Abstract: A constrained non-linear approximator for empirical process control is disclosed. The approximator constrains the behavior of the derivative of a subject empirical model without adversely affecting the ability of the model to represent generic non-linear relationships. There are three stages to developing the constrained non-linear approximator. The first stage is the specification of the general shape of the gain trajectory or base non-linear function which is specified graphically, algebraically or generically and is used as the basis for transfer functions used in the second stage. The second stage of the invention is the interconnection of the transfer functions to allow non-linear approximation. The final stage of the invention is the constrained optimization of the model coefficients such that the general shape of the input/output mappings (and their corresponding derivatives) are conserved.

Abstract: Currently lacking are effective and accurate tools to help petroleum traders and logistics personnel to make better decisions, collaborate in real-time and negotiate deals in a private and secure environment. The present invention addresses this and other needs in the industry. In particular, the present invention provides automated workflow management for a series of workflow tasks by mapping the workflow tasks to a collaborative workflow process comprising: roles, users, business processes and computer executable activities. A workflow object is received that supplies information used to set particular attributes of the roles, the users, the business activities and the computer executable activities of the collaborative workflow process. Information and data objects are shared electronically among the users performing certain of the roles. At least one of the activities is automatically executed, such that the workflow is automatically managed.

Abstract: Computer method and apparatus for managing process and plant engineering data for chemical or other engineering processes across applications. The method and apparatus include a respective class view for each of multiple software applications, a composite class view, a conceptual data model and a resulting consolidated multi-tier data model. The multi-tier data model enables sharing of engineering and other data from the multiple software applications with other process and plant engineering applications and programs. An amalgamator synthesizes the class views, composite views and conceptual data model into the multi-tier data model. In forming the multi-tier data model, there is a one-to-one mapping between an attribute in the class view and composite class view, and a one-to-one mapping between an attribute in the composite class view and a data path in the conceptual data model to corresponding software applications from which the attribute originated.

Abstract: A constrained non-linear approximator for empirical process control is disclosed. The approximator constrains the behavior of the derivative of a subject empirical model without adversely affecting the ability of the model to represent generic non-linear relationships. There are three stages to developing the constrained non-linear approximator. The first stage is the specification of the general shape of the gain trajectory or base non-linear function which is specified graphically, algebraically or generically and is used as the basis for transfer functions used in the second stage. The second stage of the invention is the interconnection of the transfer functions to allow non-linear approximation. The final stage of the invention is the constrained optimization of the model coefficients such that the general shape of the input/output mappings (and their corresponding derivatives) are conserved.

Abstract: The present invention provides a method and system for using standard global computer network communication protocol to implement server driven “push” technology. An initial communication connection is established between a server and a client. The connection is maintained by predefined periodic signals which are non-substantive messages from the server to the client. Upon existence of a substantive message at the server, the server transmits an appropriate predefined signal to the client. The client thereafter receives the substantive message. In one application, the server exchanges substantive messages between two clients and as such provides instant messaging.

Abstract: Systematic methods to detect, verify, and repair a collinear model are presented. After detecting collinearity in a model or subsets of a model, a directional test is carried out to verify if the collinearity is real. The model can then be adjusted in either direction to making a near collinear model exactly collinear or less collinear, subject to model uncertainty bounds or other linear constraints. When doing the model adjustment, deviations from the original model are minimized and the directionality of the model is kept unchanged.

Abstract: A multivariable process controller controls a chemical, polymer or other physical process. Slow tuning and over-conservative controlled variable values are employed during step testing. While all controlled process variables are within safe limits, only one manipulated variable (MV) at a time is step changed. Several manipulated variables are moved when process variables exceed safe limits to ensure that the controlled process variables return to the safe range, such that suitable MV targets for step testing are able to be automatically discovered within a closed loop control environment. Thus, the step test is able to be conducted mostly unsupervised and/or remotely via a telephone or network connection. A new process perturbation approach simultaneously perturbs multiple or all of the process input variables in such a way that the process responses (process outputs) are maximized, while the process variables are maintained inside its predefined operating constraints.

