1593 results about "Solver" patented technology

An energy management system uses an expert engine and a numerical solver to determine an optimal manner of using and controlling the various energy consumption, producing and storage equipment in a plant/communities in order to for example reduce energy costs within the plant, and is especially applicable to plants that require or that are capable of using and/or producing different types of energy at different times. The energy management system operates the various energy manufacturing and energy usage components of the plant to minimize the cost of energy over time, or at various different times, while still meeting certain constraints or requirements within the operational system, such as producing a certain amount of heat or cooling, a certain power level, a certain level of production, etc. In some cases, the energy management system may cause the operational equipment of the plant to produce unneeded energy that can be stored until a later time and then used, or that can be sold back to a public utility, for example, so as to reduce the overall cost of energy within the plant.

An energy management system uses an expert engine and a numerical solver to determine an optimal manner of using and controlling the various energy consumption, producing and storage equipment in a plant/communities in order to for example reduce energy costs within the plant, and is especially applicable to plants that require or that are capable of using and/or producing different types of energy at different times. The energy management system operates the various energy manufacturing and energy usage components of the plant to minimize the cost of energy over time, or at various different times, while still meeting certain constraints or requirements within the operational system, such as producing a certain amount of heat or cooling, a certain power level, a certain level of production, etc. In some cases, the energy management system may cause the operational equipment of the plant to produce unneeded energy that can be stored until a later time and then used, or that can be sold back to a public utility, for example, so as to reduce the overall cost of energy within the plant.

A computer-implemented decision-support tool serves as a solver to generate a projected supply planning (PSP) or estimated supply planning (ESP) match between existing assets and demands across multiple manufacturing facilities within the boundaries established by the manufacturing specifications and process flows and business policies to determine what supply can be provided over what time-frame by manufacturing and establishes a set of actions or guidelines for manufacturing to incorporate into their manufacturing execution system to ensure that the delivery commitments are met in a timely fashion. The PSP or ESP tool resides within a data provider tool that pulls the required production and distribution information. PSP matching is driven directly by user-supplied guidelines on how to flow or flush assets "forward" to some inventory or holding point. After the supply plan is created, the analyst compares this plan against an expected demand profile.

The power flow model of the multiterminal voltage-source converter-based high voltage DC (M-VSC-HVDC) transmission system for large-scale power systems is studied. The mathematical model is derived using the d-q axis decomposition of HVDC's control parameter. The developed model can be applied to all existing shunt voltage-source converter (VSC) based controllers, including Static Synchronous Compensator (STATCOM), point-to-point HVDC system, back-to-back HVDC system and multiterminal HVDC system. A unified procedure is developed for incorporating the proposed model into the conventional Newton-Raphson power flow solver. The IEEE 300-bus test system embedded with multiple HVDC transmission systems under different configurations are investigated. Simulation results reveal that the proposed model is effective and accuracy in meeting various control objectives.

A method for problem solving in a computer system includes an applications module for sending a problem statement to a complexity module, which configures a solving module with configuration parameters and also determines expected problem solver behavior. The solving module selects a set of parameter configuration vectors, determines a set of search space points, performs a partial search based on the parameter configuration vectors, and determines actual problem solver behavior. The solving module then determines whether a problem solution has been found, whether to perform a solver iteration step or request a complexity module to perform an adaptation step.

A computer implemented Availability Checking Tool enabling tool users to execute within a common work environment, from common enterprise data, and considering assets and demands across multiple order management systems and manufacturing facilities within boundaries established by manufacturing specifications and process flows and business policies. The tool receives orders from multiple demand sources or ordering systems. Tool users can easily maintain a synergistic relationship between multiple ordering systems. A demand configurator coordinates product requests based on information from the demand source according to certain rules and priorities assigned to the product requests. A material resource engine manipulates data from the demand configurator and the rules to provide material supply information. A solver manipulates the material supply information from the resource engine and the rules to provide optimized product availability information. Thus, customer business rule level definitions are supported to provide the tool users with the power to micro-manage, optimally, enterprise assets and demands.

An optimization and control system for a utility plant that uses fan based air cooled condensers controls the operation of the power generation system at the plant in conjunction with the operation of the air cooled condensers so as to run the power plant at an optimum operating point associated with minimizing or reducing the cost of each kilowatt-hour of energy or other useful energy produced by the plant. The optimization and control system includes an optimizer having a numerical solver that determines values for a set of control variables associated with an optimal operating point of the plant and an expert system that oversees and modifies the control variable settings prior to providing these settings to a plant controller. The numerical solver uses an objective function and one or more models of plant equipment to determine the operating point of the plant that minimizes the cost per unit of useful energy generated by the plant. As part of determining the optimal plant operating point, the numerical solver may determine the number of fans to run within the air cooled condensers of the plant and/or the speed of the fans to use in the air cooled condensers in conjunction with the amount of fuel to burn in the boiler, the desired temperature of the steam at the input of the steam turbine, etc., all required to produce a given amount of power (load demand) at the particular environmental conditions currently experienced at the plant. The expert system may modify these outputs by determining which fans to actually use at any particular time based on, for example, the availability of or the operational status of the fans, the wear of the fans and fan motors, etc.

