Refine
Document Type
- Article (254)
- Doctoral Thesis (56)
- Conference Proceeding (23)
- Preprint (6)
- Master's Thesis (5)
- Diploma Thesis (1)
- Habilitation (1)
Institute
- Institut für Strukturmechanik (ISM) (346) (remove)
Keywords
- Angewandte Mathematik (195)
- Strukturmechanik (186)
- Stochastik (40)
- Maschinelles Lernen (27)
- Computerunterstütztes Verfahren (22)
- OA-Publikationsfonds2020 (19)
- Architektur <Informatik> (17)
- Finite-Elemente-Methode (17)
- Machine learning (15)
- Angewandte Informatik (12)
- CAD (10)
- machine learning (10)
- Optimierung (8)
- Computer Science Models in Engineering; Multiscale and Multiphysical Models; Scientific Computing (7)
- Erdbeben (7)
- Deep learning (6)
- OA-Publikationsfonds2022 (6)
- Wärmeleitfähigkeit (6)
- big data (6)
- Neuronales Netz (5)
- Peridynamik (5)
- Beton (4)
- Building Information Modeling (4)
- Isogeometric Analysis (4)
- Modellierung (4)
- Polymere (4)
- finite element method (4)
- rapid visual screening (4)
- Batterie (3)
- Data, information and knowledge modeling in civil engineering; Function theoretic methods and PDE in engineering sciences; Mathematical methods for (robotics and) computer vision; Numerical modeling in engineering; Optimization in engineering applications (3)
- Fuzzy-Logik (3)
- Isogeometrische Analyse (3)
- Künstliche Intelligenz (3)
- Mehrskalenmodell (3)
- NURBS (3)
- OA-Publikationsfonds2018 (3)
- OA-Publikationsfonds2021 (3)
- Optimization (3)
- Peridynamics (3)
- Phasenfeldmodell (3)
- Schaden (3)
- Simulation (3)
- Strukturdynamik (3)
- Variational principle (3)
- artificial intelligence (3)
- artificial neural networks (3)
- damaged buildings (3)
- earthquake (3)
- earthquake safety assessment (3)
- random forest (3)
- support vector machine (3)
- Abaqus (2)
- Artificial neural network (2)
- Biodiesel (2)
- Bridges (2)
- Bruch (2)
- Bruchmechanik (2)
- Defekt (2)
- Dynamik (2)
- Elastizität (2)
- Erdbebensicherheit (2)
- FEM (2)
- Fahrleitung (2)
- Fehlerabschätzung (2)
- Fluid (2)
- Fotovoltaik (2)
- Fracture (2)
- Fracture mechanics (2)
- Intelligente Stadt (2)
- Internet of things (2)
- Mechanische Eigenschaft (2)
- Mehrgitterverfahren (2)
- Mehrskalenanalyse (2)
- Mikrokapsel (2)
- Modalanalyse (2)
- Multiscale modeling (2)
- Nanomechanik (2)
- Nanostrukturiertes Material (2)
- Nanoverbundstruktur (2)
- Nichtlineare Finite-Elemente-Methode (2)
- OA-Publikationsfonds2019 (2)
- Partielle Differentialgleichung (2)
- Phase-field modeling (2)
- Riss (2)
- Rissausbreitung (2)
- SHM (2)
- Schwingung (2)
- Staumauer (2)
- Tragfähigkeit (2)
- Transfer learning (2)
- Uncertainty (2)
- Unsicherheit (2)
- Vulnerability assessment (2)
- XFEM (2)
- buildings (2)
- clustering (2)
- continuum mechanics (2)
- crack (2)
- dams (2)
- data science (2)
- extreme learning machine (2)
- mathematical modeling (2)
- multiphase (2)
- multiscale (2)
- nanocomposite (2)
- optimization (2)
- reinforcement learning (2)
- smart cities (2)
- soft computing techniques (2)
- stochastic (2)
- urban morphology (2)
- variational principle (2)
- vulnerability assessment (2)
- wireless sensor networks (2)
- 2D/3D Adaptive Mesh Refinement (1)
- 3D printing (1)
- 3D reinforced concrete buildings (1)
- 3D-Druck (1)
- ANN modeling (1)
- Abbruch (1)
- Activation function (1)
- Adaptive Pushover (1)
- Adaptive central high resolution schemes (1)
- Adaptives System (1)
- Adaptives Verfahren (1)
- Aerodynamic Stability (1)
- Aerodynamic derivatives (1)
- Aerodynamik (1)
- Akkumulator (1)
- Algorithmus (1)
- Arc-direct energy deposition (1)
