Mohammed Sonebi

Performance and Cracking Behavior of Reinforced Beams Cast with Self-Consolidating Concrete

This paper aimed to investigate the uniformity of in-place strength and compare the structural performance of beams cast with self-consolidating concrete (SCC) and reference concrete. Concrete mixtures with standard 28-day compressive cube strengths of 35 and 60 MPa were evaluated. These correspond to 2 classes of concrete: C35 and C60. The distribution of compressive strength from core samples along beams was also examined. The beams of reference mixtures were cast with external vibration and those made with SCC were cast without any compaction. In general, the in-place compressive strengths of SCC were closer to standard cube strength than those of ordinary concrete. The distribution of in-place properties along the beams was found to be uniform for both SCC and ordinary concrete, and the maximum strength difference was less than 7%. At service load, there were more and wider cracks with greater penetration with the reference mixture than with the SCC of Class C60. The mode of failure and load deflection response of the beams cast with SCC and ordinary concrete were similar.

Applications of Statistical Models in Proportioning Medium-Strength Self-Consolidating Concrete

This paper reviews statistical models obtained from a factorial design carried out to determine the influence of 4 key parameters on filling and passing ability, segregation, and compressive strength. These parameters are important for successful development of medium-strength self-consolidating concrete (MS-SCC). The parameters considered were the contents of cement and pulverized-fuel ash (PFA), water-powder ratio (W/P), and dosage of HRWRA. The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined with Orimet, JRing combined with cone, fresh segregation, and compressive strength at 7, 28, and 90 days. The models are valid for mixtures made with 0.38-0.72 W/P, 60-216 kg/m3 of cement content, 183-317 kg/m3 of PFA, and 0-1% of high-range water-reducing admixture (HRWRA), by mass of powder. The utility of such models to optimize concrete mixtures to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mixture parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined with Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show tradeoffs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixtures. The paper establishes usefulness of the mathematical models as tools to facilitate the test protocol required to optimize MS-SCC.

ARTIFICIAL INTELLIGENCE MODEL FOR FLOWABLE CONCRETE MIXTURES USED IN UNDERWATER CONSTRUCTION AND REPAIR

This research explores the use of artificial neural networks (ANNs) to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and evaluate the sensitivity of such properties to variations in mixture ingredients. ANNs mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed ANN model, its architecture, training, and validation are presented. A database incorporating 175 UWC mixtures from 9 different studies was developed to train and test the ANN model. The data is arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show the ANN model thus developed is not only capable of accurately predicting slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.

Factorial Design of Cement Slurries Containing Limestone Powder for Self-Consolidating Slurry-Infiltrated Fiber Concrete

This study investigated slurries with high penetrability for production of self-consolidating slurry-infiltrated fiber concrete (SIFCON). Factorial experimental design was adopted to assess the combined effects of 5 independent variables on mini-slump test, plate cohesion meter, induced bleeding test, J-fiber penetration test, and compressive strength at 7 and 28 days. The independent variables investigated were the proportions of limestone powder (LSP) and sand, the dosages of high-range water-reducing admixture [superplasticizer (SP)] and viscosity agent (VA), and water-binder ratio (w/b). A 2-level fractional factorial statistical method was used to model the influence of key parameters on properties affecting the behavior of fresh cement slurry and compressive strength. The models are valid for mixtures with 10-50% LSP as replacement of cement, 0.02-0.06% VA by mass of cement, 0.6-1.2% SP, and 50 to 150% sand (percent mass of binder) and 0.42-0.48 w/b. The influences of LSP, SP, VA, sand, and w/b were characterized and analyzed using polynomial regression, which identifies the primary factors and their interactions on the measured properties. Mathematical polynomials were developed for mini-slump, plate cohesion meter, J-fiber penetration test, induced bleeding, and compressive strength as functions of LSP, SP, VA, sand, and w/b. The estimated results of mini-slump, induced bleeding test, and compressive strength from the derived models are compared with results obtained from earlier proposed models that were developed for cement paste. The proposed response models of the self-consolidating SIFCON offer useful information regarding the mixture optimization to secure a high penetration of slurry with low compressive strength.

Transport Properties of Self-Consolidating Concrete

This study reports the findings from an investigation carried out to study the effect of the mixture variations on the durability of medium- and high-strength self-consolidating concrete (SCC). The mixture variations studied include the type of mineral admixtures, such as limestone powder (LSP) and pulverized fuel ash (PFA), and viscosity-modifying admixtures (VMA) for both medium- and high-strength SCC. Air permeability, water permeability, capillary absorption, and chloride diffusivity were used to assess the durability of SCC mixtures in comparison with normal, vibrated concretes. The results showed that SCC mixtures, for medium- and high-strength grades using PFA followed by LSP give lower permeability, properties compared with normal concretes. SCC made with VMA had a higher sorptivity, air permeability, and water permeability compared with other SCC mixtures, which can be attributed to higher water-cement ratio (w/c) and lack of pore filling effect. An in-place migration coefficient was obtained using the in-place ion migration test. This was used to compare the potential diffusivity of different concretes. The results indicated that SCC, for both grades of strength, made with PFA showed much lower diffusivity values in comparison with other mixtures, whereas the SCC mixtures with VMA showed higher diffusivity.

