Filtern
Erscheinungsjahr
Dokumenttyp
- Zeitschriftenartikel (40)
- Beitrag zu einem Tagungsband (23)
- Vortrag (12)
- Beitrag zu einem Sammelband (4)
- Forschungsbericht (3)
- Buchkapitel (1)
- Forschungsdatensatz (1)
Sprache
- Englisch (54)
- Deutsch (28)
- Mehrsprachig (1)
- Serbisch (1)
Schlagworte
- Neural networks (7)
- Welding simulation (7)
- Aluminium (6)
- Grain refinement (5)
- Gründungsstrukturen (5)
- Laser beam welding (5)
- Welding (5)
- Ökobilanzierung (5)
- Fatigue tests (4)
- Inverse heat conduction problem (4)
- Offshore Windenergieanlagen (4)
- Tubular X-joints (4)
- Automated manufacturing (3)
- Automatisierte Fertigung (3)
- Digitalisierung (3)
- Friction stir welding (3)
- GTA welding (3)
- Leichtbau (3)
- MSG-Schweißen (3)
- Mechanical properties (3)
- Notch stress approach (3)
- Schweißverfahren (3)
- Temperature field generation (3)
- WAAM (3)
- Al Ti5B1 (2)
- Alloy 1050A (2)
- Alloy 5083 (2)
- Alloy 6082 (2)
- Arc Welding Automation (2)
- Arc welding (2)
- Automatisierte schweißtechnische Fertigung (2)
- Columnar to equiaxed transition (CET) (2)
- Energy efficiency (2)
- FEA (2)
- Fatigue (2)
- Festigkeit (2)
- GMA-laser hybrid welding (2)
- GMAW (2)
- Gas metal arc welding (2)
- Gas tungsten arc welding (GTAW) (2)
- Global optimisation (2)
- High power welding (2)
- High-strength low-alloy steel (2)
- Hochleistungsschweißen (2)
- Inverse modelling (2)
- Jacket Support Structures (2)
- Laser arc-hybrid welding (2)
- Lichtbogensensorik (2)
- Life Cycle Assessment (LCA) (2)
- Life cycle assessment (LCA) (2)
- Lightweight Design (2)
- Model prediction (2)
- Multiple experiments (2)
- Offshore Wind (2)
- Optimization (2)
- Resource efficiency (2)
- Rissbildung (2)
- Short calculation time (2)
- Stochastic search method (2)
- Structural stress approach (2)
- Technical crack detection (2)
- Temperature (2)
- Tensile tests (2)
- Transformable steels (2)
- Umweltwirkungen (2)
- Verfahrensvergleich (2)
- Volume heat source (2)
- Werkstofffragen (2)
- Wire arc additive manufacturing (2)
- Adaptive control (1)
- Additive manufacturing (1)
- Al-Mg-Si (1)
- Al-Mg-Si-Legierungen (1)
- AlMg0.7SiTiB filler wire (1)
- Aluminium/Aluminiumlegierungen (1)
- Analysis techniques (1)
- Arc sensor (1)
- Aufgelöste Tragstrukturen (1)
- Automated arc welding (1)
- Automated welding (1)
- Automation (1)
- Automatisierte schweißtechniche Fertigung (1)
- Automatisierung (1)
- Axial force (1)
- Bionik (1)
- Carbon dioxide footprint (1)
- Crack formation (1)
- Design of experiments (1)
- Digitalization (1)
- Digitization (1)
- Dissimilar welding (1)
- Duplex nucleation theory (1)
- Dynamic fracture tests (1)
- Economic wide technology replacement (1)
- Einfluss auf Schweißeigenspannungen (1)
- Elektromagnetische Schmelzbadsicherung (1)
- Energy density distribution (1)
- Energy input (1)
- Environment (1)
- Environmental impact categories (1)
- Epitaxial nucleation (1)
- Equivalent stress concentration factors (1)
- Ermüdung (1)
- Experimental validation (1)
- Fair salary (1)
- Forschungsdatenmanagement (1)
- Fracture (1)
- Functional analysis (1)
- Functional-analytical solution (1)
- GMA welding (1)
- GTAW (1)
- Gleeble experiments (1)
- Gleeble testing (1)
- Grade S960QL steel (1)
- Grain size (1)
- Greenhouse gas mitigation (1)
- HSLA (1)
- Hardly separable problem (1)
- Heat conduction (1)
- Heat flow (1)
- Heat transfer (1)
- Heissrisse (1)
- High-strength steel (1)
- Hochfester Stahl (1)
- Hohlprofilknoten (1)
- Human health (1)
- Human health G. (1)
- Hybrid laser arc welding (1)
- Implementierung (1)
- Kerbspannungskonzept (1)
- Künstliche neuronale Netze (1)
- LBW (1)
- LCA (1)
- Laser beams (1)
- Laser-MSG-Hybridschweißen (1)
- Laserstrahlschweißen (1)
- Leichtbauprinzipien (1)
- Lichtbogenschweißen (1)
- Life Cycle Assessment (LCA) Fusion welding (1)
- Life Cycle Assessment (LCA) Impact categories (1)
- Life Cycle Assessment (LCA) Schweißprozesse (1)
- Life Cycle Assessment (LCA) Umweltwirkungen (1)
- Life cycle assessment (1)
- Life-cycle assessment (1)
- Lifetime (1)
- Lightweight principles (1)
- Local fatigue approaches (1)
- Local fatigue spproaches (1)
- MAG Prozesssteuerung (1)
- MAG welding (1)