- Artificial Intelligence (1)
- Auswirkung (1)
- Autogenous (1)
- Autonomous (1)
- B-Spline (1)
- B-Spline Finite Elemente (1)
- B-spline (1)
- Battery (1)
- Battery development (1)
- Baustahl (1)
- Bayes (1)
- Bayes neuronale Netze (1)
- Bayes-Verfahren (1)
- Bayesian Inference, Uncertainty Quantification (1)
- Bayesian inference (1)
- Bayesian method (1)
- Bayesian neural networks (1)
- Bayes’schen Inferenz (1)
- Beam-to-column connection; semi-rigid; flush end-plate connection; moment-rotation curve (1)
- Berechnung (1)
- Beschleunigungsmessung (1)
- Beschädigung (1)
- Bildanalyse (1)
- Biomechanics (1)
- Biomechanik (1)
- Bodenmechanik (1)
- Bodentemperatur (1)
- Bornitrid (1)
- Bridge (1)
- Bridge aerodynamics (1)
- Bruchverhalten (1)
- Brustkorb (1)
- Brücke (1)
- Brückenbau (1)
- Bubble column reactor (1)
- Building safety assessment (1)
- CFD (1)
- Capsular clustering; Design of microcapsules (1)
- Carbon nanotubes (1)
- Catenary poles (1)
- Chirurgie (1)
- Cohesive surface technique (1)
- Collocation method (1)
- Computational fracture modeling (1)
- Computermodellierung des Bruchverhaltens (1)
- Computersimulation (1)
- Concrete (1)
- Concrete catenary pole (1)
- ContikiMAC (1)
- Continuous-Time Markov Chain (1)
- Continuum Mechnics (1)
- Control system (1)
- Cost-Benefit Analysis (1)
- Damage (1)
- Damage Identification (1)
- Damage accumulation (1)
- Damage identification (1)
- Damm (1)
- Damping (1)
- Dams (1)
- Data Mining (1)
- Data, information and knowledge modeling in civil engineering (1)
- Data-driven (1)
- Deal ii C++ code (1)
- Demolition (1)
- Design Spectra (1)
- Diskontinuumsmechanik (1)
- Diskrete-Elemente-Methode (1)
- Dissertation (1)
- Domain Adaptation (1)
- Dreidimensionales Modell (1)
- Druckluft (1)
- Dual phase steel (1)
- Dual-support (1)
- ELM (1)
- Earthquake (1)
- Electrochemical properties (1)
- Elektrochemische Eigenschaft (1)
- Elektrode (1)
- Elektrodenmaterial (1)
- Elektrostatische Welle (1)
- Empire XPU 8.01 (1)
- Energieeffizienz (1)
- Energiespeichersystem (1)
- Energiespeicherung (1)
- Entropie (1)
- Entwurf von Mikrokapseln (1)
- Erbeben (1)
- Erneuerbare Energien (1)
- Erweiterte Finite-Elemente-Methode (1)
- Explicit finite element method (1)
- Fachwerkbau (1)
- Fahrleitungsmast (1)
- Fatigue life (1)
- Fernerkung (1)
- Festkörpermechanik (1)
- Feststoff (1)
- Fiber Reinforced Composite (1)
- Finite Element Method (1)
- Finite Element Model (1)
- Flattern (1)
- Flexoelectricity (1)
- Fluid-Structure Interaction (1)
- Flutter (1)
- Fracture Computational Model (1)
- Full waveform inversion (1)
- Function theoretic methods and PDE in engineering sciences (1)
- Funktechnik (1)
- Fuzzy Logic (1)
- Fuzzy logic (1)
- Fuzzy-Regelung (1)
- Gasleitung (1)
- Gaussian process regression (1)
- Gebäude (1)
- Geoinformatik (1)
- Geometric Modeling (1)
- Geometric Partial Differential Equations (1)
- Geometrie (1)
- Geometry Independent Field Approximation (1)
- Geschwindigkeit (1)
- Gesundheitsinformationssystem (1)
- Gesundheitswesen (1)
- Gewebeverbundwerkstoff (1)
- Goal-oriented A Posteriori Error Estimation (1)
- Graphen (1)
- Graphene (1)
- Grauguss (1)
- Gravel-bed rivers (1)
- Grundwasser (1)
- Größenverhältnis (1)
- Guyed antenna masts (1)
- HPC (1)
- Healing (1)
- High-speed electric train (1)
- High-speed railway bridge (1)
- Hochbau (1)
- Holzkonstruktion (1)
- Homogenisieren (1)
- Homogenisierung (1)
- Homogenization (1)
- Hydraulic geometry (1)
- Hydrodynamik (1)
- Hydrological drought (1)
- Hyperbolic PDEs (1)
- IOT (1)
- Impact (1)
- Implicit (1)