Abstract: Described herein are methods, systems, and articles that are useful for controlling a fluid blending system, such as a fluid utility system. The methods, systems, and articles of this invention allow for the control of both a quantity metric (e.g., pressure) of the blended fluid the fluid blending system as well as at least one quality metric of a blended fluid in a fluid blending system. For example, the methods, systems, and articles of this invention provide for the simultaneous control of both the pressure and quality of fuel gas within a fuel gas header system.

Abstract: A non-linear dynamic predictive device (60) is disclosed which operates either in a configuration mode or in one of three runtime modes: prediction mode, horizon mode, or reverse horizon mode. An external device controller (50) sets the mode and determines the data source and the frequency of data. In the forward modes (prediction and horizon), the data are passed to a series of preprocessing units (20) which convert each input variable (18) from engineering units to normalized units. Each preprocessing unit feeds a delay unit (22) that time-aligns the input to take into account dead time effects. The output of each delay unit is passed to a dynamic filter unit (24). Each dynamic filter unit internally utilizes one or more feedback paths that provide representations of the dynamic information in the process. The outputs (28) of the dynamic filter units are passed to a non-linear approximator (26) which outputs a value in normalized units.

Abstract: In the present invention the NonRandom Two-Liquid segment activity coefficient model system of the parent application is extended for computation of ionic activity coefficients and solubilities of electrolytes, organic and inorganic, in common solvents and solvent mixtures. The invention method and system may be applied to the chemical and/or pharmaceutical design process. In addition to the three types of molecular parameters defined for organic nonelectrolytes, i.e., hydrophobicity X, polarity Y, and hydrophilicity Z, an electrolyte parameter, E, is introduced to characterize both local and long-range ion-ion and ion-molecule interactions attributed to ionized segments of electrolytes. Successful representations of mean ionic activity coefficients and solubilities of electrolytes, inorganic and organic, in aqueous and nonaqueous solvents are presented.

Abstract: Currently lacking are effective and accurate tools to help petroleum traders and logistics personnel to make better decisions, collaborate in real-time and negotiate deals in a private and secure environment. The present invention addresses this and other needs in the industry. In particular, the present invention provides a non-client computer resident method optimizes vessel scheduling by aggregating vessel information. At least some of the vessel information is automatically downloaded from an electronic source. The aggregated vessel information is stored in a vessel information database comprising vessel information database records. Information is obtained about a potential vessel contracting transaction. The vessel information database is searched in a real-time manner to match the potential vessel contracting transaction to at least one of the vessel information database records such that the vessel contracting transaction is optimized.

Abstract: Included are methods for modeling at least one physical property of a mixture of at least two chemical species. One or more chemical species of the mixture are approximated or represented by at least one conceptual segment. The conceptual segments are then used to compute at least one physical property of the mixture. An analysis of the computed physical properties forms a model of at least one physical property of the mixture. Also included are computer program products and computer systems for implementing the modeling methods.

Abstract: A multivariable process controller controls a chemical, polymer or other physical process. Slow tuning and over-conservative controlled variable values are employed during step testing. While all controlled process variables are within safe limits, only one manipulated variable (MV) at a time is step changed. Several manipulated variables are moved when process variables exceed safe limits to ensure that the controlled process variables return to the safe range, such that suitable MV targets for step testing are able to be automatically discovered within a closed loop control environment. Thus, the step test is able to be conducted mostly unsupervised and/or remotely via a telephone or network connection. A new process perturbation approach simultaneously perturbs multiple or all of the process input variables in such a way that the process responses (process outputs) are maximized, while the process variables are maintained inside its predefined operating constraints.