- MSG-Engspaltschweißen (1)
- Martensite start temperature (1)
- Material flow (1)
- Material modeling (1)
- Material questions (1)
- Measurement (1)
- Mechanisch technologische Kennwerte (1)
- Metallurgische Fragen (1)
- Microcracking (1)
- Model calibration (1)
- Model order reduction (1)
- Multi-attribute decision method (1)
- Multi-criteria decision support (1)
- Multi-regional inputeoutput data (1)
- Narrow gap welding (1)
- Narrow-gap welding (1)
- Neural Networks (1)
- Neural network (1)
- Normen (1)
- Numerical simulation (1)
- Numerical welding simulation (1)
- Offshore Windenergie (1)
- Offshore wind turbines (1)
- Open science (1)
- Open source (1)
- OpenScience (1)
- Optimisation (1)
- Phase transformation (1)
- Porosität (1)
- Precipitation hardening aluminum alloys (1)
- Prior austenite grain size (1)
- Process innovations (1)
- Profilvermessung (1)
- Proper generalized decomposition (1)
- Prozesskette (1)
- Prozessüberwachung (1)
- Research data management (1)
- Residual stress (1)
- Resistance spot welding (1)
- Schweißnahtfehler (1)
- Schweißnahtgeometrie (1)
- Schweißprozesse (1)
- Schweißsimulation (1)
- Schweißtechnik (1)
- Sensor (1)
- Sensorik (1)
- Simulating (1)
- Social Life Cycle Assessment (SLCA) (1)
- Social life cycle assessment (SLCA) (1)
- Standards (1)
- Steel (1)
- Strain-rate (1)
- Strength (1)
- Stress-strain behavior (1)
- Super martensitic filler material (1)
- Support structures (1)
- Sustainability assessment (1)
- TRIP (1)
- TRIP - transformation induced plasticity (1)
- Tandem Gas Metal Arc Welding (1)
- Tandem gas metal arc welding (1)
- Tandem welding (1)
- Tear tests (1)
- Temperature Field Generation (1)
- Thermal analysis (1)
- Thermal energy generation (1)
- Thermo physical simulation (1)
- Thick metal plate welding (1)
- Tool torque (1)
- Transformation induced plasticity (TRIP) (1)
- Traverse force (1)
- Tubular joints (1)
- Ultrasonic vibration (1)
- Umwandlungsplastischen Konstante K (1)
- Umweltschutz (1)
- Viscoplasticity (1)
- Volumetric heat source (1)
- Weld defects (1)
- Weld seam geometry (1)
- Welding costs (1)
- Welding process selection (1)
- Welding residual stresses (1)
- Welding-induced residual stress (1)
- Weldx (1)
- Wärmenachbehandlung (1)
- digital image correlation (1)
- dual phase steel (1)
- resistance spot welding (1)
- sensitivity analysis (1)
- welding residual stresses (1)
- Äquivalente Spannungskonzentrationsfaktoren (1)
- Ökobilanz (1)
Organisationseinheit der BAM
Eingeladener Vortrag
- nein (12)
The objective of this paper is to demonstrate a new simulation technique which allows fast and automatic generation of temperature fields as input for subsequent thermomechanical welding simulation. The basic idea is to decompose the process model into an empirical part based on neural networks and a phenomenological part that describes the physical phenomena. The strength of this composite modelling approach is the automatic calibration of mathematical models against experimental data without the need for manual interference by an experienced user. As an example for typical applications in laser beam and GMA-laser hybrid welding, it is shown that even 3D heat conduction models of a low complexity can approximate measured temperature fields with a sufficient accuracy. In general, any derivation of model fitting parameters from the real process adds uncertainties to the simulation independent of the complexity of the underlying phenomenological model. The modelling technique presented hybridises empirical and phenomenological models. It reduces the model uncertainties by exploiting additional information which keeps normally hidden in the data measured when the model calibration is performed against few experimental data sets. In contrast, here the optimal model parameter set corresponding to a given process parameter is computed by means of an empirical submodel based on relatively large set of experimental data. The approach allows making a contribution to an efficient compensation of modelling inaccuracies and lack of knowledge about thermophysical material properties or boundary conditions. Two illustrating examples are provided.
