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Related Concept Videos

Solid–Solid Solutions01:24

Solid–Solid Solutions

The temperature-composition phase diagram of two solids, A and B, which are immiscible in the solid phase but form miscible liquids, shows that when the temperature is low, these two exist as separate, pure solids (A and B). As the temperature increases, they transition into a single-phase liquid solution where A and B coexist. Moving from point a1 to a2 in the phase diagram, the composition changes such that solid B begins to separate from the solution, enriching the remaining liquid with A.
Metallic Solids02:37

Metallic Solids

Metallic solids such as crystals of copper, aluminum, and iron are formed by metal atoms. The structure of metallic crystals is often described as a uniform distribution of atomic nuclei within a “sea” of delocalized electrons. The atoms within such a metallic solid are held together by a unique force known as metallic bonding that gives rise to many useful and varied bulk properties.
All metallic solids exhibit high thermal and electrical conductivity, metallic luster, and malleability. Many...
Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
Structures of Solids02:22

Structures of Solids

Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
Mesh Analysis01:20

Mesh Analysis

Mesh analysis is a valuable method for simplifying circuit analysis using mesh currents as key circuit variables. Unlike nodal analysis, which focuses on determining unknown voltages, mesh analysis applies Kirchhoff's voltage law (KVL) to find unknown currents within a circuit. This method is particularly convenient in reducing the number of simultaneous equations that need to be solved.
A fundamental concept in mesh analysis is the definition of meshes and mesh currents. A mesh is a closed...
Network Covalent Solids02:18

Network Covalent Solids

Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...

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Updated: May 10, 2026

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

DagSolid: a new Geant4 solid class for fast simulation in polygon-mesh geometry.

Min Cheol Han1, Chan Hyeong Kim, Jong Hwi Jeong

  • 1Department of Nuclear Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, Korea.

Physics in Medicine and Biology
|June 18, 2013
PubMed
Summary
This summary is machine-generated.

A new Geant4 solid class, DagSolid, significantly accelerates Monte Carlo simulations for complex geometries. Developed using the Direct Accelerated Geometry for Monte Carlo (DAGMC) library, it drastically improves computation speed for faceted models.

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An Efficient and Flexible Cell Aggregation Method for 3D Spheroid Production
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An Efficient and Flexible Cell Aggregation Method for 3D Spheroid Production

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Related Experiment Videos

Last Updated: May 10, 2026

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

An Efficient and Flexible Cell Aggregation Method for 3D Spheroid Production
07:46

An Efficient and Flexible Cell Aggregation Method for 3D Spheroid Production

Published on: March 27, 2017

Area of Science:

  • Computational Physics
  • Particle Physics Simulation
  • Geometrical Modeling

Background:

  • Geant4's G4TessellatedSolid class struggles with performance for complex, high-facet geometries.
  • Slow computation speeds hinder detailed Monte Carlo simulations of intricate designs.

Purpose of the Study:

  • To develop an optimized Geant4 solid class for faster Monte Carlo simulations.
  • To enhance the handling of computer-aided design (CAD)-based geometries in Geant4.

Main Methods:

  • Developed a new Geant4 solid class, DagSolid, by deriving from G4VSolid.
  • Integrated ray-tracing acceleration functions from the Direct Accelerated Geometry for Monte Carlo (DAGMC) library into DagSolid.

Main Results:

  • DagSolid drastically improves computation speed compared to G4TessellatedSolid.
  • Speed improvements are more pronounced for geometries with a higher number of facets.
  • Achieved speedups of up to 1562x for Geantino and 680x for ChargedGeantino, and 53-685x for real particles.

Conclusions:

  • The DagSolid class offers a significant performance enhancement for Geant4 simulations involving complex CAD geometries.
  • DagSolid is particularly effective for intricate models with numerous facets, enabling more efficient simulations.