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The development of geopolymer concrete offers promising prospects for sustainable construction practices due to its reduced environmental impact compared to conventional Portland cement concrete. However, the complexity involved in geopolymer concrete mix design often poses challenges for engineers and practitioners. In response, this study proposes a simplified approach for designing geopolymer concrete mixtures, drawing upon principles from Portland cement concrete mix design standards and recommended molar ratios of oxides involved in geopolymer synthesis. The proposed methodology aims to streamline the mix design process while optimizing key factors such as chemical composition, alkali activation solution, water content, and curing conditions to achieve desired compressive strength and workability. By leveraging commonalities between Portland cement concrete and geopolymer concrete, this approach seeks to facilitate the adoption of geopolymer concrete in practical construction applications. The proposed mix design guidelines have been validated through examples for concrete cured under different conditions, including outdoor and oven curing. Future research should focus on validating the proposed methodology through experimental studies and exploring cost-effective alternatives for alkali activation solutions to enhance the feasibility and scalability of geopolymer concrete production. Overall, the proposed simplified approach holds promise for advancing the utilization of geopolymer concrete as a sustainable alternative in the construction industry.
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This paper presents a method for designing low carbon bio-based building materials, also named bio-concretes, produced with wood wastes in shavings form (WS) and cementitious pastes. As the aggregates phase of bio-concretes is composed of plant-based particles, known as porous and high water-absorbing materials, the bio-concretes cannot be designed by using the traditional design rules used for conventional mortar or concrete. Then, the method used in the current paper is an adaptation of a previous one that has been developed in a recent paper where bio-concretes were produced with a cement matrix, three types of bio-aggregates, and a proposal of a design abacus. However, when that abacus is used for designing WBC with low cement content in the matrix, the target compressive strength is not reached. In the present paper, the method is extended to low cement content matrix (up to 70% of cement substitution) and also considering the greenhouse gas (GHG) emission of the WBC. To obtain data for proposing a new design abacus, an experimental program was carried out by producing nine workable WBCs, varying wood volumetric fractions (40-45-50%), and water-to-binder ratios. The bio-concretes produced presented adequate consistency, lightness (density between 715 and 1207 kg/m3), and compressive strength ranging from 0.64 to 12.27 MPa. In addition, the GHG emissions of the WBC were analysed through the Life Cycle Assessment methodology. From the relationships obtained between density, compressive strength, water-to-binder ratio, cement consumption, and GHG emissions of the WBC, calibration constants were proposed for developing the updated and more complete abacus regarding an integrated mix design methodology.
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The fight against climate change has delineated new objectives, among which one of the most crucial is the replacement of high-energy-intensity materials in the construction sector with more sustainable and thermally efficient alternatives to reduce indirect emissions. Consequently, the thermal properties of materials assume fundamental importance. In this regard, the large-scale use of earth represents a promising option, not only due to its widespread availability but especially for its minimal embodied energy. However, to enhance its durability, it is necessary to stabilize the mixtures of raw materials. This study analyzes experimental systems based on earth stabilized with bio-based polymers to evaluate their thermal properties and how these vary depending on the selected mix-design. The experimental measurements showed thermal properties comparable to conventional materials. As expected, thermal conductivity increases when porosity decreases. The minimum value is equal to 0.216 W/m·K vs. a porosity of 43.5%, while the maximum is 0.507 W/m·K vs. a porosity of 33.2%. However, the data obtained for individual systems may vary depending on the topological characteristics, which were analyzed through a model for granular materials. The modeling suggests correlations between microstructures and thermal behaviour, which can be useful to develop tools for the mix-design procedure.
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The balanced mix design (BMD) constitutes a significant step forward in the pursuit of better-performing asphalt mixtures. This approach/framework offers increased innovative opportunities for the proper design and production of engineered asphalt mixtures without the need to strictly adhere to traditional volumetric requirements. The primary objective of this paper is to conduct a comprehensive investigation of the permanent deformation (rutting) behavior of surface mixtures (SMs) with conventional and high reclaimed asphalt pavement (HRAP) contents through full-scale accelerated testing under incremental loading conditions while accounting for the environmental aging effect. HRAP SMs were designed in this study, marking the initial application of Virginia Department of Transportation (VDOT) BMD special provisions, with attempts to incorporate 45% and even 60% RAP. Results showed that all BMD HRAP mixtures exhibited higher rut depths compared to the control mixture, which can be attributed to the inclusion of high binder contents aimed at enhancing cracking resistance. The asphalt pavement analyzer (APA) rut test and the stress sweep rutting tests were performed on mixtures sampled during production. Correlation analysis revealed significant and strong positive correlations between accelerated pavement testing (APT) and the multilevel laboratory rutting performance tests considered in this study. Finally, while acknowledging the limitations and all the assumptions considered in this study, the correlation analysis recommended refining the VDOT BMD APA rut depth threshold by lowering the current limit of 8 mm to 7 mm to ensure good performing mixtures from a rutting point of view.
