Abstract: A method and a system for simulating physical assets, such as wind farms, solar power plants and manufacturing facilities, comprising the steps of: a) collecting input data; b) setting up a virtual version of a physical asset; c) setting simulation length; d) running simulation according to a simulation algorithm using data collected in step a); and e) generating an output report.

Abstract: A technique for estimating activity of a plurality of muscles is disclosed. In this technique, for each of two or more muscles included in a musculoskeletal body model, a set of time-series data of muscle state change that accompanies motion of a body is acquired. A correlation between the sets of time-series data for a pair of muscles included among the two or more muscles is calculated. An activity of a plurality of muscles included in the musculoskeletal body model in a motion state that is an estimation target is estimated using an objective function including a constraint using the correlation of the sets of time-series data.

Abstract: A technique facilitates examination of a tubing string which may comprise coiled tubing or other types of pipe. A sensor is positioned to monitor a pipe for a magnetic flux leakage signal indicating a defect in the pipe. The sensor outputs data on the magnetic flux leakage signal to a data processing system. Correlations between magnetic flux leakage signals and fatigue life of the pipe may be accessed by the data processing system and these correlations may be used to automatically predict a fatigue life of the pipe. Based on the determined fatigue life, an operation with respect to the pipe is selected and such operation may comprise continued normal use, repair, or removal from service.

Abstract: Methods and systems for generating output of a simulation model in a simulation system are described. In an example, a processor may retrieve observed output data from a memory. The observed output data may be generated based on a simulation operator of a simulation model. The processor may further optimize a generalization error of a distance measure between the observed output data and model output data. The model output data may be generated based on a high-fidelity operator. The processor may further determine a correction operator based on the optimized generalization error of the distance measure. The processor may further append the correction operator to the simulation operator to produce a supplemented operator. The processor may further generate supplemented output data by applying the simulation model with the supplemented operator on a set of inputs.

Abstract: Technologies are provided in embodiments including a memory element to store a payload indicating an action to be performed associated with a remote action request (RAR) and a remote action handler circuit to identify the action to be performed, where the action includes invalidating one or more entries of a translation lookaside buffer (TLB), determine that the logical processor entered an enclave mode during a prior epoch, perform one or more condition checks on control and state pages of the enclave mode, and based on results of the one or more condition checks, adjust one or more variables associated with the logical processor to simulate the logical processor re-entering the enclave mode. Specific embodiments include the remote action handler circuit to invalidate an entry of the TLB based, at least in part, on the results of the one or more condition checks.

Abstract: Techniques that facilitate overlaying and integrating computer aided design drawings with fluid models are presented. For example, a system includes a modeling component, a machine learning component, and a graphical user interface component. The modeling component generates a three-dimensional model of a mechanical device based on a library of stored data elements. The machine learning component predicts one or more characteristics of the mechanical device based on a machine learning process associated with the three-dimensional model. The machine learning component also generates physics modeling data of the mechanical device based on the one or more characteristics of the mechanical device. The graphical user interface component generates, for a display device, a graphical user interface that presents the three-dimensional model and renders the physics modeling data on the three-dimensional model.

Abstract: Biomarker signatures for predicting breast cancer tumor aggressiveness. The signatures are derived from QTA-based parameters from a first population of low risk scores and a second population of high risk scores. The signatures may be expressed in the form log (RS)=Mx+B for linear modeling, or for logistic modeling the signatures may be expressed as either p=ex/[1+ex] where x=Ay+B, or in the form log it(p)=C(PR)+Ay+B, where y is a QTA based parameter.

Abstract: Described herein are a processor and a method of operating the processor to simulate a many-core target machine. The processor includes a plurality of processing cores arranged in a predetermined manner and a global target clock counter (GTCC) configured to count a number of simulated clock cycles in the target machine. A global stall controller (GSC) configured to halt execution of all the processing cores based on a determination of at least one processing core being in a fault condition; and wherein the processor acquires a base clock per instruction (CPI) of a target machine, the CPI corresponding to an average number of clock cycles required by the target machine to execute a single instruction, translates an application of the target machine to a compact executable trace to be executed by the processor, and adjusts a speed of simulation by adjusting an update rate of the global target clock counter.

Abstract: A method and apparatus for the formation of a simplified model. A computer system comprises a simplification system. The simplification system receives a plurality of components from a complex model, determines a number of moments of inertia for each component of the plurality of components, and creates a simplified model using the number of moments of inertia for the each component of the plurality of components, wherein the complex model is a three-dimensional computer model.

Abstract: In an embodiment, a computer-based method for automatically selecting resources to include in a building plan layout is disclosed. The method involves obtaining a set of resource rules that define resources placeable within a building plan layout, obtaining a set of behavioral rules that define the behaviors of the resources, generating a model by evaluating the set of resource rules and the set of behavioral rules, obtaining a configuration, wherein a configuration comprises at least one of building demand, resource permutations, and other simulation attributes, generating at least one set of performance metrics by executing the model with the configuration, storing the at least one set of performance metrics, the model, and the configuration as an entry in a metrics database, selecting an entry from the metrics database, and outputting the entry to a building plan layout generator.

Abstract: A design method of topology optimization for flexible hinge is disclosed in the invention, comprising following steps: step 1: establishing a design model of topology optimization for flexible hinge, setting an outline of flexible hinge with a typical notch as a shape of design domain and defining a rigid region (non-design domain); step 2: establishing a finite element model of topology optimization for flexible hinge; step 3: establishing a mathematical model of topology optimization problem for flexible hinge based on the finite element model; step 4: calculating a sensitivity of topology optimization problem for flexible hinge; step 5: employing an optimization algorithm to solve the topology optimization problem for flexible hinge, updating a design variable and obtaining a final topology result graph; step 6: according to the final topology result graph obtained by the topology optimization, extracting its outline and obtaining a novel flexible hinge by appropriate modification.