- Incompressibility (1)
- Infrastructures (1)
- Ingenieurwissenschaften (1)
- Instandhaltung (1)
- Internet der Dinge (1)
- Internet der dinge (1)
- Internet of Things (1)
- Inverse Probleme (1)
- Inverse Problems (1)
- Inverse analysis (1)
- Inverse problems (1)
- Isogeometrc Analysis (1)
- K-nearest neighbors (1)
- KNN (1)
- Kapselclustern (1)
- Kaverne (1)
- Keramik (1)
- Kirchoff--love theory (1)
- Klüftung (1)
- Kohlenstoff Nanoröhre (1)
- Kohäsionsflächenverfahren (1)
- Kollokationsmethode (1)
- Konjugierte-Gradienten-Methode (1)
- Kontinuierliche Simul (1)
- Kontinuumsmechanik (1)
- Kosten-Nutzen-Analyse (1)
- Körper (1)
- Kühlkörper (1)
- Land surface temperature (1)
- Lebensdauerabschätzung (1)
- Lebenszyklus (1)
- Loading sequence (1)
- Local maximum entropy approximants (1)
- Lufttemperatur (1)
- Lösungsverfahren (1)
- M5 model tree (1)
- MATLAB (1)
- MDLSM method (1)
- Machine Learning (1)
- Markov-Kette mit stetiger Zeit (1)
- Marmara Region (1)
- Maschinenbau (1)
- Mass Tuned Damper (1)
- Material (1)
- Materialverhalten (1)
- Materialversagen (1)
- Mathematical methods for (robotics and) computer vision (1)
- Matlab (1)
- Mechanical properties (1)
- Mechanik (1)
- Membrane contactors (1)
- Mensch (1)
- Mesh Refinement (1)
- Meso-Scale (1)
- Messtechnik (1)
- Mikro-Scale (1)
- Mild steel (1)
- MoS2 (1)
- Model assessment (1)
- Model-free status monitoring (1)
- Modellbildung (1)
- Modellkalibrierung (1)
- Modezuordung (1)
- Molecular Dynamics Simulation (1)
- Molecular Liquids (1)
- Molekulardynamik (1)
- Molekülstruktur (1)
- Monte-Carlo-Integration (1)
- Monte-Carlo-Simulation (1)
- Morphologie (1)
- Motion-induced forces (1)
- Multi-criteria decision making (1)
- Multi-objective Evolutionary Optimization, Elitist Non- Dominated Sorting Evolution Strategy (ENSES), Sandwich Structure, Pareto-Optimal Solutions, Evolutionary Algorithm (1)
- Multi-scale modeling (1)
- Multiphysics (1)
- Muscle model (1)
- Muskel (1)
- NURBS geometry (1)
- Nachhaltigkeit (1)
- Nanocomposite materials (1)
- Nanofluid (1)
- Nanomaterial (1)
- Nanomaterials (1)
- Nanomechanical Resonators (1)
- Nanopore (1)
- Nanoporöser Stoff (1)
- Nanoribbons, thermal conductivity (1)
- Nanostructures (1)
- Nasskühlung (1)
- Naturkatastrophe (1)
- Navier–Stokes equations (1)
- Neuronales Lernen (1)
- Nichtlokale Operatormethode (1)
- Nitratbelastung (1)
- Nonlocal operator method (1)
- Numerical Simulation (1)
- Numerical Simulations (1)
- Numerical modeling in engineering (1)
- Numerische Berechnung (1)
- Numerische Mathematik (1)
- OA-Publikationsfonds2023 (1)
- Oberflächentemperatur (1)
- Oberleitungsmasten (1)
- Operante Konditionierung (1)
- Operational modal analysis (1)
- Operator energy functional (1)
- Optimization in engineering applications (1)
- Optimization problems (1)
- PDEs (1)
- PU Enrichment method (1)
- Parameteridentification (1)
- Parameteridentifikation (1)
- Partial Differential Equations (1)
- Passive damper (1)
- Phase field method (1)
- Phase field model (1)
- Phase-field model (1)
- Physics informed neural network (1)
- Physikalische Eigenschaft (1)
- Piezoelectricity (1)
- Polykristall (1)
- Polymer compound (1)
- Polymer nanocomposites (1)
- Polymers (1)
- Polymerverbindung (1)
- Polymorphie (1)
- Polynomial Splines over Hierarchical T-meshes (1)
- Potential problem (1)
- RC Buildings (1)
- RSSI (1)
- Railway bridges (1)
- Rainflow counting algorithm (1)
- Rapid Visual Assessment (1)
- Rapid Visual Screening (1)
- Recovery Based Error Estimator (1)
- Referenzfläche (1)
- Rehabilitation (1)
