Results 101 to 110 of about 1,036,417 (320)

Assigning mathematics tasks versus providing pre-fabricated mathematics in order to support learning to prove [PDF]

open access: yes, 2009
We present types of mathematics tasks that we propose to our students —future high school mathematics teachers— in a geometry course whose objective is learning to prove and whose enterprise is collectively building an axiomatic system for a portion of ...
Camargo, Leonor   +4 more
core  

Azimuthally-sensitive pion HBT at RHIC

open access: yes, 2003
The STAR Collaboration has measured two-pion correlation functions versus emission angle with respect to the event plane in non-central Au+Au collisions at \sqrt{s_{NN}}=130, 200 GeV. In the context of a parameterized freezeout scenario, the data suggest
For The, Mike Lisa, Star Collaboration
core   +2 more sources

Comparative Wear and Friction Analysis of Sliding Surface Materials for Hydrostatic Bearing under Oil Supply Failure Conditions

open access: yesAdvanced Engineering Materials, EarlyView.
Hydrostatic bearings excel in high‐precision applications, but their performance hinges on a continuous external supply. This study evaluates various material combinations for sliding surfaces to mitigate damage during supply failures or misalignment and to discover the most effective materials identified for enhancing the reliability and efficiency of
Michal Michalec   +6 more
wiley   +1 more source

GEOMETRY – AN IMPORTANT MEANS OF EDUCATION IN THE CIVILISATION SCOPE

open access: yesJournal of Industrial Design and Engineering Graphics, 2017
Geometry (from the Greek: γεωμετρία; geo = earth, metria = measure) is a genuine science, rooted in mathematics, which studies the plane and spatial forms of bodies from the objective or conceptual reality and the nature of the relationship that exists ...
Liliana TOCARIU, PhD
doaj  

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

A new twist on the geometry of gravitational plane waves

open access: yesJournal of High Energy Physics, 2017
The geometry of twisted null geodesic congruences in gravitational plane wave spacetimes is explored, with special focus on homogeneous plane waves.
Graham M. Shore
doaj   +1 more source

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

open access: yesAdvanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

Robocasting of a Water‐Based Biopolymer/WO3 Nanopowder Paste as a Precursor to Tungsten Carbide Lattices

open access: yesAdvanced Engineering Materials, EarlyView.
This study demonstrates a novel, additive manufacturing approach to produce complex, porous tungsten carbide structures using water‐based direct ink writing/robocasting. Leveraging a modified commercial printer and heat treatment, the process yields lightweight, electrically conductive 3D architectures capable of supporting a mechanical load.
James Bentley Bevis   +3 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

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