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Formulating a mix design for 3D concrete printing (3DCP) is challenging, as it involves an iterative approach, wasting a lot of resources, time, and effort to optimize the mix for strength and printability. A potential solution is mix formulation through artificial intelligence (AI); however, being a new and emerging field, the open-source availability of datasets is limited. Limited datasets significantly restrict the predictive performance of machine learning (ML) models. This research explores data augmentation techniques like deep generative adversarial network (DGAN) and bootstrap resampling (BR) to increase the available data to train three ML models, namely support vector machine (SVM), artificial neural network (ANN), and extreme gradient boosting regression (XGBoost). Their performance was evaluated using R2, MSE, RMSE, and MAE metrics. Models trained on BR-augmented data showed higher accuracy than those trained on the DGAN-augmented data. The BR-trained XGBoost exhibited the highest R2 scores of 0.982, 0.970, 0.972, 0.971, and 0.980 for cast compressive strength, printed compressive strength direction 1, 2, 3, and slump flow respectively. The proposed method of predicting the slump flow (mm), cast, and anisotropic compressive strength (MPa) can effectively predict the mix design for printable concrete, unlocking its full potential for application in the construction industry. [ABSTRACT FROM AUTHOR]

Copyright of Transportation Science & Technolgy is the property of Transportation Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To solve the problem of the proportional design of cement concrete prepared by using manufactured sand instead of river sand, a new method of manufactured sand concrete mix design was proposed with the dense packing of coarse and fine aggregate. Compared with the original sieving method, the stone powder in the manufactured sand can be regarded as cementitious materials for slurry. With the proposed mix design method, there is no need to separate from the manufactured sand. This dense packing method considers the actual situation that both the manufactured sand and coarse aggregate are mechanically prepared, and all the aggregates can be unified in proportion. The composition ratio of aggregate with particle size greater than 0.075 mm is designed by the maximum density theory, and the rest of the part (below 0.075 mm) is treated as a cementitious material. As a parameter of the maximum density theory, the Fuller index of 0.45 was verified when the calculation values agreed well with the test results. With the proposed mix ratio design method, the different grades C30, C40, and C50 of manufactured sand concrete were designed. Furthermore, the properties such as workability and mechanical properties for the designed manufactured sand concrete were investigated to determine the applicability of the proposed mix design method. The test results show that the workability, uniformity, and strength of the manufactured sand concrete were better than the original mix ratio design method, which verifies the operability and reasonableness of the proposed mix ratio design method. [ABSTRACT FROM AUTHOR]

The interval of time after pouring concrete is an important factor, which directly affects the timing and cost of construction. The case study that was investigated in this research, is a tunnel project located in Iran. Eighteen mix designs were prepared using properties such as different water-cement ratios and the use of two types of superplasticizer with different dosages. The optimal mix designs among the samples were separately specified.

The research focuses on optimising the mix design of ultra high-performance geopolymer mortar by employing the Taguchi method’s orthogonal array parameters through a systematic experimental approach. Utilising an L9 orthogonal array, the investigation was structured into two phases, each examining a distinct set of variables across three levels to ascertain their impact on compressive strength. The optimal mix was characterised by a water to binder ratio of 0.28, a fibre volume of 3%, a silicon carbide to binder ratio of 0, and a superplasticizer to binder ratio of 2%. This mix achieved 126 MPa of compressive strength. [ABSTRACT FROM AUTHOR]

