Results 141 to 150 of about 112,882 (301)
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
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
We present an approach to synthesising the effects of ageing on human face images using three-dimensional modelling. We extract a set of three dimensional face models from a set of two-dimensional face images by fitting a Morphable Model.
Tiddeman, Bernard Paul +1 more
core
Karl Popper and the Mechanisms of Hydrogen Embrittlement
Representation of the beginning of loss of ductility rather than embrittlement. Small concentrations of hydrogen in a diffusible form within iron are well‐established to harm the mechanical integrity of steels. There are theories that attempt to explain the pernicious role of hydrogen.
H. K. D. H. Bhadeshia
wiley +1 more source
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
Identification of dietary patterns using partial least square regression
Partial Least Square Regression (PLS-R) is a method of reducing the dimensionality of the data. PLS-R assumes that there is a common structure underlying the blocks of predictor (X) and response (Y) variables, and that this structure can be resumed by a ...
V. Edefonti +3 more
core
Microstructure Evolution of a VMnFeCoNi High‐Entropy Alloy After Synthesis, Swaging, and Annealing
The synthesis and processing (rotary swaging and annealing) of the novel VMnFeCoNi alloy is investigated, alongside the estimation of the grain size effect on hardness. Analysis of a wide grain size range of recrystallized microstructures (12–210 µm) reveals a low annealing twin density.
Aditya Srinivasan Tirunilai +6 more
wiley +1 more source
Perbandingan Metode Partial Least Absolute Deviation Regression Dan Metode Partial Robust M Regression Pada Kasus Data Outlier [PDF]
Partial Least Square Regression (Regresi PLS) merupakan metode yang sangat berguna untuk memprediksi variabel respon berdasarkan variabel prediktor berdimensi tinggi (banyak pengamatan lebih sedikit dibanding banyak variabel prediktor). Namun regresi PLS
Maghfiroh, Aulia
core
Influence of Test Temperature and Test Frequency on Fatigue Life of Aluminum Alloy EN AW‐2618A
The influence of test temperature and test frequency on the fatigue life of EN AW‐2618A is investigated. High‐cycle fatigue tests are performed at different test temperatures and frequencies on the 1000 h/230°C overaged state. Both test parameters reduce fatigue life due to time‐dependent damage mechanisms.
Ying Han +5 more
wiley +1 more source
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova +2 more
wiley +1 more source

