Results 41 to 50 of about 29,538 (243)
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Fuzzy-Stochastic Partial Differential Equations [PDF]
31 ...
openaire +3 more sources
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Analysis of stability for stochastic delay integro-differential equations
In this paper, we concern stability of numerical methods applied to stochastic delay integro-differential equations. For linear stochastic delay integro-differential equations, it is shown that the mean-square stability is derived by the split-step ...
Yu Zhang, Longsuo Li
doaj +1 more source
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
This paper examines fractional multi-time scale stochastic functional differential equations that, in addition, are driven by fractional noises. Based on a specially crafted fixed-point principle for the so-called “local operators”, we prove a Peano-type
Arcady Ponosov, Lev Idels
doaj +1 more source
On stability for numerical approximations of stochastic ordinary differential equations
Stochastic ordinary differential equations (SODE) represent physical phenomena driven by stochastic processes. Like for deterministic differential equations, various numerical schemes are proposed for SODE (see references).
R. Horváth Bokor
doaj +1 more source
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
This review maps 2020-2025 developments in stochastic modeling, highlighting non-standard approaches and their applications to biology and epidemiology.
Yassine Sabbar, Kottakkaran Sooppy Nisar
doaj +1 more source
This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele +2 more
wiley +1 more source

