Numerical Solution by the CESE Method of a First-Order Hyperbolic Form of the Equations of Dynamic Nonlinear Elasticity

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
Lixiang Yang ◽  
Robert L. Lowe ◽  
Sheng-Tao John Yu ◽  
Stephen E. Bechtel
Keyword(s):  
Numerical Solution ◽  
Numerical Approach ◽  
The Other ◽  
Hyperbolic Partial Differential Equations ◽  
Elastic Solids ◽  
First Order ◽  
Diagonal Forms ◽  
Hyperbolic Form ◽  
Spurious Oscillations ◽  
Wave Problems

This paper reports the application of the space-time conservation element and solution element (CESE) method to the numerical solution of nonlinear waves in elastic solids. The governing equations consist of a pair of coupled first-order nonlinear hyperbolic partial differential equations, formulated in the Eulerian frame. We report their derivations and present conservative, nonconservative, and diagonal forms. The conservative form is solved numerically by the CESE method; the other forms are used to study the eigenstructure of the hyperbolic system (which reveals the underlying wave physics) and deduce the Riemann invariants. The proposed theoretical/numerical approach is demonstrated by directly solving two benchmark elastic wave problems: one involving linear propagating extensional waves, the other involving nonlinear resonant standing waves. For the extensional wave problem, the CESE method accurately captures the sharp propagating wavefront without excessive numerical diffusion or spurious oscillations, and predicts correct reflection characteristics at the boundaries. For the resonant vibrations problem, the CESE method captures the linear-to-nonlinear evolution of the resonant waves and the distribution of wave energy among multiple modes in the nonlinear regime.

scholarly journals Thematic Maps for the Variation of Bearing Capacity of Soil Using SPTs and MATLAB

Geosciences ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 329
Author(s):  
Mahdi O. Karkush ◽  
Mahmood D. Ahmed ◽  
Ammar Abdul-Hassan Sheikha ◽  
Ayad Al-Rumaithi
Keyword(s):  
Bearing Capacity ◽  
Mean Squared Error ◽  
Ground Level ◽  
The Other ◽  
Thematic Maps ◽  
First Order ◽  
Squared Error ◽  
Order Polynomial ◽  
Interpolation Polynomials ◽  
Penetration Tests

The current study involves placing 135 boreholes drilled to a depth of 10 m below the existing ground level. Three standard penetration tests (SPT) are performed at depths of 1.5, 6, and 9.5 m for each borehole. To produce thematic maps with coordinates and depths for the bearing capacity variation of the soil, a numerical analysis was conducted using MATLAB software. Despite several-order interpolation polynomials being used to estimate the bearing capacity of soil, the first-order polynomial was the best among the other trials due to its simplicity and fast calculations. Additionally, the root mean squared error (RMSE) was almost the same for the all of the tried models. The results of the study can be summarized by the production of thematic maps showing the variation of the bearing capacity of the soil over the whole area of Al-Basrah city correlated with several depths. The bearing capacity of soil obtained from the suggested first-order polynomial matches well with those calculated from the results of SPTs with a deviation of ±30% at a 95% confidence interval.

scholarly journals Numerical Solution of the Spinor-Spinor Bethe-Salpeter Equation in Functional Nonlinear Spinor Theory

1975 ◽  
Vol 30 (5) ◽  
pp. 656-671
Author(s):  
W. Bauhoff
Keyword(s):  
Angular Momentum ◽  
Excited State ◽  
Variational Method ◽  
Numerical Solution ◽  
High Precision ◽  
Nonlinear Spinor ◽  
Spinor Theory ◽  
First Order ◽  
Scalar Mesons ◽  
Functional Methods

AbstractThe mass eigenvalue equation for mesons in nonlinear spinor theory is derived by functional methods. In second order it leads to a spinorial Bethe-Salpeter equation. This is solved by a variational method with high precision for arbitrary angular momentum. The results for scalar mesons show a shift of the first order results, obtained earlier. The agreement with experiment is improved thereby. An excited state corresponding to the η' is found. A calculation of a Regge trajectory is included,too.