This study presents the development and validation of a mix design determination procedure for geopolymer concrete to achieve the desired compressive strength. The procedure integrates artificial neural network (ANN) model developed based on a comprehensive data base from literature, data clustering, and parameter optimization techniques to enhance accuracy and reliability. Experimental validation is undertaken to demonstrate the mix design determination procedure’s capability to accurately predict mix designs for geopolymer concrete based on the target compressive strength, validating its efficacy for mix proportion determination. The integration of chemical oxide content in fly ash, curing time, curing temperature, and activator properties results in a 15.9% improvement in prediction accuracy for the training dataset and a 68.3% enhancement for the testing dataset, compared to the base ANN model that includes only the weight of fly ash and activator properties. Employing data clustering techniques enables the identification of prior estimates for the mix design parameters related to specific fly ash types and target compressive strength, streamlining the mix design process by analyzing pertinent data subsets. Parameter optimization ensures refined mix proportions, achieving the desired target strength economically while minimizing material waste and cost. The development of a user interface facilitates easy manipulation of mix designs, catering to users of varying expertise levels. Additional options for deeper insights into geopolymer concrete characteristics can be integrated into the mix design determination procedure. To assess the mix design determination procedure's ability to generalize effectively, a variety of fly ash samples with distinct chemical compositions were utilized, differing from those already present in the database. This approach allows for a thorough evaluation of the mix design determination procedure's performance when presented with fly ash compositions it has not encountered before. By doing so, this provides insights into the adaptability of the mix design determination procedure beyond the limitations of the training and testing datasets. [ABSTRACT FROM AUTHOR]

The paper provides a review of mix design, construction temperature determination, performance and life-cycle assessment (LCA) of WMA mixtures. The mix design of WMA mixtures using almost the same design protocols as the HMA mixtures. The techniques used for determining WMA mixtures' construction temperatures include the analogy, phase angle, compaction energy index (CEI) and traffic densification index (TDI), and 4% air void methods. The use of Sasobit is advisable for the road prone to rutting. For the road prone to water damage, the use of foaming technologyis not suitable and Rediset is recommended. For the road prone to fatigue failure, the use of Water-based processes is not recommended, while Evotherm and Rediset are advisable. From an environmental point of view, water-based processes are recommended for the production of WMA mixtures, followed by organic additives and chemical additives, whereas the use of water-bearing additives is not recommended. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Ultra High-Performance Concrete (UHPC) has shown extraordinary performance in terms of strength and durability. However, having a cost-effective and sustainable UHPC mix design is a challenge in the construction sector. This study aims on building a predictable model that can help in determining the compressive strength of UHPC. The research focuses on applying multiple machine learning (ML) models and evaluating their performance in predicting the strength prediction of UHPC. Two reliable metrics are used to evaluate the performance of the model which are the coefficient of determination (R 2) and mean squared error (MSE). The parameters that are affecting the compressive strength of UHPC are fly ash percentage levels (FA%), superplasticizer content, water to binder ratio (w/b), and curing period. A total of 54 ML models were used, consisting of Linear Regression, Support Vector Machines (SVM), Neural Networks, and Random forests algorithms. Among these models, Random Forest proved to be the most effective in capturing the relationships in UHPC's behaviour with an R squared score of 0.8857. The Random Forest ML model is also used in this paper to conduct a parametric study that will help in obtaining the compressive strength of UHPC with higher content of FA%, which is not sufficiently studied in the literature. [ABSTRACT FROM AUTHOR]

Each component of the material that makes up concrete has a significant influence on its mechanical properties, so a mix design is needed to obtain the optimum concrete quality. This research uses three mix design methods, namely based on SNI 03-2834-2000, SNI 7656:2012, and Dreux Gorisse. SNI 03-2834-2000 refers to the DOE method from the UK, while SNI 7656:2012 adopts the ACI method from America. SNI 03-2834-2000 and SNI 7656:2012 are the applicable methods in Indonesia. While Dreux Gorisse is a concrete mix design method originating from France. This study aims to analyze the effect of concrete mix design and maximum aggregate size variation on the compressive strength of normal concrete. The maximum size of coarse aggregate used was 10, 20, and 40 mm. The planned concrete quality (f'c) was 25 MPa with cylindrical specimens measuring 15x30 cm. The highest compressive strength test results at the age of 28 days are with the SNI 7656:2012 method for a maximum aggregate size of 10 mm at 31.33 MPa. While the lowest compressive strength value with Dreux Gorisse for a maximum aggregate size of 40 mm was 25.38 MPa. In all mix design methods, the smaller the maximum size of coarse aggregate, the higher the compressive strength value. The maximum aggregate size of 10 mm in the SNI 7656:2012 method resulted in an increase in the maximum compressive strength by 25.31% from the planned compressive strength because it has a lower w/c ratio and slump values of 0.49 and 65 mm. [ABSTRACT FROM AUTHOR]

