Abstract: A process is disclosed for recovering hydroprocessing effluent from a hydroprocessing unit utilizing a hot stripper and a cold stripper. Only the hot hydroprocessing effluent is heated in a fired heater prior to product fractionation, resulting in substantial operating and capital savings.

Abstract: An apparatus is disclosed for recovering hydroprocessing effluent from a hydroprocessing unit utilizing a hot stripper and a cold stripper. Only the hot hydroprocessing effluent is heated in a fired heater prior to product fractionation, resulting in substantial operating and capital savings.

Abstract: A process is disclosed for recovering hydroprocessing effluent from a hydroprocessing unit utilizing a hot stripper and a cold stripper. The cold stripper and the hot stripper are contained in the same vessel. A barrier prevents material from the hot stripper from entering into the cold stripper.

Abstract: A data storage and analysis system for modeling complex systems and the outcome of decisions and potential alternatives. The system employs a hierarchical hybrid data model with high volumes of data organized in many dimensions, such as models of organization and business operations. A “wizard-based” data loader handles imperfect data and supports multiple servers and data sources. The structures that represent the hierarchical model for the data are defined and created as the backbone for the model using spreadsheets, multiple relational database tables, and other sources of data that may reside on one or more servers. The hierarchical hybrid data model that is built also supports the linking of many different sources of data to the model's hierarchies. Analytics generators called “microCubes™” generate answers to ‘questions’ based on the server model as they are requested.

Abstract: A data storage and analysis system for modeling complex systems and the outcome of decisions and potential alternatives. The system employs a hierarchical hybrid data model with high volumes of data organized in many dimensions, such as models of organization and business operations. A “wizard-based” data loader handles imperfect data and supports multiple servers and data sources. The structures that represent the hierarchical model for the data are defined and created as the backbone for the model using spreadsheets, multiple relational database tables, and other sources of data that may reside on one or more servers. The hierarchical hybrid data model that is built also supports the linking of many different sources of data to the model's hierarchies. Analytics generators called “microCubes™” generate answers to ‘questions’ based on the server model as they are requested.

Abstract: A data storage and analysis system for modeling complex systems and the outcome of decisions and potential alternatives. The system employs a hierarchical hybrid data model with high volumes of data organized in many dimensions, such as models of organization and business operations. A “wizard-based” data loader handles imperfect data and supports multiple servers and data sources. The structures that represent the hierarchical model for the data are defined and created as the backbone for the model using spreadsheets, multiple relational database tables, and other sources of data that may reside on one or more servers. The hierarchical hybrid data model that is built also supports the linking of many different sources of data to the model's hierarchies. Analytics generators called “microCubes™” generate answers to ‘questions’ based on the server model as they are requested.

Abstract: A data storage and analysis system for modeling complex systems and the outcome of decisions and potential alternatives. The system employs a hierarchical hybrid data model with high volumes of data organized in many dimensions, such as models of organization and business operations. A “wizard-based” data loader handles imperfect data and supports multiple servers and data sources. The structures that represent the hierarchical model for the data are defined and created as the backbone for the model using spreadsheets, multiple relational database tables, and other sources of data that may reside on one or more servers. The hierarchical hybrid data model that is built also supports the linking of many different sources of data to the model's hierarchies. Analytics generators called “microCubes™” generate answers to ‘questions’ based on the server model as they are requested.