Reduction of numerical errors in the simulation of field-particle interaction problems using the TLM algorithm

1996 ◽  
Author(s):  
M.G. Kong
Keyword(s):  
Particle Interaction ◽  
Numerical Errors

Current status of special planetary and lunar theories and ephemerides

1966 ◽  
Vol 25 ◽  
pp. 266-267
Author(s):  
R. L. Duncombe
Keyword(s):  
Observational Data ◽  
Current Status ◽  
Numerical Errors

An examination of some specialized lunar and planetary ephemerides has revealed inconsistencies in the adopted planetary masses, the presence of non-gravitational terms, and some outright numerical errors. They should be considered of temporary usefulness only, subject to subsequent amendment as required for the interpretation of observational data.

scholarly journals Simulation of Flexible Fibre Particle Interaction with a Single Cylinder

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 191
Author(s):  
Naser Hamedi ◽  
Lars-Göran Westerberg
Keyword(s):  
Reynolds Number ◽  
Shear Flow ◽  
Fibre Orientation ◽  
Flow Direction ◽  
Particle Interaction ◽  
Orientation Angle ◽  
Factors Affecting ◽  
Single Cylinder ◽  
Flow Past ◽  
Fibre Suspension

In the present study, the flow of a fibre suspension in a channel containing a cylinder was numerically studied for a very low Reynolds number. Further, the model was validated against previous studies by observing the flexible fibres in the shear flow. The model was employed to simulate the rigid, semi-flexible, and fully flexible fibre particle in the flow past a single cylinder. Two different fibre lengths with various flexibilities were applied in the simulations, while the initial orientation angle to the flow direction was changed between 45° ≤ θ ≤ 75°. It was shown that the influence of the fibre orientation was more significant for the larger orientation angle. The results highlighted the influence of several factors affecting the fibre particle in the flow past the cylinder.

scholarly journals Formfactors of Relativistic Composite Particle Interactions in Unified Nonlinear Spinorfield Models

1985 ◽  
Vol 40 (7) ◽  
pp. 752-773
Author(s):  
H. Stumpf
Keyword(s):  
Composite Particle ◽  
Particle Interaction ◽  
High Energy ◽  
Field Theories ◽  
Quantum Field Theories ◽  
Statistical Interpretation ◽  
Quantum Field ◽  
Mapping Procedure ◽  
Effective Dynamics ◽  
Rough Approximation

Unified nonlinear spinorfield models are self-regularizing quantum field theories in which all observable (elementary and non-elementary) particles are assumed to be bound states of fermionic preon fields. Due to their large masses the preons themselves are confined and below the threshold of preon production the effective dynamics of the model is only concerned with bound state reactions. In preceding papers a functional energy representation, the statistical interpretation and the dynamical equations were derived and the effective dynamics for preon-antipreon boson states and three preon-fermion states (with corresponding anti-fermions) was studied in the low energy limit. The transformation of the functional energy representation of the spinorfield into composite particle functional operators produced a hierarchy of effective interactions at the composite particle level, the leading terms of which are identical with the functional energy representation of a phenomenological boson-fermion coupling theory. In this paper these calculations are extended into the high energy range. This leads to formfactors for the composite particle interaction terms which are calculated in a rough approximation and which in principle are observable. In addition, the mathematical and physical interpretation of nonlocal quantum field theories and the meaning of the mapping procedure, its relativistic invariance etc. are discussed.

scholarly journals 3D monitoring of the surface slippage effect on micro-particle sedimentation by digital holographic microscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Majid Panahi ◽  
Ramin Jamali ◽  
Vahideh Farzam Rad ◽  
Mojtaba Khorasani ◽  
Ahamd Darudi ◽  
...  
Keyword(s):  
Slip Length ◽  
Particle Interaction ◽  
Three Dimensional ◽  
Digital Holographic Microscopy ◽  
Particle Sedimentation ◽  
Micro Particles ◽  
Slippage Effect ◽  
Holographic Microscopy ◽  
3D Information ◽  
Experimental Findings

AbstractIn several phenomena in biology and industry, it is required to understand the comprehensive behavior of sedimenting micro-particles in fluids. Here, we use the numerical refocusing feature of digital holographic microscopy (DHM) to investigate the slippage effect on micro-particle sedimentation near a flat wall. DHM provides quantitative phase contrast and three-dimensional (3D) imaging in arbitrary time scales, which suggests it as an elegant approach to investigate various phenomena, including dynamic behavior of colloids. 3D information is obtained by post-processing of the recorded digital holograms. Through analysis of 3D trajectories and velocities of multiple sedimenting micro-particles, we show that proximity to flat walls of higher slip lengths causes faster sedimentation. The effect depends on the ratio of the particle size to (1) the slip length and (2) its distance to the wall. We corroborate our experimental findings by a theoretical model which considers both the proximity and the particle interaction to a wall of different hydrophobicity in the hydrodynamic forces.

scholarly journals The Model Order Reduction Method as an Effective Way to Implement GPC Controller for Multidimensional Objects

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 178
Author(s):  
Sebastian Plamowski ◽  
Richard W Kephart
Keyword(s):  
Predictive Control ◽  
Model Order Reduction ◽  
Order Reduction ◽  
High Order ◽  
Double Precision ◽  
Model Order ◽  
Numerical Errors ◽  
Multiple Input ◽  
Multidimensional Objects ◽  
Order Reduction Method

The paper addresses issues associated with implementing GPC controllers in systems with multiple input signals. Depending on the method of identification, the resulting models may be of a high order and when applied to a control/regulation law, may result in numerical errors due to the limitations of representing values in double-precision floating point numbers. This phenomenon is to be avoided, because even if the model is correct, the resulting numerical errors will lead to poor control performance. An effective way to identify, and at the same time eliminate, this unfavorable feature is to reduce the model order. A method of model order reduction is presented in this paper that effectively mitigates these issues. In this paper, the Generalized Predictive Control (GPC) algorithm is presented, followed by a discussion of the conditions that result in high order models. Examples are included where the discussed problem is demonstrated along with the subsequent results after the reduction. The obtained results and formulated conclusions are valuable for industry practitioners who implement a predictive control in industry.

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