Abstract: A projectile designed to be lead-free and have a ballistic coefficient ranging from about 0.13 to about 0.80 or greater for enhanced energy/performance at extended ranges may have an elongated body formed with a jacket including a wall having an end defining an ogive portion and a cavity or recess defined within the jacket and in which a core is received. The projectile can be configured in various calibers and sizes. The projectile core may be formed from a plurality of core sections, and at least one of the plurality of core sections may include tungsten powder and a lead-free binder material pressed together to form a substantially cylindrical shape or compact. One or more of the core sections further can be sintered, and the one or more core sections may be received in an end-to-end relationship within the cavity defined by the jacket to form a stacked, sectional core.

Abstract: Techniques for determining device-specific information such as commissioning data, location information, images, and other data descriptive of a process device installed in a plant include obtaining the device-specific information at a local device during the process device's commissioning. Based on this information, the local device determines the relative order of the process device within a process flow, and may determine a process element alignment map indicating the activation order of a plurality of process elements within the flow. A user may modify the map at the local device. The map is transmitted to a process control big data network for use in discovery and learning analytics. The device-specific information and/or the map may be utilized to generate, at the local device, representations/views of the process flow, which may include real-time operational data. A user may zoom in or out on these views for more or less detail.

Abstract: A data modeling studio provides a structured environment for graphically creating and executing models which may be configured for diagnosis, prognosis, analysis, identifying relationships, etc., within a process plant. The data modeling studio includes a configuration engine for generating user interface elements to facilitate graphical construction of a model and a runtime engine for executing data models in, for example, an offline or an on-line environment. The configuration engine includes an interface routine that generates user interface elements, a plurality of templates stored in memory that serve as the building blocks of the model and a model compiler that converts the graphical model into a data format executable by the run-time engine. The run time engine executes the model to produce the desired output and may include a retrieval routine for retrieving data corresponding to the templates from memory and a modeling routine for executing the executable model.

Abstract: A device supporting big data in a process plant includes an interface to a communications network, a cache configured to store data observed by the device, and a multi-processing element processor to cause the data to be cached and transmitted (e.g., streamed) for historization at a unitary, logical centralized data storage area. The data storage area stores multiple types of process control or plant data using a common format. The device time-stamps the cached data, and, in some cases, all data that is generated or created by or received at the device may be cached and/or streamed. The device may be a field device, a controller, an input/output device, a network management device, a user interface device, or a historian device, and the device may be a node of a network supporting big data in the process plant. Multiple devices in the network may support layered or leveled caching of data.

Abstract: A data modeling studio provides a structured environment for graphically creating and executing models which may be configured for diagnosis, prognosis, analysis, identifying relationships, etc., within a process plant. The data modeling studio includes a configuration engine for generating user interface elements to facilitate graphical construction of a model and a runtime engine for executing data models in, for example, an offline or an on-line environment. The configuration engine includes an interface routine that generates user interface elements, a plurality of templates stored in memory that serve as the building blocks of the model and a model compiler that converts the graphical model into a data format executable by the run-time engine. The run time engine executes the model to produce the desired output and may include a retrieval routine for retrieving data corresponding to the templates from memory and a modeling routine for executing the executable model.

Abstract: Techniques for determining device-specific information such as commissioning data, location information, images, and other data descriptive of a process device installed in a plant include obtaining the device-specific information at a local device during the process device's commissioning. Based on this information, the local device determines the relative order of the process device within a process flow, and may determine a process element alignment map indicating the activation order of a plurality of process elements within the flow. A user may modify the map at the local device. The map is transmitted to a process control big data network for use in discovery and learning analytics. The device-specific information and/or the map may be utilized to generate, at the local device, representations/views of the process flow, which may include real-time operational data. A user may zoom in or out on these views for more or less detail.

