Abstract: The cubic equations of state (CEOS) relate pressure, temperature and molar volume of a mixture. The deviation of the physical properties of a mixture from ideality is expressed by the compressibility factor. The compressibility factor is calculated from the CEOS. There is described a solution to the CEOS which provides a continuous solution for compressibility factors over the entire range of operating conditions. This solution avoids the non-unique roots, trivial roots and singularities that are present in the prior art solutions of the CEOS.

Abstract: A methodology for process modeling and control and the software system implementation of this methodology, which includes a rigorous, nonlinear process simulation model, the generation of appropriate linear models derived from the rigorous model, and an adaptive, linear model predictive controller (MPC) that utilizes the derived linear models. A state space, multivariable, model predictive controller (MPC) is the preferred choice for the MPC since the nonlinear simulation model is analytically translated into a set of linear state equations and thus simplifies the translation of the linearized simulation equations to the modeling format required by the controller. Various other MPC modeling forms such as transfer functions, impulse response coefficients, and step response coefficients may also be used. The methodology is very general in that any model predictive controller using one of the above modeling forms can be used as the controller.

Abstract: A technique to provide dynamic modeling, parameter estimation and optimization for processes having operating targets. The technique has an optimization cycle and a simulation cycle. The simulation cycle runs at a rate that is equal to or faster than the run rate of the optimization cycle. Both cycles obtain data from the field about the process. The optimization cycle provides a simulation execution of a dynamic process model and the results of that simulation are used to match the model response to the actual plant response. This matching determines if a dynamic parameter estimation and data reconciliation is needed for the model parameters. Optimized operating targets are determined using either the estimated and reconciled parameters and data or if the same is not needed the collected process data. Mathematical and heuristic assessment tools are used to determine if the optimized operating targets should or should not be invoked.

Abstract: The present invention provides a radiation dosimeter comprising a support having a layer of microcapsules on the surface thereof. The microcapsules comprise a wall and an internal phase of a solution of a radiochromic dye. Upon exposure to radiation, the radiochromic dye changes color or shade plus density. The radiation dosimeter can be supplied in large as well as small formats.

Abstract: The present invention provides magnetic recording compositions containing magnetic particles and a photohardenable composition wherein the photohardenable composition contains a free radical addition polymerizable or crosslinkable compound and an ionic dye-reactive counter ion compound. The ionic dye-reactive counter ion compound is capable of absorbing actinic radiation and producing free radicals within initiate free radical polymerization or crosslinking of the polymerizable or crosslinkable compound. The present invention also provides magnetic recording media incorporating the aforementioned magnetic recording compositions.

Abstract: A radiation dosimeter comprising a support having a layer of microcapsules on the surface thereof, said microcapsules containing an image-forming agent and radiation curable composition, said composition being essentially insensitive to visible light and ultraviolet radiation and being sensitive to gamma and electron beam radiation; and a process for measuring gamma and electron beam radiation.