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This study addresses a critical gap in concrete strength prediction by conducting a comparative analysis of three deep learning algorithms: convolutional neural networks (CNNs), gated recurrent units (GRUs), and long short-term memory (LSTM) networks. Unlike previous studies that employed various machine learning algorithms on diverse concrete types, our study focuses on mixed-design concrete and fine-tuned deep learning algorithms. The objective is to identify the optimal deep learning (DL) algorithm for predicting concrete uniaxial compressive strength, a crucial parameter in construction and structural engineering. The dataset comprises experimental records for mixed-design concrete, and models were developed and optimized for predictive accuracy. The results show that the CNN model consistently outperformed GRU and LSTM. Hyperparameter tuning and regularization techniques further improved model performance. This research offers practical solutions for material property prediction in the construction industry, potentially reducing resource burdens and enhancing efficiency and construction quality.
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Concrete mixture design has been a key focus in concrete research. This study presents a new method for concrete mixture design by combining artificial neural networks (ANN), genetic algorithms (GA), and Scipy libraries for hybrid intelligent modeling. This method enables the prediction of concrete mechanical properties and the optimization of mix proportions with single or multi-objective goals. The GA is used to optimize the structure and weight parameters of ANN to improve prediction accuracy and generalization ability (R2 > 0.95, RMSE and MAE < 10). Then, the Scipy library combined with GA-ANN is used for the multi-objective optimization of concrete mix proportions to balance the compressive strength and costs of concrete. Moreover, an AI-based concrete mix proportion design system is developed, utilizing a user-friendly GUI to meet specific strength requirements and adapt to practical needs. This system enhances optimization design capabilities and sets the stage for future advancements. Overall, this study focuses on optimizing concrete mixture design using hybrid intelligent modeling and multi-objective optimization, which contributes to providing a novel and practical solution for improving the efficiency and accuracy of concrete mixture design in the construction industry.
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The design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering and difficulty predicting concrete properties. Machine learning-based methods offer a solution, as they have proven effective in predicting concrete compressive strength for concrete mix design. This paper scrutinises the association between the computational complexity of machine learning models and their proficiency in predicting the compressive strength of concrete. This study evaluates five deep neural network models of varying computational complexity in three series. Each model is trained and tested in three series with a vast database of concrete mix recipes and associated destructive tests. The findings suggest a positive correlation between increased computational complexity and the model's predictive ability. This correlation is evidenced by an increment in the coefficient of determination (R2) and a decrease in error metrics (mean squared error, Minkowski error, normalized squared error, root mean squared error, and sum squared error) as the complexity of the model increases. The research findings provide valuable insights for increasing the performance of concrete technical feature prediction models while acknowledging this study's limitations and suggesting potential future research directions. This research paves the way for further refinement of AI-driven methods in concrete mix design, enhancing the efficiency and precision of the concrete mix design process.
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This research paper systematically investigates the combined influence of fly ash, cementitious capillary crystalline waterproofing (CCCW) materials, and polypropylene fibers on the mechanical properties and impermeability of concrete through comprehensive orthogonal tests. Microscopic morphological changes in the concrete induced by different composite materials are examined via scanning electron microscopy (SEM) and X-ray diffraction (XRD) testing. The objective is to facilitate a beneficial synergetic interaction among these materials to develop highly permeable, crack-resistant concrete. Key findings of this study are: (1) The study unveils the impact of the concentration of three additive materials on the concrete's compressive strength, tensile strength, and penetration height, thereby outlining their significant influence on the mechanical properties and impermeability of the concrete; (2) An integrated scoring method determined the optimal composite dosage of three materials: 15% fly ash, 2% CCCW, and polypropylene fibers at 1.5 kg/m3. This combination increased the concrete's compressive strength by 12.5%, tensile strength by 48.4%, and decreased the average permeability height by 63.6%; (3) The collective introduction of these three materials notably augments the hydration reaction of the cement, resulting in denser concrete microstructure, enhanced bonding between fibers and matrix, and improved concrete strength and durability.
