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

Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

415
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
415
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

363
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures enhance...
363
Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

829
Newtonian fluids exhibit a constant viscosity, meaning their shear stress and shear strain rate are directly proportional. This property ensures a predictable and stable response to applied forces, maintaining a linear relationship between force and flow. Examples include water, air, and light oils, consistently demonstrating this proportional behavior regardless of external conditions.
A velocity gradient forms within the fluid when a Newtonian fluid is placed between two parallel plates, with...
829
Velocity and Position by Integral Method01:13

Velocity and Position by Integral Method

7.3K
If acceleration as a function of time is known, then velocity and position functions can be derived using integral calculus. For constant acceleration, the integral equations refer to the first and second kinematic equations for velocity and position functions, respectively.
Consider an example to calculate the velocity and position from the acceleration function. A motorboat is traveling at a constant velocity of 5.0 m/s when it starts to decelerate to arrive at the dock. Its acceleration is...
7.3K
Velocity and Acceleration in Steady and Unsteady Flow01:11

Velocity and Acceleration in Steady and Unsteady Flow

355
In fluid mechanics, velocity and acceleration are key concepts for analyzing particle motion in both steady and unsteady flow. Consider a fluid particle moving along a pathline, where its velocity depends on its position and time. The particle's acceleration is obtained by differentiating the velocity with respect to time.
The acceleration can be generalized to any point in the flow, and expressed as components along three perpendicular directions, representing changes in velocity over...
355
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

513
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
513

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 authorSame journal

An effective and accurate semi-implicit time integration scheme for dynamics in nearly- and fully-incompressible hyperelastic solids.

Journal of computational physics·2026
Same author

Adaptive Mesh Refinement for Two-Phase Viscoelastic Fluid Mixture Models.

Computers & fluids·2026
Same author

Generating patient-specific computational models with point cloud data from human atrial electrophysiology studies.

PloS one·2026
Same authorSame journal

Composite B-spline regularized delta functions for the immersed boundary method: Divergence-free interpolation and gradient-preserving force spreading.

Journal of computational physics·2026
Same author

LOCAL DIVERGENCE-FREE IMMERSED FINITE ELEMENT-DIFFERENCE METHOD USING COMPOSITE B-SPLINES.

Advances in computational science and engineering·2025
Same author

Temporal evolution of hemodynamics in murine arteriovenous fistula: A micro-CT based CFD study.

PLoS computational biology·2025

関連する実験動画

Updated: Jan 7, 2026

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions
11:51

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

Published on: February 22, 2018

9.1K

正則化された速度再構成による浸漬界面法の堅牢性の向上

Qi Sun1, Ebrahim M Kolahdouz1, Boyce E Griffith1,2,3,4,5,6

  • 1Department of Mathematics, University of North Carolina, Chapel Hill, NC, USA.

Journal of computational physics
|December 31, 2025
PubMed
まとめ

新しい安定化戦略は、流体-構造連成(FSI)アルゴリズムを強化し、流体と構造間の柔軟なメッシュ比を可能にします。これにより、計算効率が向上し、複雑な工学問題に対するFSIシミュレーションの適用範囲が広がります。

キーワード:
流体-構造連成浸漬界面法正則化安定化計算力学

さらに関連する動画

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

4.3K
High-speed Particle Image Velocimetry Near Surfaces
11:59

High-speed Particle Image Velocimetry Near Surfaces

Published on: June 24, 2013

33.7K

関連する実験動画

Last Updated: Jan 7, 2026

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions
11:51

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

Published on: February 22, 2018

9.1K
Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

4.3K
High-speed Particle Image Velocimetry Near Surfaces
11:59

High-speed Particle Image Velocimetry Near Surfaces

Published on: June 24, 2013

33.7K

科学分野:

  • 計算力学
  • 流体-構造連成(FSI)モデリング

背景:

  • 堅牢で効率的な流体-構造連成(FSI)アルゴリズムの開発は、正確な計算力学にとって重要です。
  • 既存の浸漬界面法(IIM)は、制限的なメッシュ係数比に直面しており、複雑な形状の計算コストが増加します。

研究 の 目的:

  • IIMにおける速度補間演算子の安定化戦略を考案し、メッシュ比の制限を克服すること。
  • 複雑な形状や動的条件に対するFSIシミュレーションの適用性と効率を向上させること。

主な方法:

  • チホノフ正則化に着想を得た速度補間演算子の安定化戦略を導入しました。
  • 定常界面およびFSIモデル(剛体ダイナミクス、弾性力学構造)を備えたベンチマーク問題を使用して有効性を評価しました。

主要な成果:

  • 安定化された速度補間演算子により、構造から流体へのグリッドサイズ比の範囲が広がります。
  • 精度と流れのダイナミクスは、緩和されたメッシュ比制約の影響を受けません。
  • この方法は、複雑な3D形状と多様な工学アプリケーションをモデル化することに成功しています。

結論:

  • 安定化されたIIMは、複雑な形状や動的条件を持つFSI問題に対して、堅牢で実用的なソリューションを提供します。
  • この進歩により、計算力学におけるIIMの適用範囲が大幅に広がります。