Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Frictional Force01:07

Frictional Force

8.3K
When a body is in motion, it encounters resistance because the body interacts with its surroundings. This resistance is known as friction, a common yet complex force whose behavior is still not completely understood. Friction opposes relative motion between systems in contact, but also allows us to move. Friction arises in part due to the roughness of surfaces in contact. For one object to move along a surface, it must rise to where the peaks of the surface can skip along the bottom of the...
8.3K
Friction: Problem Solving01:21

Friction: Problem Solving

275
Friction is an essential force that influences the motion of objects in daily life. Depending on the situation, it can be either beneficial or problematic. Consider a bus with a mass of three megagrams and its center of mass at a specific point, moving along a banked road at a constant speed. The coefficient of static friction between the tires and the road is 0.5. Find the maximum angle of the banked road at which the bus would not slip or tip.
Initially, a visual representation of the...
275
Dry Friction01:30

Dry Friction

462
Dry friction occurs between two solid surfaces in contact as they attempt to move relative to one another. In daily life, dry friction is encountered in various forms, such as when walking on the ground, sliding an object across a table, or rubbing hands together. Despite its ubiquity, the underlying mechanisms behind dry friction are not readily visible.
To illustrate this concept, imagine a wooden crate resting on a rough, non-uniform horizontal surface. When an external force is applied to...
462
Frictional Forces on Flat Belts01:28

Frictional Forces on Flat Belts

1.0K
Flat belts are commonly used in various industrial applications for transmitting power from one pulley to another. When a flat belt is wrapped around a set of pulleys, it experiences different tensions at the driving pulley ends due to the friction between the belt and pulley surface. When the pulley moves in a counterclockwise direction, the tension T2 on the opposite side of the pulley where the belt is moving away from is higher than the tension T1 on the side where the belt is moving...
1.0K
Static and Kinetic Frictional Force01:05

Static and Kinetic Frictional Force

16.1K
One of the simpler characteristics of sliding friction is that it is parallel to the contact surfaces between systems, and is always in a direction that opposes the motion or attempted motion of the systems relative to each other. If two systems are in contact and moving relative to one another, then the friction between them is called kinetic friction. For example, kinetic friction slows a hockey puck sliding on ice.
However, if two systems are in contact and are stationary relative to one...
16.1K
Characteristics of Dry Friction01:21

Characteristics of Dry Friction

676
Dry friction occurs when two solid surfaces slide against each other without any lubrication or fluid present. It causes resistance when pushing objects along a surface, like a gardener pushing a wheelbarrow. The force applied to move the cart causes dry friction between the wheel and the ground.
Before the wheelbarrow starts moving, the static frictional force acts tangentially to the contact surface, opposing the force that is about to induce the motion. This frictional force prevents the...
676

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

First-principles mode Gruneisen parameters and negative thermal expansion in α-ZrW2O8.

Physical review letters·2012
Same author

Modeling of amorphous carbon structures with arbitrary structural constraints.

Journal of physics. Condensed matter : an Institute of Physics journal·2011
関連記事をすべて見る

関連する実験動画

Updated: Sep 8, 2025

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
11:05

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

Published on: December 13, 2016

12.3K

人工知能を用いた摩擦材料の複合材料の機械的振る舞いを調査する

D Matté1, C A Perottoni1

  • 1Universidade de Caxias do Sul, Caxias do Sul - RS, 95070-560, Brazil.

Neural networks : the official journal of the International Neural Network Society
|September 5, 2025
PubMed
まとめ

人工知能 (AI) モデルは,化学組成から摩擦材料の性質を予測します. ニューラルネットワークは 多線形モデルよりも優れた精度で 新材料の予測を可能にします

科学分野:

  • 材料科学
  • コンピュータ材料科学
  • トリボロジー

背景:

  • 人工知能 (AI) は 科学や工学における複雑な問題に対する 先進的な解決策を提供します
  • 摩擦複合材料のような新しい材料を開発するための伝統的な方法は,しばしば高いコストと広範な実験を伴う.
  • AIは素材のデザインを最適化し 性能をより効率的に予測できます

研究 の 目的:

  • 化学組成に基づいて摩擦材料の機械的性質を予測するためのAI駆動数学モデルを開発する.
  • 既存の摩擦材料の組成を最適化し,新しい摩擦材料の組成を提案するためのアルゴリズムを作成する.
  • 伝統的な方法と比較してAIモデルの予測精度を評価する.

主な方法:

  • 摩擦材料の化学組成と機械的性質の広範なデータベースを使用しました.
  • ルールベースのシステムと ニューラルネットワークと 粒子群の最適化を組み合わせた AI アルゴリズムを開発しました
  • モデルの精度を検証するために,アルゴリズムの予測に基づいて物理的なサンプルを生産し,テストしました.

主要な成果:

  • AIモデル,特にニューラルネットワークは,新しい摩擦材料組成の予測精度が著しく高いことを示しました.
  • ニューラルネットワークの予測のルート・ミーン・スクエア・エラー (RMSE) は,多線型モデルよりも大幅に低かった.
キーワード:
人工知能摩擦材料機械学習

さらに関連する動画

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy
06:54

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

Published on: January 20, 2023

2.4K
Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry
11:19

Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry

Published on: September 6, 2016

12.5K

関連する実験動画

Last Updated: Sep 8, 2025

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
11:05

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

Published on: December 13, 2016

12.3K
A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy
06:54

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

Published on: January 20, 2023

2.4K
Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry
11:19

Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry

Published on: September 6, 2016

12.5K
  • 平均して,多線形モデルは,存在しない組成物のAI予測と比較して48.6%大きなRMSEを示した.

    • 結論:

    • AIは,特にニューラルネットワークは,新しい摩擦材料の機械的性質を予測するための優れたアプローチを提供します.
    • 開発されたアルゴリズムは,材料の組成を効果的に最適化し,新しい配列を提案します.
    • AIベースのモデリングは 高価な物理実験の必要性を減らし 材料の発見を加速します