Results 211 to 220 of about 917,002 (254)
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar +2 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.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
Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
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2023
This book provides an accessible introduction to causal inference and data analysis with R, specifically for a public policy audience. It aims to demystify these topics by presenting them through practical policy examples from a range of disciplines. It provides a hands-on approach to working with data in R using the popular tidyverse package.
Dayal, Vikram, Murugesan, Anand
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This book provides an accessible introduction to causal inference and data analysis with R, specifically for a public policy audience. It aims to demystify these topics by presenting them through practical policy examples from a range of disciplines. It provides a hands-on approach to working with data in R using the popular tidyverse package.
Dayal, Vikram, Murugesan, Anand
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Journal of PeriAnesthesia Nursing, 1996
The goal of research is to discover new knowledge to improve patient care. Research is essential because of its ability to establish causal relationships. This article discusses the minimum requirements a research report must meet to establish a causal relationship.
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The goal of research is to discover new knowledge to improve patient care. Research is essential because of its ability to establish causal relationships. This article discusses the minimum requirements a research report must meet to establish a causal relationship.
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Causal Estimation and Causal Inference
2020This entry provides an introduction to causal inference. Causal inference refers to the estimation of the effect of a treatment, policy, or intervention on an outcome of interest. Causal inference is, therefore, at the centre of science and social sciences. This entry emphasises Rubin’s potential outcomes framework.
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2015 49th Asilomar Conference on Signals, Systems and Computers, 2015
We provide a framework to infer causal relationships in a system of multivariate, stochastic, delayed signals, with application to their prediction. First we address the dimensionality problem in information causality estimation and propose a method to improve the efficiency of calculations by retaining only the most essential components.
Simona Poilinca +2 more
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We provide a framework to infer causal relationships in a system of multivariate, stochastic, delayed signals, with application to their prediction. First we address the dimensionality problem in information causality estimation and propose a method to improve the efficiency of calculations by retaining only the most essential components.
Simona Poilinca +2 more
openaire +1 more source