We present a simulation environment called SPIKELAB which incorporates a simulator that is able to simulate large networks of spiking neurons using a distributed event driven simulation. Contrary to a time driven simulation, which is usually used to simulate spiking neural networks, our simulation needs less computational resources because of the low average activity of typical networks. The paper addresses the speed up using an event driven versus a time driven simulation and how large networks can be simulated by a distribution of the simulation using already available computing resources. It also presents a solution for the integration of digital or analogue neuromorphic circuits into the simulation process.
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http://dx.doi.org/10.1142/s0129065799000502 | DOI Listing |
Adv Model Simul Eng Sci
January 2025
Department of Mechanical and Process Engineering, Institute for Mechanical Systems, ETH Zürich, Zürich, 8092 Switzerland.
We extend (EUCLID Efficient Unsupervised Constitutive Law Identification and Discovery)-a data-driven framework for automated material model discovery-to pressure-sensitive plasticity models, encompassing arbitrarily shaped yield surfaces with convexity constraints and non-associated flow rules. The method only requires full-field displacement and boundary force data from one single experiment and delivers constitutive laws as interpretable mathematical expressions. We construct a material model library for pressure-sensitive plasticity models with non-associated flow rules in four steps: (1) a Fourier series describes an arbitrary yield surface shape in the deviatoric stress plane; (2) a pressure-sensitive term in the yield function defines the shape of the shear failure surface and determines plastic deformation under tension; (3) a compression cap term determines plastic deformation under compression; (4) a non-associated flow rule may be adopted to avoid the excessive dilatancy induced by plastic deformations.
View Article and Find Full Text PDFJ Phys Chem C Nanomater Interfaces
January 2025
Center for Materials Science and Nanotechnology (SMN), Department of Chemistry, University of Oslo, P.O. Box 1033, Blindern, Oslo N-0315, Norway.
The flexibility of the H-ZSM-5 zeolite upon adsorption of selected coke precursors was investigated using both theoretical and experimental approaches. Four structural models with varying active site locations were analyzed through density functional theory (DFT) simulations to determine their responses to different types and quantities of aromatic molecules. Complementary experimental analysis was performed, allowing for a direct comparison with the theoretical findings, using thermogravimetric analysis (TGA), nitrogen adsorption (N adsorption), solid-state NMR, and X-ray diffraction (XRD).
View Article and Find Full Text PDFNat Commun
January 2025
Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA, 70118, USA.
Mercury (Hg) contamination poses a persistent threat to the remote Arctic ecosystem, yet the mechanisms driving the pronounced summer rebound of atmospheric gaseous elemental Hg (Hg) and its subsequent fate remain unclear due to limitations in large-scale seasonal studies. Here, we use an integrated atmosphere-land-sea-ice-ocean model to simulate Hg cycling in the Arctic comprehensively. Our results indicate that oceanic evasion is the dominant source (~80%) of the summer Hg rebound, particularly driven by seawater Hg release facilitated by seasonal ice melt (~42%), with further contributions from anthropogenic deposition and terrestrial re-emissions.
View Article and Find Full Text PDFNat Commun
January 2025
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
The kinetics of dislocation reactions, such as dislocation multiplication, controls the plastic deformation in crystals beyond their elastic limit, therefore critical mechanisms in a number of applications in materials science. We present a series of large-scale molecular dynamics simulations that shows that one such type of reactions, the nucleation of dislocation at free surfaces, exhibit unconventional kinetics, including unexpectedly large nucleation rates under compression, very strong entropic stabilization under tension, as well as strong non-Arrhenius behavior. These unusual kinetics are quantitatively rationalized using a variational transition state theory approach coupled with an efficient numerical scheme for the estimation of vibrational entropy changes.
View Article and Find Full Text PDFSci Rep
January 2025
Wollega University, Nekemte, Ethiopia.
This research paper presents an advanced AI-driven hybrid power quality management system for electrical railways that addresses critical challenges in 25 kV AC traction networks through a novel integration of single-phase PV-UPQC with ANN-Lyapunov control architecture. The system effectively manages voltage unbalance exceeding 2%, high THD, voltage variations of ± 10%, and poor power factor through a dual-approach methodology combining ANN-based reference signal generation with Lyapunov optimization, enabling dynamic parameter tuning and real-time load adaptation. MATLAB/Simulink simulations validate the system's superior performance, demonstrating significant improvements, including voltage unbalance reduction from 1.
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