Evaluation of structural behavior of externally prestressed segmented bridge with shear key under torsion

Externally Prestressed Segmented (EPS) concrete beams are generally used in the construction of bridge structures. External Prestressed technique uses tendons that are placed completely outside the concrete section and attached to the concrete at anchorages and deviators only. Segmented bridge is a bridge built in short sections. Segmented bridge applies smart technique that is a part of an engineering management. EPS bridges are affected by combined stresses i.e., bending, shear, normal, and torsion stresses especially at the segments interface joints. Previous studies on EPS bridges did not include the effect of torsion in the load carrying capacity and other structural behavior. This paper presents an experimental investigation of the structural behavior of EPS bridged under combined bending, shear, normal, and torsion stresses. The aim of this paper is to improve the existing equation to include the effect of torsion in estimating the failure load of EPS bridge. A parametric study was carried out to investigate the effect of different external tendon layouts and different levels of torsion

Effects of nano-carbon reinforcement on the swelling and shrinkage behaviour of soil

In this study, the performance of two types of nanocarbons (NCs), namely carbon nanotubes (CNTs) and carbon nanofibers (CNFs), on the three-dimensional shrinkage and swelling properties of three clayey soils were investigated. The specimens of soil mixed with clay with bentonite contents of 0, 10 and 20% by weight of dry soil. NC contents of 0.05, 0.075, 0.10 and 0.20% were chosen to investigate the influence of different NC types, CNTs and CNFs. All soil specimens were compacted under maximum dry unit weight and optimum water content conditions by using standard compaction tests. The physical and mechanical characteristics of the reinforced samples were then determined. These included the desiccation cracking area, used to determine the crack intensity factor (CIF), as well as the shrinkage and swelling. The CIF for the soil specimens without NCs were higher than the soil specimens with NC additives. These results show that NCs decrease the development of desiccation cracks on the surface of compacted samples. The shrinkage and swelling tests showed that the rate of volume changing of the compacted soil specimens reduced with the increasing of NCs

Prediction of rockfill materials’ shear strength using various kernel function-based regression models—a comparative perspective

The mechanical behavior of the rockfill materials (RFMs) used in a dam’s shell must be evaluated for the safe and cost-effective design of embankment dams. However, the characterization of RFMs with specific reference to shear strength is challenging and costly, as the materials may contain particles larger than 500 mm in diameter. This study explores the potential of various kernel function-based Gaussian process regression (GPR) models to predict the shear strength of RFMs. A total of 165 datasets compiled from the literature were selected to train and test the proposed models. Comparing the developed models based on the GPR method shows that the superlative model was the Pearson universal kernel (PUK) model with an R-squared (R2 ) of 0.9806, a correlation coefficient (r) of 0.9903, a mean absolute error (MAE) of 0.0646 MPa, a root mean square error (RMSE) of 0.0965 MPa, a relative absolute error (RAE) of 13.0776%, and a root relative squared error (RRSE) of 14.6311% in the training phase, while it performed equally well in the testing phase, with R2 = 0.9455, r = 0.9724, MAE = 0.1048 MPa, RMSE = 0.1443 MPa, RAE = 21.8554%, and RRSE = 23.6865%. The prediction results of the GPR-PUK model are found to be more accurate and are in good agreement with the actual shear strength of RFMs, thus verifying the feasibility and effectiveness of the model

The effect of carbon-nanofiber and hydrated lime on weak soil stability

The vast amount of waste cooking oil (WCO) has invited odds effects on the environment when disposed of improperly. Incorporating waste materials into asphalt mixture is common practice these days as it minimizes the amount of waste material as well as improves the performance of the mixture. WCO is known for its natural fluidity characteristics, wherein affecting good cracking performance at low temperature, yet indicate poor rutting resistance at high temperature. Plus, less strength in porous asphalt has worsened the rutting condition. Hence, pretreatment of WCO is suggested before the modification was done. In this study, WCO is being treated with chemical treatment of the transesterification process. Then, the modified binder of 5%, 10%, 15% and 20% untreated and treated WCO were tested with physical testing of penetration and softening point temperature. Later, a similar percentage of untreated and treated WCO were incorporated into porous asphalt mixture to analyze the mechanical performance of Marshall Stability, Flow and Stiffness. The result of porous asphalt mixture with 10% treated WCO showed an improvement in Marshall Stability, Flow and Stiffness. It can be concluded, samples with treated WCO indicated remarkable performance in terms of physical and mechanical evaluation, owing to similar polarity which enhances good interaction bonding that strengthens the asphalt mixture