- Reliability Analysis (1)
- Reliability Theory (1)
- Renewable energy (1)
- Residual-based variational multiscale method (1)
- Resonator (1)
- Rotorblatt (1)
- Schadenerkennung (1)
- Schadensakkumulation (1)
- Schadensdetektionsverfahren (1)
- Schadenserkennung (1)
- Schadensmechanik (1)
- Schubspannung (1)
- Schwellenwert (1)
- Schwingungsanalyse (1)
- Schwingungsdämpfer (1)
- Schädigung (1)
- Schätztheorie (1)
- Seismic Vulnerability (1)
- Seismic risk (1)
- Selbstheilendem Beton (1)
- Selbstheilung (1)
- Self-healing concrete (1)
- Semi-active damper (1)
- Sensitivity (1)
- Sensitivitätsanalyse (1)
- Sensor (1)
- Sigmoid function (1)
- Simulationsprozess (1)
- Solar (1)
- Spannungs-Dehnungs-Beziehung (1)
- Sprödbruch (1)
- Stabilität (1)
- Stahlbau (1)
- Stahlbetonkonstruktion (1)
- Standsicherheit (1)
- Staudamm (1)
- Steifigkeit (1)
- Stiffness matrix (1)
- Stochastic Subspace Identification (1)
- Stochastic analysis (1)
- Stoffeigenschaft (1)
- Stress-strain curve (1)
- Strukturanalyse (1)
- Strukturoptimierung (1)
- Strömungsmechanik (1)
- Stütze (1)
- Super Healing (1)
- Surface effects (1)
- Sustainability (1)
- Sustainable production (1)
- System Identification (1)
- Systemidentifikation (1)
- TPOGS (1)
- Talsperre (1)
- Taylor Series Expansion (1)
- Taylor series expansion (1)
- Thermal Fluid-Structure Interaction (1)
- Thermal conductivity (1)
- Thermoelastic damping (1)
- Thermoelasticity (1)
- Thermoelastizität (1)
- Thin shell (1)
- Thorax (1)
- Tichonov-Regularisierung (1)
- Tikhonov regularization (1)
- Träger (1)
- Tsallis entropy (1)
- Uncertainty analysis (1)
- Unschärfequantifizierung (1)
- Variationsprinzip (1)
- Verbundwerkstoff (1)
- Vernetzung (1)
- Vesicle dynamics (1)
- Vesikel (1)
- Vortex Induced Vibration (1)
- Vulnerability (1)
- Wasserbau (1)
- Wave propagation (1)
- Wavelet (1)
- Wavelet based adaptation (1)
- Wechselwirkung (1)
- Werkstoff (1)
- Werkstoffdämpfung (1)
- Werkstoffprüfung (1)
- Wind Energy (1)
- Wind Turbines (1)
- Wind load (1)
- Windenergie (1)
- Windkraftwerk (1)
- Windlast (1)
- Windturbine (1)
- Zementbeton (1)
- Zustandsraummodell (1)
- Zuverlässigkeitsanalyse (1)
- Zuverlässigkeitstheorie (1)
- action recognition (1)
- adaptive neuro-fuzzy inference system (ANFIS) (1)
- adaptive pushover (1)
- adaptive simulation (1)
- ant colony optimization algorithm (ACO) (1)
- artificial neural network (1)
- atomistic simulation methods (1)
- automatic modal analysis (1)
- back-pressure (1)
- battery (1)
- beton (1)
- biodiesel (1)
- brittle fracture (1)
- buckling (1)
- building information modelling (1)
- capsular clustering (1)
- ceramics (1)
- circumferential contact length (1)
- classification (1)
- classifier (1)
- clear channel assessments (1)
- cluster density (1)
- cluster shape (1)
- cohesive elements (1)
- composite (1)
- computation (1)
- computational fluid dynamics (CFD) (1)
- computational hydraulics (1)
- concrete (1)
- congestion control (1)
- conjugate gradient method (1)
- continuum damage mechanics (1)
- coronary artery disease (1)
- crack detection (1)
- crack identification (1)
- cylindrical shell structures (1)
- damage (1)
- damage identification (1)
- decay experiments (1)
- deep learning (1)
- deep learning neural network (1)
- deep neural network (1)
- defects (1)
- diesel engines (1)
- dimensionality reduction (1)
- diskontinuum mechanics (1)
- dissimilarity measures (1)
- domain decomposition (1)
- dual-support (1)
- duty-cycles (1)
- earthquake damage (1)
- earthquake vulnerability assessment (1)
- effective properties (1)