For the 3D STAR project and 3D printing purposes, a special finegrained cement mixture from locally available raw materials was developed. The reason for the development of the custom mixture was the possibility of arbitrary optimization of the developed mixture at any stage of the project and for any type of application. Mix design, printing head and the entire system from mixing to extrusion was the subject of research and development for this project. It was therefore necessary to address both issues in parallel and to respond in both sectors to the realities arising from the partial results of the different groups involved in the development. [ABSTRACT FROM AUTHOR]

The effects of grades of coarse aggregates on the cost of concrete was studied. Several times in real life practice, the engineer at construction site is faced with the problem of not having the required grade of coarse aggregate for a given project. . This could be caused by several reasons such as; non-availability of desired grade, the different grades of coarse aggregate being obtained as a left over from a sister project, etc. In Nigeria, coarse aggregate for concrete is very expensive and thus, the engineer will think of how to use the available grade of coarse aggregate in his concrete mix design to achieve the desired results instead of discarding it. In this study, seven different grades of coarse aggregate were investigated. The fineness modulus of the fine aggregate and bulk densities of the various grades of coarse aggregate were determined. The results were used together with tables from American Concrete Institute (ACI) code to carry out concrete mix design on all the various grades of coarse aggregate to calculate the quantities of the different elements of concrete. From the mix design, the cost of the materials for producing one cubic meter of concrete was determined. The result showed that the Well graded aggregate had the highest bulk density of 1717Kg/m³ while uniformly graded retained on 10mm sieve had the least bulk density of 1580Kg/m³. Uniformly graded aggregate retained on 10mm sieve required the highest cost of N58,278.81 to produce a cubic meter of grade 25 concrete while the cost was least at N56,242.52 when uniformly graded retained on 20mm sieve and Gap-graded without 5mm size were used. This suggests that the larger the size of coarse aggregate (within the size limits studied) the less the cement paste required and hence the less the cost. [ABSTRACT FROM AUTHOR]

Cemented paste backfill (CPB), a mixture of wet tailings, binding agent, and water, proves cost-effective and environmentally beneficial. Determining the Young modulus during CPB mix design is crucial. Utilizing machine learning (ML) tools for Young modulus evaluation and prediction streamlines the CPB mix design process. This study employed six ML models, including three shallow models Extreme Gradient Boosting (XGB), Gradient Boosting (GB), Random Forest (RF) and three hybrids Extreme Gradient Boosting-Particle Swarm Optimization (XGB-PSO), Gradient Boosting-Particle Swarm Optimization (GB-PSO), Random Forest-Particle Swarm Optimization (RF-PSO). The XGB-PSO hybrid model exhibited superior performance (coefficient of determination R2 = 0.906, root mean square error RMSE = 19.535 MPa, mean absolute error MAE = 13.741 MPa) on the testing dataset. Shapley Additive Explanation (SHAP) values and Partial Dependence Plots (PDP) provided insights into component influences. Cement/Tailings ratio emerged as the most crucial factor for enhancing Young modulus in CPB. Global interpretation using SHAP values identified six essential input variables: Cement/Tailings, Curing age, Cc, solid content, Fe2O3 content, and SiO2 content. [ABSTRACT FROM AUTHOR]

