Abstract: A system may include: an input unit providing a data structure storing a computer simulation model package; a first processing unit to store: a binary file or source code comprising a computer simulation model of the technical system; and a text file assigned to the model; a computing unit to derive a first checksum of the binary file or the source code; a second processing unit to store the first checksum in the text file; a generator to generate an instantiation function for verifying the model, run each time the model is instantiated and including: deriving a second checksum from the binary file or source code stored in the package; comparing the second checksum with the first; and generating a comparison result; a third processing unit to store the instantiation function in the data structure as part of the package; and an output to provide the package.

Abstract: A method for controlling distribution of pressure and flow in a water supply system which includes a plurality of pumping stations is provided, including: (a) reading in a computer-assisted hydraulic model of the water supply system, the hydraulic model mapping a time-dependent distribution of pressure and flow, (b) determining resource-optimized pressure and flow target values for the pumping stations for a specified forecast period using the computer-assisted hydraulic model by a first method of optimization, (c) reading in a pumping model behavior for a pumping station, the pumping model mapping an operational behavior of pumping devices of the pumping station, (d) determining resource optimized operating parameters for the pumping devices of the pumping station by the pumping model at a specified time by a second method of optimization, and (e) outputting the resource-optimized operating parameters for controlling the pumping devices of the pumping station.

Abstract: A training data generator includes an interface to read symbols extracted from digital system plans for technical systems, wherein each of the system plans represents the design and/or the functionality of a technical system by of symbols, and the system plans are identical. The training data generator also includes a storage module which is designed to store the extracted symbols, a selection module which is designed to randomly select a symbol sub-quantity of the stored symbols using a random generator, a generator which is designed to generate at least one synthetic system plan on the basis of the selected symbol sub-quantity, and an output module to output the at least one synthetic system plan as training data in order to train a trainable image detection module, wherein the trainable image detection module is designed to generate a digital system plan using an analog system plan of a technical system.

Abstract: 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.

Abstract: A process-engineering plant module is provided including plant components configured to carry out a process-engineering process, wherein a first chemical substance is changed, a sensor, configured to detect a sensor value of a physical quantity of the first chemical substance in a plant component, a simulation unit configured to simulate a chemical reaction, a temperature change and/or a mass transfer for a second chemical substance in a computer-aided manner as a function of the sensor value, wherein the first chemical substance and the second chemical substance are the same or different, and to output a simulated temperature value and a simulated mole fraction of the second chemical substance, and a control unit, which is configured to control actuators of the plant components. A hybrid commissioning of a process-engineering plant, in which a computer-aided simulation of the process-engineering process is carried out in parallel with a cold-commissioning is also provided.

Abstract: A computer-implemented method for manufacturing or controlling a technical system includes the method steps: (a) inputting a sample of parameter sets suitable for manufacturing or controlling the technical system, with a feasibility identifier assigned to each of the parameter sets, wherein the feasibility identifier marks each parameter set either as technically feasible or technically non-feasible or erroneous in terms of manufacturing or controlling the technical system, (b) generating a computerized surrogate model for the technical system based on the respective parameter sets of the sample, which are marked as technically feasible, by means of a regression method, (c) determining an optimized parameter set based on the surrogate model by means of a computerized optimization method, and (d) outputting the optimized parameter set for manufacturing or controlling the technical system.

Abstract: A method to orchestrate configurations of simulations based on digital twin models of modular plants such that the configurations of the model-based simulations are generated and deployed automatically, is proposed and based on a logical “System Structure and Parameterization” functionality including a “Functional Mock-up Interface”-functionality combined with a “Functional Mock-up Unit”-functionality to generate for distributed operational-technology-applications of the modular plants simulated model components including assignment rules for automation data captured due to automation of the plants and assigned to the distributed operational-technology-applications, and deploying the simulated model components on the distributed operational-technology-applications by using the SSP-functionality with “Functional Mock-up Unit”-functionalities as part of the FMI-functionality for the distributed operational-technology-applications and implementing for the distributed operational-technology-applications and as pa

Abstract: The disclosure pertains to optimizing a charging strategy for one or more charging stations to which one or more electric vehicles are connected. The charging strategy is optimized taking into account power generation within a decentral energy system, also referred to as microgrid.

Abstract: An apparatus, such as a virtual sensor, for measuring a value of a physical variable of a technical system includes a generative machine learning model that is trained, e.g., on the basis of generative adversarial networks (GANs for short), in such a way as to take at least one value of a first physical variable of a technical system as a basis for generating and outputting at least one value of a second physical variable of the technical system. The apparatus is configured in such a way as to use the generative machine learning model to generate and output a value of a second physical variable of the technical system on the basis of a measured value of a first physical variable of the technical system.

