DE102020122824A1 - Method for generating a model for the assessment and/or prediction of the fatigue strength of components, system - Google Patents

Abstract

The invention relates to a method for generating a model for the assessment and / or prediction of the durability of components that have a first reinforced plastic material, characterized in that - in a first step - using measurements on one or more samples concerning a data or several parameters and/or properties are determined, and/or-- data relating to one or more parameters and/or properties are determined using simulations of one or more samples,wherein the one or more samples each comprise the first reinforced plastic material; - In a second step, depending on the data determined, the model for the first reinforced plastic material is generated.

Description

The invention relates to a method for generating a model for evaluating and/or predicting the durability of components that have a first reinforced plastic material. Furthermore, the invention relates to a method for evaluating and/or predicting the fatigue strength of a component, a method for producing a component and a system for generating a model for evaluating and/or predicting the fatigue strength of components.

Durability is a crucial parameter when evaluating and testing components. The fatigue strength describes the ability of materials and components to withstand static, quasi-static and dynamic (recurring or sudden) loads within the calculated service life and taking into account the relevant environmental conditions without damage. The operational stability evaluates the design, dimensioning and durability of components and systems in relation to mechanical loads.

The mechanical testing of real components is complex and expensive, since highly specialized methods and machines have to be used to test and characterize individual components.

For metal materials, for example, Rennert, R. et. al., "Analytical Strength Assessment of Components", FKM-Guidelines 6th Edition, VDMA-Verlag, Frankfurt (2012).

For components that have reinforced plastic materials or consist of such, there are always broader and more innovative possible uses, for example in vehicle technology, due to their versatile and advantageous properties. An advantageous fatigue strength assessment is therefore desirable for a large number of possible uses of such components. However, when evaluating and testing the fatigue strength of reinforced plastic materials, there are special requirements due to the complex material properties.

Against this background, the task arises of improving the assessment and/or prediction of the fatigue strength of components that have a reinforced plastic material, so that in particular a cost-effective and/or time-efficient characterization of the fatigue strength becomes possible.

• - in einem ersten Schritt
• -- mithilfe von Messungen an einer oder mehreren Proben Daten betreffend einen oder mehrere Parameter und/oder Eigenschaften ermittelt werden, und/oder
• -- mithilfe von Simulationen von einer oder mehreren Proben Daten betreffend einen oder mehrere Parameter und/oder Eigenschaften ermittelt werden,

wobei die eine oder die mehreren Proben jeweils das erste verstärkte Kunststoffmaterial aufweisen;

• - in einem zweiten Schritt in Abhängigkeit der ermittelten Daten, das Modell für das erste verstärkte Kunststoffmaterial erzeugt wird.

To solve the problem, a method for generating a model for evaluating and/or predicting the fatigue strength of components that have a first reinforced plastic material is proposed, characterized in that

• - in a first step
• -- data relating to one or more parameters and/or properties are determined by means of measurements on one or more samples, and/or
• -- data relating to one or more parameters and/or properties are determined by means of simulations of one or more samples,

wherein the one or more samples each comprise the first reinforced plastic material;

• - In a second step, depending on the data determined, the model for the first reinforced plastic material is generated.

This makes it possible according to the invention to generate a model for a specific first reinforced plastic material that can subsequently be used for evaluating or testing the fatigue strength of components that have this specific first reinforced plastic material or consist partially or entirely of it. As a result, an efficient and cost-saving evaluation can be carried out using the model. Furthermore, according to the invention, a prediction can be made for the suitability of various or different components (each having the first reinforced plastic material) for different applications.

According to the invention, it is conceivable in an advantageous manner to enable an evaluation method for the material class of reinforced plastic materials. A multi-stage simulation chain can be used for the simulative evaluation of these products. A model can be created with the help of integrated calibration and validation. According to the invention, these findings and material data can advantageously be used in the course of a virtual strength assessment. The model generated according to the invention can advantageously be used for evaluating and/or predicting the durability for each product or component in which the first reinforced plastic material has been or is to be processed.

