Results 111 to 120 of about 8,297,419 (289)
Abstract We develop a delay‐aware estimation and control framework for a non‐isothermal axial dispersion tubular reactor modelled as a coupled parabolic‐hyperbolic PDE system with recycle‐induced state delay. The infinite‐dimensional dynamics are preserved without spatial discretization by representing the delay as a transport PDE and adopting a late ...
Behrad Moadeli, Stevan Dubljevic
wiley +1 more source
Modelling of continuous low‐temperature emulsion co‐polymerization in 3D‐printed reactor
A kinetic model for the emulsion copolymerization of butyl acrylate/styrene at low temperatures is proposed and validated against experiments with a redox initiator system. The model was successfully transferred to a 3D‐printed tubular reactor and conversions of more than 80% and small particles sizes below 40 nm were observed.
Ferel Issa +2 more
wiley +1 more source
Optimal model‐based design of experiments for parameter precision: Supercritical extraction case
Abstract This study investigates the process of chamomile oil extraction from flowers. A parameter‐distributed model consisting of a set of partial differential equations is used to describe the governing mass transfer phenomena in a cylindrical packed bed with solid chamomile particles under supercritical conditions using carbon dioxide as a solvent ...
Oliwer Sliczniuk, Pekka Oinas
wiley +1 more source
A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control
Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao +2 more
wiley +1 more source
A‐optimal model‐based design of experiments for processes with uncertain inputs
Abstract Model‐based design of experiments (MBDoE) techniques are tools for selecting experimental conditions that enable accurate parameter estimation for mechanistic models. Most MBDoE approaches assume that the selected experimental conditions will be implemented perfectly, without uncertainties in the independent variables.
Bright Ofori +3 more
wiley +1 more source
Ngoc Hung Nguyen, K. Doğançay
semanticscholar +1 more source
Subuniformity of harmonic mean p$$ p $$‐values
Abstract We obtain several inequalities on the generalized means of dependent p$$ p $$‐values. In particular, the weighted harmonic mean of p$$ p $$‐values is strictly subuniform under several dependence assumptions of p$$ p $$‐values, including independence, negative upper orthant dependence, the class of extremal mixture copulas, and some Clayton ...
Yuyu Chen +3 more
wiley +1 more source
Symdyn: An automated algebraic solution for high-order quantum systems
Many important quantum systems are characterized by Hamiltonians expressible as a linear combination of time-independent generators of a finite Lie algebra, H[over ̂](t)=∑_{l=1}^{L}η_{l}(t)g[over ̂]_{l}.
D. Martínez-Tibaduiza +4 more
doaj +1 more source
An observation‐driven state‐space model for claims size modelling
Abstract State‐space models are popular in econometrics. Recently, these models have gained some popularity in the actuarial literature. The best known state‐space models are of the Kalman‐filter type. These are called parameter‐driven because the observations do not impact the state‐space dynamics.
Jae Youn Ahn +2 more
wiley +1 more source
Asymptotic properties of cross‐classified sampling designs
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley +1 more source

