Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Alexander Schein"'
Autor:
Alexander Schein, Michael W. Gee
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences, Vol 8, Iss 1, Pp 1-31 (2021)
Abstract This work proposes a framework for projection-based model order reduction (MOR) of computational models aiming at a mechanical analysis of abdominal aortic aneurysms (AAAs). The underlying full-order model (FOM) is patient-specific, stationa
Externí odkaz:
https://doaj.org/article/dc01572900c74d4cbca95d3889442e78
Autor:
Alexander Scheinker
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Imaging the 6D phase space of a beam in a particle accelerator in a single shot is currently impossible. Single shot beam measurements only exist for certain 2D beam projections and these methods are destructive. A virtual diagnostic that ca
Externí odkaz:
https://doaj.org/article/a2e5a96d19f3437e98dd8e4d12107afb
Autor:
Alexander Scheinker
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Advanced accelerator-based light sources such as free electron lasers (FEL) accelerate highly relativistic electron beams to generate incredibly short (10s of femtoseconds) coherent flashes of light for dynamic imaging, whose brightness exce
Externí odkaz:
https://doaj.org/article/61b9f6e144014a1fb554ee15cb0d5986
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract Particle accelerators are complex systems that focus, guide, and accelerate intense charged particle beams to high energy. Beam diagnostics present a challenging problem due to limited non-destructive measurements, computationally demanding
Externí odkaz:
https://doaj.org/article/9761791bdb6643649e47682863f473e4
Autor:
Christopher Leon, Alexander Scheinker
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract We utilize a Fourier transformation-based representation of Maxwell’s equations to develop physics-constrained neural networks for electrodynamics without gauge ambiguity, which we label the Fourier–Helmholtz–Maxwell neural operator me
Externí odkaz:
https://doaj.org/article/ca215c941a214b3eaa4c85f12a77a0ae
Model-reduction techniques aim to reduce the computational complexity of simulating dynamical systems by applying a (Petrov-)Galerkin projection process that enforces the dynamics to evolve in a low-dimensional subspace of the original state space. F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14ee7da8f8b204403fdc06bde51058c6
Publikováno v:
Physical Review Accelerators and Beams, Vol 27, Iss 2, p 024601 (2024)
In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through
Externí odkaz:
https://doaj.org/article/6dada45a51a547f696fe9ea528ba714c
Autor:
Alexander Scheinker, Reeju Pokharel
Publikováno v:
APL Machine Learning, Vol 1, Iss 2, Pp 026109-026109-11 (2023)
We present a physics-constrained neural network (PCNN) approach to solving Maxwell’s equations for the electromagnetic fields of intense relativistic charged particle beams. We create a 3D convolutional PCNN to map time-varying current and charge d
Externí odkaz:
https://doaj.org/article/f21abe4daaf041578ae40bf41313eff0
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However, for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no
Externí odkaz:
https://doaj.org/article/1b5bd259315f456690de4a256e722122
Autor:
Alexander Scheinker, Simon Hirlaender, Francesco Maria Velotti, Spencer Gessner, Giovanni Zevi Della Porta, Verena Kain, Brennan Goddard, Rebecca Ramjiawan
Publikováno v:
AIP Advances, Vol 10, Iss 5, Pp 055320-055320-5 (2020)
Multi-objective optimization is important for particle accelerators where various competing objectives must be satisfied routinely such as, for example, transverse emittance vs bunch length. We develop and demonstrate an online multi-time scale multi
Externí odkaz:
https://doaj.org/article/dc3bc4b606fa4337996c3ef593e34e9f