Nanomaterials characteristics and current utilization status in rigid pavements: mechanical features and sustainability. a review

Rigid pavements are recognized as one of the most widely means by which people and goods move around for popular aims and certain objectives. Nowadays, the utilization of rigid pavements is becoming an urgent demand and an increasing need, for these pavements require less maintenance and less renovation compared to other types. As a result, the structures are becoming more economical and more profitable. However, during its lifespan, normal rigid pavement is facing many challenges and difficulties. Its initial erection cost is extremely higher compared to asphalt pavements, its higher sensitivity to dynamic stresses, its higher susceptibility to temperature variations caused cracking, and further to its greater contribution to global carbon dioxide emissions. Past works of literature have been dealing with these drawbacks through employing efficient materials as alternatives to replace cement and/or aggregates in the concrete pavement mixtures. In recent years, the application of nanomaterials has received considerable interest to enhance the mechanical performance of construction materials which can also be available for rigid pavement constructions. Despite its poor performance in the fresh conditions, the addition of nanomaterials to rigid pavements has shown significant improvements in static properties like compressive and tensile strengths; dynamic properties like fatigue flexure and impact strengths. This enhancement is mainly due to the role of nanomaterials which acting as nano reinforcements and nanofillers within the concrete pavement blends. This review paper presents and discusses the behavior of nano-modified rigid pavements under different external loads. The effect of nano-SiO2, nano-CaCO3, nano-Al2O3, nano-TiO2, nano-clay and nanotubes are focused. Besides, as a promising sustainable structure, the influence of nano-SiO2 on the hardened properties of recycled rigid pavement is deeply discussed (both in normal and supplementary cementitious structures). Mechanical characteristics and optimal percentages are reviewed. A better comprehension of the characteristics of the nanostrengthening rigid pavements can provide an academic base for future works and engineering applications of developed concrete materials in the pavement construction industry

Comparison between mixtures of asphalt with Palm Oil Shells and coconut Shells as additives

The finding of other alternative material that has become the concern of various works lies in the fact that the material is to serve as an additive in asphalt mixes to enhance its physical properties. This paper deals with a laboratory study which compares the performance of hot mix asphalt (HMA) with the use of palm oil shells (POS), also with coconut shells (CS) as an additive and control samples. Both the palm oil shells and coconut shells are put in separately, taking up the shape of coarse aggregate with the size of 4.75 mm. The amount of these palm oil shells and coconut shells blended into the mixes is expressed in respective percentage (0,5, 10, 15 and 20%) of the total weight of the size 4.75 mm of aggregate. The Superpave method was employed to design the mixes. Samples were prepared and put to the test for the rutting characteristic as the indicator to the performance examined. It was observed that the addition of the coconut shells has made the HMA better with respect to their resilient modulus under 40˚C of temperature, it is cleared that 20% of CS as additive is the best percentage in term of resilient modulus among the percentages that have been chosen. However, it is contrary for the POS. The POS and CS addition will lead to that the asphalt concrete becoming more responsive to permanent deformation (static and dynamic creep) for more than 5% of shells content. In general, the CS emerges as better additives than POS in the HMA

Nanomaterials in recycled aggregates concrete applications: mechanical properties and durability. A review

