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A novel system for the forming of three dimensional sheet metal parts is described that can form a variety of part shapes without the need for fixed tooling, and given only geometry (CAD) information about the desired part. The central elements of this system are a tooling concept based on a programmable discrete die surface and closed-loop shape control. The former give the process the degrees of freedom to change shape rapidly, and the latter is used to insure that the correct shape is formed with a minimum of forming trials. A 540 kN (60 ton) lab press has been constructed with a 0.3 m (12 in) square pair of discrete tools that can be rapidly re-shaped between forming trials. The shape control system uses measured part shapes to determine a shape error and to correct the tooling shape. This correction is based on a unique “Deformation Transfer Function” approach using a spatial frequency decomposition of the surface.

Efficient aftertreatment management requires accurate sensing of both particulate filter soot and ash levels for optimized feedback control. Currently a combination of pressure drop measurements and predictive models are used to indirectly estimate the loading state of the filter. Accurate determination of filter soot loading levels is challenging under certain operating conditions, particularly following partial regeneration events and at low flow rate (idle) conditions. This work applied radio frequency (RF)-based sensors to provide a direct measure of the particulate filter soot levels in situ. Direct measurements of the filter loading state enable advanced feedback controls to optimize the combined engine and aftertreatment system for improved DPF management. This study instrumented several cordierite and aluminum titanate diesel particulate filters with RF sensors. The systems were tested on a range of light- and heavy-duty applications, which included on- and off-road engines.

The MIT-based Mars Gravity Biosatellite payload engineering team has been engaged in designing and prototyping sensor and control systems for deployment within the rodent housing zone of the satellite, including novel video processing and atmospheric management tools. The video module will be a fully autonomous real-time analysis system that takes raw video footage of the specimen mice as input and distills those parameters which are of primary physiological importance from a scientific research perspective. Such signals include activity level, average velocity and rearing behavior, all of which will serve as indicators of animal health and vestibular function within the artificial gravity environment. Unlike raw video, these parameters require minimal storage space and can be readily transmitted to earth over a radio link of very low bandwidth.