Large-particle-size graded crushed stone mixtures (LPS-GCSMs) can improve the shortcomings of conventional graded crushed stone, such as low strength, high deformation, and a low modulus of resilience. At present, there is no systematic research on the gradation design and field evaluation of the LPS-GCSMs. In this study, compaction and California bearing ratio (CBR) tests and field construction conditions were combined to design six kinds of gradation of LPS-GCSM, and the optimum gradation was revealed. In order to improve the mechanical properties of LPS-GCSM, 2.5% cement was added to the mixture to prepare a low-content cement-modified LPS-GCSM (LCC-LPS-GCSM) based on the suggested gradation. The mechanical properties of the LCC-LPS-GCSM were investigated through unconfined compression strength (UCS) and compression rebound modulus (CRM) tests. Moreover, the compaction and deflection properties of LPS-GCSM and LCC-LPS-GCSM were examined through the test battery. The results showed that the optimum gradation of LPS-GCSM can be achieved with a combination of aggregate sizes of 20–40 mm, 10–20 mm, 5–10 mm, and 0–5 mm at a ratio of 44:20:10:26. The passing rates of 19 mm and 4.75 mm should be approximately at the median value of the gradation in view of field construction uniformity and a coarse aggregate interlocking effect. The UCS and CRM values of LCC-LPS-GCSM increased rapidly from 0 day to 28 days while they slowed after 28 days, which was similar to those of cement-stabilized materials. The field detection suggested that LPS-GCSM exhibited favorable compaction and that the addition of cement improved the stability of the field compaction of the mixture. Adding a subbase course of LPS-GCSM between the old pavement and the LCC-LPS-GCSM base can lead to more uniform stress on the base. The results of this study provide a reference for the gradation design of LPS-GCSM and optimization of the design indicators. [ABSTRACT FROM AUTHOR]

Geopolymer Concrete (GPC) is an innovative type of concrete that offers significant advancements in sustainability and environmental impact, particularly in the areas of recycling and alternative construction techniques. Geopolymers provide a sustainable and energy-efficient alternative to Portland cement binder for civil infrastructure applications. They have a low carbon footprint and can completely replace Portland cement. However, there is no established specification or standard for developing GPC mixes. This is partially due to the numerous variables that influence the production of GPC, including the properties of unprocessed materials, the kind and amount of the activator, and the cure program. This review study aims to provide a comprehensive and up-to-date analysis of the various methods used in the design of geopolymer concrete (GPC). This paper examines three different mix proportioning methodologies for GPC: the target strength, the performance approach, and statistical approaches. It is recommended to select a design method based on production conditions and GPC requirements.

The process of urbanization generates substantial amounts of solid waste materials, including glass, red brick, concrete, and ceramic tile. Effective treatment methods for these waste materials are currently lacking, resulting in significant land wastage and environmental pollution. Utilizing these waste materials in the construction of asphalt pavements presents a viable solution for their high-quality and large-scale utilization. In this study, the properties of commonly produced urban solid waste materials, including glass, red brick, concrete, and ceramic tile, were investigated for their suitability as limestone porous asphalt mixtures. The physical and chemical properties of the coarse aggregate were examined using four groups of preliminary tests, including leakage analysis, scattering, rutting, and freeze-thaw splitting tests. The results revealed that the apparent relative density varied for different particle sizes within the range of 2.36–4.75 mm, 4.75–9.5 mm, 9.5–16 mm, and 13.2–16 mm. However, the dynamic stability of the glass specimen was only 740 times/mm, which falls significantly below the technical requirement of 1500 times/mm. Additionally, the high-temperature stability of the glass specimen was deemed unsatisfactory. The red brick test piece exhibited inadequate water stability due to its high-water absorption rate. Therefore, reducing the amount of waste glass and minimizing the incorporation of waste red brick are recommended. The findings of this study contribute to the expansion of application methods and techniques for urban solid waste, improving the utilization rate of solid waste resources. Furthermore, the study sheds light on the changes in the performance of solid waste aggregates mixed with porous asphalt mixtures, providing valuable insights for road engineering endeavors.