It is preferably possible for the generated model to depict the actually existing load condition, for example a combination from load, moisture, fiber orientation and, if necessary, other parameters and properties.

According to the invention, a reinforced plastic material can be understood in particular as a plastic that has reinforcements in the form of at least one filler. Examples are fiber-reinforced plastics or plastics reinforced with particles.

The method according to the invention is preferably a computer-implemented method.

Advantageous configurations and developments of the invention can be found in the subclaims and the description with reference to the drawings.

According to an advantageous embodiment of the invention, it is provided that the model in the second step using a multidimensional interpolation, in particular a multiple linear and / or non-linear regression and / or an optimization method according to several parameters, and / or an artificial intelligence method, in particular one neural network, depending on which data is generated. In the second step, the model required for the evaluation can be fitted to real (and possibly simulated) test data obtained in the first step by means of suitable multidimensional interpolations using optimization methods and/or artificial intelligence methods such as neural networks. The second step preferably takes place in a computer-implemented manner.

According to an advantageous embodiment of the invention, it is provided that the data determined in the first step contain information on the measured and/or simulated fatigue strength of the one or more samples.

According to an advantageous embodiment of the invention, it is conceivable for the data measured in the first step to be determined at least partially with the aid of static and/or cyclic load measurements and/or with the aid of creep tests. For the relevant parameter space for the fatigue strength assessment (e.g. comprising the load, moisture, fiber orientation and typically other parameters and/or properties), in practice only certain points or parameter combinations (in this parameter space) can be obtained or determined through real measurements or tests. being checked. This real data, obtained in a first step, is the basis for generating the model in this parameter space in the second step. The model can preferably be generated based on the real data of the first step.

A model can thus be obtained for the entire parameter space, which also includes points or parameter combinations in the parameter space that were not explicitly measured in the first step.

According to an advantageous embodiment of the invention it is provided that the data determined in the first step have information on one or more parameters and / or properties of the samples, and / or that the data determined in the first step information on one or more parameters relating to environmental influences, which the samples are exposed during the collection of the data (especially during the measurements in the first step).

• - einer, insbesondere lokalen, Temperatur der Probe,
• - einer, insbesondere lokalen, Feuchtigkeit der Probe, bevorzugt einer Wasserfeuchtigkeit,
• - einer geometrischen Ausbildung der Probe, insbesondere zu lokalen mechanischen Spannungszuständen, bevorzugt Normal- und/oder Subspannungen, und/oder Spannungsgradienten innerhalb der Probe,
• - einer Faserorientierung eines Füllstoffs des ersten verstärkten Kunststoffmaterials in der Probe,
• - Einflüssen von Umgebungsmedien der Probe, insbesondere von lokal vorhandenen Ölen und/oder Fetten, und/oder
• - Einflüssen von Bindenähten der Probe,
• - einem, insbesondere lokalen, Spannungsverhältnis und/oder einer Mittelspannung der Probe bei zyklischer Prüfung (Belastung und Entlastung). Mithilfe einiger oder aller der vorhergehend aufgeführten Parameter und Eigenschaften ist der Parameterraum gebildet, für den das Modell ermittelt wird. Durch die Messungen und/oder Simulationen im ersten Schritt werden für bestimmte Stellen in diesem Parameterraum Datensätze erhalten, auf deren Grundlage im zweiten Schritt das Modell für diesen Parameterraum erzeugt werden kann. Mithilfe des erzeugten Modells können somit Bewertungen und/oder Vorhersagen bezüglich des Parameterraums durchgeführt werden, auch für Stellen bzw. spezifische Parameterkombinationen innerhalb des Parameterraums, die im ersten Schritt nicht vermessen wurden.

