Jove
Visualize
Contact Us

Related Concept Videos

Couette Flow01:22

Couette Flow

939
Couette flow represents the flow of fluid between two parallel plates, with one plate fixed and the other moving with a constant velocity. This configuration allows for a simplified analysis using the Navier-Stokes equations, which govern fluid motion under conditions of viscosity and incompressibility. For Couette flow, the assumptions include a steady, laminar, incompressible flow with a zero-pressure gradient in the flow direction. This flow type is beneficial for understanding shear-driven...
939
Accelerating Fluids01:17

Accelerating Fluids

2.1K
When a fluid is in constant acceleration, the pressure and buoyant force equations are modified. Suppose a beaker is placed in an elevator accelerating upward with a constant acceleration, a. In the beaker, assume there is a thin cylinder of height h with an infinitesimal cross-sectional area, ΔS.
The motion of the liquid within this infinitesimal cylinder is considered to obtain the pressure difference. Three vertical forces act on this liquid:
2.1K
Rapidly Varying Flow01:24

Rapidly Varying Flow

441
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
441
Turbulent Flow01:24

Turbulent Flow

671
Turbulent flow is characterized by unpredictable fluctuations in velocity and pressure, which result in a chaotic fluid movement distinct from the orderly patterns of laminar flow. While laminar flow is governed by smooth, parallel layers with minimal mixing, turbulent flow exhibits highly irregular, three-dimensional patterns. This behavior arises due to instabilities in the fluid's velocity profile, and amplifies as the flow velocity increases. Minor disturbances, known as turbulent...
671
Steady Flow of a Fluid Stream01:27

Steady Flow of a Fluid Stream

664
Consider a control volume, such as a pipe with solid boundaries, through which fluid flows and changes direction due to the impulse exerted by the resulting force from the pipe walls. In steady flow, the mass of fluid entering the control volume at a given time, t, with velocity v1, is equal to the mass leaving after infinitesimal time dt, with velocity v2.
During this process, the momentum of the fluid within the control volume remains constant over the time interval dt. By applying the...
664
Gradually Varying Flow01:29

Gradually Varying Flow

406
Gradually varying flow (GVF) in open channels describes situations where water depth changes slowly along the channel due to factors like non-uniform bed slope, channel shape variations, or obstructions. This flow type occurs when the depth adjusts gradually to balance gravitational forces, shear forces, and energy requirements, resulting in a low rate of depth change.Characteristics of Gradually Varying FlowGVF is commonly observed in natural streams, rivers, and canals, where flow depth...
406

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Application of Machine Learning Algorithms to Metadynamics for the Elucidation of the Binding Modes and Free Energy Landscape of Drug/Target Interactions: a Case Study.

Chemistry (Weinheim an der Bergstrasse, Germany)·2023
Same author

Deep coarse-grained potentials via relative entropy minimization.

The Journal of chemical physics·2022
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jan 14, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.0K

Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework without Data.

Maximilian Stupp1, P S Koutsourelakis1,2

  • 1Professorship of Data-Driven Materials Modeling, School of Engineering and Design, Technical University of Munich, Garching bei München 85748, Germany.

Journal of Chemical Theory and Computation
|October 24, 2025
PubMed
Summary

This study introduces a novel data-free generative framework for coarse-graining molecular simulations. The method accurately reconstructs atomic configurations and learns meaningful representations without relying on extensive simulation data.

More Related Videos

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.3K
Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

5.0K

Related Experiment Videos

Last Updated: Jan 14, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.0K
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.3K
Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

5.0K

Area of Science:

  • Computational Chemistry and Molecular Modeling
  • Statistical Mechanics
  • Machine Learning in Science

Background:

  • Conventional coarse-grained (CG) models require extensive all-atom simulation data, limiting accuracy and generalizability.
  • Data dependence excludes unvisited configurations, posing challenges for sampling configurational space.
  • The "chicken-and-egg" problem and back-mapping inaccuracies hinder traditional CG methods.

Purpose of the Study:

  • To develop a fully data-free generative framework for coarse-graining.
  • To directly target the all-atom Boltzmann distribution without prior simulation trajectories.
  • To enable accurate reconstruction of molecular structures and address the back-mapping problem.

Main Methods:

  • A generative framework defining a structured latent space with slow and fast collective variables.
  • A learnable, bijective map from latent space to atomistic coordinates for structure reconstruction.
  • Training via an energy-based objective minimizing reverse Kullback-Leibler divergence, using an adaptive tempering scheme.

Main Results:

  • The framework successfully captures all relevant modes of the Boltzmann distribution on synthetic and benchmark systems.
  • High-fidelity reconstruction of atomic configurations from the learned latent space.
  • Automatic learning of physically meaningful coarse-grained representations without external data.

Conclusions:

  • The proposed data-free framework offers a promising alternative to traditional coarse-graining techniques.
  • It effectively addresses the limitations of data dependence and the back-mapping problem.
  • The method provides a principled approach for accurate molecular structure generation and simulation.