To optimise the mechanical performance of a buton-rock-asphalt (BRA)- modified asphalt mixture with basalt-fibre (BF), the optimum contents of BF and BRA, as well as the optimal asphalt stone ratio were obtained using response surface methodology (RSM). The feasibility of the mixed-ratio optimised design method was verified via a Marshall stability test. The results indicated that the optimal BF, BRA and asphalt stone ratios were 0.324 %, 22.44 % and 5.23 %, respectively. Moreover, there were some deviations between the average and predicted values of each response index. However, the error range was less than 5 %. A pavement performance index paired comparison matrix calculation method was established, and the pavement performance of the BF-BRA modified asphalt mixture was evaluated using the analytic hierarchy process (AHP). The process comprised eight different content combinations of BF and BRA. The maximum values of dynamic stability, bending strain, immersion Marshall residual stability, and tensile strength ration of BF-BRA modified asphalt mixture were 6512 cycles/mm, 4091 με, 97.4 %, 96.2 % respectively. This indicated that the pavement performance of asphalt mixture can be improved effectively by adding BF and BRA. Additionally, the BF-BRA modified asphalt mixture, which scored highest in pavement performance as evaluated by AHP, aligned with results obtained through response surface methodology(RSM) optimization. This consistency indicates that the BF-BRA modified asphalt mixture derived from RSM exhibits the best pavement performance.

The lack of a code for preparing one-part geopolymer concrete (GPC) is one of the major obstacles to its wide use. This study adopted one of the most common methods for preparing ordinary concrete, the ACI method, taking into account the most important variables affecting this method and then modified it to suit one-part GPC. Three different sizes of aggregates and four water-to-binder ratios (W/B) were used in preparing the concrete mixtures in this study. In addition, three different proportions of sodium metasilicate were used as the activator, which ultimately resulted in a total of 36 mix designs. Specimens were subjected to various tests, including setting time, workability, and compressive strength. In addition, the material's behaviour was studied using X-ray diffraction and scanning electron microscope. The results indicate that the ACI method is generally applicable for designing geopolymer concrete mixtures with minor adjustments. Consequently, the table used for predicting concrete strength based on a specific water/cement ratio has been replaced with relevant figures that depict the relationship between compressive strength and the water-to-binder ratio. In addition, a step-by-step flowchart has been presented that explains how to design one-part geopolymer concrete. Conducted experiments indicated that the properties of geopolymer concrete are greatly affected by the ratio of W/B and the size of aggregate used in preparing the concrete mixture. Furthermore, the quantity of activators has significant effects on concrete's workability and compressive strength. Results of the experiment suggest that one-part GPC can provide greater compressive strength than ordinary concrete. [ABSTRACT FROM AUTHOR]

Static and cyclic fracture properties (Modes I, III, and I/III) of cement emulsified asphalt mortar at three frequencies were investigated in terms of the fracture energy and fatigue life, respectively. For this to achieve, 576 edge notched disk bend specimens with 16 haphazard mix designs including, disparate bitumen‐to‐cement (B/C), water‐to‐cement (W/C) ratios, and cement contents (C) were tested. By developing statistical models (at the 5% significance level, p value < 0.05), the findings revealed that under static loading, the fracture energy got highest in tearing mode and lowest in opening mode. In all fracture modes, the fracture energy decreased with an increase of C and decrease of B/C while the mortar's fatigue life augmented due to a rise in C and B/C. Moreover, the fatigue life gained an increase with the increase in the fracture energy, loading frequency, and Me in the nonlinear trend. The utmost variation of fatigue life was explained with the increase of fracture energy which had the greatest effect in mode‐III loading. Highlight: Predicting CEAM's static and cyclic fracture behavior (I/III) at three frequencies by RSM.Under static loading, the fracture energy is highest in mode III and lowest in mode I.Fatigue life increased with the increase in C, A/C, fracture energy, and loading frequency.Cement content had the greatest nonlinear effect on fatigue life in the mixed‐mode I/III. [ABSTRACT FROM AUTHOR]

