The present disclosure describes systems and techniques that enhance effectiveness and efficiency of a contingency analysis tool that is used for studying the magnitude and likelihood of extreme contingencies and potential cascading events across a power system. The described systems and techniques include deploying the contingency analysis tool in a high-performance computing (HPC) environment and incorporating visual situational awareness approaches to allow power system engineers to quickly and efficiently evaluate multiple power system simulation models. Furthermore, the described systems and techniques include the power system contingency-analysis tool calculating and coordinating protection element settings, as well as assessing controls of the power system using small-signal nomograms, allowing power system engineers to more effectively comprehend, evaluate, and analyze causes and effects of cascading events against a topology of a power system.

The invention relates to a method for designing grippers and fixtures for handling objects in robotic manufacturing and pick-and-place tasks. To achieve this a method for determining a shape of the holding or support surface of the gripper or fixture is presented. This method includes steps of determining an initial shape of the support surface based on an outer shape of the object, applying a shaping function to different locations of the initial shape, determining modified shape points at locations of the initial shape by comparing the applied shaping function with the initial shape. If the application of the shaping function results in an extension of the initial shape G(xi,yj) at the neighbour location (xi, yj) this extension forms part of a modified support surface for the gripper or fixture. A method for determining an optimum shape of the support surface with respect to optimization conditions is also presented.

A method may include obtaining wellhead temperature data from a wellhead coupled to a wellbore. The method may further include obtaining production data regarding the wellhead. The method may further include obtaining water cut data from the wellhead. The method may further include calibrating a production model for the wellhead based on the production data and the wellhead temperature data to generate a calibrated production model. The method may further include determining a predicted production rate of the wellhead using the calibrated production model, the water cut data, and flowing wellhead temperature data.

Described herein are systems and methods for evaluating and mitigating the fouling potential of a given crude oil. The system and methods enable the refiner to rapidly and readily identify the particular mechanisms by which a crude oil may foul, and to select the optimal chemical treatment and/or crude blend to mitigate fouling potential.

A method for generating a technical system model executable on a test unit, wherein the test unit and the executable model are designed for real-time-capable testing of a control unit connected to the test unit, and wherein the executable model is constructed from a plurality of executable submodels communicating with each other, wherein each executable submodel has a separate address space and/or is executed on a separate processor or separate processor core when a test of a control unit connected to the test unit is being run.

A method for generating a technical system model executable on a test unit, wherein the test unit and the executable model are designed for real-time-capable testing of a control unit connected to the test unit, and wherein the executable model is constructed from a plurality of executable submodels communicating with each other, wherein each executable submodel has a separate address space and/or is executed on a separate processor or separate processor core when a test of a control unit connected to the test unit is being run.

Systems and methods include a method for multi-segmented oil production. A multi-segmented well production model representing production at a multi-segmented oil production facility is calibrated. The model models production based on well rates and flowing bottom-hole pressure data at various choke settings for multiple flow conditions for each segment of the multi-segmented well. Real-time updates to the well rates and the flowing bottom-hole pressure data are received. Changes to triggers identifying thresholds for identifying production improvements are received. The model is re-calibrated based on the changes to the triggers and the real-time updates. An optimization algorithm is executed to determine new optimal inflow control valve (ICV) settings. Using the re-calibrated multi-segmented well production model, a determination is made whether the new optimal ICV settings improve production. If so, the optimal ICV settings are provided to a control panel for the multi-segmented oil production facility.

A control system includes: a specifying part for specifying a model corresponding to a processing apparatus and a control algorithm that generates a control signal for controlling the processing apparatus; a simulator for simulating the state of the processing apparatus with the model; a first control signal generation part for generating a control signal based on the measurement value by using the control algorithm; a second control signal generation part for generating a control signal based on an output value of the simulator by using the control algorithm; a first adjustment part for adjusting a value of a model parameter included in the model; and a second adjustment part for adjusting a value of a control parameter included in the control algorithm so that an evaluation value calculated for the output value of the simulator becomes closer to a target value.

A method of determining a parameter and state of a system from a time series of a system measurement, comprising using a processor to: a) build an approximate model of the system; b) sample a plurality of approximate system parameters for a current time interval from a posterior probability distribution; c) determine an estimate of the system parameter at the current time interval from the distribution of the plurality of approximate system parameters; d) determine an estimate of the system state at the current time interval given the estimate of the system parameter; e) repeat b) to d) for the next time interval. An apparatus for performing the method is disclosed, and application of the method to drilling and wellbores is discussed.

A plant control system is equipped with a plant, an actuator that controls a state of the plant based on a command value, and an arithmetic device that calculates the command value through the use of state information indicating the state of the plant and that outputs the command value to the actuator. The arithmetic device adopts, as the command value, a value of u obtained by deleting a time differential of y from equations: dy/dt=f(y, u, d, t) and K.sub.4×dy/dt=K.sub.3×y.sub.ref−K.sub.1×y+K.sub.2×(time integral of (y.sub.ref−y))+K.sub.5.