Ford Motor Company

About: Ford Motor Company is a company organization based out in Dearborn, Michigan, United States. It is known for research contribution in the topics: Internal combustion engine & Clutch. The organization has 36123 authors who have published 51450 publications receiving 855200 citations. The organization is also known as: Ford Motor & Ford Motor Corporation.

Experience with approximate reliability-based optimization methods

Abstract: Traditional reliability-based design optimization (RBDO) requires a double loop iteration process. The inner optimization loop is to find the most probable point (MPP) and the outer is the regular optimization loop to optimize the RBDO problem with reliability objectives or constraints. It is well known that the computation can be prohibitive when the associated function evaluation is expensive. As a result, many approximate RBDO methods, which convert the double loop to a single loop, have been developed. In this work, several approximate RBDO methods are coded, discussed, and tested against a double loop algorithm through four design problems.

Representation and Shape Matching of 3-D Objects

Abstract: A three-dimensional scene analysis system for the shape matching of real world 3-D objects is presented. Various issues related to representation and modeling of 3-D objects are addressed. A new method for the approximation of 3-D objects by a set of planar faces is discussed. The major advantage of this method is that it is applicable to a complete object and not restricted to single range view which was the limitation of the previous work in 3-D scene analysis. The method is a sequential region growing algorithm. It is not applied to range images, but rather to a set of 3-D points. The 3-D model of an object is obtained by combining the object points from a sequence of range data images corresponding to various views of the object, applying the necessary transformations and then approximating the surface by polygons. A stochastic labeling technique is used to do the shape matching of 3-D objects. The technique matches the faces of an unknown view against the faces of the model. It explicitly maximizes a criterion function based on the ambiguity and inconsistency of classification. It is hierarchical and uses results obtained at low levels to speed up and improve the accuracy of results at higher levels. The objective here is to match the individual views of the object taken from any vantage point. Details of the algorithm are presented and the results are shown on several unknown views of a complicated automobile casting.

Magnetic resonance imaging and neurosphere therapy of stroke in rat

Abstract: We intracisternally transplanted subventricular zone (SVZ) cells labeled by ferromagnetic particles into stroked rats. Migration of transplanted cells was non-invasively tracked using magnetic resonance imaging (MRI). We found that transplanted cells selectively migrated towards the ischemic parenchyma at a mean speed of 65 +/- 14.6 microm/hr in living rats. Migration of transplanted cells in the brain was also measured histopathologically. Rats transplanted with SVZ cells exhibited significant improvement of neurological function. Our data suggest that intracisternal transplantation of SVZ cells provides an avenue for cell therapy of stroke and that MRI can be used to track grafted cells in the brain.

Characteristic Study and Time-Domain Discrete- Wavelet-Transform Based Hybrid Detection of Series DC Arc Faults

Abstract: DC arc fault introduces major safety concerns in a wide variety of components in dc networks However, the randomness and instability of dc arc makes it difficult to be detected In this paper, an experimental system was designed and tested at different load current, dc source voltage, and gap length to evaluate the impact of each parameter to the dc arc Based on the experimental results, characteristics in the electrical behavior were studied and fault detection oriented analysis was conducted A detection algorithm utilizing both time and time-frequency domain characteristics was proposed to differentiate between dc arc fault and normal condition The detection algorithm was then realized on a digital signal processing board and tested to verify the effectiveness Experimental results show that the proposed algorithm can detect arc fault in a timely manner and is free of nuisance trip from normal circuit operations such as load change condition