According to an advantageous embodiment of the invention, it is provided that the data determined in the first step have information on one or more of the following parameters and/or properties for one, several or each of the samples:

• - a, in particular local, temperature of the sample,
• - a, in particular local, moisture of the sample, preferably a water moisture,
• - a geometric design of the sample, in particular to local mechanical stress states, preferably normal and/or sub-stresses, and/or stress gradients within the sample,
• - a fiber orientation of a filler of the first reinforced plastic material in the sample,
• - Influences from the media surrounding the sample, in particular from locally present oils and/or fats, and/or
• - influences of weld lines of the sample,
• - a, in particular local, stress ratio and/or a mean stress of the sample during cyclic testing (loading and unloading). The parameter space for which the model is determined is formed using some or all of the parameters and properties listed above. Through the measurements and/or simulations in the first step, data sets are obtained for specific points in this parameter space, on the basis of which the model for this parameter space can be generated in the second step. The generated model can thus be used to carry out assessments and/or predictions with regard to the parameter space, even for points or specific parameter combinations within the parameter space that were not measured in the first step.

• - der Füllstoff ein Fasermaterial, insbesondere Glasfasern und/oder Kohlenstofffasern, umfasst, und/oder
• - der Füllstoff mineralische Partikel umfasst. Für die Polymermatrix kommen vorzugsweise duroplastische und/oder thermoplastische Kunststoffe infrage. Das Fasermaterial des Füllstoffs kann insbesondere Superkurzfasern, Kurzfasern und/oder Langfasern umfassen. Die durchschnittlichen Faserlängen liegen dementsprechend vorzugsweise im Millimeter- oder Zentimeterbereich. Bei den Partikeln des Füllstoffs kann es sich beispielsweise um Kügelchen oder Fasern handeln.

According to an advantageous embodiment of the invention, it is provided that the first reinforced plastic material comprises a polymer matrix and a filler, with preference being given to this

• - the filler comprises a fiber material, in particular glass fibers and/or carbon fibers, and/or
• - the filler comprises mineral particles. Thermosetting and/or thermoplastic plastics are preferably suitable for the polymer matrix. The fibrous material of the filler can in particular comprise super short fibers, short fibers and/or long fibers. Accordingly, the average fiber lengths are preferably in the millimeter or centimeter range. The particles of the filler can be, for example, beads or fibers.

• - in einem weiteren ersten Schritt
• -- mithilfe von Messungen an einer oder mehreren weiteren Proben Daten betreffend einen oder mehrere Parameter und/oder Eigenschaften ermittelt werden, und/oder
• -- mithilfe von Simulationen von einer oder mehreren weiteren Proben Daten betreffend einen oder mehrere Parameter und/oder Eigenschaften ermittelt werden, wobei die eine oder die mehreren weiteren Proben jeweils ein zweites verstärktes Kunststoffmaterial aufweisen;
• - in einem weiteren zweiten Schritt in Abhängigkeit der ermittelten Daten, das weitere Modell für das zweite verstärkte Kunststoffmaterial erzeugt wird. Das weitere Modell für das zweite verstärkte Kunststoffmaterial kann dabei entsprechend dem Modell für das erste Kunststoffmaterial erzeugt werden. Entsprechend können auch für ein drittes oder noch weitere verstärkte Kunststoffmaterialien Modelle erzeugt werden. Es ist somit denkbar, dass pro spezifischem verstärktem Kunststoffmaterial mithilfe eines Verfahrens gemäß der vorliegenden Erfindung ein eigenes Modell erzeugt wird, das für dieses spezifische verstärkte Kunststoffmaterial verwendet werden kann bzw. gültig ist.