Embodiments of the present invention relate to a method of providing an automated public Turing test to a client display system. The method includes providing an image having a plurality of random characters, as well as providing a browser code to the client, whereby the browser code is adapted to restrict display of the image to only a predetermined portion of the image. The method further includes detecting a client response to receiving the predetermined portion of said image.

A method for predicting localized damage and naturally occurring fractures in a subsurface region is provided. This invention uses a hybrid FEM-DEM (i.e. finite-discrete element) framework combined with a fracture risking analysis and fracture initiation and propagation criteria, to model the transition of rock from a state of continuum to discontinuum. The risking analysis combines results from other natural fracture prediction tools (e.g. displacement discontinuity method, restoration analyses, curvature analysis, analytical solutions, continuum analysis) to augment FEM-DEM solutions, such as by providing remote and local boundary conditions and identifying potential regions of anticipated damage and fracturing. Natural fractures and damage information is extracted from the modeling results and may be used directly for predictions or used as input into other fracture analysis tools or techniques. The FEM-DEM and risking techniques can be incorporated into a variety of numerical simulation software packages that use a finite-discrete method solver.

A computer implemented decision support tool serves as a vehicle to enable a user to execute within a common work environment, from common production information files, and at the discretion of the user one of three types of matching between existing assets and demands across multiple manufacturing facilities within boundaries established by manufacturing specifications and process flows and business policies. The tool provides an environment which permits the user to easily gain the advantages of a synergistic relationship between the three types of matching. The tool directly supports three types of matching: (1) material requirements planning (MRP) type of matching, (2) best can do (BCD) type of matching, and (3) projected supply planning (PSP) type of matching.

The present invention provides computer implemented methodology that permits the safe landing and recovery of rotorcraft following engine failure. With this invention successful autorotations may be performed from well within the unsafe operating area of the height-velocity profile of a helicopter by employing the fast and robust real-time trajectory optimization algorithm that commands control motion through an intuitive pilot display, or directly in the case of autonomous rotorcraft. The algorithm generates optimal trajectories and control commands via the direct-collocation optimization method, solved using a nonlinear programming problem solver. The control inputs computed are collective pitch and aircraft pitch, which are easily tracked and manipulated by the pilot or converted to control actuator commands for automated operation during autorotation in the case of an autonomous rotorcraft. The formulation of the optimal control problem has been carefully tailored so the solutions resemble those of an expert pilot, accounting for the performance limitations of the rotorcraft and safety concerns.

Systems and methods for interactive image compositing may integrate image searching using visual search criteria (e.g., color, composition, tonal distribution, or lighting effects), non-destructive image compositing, and high-performance rendering using a fast gradient solver to provide an efficient workflow for users. An image compositing application, executable by a CPU and/or GPU, may employ a sketch-and-refine approach, whereby a user draws a rough perimeter around an object of interest in an image and (following an initial application of the fast gradient solver to a lower-resolution version of the image) receives a preview of how it would fit into a composition. The fast gradient solver may differentiate between the object and its background by applying artificial intelligence techniques and/or dependent on user-supplied hints. In a second stage, the fast gradient solver may refine the solution for a final rendering of the composite image by operating on successively higher-resolution versions of the image.

A ride matching method is disclosed herein. The ride matching method addresses many of the limitations associated with traditional dynamic ride matching applications. The method is unique in its ability to accept trips with schedules that cannot be expressed in terms of a simple recurrence pattern (e.g. Monday thru Friday work schedule). It can handle one-time and occasional trips. It is also distinct in its use of spatial analysis techniques to locate matches. Specifically, the use of a shortest path solver enables the ride matching method to perform a search along the path of a user's trip, in addition to the customary radial search around the endpoints. The shortest path solver is also used to calculate the driving distance between the user and a match. This provides a more accurate measurement than the straight-line distance used by other methods, especially in the presence of barriers.

