Results 81 to 90 of about 2,699 (199)
Truss Structure Optimization with Subset Simulation and Augmented Lagrangian Multiplier Method
This paper presents a global optimization method for structural design optimization, which integrates subset simulation optimization (SSO) and the dynamic augmented Lagrangian multiplier method (DALMM).
Feng Du, Qiao-Yue Dong, Hong-Shuang Li
doaj +1 more source
ABSTRACT Fluid‐filled phase‐field fracture simulations require robust, scalable solvers that can handle strongly nonlinear, non‐smooth mechanics and tightly coupled flow on locally refined meshes. In this work, we develop an adaptive finite element framework for quasi‐static, fluid‐filled phase‐field fractures that combines semi‐smooth Newton methods ...
Leon M. Kolditz +3 more
wiley +1 more source
An exciting Approach to Theoretical Spectroscopy
ABSTRACT Theoretical spectroscopy, and more generally, electronic‐structure theory, are powerful concepts for describing the complex many‐body interactions in materials. They cover methods from ground‐state properties to lattice excitations and light‐matter interaction, including time‐resolved variants.
Martí Raya‐Moreno +29 more
wiley +1 more source
Pontryagin’s Principle-Based Algorithms for Optimal Control Problems of Parabolic Equations
This paper applies the Method of Successive Approximations (MSA) based on Pontryagin’s principle to solve optimal control problems with state constraints for semilinear parabolic equations.
Weilong You, Fu Zhang
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Challenges and enablers in fluidization technology
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley +1 more source
AL-COLE: Augmented Lagrangian for Constrained Learning
Despite the non-convexity of most modern machine learning parameterizations, Lagrangian duality has become a popular tool for addressing constrained learning problems. We revisit Augmented Lagrangian methods, which aim to mitigate the duality gap in non-convex settings while requiring only minimal modifications, and have remained comparably unexplored ...
Ignacio Boero +2 more
openaire +2 more sources
Abstract Background Lattice radiotherapy (LRT) is a spatially fractionated technique that delivers three‐dimensional high‐dose vertices within tumors. However, conventional LRT is constrained by geometric limitations when applied to small and medium‐sized tumor volumes, primarily due to the large beam sizes that restrict optimal lattice pattern ...
Wei Wu +7 more
wiley +1 more source
A Model-Based Stochastic Augmented Lagrangian Method for Online Stochastic Optimization
In this paper, we focus on online stochastic optimization problems in which random parameters follow time-varying distributions. In each round t, a decision is obtained from solving the current optimization problem.
Zewei Wang, Dan Xue, Yujia Zhai, Cong Li
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ABSTRACT This work presents a general framework for deriving the Young–Laplace equation and the Young's equations for an axisymmetric capillary bridge between two parallel plates by minimizing the system's total energy. These Young's equations naturally emerge as boundary conditions associated with the Young–Laplace equation.
Olivier Millet +3 more
wiley +1 more source
Monotone Clusters With Ordinal Interpretation
ABSTRACT There has been a growing demand in various sectors, such as healthcare, finance, and social sciences, for clustering methods that not only find quality clusters in data but also provide inherent order among the clusters for better decision‐making and risk assessment. Traditional clustering methods, though effective at grouping data, often fall
Hee Cheol Chung +3 more
wiley +1 more source

