Abstract: Real-time dynamic process modeling in an online model-based process control computing environment. A solver system utilizes an oracle to implement adaptive algorithms for a mixed integer nonlinear programming (MINLP) solver and a nonlinear programming (NLP) solver.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes grouping of first-principle model units to implement constraints of the underlying process. A group identifier parameter and a group complement parameter enable the grouping behavior through association with the first-principles model units.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes a switch to activate and deactivate a first-principle model of a process unit. The switch enables MINLP behavior by attaching to the first-principle model.

Abstract: Some embodiments include a server system including a first logic module executable by a processor for receiving a data communication from an industrial control system coupled to a communications network. In some embodiments, the data communication comprises data or data streams associated with the industrial process. The program logic of the first logic module includes a model configured to receive a variable and iterate and converge an optimization problem to an optimization solution to a first level of optimization based at least in part on the variable and the data or data streams. A second logic module executable by the processor is operatively data-linked to the first logic module and utilizes a model to iteratively process data values of the optimization solution to a second level of optimization with an increased level of optimization over the first level of optimization.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes grouping of first-principle model units to implement constraints of the underlying process. A group identifier parameter and a group complement parameter enable the grouping behavior through association with the first-principles model units.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes grouping of first-principle model units to implement constraints of the underlying process. A group identifier parameter and a group complement parameter enable the grouping behavior through association with the first-principles model units.

Abstract: Real-time dynamic process modeling in an online model-based process control computing environment. A solver system utilizes an oracle to implement adaptive algorithms for a mixed integer nonlinear programming (MINLP) solver and a nonlinear programming (NLP) solver.

Abstract: Real-time dynamic process modeling in an online model-based process control computing environment. A solver system utilizes an oracle to implement adaptive algorithms for a mixed integer nonlinear programming (MINLP) solver and a nonlinear programming (NLP) solver.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes a switch to activate and deactivate a first-principle model of a process unit. The switch enables MINLP behavior by attaching to the first-principle model.

Abstract: Some embodiments include a server system including a first logic module executable by a processor for receiving a data communication from an industrial control system coupled to a communications network. In some embodiments, the data communication comprises data or data streams associated with the industrial process. The program logic of the first logic module includes a model configured to receive a variable and iterate and converge an optimization problem to an optimization solution to a first level of optimization based at least in part on the variable and the data or data streams. A second logic module executable by the processor is operatively data-linked to the first logic module and utilizes a model to iteratively process data values of the optimization solution to a second level of optimization with an increased level of optimization over the first level of optimization.

Abstract: Real-time dynamic process modeling in an online model-based process control computing environment. A solver system utilizes an oracle to implement adaptive algorithms for a mixed integer nonlinear programming (MINLP) solver and a nonlinear programming (NLP) solver.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes grouping of first-principle model units to implement constraints of the underlying process. A group identifier parameter and a group complement parameter enable the grouping behavior through association with the first-principles model units.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes grouping of first-principle model units to implement constraints of the underlying process. A group identifier parameter and a group complement parameter enable the grouping behavior through association with the first-principles model units.

Abstract: Real-time dynamic process modeling in an online model-based process control computing environment. A solver system utilizes an oracle to implement adaptive algorithms for a mixed integer nonlinear programming (MINLP) solver and a nonlinear programming (NLP) solver.

Abstract: Real-time dynamic process modeling in an online model-based process control computing environment. A solver system utilizes an oracle to implement adaptive algorithms for a mixed integer nonlinear programming (MINLP) solver and a nonlinear programming (NLP) solver.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes grouping of first-principle model units to implement constraints of the underlying process. A group identifier parameter and a group complement parameter enable the grouping behavior through association with the first-principles model units.

Abstract: Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes a switch to activate and deactivate a first-principle model of a process unit. The switch enables MINLP behavior by attaching to the first-principle model.

Abstract: A system and method for modeling industrial processes is described. One embodiment includes collecting a plurality of flowsheets, which include corresponding groups of unit models and combining the plurality of flowsheets to create a combined model. In addition, a first macro associated with a first flowsheet is initiated and other macros by the same name as the first macro are automatically executed. In variations, the other macros are executed from a lowest hierarchical level flowsheet relative to the first flowsheet to a higher hierarchical level until the first macro is run.

Abstract: A system and method for modeling industrial processes is described. One embodiment includes collecting a plurality of flowsheets, which include corresponding groups of unit models and combining the plurality of flowsheets to create a combined model. In addition, a first macro associated with a first flowsheet is initiated and other macros by the same name as the first macro are automatically executed. In variations, the other macros are executed from a lowest hierarchical level flowsheet relative to the first flowsheet to a higher hierarchical level until the first macro is run.

Abstract: A software plant process modeling system operates in multiple modes. The software system uses process unit models. A process unit model includes at least one equation and at least one variable. The software system sets a status of a variable in the unit model to a first state. The first state is associated with a first mode of operation. The software system then sets the status of the same variable in the unit model to a second state. The second state is associated with a second mode of operation. The software system generates an open-equation model in operating in multiple modes. The software system receives a modification to at least one process unit model. Thus, a user may create a single plant process model for operation in multiple modes.