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The results indicate that the performance criterion can only be achieved if the splitless injection settings are carefully optimized.
The optimization includes the key combustion system related hardware, bowl geometry and injection nozzle design, together with the most relevant air management and injection settings.
Several variables including the backflow ratio, the radial nonuniformity index and the mean residence time of feed, are further introduced to quantify the hydrodynamic dependence of flow and mixing on the injection settings.
The newly designed Partially Premixed Combustion (PPC) concept operating with high octane fuels like gasoline has confirmed the possibility to combine low NOx and soot emissions keeping high indicated efficiencies, while offering a control over combustion profile and phasing through the injection settings.
The effects of the most important injection settings on the engine performance have been detailed, applying a Design of Experiment (DoE) method, to identify the most important parameters affecting emissions and the potentiality offered by a proper engine calibration to optimize the ethanol blend use.
The electronic auto-injector device, easypod™, has a number of features, such as preset dosing, an electronic skin sensor and adjustable injection settings, designed to make daily administration of r-hGH easier, more comfortable and convenient; it also allows accurate monitoring of treatment adherence [ 13]. easypod™ has an injection log that automatically records injection history.
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Figure 3 plots the calculated number of liposomes optically injected into single cells for durations of 10, 30, 45, 60, 90, and 120 s at a constant lipid concentration of 10 mM (approximately 6 × 10 liposomes/μL) and the optical injection laser settings described in Methods.
Injections were made using the semiautomatic mode of the system with the following instrumental settings: injection pressure 6 8 kPa, compensatory pressure 2.5 4 kPa, injection time 0.5 s and velocity of the pipette 700 μm/s.
Various studies have shown that dynamic (time-varying) injection and production settings can yield a higher Net Present Value (NPV) than conventional reactive settings.
However, the shape of the optimal injection and production settings is generally not known beforehand.
One of the best examples about gas lift optimization has been achieved by McKie et al. (2001), in which gas lift injection rates, compressor settings, and field fuel consumption for more than 500 wells were optimized to maximize liquid production.
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