- electromagnetic waves (1)
- energy consumption (1)
- energy dissipation (1)
- energy efficiency (1)
- energy form (1)
- energy, exergy (1)
- ensemble model (1)
- estimation (1)
- explicit time integration (1)
- extreme events (1)
- extreme pressure (1)
- finite element (1)
- firefly optimization algorithm (1)
- flow pattern (1)
- fog computing (1)
- food informatics (1)
- fractional-order control (1)
- full-waveform inversion (1)
- fused filament fabrication (1)
- fuzzy decision making (1)
- gas pipes (1)
- genetic algorithm (1)
- genetic programming (1)
- geoinformatics (1)
- gradient elasticity (1)
- grid-based (1)
- ground structure (1)
- ground water contamination (1)
- growth mode (1)
- gully erosion susceptibility (1)
- health (1)
- health informatics (1)
- heart disease diagnosis (1)
- heat sink (1)
- heterogeneous material (1)
- high-performance computing (1)
- human blob (1)
- human body proportions (1)
- hybrid machine learning (1)
- hybrid machine learning model (1)
- hybride Werkstoffe (1)
- hydraulic jump (1)
- hydrological model (1)
- hydrology (1)
- image processing (1)
- industry 4.0 (1)
- intergranular damage (1)
- inverse analysis (1)
- isogeometric analysis (1)
- isogeometric methods (1)
- jointed rock (1)
- least square support vector machine (LSSVM) (1)
- level set method (1)
- longitudinal dispersion coefficient (1)
- maschinelles Lernen (1)
- material failure (1)
- matrix-free (1)
- maximum stress (1)
- mehrphasig (1)
- microcapsule (1)
- mitigation (1)
- modal analysis (1)
- modal damping (1)
- modal parameter estimation (1)
- modal tracking (1)
- mode pairing (1)
- model updating (1)
- molecular dynamics (1)
- mortar method (1)
- multigrid (1)
- multigrid method (1)
- multiscale method (1)
- nanofluid (1)
- nanoreinforced composites (1)
- nanosheets (1)
- natural hazard (1)
- neural architecture search (1)
- neural networks (NNs) (1)
- nonlocal Hessian operator (1)
- nonlocal operator method (1)
- numerical methods (1)
- numerical modelling (1)
- operator energy functional (1)
- optimal sensor positions (1)
- optimale Sensorpositionierung (1)
- parameter identification (1)
- partical swarm optimization (1)
- passive control (1)
- peridynamics (1)
- phase field (1)
- phase field fracture method (1)
- photovoltaic (1)
- photovoltaic-thermal (PV/T) (1)
- physical activities (1)
- polymorphe Unschärfemodellierung (1)
- precipitation (1)
- prediction (1)
- predictive model (1)
- principal component analysis (1)
- public health (1)
- public space (1)
- quasicontinuum method (1)
- randomized spectral representation (1)
- rapid assessment (1)
- rapid classification (1)
- received signal strength indicator (1)
- recovery-based and residual-based error estimators (1)
- remote sensing (1)
- residential buildings (1)
- response surface methodology (1)
- rice (1)
- rivers (1)
- rule based classification (1)
- scalable smeared crack analysis (1)
- scale transition (1)
- seasonal precipitation (1)
- seismic assessment (1)
- seismic control (1)
- seismic hazard analysis (1)
- seismic risk estimation (1)
- seismic vulnerability (1)
- self healing concrete (1)
- self-healing concrete (1)
- signal processing (1)
- site-specific spectrum (1)
- smart sensors (1)
- smooth rectangular channel (1)
- smoothed particle hydrodynamics (1)
- soil temperature (1)
- solver (1)
- spatial analysis (1)
- spatiotemporal database (1)
- spearman correlation coefficient (1)
- square root cubature calman filter (1)
- standard deviation of pressure fluctuations (1)
- statistical analysis (1)