According to an embodiment of the present invention, it is conceivable that the method for generating a model for evaluating and/or predicting the durability of components comprising a first reinforced plastic material further comprises a method for generating a further model for evaluating and/or Predicting the durability of components comprising a second reinforced plastic material comprising, wherein

• - in another first step
• -- data relating to one or more parameters and/or properties are determined by means of measurements on one or more other samples, and/or
• -- with the aid of simulations of one or more further samples, data relating to one or more parameters and/or properties are determined, wherein the one or more further samples each have a second reinforced plastic material;
• - In a further second step, depending on the data determined, the further model for the second reinforced plastic material is generated. The additional model for the second reinforced plastic material can be generated in accordance with the model for the first plastic material. Correspondingly, models can also be produced for a third or even further reinforced plastic material. It is thus conceivable that for each specific reinforced plastic material, a separate model is generated with the aid of a method according to the present invention, which model can be used or is valid for this specific reinforced plastic material.

Another subject of the present invention is a method for evaluating and/or predicting the durability of a component using a model generated according to a method according to an embodiment of the present invention,
wherein the component comprises the first reinforced plastic material,
wherein the fatigue strength of the component is evaluated and/or predicted using the generated model. Reinforced polymers, ie in particular polymers which are filled with filler particles such as fibers or spheres, have strongly anisotropic, viscoelastoplastic, temperature-dependent properties which are also dependent on the medium, for example humidity. Furthermore, in addition to external notches, there are also internal weak points, so-called weld lines, in components made of polymers. Using the method according to the invention for generating a model for evaluating and/or predicting the structural strength of components, it is possible, within the framework of an integrative simulation chain, from filling simulation to transient temperature and/or moisture field calculation to time-dependent, nonlinear mechanical simulation, to carry out a strength assessment all relevant damage mechanisms for components that have a specific reinforced plastic material (e.g. the first reinforced plastic material). A method for evaluating and/or predicting the fatigue strength of a component can thus be implemented using the generated model. With the help of the method, it is preferably possible that at a point in time when the component only exists virtually and, in particular, has not yet been manufactured, it can be predicted whether it will withstand the later real loads.

According to one embodiment of the present invention, it is conceivable that the fatigue strength of a further component is evaluated and/or predicted using the generated model, the further component also having the first reinforced plastic material, the further component having a different geometric configuration than the component . It is thus conceivable that the generated model for the first reinforced plastic material is used for testing and evaluating the durability of a large number of specific components which are each manufactured using or have the first reinforced plastic material. Thus, the fatigue strength of components with different geometries and configurations can be evaluated and predicted by the model once it has been created.

Another object of the invention is a method for producing a component, wherein the component comprises a first reinforced plastic material,
wherein in an evaluation step, the durability of the component is evaluated and/or predicted using a method for evaluating and/or predicting the durability of a component according to an embodiment of the present invention;
wherein the component is produced in a production step. The fatigue strength of a component intended for production can thus be predicted and/or evaluated in particular before the component is produced. It is particularly advantageously possible for the component to be produced or manufactured if the assessment and/or prediction of the operational stability shows that the operational stability of the component corresponds to a specification
and/or definable criteria are met. In this way, the effort involved in developing new components can be reduced, since an advantageous evaluation of operational stability becomes possible. It is thus advantageously possible to make an assessment of the fatigue strength before the component is manufactured.

• -- dass mithilfe von Messungen an einer oder mehreren Proben Daten betreffend einen oder mehrere Parameter und/oder Eigenschaften ermittelt werden, und/oder
• -- dass mithilfe von Simulationen von einer oder mehreren Proben Daten betreffend den einen oder die mehreren Parameter und/oder Eigenschaften ermittelt werden,

wobei die Proben jeweils das erste verstärkte Kunststoffmaterial aufweisen;
wobei das System ferner derart konfiguriert ist,
dass in Abhängigkeit der ermittelten Daten das Modell für das erste verstärkte Kunststoffmaterial erzeugt wird. Das System kann insbesondere ein computerimplementiertes System sein. Das erzeugte Modell ist für ein bestimmtes erstes verstärktes Kunststoffmaterial gültig. Das Modell ist vorzugsweise derart eingerichtet, dass mithilfe des Modells die Betriebsfestigkeit (Lebenszeit, Abnutzung usw.) für unterschiedliche, insbesondere beliebige, Bauteile (und somit beliebige Bauteilgeometrien) bewertet bzw. vorhergesagt werden kann, sofern die Bauteile das erste verstärkte Kunststoffmaterial aufweisen oder aus dem ersten verstärkten Kunststoffmaterial bestehen.A further object of the invention is a system for generating a model for evaluating and/or predicting the durability of components comprising a first reinforced plastic material, characterized in that the system is configured in such a way

