Results 31 to 40 of about 475,912 (124)
In this article ideas from Kit Fine's theory of arbitrary objects are applied to questions regarding mathematical structuralism. I discuss how sui generic mathematical structures can be viewed as generic systems of mathematical objects, where mathematical objects are conceived of as arbitrary objects in Fine's sense.
arxiv
Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani+2 more
wiley +1 more source
Digital Methods for the Fatigue Assessment of Engineering Steels
The use of engineering steels is often limited by their fatigue strength. In the sake of a faster product development, the fatigue behavior can be predicted by machine learning (ML). In this work, ML is applied on a heterogeneous database, covering a wide range of steel types.
Sascha Fliegener+7 more
wiley +1 more source
Analysis of moving least squares approximation revisited [PDF]
In this article the error estimation of the moving least squares approximation is provided for functions in fractional order Sobolev spaces. The analysis presented in this paper extends the previous estimations and explains some unnoticed mathematical details. An application to Galerkin method for partial differential equations is also supplied.
arxiv +1 more source
Electrospinning Technology, Machine Learning, and Control Approaches: A Review
Electrospinning produces micro‐ and nanoscale fibers, holding great promise in biomedical engineering. Industrial adoption faces challenges in controlling fiber properties, reproducibility, and scalability. This review explores electrospinning techniques, modeling, and machine learning for process optimization.
Arya Shabani+5 more
wiley +1 more source
A Case‐Based Reasoning Approach to Model Manufacturing Constraints for Impact Extrusion
A hybrid modeling approach is presented that combines constraint‐based process modeling and case‐based reasoning. The model formalizes manufacturing constraints and integrates simulation data to model complex manufacturing processes. The approach supports manufacturability analysis during product design through an adaptive modeling environment.
Kevin Herrmann+5 more
wiley +1 more source
Simulation of Inhomogeneous Refractive Index Fields Induced by Hot Tailored Forming Components
This article presents a simulation model for simulating inhomogeneous refractive index fields (IRIF) in hot‐forged components, accounting for thermal influences and complex geometries. Through this simulation, a priori knowledge about the propagation of the IRIF can be obtained, allowing for the positioning of the component or an optical measurement ...
Pascal Kern+3 more
wiley +1 more source
On the mathematical modelling of measurement [PDF]
The operations of linear algebra, calculus, and statistics are routinely applied to measurement scales but certain mathematical conditions must be satisfied in order for these operations to be applicable. We call attention to the conditions that lead to construction of measurement scales that enable these operations.
arxiv
A methodology for establishing an ontology‐augmented structural digital twin for fiber‐reinforced polymer structures dedicated to individual lifetime prediction, in this case, a wind turbine rotor blade, is introduced. The methodology resembles the manufacturing as well as the operation of the structure.
Marc Luger+6 more
wiley +1 more source
Minimal Operation Time of Energy Devices [PDF]
We consider the problem of determining the minimal time for which an energy supply source should operate in order to supply a system with a desired amount of energy in finite time.
arxiv