Numerical Study of Concrete

Concrete is one of the most widely used construction material in the word today. The research in concrete follows the environment impact, economy, population and advanced technology. This special issue presents the recent numerical study for research in concrete. The research topic includes the finite element analysis, digital concrete, reinforcement technique without rebars and 3D printing

Innovating Two-Stage Concrete with Improved Rheological, Mechanical and Durability Properties

Two-stage concrete (TSC), also known as preplaced aggregate concrete, is a special type of concrete that is produced using a unique procedure which differs from that of conventional concrete. TSC is distinguished by its high coarse aggregate content and exceptional placement technique, whereby aggregates are first pre-placed in the mold then injected with a special grout. The preplacement of aggregates saves substantial energy since only the grout needs mechanical mixing; the grout is self-leveling and needs no vibration and no mechanical compaction. However, TSC applications are still limited despite substantial advancement of modern concrete technology. Therefore, there is a need to explore new possibilities and applications for TSC through adjusting and improving its properties. The objective of this study is to advance the TSC technology through the use of supplementary cementitious materials (SCMs), fibre reinforcement, capturing its sustainability features to develop novel pavements with very high recycled content, and establishing models with predictive capability for its engineering properties. Therefore, the fresh and hardened properties of grout mixtures incorporating various SCMs, including fly ash (FA), silica fume (SF) and metakaolin (MK) were investigated. An attempt was made to identify the optimum water-to-binder (w/b) ratio and the high-range water-reducing admixture (HRWRA) dosages for grout mixtures that meet the recommended efflux time (i.e. 35-40 ± 2 sec) according to ACI 304.1. Moreover, the effects of various SCMs at different dosages on the development of TSC mechanical properties were investigated. Likewise, the performance of TSC made with single, binary and ternary binders exposed to different environments conducive to physical and chemical sulfate attack was explored. The negative influence of fibres on the workability of conventional concrete is eliminated in TSC since the coarse aggregates and fibres are preplaced in the formwork and then injected with a flowable grout. This allows using fibre dosages beyond the practical levels typically adopted in conventionally mixed concrete. Therefore, the mechanical performance of two-stage steel fibre-reinforced concrete (TSSFRC) made with different dosages of steel fibres having various lengths was explored for the first time. The high coarse aggregate content endows TSC with superior volume stability, making it an ideal contender for pavements and sidewalks, which typically suffer from shrinkage and thermal cracking. In this study, the preplaced material consists of recycled concrete aggregate and scarp tire rubber granules along with scrap tire steel wire fibres, while the grout uses high-volume fly ash. The performance of such a “green” TSC pavement construction technology was explored. Finally, the experimental results were used to create a database which was utilized for developing fuzzy logic (FL) models as a means of predicting the grout flowability (i.e. efflux time and spread flow) and the mechanical properties (i.e. compressive and tensile strength) of a variety of two-stage concrete (TSC) mixtures. Results indicated that grouts made with water-to-binder ratio (w/b) = 0.45 can achieve the recommended grout flowability for successful TSC production. Moreover, TSC grout properties highly depended on the type and dosage of SCM used. The grout flowability was significantly enhanced as the FA dosage was increased, while the compressive strength was decreased. Partially replacing cement with 10% SF or 10% MK reduced the grout flowability and enhanced its compressive strength. Moreover, the binder composition has a great influence on the TSC mechanical properties. Empirical relationships between the properties of the grout and those of the corresponding TSC were proposed, offering a potential tool for estimating TSC properties based on primary grout properties. Furthermore, the ease of using a high dosage of pre-placed fibres in TSSFRC allowed achieving exceptional engineering properties for the pre-placed aggregate concrete. Indeed, TSSFRC can easily be produced with 6% steel fibre dosage, which makes it an innovative option and a strong contender in many construction applications. Fully immersed TSC specimens incorporating FA or MK in sodium sulfate solution exhibited high sulfate resistance. Surprisingly, TSC specimens incorporating SF deteriorated significantly due to thaumasite formation. Under physical sulfate attack exposure, TSC specimens incorporating FA and/or SF incurred severe surface scaling at the evaporative front, while those made with MK exhibited high resistance to surface scaling. A novel eco-efficient technology for the construction of pavements and sidewalks was proposed. The results demonstrate the feasibility of TSC eco-efficient technology to produce durable and cost-effective sidewalks and pavements, offering ease of placement and superior sustainability features. Finally, the performance of the developed FL models was evaluated using error and statistical analyses. The results indicate that the FL models can offer a flexible, adaptable and reasonably accurate tool for predicting the TSC grout flowability and mechanical properties. The findings of this study should provide a leap forward in establishing the TSC technology as a strong contender in many construction applications. It contributes to taking the TSC from a basic technology to a more modern system that benefits from advancements in concrete technology through the use of SCMs, chemical admixtures and fibre reinforcement. In particular, in a new context that values sustainability and “green” construction technology, this study has proven TSC to be exceptional in its ability to use recycled materials without the drawbacks observed in normal concrete technology. These findings should contribute to enhancing the understanding of the TSC behaviour, paving the way for its wider implementation in today’s concrete industry