The invention provides a vehicle autonomous parking path programming method used for multiple parking scenes. The method is used for automatically parking a vehicle in a parking space through an autonomous parking system when the autonomous parking system detects the available parking space. The method includes the steps that target parking space information is detected, and a parking scene is determined; the initial state and target state of the to-be-parked vehicle are determined; a vehicle kinematics differential equation is established; state variables and control variables of the vehicle are segmented, equidistance sampling is performed on each segment according to certain time step, and to-be-optimized variables are obtained; an equality constraint, boundary constraints and inequality constraints of the to-be-optimized variables are formed; motion range constraints of the to-be-parked vehicle are formed according to the motion range limit in the parking process of the vehicle; an optimization objective is determined, and an objective function is established; and by means of a nonlinear programming solver, an optimal solution of a parking path is obtained. The vehicle autonomous parking path programming method is suitable for the multiple parking scenes, the design is reasonable, abundant information can be provided so as to control autonomous parking of the vehicle, and the security coefficient is high.

A method and system for equivalence checking of logical circuits using iterative circuit reduction and satisfiability techniques provide improved performance in computer-based verification and design tools. By intertwining a structural satisfiability solver and binary decision diagram functional circuit reduction method, computer-based tools can make more efficient use of memory and decrease computation time required to equivalence check large logical networks. Using the circuit reduction technique back-to-back with the simulation technique, optimum local and global circuit reduction are simultaneously achieved. By iterating between the structural and functional techniques, and adjusting the size of sub-networks being analyzed within a larger network, sub-networks can be reduced or eliminated, decreasing the amount of memory required to represent the next larger inclusive network.

A flexible and extensible automated design partitioning mechanism that facilitates simulation sessions employing two or more simulators is provided. A simulation backplane includes partitioning logic that identifies the design blocks of an overall design pertaining to each of a plurality of simulators. Once the partitions have been identified, nets that cross simulator boundaries (e.g., mixed nets) are determined and inter-simulator connectivity information is generated for the simulators. According to one aspect of the present invention, the partitioning logic is able to accomodate arbitrary (e.g., instance-based) partitioning. A design source expressed in a design representation upon which a first simulator may operate is received. Design blocks to be partitioned to each of a plurality of solvers are identified based upon one or more partitioning directives and the design source. A first instance of a cell is assigned to a first solver and a second instance of the cell is assigned to a second solver. Netlist like information is generated for those of the design blocks that are partitioned to a non-design source solver. To accomodate a folded representation of a design block containing the first or second instance of the cell, one or more additional cells are created. According to another aspect of the present invention, name space mapping is retained across all simulators. A design source upon which a first simulator may operate is read. Based upon a set of rules, a primary partition that is to be simulated by a first solver is identified. The primary partition includes a top cell of the design representation. Additionally, a secondary partition that is to be simulated by a second solver is identified. Subsequently, netlist information is generated for the second solver while retaining name space mapping in the secondary partition by adding one or more levels of hierarchy so as to include information about the top cell in the secondary partition.

The parallel kinematic machine (PKM) trajectory planning method is operable via a data-driven neuro-fuzzy multistage-based system. Offline planning based on robot kinematic and dynamic models, including actuators, is performed to generate a large dataset of trajectories, covering most of the robot workspace and minimizing time and energy, while avoiding singularities and limits on joint angles, rates, accelerations and torques. The method implements an augmented Lagrangian solver on a decoupled form of the PKM dynamics in order to solve the resulting non-linear constrained optimal control problem. Using outcomes of the offline-planning, the data-driven neuro-fuzzy inference system is built to learn, capture to and optimize the desired dynamic behavior of the PKM. The optimized system is used to achieve near-optimal online planning with a reasonable time complexity. The effectiveness of the method is illustrated through a set of simulation experiments proving the technique on a 2-degrees of freedom planar PKM.

The invention provides a redundant manipulator motion planning method which comprises the following steps that: (1) an upper computer analyzes the inverse kinematics of a manipulator on a velocity layer through quadratic optimization, the designed minimum performance index can be velocity norm, repetitive motion or kinetic energy and is bound by a velocity jacobian equation, an inequation and a joint angular velocity limit, and the angular velocity limit changes with a joint angle; (2) the quadratic optimization of step (1) is optimized into a quadratic programming problem; (3) the quadratic programming problem in step (2) is calculated by a linear variational inequation primal-dual neural network solver or a numerical method; and (4) the calculation result in step (3) is transmitted to a lower computer controller to drive the manipulator to move. The redundant manipulator motion planning method is based on the primal-dual neural network of the linear variational inequation, has global exponential convergence, does not involve matrix inversion and other complicated operations, greatly improves the calculation efficiency, and simultaneously has strong real-time performance, and can adapt to the changes to the joint angular velocity limit.