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Traditional methods for designing concrete mixtures provide good results; however, they do not guarantee the optimum composition. Consequently, applying operational research techniques is motivated by an increasing need for designers to proportion the concrete's raw materials that satisfy the concrete performance requirements such as mechanical properties, chemical properties, workability, sustainability, and cost. For this reason, many authors have been looking for mathematical programming and machine learning solutions to predict concrete mix properties and optimise concrete mixtures. Therefore, a comprehensive review of operational research techniques concerning the design and proportioning of concrete mixtures and a classification framework are presented herein.
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The decrease in the quality of recycled aggregate due to an increase in the number of recycling is a primary factor that limits the multi-recycling of concrete. This degradation adversely affects concrete performance; thus, the characteristics of recycled aggregate should be considered during the mix design stage, but little research has taken that into account. This study investigates the effect of the equivalent mortar volume (EMV) mix design on some physical, mechanical and durability properties of concrete made of multiple recycled coarse aggregates at 50% and 100% replacement ratios compared to concrete made by the conventional mix design (CMD). The results showed that the performances of concrete by the CMD decreased with an increasing number of recycling cycles. The properties of EMV-based concrete deteriorated with an increase in the number of recycling cycles at 100% replacement ratio due to poor workability caused by a shortage of fresh mortar. However, at 50% replacement, the EMV-based concrete exhibited similar performance across the three cycles of recycling, as well as improved properties over natural aggregate concrete. This study demonstrated that an appropriate mix design and optimal aggregate replacement ratio can offset the property loss of multiple recycled aggregate concrete.
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This paper proposes a performance-based mix design (PBMD) framework to support performance-related specifications (PRS) needed to establish relationships between acceptable quality characteristics (AQCs) and predicted performance, as well as to develop fatigue-preferred, rutting-preferred, and performance-balanced mix designs. The framework includes defining performance tests and threshold values, developing asphalt mix designs, identifying available performance levels, conducting sensitivity analysis, establishing the relationships between AQCs and predicted performance, and determining performance targets and AQC values for the three PBMDs using predicted performance criteria. Additionally, the framework recommends selecting the PBMD category for each asphalt layer to minimize pavement distresses. In this study, the proposed PBMD protocol was applied to FHWA accelerated loading facility (ALF) materials using asphalt mixture performance tester (AMPT) equipment coupled with mechanistic models. The study developed nine mix designs with varying design VMAs and air voids using the Bailey method. The cracking and rutting performance of the mix designs were determined by direct tension cyclic (DTC) fatigue testing, triaxial stress sweep (TSS) testing, and viscoelastic continuum damage (S-VECD) and viscoplastic shift models for temperature and stress effects. The study found that adjusting the design VMA was the primary way to achieve required performance targets. For fatigue-preferred mix design, the recommended targets were a cracking area of 0 to 1.9%, a rut depth of 10 mm, and a design VMA of 14.6 to 17.6%. For rutting-preferred mix design, the recommended targets were a cracking area of 18%, a rut depth of 0 to 3.8 mm, and a design VMA of 10.1 to 13.1%. For performance-balanced mix design, the recommended targets were a cracking area of 8.1 to 10.7%, a rut depth of 4.6 to 6.4 mm, and a design VMA of 12.6 to 14.3%. Finally, pavement simulation results verified that the proposed PBMD pavement design with fatigue-preferred mix in the bottom layer, performance-balanced mix in the intermediate layer, and rutting-preferred mix in the surface mix could minimize bottom-up cracking propagation without exceeding the proposed rutting performance criterion for long-life.
