Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Dario Mangoni"'
Publikováno v:
Machines, Vol 11, Iss 2, p 218 (2023)
In this work, we discuss the numerical challenges involved in the computation of the complex eigenvalues of damped multi-flexible-body problems. Aiming at the highest generality, the candidate method must be able to deal with arbitrary rigid body mod
Externí odkaz:
https://doaj.org/article/80e6ecfdfcf24be4ad413da01aae69d0
In this work we discuss the numerical challenges involved in the computation of the complex eigenvalues of damped multi-flexible-body problems. Aiming at the highest generality, the candidate method must be able to deal with arbitrary rigid body mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a0f209f76bdd65076cb916041c4b6eb
Publikováno v:
NODYCON Conference Proceedings Series ISBN: 9783030811655
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::501e7d3a51b4b0bcfc47123d5a9251ec
https://doi.org/10.1007/978-3-030-81166-2_49
https://doi.org/10.1007/978-3-030-81166-2_49
Autor:
Simone Benatti, Aaron Young, Asher Elmquist, Jay Taves, Radu Serban, Dario Mangoni, Alessandro Tasora, Dan Negrut
Publikováno v:
NODYCON Conference Proceedings Series ISBN: 9783030811655
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c8bf66e8f06f0cb3b59a9235fb0b3ff8
https://doi.org/10.1007/978-3-030-81166-2_50
https://doi.org/10.1007/978-3-030-81166-2_50
Publikováno v:
Computer Methods in Applied Mechanics and Engineering. 330:351-367
Time-stepping methods for non-smooth dynamics are based on the solution of multiple complementarity problems: solving this class of problems represents a major numerical bottleneck, especially when dealing with near-singular and ill-posed systems suc
Publikováno v:
Proceedings of the 2019 3rd International Conference on Automation, Control and Robots.
In this work we focus on the role of Multibody Simulation in creating Reinforcement Learning virtual environments for robotic manipulation, showing a versatile, efficient and open source toolchain to create directly from CAD models. Using the Chrono:
Publikováno v:
Multibody Dynamics 2019 ISBN: 9783030231316
In this paper we use the Proximal Policy Optimization (PPO) deep reinforcement learning algorithm to train a Neural Network to control a four-legged robot in simulation. Reinforcement learning in general can learn complex behavior policies from simpl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4917569ce0d90dbcba72e395c728372
https://doi.org/10.1007/978-3-030-23132-3_47
https://doi.org/10.1007/978-3-030-23132-3_47
Publikováno v:
Multibody Dynamics 2019 ISBN: 9783030231316
The increasing complexity of dynamic simulations involving unilateral constraints, such as contacts, is pushing for new solvers that may address the problem of handling non-smooth impact events in a more efficient and accurate manner, especially in m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9cc802e8f1890128c2933e1a4cf6428d
https://doi.org/10.1007/978-3-030-23132-3_41
https://doi.org/10.1007/978-3-030-23132-3_41
Autor:
Dario Mangoni, Alessandro Soldati
Publikováno v:
International Journal of Vehicle Performance. 7:156
The wide-spread e-mobility revolution is asking for new software solutions capable of providing meaningful information not only for the mechanical part of the vehicle architecture, as in the past, but also for novel electric and hybrid driveline comp
Autor:
Alessandro Tasora, Alessandro Soldati, Matteo Dalboni, Francesco Corradini, Dario Mangoni, Filippo Savi, Davide Lusignani
Publikováno v:
IECON
This paper talks about the creation of fast and lightweight 2D electric road vehicle models in order to design the whole electric powertrain. Two models are developed. The first one is very essential: it consists of three dynamics, that is full vehic