Copyright of Iron Steel Vanadium Titanium is the property of Iron Steel Vanadium Titanium Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Nanchang University (Engineering & Technology) is the property of Nanchang University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the use of 3D-printed concrete becomes more prevalent, the need for effective recycling methods becomes paramount. This study addresses this concern by exploring the repurposing of 3D-printed concrete waste as an aggregate in normal-strength concrete for C30/37 and C40/50 classes, covering both fine and coarse aggregates in its particle size distribution. The extent of recycled aggregate (RA) replacement was determined through sieve analysis. A two-stage investigation assessed the compressive strength performance of the concrete specimens. The initial stage produced reference specimens with no replacement, representing conventional concrete. In the second stage, variable specimens incorporated 50% and 67% recycled aggregate (RA) from 3D-printed concrete waste. Results revealed that in C40/50, both the 50% and 67% replacements consistently exhibited a higher strength than 0%. In C30/37, the 50% replacement displayed decreased strength compared to the 0% and 67%, while the 67% replacement consistently showed superior strength. Adjusting the water content impacted strength; at 67%, slight variations occurred, while at 50%, extra water led to a significant decrease. An overarching discovery is that the efficacy of the 67% replacement level holds regardless of the concrete strength class. [ABSTRACT FROM AUTHOR]

Three-dimensional concrete printing (3DCP) is a sustainable and green approach for rapid construction with the ability to create complex shapes to preserve the intended aesthetic appearance for an affordable cost. Even after a decade of attempts, there are many limitations and challenges to applying this technology for constructions without borders. The lack of guidelines for mix designs, quality control procedures during extrusion, printing and building phases, compatibility of material with extruder, standard testing, and guidelines to verify suitability of mixture with respect to the application and exposure conditions and limited machine capacity are several areas to be addressed for applications without borders. The development of 3DCP applications as a sustainable and green technology is another challenging task due to high Portland cement consumption in 3DCP. However, reducing the high usage of ordinary Portland cement (OPC) with pozzolanic waste materials replacement and environmentally friendly cement indicates the direction of moving 3DCP into a sustainable pathway. The authors reviewed more than 200 refereed articles published on materials and techniques in 3DCP. Inconsistency in disseminating knowledge in research articles has hindered the creation of a monolithically connected chain of research efforts and findings in accelerating the development and adoption of this technology. This paper summarizes the common approach to developing 3DCP mix designs and identifies the key areas for the future development of materials and techniques and challenges to be addressed for the global adoption of 3DCP. The current progress and challenges in the context of Australia's construction industry and future trends for the acceptance of 3DCP are also reviewed. [ABSTRACT FROM AUTHOR]

Abstract Six printing mixtures with variations in cement:sand ratios (in mass) were analyzed, keeping the water/dry material ratio constant, evaluating their printability, considering visual aspects, pumpability and filament integrity. The mixtures were subjected to mini-slump tests, spread on a consistency table, squeeze-flow, and deformation under load of the printed filaments at printing intervals of 0 min, 15 min and 30 min, and then the proportions of the compatible mixtures were determined. with the print. The properties in the hardened state, resistance to bending and compression, adhesion between layers, specific mass and voids index were determined for specimens extracted from printed parts. It was possible to observe that for the printing system used there is an ideal range for these constitutive relationships, and that the mixtures, even with different viscosities, measured according to the squeeze flow, can be printable, provided they meet the ideal ranges for the determined relationships. Regarding the interface of the printed layers, these are critical points of fragility, due to factors such as the formation of regions with voids and loss of surface moisture, which favors the reduction of the mechanical performance of the parts, with the increase in the deposition time.

Recent advances highlight the potential of low-carbon concrete using recycled aggregates from precast rejects. This material, called precast recycled aggregate concrete (PRAC), shows superior properties compared to traditional recycled aggregate concrete. However, accurately predicting PRAC’s mechanical properties remains challenging due to numerous influencing variables. This challenge is further compounded when PRAC’s design must align with mechanical, economic and ecological objectives. In light of these challenges, this study presents a framework that leverages Bayesian model updating and metaheuristic techniques to optimize PRAC’s mix proportions. Initially, a comprehensive database was compiled from existing literature. Subsequently, employing Bayesian model updating, two definitive expressions were established linking PRAC’s mechanical strengths to key variables. Finally, a multi-objective optimization approach, integrating the posterior model and the Cuckoo search algorithm, was devised to identify optimal mix designs for PRAC. The proposed models adeptly capture PRAC’s nuanced property trends, while the Bayesian-Cuckoo search hybrid significantly expedites the mix optimization process. Results advocate for a minimum of 60 % recycled aggregate substitution to strike a balance between PRAC’s strength and environmental impact. In essence, this framework furnishes dependable solutions for PRAC formulations and demonstrates adaptability for potential use in broader concrete mix design scenarios.