Abstract: Techniques for determining device-specific information such as commissioning data, location information, images, and other data descriptive of a process device installed in a plant include obtaining the device-specific information at a local device during the process device's commissioning. Based on this information, the local device determines the relative order of the process device within a process flow, and may determine a process element alignment map indicating the activation order of a plurality of process elements within the flow. A user may modify the map at the local device. The map is transmitted to a process control big data network for use in discovery and learning analytics. The device-specific information and/or the map may be utilized to generate, at the local device, representations/views of the process flow, which may include real-time operational data. A user may zoom in or out on these views for more or less detail.

Abstract: A big data network or system for a process control system or plant includes a big data apparatus including a data storage area configured to store, using a common data schema, multiple types of process data and/or plant data (such as configuration and real-time data) that is used in, generated by or received by the process control system, and one or more data receiver computing devices to receive the data from multiple nodes or devices. The data may be cached and time-stamped at the nodes and streamed to the big data apparatus for storage. The process control system big data system provides services and/or data analyzes to automatically or manually discover prescriptive and/or predictive knowledge, and to determine, based on the discovered knowledge, changes and/or additions to the process control system and to the set of services and/or analyzes to optimize the process control system or plant.

Abstract: Techniques for determining device-specific information such as commissioning data, location information, images, and other data descriptive of a process device installed in a plant include obtaining the device-specific information at a local device during the process device's commissioning. Based on this information, the local device determines the relative order of the process device within a process flow, and may determine a process element alignment map indicating the activation order of a plurality of process elements within the flow. A user may modify the map at the local device. The map is transmitted to a process control big data network for use in discovery and learning analytics. The device-specific information and/or the map may be utilized to generate, at the local device, representations/views of the process flow, which may include real-time operational data. A user may zoom in or out on these views for more or less detail.

Abstract: A data modeling studio provides a structured environment for graphically creating and executing models which may be configured for diagnosis, prognosis, analysis, identifying relationships, etc., within a process plant. The data modeling studio includes a configuration engine for generating user interface elements to facilitate graphical construction of a model and a runtime engine for executing data models in, for example, an offline or an on-line environment. The configuration engine includes an interface routine that generates user interface elements, a plurality of templates stored in memory that serve as the building blocks of the model and a model compiler that converts the graphical model into a data format executable by the run-time engine. The run time engine executes the model to produce the desired output and may include a retrieval routine for retrieving data corresponding to the templates from memory and a modeling routine for executing the executable model.

Abstract: A data modeling studio provides a structured environment for graphically creating and executing models which may be configured for diagnosis, prognosis, analysis, identifying relationships, etc., within a process plant. The data modeling studio includes a configuration engine for generating user interface elements to facilitate graphical construction of a model and a runtime engine for executing data models in, for example, an offline or an on-line environment. The configuration engine includes an interface routine that generates user interface elements, a plurality of templates stored in memory that serve as the building blocks of the model and a model compiler that converts the graphical model into a data format executable by the run-time engine. The run time engine executes the model to produce the desired output and may include a retrieval routine for retrieving data corresponding to the templates from memory and a modeling routine for executing the executable model.

Abstract: A device supporting big data in a process plant includes an interface to a communications network, a cache configured to store data observed by the device, and a multi-processing element processor to cause the data to be cached and transmitted (e.g., streamed) for historization at a unitary, logical centralized data storage area. The data storage area stores multiple types of process control or plant data using a common format. The device time-stamps the cached data, and, in some cases, all data that is generated or created by or received at the device may be cached and/or streamed. The device may be a field device, a controller, an input/output device, a network management device, a user interface device, or a historian device, and the device may be a node of a network supporting big data in the process plant. Multiple devices in the network may support layered or leveled caching of data.

Abstract: A big data network or system for a process control system or plant includes a big data apparatus including a data storage area configured to store, using a common data schema, multiple types of process data and/or plant data (such as configuration and real-time data) that is used in, generated by or received by the process control system, and one or more data receiver computing devices to receive the data from multiple nodes or devices. The data may be cached and time-stamped at the nodes and streamed to the big data apparatus for storage. The process control system big data system provides services and/or data analyses to automatically or manually discover prescriptive and/or predictive knowledge, and to determine, based on the discovered knowledge, changes and/or additions to the process control system and to the set of services and/or analyses to optimize the process control system or plant.

