2 research outputs found
Microstructural and mechanical behaviours of Y-TZP prepared via slip-casting and fused deposition modelling (FDM)
No full textThis paper reports the microstructural characteristics and mechanical properties of yttria-stabilized zirconia prepared via fused deposition modelling and slip casting. X-Ray Diffraction peaks indicated that yttria-stabilized zirconia crystallized in tetragonal structure for both slip casted(SC) and fused deposition modelled(FDM) samples. Further, scanning electron microscopy of slip casted sample showcased closely packed structure with fine grains and an average grain size of ∼65 nm whilst fused deposition modelled samples showcased non-homogeneous pores with ∼20 nm grain size. Average relative density of slip casted samples was ∼99.4 % while that of fused deposition modelled sample exhibited ∼96.2 %. The Vickers Hardness of slip casted (∼15.26 ± 0.4 GPa) was ∼10 % higher than the fused deposition modelled samples (∼13.79 ± 0.3 GPa). Likewise, indentation fracture toughness of slip casted (5.78 ± 0.5 MPa m1/2) was 14 % higher than fused deposition modelled samples which could have been due to the change in grain size as well as porosity of the ceramics. Compressive strength of the fused deposition modelled samples was 32 % less than slip casted samples (∼510 ± 10 MPa) due to its non-homogenous pores which led to weakening van der Waals force of attraction
Infinite Coffee Cup
No full textImagine you go to your favorite cafe house or a restaurant and the system recognizes your presence and alerts the waiter and caters to your favorite beverage you longed for the day. The main motivation to Infinite Coffee Cup is to detect the presence of a person and dynamically and non-Invasively estimate the amount of coffee in a circular cup on the table. One of the more popular devices used is Microsoft Kinect, which has cameras that capture both RGB and Depth data. Kinect is a low cost sensing device which provides two streams of images, 8 bit 3 channel RGB image and 11 bit single channel depth image. The system is fixed at the roof facing downwards and it takes a top view of the cup placed on the table. We use ``libfreenect'' 1] drivers which is an open source project, to stream data from kinect. We employ various image processing algorithms using OpenCV (Open Source Computer Vision) which is a library of programming functions for real time computer vision. The algorithms are used to manipulate the data from kinect to, - Detect the circular coffee cups in the RGB image. - Overlay and correlate the depth values of cups in the depth image to get the height and amount of coffee in the cup