Formulating a mix design for 3D concrete printing (3DCP) is challenging, as it involves an iterative approach, wasting a lot of resources, time, and effort to optimize the mix for strength and printability. A potential solution is mix formulation through artificial intelligence (AI); however, being a new and emerging field, the open-source availability of datasets is limited. Limited datasets significantly restrict the predictive performance of machine learning (ML) models. This research explores data augmentation techniques like deep generative adversarial network (DGAN) and bootstrap resampling (BR) to increase the available data to train three ML models, namely support vector machine (SVM), artificial neural network (ANN), and extreme gradient boosting regression (XGBoost). Their performance was evaluated using R2, MSE, RMSE, and MAE metrics. Models trained on BR-augmented data showed higher accuracy than those trained on the DGAN-augmented data. The BR-trained XGBoost exhibited the highest R2 scores of 0.982, 0.970, 0.972, 0.971, and 0.980 for cast compressive strength, printed compressive strength direction 1, 2, 3, and slump flow respectively. The proposed method of predicting the slump flow (mm), cast, and anisotropic compressive strength (MPa) can effectively predict the mix design for printable concrete, unlocking its full potential for application in the construction industry.

This work presents the results of the characterisation of the mortars used to build the vaults of the choir and a transverse arch in the nave of Notre-Dame de Paris. The aim is to highlight the mixes used and technological choices made by the builders at the end of the 12th century. A multi-analytical approach made it possible to characterise the binders, aggregates, particle size distributions and the physical and chemical properties of about thirty samples. They lead to the definition of mortar mix equivalent to medieval ones. First investigations conducted on the fresh mortar show its ability to erect an arch or the panels of the vaults and validate the mortar mix proportions. These results will sufficiently support the ongoing project on the reconstitution of compatible mortars as well as on modelling the structural comportment of the edifice. [ABSTRACT FROM AUTHOR]

Tailings volumes continue to collectively increase worldwide, leading to larger dams and tailings management facilities. With numerous high-profile dam failures in the past decade, the risks of these management practices are also growing. A potential shift to waste management practices at mineral mines is to commingle waste rock and dewatered tailings. This blended material should have superior physical strength properties provided by the waste rock together with improved chemical stability characteristics associated with the low permeability of the tailings. Ideally, commingled tailings and waste rock can be used to construct various mined earth landforms that are both physically and chemically stable, which will enhance operational performance and ultimately provide for the sustainable decommissioning and closure of the mining facility. To study these materials, the University of Alberta Geotechnical Centre is working with global industry partners to test commingled materials from several mine sites with varying ore and host rock types and climate regimes. The first stage of this study is described here and is focused on the optimum density, saturated hydraulic conductivity, and soil–water characteristic curves of various blend ratios, performed at laboratory scale. [ABSTRACT FROM AUTHOR]

