Hydraulic regeneration systems have been considered by the automotive industry for implementation in hybrid vehicles for a number of years. The combination of an internal combustion engine and an energy storage device has great potential for improving vehicle performance and fuel economy as well as reducing brake wear. This study describes an analytical model of a hydraulic regeneration system consisting of an accumulator, an oil reservoir, a variable-displacement pump/motor, connecting lines and a flywheel which is used to simulate vehicle inertia. An integration algorithm is used to simultaneously solve the governing equations and predict the system performance. Variables including accumulator pressure and temperature, pump/motor torque and efficiencies, pressure losses, and flywheel speed as functions of time are predicted. Power losses and round-trip efficiencies can be readily determined once the system performance variables have been calculated.

Tract ablation with thermocouple-monitored RF energy decreased postprocedural hemorrhage after hepatic and renal biopsy.

The statics and dynamics of pneumatic power screwdriver operation were investigated in the context of predicting forces acting against the human operator. A static force model is described in the paper, based on tool geometry, mass, orientation in space, feed force, torque build up, and stall torque. Three common power hand tool shapes are considered, including pistol grip, right angle, and in-line. The static model estimates handle force needed to support a power nutrunner when it acts against the tightened fastener with a constant torque. A system of equations for static force and moment equilibrium conditions are established, and the resultant handle force (resolved in orthogonal directions) is calculated in matrix form. A dynamic model is formulated to describe pneumatic motor torque build-up characteristics dependent on threaded fastener joint hardness. Six pneumatic tools were tested to validate the deterministic model. The average torque prediction error was 6.6% (SD = 5.4%) and the average handle force prediction error was 6.7% (SD = 6.4%) for a medium-soft threaded fastener joint. The average torque prediction error was 5.2% (SD = 5.3%) and the average handle force prediction error was 3.6% (SD = 3.2%) for a hard threaded fastener joint. Use of these equations for estimating handle forces based on passive mechanical elements representing the human operator is also described. These models together should be useful for considering tool handle force in the selection and design of power screwdrivers, particularly for minimizing handle forces in the prevention of injuries and work related musculoskeletal disorders.

This study reports experimental data taken with a hydraulic energy regeneration system and compares the measured data with analytical results. The system tested consisted of two foam-filled hydraulic accumulators, a variable-displacement piston-type pump/motor, a reservoir and a flywheel. During a series of experiments, energy was repeatedly transferred between the hydraulic accumulators and the flywheel through the pump/motor. Computed system variables compared favorably with the experimental results. At high and moderate pump/motor swivel angles, the round-trip efficiency varied from 61 to 89 percent. It was significantly lower at small angles.

A deterministic mechanical model based on physical tool parameters was used for estimating static and dynamic hand forces from kinematic measurements. We investigated the effects of target torque (25, 40, and 55 Nm) and threaded fastener joint hardness (35-, 150-, 300-, 500-, and 900-ms torque buildup time) on hand force. Estimated hand force was affected by target torque and joint hardness. Peak and average dynamic hand force was least for the hard joint (35-ms buildup) and greatest for the medium hardness joint (150-ms buildup). Tool inertia played the major role in reducing hand reaction force. Estimated hand force decreased when the inertial force component increased. Inertial force decreased by 366% when buildup time increased from 35 to 300 ms. Static modeling overestimated hand force; the error ranged from 10% for a soft joint to 40% for a hard joint. Results from direct hand force measurements using a strain gauge dynamometer showed that the dynamic model overestimated peak hand force by 9%. However, average hand force and force impulse were not significantly overestimated.