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

In this study, efforts were made in order to put forward an integrated recycling approach for the thermoset based glass fibre reinforced polymer (GPRP) rejects derived from the pultrusion manufacturing industry. Both the recycling process and the development of a new cost-effective end-use application for the recyclates were considered. For this purpose, i) among the several available recycling techniques for thermoset based composite materials, the most suitable one for the envisaged application was selected (mechanical recycling); and ii) an experimental work was carried out in order to assess the added-value of the obtained recyclates as aggregates and reinforcement replacements into concrete-polymer composite materials. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified concrete-polymer composites with regard to unmodified materials. In the mix design process of the new GFRP waste based composite material, the recyclate content and size grade, and the effect of the incorporation of an adhesion promoter were considered as material factors and systematically tested between reasonable ranges. The optimization process of the modified formulations was supported by the Fuzzy Boolean Nets methodology, which allowed finding the best balance between material parameters that maximizes both flexural and compressive strengths of final composite. Comparing to related end-use applications of GFRP wastes in cementitious based concrete materials, the proposed solution overcome some of the problems found, namely the possible incompatibilities arisen from alkalis-silica reaction and the decrease in the mechanical properties due to high water-cement ratio required to achieve the desirable workability. Obtained results were very promising towards a global cost-effective waste management solution for GFRP industrial wastes and end-of-life products that will lead to a more sustainable composite materials industry

Determination of compressive strength of perlite-containing slag-based geopolymers and its prediction using artificial neural network and regression-based methods

This study has two main objectives: (i) to investigate the parameters affecting the compressive strength (CS) of perlite-containing slag-based geopolymers and (ii) to predict the CS values obtained from experimental studies. In this regard, 540 cubic geopolymer samples incorporating different raw perlite powder (RPP) replacement ratios, different sodium hydroxide (NaOH) molarity, different curing time, and different curing temperatures for a total of 180 mixture groups were produced and their CS results were experimentally determined. Then conventional regression analysis (CRA), multivariate adaptive regression splines (MARS), and TreeNet methods, as well as artificial neural network (ANN) methods, were used to predict the CS results of geopolymers using this experimentally obtained data set. Root mean square error (RMSE), mean absolute error (MAE), scatter index (SI) and Nash-Sutcliffe (NS) performance statistics were used to evaluate the CS prediction capabilities of the methods. As a result, it was determined that the optimum molarity, curing time, and curing temperature were 14 M, 24 h, and 110 celcius, respectively and 48 h of heat curing did not have a significant effect on increasing the CS of the geopolymers. The highest performances in regression-based models were obtained from the MARS method. However, the ANN method showed higher prediction performance than the regression-based methods. Considering the RMSE values, it was seen that the ANN method made improvements by 24.7, 2.1, and 13.7 %, respectively, compared to the MARS method for training, validation, and test sets

Advances in Binders for Construction Materials

The global binder production for construction materials is approximately 7.5 billion tons per year, contributing ~6% to the global anthropogenic atmospheric CO2 emissions. Reducing this carbon footprint is a key aim of the construction industry, and current research focuses on developing new innovative ways to attain more sustainable binders and concrete/mortars as a real alternative to the current global demand for Portland cement.With this aim, several potential alternative binders are currently being investigated by scientists worldwide, based on calcium aluminate cement, calcium sulfoaluminate cement, alkali-activated binders, calcined clay limestone cements, nanomaterials, or supersulfated cements. This Special Issue presents contributions that address research and practical advances in i) alternative binder manufacturing processes; ii) chemical, microstructural, and structural characterization of unhydrated binders and of hydrated systems; iii) the properties and modelling of concrete and mortars; iv) applications and durability of concrete and mortars; and v) the conservation and repair of historic concrete/mortar structures using alternative binders.We believe this Special Issue will be of high interest in the binder industry and construction community, based upon the novelty and quality of the results and the real potential application of the findings to the practice and industry

Influence of Using High Volume Fraction of Silica Fume on Mechanical and Durability Properties of Cement Mortar

The high pollution caused by CO2 emission and the high level of energy consumed during cement manufacturing led the researchers to look for alternative techniques to reduce these environmental effects. One of these techniques includes reducing the content of cement in the mix by replacing it with supplementary cementitious materials such as fly ash, slag, silica fume, and so on. Many previous studies dealt with the utilizing of the high volume of supplementary cementitious materials, such as fly ash and slag. However, limited studies investigated the impact of silica fume on mortar or concrete properties in percentages of more than 30%. Thus, to produce environmentally friendly concrete, this study was performed to investigate the effect of the high replacement level of cement with silica fume on the properties of cement mortar. Six replacement proportions of silica fume (0%, 30%, 40%, 50%, 60% and 70%) were used in this paper. This paper used the flow rate, compressive strength, water absorption, bulk density and volume of permeable voids tests to test the effect of silica fume on different mortar characteristics. The results indicated that the best mixture among all other mixes was found by 50% substitution of silica fume. At this percentage, an enhancement in compressive strength of nearly 83%, 74% and 75% at 7, 28 and 56 days, respectively and an improvement in water absorption resistance by 8% compared to the control mixture were achieved

