Siemens Industry Software NV

A computer-implemented method of modifying a finite element mesh. The method includes providing an original-input-orphan-mesh, selecting and extracting at least a part of the original-input-orphan-mesh as an orphan-element-patch-object, generating faces on the orphan-element-patch-object as a faces-on-mesh-object geometry, generating a new mesh patch element based on the faces-on-mesh-object-geometry and at least one changed meshing-parameter. The changed meshing-parameter is assigned to generate a new mesh patch element that is different to the corresponding original-input-orphan-mesh. The method further includes generating an amended orphan mesh by replacing the orphan-element-patch-object of the original-input-orphan-mesh by the new mesh patch element.

Sensitivity analysis of failure events associated with components of a technical system is provided. It is possible to determine, for a plurality of components of a technical system configured in accordance with at least one initial design, importance values which are indicative of a dependency of at least one non-functional specification of a plurality of non-functional specifications of the technical system configured in accordance with the at least one initial design on a change of the technical system with respect to the components of the plurality of components. The method further includes determining a further design of the technical system based on the at least one initial design, the importance values, and a predefined function describing a joint quality score of the plurality of non-functional specifications for the technical system being configured in accordance with a respective design of the technical system.

A method and a device for configuring a controller and to a method and a controller for controlling a technical system by means of a data-based control model is provided, in particular a model based on reinforcement learning. This data-based control model is configured using a model-predictive control model. Configuration parameters of the data-based control model are set by mapping the model-predictive control model onto the data-based control model in such a way that the data-based control model reproduces the output data of the model predictive control model depending on state data of the technical system read in, and determines optimized control parameters configured in this way. A computationally intensive training procedure for configuring the data-based control model can thus be avoided.

A system, device, and method for testing autonomous vehicles are disclosed. A device for testing a plurality of components of at least one autonomous vehicle includes a communication module including a set of interfaces communicatively couplable to the plurality of components of the at least one autonomous vehicle. The device also includes a processing unit communicatively coupled to the communication module and capable of mapping simulation instances to the set of interfaces of the communication module. The simulation instances include simulated sensor data and/or vehicle dynamics data reflecting behavior of the at least one autonomous vehicle.

A computer-implemented method for generating domain specific training data for a large language model includes providing a domain specific ontology relating to the domain, providing domain specific information relating to the domain, and processing the domain specific information in a data processing-pipeline for structuring data for training of the large language model. The domain specific ontology is provided as a recognition pattern in a step of the data processing-pipeline, such that the structured training data includes domain specific ontology annotations.

A computer-implemented method for modeling acoustics of an object as a numerical simulation model in an unbounded domain to determine a field variable within a control volume of the unbounded domain includes providing a coordinate system mapping positions in the control volume. A geometrical specification of a sound source is provided in the control volume based on the coordinate system. To improve efficiency of numerically modelling transient acoustics wave propagation phenomena in unbounded domains, a convex shape is constructed around the sound source using Quickhull algorithm, infinite elements are extruded starting from the convex shape, and the coordinate system is transformed into a field variable coordinate system by mapping a radial coordinate of the coordinate system to an auxiliary coordinate extending from the convex shape to the infinite elements. Field shape functions are constructed using the auxiliary coordinate, and the field variable is determined by solving the numerical simulation model.

A method and system for determining the static stiffness of a body structure from dynamic data are disclosed. The method and system include providing dynamic data and defining flexible-body modes of the dynamic data of the body structure. To overcome the limitations of conventional methods and systems, the method and system further include: performing a modal decomposition of all defined flexible-body modes into contributions of rigid-body modes and a residual term. The modal decomposition of the body structure is defined as Formula (I), wherein R j is a residual term for the j th flexible mode, such that the residual term results as free of inertial effects. The method and system further include determining the residual term R j from the modal decomposition and determining the static stiffness from the residual terms Rj.

The invention relates to a computer-implemented method computer product, computer-readable medium, and system for determining acoustic parameters of an object's (OBJ) emission and/or scattering within a predetermined frequency range (FRG), by applying Boundary Element Method (BEM) to the object, comprising splitting said object's (OBJ) surface into surface elements (ESF) and assigning boundary conditions (BCD) to said surface elements (ESF), further comprising •Providing polynomial shape functions (SFC) over each of said elements (ESF) for mapping geometry and acoustic parameters to said elements (ESF), wherein for each surface element (ESF) the order (SFO) of said shape functions (SFC) is determined by an adaptivity module (ADM), •Assembling the elements (ESF) of said surface by recombining the shape functions (SFC) obtaining a system matrix (SMX), •Solving said system matrix (SMX), •Determining said acoustic parameters (PRT) from said shape functions (SFC).

Method of determining acoustic parameters of an object's (OBJ) emission and/or scattering, in particular for improving acoustic properties of said object (OBJ), comprising: (a) defining a model (MDL) including said object (OBJ), a sound source (SCR), and a surrounding area, (b) processing said model (MDL) obtaining a result (RST), (c) post-processing the result (RST) by assigning to said field points (PTS) at least one parameter (PRM) determined from calculating the Helmholtz-Kirchhoff integral from said result (RST). To improve the accuracy and efficiency the post-processing comprises the additional steps: (d) identifying field points (PTS) as near field singularity field points (NEP) of potential lower result (RST) accuracy (ACR), (c) determining for said near field singularity field points (NEP) respectively an associated model mesh element (AME), by determining a local projection from said near field singularity field point (NEP) to the object's (OBJ) surface by calculating a minimum normal distance (MND) to the object's (OBJ) surface, wherein the associated model mesh element (AME) being the touchdown point of the local projection, (f) determining for said near field singularity field points (NEP) respectively a ratio (RTO) of the minimum normal distance (MND) to said element size (ESZ) of the associated model mesh element (AME), (g) calculating the Helmholtz-Kirchhoff integral by: (g11) providing a relation (PCR) of quadrature order (QOD) and said ratio (RTO), (g2) determine the respective quadrature order (QOD) by applying said relation (PCR), (g3) calculating the Helmholtz-Kirchhoff integral from said result (RST).

A method of operating a vehicle includes: sensing the vehicle's surroundings and vehicle's operating parameters by sensors; supporting the vehicle's driving by a first autonomous driving control receiving the sensed surroundings and the sensed operating parameters and the first autonomous driving control generating vehicle driving commands for controlling the vehicle's driving; simulating the vehicle operation by a digital twin of the vehicle that includes a second autonomous driving control generating vehicle operation control commands for controlling the digital twin's driving; aligning the vehicle simulation with the vehicle's driving by feedback of the sensed vehicle's surroundings and the sensed vehicle's operating parameters; and evaluating a detachment criterium and changing the operating mode of the vehicle simulation from being aligned with the vehicle's driving to a detachment of the simulation allowing a deviation of the simulated values to at least one of the sensed vehicle's surroundings and/or sensed vehicle's operating parameters.