The present invention provides a mixed integer cone programming based intelligent distribution system synthetic voltage reactive power optimization method. The method comprises: inputting a distribution system structure and a parameter of a distribution system; establishing a time sequence optimization model of a distribution system synthetic voltage reactive power control problem considering various types of adjustment means; converting the established model into a mixed integer second-order cone model; solving the obtained mixed integer second-order cone model by using a mathematical solver capable of solving mixed integer second-order cone programming; and outputting a solution result. The method provided by the present invention greatly reduces solving difficulty and facilitates performing solution by using a solving tool, so that a complex mixed integer non-linear programming problem can be solved, cumbersome iteration and a large number of tests are avoided, and the calculation speed is greatly improved.

Proposed is a method, implemented in software, for estimating fault state of an apparatus outfitted with sensors. At each execution period the method processes sensor data from the apparatus to obtain a set of parity parameters, which are further used for estimating fault state. The estimation method formulates a convex optimization problem for each fault hypothesis and employs a convex solver to compute fault parameter estimates and fault likelihoods for each fault hypothesis. The highest likelihoods and corresponding parameter estimates are transmitted to a display device or an automated decision and control system. The obtained accurate estimate of fault state can be used to improve safety, performance, or maintenance processes for the apparatus.

A method and system locates a position of a transceiver in a cooperative relay network of nodes. A primary node broadcasts a range request (RREQ) message. A target node, in response to receiving the RREQ message, broadcasts a range reply (RREP) message, wherein the RREP message includes a time difference between receiving the RREQ message and broadcasting the RREP message. A secondary node, in response to receiving the RREQ message and the RREP message, broadcasts a range data (RDAT) message, wherein the RDAT message includes a time difference between receiving the RREQ message and the RREP message. Then, a position solver can determine a location of the target node based on the time differences in the RREP message and the RDAT message.

A high integrity protection system (HIPS) for the protection of a piping system downstream of a wellhead has an inlet connected to the wellhead and an outlet connected to the downstream piping system and includes: two sets of series-connected surface safety valves (SSVs) in fluid communication with the inlet, the two sets being in parallel fluid flow relation to each other, each set of SSVs consisting of two SSVs in series, either one or both of the two sets of SSVs operable as a flowpath for fluids entering the inlet and passing through the HIPS outlet to the piping system; two vent control valves (VCVs), each of which is connected to piping intermediate each of the two series-connected SSVs, each of the VCVs being in fluid flow relation to each other, each set of SSVs consisting of SSVs in series, either one or both of the two sets of SSVs operable as a flowpath for fluids entering the inlet and passing through the HIPS outlet to the piping system; two vent control valves (VCVs), each of which is connected to piping intermediate each of the two series connected SSVs, each of the VCVs being in fluid communication with a vent line, whereby, upon opening of a VCV, process pressure between the two SSVs is vented; a signal-generating safety logic solver, in accordance with preprogrammed safety and operational protocols; and pressure sensing transmitters attached to piping upstream of the HIPS outlet. The HIPS performs independent, tight shut-off tests of each of the series-connected SSV sets and all valves are closed in the event of an electrical and/or hydraulic system failure.

The computational efficiency of Finite Element Methods (FEM) on parallel architectures is typically severely limited by sparse iterative solvers. Standard iterative solvers are based on sequential steps of global algebraic operations, which limit their parallel efficiency, and prior art techniques exploit sophisticated programming techniques tailored to specific CPU architectures to improve performance. The inventors present a FEM Multigrid Gaussian Belief Propagation (FMGaBP) technique that eliminates global algebraic operations and sparse data-structures based upon reformulating the variational FEM into a probabilistic inference problem based upon graphical models. Further, the inventors present new formulations for FMGaBP, which further enhance its computation and communication complexities where the parallel features of FMGaBP are leveraged to multicore architectures.

The invention provides a repetitive motion planning method for a redundant manipulator, which comprises the following steps of: 1) resolving a manipulator repetitive motion scheme on an acceleration layer by adopting quadratic model optimization through an upper computer, designing the minimum performance index as repetitive motion, and restraining by an acceleration Jacobian equation, a joint angle limit, a joint speed limit and a joint acceleration limit; 2) converting the quadratic model optimization in the step 1) into standard quadratic programming; 3) solving the standard quadratic programming in the step 2) by using a linear projection equation-based primal-dual neural-network solver or quadratic programming numerical method; and 4) transmitting a solving result in the step 3) to acontroller of a lower computer for driving the manipulator to move. The method realizes the repetitive motion of the manipulator on the acceleration layer, has good control effect on the redundant manipulator inconvenient to control, and can effectively prevent the manipulator from exceeding the limits and being physically damaged according to various joint limits.