Abstract: A method of determining operational performance parameters of a device (e.g., of a vehicle) with device mounted sensors and computer-implemented models. Further, a system, such as a virtual sensor applied to a device, such as a vehicle, for determining operational performance parameters of the device is provided. The system includes device mounted sensors and at least one processing unit configured to execute the computer-implemented method to generate an output parameter set. Measured data may be combined, and calculated parameters may be provided to a Kalman-filter to enable virtual sensing of unobservable parameters.

Abstract: A computer-implemented method for generating unknown-unsafe scenarios for assessing and improving the safety of automated vehicles includes a first process of providing a plurality of different scenarios. To improve the safety of automated vehicles and the efficiency of designing these, a second process of reducing the plurality of different scenarios to scenarios that are unknown-unsafe scenarios is provided.

Abstract: A system and a method for analyzing the motions of a mechanical structure. The System includes (a) accelerometers provided as standard accelerometers to measurement-points of the mechanical structure, (b) at least three accelerometers provided as reference accelerometers to measurement-points of the mechanical structure, (c) at least one shaker being attached to the mechanical structure for moving the structure periodically within a first frequency range, and at least one data processing system being configured to: (d) receiving measurements from the accelerometers at the measurement-points when periodically moving the structure within the first frequency range by the at least one shaker.

Abstract: The invention relates to a method for producing a test data record (12) for an algorithm (1), comprising the following steps: 1.1 a trained artificial intelligence (8) is provided. 1.2 the artificial intelligence (8) is stimulated, particularly using a random signal (11) and/or using a quasi linearity property for visual concepts, and 1.3 the artificial intelligence (8) produces at least one test data record (14), which comprises image data (15) and action regions (16) associated with the image data (1g) and/or sensor data and action regions associated with the sensor data. The invention furthermore relates to a method for operating a system for the automated, image-dependent control of a device and an apparatus for carrying out the aforementioned method. Finally, the invention relates to a control system for a device which comprises such an apparatus, and a computer program product, a computer-readable medium, the production of a data storage device and the use of an artificial intelligence (8).

Abstract: Systems and methods for synchronizing programs for simulation of a technical system. The programs including a first simulation program and a second simulation program. The first simulation program simulates the kinematics of the technical system and the second simulation program simulates a control of the operation of the technical system. The first simulation program outputs values of a first variable at first-time points between first-time intervals according to a first frequency in virtual simulated time and the second simulation program outputs values of a second variable at second time points between second time intervals according to a second frequency in virtual simulated time, the first frequency being lower than the second frequency.

Abstract: A method for retrieval of multi spectral bidirectional reflectance distribution function (BRDF) parameters by using red-green-blue-depth (RGB-D) data includes capturing, by an RGB-D camera, at least one image of one or more objects in a scene. The captured at least one image of the one or more objects includes RGB-D data including color and geometry information of the objects. A processing unit reconstructs the captured at least one image of the one or more objects to one or more 3D reconstructions by using the RGB-D data. A deep neural network classifies the BRDF of a surface of the one or more objects based on the 3D reconstructions. The deep neural network includes an input layer, an output layer, and at least one hidden layer between the input layer and the output layer. The multi spectral BRDF parameters are retrieved by approximating the classified BRDF by using an iterative optimization method.

Abstract: A method and apparatus for estimating electromagnetic forces active in an electric machine. The method includes the steps of: measuring at least one first operation parameter of the electric machine while the electric machine is operated under at least one operational condition, and estimating electromagnetic forces active in an electric machine during operation of the electric machine by multiplying the measured at least one first operation parameter and a respective second operation parameter provided by a stored structural/vibro-acoustic model.

Abstract: A system and method for accelerated simulation setup includes receiving a description of a new problem for simulation, extracting input data and output data of previous simulation results, generating a representation of data based on the extracted input data and output data, and quantifying similarities between the new problem and the extracted input data and output data to identify a candidate simulation for the new problem. A machine learning component infers a solution output for the new problem based on extrapolation or interpolation of outputs of the candidate simulation, thereby conserving resources by eliminating a simulation generation and execution. Alternatively, an efficient simulation setup can be generated using the queried knowledge, input variables, and input parameters corresponding to the candidate simulation.

Abstract: A computer-implemented method of generating a digital twin. To improve the efficiency of handling a digital twin the method includes the steps of: providing a digital twin modular system, the digital twin modular system being characterized by digital twin modules being adapted or being adaptable to digital twin features, the digital twin features relating to at least one of calculation properties, scope of simulation, model architecture, communication safety, accessibility, data storage, encryption functions, resource allocation, hardware requirements, providing a tuning module, wherein the tuning module includes a tuning module parameter set, wherein the tuning module parameter-set includes tuning module parameters respectively corresponding to at least one digital twin feature generating a digital twin by using the tuning module performing the steps of selecting, configuring, and combining digital twin modules of the digital twin modular system according to the tuning module parameters.

Abstract: A method and system for computer-implemented simulation of radar raw data, where the radar raw data are generated for a synthetic MIMO radar system including a transmitter array of several transmitters for transmitting radar signals and a receiver array of several receivers for receiving radar echoes of the radar signals. In this method, ray tracing of a radar signal sent from a preset transmitting position within the transmitter array and received at a preset receiving position within the receiver array is performed based on a 3D model of a virtual area adjacent to the MIMO radar system, where the ray tracing determines propagations of a plurality of rays within the radar signal from the preset transmitting position to the preset receiving position. The propagation of each ray is dependent on a first angle and a second angle describing the direction of a respective ray at the preset transmitting position.

