Results 91 to 100 of about 157,970 (240)
ABSTRACT Efficient thermal management in advanced industrial systems requires improved heat transfer performance, particularly under non‐Newtonian fluid behavior and complex surface geometries. This study investigates the two‐dimensional flow and heat transfer characteristics of ternary hybrid nanofluids over both stationary and moving wedge surfaces ...
A. O. Akindele +4 more
wiley +1 more source
Risk‐aware safe reinforcement learning for control of stochastic linear systems
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
Approximation to certain transcendental decimal fractions by algebraic numbers
For a positive integer \(g\geq 2\) consider the number \(M(g)=0.(1)_ g(2)_ g...(n)_ g...\) where for \(n\in {\mathbb{N}}\) \((n)_ g\) means digit representation of n to base g and \(0.(1)_ g(2)_ g...\) means digit representation of the real M(g) to base g. It is known that M(g) is transcendental. The author gives estimates for Mahler's function \(w_ d\)
openaire +1 more source
Abstract The linear‐quadratic regulator (LQR) problem of optimal control of an uncertain discrete‐time linear system (DTLS) is revisited in this paper from the perspective of Tikhonov regularization. We show that an optimally chosen regularization parameter reduces, compared to the classical LQR, the values of a scalar error function, as well as the ...
Fernando Pazos, Amit Bhaya
wiley +1 more source
ABSTRACT This study systematizes the literature on eco‐innovation and economic complexity, aiming to understand how the sophistication of productive structures shapes countries' capacity to develop environmentally responsible innovations, and how eco‐innovation may, in turn, influence productive sophistication.
Gregory Matheus Pereira de Moraes +1 more
wiley +1 more source
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
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
On approximation of real numbers by algebraic numbers of bounded degree
Dirichlet proved that, for any real irrational number \(\xi\), there exist infinitely many rational numbers \(\frac{p}{q}\) such that \(|\xi-\frac{p}{q}|2\). Let \(\mathbf A_n, \;n>2\) denote the set of algebraic numbers of degree \(\leq n\). Let \(\alpha\in \mathbf A_n\) and \(H(\alpha)\) the height of \(\alpha\), that is the largest absolute value of
openaire +2 more sources
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

