Results 201 to 210 of about 208,181 (263)
Advanced Engineering Materials, EarlyView.A flexure‐based variable stiffness structure is developed by integrating phase‐change modulation and adhesive interfacial locking of gallium. The design enables a wide stiffness variability, transitioning from soft, flexible behavior to rigid, load‐supporting performance.
Sungjin Kim +2 more
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Advanced Engineering Materials, EarlyView.Mg–Zn composites with a thickness of 0.21 mm were fabricated using roll bonding of a kirigami‐patterned Mg alloy inlay within a Zn matrix. Thermal activation following this process led to the formation of tailored intermetallic structures, which provided the composite with enhanced flexural strength.
Yaroslav Frolov +4 more
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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
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Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading
Advanced Engineering Materials, EarlyView.The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
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Karl Popper and the Mechanisms of Hydrogen Embrittlement
Advanced Engineering Materials, EarlyView.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
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Robust Maximum Likelihood Estimation
INFORMS Journal on Computing, 2019In many applications, statistical estimators serve to derive conclusions from data, for example, in finance, medical decision making, and clinical trials. However, the conclusions are typically dependent on uncertainties in the data. We use robust optimization principles to provide robust maximum likelihood estimators that are protected against data ...
Dimitris Bertsimas, Omid Nohadani
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On bias in maximum likelihood estimators
Journal of Statistical Planning and Inference, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mardia, K. V. +2 more
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Modified maximum likelihood estimator
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016In this paper, we present a modified maximum likelihood estimation method, which is suitable to be used with φ-families rather than exponential families. An indicative result of the efficacy of this method is established. We perform numerical experiments to illustrate the accuracy of this method for estimating the dispersion parameter σ in φ-Gaussians.
David C. de Souza +2 more
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Linear maximum likelihood estimator
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991A general linear and quasi-efficient estimator is presented which is an optimal (for a given criterion) approximation of the maximum likelihood estimator (MLE with nonlinear measurement equation) when the measurements are corrupted by a Gaussian noise. This approach consists of choosing a particular state vector which characterizes the signal.
Christian J. Musso, Claude Jauffret
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