This study addresses the critical issue of traffic safety in winter, particularly focusing on the challenges posed by ice and snow on roads. Traditional methods of snow and ice removal are often labor-intensive, inefficient, and environmentally harmful. The objective is to develop a more effective solution for asphalt pavement deicing. Inspired by the anti-icing coating technology used in high-voltage conductors, this research develops an ice-suppressing material designed to reduce the adhesion between snow, ice, and pavement surfaces. The material's performance is evaluated in terms of deicing efficiency, durability, adhesive properties, and its impact on pavement performance. Test results demonstrate that the developed ice-suppressing material significantly reduces the adhesion between the ice layer and the pavement, facilitating easier removal. This study concludes that the developed ice-suppressing material significantly enhances deicing efficiency on asphalt pavements. It exhibits strong hydrophobic properties, as evidenced by increased water droplet contact angles on coated surfaces (99.5° to 83.3°) compared to clean glass slides (39.2° to 29°). This hydrophobicity effectively reduces ice adhesion, decreasing tensile and shear strength of the ice layer by 38.2% and 63.6%, respectively. Additionally, the material demonstrates superior ice-melting capabilities in sub-zero temperatures, with coated ice cubes showing a higher mass reduction rate than uncoated ones. Importantly, its slow-release nature ensures sustained deicing performance over multiple cycles, maintaining effectiveness after seven test cycles. This study introduces an innovative ice-suppressing material that not only improves the efficiency and environmental impact of deicing methods but also contributes to enhancing road safety in winter conditions. The material's novel composition and sustained effectiveness present a significant advancement in the field of winter road maintenance. [ABSTRACT FROM AUTHOR]

Due to the presence of free lime (FL) in slag and its lack of reaction with concrete components, concrete containing slag reduces strength. Pozzolanic Portland cement (PPC) in the presence of moisture and normal heat during chemical reactions with lime (calcium hydroxide) generates stable calcium silicates that have adhesion properties. By using PPC instead of Portland cement type I in roller compacted concrete (RCC) containing basic oxygen furnace slag (BOFS), it is possible to determine the mechanical properties of RCC due to the reaction between the FL in BOFS and PPC. Therefore, this study aims to investigate the effect of PPC on the mechanical properties of RCC containing BOFS. For this purpose, specimens are made with various cement content values (225-400 kg/m3), various BOFS content values (0-50%) and with the optimum moisture. The properties examined in this paper are compressive strength, indirect tensile strength, and static modulus of elasticity tests. The results show that the use of PPC is effective in compensating the negative impact of using BOFS and providing the minimum specified mechanical properties. Also, the proportion of consumption of PPC with BOFS value is determined for the possibility of maximum reaction between FL and pozzolan in cement. [ABSTRACT FROM AUTHOR]

The use of reclaimed asphalt pavement (RAP) and recycled asphalt shingles (RAS) in asphalt mixtures is a routine process. Recycled binder availability reflects the proportion of the total recycled binder in a given recycled asphalt material (RAM) that is available to blend with the virgin binder. Studies show that agglomerations of adhered RAM particles preclude complete availability. However, the Superpave volumetric mixture design methods adopted by the majority of state agencies assume complete availability. This study makes use of a sieve analysis method and tracer-based microscopy analysis to quantify recycled binder availability. Revisions to asphalt mix design procedures to account for partial availability are proposed, including consideration of the unavailable binder as part of the bulk aggregate volume and the use of the RAM gradation (i.e. black curve) rather than the recovered aggregate gradation (i.e. white curve) to design the mixture's aggregate structure. Three high RAM content 'control' mixtures that were originally designed under the assumption of complete recycled binder availability are redesigned according to the proposed approach. The redesigned mixtures had notably higher virgin binder content than the control mixtures. The redesigned mixtures also had significantly better cracking resistance than the control mixtures while still meeting permanent deformation requirements. [ABSTRACT FROM AUTHOR]

The main objective of this proposed study is to explore the correlations between the performance parameters measured from the state-of-practice mixture laboratory cracking tests and develop a prior model to predict the mixture cracking performance using the identified significant mix design variables for asphalt material selection and mix design stages. Total 20 plant-produced asphalt mixtures with varying design information were evaluated and the disparate mixture cracking performance tests were performed on these mixtures to characterise their performance. The analysis results indicate that the Flexibility Index (FI) parameter shows the overall good correlations with other cracking indices and thus is selected as the index to modelling mixture cracking performance in general. The stepwise regression model was employed to identify the significant mix design variables which were then used for the development of the prediction models to predict the mixture cracking performance in the form of FI parameter. The developed models can be used as a prior tool for material selection and mix design procedure, eliminating the time and effort for sample preparations and running the tests. [ABSTRACT FROM AUTHOR]