Analysis of the piston ring/liner oil film development during warm-up for an SI-engine

A one-dimensional ring-pack lubrication model developed at MIT is applied to simulate the oil film behavior during the warm-up period of a Kohler spark ignition engine [1]. This is done by making assumptions for the evolution of the oil temperatures during warm-up and that the oil control ring during downstrokes is fully flooded. The ring-pack lubrication model includes features such as three different lubrication regimes, i.e. pure hydrodynamic lubrication, boundary lubrication and pure asperity contact, non-steady wetting of both inlet and outlet of the piston ring, capability to use all ring face profiles that can be approximated by piece-wise polynomials and, finally, the ability to model the rheology of multi-grade oils. Not surprisingly, the simulations show that by far the most important parameter is the temperature dependence of the oil viscosity. This dependence is subsequently examined further by choosing different oils. The baseline oil is SAE 10W30 and results are compared to those using the SAE 30 and the SAE 10W50 oils.

Towards a complete dense geometric and photometric reconstruction under varying pose and illumination

This paper proposes a novel framework to construct a geometric and photometric model of a viewed object that can be used for visualisation in arbitrary pose and illumination. The method is solely based on images and does not require any specialised equipment. We assume that the object has a piece-wise smooth surface and that its reflectance can be modelled using a parametric bidirectional reflectance distribution function. Without assuming any prior knowledge on the object, geometry and reflectance have to be estimated simultaneously and occlusion and shadows have to be treated consistently. We exploit the geometric and photometric consistency using the fact that surface orientation and reflectance are local invariants. In a first implementation, we demonstrate the method using a Lambertian object placed on a turn-table and illuminated by a number of unknown point light-sources. A discrete voxel model is initialised to the visual hull and voxels identified as inconsistent with the invariants are removed iteratively. The resulting model is used to render images in novel pose and illumination. © 2004 Elsevier B.V. All rights reserved.

Inventors and entrepreneurs in academia: What types of skills and experience matter?

This paper aims to improve our understanding of the attributes of academic researchers that influence the capacity to contribute to technical advance, by adding to the pool of technological opportunities available to industry or engaging in the exploitation of entrepreneurial opportunities. We investigate a number of factors associated with the skills developed by academic researchers. We find that contributions to the pool of technological opportunities and exploitation of entrepreneurial opportunities involve different sets of skills and expertise of scientists. Our results show that the former is driven by academic scientists research excellence and discovery of earlier technological opportunities and the latter is driven by previous collaboration with industry partners, scientific breadth and experience of technological discovery. © 2011 Elsevier Ltd. All rights reserved.

Investigation of low nanosecond light-matter interaction mechanisms

Laser ablation of solid Silicon targets using pulsed Yb fiber lasers of pulse duration 1.5-400 ns Yb fiber lasers is studied in this work. Material responses of a range of pulse envelopes are examined including front peak (FP) and double peak (DP) pulses. Theoretical models for the interactions are examined and qualitative explanations of material response experiments are presented.

Light-matter interaction in a microcavity-controlled graphene transistor

Graphene has extraordinary electronic and optical properties and holds great promise for applications in photonics and optoelectronics. Demonstrations including high-speed photodetectors, optical modulators, plasmonic devices, and ultrafast lasers have now been reported. More advanced device concepts would involve photonic elements such as cavities to control light-matter interaction in graphene. Here we report the first monolithic integration of a graphene transistor and a planar, optical microcavity. We find that the microcavity-induced optical confinement controls the efficiency and spectral selection of photocurrent generation in the integrated graphene device. A twenty-fold enhancement of photocurrent is demonstrated. The optical cavity also determines the spectral properties of the electrically excited thermal radiation of graphene. Most interestingly, we find that the cavity confinement modifies the electrical transport characteristics of the integrated graphene transistor. Our experimental approach opens up a route towards cavity-quantum electrodynamics on the nanometre scale with graphene as a current-carrying intra-cavity medium of atomic thickness. © 2012 Macmillan Publishers Limited. All rights reserved.

Innovative Stereo Vision-Based Approach to Generate Dense Depth Map of Transportation Infrastructure

Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.

Innovative Stereo Vision-Based Approach to Generate Dense Depth Map of Transportation Infrastructure

Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.