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At present, achieving good storability and water damage resistance remains challenging for cold-patching asphalt mixtures (CAMs). To address this issue, this study selects styrene-ethylene-butadiene-styrene copolymer (SEBS) and diesel as a modifier and diluent, respectively, to improve the water stability and storability of CAMs. The diesel oil content is determined through the Brookfield rotational viscosity test, and the modifier content is obtained through the Marshall stability test. With the empirical formula method, paper trail test, and modified Marshall test, mixed designs of CAMs modified with and without SEBS are established to determine the best cold-patching asphalt content. On this basis, the modification effect of SEBS is verified by comparing the test results of the modified and unmodified CAMs, and the water stability and Marshall stability tests are conducted before and after CAM storage, respectively. Results show that the optimum contents of SEBS and diesel oil are 7.5% and 40% of the base asphalt weight, respectively, and the best modified asphalt content is 4.6% of the mineral material weight in CAM. The Marshall residual stability and freeze-thaw splitting strength ratio of the 7.5% SEBS-modified CAM are increased by 20.1% and 15.7%, respectively, relative to the unmodified CAM, and the storage performance requirement of at least two months can be guaranteed.
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Alkali-activated materials (AAM) are recognized as potential alternatives to ordinary Portland cement (OPC) to limit CO2 emissions and beneficiate several wastes into useful products. Compared with its counterparts involving the concentrated aqueous alkali solutions, the development of "just add water" one-part alkali-activated materials (OP-AAM) has drawn much attention, mainly attributed to their benefits in overcoming the hazardous, irritating, and corrosive nature of activator solutions. This study starts with a comprehensive overview of the OP-AAM; 89 published studies reported on mortar or concrete with OP-AAM were collected and concluded in this paper. Comprehensive comparisons and discussions were conducted on raw materials, preparation, working performance, mechanical properties, and durability, and so on. Moreover, an in-depth comparison of different material pretreatment methods, fiber types, and curing methods was presented, and their potential mechanisms were discussed. It is found that ground granulated blast-furnace slag (GGBS) provides the best mechanical properties, and the reuse of most aluminosilicate materials can improve the utilization efficiency of solid waste. The curing temperature can be improved significantly for precursor materials with low calcium contents. In order to overcome the brittleness of the AAM, fiber reinforcement might be an efficient way, and steel fiber has the best chemical stability. It is not recommended to use synthetic fiber with poor chemical stability. Based on the analysis of current limitations, both the recommendations and perspectives are laid down to be the lighthouse for further research.
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Geopolymer (GP) concrete is a novel construction material that can be used in place of traditional Portland cement (PC) concrete to reduce greenhouse gas emissions and effectively manage industrial waste. Fly ash (FA) has long been utilized as a key constituent in GPs, and GP technology provides an environmentally benign alternative to FA utilization. As a result, a thorough examination of GP concrete manufactured using FA as a precursor (FA-GP concrete) and employed as a replacement for conventional concrete has become crucial. According to the findings of current investigations, FA-GP concrete has equal or superior mechanical and physical characteristics compared to PC concrete. This article reviews the clean production, mix design, compressive strength (CS), and microstructure (Ms) analyses of the FA-GP concrete to collect and publish the most recent information and data on FA-GP concrete. In addition, this paper shall attempt to develop a comprehensive database based on the previous research study that expounds on the impact of substantial aspects such as physio-chemical characteristics of precursors, mixes, curing, additives, and chemical activation on the CS of FA-GP concrete. The purpose of this work is to give viewers a greater knowledge of the consequences and uses of using FA as a precursor to making effective GP concrete.
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Long-term deterioration and durability concerns in harsh environments with acidic attacks are considered as the weaknesses of ordinary Portland cement (OPC) concrete. Although the performance of alkali-activated slag concrete (AASC) has been reported to be superior in acidic environments, there is a poor understanding regarding the impacts of diverse mix design parameters on AASC durability in an acidic environment. This research aims to understand the impact of mix design parameters on the durability of AASC in the sulfuric acid (H2SO4) environment with pH = 3. The type of alkaline solution, the molarity of alkaline solutions, the weight ratio of alkaline solutions to slag, and the weight ratio of NaOH to Na2SiO3 are mix design parameters investigated in this study. The compressive strength reduction and weight loss were monitored from early ages up to 180 days. Moreover, an OPC concrete sample was produced as a reference.
