Concept

Monte Carlo method

Related publications (809)

Leveraging the Snap Buckling of Bistable Magnetic Shells to Design a Refreshable Braille Dot

Pedro Miguel Nunes Pereira de Almeida Reis, Tian Chen, Arefeh Abbasi, Bastien Freddy Gustave Aymon

A design concept is proposed for the building block, a dot, of programmable braille readers utilizing bistable shell buckling, magnetic actuation, and pneumatic loading. The design process is guided by Finite Element simulations, which are initially valida ...

Hoboken2023

Dynamic Monte Carlo reactor modeling of calcium looping with sorbent purge and utilization decay

This work presents a new dynamic modelling approach for calcium looping systems that allows explicit sorbent deactivation and purge/makeup. These are common in plant operations, but often neglected in modelling. This model adopts a Monte Carlo approach, tr ...

2022

Single photon detection with amorphous silicon-based microchannel plates: A Monte Carlo model

Christophe Ballif, Jonathan Emanuel Thomet, Janina Christine Isabelle Löffler, Samira Alexandra Frey

Microchannel plates based on amorphous silicon have the inherent capability to overcome the existing spatial and temporal resolution limitations of single photon detectors. A Monte Carlo model-based study is presented here that serves to exploit their full ...

2022

Monte-Carlo Method for EMF Exposure Distribution Assessment in 5G Base Station

Anja Skrivervik, Tingyong Jiang

This paper proposes a studied case to assess the EMF (electromagnetic field) exposure distribution for a specific deployment scenario. This developed novel approach based on a Monte-Carlo (MC) approach took into account the non-uniform user distribution an ...

IEEE2022

Uncertainty Quantification by Multilevel Monte Carlo and Local Time-Stepping for Wave Propagation

Fabio Nobile

Because of their robustness, efficiency, and non intrusiveness, Monte Carlo methods are probably the most popular approach in uncertainty quantification for computing expected values of quantities of interest. Multilevel Monte Carlo (MLMC) methods signific ...

2022

Space Oddity? A Statistical Formulation of Conjunction Assessment

Anthony Christopher Davison, Soumaya Elkantassi

Satellite conjunctions involving "near misses" of space objects are becoming increasingly likely. One approach to risk analysis for them involves the computation of the collision probability, but this has been regarded as having some counterintuitive prope ...

AMER INST AERONAUTICS ASTRONAUTICS2022

Tensor network investigation of the hard-square model

Frédéric Mila, Samuel Louis Nyckees

Using the corner-transfer matrix renormalization group to contract the tensor network that describes its partition function, we investigate the nature of the phase transitions of the hard-square model, one of the exactly solved models of statistical physic ...

AMER PHYSICAL SOC2022

New Capabilities of the FLUKA Multi-Purpose Code

André Donadon Servelle, Nikolaos Charitonidis, Philippe Jean Schoofs, Francesco Cerutti

FLUKA is a general purpose Monte Carlo code able to describe the transport and interaction of any particle and nucleus type in complex geometries over an energy range extending from thermal neutrons to ultrarelativistic hadron collisions. It has many diffe ...

FRONTIERS MEDIA SA2022

Auto-tuning deep forest for shear stiffness prediction of headed stud connectors

Xianlin Wang, Yuqing Liu

The shear stiffness of headed stud connector is a critical parameter for the calculation of deflection and inter-facial shear force for steel-concrete composite structure. Thus, this study presented a promising data-driven model auto-tuning Deep Forest (AT ...

2022

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

James Gonzalo King, Pramod Shivaji Kumbhar, Iain Hepburn, Weiliang Chen, Tristan Mathieu Carel, Alessandro Cattabiani, Nicola Cantarutti, Omar Awile, Christos Kotsalos, Samuel Marie A Melchior, Baudouin Paul Michel Maria Joseph Del Marmol, Giacomo Castiglioni

Recent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parallel imp ...

FRONTIERS MEDIA SA2022

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