Jörg F. Unger
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View article: Mechanical properties of 3D printed concrete: a RILEM TC 304-ADC interlaboratory study-Design and implementation of a database system for querying, sharing, and analyzing experimental data
Mechanical properties of 3D printed concrete: a RILEM TC 304-ADC interlaboratory study-Design and implementation of a database system for querying, sharing, and analyzing experimental data Open
Interlaboratory studies are essential for implementing standardized test methods for new innovative materials or technologies such as 3D concrete printing, certifying reference materials, and validating methods. They provide the basis for …
View article: Integrating custom constitutive models into FEniCSx: A versatile approach and case studies
Integrating custom constitutive models into FEniCSx: A versatile approach and case studies Open
View article: Advancing Digital Transformation in Material Science: The Role of Workflows Within the MaterialDigital Initiative
Advancing Digital Transformation in Material Science: The Role of Workflows Within the MaterialDigital Initiative Open
View article: Advancing Digital Transformation in Material Science: The Role of Workflows Within the MaterialDigital Initiative
Advancing Digital Transformation in Material Science: The Role of Workflows Within the MaterialDigital Initiative Open
The MaterialDigital initiative represents a major driver toward the digitalization of material science. Next to providing a prototypical infrastructure required for building a shared data space and working on semantic interoperability of d…
View article: Regularization of softening plasticity models for explicit dynamics using a gradient-enhanced modified Johnson–Holmquist model
Regularization of softening plasticity models for explicit dynamics using a gradient-enhanced modified Johnson–Holmquist model Open
View article: Bias Identification Approaches for Model Updating of Simulation-based Digital Twins of Bridges
Bias Identification Approaches for Model Updating of Simulation-based Digital Twins of Bridges Open
. Simulation-based digital twins of bridges have the potential not only to serve as monitoring devices of the current state of the structure but also to generate new knowledge through physical predictions that allow for better-informed dec…
View article: Posterior sampling with Adaptive Gaussian Processes in Bayesian parameter identification
Posterior sampling with Adaptive Gaussian Processes in Bayesian parameter identification Open
Posterior sampling by Monte Carlo methods provides a more comprehensive solution approach to inverse problems than computing point estimates such as the maximum posterior using optimization methods, at the expense of usually requiring many…
View article: A Bayesian framework for constitutive model identification via use of full field measurements, with application to heterogeneous materials
A Bayesian framework for constitutive model identification via use of full field measurements, with application to heterogeneous materials Open
View article: Embedded Model Form Uncertainty Quantification with Measurement Noise for Bayesian Model Calibration
Embedded Model Form Uncertainty Quantification with Measurement Noise for Bayesian Model Calibration Open
A key factor in ensuring the accuracy of computer simulations that model physical systems is the proper calibration of their parameters based on real-world observations or experimental data. Inevitably, uncertainties arise, and Bayesian me…
View article: Model Bias Identification for Bayesian Calibration of Stochastic Digital Twins of Bridges
Model Bias Identification for Bayesian Calibration of Stochastic Digital Twins of Bridges Open
Simulation‐based digital twins must provide accurate, robust, and reliable digital representations of their physical counterparts. Therefore, quantifying the uncertainty in their predictions plays a key role in making better‐informed decis…
View article: Adaptive Gaussian Process Regression for Bayesian inverse problems
Adaptive Gaussian Process Regression for Bayesian inverse problems Open
We introduce a novel adaptive Gaussian Process Regression (GPR) methodology for efficient construction of surrogate models for Bayesian inverse problems with expensive forward model evaluations. An adaptive design strategy focuses on optim…
View article: PGD in thermal transient problems with a moving heat source: A sensitivity study on factors affecting accuracy and efficiency
PGD in thermal transient problems with a moving heat source: A sensitivity study on factors affecting accuracy and efficiency Open
Thermal transient problems, essential for modeling applications like welding and additive metal manufacturing, are characterized by a dynamic evolution of temperature. Accurately simulating these phenomena is often computationally expensiv…
View article: Efficient bead-on-plate weld model for parameter estimation towards effective wire arc additive manufacturing simulation
Efficient bead-on-plate weld model for parameter estimation towards effective wire arc additive manufacturing simulation Open
View article: From concrete mixture to structural design—a holistic optimization procedure in the presence of uncertainties
From concrete mixture to structural design—a holistic optimization procedure in the presence of uncertainties Open
We propose a systematic design approach for the precast concrete industry to promote sustainable construction practices. By employing a holistic optimization procedure, we combine the concrete mixture design and structural simulations in a…
View article: An Efficient Localized Model Order Reduction Framework for the Shape Optimization of Additively Manufactured Lattice Structures
An Efficient Localized Model Order Reduction Framework for the Shape Optimization of Additively Manufactured Lattice Structures Open
View article: Model bias identification for Bayesian calibration of stochastic digital twins of bridges
