In order to understand the effect of the number of piles (N), the history response of dynamic pile load in piled raft system and deflection time history of piled raft under repeated impact load applied on the center of piled raft resting on loose sand, laboratory model tests were conducted on small-scale models. The results of experimental work are found to be dynamic load increase with increase height of drop, the measured repeated dynamic load time history on the center of piled raft was close approximately to three a half sine wave shape with small duration in about (0.015 Sec). The maximum peak of impact loads occurs in pile and deflection time history occur after at the time of the peak repeated impact loads, dynamic pile load

Experimental investigations had been done in this research to demonstrate the effect of carbon fiber and Ceramic fillers contents on the tribological behaviour of (15% volume fraction) carbon-epoxy composite system under varying volume fraction, load, time and sliding distance. The wear resistance were investigated according to ASTM G99-05standard using pin on disc machine to present the composite tribological behaviour. The influence of three ceramic fillers, granite, perlite and calcium carbonate (CaCO₃), on the wear of the carbon fabric reinforced epoxy composites under dry sliding conditions has been investigated. The effect of variants in volume fraction, applied load, time and sliding distance on the wear behaviour of po

This research aims to Measurement provide the service from Two perspectives The first perspective Service Provider (doctors) and the second recipient of the service (patients) in Numan General Hospital, and represented the research problem in perceptions of medical staff in the hospital assigned to them responsibility by providing superior services satisfy customers, and how they maintained ready to assist customers and provide services that exceed their perceptions of these services through the use of the developer scale by (Frimpong and Wilson, 2012), includes orientation to provide the service scale four dimensions (Internal cooperative behaviors, service Competence, Service Responsiveness and Enhanced service) and includes do

The current study presents an experimental investigation of heat transfer and flow characteristic for subcooled flow boiling of deionized water in the microchannel heat sink. The test section consisted of a single microchannel having 300μm wide nominal dimensions and 300μm height (hydraulic diameter of 300μm). The test section formed of oxygen-free copper with 72mm length and 12mm width. Experimental operation conditions spanned the heat flux (78-800) kW/m², mass flux (1700 and 2100) kg/m².s at 31˚C subcooled inlet temperature. The boiling heat transfer coefficient is measured and compared with existing correlations. Also, the experimental pressure drop is measured and compared with microscale p

Abstract. This study presents experimental and numerical investigation on the effectiveness of electrode geometry on flushing and debris removal in Electrical Discharge Drilling (EDD) process. A new electrode geometry, namely side-cut electrode, was designed and manufactured based on circular electrode geometry. Several drilling operations were performed on stainless steel 304 using rotary tubular electrodes with circular and side-cut geometries. Drilling performance was characterized by Material Removal Rate (MRR), Electrode Wear Rate (EWR), and Tool Wear Ratio (TWR). Dimensional features and surface quality of drilled holes were evaluated based on Overcut (OC), Hole Depth (HD), and Surface Roughness (SR). Three-dimensional

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d