- statistical coeffcient of the probability distribution (1)
- stilling basin (1)
- stochastic subspace identification (1)
- structural control (1)
- structural dynamics (1)
- sugarcane (1)
- supervised learning (1)
- support vector regression (1)
- sustainability (1)
- tall buildings (1)
- thermal conductivity (1)
- three-dimensional truss structures (1)
- topology optimization (1)
- tuned mass damper (1)
- tuned mass dampers (1)
- type-3 fuzzy systems (1)
- urban health (1)
- urban sustainability (1)
- vibration-based damage identification (1)
- vibration-based methodology (1)
- water quality (1)
- wave propagation (1)
- wavelet transform (1)
- weak form (1)
- weighted residual method (1)
- wind turbine rotor blades (1)
- wireless sensor network (1)
- woven composites (1)
The computational costs of newly developed numerical simulation play a critical role in their acceptance within both academic use and industrial employment. Normally, the refinement of a method in the area of interest reduces the computational cost. This is unfortunately not true for most nonlocal simulation, since refinement typically increases the size of the material point neighborhood. Reducing the discretization size while keep- ing the neighborhood size will often require extra consideration. Peridynamic (PD) is a newly developed numerical method with nonlocal nature. Its straightforward integral form equation of motion allows simulating dynamic problems without any extra consideration required. The formation of crack and its propagation is known as natural to peridynamic. This means that discontinuity is a result of the simulation and does not demand any post-processing. As with other nonlocal methods, PD is considered an expensive method. The refinement of the nodal spacing while keeping the neighborhood size (i.e., horizon radius) constant, emerges to several nonphysical phenomena.
This research aims to reduce the peridynamic computational and imple- mentation costs. A novel refinement approach is introduced. The pro- posed approach takes advantage of the PD flexibility in choosing the shape of the horizon by introducing multiple domains (with no intersections) to the nodes of the refinement zone. It will be shown that no ghost forces will be created when changing the horizon sizes in both subdomains. The approach is applied to both bond-based and state-based peridynamic and verified for a simple wave propagation refinement problem illustrating the efficiency of the method. Further development of the method for higher dimensions proves to have a direct relationship with the mesh sensitivity of the PD. A method for solving the mesh sensitivity of the PD is intro- duced. The application of the method will be examined by solving a crack propagation problem similar to those reported in the literature.
New software architecture is proposed considering both academic and in- dustrial use. The available simulation tools for employing PD will be collected, and their advantages and drawbacks will be addressed. The challenges of implementing any node base nonlocal methods while max- imizing the software flexibility to further development and modification will be discussed and addressed. A software named Relation-Based Sim- ulator (RBS) is developed for examining the proposed architecture. The exceptional capabilities of RBS will be explored by simulating three distinguished models. RBS is available publicly and open to further develop- ment. The industrial acceptance of the RBS will be tested by targeting its performance on one Mac and two Linux distributions.