Abstract: A method or apparatus automatically configures a control module for synchronous execution on a Fieldbus segment of a process control network by determining if all of the critical function blocks of a particular control module can be assigned to FOUNDATION® Fieldbus field devices or to the I/O device associated with a particular Fieldbus segment. If so, the method or apparatus automatically assigns the function blocks of the control module, which would otherwise be scheduled to execute in a controller, to the I/O device for the Fieldbus segment. This technique enables all of the critical or necessary function blocks within the control module to execute in one macrocycle of the Fieldbus segment, thereby executing synchronously on a Fieldbus segment.

Abstract: A network identification system for use in a process control system creates and stores a unique network identification tag for input/output networks in the process control system. During the configuration process, each process controller is assigned a unique controller identification tag. In addition, each input/output device installed on each process controller is assigned a device identification tag. The network identification system creates a network identification tag for an input/output network by concatenating and combining the unique controller identification tag and the device identification tag. The network identification system may be configured to periodically transmit the network identification tag or to provide the network identification tag is response to a request for identification.

Abstract: A versatile controller that can be used as either a stand-alone controller in a relatively small process plant or as one of numerous controllers in a distributed process control system depending on the needs of the process plant includes a processor adapted to be programmed to execute one or more programming routines and a memory, such as a non-volatile memory, coupled to the processor and adapted to store the one or more programming routines to be executed on the processor. The versatile controller also includes a plurality of field device input/output ports communicatively connected to the processor, a configuration communication port connected to the processor and to the memory to enable the controller to be configured with the programming routines and a second communication port which enables a user interface to be intermittently connected to the controller to view information stored within the controller memory.

Abstract: A hand-held communication control device which, when coupled to a process control system communication bus, controls communication occurring on the bus using a communication schedule that dictates when each of the devices coupled to the bus will be permitted to communicate on the bus. The hand-held communication control device further uses a probing algorithm to detect devices, including other communication control devices, that are coupled to the bus. The probing algorithm causes the hand-held communication control device to select an address from one of a set of three address lists to which a probe node message is then transmitted to detect the presence of a device at that address. One of the address lists is reserved for communication control devices and uses only a limited number of maximum possible addresses.

Abstract: A method of and a device for implementing redundancy in a process control network using a pair of redundant devices, such as redundant I/O devices, communicatively connected to a segment of the bus in parallel to each other and in series between the controller and field devices on the segment. The redundant devices are assigned a virtual publishing address, which may be the unique address of one of the redundant devices, that is used in communicating over the bus. At all times, one of the redundant devices is operating in an active mode and communicating with the devices in process control network, and the other redundant device is operating in a backup mode wherein the redundant device maintains a communication connection with the devices and listens for messages transmitted by the devices and intended for the redundant devices, but does not respond to messages from the other devices until the device switches to the active mode.

Abstract: A network identification system for use in a process control system creates and stores a unique network identification tag for input/output networks in the process control system. During the configuration process, each process controller is assigned a unique controller identification tag. In addition, each input/output device installed on each process controller is assigned a device identification tag. The network identification system creates a network identification tag for an input/output network by concatenating and combining the unique controller identification tag and the device identification tag. The network identification system may be configured to periodically transmit the network identification tag or to provide the network identification tag is response to a request for identification.

Abstract: A method of and a device for implementing redundancy in a process control network using a pair of redundant devices, such as redundant I/O devices, communicatively connected to a segment of the bus in parallel to each other and in series between the controller and field devices on the segment. The redundant devices are assigned a virtual publishing address, which may be the unique address of one of the redundant devices, that is used in communicating over the bus. At all times, one of the redundant devices is operating in an active mode and communicating with the devices in process control network, and the other redundant device is operating in a backup mode wherein the redundant device maintains a communication connection with the devices and listens for messages transmitted by the devices and intended for the redundant devices, but does not respond to messages from the other devices until the device switches to the active mode.