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19 Einträge gefunden

Vorhersage des Ermüdungsfestigkeitsverhaltens von Stumpfstößen mittels Explainable Artificial Intelligence
2022 - TUHH Open Research
Ice pressure measurements with tekscan sensors-behaviour, calibration and application limits
2022 - TUHH Open Research
Determination of weld geometry parameter and stress concentration distributions for butt joints using deep neural networks
2022 - TUHH Open Research
Statistical characterization of stress concentrations along butt joint weld seams using deep neural networks
2022 - TUHH Open Research - frei zugänglich
Analyzing flexural strength data of ice: how useful is explainable machine learning?
2022 - TUHH Open Research
Analyzing the complexity of ice with explainable machine learning for the development of an ice material model
1. Kellner, Leon
2022 - TUHH Open Research - frei zugänglich
Explainable machine learning ice study
1. Kellner, Leon
2022 - TUHH @ Zenodo - frei zugänglich
Predicting compressive strength and behavior of ice and analyzing feature importance with explainable machine learning models
2022 - TUHH Open Research
Prognose von Anrissorten und Lebensdauer von Stumpfstößen mittels explainable artificial intelligence
1. Braun, Moritz
2. Kellner, Leon
2022 - TUHH Open Research
Comparison of machine learning and stress concentration factors-based fatigue failure prediction in small-scale butt-welded joints
1. Braun, Moritz
2. Kellner, Leon
2022 - TUHH Open Research - frei zugänglich
Study on the cohesive edge crack in a square plate with the cohesive element method
2021 - TUHH Open Research - frei zugänglich
Prediction of fatigue failure in small-scale butt-welded joints with explainable machine learning
2021 - TUHH Open Research - frei zugänglich
Data from the paper: Study on the Cohesive Edge Crack in a Square Plate with the Cohesive Element Method
1. Kellner, Leon
2. Lu, Wenjun
2020 - TUHH Open Research - frei zugänglich
A cohesive model for ice and its verification with tensile splitting tests
2019 - TUHH Open Research
Simulation of temperature distribution in ship structures for the determination of temperature- dependent material properties
2019 - TUHH Open Research
Establishing a common database of ice experiments and using machine learning to understand and predict ice behavior
2019 - TUHH Open Research
State of the art and knowledge gaps on modelling structures in cold regions
2019 - TUHH Open Research
The non-linear behavior of aqueous model ice in downward flexure
2019 - TUHH Open Research
Review of ice load standards and comparison with measurements
2017 - TUHH Open Research

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Vorhersage des Ermüdungsfestigkeitsverhaltens von Stumpfstößen mittels Explainable Artificial Intelligence

Ice pressure measurements with tekscan sensors-behaviour, calibration and application limits

Determination of weld geometry parameter and stress concentration distributions for butt joints using deep neural networks

Statistical characterization of stress concentrations along butt joint weld seams using deep neural networks

Analyzing flexural strength data of ice: how useful is explainable machine learning?

Analyzing the complexity of ice with explainable machine learning for the development of an ice material model

Explainable machine learning ice study

Predicting compressive strength and behavior of ice and analyzing feature importance with explainable machine learning models

Prognose von Anrissorten und Lebensdauer von Stumpfstößen mittels explainable artificial intelligence

Comparison of machine learning and stress concentration factors-based fatigue failure prediction in small-scale butt-welded joints

Study on the cohesive edge crack in a square plate with the cohesive element method

Prediction of fatigue failure in small-scale butt-welded joints with explainable machine learning

Data from the paper: Study on the Cohesive Edge Crack in a Square Plate with the Cohesive Element Method

A cohesive model for ice and its verification with tensile splitting tests

Simulation of temperature distribution in ship structures for the determination of temperature- dependent material properties

Establishing a common database of ice experiments and using machine learning to understand and predict ice behavior

State of the art and knowledge gaps on modelling structures in cold regions

The non-linear behavior of aqueous model ice in downward flexure

Review of ice load standards and comparison with measurements