• -- that data relating to one or more parameters and/or properties are obtained by means of measurements on one or more samples, and/or
• -- that data relating to one or more parameters and/or properties are determined using simulations of one or more samples,

the samples each comprising the first reinforced plastic material;
the system being further configured such that
that depending on the data determined, the model for the first reinforced plastic material is generated. In particular, the system can be a computer-implemented system. The model generated is valid for a specific first reinforced plastic material. The model is preferably set up in such a way that the model can be used to evaluate or predict the operational stability (service life, wear and tear, etc.) for different, in particular any, components (and thus any component geometries), provided that the components have or are made of the first reinforced plastic material the first reinforced plastic material.

For the method according to the invention for evaluating and/or predicting the fatigue strength of a component, the method according to the invention for producing a component and the system according to the invention for creating a model, the advantages and configurations can be applied which have already been mentioned in connection with the method according to the invention for creating a model for evaluating and/or predicting the durability of components or in connection with an embodiment of the method according to the invention for generating a model for evaluating and/or predicting the durability of components.

• 1 eine schematische Darstellung eines Ausführungsbeispiels eines erfindungsgemäßen Verfahrens zur Erzeugung eines Modells; und
• 2 eine schematische Darstellung eines Ausführungsbeispiels eines erfindungsgemäßen Verfahrens zur Bewertung und/oder Vorhersage der Betriebsfestigkeit eines Bauteils.

Further details and advantages of the invention are to be explained below with reference to the exemplary embodiments illustrated in the drawings. Herein shows:

• 1 a schematic representation of an embodiment of a method according to the invention for generating a model; and
• 2 a schematic representation of an embodiment of a method according to the invention for evaluating and / or predicting the durability of a component.

• - einer Temperatur der Probe 10, 11, 12,
• - einer Feuchtigkeit der Probe 10, 11, 12
• - einer geometrischen Ausbildung der Probe 10, 11, 12, insbesondere zu lokalen mechanischen Spannungen und/oder Spannungsgradienten innerhalb der Probe 10, 11, 12,
• - einer Faserorientierung eines Füllstoffs des ersten verstärkten Kunststoffmaterials in der Probe 10, 11, 12,
• - Einflüssen von Umgebungsmedien der Probe 10, 11, 12,
• - Einflüssen von Bindenähten der Probe 10, 11, 12,
• - einem, insbesondere lokalen, Spannungsverhältnis und/oder einer Mittelspannung der Probe 10, 11, 12 bei zyklischer Prüfung. Die betrachteten Parameter bzw. Eigenschaften bilden einen Parameterraum. Diese realen Daten, die in einem ersten Schritt erhalten werden, sind die Grundlage für die Erzeugung bzw. Ermittlung eines Modells 104 betreffend diesen Parameterraum im zweiten Schritt.

In 1 1 is shown a block diagram for a method of generating a model according to an embodiment of the present invention. In a first step 101, measurements are carried out on physical or real samples 10, 11, 12 (ie specific manufactured components) and data 103, in particular real test data, relating to these measurements are thus generated. The measurements can be, for example, creep tests, cyclic load measurements and/or other series of measurements known from material testing. In addition or as an alternative, it is optionally possible for simulation data, for example provided by multiscale simulations, to be determined in the first step and to be part of the data 103 . The samples 10, 11, 12, which are tested, measured and/or simulated in the first step, each comprise a first reinforced plastic material. In the first step 101, data 103, comprising information or details on the following parameters and/or properties, are thus determined for these samples:

