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US 2023/0419086 A1Published application
System and method for processing material properties of structural materials
AssigneeTotal Materia AG
InventorsViktor Pocajt, Davor Antanasijevic
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Abstract
A computer implemented method for processing material properties of structural materials, the method comprising: generating training dataset(s) for training a machine learning algorithm for determining values(s) of specific target material property(s) of an assessment material; training a machine learning algorithm for determining value(s) of specific target material property(s) of an assessment material using the training dataset; and determining value(s) of specific target material property(s) of an assessment material using the trained machine learning model.
Claims15
A computer implemented method for processing material properties of structural materials, the method comprising:
- generating one or more training datasets for training one or more machine learning algorithms for determining values of one or more target material properties of assessment materials, a training dataset being generated specifically for each of the one or more target material properties, the generation of training datasets comprising the steps:
- providing a database comprising data records indicative of input values of material properties of a multitude of structural materials, comprising at least chemical composition and processing parameter(s) of the multitude structural materials;
- classifying the data records into a plurality of classes according to the input value(s) of one or more of the material properties, at least according to the values of chemical composition and processing parameter(s);
- within each of the plurality of classes, extracting target-relevant material properties from the data records having a dependency relationship with the specific target material property(s);
- and
- generating at least one training dataset corresponding to one or more of the plurality of classes using values of the extracted target-relevant material properties and corresponding values of the specific target material property(s);
- training of one or more machine learning algorithms for one or more of the plurality of classes, each machine learning algorithm being trained for determining a specific target material property of assessment materials using one of the plurality of training datasets;
- and
- determining output value(s) of the specific target material property(s) of an assessment material using one of the plurality of machine learning algorithms trained using a training dataset corresponding to the class of the assessment material and trained for determining the specific target material property.
6 more elements
A system for processing material properties of structural materials comprising:
- a data storage device for storing a database comprising data records indicative of input values of material properties of a multitude of structural materials, and for storing training dataset(s);
- a computing device communicatively connected to the data storage device;
- an input interface for receiving input indicative of value(s) of a first set of material properties of the assessment material and/or for receiving a selection of a machine learning model;
- and
- an output interface for outputting output data indicative of values of target material property(s) of an assessment material,
- wherein the system is configured to carry out a method comprising:
- generating one or more training datasets for training one or more machine learning algorithms for determining values of one or more target material properties of assessment materials, a training dataset being generated specifically for each of the one or more target material properties, the generation of training datasets comprising the steps:
- providing a database comprising data records indicative of input values of material properties of a multitude of structural materials, comprising at least chemical composition and processing parameter(s) of the multitude structural materials;
- classifying the data records into a plurality of classes according to the input value(s) of one or more of the material properties, at least according to the values of chemical composition and processing parameter(s);
- within each of the plurality of classes, extracting target-relevant material properties from the data records having a dependency relationship with the specific target material property(s);
- and
- generating at least one training dataset corresponding to one or more of the plurality of classes using values of the extracted target-relevant material properties and corresponding values of the specific target material property(s);
- training of one or more machine learning algorithms for one or more of the plurality of classes, each machine learning algorithm being trained for determining a specific target material property of assessment materials using one of the plurality of training datasets;
- and
- determining output value(s) of the specific target material property(s) of an assessment material using one of the plurality of machine learning algorithms trained using a training dataset corresponding to the class of the assessment material and trained for determining the specific target material property.
12 more elements
A computer program product comprising instructions which, when executed by a computing device, cause the computing device to carry out a method comprising:
- generating one or more training datasets for training one or more machine learning algorithms for determining values of one or more target material properties of assessment materials, a training dataset being generated specifically for each of the one or more target material properties, the generation of training datasets comprising the steps:
- providing a database comprising data records indicative of input values of material properties of a multitude of structural materials, comprising at least chemical composition and processing parameter(s) of the multitude structural materials;
- classifying the data records into a plurality of classes according to the input value(s) of one or more of the material properties, at least according to the values of chemical composition and processing parameter(s);
- within each of the plurality of classes, extracting target-relevant material properties from the data records having a dependency relationship with the specific target material property(s);
- and
- generating at least one training dataset corresponding to one or more of the plurality of classes using values of the extracted target-relevant material properties and corresponding values of the specific target material property(s);
- training of one or more machine learning algorithms for one or more of the plurality of classes, each machine learning algorithm being trained for determining a specific target material property of assessment materials using one of the plurality of training datasets;
- and
- determining output value(s) of the specific target material property(s) of an assessment material using one of the plurality of machine learning algorithms trained using a training dataset corresponding to the class of the assessment material and trained for determining the specific target material property.
6 more elements
Dependencies are inferred from the claim text.