Abstract: Computer method and apparatus determines state of physical properties, i.e. product quality, of a chemical manufacturing process. A steady state modeler provides a rigorous steady state model of the process and instantaneous state of physical properties. An estimator or inferential sensing member determines state of the physical properties over time based on the steady state (instantaneous) values of the physical properties. To that end, a dynamic model of the subject process is formed from the steady state model. The computer method and apparatus may be part of a network such that laboratory and sensor measured process data is made accessible by the steady state modeler and the estimator, and the estimator provides process parameter values for maintaining state of the physical properties. The network also enables online and user-interactive access to the steady state model, the dynamic model and/or the parameter values for enabling control of the subject process.

Abstract: A multivariable process controller controls a chemical, polymer or other physical process. Slow tuning and over-conservative controlled variable values are employed during step testing. While all controlled process variables are within safe limits, only one manipulated variable (MV) at a time is step changed. Several manipulated variables are moved when process variables exceed safe limits to ensure that the controlled process variables return to the safe range, such that suitable MV targets for step testing are able to be automatically discovered within a closed loop control environment. Thus, the step test is able to be conducted mostly unsupervised and/or remotely via a telephone or network connection.

Abstract: Computer method and apparatus for managing process and plant engineering data for chemical or other engineering processes across applications. The method and apparatus include a respective class view for each of multiple software applications, a composite class view, a conceptual data model and a resulting consolidated multi-tier data model. The multi-tier data model enables sharing of engineering and other data from the multiple software applications with other process and plant engineering applications and programs. An amalgamator synthesizes the class views, composite views and conceptual data model into the multi-tier data model. In forming the multi-tier data model, there is a one-to-one mapping between an attribute in the class view and composite class view, and a one-to-one mapping between an attribute in the composite class view and a data path in the conceptual data model to corresponding software applications from which the attribute originated.

Abstract: The present invention relates to a system and a method of screening potential customers of chemical products for safe practices related to the chemicals that they wish to purchase or otherwise obtain from manufacturers and/or distributors. A customer may order chemical products on-line that may be are categorized based upon the degree of hazard they pose. The customer may be presented with a query form when the customer orders a chemical product for the first time. The query is designed to include allow the customer to provide information concerning the preparedness of the customer should an emergency with the product arise. Moreover, the customer may automatically affirm that the responses to the query form are true and correct. A reviewer may determine whether the product order should be approved or rejected. If approved, the order is finalized.

Abstract: A method and apparatus for steady-state target calculation that explicitly accounts for model uncertainty is disclosed. In accordance with one aspect of the invention, when model uncertainty is incorporated, the linear program associated with the steady-state target calculation can be recast as a highly structured nonlinear program. In accordance with another aspect of the invention, primal-dual interior point methods can be applied to take advantage of the resulting special structure. For a system having characteristic gain parameters G having a known uncertainty description, the present invention provides a method and apparatus for selecting steady-state targets for said system-manipulated variables such that all system-controlled variables will remain feasible at steady-state for all possible values of the parameters G within the known uncertainty description.

Abstract: A first principles, steady state model of a desired polymer process is applied with a non-linear optimizer to a linear controller. Model process gains and optimal target values for controller variables result. These results are utilized by a multivariable linear controller to achieve nonlinear control of the subject process. Preferably the nonlinear optimizer is DMO/SQP. The steady state model is produced by Polymers Plus and the linear controller is DMCplus, all of Aspen Technology, Inc. in Cambridge Mass.

Abstract: An apparatus and method is disclosed for detecting, identifying, and classifying faults occurring in sensors measuring a process. A variety of process models can be used such as first principles models, dynamic multivariable predictive control models, from data using statistical methods such as partial least squares (PLS) or principal component analysis. If faults are identified in one or more sensors, the apparatus and method provide replacement values for the faulty sensors so that any process controllers and process monitoring systems that use these sensors can remain in operation during the fault period. The identification of faulty sensors is achieved through the use of a set of structured residual transforms that are uniquely designed to be insensitive to specific subsets of sensors, while being maximally sensitive to sensors not in the subset. Identified faults are classified into one of the types Complete Failure, Bias, Drift, Precision Loss, or Unknown.