Results 51 to 60 of about 691,873 (239)
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
Measuring Fine Tuning In Supersymmetry
The solution to fine tuning is one of the principal motivations for supersymmetry. However constraints on the parameter space of the Minimal Supersymmetric Standard Model (MSSM) suggest it may also require fine tuning (although to a much lesser extent ...
Athron, Peter, Miller, D. J.
core
The tribological behavior of 100Cr6 steel spheres textured via Vickers microindentation is evaluated under lubricated sliding by varying both dimple size and density. Fine and dense textures significantly reduce friction across all lubrication regimes, while large dimples increase it.
Farideh Davoodi +3 more
wiley +1 more source
Innovating Aircraft Repair Processes: The Role of Digitalization in Sustainability
This research explores how digitalization—by storing detailed non‐destructive testing data in structured DICONDE databases and creating a standard data model of the component—innovates aviation maintenance and repair processes. Coupled with a developed state‐based simulation model, it enables data‐driven, sustainable repair strategies that reduce waste,
Johanna Aigner +3 more
wiley +1 more source
Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials
Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai +2 more
wiley +1 more source
How Correlations Influence Lasso Prediction
We study how correlations in the design matrix influence Lasso prediction. First, we argue that the higher the correlations are, the smaller the optimal tuning parameter is.
Hebiri, Mohamed, Lederer, Johannes C.
core +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
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
Elinvar Materials: Recent Progress and Challenges
Elinvar materials, exhibiting temperature‐invariant elastic modulus, are critical for precision instruments and emerging technologies. This article reviews recent progress in the field, with a focus on the anomalous thermoelastic behavior observed in key material systems.
Wenjie Li, Yang Ren
wiley +1 more source
In this experimental study, the mechanical properties of additively manufactured Ti‐6Al‐4V lattice structures of different geometries are characterized using compression, four point bending and fatigue testing. While TPMS designs show superior fatigue resistance, SplitP and Honeycomb lattice structures combine high stiffness and strength. The resulting
Klaus Burkart +3 more
wiley +1 more source