• - a temperature of the sample 10, 11, 12,
• - a humidity of the sample 10, 11, 12
• - a geometric design of the sample 10, 11, 12, in particular with regard to local mechanical stresses and/or stress gradients within the sample 10, 11, 12,
• - a fiber orientation of a filler of the first reinforced plastic material in the sample 10, 11, 12,
• - Influences of environmental media of sample 10, 11, 12,
• - Influences of weld lines of sample 10, 11, 12,
• - A, in particular local, stress ratio and/or a mean stress of the sample 10, 11, 12 during cyclic testing. The parameters or properties considered form a parameter space. This real data, which is obtained in a first step, is the basis for the generation or determination of a model 104 relating to this parameter space in the second step.

In a second step, a model 104 for the first reinforced plastic material is generated from the data 103 obtained. It is thus preferably possible for the generated model to depict a really existing load condition, in particular a combination of load, moisture, fiber orientation and the other parameters and properties considered.

In the second step 102, the model 104 is generated or fitted with the aid of a multidimensional interpolation (relating to the parameter space considered), a multiple regression (relating to the parameter space considered), and/or an optimization method based on a plurality of parameters (relating to the parameter space considered) and/or or generated using an artificial intelligence method such as a neural network.

According to the invention, a separate model 104 can be generated for each specific reinforced plastic material using a method of the present invention, which can be used or is valid for this specific reinforced plastic material.

The method according to the invention serves to carry out a strength assessment of all relevant damage mechanisms within the framework of an integrative simulation chain, from the filling simulation via transient temperature and humidity field calculation to the time-dependent, nonlinear mechanical simulation. The complex data is preferably always prepared in a user-friendly manner and integrated directly into the integrative simulation chain by means of suitable automated interfaces and/or presented as required with clearly designed graphical interfaces. In this case, the algorithm or the method preferably includes a standardized workflow in order to ensure the quality of the results independently of the specific processor. High degrees of automation for the exchange of data models can increase efficiency in a particularly advantageous way. The method also relates to the parameterization of the models (or the model 104 that is generated in the second step, as well as other models for other specific reinforced plastic materials). It is preferably possible for the method or the algorithm to provide a suitable test plan, for example from static and cyclic tests, creep tests, etc., in order to optimally parameterize the material models using specially designed sample geometries (in the first step 101). In addition, it is conceivable that virtual test plans, for example anisotropic and/or multiscale simulations, are provided and carried out in the first step 101 in order to upgrade the test data for the material models, so that particularly advantageous data 103 are generated.

In 2 an exemplary embodiment of a method for evaluating and/or predicting the durability of a component 200 is shown, the evaluation and/or prediction being carried out using or on the basis of a model 104 which, for example, is carried out using a method according to the exemplary embodiment of FIG 1 was generated. Because model 104 relates to the first reinforced plastic material, it can be used to evaluate component 200, which also includes the first reinforced plastic material. With the model 104, the durability or service life of the component 200 under loads can be evaluated and predicted. Weak points and possible problem zones can thus be identified. Advantageously, the model 104, once generated, can be used for evaluating and/or predicting the operational strength of a wide variety of other components 201, 202, each of which also has the first reinforced plastic material. Statements can thus be made about the operational strength of components 200, 201, 202, which each have the same first reinforced plastic material, but which are designed differently and independently of one another and, for example, have independent geometric shapes. It is advantageously possible to manufacture the component 200, 201, 202 before, during and/or after its durability has been predicted and/or evaluated.

The method according to the invention thus relates in particular to the operational stability assessment of reinforced polymer components. The method preferably includes all stations relevant to the assessment from modeling and validation (in particular in the first and second step 101, 102) to the simulative assessment and the monitoring of physical tests.

