Results 41 to 50 of about 177 (131)
Optimal Control‐Based Generic Framework for Radiofrequency Pulse Design in MRI
NMR in Biomedicine, Volume 39, Issue 6, June 2026.This paper presents an open‐source Python‐based optimal control RF design framework, which can tackle various problems (short‐T2 selective excitation or B1‐robust excitation/inversion). It features three main methodological contributions: a specific cost is introduced to reduce pulse peak amplitude; consistent integration of various hard constraints on
Emilio Molina +2 more
wiley +1 more source
Building a Digital Twin for Material Testing: Model Reduction and Data Assimilation
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT The rapid advancement of industrial technologies, data collection, and handling methods has paved the way for the widespread adoption of digital twins (DTs) in engineering, enabling seamless integration between physical systems and their virtual counterparts.
Rubén Aylwin +5 more
wiley +1 more source
Predictive Building Energy Management by Means of Mixed‐Integer Optimal Control With Automated Setup
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT Today, a significant portion of total final energy consumption can be attributed to heating systems in buildings. Reducing energy consumption and carbon dioxide emissions in this sector is, therefore, crucial to achieving the goals of climate action initiatives worldwide.
Artyom Burda +4 more
wiley +1 more source
On Cahn–Hilliard Type Viscoelastoplastic Two‐Phase Flows
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT This contribution deals with a model for viscoelastoplastic two‐phase flows of Cahn–Hilliard type. We present the modeling framework for the flow, the notion of a generalized solution, namely the so‐called dissipative solution, and the key ideas of the existence proof.
Fan Cheng +2 more
wiley +1 more source
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT In this work, we present an anisotropic multi‐goal error control based on the dual weighted residual (DWR) method for time‐dependent convection–diffusion–reaction (CDR) equations. Motivated by former work, we combine multiple goals to single error functionals with weights chosen as algorithmic parameters.
Markus Bause +5 more
wiley +1 more source
Analysis of a Viscoplastic Burgers Equation
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT We study a Burgers equation featuring an additional stress term that is governed by a positively 1$\hskip.001pt 1$‐homogeneous potential. This problem is motivated by the so‐called Hibler's sea ice model, which treats sea ice as a non‐Newtonian fluid, where the stress tensor includes such a term in order to account for the plastic response of ...
Marita Thomas, Xin Liu, Edriss Titi
wiley +1 more source
Modelling hydrogen production from biomass pyrolysis for energy systems using machine learning techniques. [PDF]
Environ Sci Pollut Res Int, 2023 García-Nieto PJ +3 more
europepmc +1 more source
Wasserstein Regression, Forecasting, and Change‐Point Detection for Daily Traffic Flow Distributions
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 3, June 2026.ABSTRACT We develop a distribution‐valued framework for modeling, forecasting, and monitoring traffic flow counts by treating each day as a probability distribution summarized by jittered empirical quantile signatures. Inference is conducted under the 2‐Wasserstein geometry, which in one dimension is isometric to the L2(0,1)$$ {L}^2\left(0,1\right ...
Abdolnasser Sadeghkhani
wiley +1 more source
Mixture‐Based Estimation of Multivariate Data Hypervolume
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 3, June 2026.ABSTRACT Estimating the hypervolume occupied by multivariate data is a fundamental problem in statistics and data science, with applications ranging from ecology and machine learning to multi‐objective optimization and Bayesian inference. Traditional approaches rely on geometric approximations, kernel density estimation, or convex‐hull constructions ...
Luca Scrucca
wiley +1 more source
Statistics in Medicine, Volume 45, Issue 13-14, June 2026.ABSTRACT Depicting patient transitions among multiple clinical states is a common objective in health services and epidemiological research. Multistate models (MSM) are the primary analytical approach used in such studies. Although the structure of an MSM is typically determined by the research questions of a specific application, models are typically ...
Jason Mao, Yang Li, Wanzhu Tu
wiley +1 more source