Abstract: A method for controlling distribution of pressure and flow in a water supply system which includes a plurality of pumping stations is provided, including: (a) reading in a computer-assisted hydraulic model of the water supply system, the hydraulic model mapping a time-dependent distribution of pressure and flow, (b) determining resource-optimized pressure and flow target values for the pumping stations for a specified forecast period using the computer-assisted hydraulic model by a first method of optimization, (c) reading in a pumping model behavior for a pumping station, the pumping model mapping an operational behavior of pumping devices of the pumping station, (d) determining resource optimized operating parameters for the pumping devices of the pumping station by the pumping model at a specified time by a second method of optimization, and (e) outputting the resource optimized operating parameters for controlling the pumping devices of the pumping station.

Abstract: A training data generator includes an interface to read symbols extracted from digital system plans for technical systems, wherein each of the system plans represents the design and/or the functionality of a technical system by of symbols, and the system plans are identical. The training data generator also includes a storage module which is designed to store the extracted symbols, a selection module which is designed to randomly select a symbol sub-quantity of the stored symbols using a random generator, a generator which is designed to generate at least one synthetic system plan on the basis of the selected symbol sub-quantity, and an output module to output the at least one synthetic system plan as training data in order to train a trainable image detection module, wherein the trainable image detection module is designed to generate a digital system plan using an analog system plan of a technical system.

Abstract: 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.

Abstract: An aircraft that includes a helicopter drone on which a 3D scanner is mounted via an actively rotatable joint is provided. The 3D scanner has at least one high-resolution camera for recording a multiplicity of overlapping images of the object from different recording positions and recording directions, so that comparison of the images allows a position and orientation of the 3D scanner relative to the object to be ascertained. In addition, the aircraft has a coordination device for coordinated control of the 3D scanner, the joint and the helicopter drone. The system for damage analysis has an aircraft and an image processing module generating a data representation of a surface profile of the object on the basis of the recorded images. In addition, the system includes a rating device for checking the surface profile and for outputting a damage statement on the basis of the check.

Abstract: Provided is a method and an apparatus for computer-implemented traffic control of motor vehicles in a predetermined area, in which, at predetermined intervals, respectively: values of traffic parameters are ascertained in the predetermined area by way of data capture, wherein at least some of the traffic parameters relate to the motor vehicles traveling in the predetermined area and the traffic parameters of a respective motor vehicle include its current position, direction of travel and speed; a set of optimized traffic control actions, which include the adjustment of variable traffic signaling devices, is determined by an optimization using a learned data-driven model and the optimized traffic control actions are carried out, wherein the optimization takes account of predicted air quality values and the data-driven model is learned by training data from a simulation.

Abstract: Provided is a control device for a production module having a data memory for storing operational settings of production modules and restrictions, which must be complied with by at least some of the operational settings. A settings management module is used to determine the external operational setting of an adjacent production module on which a local operational setting of the production module is dependent on the basis of a common restriction. An optimization module is also provided and has a local assessment function, which assesses the local operational setting, and a further assessment function which assesses noncompliance with the common restriction.

Abstract: An aircraft that includes a helicopter drone on which a 3D scanner is mounted via an actively rotatable joint is provided. The 3D scanner has at least one high-resolution camera for recording a multiplicity of overlapping images of the object from different recording positions and recording directions, so that comparison of the images allows a position and orientation of the 3D scanner relative to the object to be ascertained. In addition, the aircraft has a coordination device for coordinated control of the 3D scanner, the joint and the helicopter drone. The system for damage analysis has an aircraft and an image processing module generating a data representation of a surface profile of the object on the basis of the recorded images. In addition, the system includes a rating device for checking the surface profile and for outputting a damage statement on the basis of the check.

Abstract: Provided is a control device for a production module having a data memory for storing operational settings of production modules and restrictions, which must be complied with by at least some of the operational settings. A settings management module is used to determine the external operational setting of an adjacent production module on which a local operational setting of the production module is dependent on the basis of a common restriction. An optimization module is also provided and has a local assessment function, which assesses the local operational setting, and a further assessment function which assesses noncompliance with the common restriction.

Abstract: The rotational speed of the drum of an ore mill may be controlled variably over time. By rotating the drum during a first time interval at high speed, especially hard or dense particles are broken up by tumbling. At the same time, the discharge characteristics of the mill are adversely affected. In a subsequent second time interval, the drum is rotated at a slower speed, and the material is discharged more effectively, whereas the tumbling movement inside the mill is not achieved. The combination of said different modes of operation within short time periods in continuous operation may improve both the comminution as a result of a tumbling motion of the material and also the discharge of the ground material. By regulating the rotational speed with different target values within short time windows, different requirements for the movement behavior of the material to be ground and for the discharge characteristics of the ground material can be simultaneously optimized.

Abstract: A method implemented in a computer system for automatically establishing a data record from two technical drawings, where the data record characterizes the two technical drawings that include symbols and lines connecting the symbols.

Abstract: A method for automatically creating a data set, which characterizes a technical drawing having symbols and lines connecting the symbols, from the technical drawing.