Zobrazeno 1 - 10
of 2 101
pro vyhledávání: '"P Mowbray"'
In this paper we provide a detailed investigation of the energisation processes in two-dimensional, two and a half-dimensional and three-dimensional collapsing magnetic trap models. Using kinematic magnetohydrodynamic models of collapsing magnetic tr
Externí odkaz:
http://arxiv.org/abs/2411.14881
Autor:
Bloor, Maximilian, Torraca, José, Sandoval, Ilya Orson, Ahmed, Akhil, White, Martha, Mercangöz, Mehmet, Tsay, Calvin, Chanona, Ehecatl Antonio Del Rio, Mowbray, Max
PC-Gym is an open-source tool for developing and evaluating reinforcement learning (RL) algorithms in chemical process control. It features environments that simulate various chemical processes, incorporating nonlinear dynamics, disturbances, and con
Externí odkaz:
http://arxiv.org/abs/2410.22093
Identification and parameterisation of constitutive models can be a challenging task in rheology. We investigate the use of Random Forest (RF) regression to estimate viscoelastic constitutive model parameters using Large Amplitude Oscillatory Shear (
Externí odkaz:
http://arxiv.org/abs/2312.13793
Autor:
Mousa, Marwan, van de Berg, Damien, Kotecha, Niki, del Rio-Chanona, Ehecatl Antonio, Mowbray, Max
Most solutions to the inventory management problem assume a centralization of information that is incompatible with organisational constraints in real supply chain networks. The inventory management problem is a well-known planning problem in operati
Externí odkaz:
http://arxiv.org/abs/2307.11432
Reinforcement Learning (RL) has recently received significant attention from the process systems engineering and control communities. Recent works have investigated the application of RL to identify optimal scheduling decision in the presence of unce
Externí odkaz:
http://arxiv.org/abs/2203.00636
Autor:
Sachio, Steven, Mowbray, Max, Papathanasiou, Maria, del Rio-Chanona, Ehecatl Antonio, Petsagkourakis, Panagiotis
To create efficient-high performing processes, one must find an optimal design with its corresponding controller that ensures optimal operation in the presence of uncertainty. When comparing different process designs, for the comparison to be meaning
Externí odkaz:
http://arxiv.org/abs/2108.05242
Publikováno v:
Phys. Rev. B 104, 115421 (2021)
Starting from the rigorous quantum-field-theory formalism we derive a formula for the screened conductivity designed to study the coupling of light with elementary electron excitations and the ensuing electromagnatic modes in two-dimensional (2D) sem
Externí odkaz:
http://arxiv.org/abs/2106.05583
Reinforcement Learning (RL) controllers have generated excitement within the control community. The primary advantage of RL controllers relative to existing methods is their ability to optimize uncertain systems independently of explicit assumption o
Externí odkaz:
http://arxiv.org/abs/2104.11706
Autor:
Pan, Elton, Petsagkourakis, Panagiotis, Mowbray, Max, Zhang, Dongda, del Rio-Chanona, Antonio
Reinforcement learning (RL) is a control approach that can handle nonlinear stochastic optimal control problems. However, despite the promise exhibited, RL has yet to see marked translation to industrial practice primarily due to its inability to sat
Externí odkaz:
http://arxiv.org/abs/2011.07925
Autor:
Zhang, Yunyan, Velichko, Anton V., Fonseka, H. Aruni, Parkinson, Patrick, Davis, George, Gott, James A., Aagesen, Martin, Sanchez, Ana M., Mowbray, David, Liu, Huiyun
Axially-stacked quantum dots (QDs) in nanowires (NWs) have important applications in fabricating nanoscale quantum devices and lasers. Although their performances are very sensitive to crystal quality and structures, there is relatively little study
Externí odkaz:
http://arxiv.org/abs/2002.07071