Abstract: A method for facilitating the design and manufacturing of a tiltrotor aircraft, including the steps of: determining a compatible mission data set; identifying lift propulsion module components for the compatible mission data set; determining compatible specifications; and generating a design for a lift propulsion module; wherein the lift propulsion module is configured to be connected to at least two different fuselages. There is also a method of designing a tiltrotor aircraft, comprising the step of modularizing a lift propulsion system, wherein the lift propulsion system is configured to be connected to at least two different fuselages. In another aspect, there is a tiltrotor aircraft including a fuselage; and a lift propulsion module, the lift propulsion module including a mounting surface; wherein the lift propulsion module is coupled to the fuselage on the mounting surface. Also included are methods of assembling and systems including a lift propulsion module.

Abstract: The example embodiments are directed to a system and method for simulating an application performance using a test environment associated with an application marketplace where the application can be purchased. In one example, the method may include operating a virtual test environment which includes virtual hardware for testing software, receiving, from the application marketplace, information about an application and operating characteristics of a target installation environment for the application, executing the application via the virtual hardware of the virtual test environment based on the operating characteristics of the target installation environment to generate simulated test results of the application in the target installation environment, and outputting information of the simulated application test results for the target installation environment for display on a display device.

Abstract: A multiple fluid model tool for interdisciplinary fluid modeling is presented. For example, a system includes a modeling component, a machine learning component, and a three-dimensional design component. The modeling component generates a three-dimensional model of a mechanical device based on a library of stored data elements. The machine learning component predicts one or more characteristics of the mechanical device based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional design component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the mechanical device based on the input data and the one or more characteristics of the mechanical device on the three-dimensional model.

Abstract: Predicting hydraulic fracture treatment uses well log data and core data from one well in a given subsurface region to create a petrophysical properties model for the subsurface region. The petrophysical properties model yields fluid volumes and mineral volumes in any given well passing through the subsurface region using only well log data as inputs. The fluid and mineral volumes are used with dipole sonic data from a second well to create an elastic rock properties model for the given subsurface that yields elastic properties in any well passing through the subsurface region using only well log data and mineral and fluid volumes. For wells in the subsurface having only well log data, the petrophysical properties model and the elastic rock properties model are used with the well log data to predict an amount of recoverable hydrocarbons within wells that will respond to hydraulic fracture treatments.

Abstract: Systems and techniques for processing three-dimensional (3D) data are presented. Captured three-dimensional (3D) data associated with a 3D model of an architectural environment is received and at least a portion of the captured 3D data associated with a flat surface is identified. Furthermore, missing data associated with the portion of the captured 3D data is identified and additional 3D data for the missing data is generated based on other data associated with the portion of the captured 3D data.

Abstract: Generally speaking, pursuant to these various embodiments a memory stores prescribed treatment instructions for a particular patient radiation therapy. Those treatment instructions specify clinical metrics for goals pertaining to at least one treatment volume for the particular patient. Either directly or inferentially those clinical metrics are prioritized. A control circuit automatically converts those treatment instructions into resultant radiation treatment plan optimization objectives where the automatic conversion can compatibly comprise a non-convex optimization objective. The control circuit then automatically iteratively optimizes the radiation treatment plan for the particular patient radiation therapy as a function, at least in part, of the aforementioned resultant optimization objectives to thereby produce an optimized radiation treatment plan for the particular patient that a radiation treatment platform then utilizes to administer therapeutic radiation to the particular patient.

Abstract: A LINear particle ACcelerator (LINAC) simulator employs a Monte Carlo-based use of repeated random sampling to produce a simulated result representing use of a particular physical medical-services LINAC with particular corresponding real-world parameters. A browser-based user opportunity permits uploading at least some of those real-world parameters to employ when using the LINAC simulator to produce the simulated result. By one approach the browser-based user opportunity includes, at least in part, an opportunity to upload a file that contains information regarding geometrical positions for the particular physical LINAC. The opportunity to upload the file may, by one approach, presume using a file format that comprises a non-standard file format for the particular physical medical-services LINAC.

Abstract: In a simulation apparatus (100), a selection unit (101) repetitively selects context information individually generated for each of a plurality of cores and indicating an instruction to be executed by a corresponding one of the plurality of cores. A simulation unit (102) simulates execution of the instruction indicated by the context information of a core during a period from when the context information of the core is selected by the selection unit (101) till when the context information of another core is selected by the selection unit (101). An adjustment unit (103) refers to definition information (251) to individually define a length of the period for at least one or some instructions.

Abstract: A disclosed policy introduced effect prediction apparatus includes a memory storing a set of instructions of a policy introduced effect prediction program, and processors programed to execute the instructions to perform a policy introduced effect prediction process. The policy introduced effect prediction process includes calculating at least one calculation model based on first difference data calculated based on time series data of an objective variable and second difference data calculated based on time series data of an explanatory variable, calculating a difference amount of the objective variable by inputting a difference amount of the explanatory variable for introducing a policy into the calculated calculation model, and calculating a predicted value of the objective variable in response to introduction of the policy by adding the calculated difference amount of the objective variable to a predicted value of the objective variable in the absence of the introduction of the policy.