Application of variably graded mesh to the spatial network method in three-dimensional space

1991 ◽  
Vol 74 (12) ◽  
pp. 1-13
Author(s):  
Naoya Kukutsu ◽  
Norinobu Yoshida ◽  
Ichiro Fukai
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Spatial Network ◽  
Graded Mesh ◽  
Network Method ◽  
Three Dimensional Space

Dynamic Simulation of Multibody Mechanical Systems Using the Vector-Network Model

1988 ◽  
Vol 12 (1) ◽  
pp. 21-30 ◽  
Author(s):  
M.J. Richard
Keyword(s):  
Dynamic Models ◽  
Analytical Procedure ◽  
Dimensional Space ◽  
Digital Simulation ◽  
Three Dimensional ◽  
General Purpose ◽  
New Approach ◽  
Network Method ◽  
Definition Of ◽  
Three Dimensional Space

Pressing technological problems have created a growing interest in the development of dynamic models for the digital simulation of multibody systems. This paper describes a new approach to the problem of motion prediction. An extension of the “vector-network” method to rigid body systems in three-dimensional space is introduced. The entire procedure is a basic application of concepts of graph theory in which laws of vector dynamics are combined. The analytical procedure was successfully implemented within a general-purpose digital simulation program since, from a minimal definition of the mechanism, it will automatically predict the behavior of the system as output, thereby giving the impression that the equations governing the motion of the mechanical system have been completely formulated and solved by the computer. Simulations of the response of a rail vehicle which demonstrate the validity, applicability and self-formulating aspect of the automated model are provided.

A General Model for Thermal Conductivity and Electric Conductivity of Nanofluids

2012 ◽  
Vol 614-615 ◽  
pp. 529-535 ◽  
Author(s):  
Wei Ting Jiang
Keyword(s):  
Electric Conductivity ◽  
Volume Fraction ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Simulation Method ◽  
Space Structure ◽  
Liquid Molecule ◽  
Nanoparticle Clusters ◽  
Network Method ◽  
Three Dimensional Space

Nanoparticles in nanofluids are in the form of nanoparticle clusters caused by aggregation. In order to calculate the thermal and electric conductivity of the nanofluids, the growth process and three-dimensional space structure of the nanoparticle cluster in the host fluid is simulated, and then the thermal and electric conductivity of the cluster are calculated with the resistance network method. The thermal and electric conductivity of the nanofluid are calculated based on the simulated thermal and electric conductivity of nanoparticle clusters, the volume fraction of nanoparticle clusters to the nanofluid as well as the liquid molecule adsorption layer of the nanoparticle. The simulation method is validated by experimental data.

A Prediction Method for Thermal Conductivity and Electric Conductivity of Nanofluids Based on Particles Aggregation Theory

2007 ◽  
Author(s):  
Guo-Liang Ding ◽  
Wei-Ting Jiang ◽  
Yi-Feng Gao
Keyword(s):  
Volume Fraction ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Prediction Method ◽  
Simulation Method ◽  
Space Structure ◽  
Liquid Molecule ◽  
Nanoparticle Clusters ◽  
Network Method ◽  
Three Dimensional Space

Nanoparticles in nanofluids are in the form of nanoparticle clusters caused by aggregation. In order to calculate the thermal and electric conductivities of the nanofluids, the growth process and three-dimensional space structure of the nanoparticle cluster in the host fluid was simulated, and then the thermal and electric conductivities of the cluster were calculated with the resistance network method. The thermal and electric conductivities of the nanofluid were calculated based on the simulated thermal and electric conductivities of nanoparticle clusters, the volume fraction of nanoparticle clusters to the nanofluid as well as the liquid molecule adsorption layer of the nanoparticle. The simulation method was validated by experimental data.

Extension of the Spatial PDI Model to Three Dimensions

1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien
Keyword(s):  
Population Density ◽  
Dimensional Space ◽  
Finite Lattice ◽  
Three Dimensional ◽  
Upper Bounds ◽  
Three Dimensions ◽  
Lower And Upper Bounds ◽  
Density Index ◽  
Three Dimensional Space

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.

A Peptoid with Extended Shape in Water

2019 ◽  
Author(s):  
Jumpei Morimoto ◽  
Yasuhiro Fukuda ◽  
Takumu Watanabe ◽  
Daisuke Kuroda ◽  
Kouhei Tsumoto ◽  
...  
Keyword(s):  
Spectroscopic Analysis ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Biomolecular Recognition ◽  
Biological Application ◽  
New Class ◽  
Proteolytic Resistance ◽  
Pharmacokinetic Properties ◽  
Optically Pure ◽  
Three Dimensional Space

<div> <div> <div> <p>“Peptoids” was proposed, over decades ago, as a term describing analogs of peptides that exhibit better physicochemical and pharmacokinetic properties than peptides. Oligo-(N-substituted glycines) (oligo-NSG) was previously proposed as a peptoid due to its high proteolytic resistance and membrane permeability. However, oligo-NSG is conformationally flexible and is difficult to achieve a defined shape in water. This conformational flexibility is severely limiting biological application of oligo-NSG. Here, we propose oligo-(N-substituted alanines) (oligo-NSA) as a new peptoid that forms a defined shape in water. A synthetic method established in this study enabled the first isolation and conformational study of optically pure oligo-NSA. Computational simulations, crystallographic studies and spectroscopic analysis demonstrated the well-defined extended shape of oligo-NSA realized by backbone steric effects. The new class of peptoid achieves the constrained conformation without any assistance of N-substituents and serves as an ideal scaffold for displaying functional groups in well-defined three-dimensional space, which leads to effective biomolecular recognition. </p> </div> </div> </div>

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