The aim of this study is controlling of spurious oscillations developing around discontinuous solutions of both linear and non-linear wave equations or hyperbolic partial differential equations (PDEs). The equations include both first-order and second-order (wave) hyperbolic systems. In these systems even smooth initial conditions, or smoothly varying source (load) terms could lead to discontinuous propagating solutions (fronts). For the first order hyperbolic PDEs, the concept of central high resolution schemes is integrated with the multiresolution-based adaptation to capture properly both discontinuous propagating fronts and effects of fine-scale responses on those of larger scales in the multiscale manner. This integration leads to using central high resolution schemes on non-uniform grids; however, such simulation is unstable, as the central schemes are originally developed to work properly on uniform cells/grids. Hence, the main concern is stable collaboration of central schemes and multiresoltion-based cell adapters. Regarding central schemes, the considered approaches are: 1) Second order central and central-upwind schemes; 2) Third order central schemes; 3) Third and fourth order central weighted non-oscillatory schemes (central-WENO or CWENO); 4) Piece-wise parabolic methods (PPMs) obtained with two different local stencils. For these methods, corresponding (nonlinear) stability conditions are studied and modified, as well. Based on these stability conditions several limiters are modified/developed as follows: 1) Several second-order limiters with total variation diminishing (TVD) feature, 2) Second-order uniformly high order accurate non-oscillatory (UNO) limiters, 3) Two third-order nonlinear scaling limiters, 4) Two new limiters for PPMs. Numerical results show that adaptive solvers lead to cost-effective computations (e.g., in some 1-D problems, number of adapted grid points are less than 200 points during simulations, while in the uniform-grid case, to have the same accuracy, using of 2049 points is essential). Also, in some cases, it is confirmed that fine scale responses have considerable effects on higher scales.
In numerical simulation of nonlinear first order hyperbolic systems, the two main concerns are: convergence and uniqueness. The former is important due to developing of the spurious oscillations, the numerical dispersion and the numerical dissipation. Convergence in a numerical solution does not guarantee that it is the physical/real one (the uniqueness feature). Indeed, a nonlinear systems can converge to several numerical results (which mathematically all of them are true). In this work, the convergence and uniqueness are directly studied on non-uniform grids/cells by the concepts of local numerical truncation error and numerical entropy production, respectively. Also, both of these concepts have been used for cell/grid adaptations. So, the performance of these concepts is also compared by the multiresolution-based method. Several 1-D and 2-D numerical examples are examined to confirm the efficiency of the adaptive solver. Examples involve problems with convex and non-convex fluxes. In the latter case, due to developing of complex waves, proper capturing of real answers needs more attention. For this purpose, using of method-adaptation seems to be essential (in parallel to the cell/grid adaptation). This new type of adaptation is also performed in the framework of the multiresolution analysis.
Regarding second order hyperbolic PDEs (mechanical waves), the regularization concept is used to cure artificial (numerical) oscillation effects, especially for high-gradient or discontinuous solutions. There, oscillations are removed by the regularization concept acting as a post-processor. Simulations will be performed directly on the second-order form of wave equations. It should be mentioned that it is possible to rewrite second order wave equations as a system of first-order waves, and then simulated the new system by high resolution schemes. However, this approach ends to increasing of variable numbers (especially for 3D problems).
The numerical discretization is performed by the compact finite difference (FD) formulation with desire feature; e.g., methods with spectral-like or optimized-error properties. These FD methods are developed to handle high frequency waves (such as waves near earthquake sources). The performance of several regularization approaches is studied (both theoretically and numerically); at last, a proper regularization approach controlling the Gibbs phenomenon is recommended.
At the end, some numerical results are provided to confirm efficiency of numerical solvers enhanced by the regularization concept. In this part, shock-like responses due to local and abrupt changing of physical properties, and also stress wave propagation in stochastic-like domains are studied.
Finite Element Simulations of dynamically excited structures are mainly influenced by the mass, stiffness, and damping properties of the system, as well as external loads. The prediction quality of dynamic simulations of vibration-sensitive components depends significantly on the use of appropriate damping models. Damping phenomena have a decisive influence on the vibration amplitude and the frequencies of the vibrating structure. However, developing realistic damping models is challenging due to the multiple sources that cause energy dissipation, such as material damping, different types of friction, or various interactions with the environment.
This thesis focuses on thermoelastic damping, which is the main cause of material damping in homogeneous materials. The effect is caused by temperature changes due to mechanical strains. In vibrating structures, temperature gradients arise in adjacent tension and compression areas. Depending on the vibration frequency, they result in heat flows, leading to increased entropy and the irreversible transformation of mechanical energy into thermal energy.
