9 resultados para Pockets
em Cambridge University Engineering Department Publications Database
Resumo:
Air pockets, one kind of concrete surface defects, are often created on formed concrete surfaces during concrete construction. Their existence undermines the desired appearance and visual uniformity of architectural concrete. Therefore, measuring the impact of air pockets on the concrete surface in the form of air pockets is vital in assessing the quality of architectural concrete. Traditionally, such measurements are mainly based on in-situ manual inspections, the results of which are subjective and heavily dependent on the inspectors’ own criteria and experience. Often, inspectors may make different assessments even when inspecting the same concrete surface. In addition, the need for experienced inspectors costs owners or general contractors more in inspection fees. To alleviate these problems, this paper presents a methodology that can measure air pockets quantitatively and automatically. In order to achieve this goal, a high contrast, scaled image of a concrete surface is acquired from a fixed distance range and then a spot filter is used to accurately detect air pockets with the help of an image pyramid. The properties of air pockets (the number, the size, and the occupation area of air pockets) are subsequently calculated. These properties are used to quantify the impact of air pockets on the architectural concrete surface. The methodology is implemented in a C++ based prototype and tested on a database of concrete surface images. Comparisons with manual tests validated its measuring accuracy. As a result, the methodology presented in this paper can increase the reliability of concrete surface quality assessment
Resumo:
Superhydrophobic surfaces are shown to be effective for surface drag reduction under laminar regime by both experiments and simulations (see for example, Ou and Rothstein, Phys. Fluids 17:103606, 2005). However, such drag reduction for fully developed turbulent flow maintaining the Cassie-Baxter state remains an open problem due to high shear rates and flow unsteadiness of turbulent boundary layer. Our work aims to develop an understanding of mechanisms leading to interface breaking and loss of gas pockets due to interactions with turbulent boundary layers. We take advantage of direct numerical simulation of turbulence with slip and no-slip patterned boundary conditions mimicking the superhydrophobic surface. In addition, we capture the dynamics of gas-water interface, by deriving a proper linearized boundary condition taking into account the surface tension of the interface and kinematic matching of interface deformation and normal velocity conditions on the wall. We will show results from our simulations predicting the dynamical behavior of gas pocket interfaces over a wide range of dimensionless surface tensions.
Resumo:
Laser micro machining is fast gaining popularity as a method of fabricating micro scale structures. Lasers have been utilised for micro structuring of metals, ceramics and glass composites and with advances in material science, new materials are being developed for micro/nano products used in medical, optical, and chemical industries. Due to its favourable strength to weight ratio and extreme resistance to chemical attack, glassy carbon is a new material that offers many unique properties for micro devices. The laser machining of SIGRADUR® G grade glassy carbon was characterised using a 1065 nm wavelength Ytterbium doped pulsed fiber laser. The laser system has a selection of 25 preset waveforms with optimised peak powers for different pulsing frequencies. The optics provide spot diameter of 40 μm at the focus. The effect of fluence, transverse overlap and pulsing frequency (as waveform) on glassy carbon was investigated. Depth of removal and surface roughness were measured as machining quality indicators. The damage threshold fluence was determined to be 0.29 J/cm2 using a pulsing frequency of 250 kHz and a pulse width of 18 ns (waveform 3). Ablation rates of 17 < V < 300 μm3/pulse were observed within a fluence range of 0.98 < F < 2.98 J/cm2. For the same fluence variation, 0.6 μm to 6.8 μm deep trenches were machined. Trench widths varied from 29 μm at lower fluence to 47 μm at the higher fluence. Square pockets, 1 mm wide, were machined to understand the surface machining or milling. The depth of removal using both waveform 3 and 5 showed positive correlation with fluence, with waveform 5 causing more removal than waveform 3 for the same fluence. Machined depths varied from less than 1 μm to nearly 40 μm. For transverse overlap variation using waveform 3, the best surface finish with Rz = 1.1 μm was obtained for fluence 0.792 J/cm2 for transverse overlap of 1 μm, 6 μm, and 9 μm at machined depths of 22.9 μm, 6.6 μm, and 4.6 μm respectively. For fluence of 1.426 J/cm2, the best surface finish with Rz = 1.2 μm was obtained for transverse overlap of 6 μm, and 9 μm at machined depths of 12.46 μm, and 8.6 μm respectively. The experimental data was compiled as machining charts and utilised for fabricating a micro-embossing glassy carbon master toolsets as a capability demonstration.
Resumo:
Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance. Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0000126?journalCode=jcemd4
Resumo:
Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.
Resumo:
Surface texturing has a great potential to improve tribological performance. First, possible texturing methods were identified and classified according to their physical principles. In sequence, some alternative texturing methods are presented. Some of them are already currently used either in industry or in laboratory, and innovations or simplifications are described for them. Others are innovative techniques. Some were explored only tentatively, where basic ideas and simple experimental investigations were developed to check their validity. Others were explored in more detail, so that their practical applicability could be identified. The first texturing method was photochemical texturing using a simple and cheap apparatus. Masking with inkjet printing before chemical etching was also successful to texture metallic samples. A new method involving electrochemical texturing, without the need to previously mask the samples to be textured have been studied in terms of voltage, current, mechanical configuration of the apparatus and electrolyte flushing. Another method aims to generate randomly distributed circular pockets on steel surfaces and involves dispersion of small acid droplets in oil. The final method involves the selective formation of hard areas on a steel surface by locallised diffusion, which should then develop into a texture during wear.
Resumo:
Air, trapped interfacially between the adhesive and the substrate, can have a detrimental effect on the peel strength of bonds formed by a PSA and relatively impermeable adherends. If the adhesive wets the substrate surface so that the contact angle is small then the forces of the surface tension within the adhesive can lead to the gradual expulsion of these pockets of air and thereby to the enhancement of the peel strength-the dwell-time effect. Using a high-performance PSA transfer tape it has been found that this strengthening effect may operate over many thousands of hours. With increasing hydrophobicity of the surfaces, this effect can be suppressed and a poor peel strength remains essentially constant with time. The observed rates at which the peel strength increases are quantitatively consistent with diffusion of entrapped air out of the interface. © 2012 Copyright Taylor and Francis Group, LLC.