Results 51 to 60 of about 48,822 (259)
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
Simultaneous perturbation stochastic aproximation for Lipshitz functions
The convergence conditions of Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm with Gaussian smoothing operator are established in the class of Lipshitz functions.
Vaida Bartkutė, Leonidas Sakalauskas
doaj +3 more sources
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
Identified through the use of statistical design of experiments and metallographic investigation, this study exposes the stochastic origins of intergranular cracks in blown powder laser beam directed energy deposition additive manufacturing of pure molybdenum. It further demonstrates a successful crack mitigation approach with direct correlation to the
Nathaniel J. Lies +2 more
wiley +1 more source
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
Accelerated Stochastic Approximation
Using a stochastic approximation procedure $\{X_n\}, n = 1, 2, \cdots$, for a value $\theta$, it seems likely that frequent fluctuations in the sign of $(X_n - \theta) - (X_{n - 1} - \theta) = X_n - X_{n - 1}$ indicate that $|X_n - \theta|$ is small, whereas few fluctuations in the sign of $X_n - X_{n - 1}$ indicate that $X_n$ is still far away from ...
openaire +3 more sources
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
A tutorial introduction to reinforcement learning
In this paper, we present a brief survey of reinforcement learning, with particular emphasis on stochastic approximation (SA) as a unifying theme. The scope of the paper includes Markov reward processes, Markov decision processes, SA algorithms, and ...
Mathukumalli Vidyasagar
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
Sarsa(Λ)-Based Logistics Planning Approximated by Value Function with Policy Iteration
The logistics planning problem has been extensively investigated for a long time. However, with the increasing number of stochastic events occurred in road, increasing number of stochastic factors should be taken into consideration. A dynamic approach is
Yu Tang
doaj +1 more source