The objective of this paper is to demonstrate a new simulation technique which allows the fast and automatic generation to temperature fields based on a combination of empirical and phenomenological modelling techniques. The automatic calibration of the phenomenological model is performed by a multi-variable global optimisation routine which yields the optimal fit between simulated and experimental weld charcteristics without the need for initial model parameters. For exemplary welding processes it is shown that linear 3D heat conduction models can approximate measured temperature fields with a high accuracy. The modelling approach presented comprises the automatic calibration against multiple experiments which permits simulating the temperature field for unknown process parameters. The validation of this composite simulation model is performed for exemplary welding processes and includes the prediction of the fusion line in the cross section and the corresponding thermal cycles.
Fast temperature field generation for welding simulation and reduction of experimental effort
(2009)
The quality of welding processes is governed by the occurring induced distortions yielding an
increase in production costs due to necessary reworking. Especially for more complex specimens
it is difficult to evaluate the optimal configuration of welding sequences in order to
minimise the distortion. Even experienced welding operators can solve this task only by trial
and error which is time and cost consuming.
In modern engineering the application of welding simulation is already known to be able to
analyse the heat effects of welding virtually. However, the welding process is governed by
complex physical interactions. Thus, recent weld thermal models are based on many simplifications.
The state of the art is to apply numerical methods in order to solve the transient heat
conduction equation. Therefore, it is not possible to use the real process parameters as input
for the mathematical model. The model parameters which allow calculating a temperature
field that is in best agreement with the experiments cannot be defined directly but inversely by
multiple simulations runs. In case of numerical simulation software based on finite discretisation
schemes this approach is very time consuming and requires expert users. The weld
thermal model contains an initial weakness which has to be adapted by finding an optimal set
of model parameters. This process of calibration is often done against few experiments. The
range of model validity is limited. An extension can be obtained by performing a calibration
against multiple experiments.
The focus of the paper is to show a combined modelling technique which provides an efficient
solution of the inverse heat conduction problem mentioned above. On the one hand the inverse
problem is solved by application of fast weld thermal models which are closed form
solutions of the heat conduction equation. In addition, a global optimisation algorithm allows
an automated calibration of the weld thermal model. This technique is able to provide a temperature
field automatically that fits the experimental one with high accuracy within minutes
on ordinary office computers. This fast paradigm permits confirming the application of welding
simulation in an industrial environment as automotive industry.
On the other hand, the initial model weakness is compensated by calibrating the model
against multiple experiments. The unknown relationship between model and process parameters
is approximated by a neural network. The validity of the model is increased successively
and enables to decrease experimental effort. For a test case it is shown, that this approach
yields accurate temperature fields within very short amount of time for unknown process parameters
as input data to the model contributing to the requirement to construct a substitute
system of the real welding process.
Fast temperature field generation for welding simulation and reduction of experimental effort
(2011)
The quality of welding processes is governed by the occurring induced distortions yielding an increase in production costs due to necessary reworking. Especially for more complex specimens, it is difficult to evaluate the optimal configuration of welding sequences in order to minimize the distortion. Even experienced welding operators can solve this task only by trial and error which is time and cost consuming. In modern engineering the application of welding simulation is already known to be able to analyse the heat effects of welding virtually. However, the welding process is governed by complex physical interactions. Thus, recent weld thermal models are based on many simplifications. The state of the art is to apply numerical methods in order to solve the transient heat conduction equation. Therefore, it is not possible to use the real process parameters as input for the mathematical model. The model parameters which allow calculating a temperature field that is in best agreement with the experiments cannot be defined directly but inversely by multiple simulations runs. In case of numerical simulation software based on finite discretization schemes this approach is very time consuming and requires expert users. The weld thermal model contains an initial weakness which has to be adapted by finding an optimal set of model parameters. This process of calibration is often done against few experiments. The range of model validity is limited. An extension can be obtained by performing a calibration against multiple experiments. The focus of the paper is to show a combined modelling technique which provides an efficient solution of the inverse heat conduction problem mentioned above. On the one hand the inverse problem is solved by application of fast weld thermal models which are closed form solutions of the heat conduction equation. In addition, a global optimization algorithm allows an automated calibration of the weld thermal model. This technique is able to provide a temperature field automatically that fits the experimental one with high accuracy within minutes on ordinary office computers. This fast paradigm permits confirming the application of welding simulation in an industrial environment as automotive industry. On the other hand, the initial model weakness is compensated by calibrating the model against multiple experiments. The unknown relationship between model and process parameters is approximated by a neural network. The validity of the model is increased successively and enables to decrease experimental effort, For a test case, it is shown that this approach yields accurate temperature fields within very short amount of time for unknown process parameters as input data to the model contributing to the requirement to construct a substitute system of the real welding process.