Model bias identification for Bayesian calibration of stochastic digital twins of bridges Open
Simulation-based digital twins must provide accurate, robust and reliable digital representations of their physical counterparts. Quantifying the uncertainty in their predictions plays, therefore, a key role in making better-informed decis…
View article: Wissensbasierte Digitalisierung von betontechnologischen Materialdaten
Wissensbasierte Digitalisierung von betontechnologischen Materialdaten Open
Kurzfassung Die sprunghaft zunehmende Wichtigkeit von FAIR‐ und Open‐Data für die Qualitätssicherung, aber auch für die Nachnutzbarkeit von Daten und den Erkenntnisfortschritt führt zu enormem Handlungsbedarf in Forschung und Entwicklung. …
View article: A Bayesian Framework for Simulation‐based Digital Twins of Bridges
A Bayesian Framework for Simulation‐based Digital Twins of Bridges Open
Simulation‐based digital twins have emerged as a powerful tool for evaluating the mechanical response of bridges. As virtual representations of physical systems, digital twins can provide a wealth of information that complements traditiona…
View article: Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction
Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction Open
In this article, a methodology for fine scale modeling of large scale linear elastic structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale …
View article: Temperature dependent modelling approach for early age behavior of printable mortars
Temperature dependent modelling approach for early age behavior of printable mortars Open
Structural build-up describes the stability and early-age strength development of fresh mortar used in 3D printing. It is influenced by several factors, i.e. the composition of the printable material, the printing regime, and the ambient c…
View article: Bayesian model calibration and damage detection for a digital twin of a bridge demonstrator
Bayesian model calibration and damage detection for a digital twin of a bridge demonstrator Open
Using digital twins for decision making is a very promising concept which combines simulation models with corresponding experimental sensor data in order to support maintenance decisions or to investigate the reliability. The quality of th…
View article: EVALUATION OF MODEL BIAS IDENTIFICATION APPROACHES BASED ON BAYESIAN INFERENCE AND APPLICATIONS TO DIGITAL TWINS
EVALUATION OF MODEL BIAS IDENTIFICATION APPROACHES BASED ON BAYESIAN INFERENCE AND APPLICATIONS TO DIGITAL TWINS Open
In recent years, the use of simulation-based digital twins for monitoring and assessment of complex mechanical systems has greatly expanded.Their potential to increase the information obtained from limited data makes them an invaluable too…
View article: Evaluation of tools for describing, reproducing and reusing scientific workflows
Evaluation of tools for describing, reproducing and reusing scientific workflows Open
In the field of computational science and engineering, workflows often entail the application of various software, for instance, for simulation or pre- and postprocessing. Typically, these components have to be combined in arbitrarily comp…
View article: Bayesian inference for random field parameters with a goal-oriented quality control of the PGD forward model’s accuracy
Bayesian inference for random field parameters with a goal-oriented quality control of the PGD forward model’s accuracy Open
Numerical models built as virtual-twins of a real structure (digital-twins) are considered the future of monitoring systems. Their setup requires the estimation of unknown parameters, which are not directly measurable. Stochastic model ide…
View article: A Perspective on Digital Knowledge Representation in Materials Science and Engineering
A Perspective on Digital Knowledge Representation in Materials Science and Engineering Open
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, …
View article: Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction
Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction Open
In this paper, a methodology for fine scale modeling of large scale structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse sca…
View article: A Three-Phase Transport Model for High-Temperature Concrete Simulations Validated with X-ray CT Data
A Three-Phase Transport Model for High-Temperature Concrete Simulations Validated with X-ray CT Data Open
Concrete exposure to high temperatures induces thermo-hygral phenomena, causing water phase changes, buildup of pore pressure and vulnerability to spalling. In order to predict these phenomena under various conditions, a three-phase transp…
View article: A three-phase transport model for high-temperature concrete simulations validated with X-ray CT data
A three-phase transport model for high-temperature concrete simulations validated with X-ray CT data Open
Concrete exposure to high temperatures induces thermo-hygral phenomena, causing water phase changes, buildup of pore pressure and vulnerability to spalling. In order to predict these phenomena under various conditions, a three-phase transp…
View article: A three-phase transport model for high-temperature concrete simulations validated with X-ray CT data
A three-phase transport model for high-temperature concrete simulations validated with X-ray CT data Open
Concrete exposure to high temperatures induces thermo-hygral phenomena, causing water phase changes, buildup of pore pressure and vulnerability to spalling. In order to predict these phenomena under various conditions, a three-phase transp…
View article: A three-phase transport model for high-temperature concrete simulations validated with X-ray CT data
A three-phase transport model for high-temperature concrete simulations validated with X-ray CT data Open
Concrete exposure to high temperatures induces thermo-hygral phenomena, causing water phase changes, buildup of pore pressure and vulnerability to spalling. In order to predict these phenomena under various conditions, a three-phase transp…