The steady state performance of the counter rotating floating ring Journal bearing is analyzed with isothermal finite bearing theory. The effect of different parameters affecting the performance of the bearing (namely speed ratio, clearance ratio and radii ratio), have been investigated. The load carrying capacity of the bearing increasing with decreasing the radii ratio (R₂/R₁) of the ring and clearance ratio (c₁/c₂), in the other hand, the coefficient of friction increases with increasing the clearance and radii ratios, while decreases with incre4asing the bearing to journal speed ratio (γ). It is shown during this work that different operating conditions are greatly enhanced the performance

3D models delivered from digital photogrammetric techniques have massively increased and developed to meet the requirements of many applications. The reliability of these models is basically dependent on the data processing cycle and the adopted tool solution in addition to data quality. Agisoft PhotoScan is a professional image-based 3D modelling software, which seeks to create orderly, precise n 3D content from fixed images. It works with arbitrary images those qualified in both controlled and uncontrolled conditions. Following the recommendations of many users all around the globe, Agisoft PhotoScan, has become an important source to generate precise 3D data for different applications. How reliable is this data for accurate 3D mo

Generally fossil based fuels are used in internal combustion engines as an energy source.
Excessive use of fossil based fuels diminishes present reserves and increases the air pollution in
urban areas. This enhances the importance of the effective use of present reserves and/or to develop
new alternative fuels, which are environment friendly. Use of alternative fuel is a way of emission
control. The term “Alternative Gaseous Fuels” relates to a wide range of fuels that are in the
gaseous state at ambient conditions, whether when used on their own or as components of mixtures
with other fuels.
In this study, a single cylinder diesel engine was modified to use LPG in dual fuel mode to study
the performance, emis

There is an interesting potential for the use of GFRP-pultruded profiles in hybrid GFRP-concrete structural elements, either for new constructions or for the rehabilitation of existing structures. This paper provides experimental and numerical investigations on the flexural performance of reinforced concrete (RC) specimens composite with encased pultruded GFRP I-sections. Five simply supported composite beams were tested in this experimental program to investigate the static flexural behavior of encased GFRP beams with high-strength concrete. Besides, the effect of using shear studs to improve the composite interaction between the GFRP beam and concrete as well as the effect of web stiffeners of GFRP were explored. Encasing the GFRP

Advancing the multi-scale performance of asphalt pavements requires innovative binder modifications that address limitations in rutting resistance, fatigue resistance, and durability across the binder, mixture, and structural levels. This study evaluates the performance of asphalt cement, mixtures, and pavement systems modified with a combination of polyethylene (PE) and carbon nanotubes (CNTs). The binder was modified using 4% PE and varying CNT contents (0.5%, 1%, 1.5%, and 2% by weight of the modified binder). Binder performance was assessed through conventional and rheological tests, including penetration, softening point, viscosity, performance grade (PG) evaluation, and master curve analysis. Mixture-level performance was eval

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

This study investigates the characterization and mechanical performance of Stone Mastic Asphalt (SMA) mixtures modified with two types of polymers: styrene–butadiene–styrene (SBS) and high-molecular-weight polyethylene (PE). Neat asphalt cement PG 64-16 was modified using a higher content of SBS and PE at concentrations of 6%, 7%, and 8% by weight of asphalt through the dry blending method to produce Highly Modified Asphalts (HiMA). The physical and rheological properties of the modified binders were evaluated using penetration, softening point, rotational viscosity, and dynamic shear rheometer (DSR) tests. Also, their phase compatibility and morphological changes were evaluated using the storage stability testing and scanning electron