Siemens Industry Software NV

A machine learning module is provided which is trained to generate from a design data record specifying a design variant of a product, a first performance signal quantifying a predictive performance of the design variant and a predictive uncertainty of the predictive performance. A variety of design data records each specifying a design variant of the product is generated. For a respective design data record, the following steps are performed: a first performance signal and a corresponding predictive uncertainty are generated, depending on the predictive uncertainty, a simulation yielding a second performance signal quantifying a simulated performance of the corresponding design variant is either run or skipped, and a performance value is derived from the second performance signal if the simulation is run or, otherwise, from the first performance signal. Depending on the derived performance values, a performance-optimizing design data record is determined and output to control the production plant.

A computer-implemented method for modelling variations of repeating parts of a component is disclosed herein. The method includes providing parameter sets for part configurations of a plurality of different of parts, wherein the parameters of each parameter set respectively define the part configuration of a part; selecting a selection of the part configurations; providing a part model for each part configuration of the selection, wherein the part model relates forces and displacements to locations of the respective part; and building an approximator, wherein the approximator is provided for interpolating the part models to approximate a part model of a part configuration that does not belong to the selection of the part configurations.

A computing platform for simulating an industrial system and a method of managing the simulation are disclosed. The method relates to generating at least one instance of a simulation model of the industrial system. The method includes: generating the instance using a contiguous memory allocator for a dynamic memory region associated with a first processor of the heterogenous processors; enabling a second processor to use the instance in the dynamic memory region based on a memory pointer associated with the address of a copy of the instance; and simulating the industrial system by the second processor by accessing the instance-copy.

A method for generating a test coupon specification for predicting fatigue life of a component includes determining a load condition for the component, providing a component design, and performing a strength analysis of the component design under the load condition determining a critical area of the component and a stress-related parameter of the critical area. The method includes providing a material condition of the component at least for the critical area of the component. To assist an end-user in determining which are optimal tests to be performed in order to obtain most relevant data for fatigue prediction of a specific component, the method also includes providing a material model and providing, as an input to the material model, the stress-related parameter, and the material condition. The material model generates, as an output, a test coupon specification for being tested in a testing machine.

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 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).