The central objective of this thesis is the development of efficient simulation methods to incorporate thermoelastic damping in finite element analyses based on modal superposition. The thermoelastic loss factor is derived from the structure's mechanical mode shapes and eigenfrequencies. In subsequent analyses that are performed in the time and frequency domain, it is applied as modal damping.
Two approaches are developed to determine the thermoelastic loss in thin-walled plate structures, as well as three-dimensional solid structures. The realistic representation of the dissipation effects is verified by comparing the simulation results with experimentally determined data. Therefore, an experimental setup is developed to measure material damping, excluding other sources of energy dissipation.
The three-dimensional solid approach is based on the determination of the generated entropy and therefore the generated heat per vibration cycle, which is a measure for thermoelastic loss in relation to the total strain energy. For thin plate structures, the amount of bending energy in a modal deformation is calculated and summarized in the so-called Modal Bending Factor (MBF). The highest amount of thermoelastic loss occurs in the state of pure bending. Therefore, the MBF enables a quantitative classification of the mode shapes concerning the thermoelastic damping potential.
The results of the developed simulations are in good agreement with the experimental results and are appropriate to predict thermoelastic loss factors. Both approaches are based on modal superposition with the advantage of a high computational efficiency. Overall, the modeling of thermoelastic damping represents an important component in a comprehensive damping model, which is necessary to perform realistic simulations of vibration processes.
Identification of modal parameters of a space frame structure is a complex assignment due to a large number of degrees of freedom, close natural frequencies, and different vibrating mechanisms. Research has been carried out on the modal identification of rather simple truss structures. So far, less attention has been given to complex three-dimensional truss structures. This work develops a vibration-based methodology for determining modal information of three-dimensional space truss structures. The method uses a relatively complex space truss structure for its verification. Numerical modelling of the system gives modal information about the expected vibration behaviour. The identification process involves closely spaced modes that are characterised by local and global vibration mechanisms. To distinguish between local and global vibrations of the system, modal strain energies are used as an indicator. The experimental validation, which incorporated a modal analysis employing the stochastic subspace identification method, has confirmed that considering relatively high model orders is required to identify specific mode shapes. Especially in the case of the determination of local deformation modes of space truss members, higher model orders have to be taken into account than in the modal identification of most other types of structures.
As an optimization that starts from a randomly selected structure generally does not guarantee reasonable optimality, the use of a systemic approach, named the ground structure, is widely accepted in steel-made truss and frame structural design. However, in the case of reinforced concrete (RC) structural optimization, because of the orthogonal orientation of structural members, randomly chosen or architect-sketched framing is used. Such a one-time fixed layout trend, in addition to its lack of a systemic approach, does not necessarily guarantee optimality. In this study, an approach for generating a candidate ground structure to be used for cost or weight minimization of 3D RC building structures with included slabs is developed. A multiobjective function at the floor optimization stage and a single objective function at the frame optimization stage are considered. A particle swarm optimization (PSO) method is employed for selecting the optimal ground structure. This method enables generating a simple, yet potential, real-world representation of topologically preoptimized ground structure while both structural and main architectural requirements are considered. This is supported by a case study for different floor domain sizes.
The study presents a Machine Learning (ML)-based framework designed to forecast the stress-strain relationship of arc-direct energy deposited mild steel. Based on microstructural characteristics previously extracted using microscopy and X-ray diffraction, approximately 1000 new parameter sets are generated by applying the Latin Hypercube Sampling Method (LHSM). For each parameter set, a Representative Volume Element (RVE) is synthetically created via Voronoi Tessellation. Input raw data for ML-based algorithms comprises these parameter sets or RVE-images, while output raw data includes their corresponding stress-strain relationships calculated after a Finite Element (FE) procedure. Input data undergoes preprocessing involving standardization, feature selection, and image resizing. Similarly, the stress-strain curves, initially unsuitable for training traditional ML algorithms, are preprocessed using cubic splines and occasionally Principal Component Analysis (PCA). The later part of the study focuses on employing multiple ML algorithms, utilizing two main models. The first model predicts stress-strain curves based on microstructural parameters, while the second model does so solely from RVE images. The most accurate prediction yields a Root Mean Squared Error of around 5 MPa, approximately 1% of the yield stress. This outcome suggests that ML models offer precise and efficient methods for characterizing dual-phase steels, establishing a framework for accurate results in material analysis.