Reference List

10, 11, 12

rehearse

101

first step

102

second step

103

Data

104

model

200

component

201

another component

202

another component

Claims (11)

A method for generating a model (104) for evaluating and / or predicting the durability of components (200, 201, 202) having a first reinforced plastic material, characterized in that - in a first step (101) -- using Measurements on one or more samples (10, 11, 12) data (103) relating to one or more parameters and/or properties are determined, and/or -- using simulations of one or more samples (10, 11, 12) data (103) determining one or more parameters and/or properties, the one or more samples (10, 11, 12) each comprising the first reinforced plastic material; - In a second step (102) depending on the determined data (103), the model (104) for the first reinforced plastic material is generated. procedure after claim 1 , characterized in that the model (104) in the second step (102) using a multidimensional interpolation, in particular a multiple linear and / or non-linear regression and / or an optimization method according to several parameters, and / or an artificial intelligence method, in particular one neural network, depending on the data (103) is generated. Method according to one of the preceding claims, characterized in that the data (103) determined in the first step (10) has information on the measured and/or simulated operational strength of the one or more samples (10, 11, 12). Method according to one of the preceding claims, characterized in that the data (103) measured in the first step (101) are determined at least in part with the aid of static and/or cyclic load measurements and/or with the aid of creep tests. Method according to one of the preceding claims, characterized in that the data (103) determined in the first step (101) have information on one or more parameters and / or properties of the samples (10, 11, 12), and / or that the im data (103) determined in the first step (101) have information on one or more parameters relating to environmental influences to which the samples (10, 11, 12) are exposed when the data (103) are determined. Method according to one of the preceding claims, characterized in that the data (103) determined in the first step (101) for one, several or each of the samples (10, 11, 12) contains information on one or several of the following parameters and/or properties exhibit: - a, in particular local, temperature of the sample (10, 11, 12), - a, in particular local, humidity of the sample (10, 11, 12), preferably water humidity, - a geometric configuration of the sample (10, 11 , 12), in particular to local mechanical stress states, preferably normal and/or substresses, and/or stress gradients within the sample (10, 11, 12), - a fiber orientation of a filler of the first reinforced plastic material in the sample (10, 11, 12), - influences of the media surrounding the sample (10, 11, 12), in particular locally present oils and/or fats, - influences of weld lines of the sample (10, 11, 12), and/or - a particularly local voltage conn ratio and / or a mean stress of the sample (10, 11, 12) in cyclic testing. Method according to one of the preceding claims, characterized in that the first reinforced plastic material comprises a polymer matrix and a filler, wherein preferably - the filler comprises a fiber material, in particular glass fibers and/or carbon fibers, and/or - the filler comprises mineral particles. Method for evaluating and / or predicting the durability of a component (200) using a according to a method according to one of Claims 1 until 7 generated model (104), wherein the component (200) comprises the first reinforced plastic material, wherein the generated model (104) is used to evaluate and/or predict the durability of the component (200). procedure after claim 8 , characterized in that using the generated Model (104) evaluates and/or predicts the operational strength of a further component (200), the further component (201, 202) also having the first reinforced plastic material, the further component (201, 202) having a different geometric configuration than the component (200). A method for producing a component (200), the component (200) having a first reinforced plastic material, wherein in an evaluation step using a method for evaluating and / or predicting the durability of a component (200) according to claim 8 or 9 the durability of the component (200) is evaluated and/or predicted; wherein the component (200) is produced in a production step. System for generating a model (104) for evaluating and/or predicting the durability of components (200, 201, 202) having a first reinforced plastic material, characterized in that the system is configured such that -- that using measurements data (103) relating to one or more parameters and/or properties are determined on one or more samples (10, 11, 12), and/or -- that data are obtained from one or more samples (10, 11, 12) with the aid of simulations (103) are determined regarding the one or more parameters and/or properties, the samples (10, 11, 12) each comprising the first reinforced plastic material; wherein the system is further configured such that the model (104) for the first reinforced plastic material is generated as a function of the determined data (103).

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