Abstract: Examples of techniques for machine learning-based system architecture determination are described herein. An aspect includes receiving a system architecture specification corresponding to a system design, and a plurality of topological variants of the system architecture specification. Another aspect includes determining a system architecture graph based on the system architecture specification. Another aspect includes classifying, by a neural network-based classifier, each of the topological variants as a feasible architecture or an infeasible architecture based on the system architecture graph. Another aspect includes identifying a subset of the feasible architectures as system design candidates based on performance predictions.

Abstract: A method and a system for fatigue life prediction of additive manufactured components accounting for localized material properties. The method and the system is employed for prediction of fatigue life properties of an additive manufactured element, with a data collection step in which several data points for maximum stress vs. cycles to failure for different given processing steps of the element are collected, with a training step in which a Machine Learning system is trained with the collected data, and with an evaluation step in which the trained Machine Learning system is confronted with actual processing steps and used to predict the fatigue life properties of the element.

Abstract: Provided is a system for safety analysis of failure behavior for a unit including two or more components with at least one inport for receiving failure data and one outport for transmitting failure data, wherein for the analysis of the failures data of the components and/or the unit a safety contract is used, and wherein the safety contract is generated automatically by a model-based safety analysis model comprising separate SAM modules which are related to the components of the unit.

Abstract: A method for controlling an autonomous vehicle to repeatedly follow a same predetermined trajectory comprises: a) receiving a target trajectory signal indicative of the predetermined trajectory; b) generating a control signal adapted to steer the vehicle along the predetermined trajectory; and, for at least one of a number of iterations: c) steering the vehicle along the predetermined trajectory by feeding the control signal to the vehicle; d) measuring an actual trajectory followed by the vehicle in response to being steered according to the control signal; e) recording an actual trajectory signal indicative of the measured actual trajectory; f) using an iterative learning controller to determine an altered control signal using the control signal, the actual trajectory signal and the target trajectory signal. The method allows to improve a tracking performance during a subsequent iteration.

Abstract: Method and apparatus for detecting vibrational and/or acoustic transfers in a mechanical system A method and apparatus for detecting vibro-acoustic transfers in a mechanical system are provided. The method comprises: while operating the mechanical system, acquiring, at each of multiple input points, an input signal indicative of a mechanical load acting on the input point, and acquiring, at a response point, a response signal indicative of a mechanical response; training a neural network device using the input signals acquired at the input points and using the response signal acquired at the response point; and, for each of the input points: providing only the input signal acquired at the respective input point to the trained neural network device and obtaining, from the neural network device, a contribution signal indicative of a predicted contribution of the respective input signal to the response signal.

Abstract: Modeling a multi-component control or actuator system using a fault tree is provided, which solves the problem of ring closures included in a fault tree. To identify ring closures, failure propagation paths are back-traced and is checked if the respective failure propagation path forms a ring closure.

Abstract: A method and system for calibrating an integrated volume acceleration sensor of a loudspeaker, wherein the method includes driving the loudspeaker with a calibration signal and meanwhile generating a sensor output signal by the integrated volume acceleration sensor measuring a volume acceleration over time of a motion element fixed to a moving part of the loudspeaker and/or of the moving part while the loudspeaker is driven with the calibration signal as well as generating a reference output signal by a reference sensor measuring the volume acceleration over time of the motion element and/or of the moving part of the loudspeaker while the loudspeaker is driven with the calibration signal, and additionally includes calculating a calibration value for the integrated volume acceleration sensor based on a ratio of the sensor output signal and the reference output signal and based on a predetermined reference calibration value of the reference sensor.

Abstract: Design of lattice structures for additive manufacturing The present embodiments relate to additive manufacturing, such as three-dimensional printing. By way of introduction, the present embodiments described below include methods and systems for designing, modeling and manufacturing lattice structures. Lattice cells are modeled as parametrized representative unit cell (RUC) models providing a virtual material characterization for a lattice structure. The parametrized RUC models include phase functions for the virtual material characterization and identification of corresponding normalized material curves fit with polynomial functions for each lattice cell structure. Parametrized lattice models with underlying normalized lattice material curves provide design and simulation of true lattice material behavior for use in topology optimization.

Abstract: Methods and Systems for verifying a software program in an integrated-development environment are disclosed. In one embodiment, a method of verifying the software program in the integrated-development environment includes generating a source code of a software program in comprising logging statements based on a specification of the software program. Furthermore, the method includes executing the source code with the logging statements and generating one or more log files during execution of the source code based on the logging statements. Moreover, the method includes generating a representation of the source code in a modeling language based on the one or more log files. The method includes verifying compliance of the source code with the specification by comparing the representation of the source code in the modeling language with the specification in the modeling language.

Abstract: A method, system, apparatus and computer program for identifying loads impacting a vehicle that includes a vehicle body and a suspension system, wherein the method includes acquisition of a system response from a plurality of sensors under dedicated conditions in a test environment, where the said sensors are assigned to the suspension of the vehicle, acquisition of system loads by applying the same dedicated conditions in a simulation environment, generation of a calibration matrix based on data pertaining to the system response and data pertaining to the system loads, acquisition of an operational system response from the plurality of sensors in a test-track situation, and utilization of the acquired operational system response and the calibration matrix for calculating numerical values for the loads impacting the vehicle.