 mm), 150–175 mm), and (> 175 mm). This research method uses an experimental research method at the Civil Engineering Laboratory, Faculty of Engineering, Muhammadiyah Parepare, in June–August 2022. The research results obtained show that the brackish water mixture in concrete results in a 10% decrease in the material's compressive strength compared to normal concrete and split tensile strength. The compressive strength of brackish water-mixed concrete with slump variation (75–100) is an average of 2.67 MPa, which is 10.68% of the normal concrete compressive strength value of 25 MPa. The compressive strength of brackish water mixed concrete with slump variation (75–100) is the result of the highest concrete compressive strength compared to other slump variations, and the compressive strength of brackish water mixed concrete with slump variation (> 175) is the lowest in concrete compressive strength results compared to other slump variations.

Variation of dynamic elasticity modulus with experimentally determined concrete compressive strength

In reinforced concrete structures, one of the most important factors for structural safety is the quality of concrete. The first thing that comes to mind for concrete quality is the compressive strength of concrete. However, properties such as elasticity modulus are also among the properties that determine concrete quality. Since concrete is a brittle material, different methods are used to determine dynamic elasticity modulus. In practice, dynamic elasticity modulus of concrete can be identified by utilizing concrete compressive strength value. In this context; compressive strength tests were performed on a series of concretes accordingly relevant standards. Since it is difficult to determine elasticity modulus from the stress and strain relationship, the dynamic elasticity modulus values in this study was calculated using empirical formulas according to TS 500-2000, ACI 318-95 and CEB-FIP 1978 on the basis of experimental data in this study. The relationship between the calculated dynamic elasticity modulus values and concrete compressive strength was analyzed. From the study, it is concluded that as concrete compressive strength increases, dynamic elasticity modulus increases for the concrete specimens.

Interpretable machine learning model for evaluating mechanical properties of concrete made with recycled concrete aggregate

AbstractThe main objective of this paper is to use the data‐driven approach to predict and evaluate the mechanical properties of concrete made with recycled concrete aggregate (RCA), including compressive strength and elastic modulus. Using 358 data samples, including 10 input variables, 10 popular machine learning (ML) algorithms are introduced to select the best ML performance model for predicting RCA concrete's compressive strength and elastic modulus. Gradient Boosting and Categorial Boosting have the best performance in predicting the compressive strength of RCA concrete, with R2 = 0.9112, RMSE = 5.3464 MPa, MAE = 4.0845 MPa, and R2 = 0.9175, RMSE = 5.1520 MPa, MAE = 3.7567 MPa, respectively. Light Gradient Boosting and Categorial Boosting have the best performance in predicting the elastic modulus of RCA concrete, with R2 = 0.8775, RMSE = 2.3560 GPa, MAE = 1.8330 GPa, and R2 = 0.9300, RMSE = 2.3560 MPa, MAE = 1.2589 MPa, respectively. Based on the Shapley Additive Explanation analysis, the influence of main factors on compressive strength and elastic modulus of RCA concrete values has been analyzed qualitatively and quantitatively. RCA replacement level and cement/sand ratio slightly affect compressive strength but have a dominant influence on the elastic modulus of RCA concrete.