Numerıcal Modelıng And Experımental Evaluatıon Of Shrınkage Of Concretes Incorporatıng Fly Ash And Sılıca Fume

Rötre genellikle sertleşmiş betonun önemli bir özelliği olarak ele alınır. Kuruma sürecinde boşluk yapısında bulunan serbest ve emilmiş su kaybedilir. Betonun rötresi kısıtlandığı zaman betonda olşan gerilmelere bağlı olarak çatlak oluşumu gözlenir. Bu çatlaklardan zararlı maddelerin geçmesiyle betonun dayanım ve dayanıklılıgında azalma olur. Bu çalışman ilk aşamasinda genetik programlama ve yapay sinir ağları yöntemleri kullanılarak rötre tahmin modelleri geliştirilmiştir. Modellerin eğitimi ve test edilmesi için literatürden veri toplanmıştır. Çalışmanın ikinci aşamasında ise uçucu kül ve silis dumanı içeren betonlar hazırlanarak kırk günlük kuruma sürecinde rötreleri ölçülmüştür. En yüksek rötre değerleri en çok mineral katkı içeren betonlarda gözlenmiştir. Bunların yanı sıra deneysel çalışmada elde edilen sonuçlar tahmin modellerinin verdikleriyle karşılaştırılmışlardır. YSA ile elde edilen değerlerin GP ile elde edilenlere göre gerçeğe daha yakın oldukları görülmüştür

PRIMJENA METODOLOGIJA MEKOGA RAČUNARSTVA U PREDVIĐANJU 28-DNEVNE TLAČNE ČVRSTOĆE MLAZNOGA BETONA: KOMPARATIVNA USPOREDBA INDIVIDUALNOGA I HIBRIDNOGA MODELA

Shotcreting is a popular construction technique with wide-ranging applications in mining and civil engineering. Compressive strength is a primary mechanical property of shotcrete with particular importance for project safety, which highly depends on its mix design. But in practice, there is no reliable and accurate method to predict this strength. In this study, existing experimental data related to shotcretes with 59 different mix designs are used to develop a series of soft computing methodologies, including individual artificial neural network, support vector regression, and M5P model tree and their hybrids with the fuzzy c-means clustering algorithm so as to predict the 28-day compressive strength of shotcrete. Analysis of the results shows the superiority of the hybrid model over the individual models in predicting the compressive strength of shotcrete. Overall, data clustering prior to use of machine learning techniques leads to certain improvement in their performance and reliability and generalizability of their results. In particular, the M5P model tree exhibits excellent capability in anticipating the compressive strength of shotcrete.Mlazni beton popularna je konstrukcijska tehnika široke uporabe u rudarstvu i građevinarstvu. Tlačna čvrstoća primarno je mehaničko svojstvo mlaznoga betona s posebnom važnošću za sigurnost projekta, ovisno o sastavu betona. U praksi ne postoji pouzdana i točna metoda za predviđanje toga svojstva. Ovdje su prikazani eksperimentalni podatci za 59 različitih sastava mlaznoga betona, na kojima je razvijen niz metodologija temeljem mekoga računarstva, uključujući pojedinačnu umjetnu neuronsku mrežu, podržanu vektorskom regresijom, stablastim dijagramima, njihovim hibridima na temelju klastera vrijednosti c-sredina, a s ciljem predviđanja promjene tlačne čvrstoće mlaznoga betona tijekom 28 dana. Općenito su klasteri podataka već prije uporabe strojnoga učenja znatno pomogli u kvaliteti, pouzdanosti i općenitosti rezultata. Posebno je istaknut stablasti model M5P kao onaj koji izvrsno predviđa tlačnu čvrstoću mlaznoga betona

A Review of the Compressive Strength Predictor Variables of Geopolymer Concrete

Having a prediction model for the geopolymer concrete (GPC) compressive strength gives Engineers an edge in project quality and cost control. Compressive strength of geopolymer concrete is dependent on various components that formed the concrete, and the curing regime. This paper is the outcome of a review of various variables (components and relationships) that influence the compressive strength of (GPC). The variables identified from the literature are; Concentration (Molarity) of the Hydroxide solution, Alkaline Liquid/Geopolymer Solids (Liquid/Binder) ratio, Sodium silicate to Sodium hydroxide ratio (SS/SH), curing time, curing temperature, Water/Geopolymer Solids ratio, age, fineness of the binder (pozzolan), rest period, admixtures and aggregates. A careful examination of the influence of each variable on compressive strength revealed that Hydroxide concentration, SS/SH, curing temperature, Alkaline Liquid/Geopolymer Solid ratio and Water/Geopolymer Solid ratio are the major determinants of GPC compressive strength