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This study investigates the effects of two waste materials from construction and industry, namely recycled concrete aggregate (RCA) and Type C fly ash, on the overall performance of a special type of pavement surface mixture, porous asphalt mixture. Mixtures of different combinations of RCA (for partial aggregate replacement) and fly ash (for filler replacement) were prepared in the laboratory and tested for a variety of pavement surface performance parameters, including air-void content, permeability, Marshall stability, indirect tensile strength, moisture susceptibility, Cantabro loss, macrotexture, and sound absorption. The analysis of the results showed that incorporating RCA or fly ash in a porous asphalt mixture slightly reduced the air-void content, permeability, and surface macrotexture of the mixture. A 10% replacement of granite aggregates with RCA in the porous asphalt mixtures led to a reduction in mixture stability, indirect tensile strength, resistance to raveling, and sound absorption. The further substitution of mineral filler with fly ash in the mixture, however, helped to offset the negative impact of RCA and brought the mechanical properties of the mixture with 10% RCA to levels comparable to those of the control mixture.
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The interaction between compositional ratios, namely, SiO2/Al2O3, Na2O/Al2O3, H2O/Na2O and the liquid-to-solid ratio, triggers mutual sacrifice between workability, setting time and strength for N-A-S-H geopolymers. The present study characterizes the mechanism underlying the effect of these compositional ratios and, in turn, develops guidelines for mixture design that requires a simultaneous and satisfactory delivery of these engineering properties. The experimental results show that an increase in either the SiO2/Al2O3, Na2O/Al2O3 or H2O/Na2O ratio raises the liquid-to-solid ratio, which in turn improves the workability of fresh mixtures. A continuous increase beyond 2.8 for the SiO2/Al2O3 ratio boosts its strength, but also significantly extends its final set. Lowering the Na2O/Al2O3 ratio from 1.3 to 0.75 raises the compressive strength significantly, while the shortest final set was seen at the median value, 1.0. A H2O/Na2O ratio of 9~10 yields the highest strength and the fastest final set simultaneously, due to the maximized degree of geopolymerization. Moreover, the accompanying sensitivity analysis indicates that the workability depends chiefly upon the H2O/Na2O ratio, the final setting time on the SiO2/Al2O3 ratio and, that the compressive strength relies on both of them. Also, this study proposes an optimal range of 2.8~3.6 for SiO2/Al2O3, 0.75~1.0 for Na2O/Al2O3 and 9~10 for H2O/Na2O to guarantee high strength, together with high flow and within the allowable final setting time. Furthermore, multi-factor predictive models are established with acceptable accuracy for practitioners to regulate oxide compositions in N-A-S-H geopolymers, which will guide future mixture design.
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The global desire to improve the performance of road pavements and move towards a sustainable transportation system has immensely encouraged the usage of fibers in asphalt paving materials. In this study, glass fibers trademarked as ESGFIBER produced by the ESG Industry company Limited from Daejeon, Korea were added in dense-graded asphalt mix. The purpose of this study was to evaluate effects that fibers have on volumetric properties, mechanical properties, and long-term performance of asphalt concrete mixes. ESGFIBER were mixed together with aggregates and asphalt binder in asphalt mix and five different asphalt mixes with different dosage of fibers were evaluated in this study. The Marshall mix design method was used for designing all asphalt mixes, and laboratory tests indirect tensile strength test, deformation strength test and Hamburg wheel tracking test were conducted to evaluate moisture susceptibility, fatigue cracking behavior and rutting resistance of asphalt concrete mixes. The results showed that when ESGFIBER were added in asphalt mix moisture susceptibility, fatigue cracking and rutting resistance were both improved. The usage of ESGFIBER in asphalt concrete mixes can be very beneficial since the mechanical and long-term performance were improved upon the addition of fibers.
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In recent years, due to the advent of several additives and innovations, asphalt mix design has become more complex. The mixes meeting the volumetric mix design requirements may still fail prematurely in the field. Thus, a transition from a simplistic volumetric-based mix design to a performance-based mix design is required, which was also envisioned in the Strategic Highway Research Program (SHRP) and Superpave mix design. In addition to performance verification, asphalt mix designs should also be evaluated for the life-cycle costs and environmental impact to encourage durable as well as sustainable and cost-effective alternatives. In this study, three asphalt mixtures with different reclaimed asphalt pavement (RAP) contents and additives were evaluated for cracking and rutting performance by using different performance thresholds for asphalt mixtures that are generally used in the construction of high-volume roads in Oregon. A balanced mix design process was followed to determine the required binder content for the three mixtures. Based on the life cycle cost and environmental impact analyses, the mixture with warm mix additive (WMA) was selected as the most economically and environmentally viable asphalt mixture to be used for construction in Oregon.