Results 91 to 100 of about 43,852 (309)

Sparse identification of Lagrangian for nonlinear dynamical systems via proximal gradient method. [PDF]

Sci Rep, 2023
Purnomo A, Hayashibe M.
europepmc   +1 more source

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

Advanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi, Hadi Moutablaleh, Ignatius A. Setiawan, Mehrshad Mehrpouya   +3 more
wiley   +1 more source

Hybrid Analog Computer for Modeling Nonlinear Dynamical Systems: The Complete Cookbook. [PDF]

Sensors (Basel), 2023
Rujzl M, Polak L, Petrzela J.
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Balanced truncation of perturbative representations of nonlinear systems [PDF]

, 2007
The paper presents a novel approach for a balanced truncation style of model reduction of a perturbative representation of a nonlinear system. Empirical controllability and observability gramians for nonlinear systems are employed to define a projection ...
Condon, Marissa, Grahovski, Georgi G.
core  

Solution‐Processed Two‐Dimensional Indium Oxide on Sodium‐Embedded Alumina for Reconfigurable Optoelectronic Synaptic Transistors

Advanced Functional Materials, EarlyView.
Wafer‐scale two‐dimensioanl In2Se3 oxidized into InOx on sodium‐embedded beta‐alumina enables multifunctional reconfigurable electronics. Sodium ions accumulate within distinct spatial distribution under drain‐controlle and gate‐controlled operation. Drain‐control operation gives controllability of ultraviolet‐driven optoelectronic synaptic conductance
Jinhong Min, Yonghyun Albert Kwon, Hyunbin Kim, Jihyun Kim, Myeongjin Jung, Jaewon Heo, Gwang Ya Kim, Vlastimil Mazanek, Zdeněk Sofer, In Soo Kim, Jeong Ho Cho, Hyesung Park, Sang Min Won, Joohoon Kang   +13 more
wiley   +1 more source

Energy-Storage Balanced Reduction of Port-Hamiltonian Systems [PDF]

, 2003
Supported by the framework of dissipativity theory, a procedure based on physical energy to balance and reduce port-Hamiltonian systems with collocated inputs and outputs is presented.
Fujimoto, Kenji, Ricardo Lopezlena, Scherpen, Jacquelien M.A.,, Lopezlena, Ricardo, Jacquelien M. A. Scherpen, Scherpen, Jacquelien M.A., Jacquelien M.A. Scherpen, Lopezlena, Ricardo,, Fujimoto, Kenji,, Kenji Fujimoto   +9 more
core   +1 more source

Exponential observers for nonlinear dynamic systems

Information and Control, 1975
An observer theory is presented for nonlinear dynamic systems in this paper. Exponential observers are defined (asymptotic state estimators with exponentially decaying error). A Lyapunov-like method is introduced for the design of exponential observers.
Shauying R. Kou, David L. Elliott, Tzyh Jong Tarn   +2 more
openaire   +2 more sources

Deep multi-modal learning for joint linear representation of nonlinear dynamical systems. [PDF]

Sci Rep, 2022
Qian S, Chou CA, Li JS.
europepmc   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source