The use of recycled aggregates concrete (RAC) contributes effectively to reduce CO2 emissions from concrete manufacturing process while also protecting natural resources by utilizing existing available concrete as an aggregates source for a new one. Studies on the behaviour of RAC have revealed negative effects on concrete strength and microstructure development, resulting in deterioration of mechanical and durability properties. As a result, numerous practical studies have been implemented to enhance the RAC properties using various treatment techniques such as chemical, physical and heating treatments. However, most of these techniques are ineffective compared to conventional concrete applications due to poor mechanical performance of RAC, insufficient environmental requirements, and prolonged treatment times. Recently, the use of nanomaterials has been given significant concern in RAC research. Their nano-sized particles can help to reduce micropores formation by acting as a filling agent to produce a high-density microstructure, thereby enhancing the mechanical properties and durability of RAC. This had led to a wide range of studies being published on improving RAC properties by using nanomaterials. However, relatively few literatures had been conducted on the effects of different types of nanomaterials on the performance of RAC exposed to various types of loads and various external environmental impacts. Besides, the conditions used by authors in these literatures limit comparisons, and in some cases contradictory findings are observed. Thus, this paper aims to bridge the knowledge gap between researchers. This would allow the potential of nanotechnology in innovations to be applied in appropriate areas of RAC applications to benefit the general public good. This paper aims to provide a critical review and comprehensive conclusions on the performance of nano-modified RAC under external loads, environmental impacts and other various conditions. The effects of nanomaterials on the compressive, tensile, and flexural strength of RAC are discussed. The nanomaterials considered are nano-SiO2, nano-CaCO3, nano-TiO2, nano-Clay, nano-Al2O3, and nano-Carbon. Durability characteristics including water absorption, chloride penetration, fire exposure, abrasion resistance, acid and carbonation diffusions are extensively discussed. Microstructure characteristics using SEM, XRD, EDS, and micro-hardness of nano-modified RAC are addressed as well

Boosting-based ensemble machine learning models for predicting unconfined compressive strength of geopolymer stabilized clayey soil

The present research employs new boosting-based ensemble machine learning models i.e., gradient boosting (GB) and adaptive boosting (AdaBoost) to predict the unconfined compressive strength (UCS) of geopolymer stabilized clayey soil. The GB and AdaBoost models were developed and validated using 270 clayey soil samples stabilized with geopolymer, with ground-granulated blast-furnace slag and fly ash as source materials and sodium hydroxide solution as alkali activator. The database was randomly divided into training (80%) and testing (20%) sets for model development and validation. Several performance metrics, including coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and mean squared error (MSE), were utilized to assess the accuracy and reliability of the developed models. The statistical results of this research showed that the GB and AdaBoost are reliable models based on the obtained values of R2 (= 0.980, 0.975), MAE (= 0.585, 0.655), RMSE (= 0.969, 1.088), and MSE (= 0.940, 1.185) for the testing dataset, respectively compared to the widely used artificial neural network, random forest, extreme gradient boosting, multivariable regression, and multi-gen genetic programming based models. Furthermore, the sensitivity analysis result shows that ground-granulated blast-furnace slag content was the key parameter affecting the UCS.Validerad;2024;Nivå 2;2024-02-16 (joosat);Funder: Najran University (NU/NRP/SERC/12/12);Full text license: CC BY</p

Prediction of ultimate bearing capacity of shallow foundations on cohesionless soils: a gaussian process regression approach

This study examines the potential of the soft computing technique—namely, Gaussian process regression (GPR), to predict the ultimate bearing capacity (UBC) of cohesionless soils be‐ neath shallow foundations. The inputs of the model are width of footing (B), depth of footing (D), footing geometry (L/B), unit weight of sand (γ), and internal friction angle (ϕ). The results of the present model were compared with those obtained by two theoretical approaches reported in the literature. The statistical evaluation of results shows that the presently applied paradigm is better than the theoretical approaches and is competing well for the prediction of UBC (qu). This study shows that the developed GPR is a robust model for the qu prediction of shallow foundations on cohesionless soil. Sensitivity analysis was also carried out to determine the effect of each input pa‐ rameter