Optimization of Cement Grouts Containing Silica Fume and Viscosity Modifying Admixture

There is an increasing need to identify the effect of mix composition on the rheological properties of cementitious grouts using minislump, Marsh cone, cohesion plate, washout test, and cubes to determine the fluidity, the cohesion, and other mechanical properties of grouting applications. Mixture proportioning involves the tailoring of several parameters to achieve adequate fluidity, cohesion, washout resistance and compressive strength. This paper proposes a statistical design approach using a composite fractional factorial design which was carried out to model the influence of key parameters on the performance of cement grouts. The responses relate to performance included minislump, flow time using Marsh cone, cohesion measured by Lombardi plate meter, washout mass loss and compressive strength at 3, 7, and 28 days. The statistical models are valid for mixtures with water-to-binder ratio of 0.37–0.53, 0.4–1.8% addition of high-range water reducer (HRWR) by mass of binder, 4–12% additive of silica fume as replacement of cement by mass, and 0.02–0.8% addition of viscosity modifying admixture (VMA) by mass of binder. The models enable the identification of underlying factors and interactions that influence the modeled responses of cement grout. The comparison between the predicted and measured responses indicated good accuracy of the established models to describe the effect of the independent variables on the fluidity, cohesion, washout resistance and the compressive strength. This paper demonstrates the usefulness of the models to better understand trade-offs between parameters. The multiparametric optimization is used to establish isoresponses for a desirability function for cement grout. An increase of HRWR led to an increase of fluidity and washout, a reduction in plate cohesion value, and a reduction in the Marsh cone time. An increase of VMA demonstrated a reduction of fluidity and the washout mass loss, and an increase of Marsh cone time and plate cohesion. Results indicate that the use of silica fume increased the cohesion plate and Marsh cone, and reduced the minislump. Additionally, the silica fume improved the compressive strength and the washout resistance.

Effect of Mixture Composition on Washout Resistance of Highly Flowable Underwater Concrete

The underwater casting of relatively thin lifts of concrete in water requires the proportioning of highly flowable concrete that can resist water dilution and segregation and spread readily into place. This paper describes an investigation conducted to examine the effects of anti-washout admixture concentration, water-cementitious materials ratio, and binder composition on the washout resistance of highly flowable concrete. The data presented is important given the increasing demand to secure quality repairs underwater and the higher environmental constraints to limit water pollution caused by such operations.

Performance of sustainable SCC mixes with mineral additions for use in precast concrete industry

The aim of this research was to study the impact that different mineral powders have on the properties of self-compacting concrete (SCC) in order to obtain relations that make it possible to optimize their dosages for being used in precast concrete applications. Different combinations and contents of cement, mineral additions (active and inert), superplasticizers, and aggregates are considered. A new approach for determining the saturation point of superplasticizers is introduced. The fresh state performance was assessed by means of the following tests: slump flow, V-funnel, and J-ring. Concrete compressive strength values at different ages up to 56 days have been retained as representative of the materials’ performance in its hardened state. All these properties have been correlated with SCC proportioning. As a result, a number of recommendations for the precast concrete industry arise to design more stable SCC mixes with a reduced carbon footprint.

The Collapse Behaviour of Cold-formed Steel Portal Frames at Elevated Temperatures

This paper describes the results of non-linear elasto-plastic implicit dynamic finite element analyses that are used to predict the collapse behaviour of cold-formed steel portal frames at elevated temperatures. The collapse behaviour of a simple rigid-jointed beam idealisation and a more accurate semi-rigid jointed shell element idealisation are compared for two different fire scenarios. For the case of the shell element idealisation, the semi-rigidity of the cold-formed steel joints is explicitly taken into account through modelling of the bolt-hole elongation stiffness. In addition, the shell element idealisation is able to capture buckling of the cold-formed steel sections in the vicinity of the joints. The shell element idealisation is validated at ambient temperature against the results of full-scale tests reported in the literature. The behaviour at elevated temperatures is then considered for both the semi-rigid jointed shell and rigid-jointed beam idealisations. The inclusion of accurate joint rigidity and geometric non-linearity (second order analysis) are shown to affect the collapse behaviour at elevated temperatures. For each fire scenario considered, the importance of base fixity in preventing an undesirable outwards collapse mechanism is demonstrated. The results demonstrate that joint rigidity and varying fire scenarios should be considered in order to allow for conservative design.

APPLICATIONS OF STATISTICAL MODELS FOR PROPORTIONING UNDERWATER CONCRETE

A factorial design was carried out to model mathematically the influence of five key parameters on slump consistency, washout mass loss, and compressive strength that are important for the successful development of underwater concrete. The parameters considered were the content of cementitious materials, water-to-cementitious material ratio, sand-to-total aggregate ratio, and concentrations of antiwashout admixture and high-range water reducer. The derived statistical models are valid for a wide range of mixture proportioning and reveal the order of influence of each parameter on the modeled responses. The utility of such models to optimize concrete mixtures to achieve good balance between slump consistency, washout resistance, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using contour diagrams to demonstrate single and coupled effects of mixture parameters on consistency and washout resistance. Cost analysis is carried out to show trade-offs between material cost and specified consistency and washout resistance levels that can be used to identify economic mixtures. This paper establishes the usefulness of the mathematical models as a tool to facilitate the test protocol required to optimize high-performance concrete for underwater applications.