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Saturation arithmetic is a version of arithmetic in which all operations, such as addition and multiplication, are limited to a fixed range between a minimum and maximum value. If the result of an operation is greater than the maximum, it is set (" clamped ") to the maximum; if it is below the minimum, it is clamped to the minimum.
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The saturation flow is the rate at which a continuous flow of vehicles can pass through a constant green signal, typically expressed in vehicles per hour or PCUs per hour. [1] A formula to calculate saturation flows based on lane geometry is given in Transport and Road Research Laboratory RR67. [2]
where temperature T is in degrees Celsius (°C) and saturation vapor pressure P is in kilopascals (kPa). According to Monteith and Unsworth, "Values of saturation vapour pressure from Tetens' formula are within 1 Pa of exact values up to 35 °C." Murray (1967) provides Tetens' equation for temperatures below 0 °C: [3]
The saturation with respect to water cannot be measured much below –50 °C, so manufacturers should use one of the following expressions for calculating saturation vapour pressure relative to water at the lowest temperatures – Wexler (1976, 1977), [1] [2] reported by Flatau et al. (1992)., [3] Hyland and Wexler (1983) or Sonntag (1994 ...
The Arden Buck equations are a group of empirical correlations that relate the saturation vapor pressure to temperature for moist air.The curve fits have been optimized for more accuracy than the Goff–Gratch equation in the range −80 to 50 °C (−112 to 122 °F).
The Köhler curve is the visual representation of the Köhler equation. It shows the saturation ratio – or the supersaturation = % – at which the droplet is in equilibrium with the environment over a range of droplet diameters. The exact shape of the curve is dependent upon the amount and composition of the solutes present in the atmosphere.
In computer science and mathematical logic, satisfiability modulo theories (SMT) is the problem of determining whether a mathematical formula is satisfiable.It generalizes the Boolean satisfiability problem (SAT) to more complex formulas involving real numbers, integers, and/or various data structures such as lists, arrays, bit vectors, and strings.