Results 71 to 80 of about 2,824 (289)
Laminar Burning Velocity of Ammonia‐Hydrogen Mixtures Predicted by Machine Learning
Chemie Ingenieur Technik, EarlyView.Ammonia–hydrogen blends aid defossilization, but slow combustion kinetics require complex modeling. Although chemical kinetic modeling is computationally expensive, machine learning surrogates offer fast predictions. This study trained GPR, DT, and ANN models on 1445 experimental points.
Georg Klepp +2 more
wiley +1 more source
Advances in the Design of Symbolic Computation Systems
, 1997 New methodological aspects related to design and implementation of symbolic computation systems are considered in this volume aiming at integrating such aspects into a homogeneous software environment for scientific computation.
TEMPERINI, Marco, Alfonso Miola
core
Algebraic Curve Interpolation for Intervals via Symbolic-Numeric Computation [PDF]
Algebraic curve interpolation is described by specifying the location of N points in the plane and constructing an algebraic curve of a function f that should pass through them.
Yang, Zhengfeng +4 more
core +1 more source
A lumped modelling framework for the epoxidation of vegetable oils and fatty acid methyl esters
The Canadian Journal of Chemical Engineering, EarlyView.Abstract Epoxidized vegetable oils and fatty acid methyl esters are promising bio‐based alternatives to phthalates for plasticizer applications. Their synthesis typically involves the reaction of unsaturated double bonds with peracetic acid in a biphasic liquid–liquid system, where the simultaneous occurrence of reaction and phase partitioning makes ...
Irene Presti +3 more
wiley +1 more source
Solution of polynomial Lyapunov and Sylvester equations
, 2006 A two-variable polynomial approach to solve the one-variable polynomial Lyapunov and Sylvester equations is proposed. Lifting the problem from the one-variable to the two-variable context gives rise to associated lifted equations which live on finite ...
Peeters, Ralf, Rapisarda, Paolo
core +1 more source
Analog and symbolic computation through the Koopman framework
Journal of Physics: ComplexityWe develop a Koopman operator framework for studying the computational structure of dynamical systems. Specifically, we show that the resolvent of the Koopman operator provides a natural abstraction of halting, yielding a ‘Koopman halting problem’ that ...
Francesco Caravelli +1 more
doaj +1 more source
A Note on Truncated Exponential-Based Appell Polynomials via Fractional Operators
AxiomsIn this work, we construct a new class of Appell-type polynomials generated through extended truncated and truncated exponential kernels, and we analyze their core algebraic and operational features.
Waseem Ahmad Khan +4 more
doaj +1 more source
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.A physics‐informed machine learning approach successfully decodes the complex catalytic activity of high‐entropy alloys for ammonia oxidation. By revealing a synergistic mechanism involving lattice and electronic couplings, the study identifies a superior “isolated‐surrounded” platinum motif.
Shangfeng Jiang +5 more
wiley +1 more source
<p>This upload contains the dataset and code used throught Tereso del Río Almajano's thesis titled "Heuristics and Machine Learning to Improve Symbolic Computation Algorithms: Speeding Up Cylindrical Algebraic Decomposition" to ...
del Río, Tereso
core +4 more sources
New Analytical Solutions and Stability Analysis of Coupled Time-Fractional Boussinesq-Burgers System
Universal Journal of Mathematics and ApplicationsThis manuscript investigates a coupled time-fractional Boussinesq-Burgers system (CTFBBS) and presents new analytical solutions for the model. The exact solutions are obtained by employing the Exp$(-\Phi(\eta))$-expansion method combined with the ...
Rachid Cherief +4 more
doaj +1 more source