Neural computation of motion in the fly visual system: quadratic nonlinearity of responses induced by picrotoxin in the HS and CH cells

1995 ◽  
Vol 74 (6) ◽  
pp. 2665-2684 ◽  
Author(s):  
Y. Kondoh ◽  
Y. Hasegawa ◽  
J. Okuma ◽  
F. Takahashi
Keyword(s):  
Mean Square Error ◽  
Order Term ◽  
Mirror Image ◽  
Second Order ◽  
The Other ◽  
Linear Component ◽  
Mean Square ◽  
Nonlinear Component ◽  
First Order ◽  
Order Kernel

1. A computational model accounting for motion detection in the fly was examined by comparing responses in motion-sensitive horizontal system (HS) and centrifugal horizontal (CH) cells in the fly's lobula plate with a computer simulation implemented on a motion detector of the correlation type, the Reichardt detector. First-order (linear) and second-order (quadratic nonlinear) Wiener kernels from intracellularly recorded responses to moving patterns were computed by cross correlating with the time-dependent position of the stimulus, and were used to characterize response to motion in those cells. 2. When the fly was stimulated with moving vertical stripes with a spatial wavelength of 5-40 degrees, the HS and CH cells showed basically a biphasic first-order kernel, having an initial depolarization that was followed by hyperpolarization. The linear model matched well with the actual response, with a mean square error of 27% at best, indicating that the linear component comprises a major part of responses in these cells. The second-order nonlinearity was insignificant. When stimulated at a spatial wavelength of 2.5 degrees, the first-order kernel showed a significant decrease in amplitude, and was initially hyperpolarized; the second-order kernel was, on the other hand, well defined, having two hyperpolarizing valleys on the diagonal with two off-diagonal peaks. 3. The blockage of inhibitory interactions in the visual system by application of 10-4 M picrotoxin, however, evoked a nonlinear response that could be decomposed into the sum of the first-order (linear) and second-order (quadratic nonlinear) terms with a mean square error of 30-50%. The first-order term, comprising 10-20% of the picrotoxin-evoked response, is characterized by a differentiating first-order kernel. It thus codes the velocity of motion. The second-order term, comprising 30-40% of the response, is defined by a second-order kernel with two depolarizing peaks on the diagonal and two off-diagonal hyperpolarizing valleys, suggesting that the nonlinear component represents the power of motion. 4. Responses in the Reichardt detector, consisting of two mirror-image subunits with spatiotemporal low-pass filters followed by a multiplication stage, were computer simulated and then analyzed by the Wiener kernel method. The simulated responses were linearly related to the pattern velocity (with a mean square error of 13% for the linear model) and matched well with the observed responses in the HS and CH cells. After the multiplication stage, the linear component comprised 15-25% and the quadratic nonlinear component comprised 60-70% of the simulated response, which was similar to the picrotoxin-induced response in the HS cells. The quadratic nonlinear components were balanced between the right and left sides, and could be eliminated completely by their contralateral counterpart via a subtraction process. On the other hand, the linear component on one side was the mirror image of that on the other side, as expected from the kernel configurations. 5. These results suggest that responses to motion in the HS and CH cells depend on the multiplication process in which both the velocity and power components of motion are computed, and that a putative subtraction process selectively eliminates the nonlinear components but amplifies the linear component. The nonlinear component is directionally insensitive because of its quadratic non-linearity. Therefore the subtraction process allows the subsequent cells integrating motion (such as the HS cells) to tune the direction of motion more sharply.

Milling Curves Influence in Ring Rolling Processes

2014 ◽  
Vol 622-623 ◽  
pp. 956-963 ◽  
Author(s):  
Luca Giorleo ◽  
Elisabetta Ceretti ◽  
Claudio Giardini
Keyword(s):  
Numerical Approach ◽  
The Other ◽  
Ring Rolling ◽  
Roll Speed ◽  
Forming Process ◽  
Industrial Case Study ◽  
Industrial Environment ◽  
Ring Shape ◽  
Deformation Processes

Ring Rolling is a complex hot forming process used for the production of shaped rings, seamless and axis symmetrical workpieces. The main advantage of workpieces produced by ring rolling, compared to other technological processes, is given by the size and orientation of grains, especially on the worked surface which give to the final product excellent mechanical properties. In this process different rolls (Idle, Axial, Guide and Driver) are involved in generating the desired ring shape. Since each roll is characterized by a speed law that can be set independently by the speed law imposed to the other rolls, an optimization is more critical compared with other deformation processes. Usually, in industrial environment, a milling curve is introduced in order to correlate the Idle and Axial roll displacement, however it must be underlined that different milling curves lead to different loads and energy for ring realization. In this work an industrial case study was modeled by a numerical approach: different milling curves characterized by different Idle and Axial roll speed laws (linearly decreasing, constant, linearly increasing) were designed and simulated. The results were compared in order to identify the best milling curve that guarantees a good quality ring (higher diameter, lower fishtail) with lower loads and energy required for manufacturing.

A Numerical Approach to Determine Some Properties of Cylindrical Pieces of Bananas During Drying

2015 ◽  
Vol 11 (3) ◽  
pp. 335-347 ◽  
Author(s):  
Wilton Pereira da Silva ◽  
Cleide M. D. P. S. e Silva ◽  
Aluizio Freire da Silva Junior ◽  
Alexandre José de Melo Queiroz
Keyword(s):  
Numerical Solution ◽  
Numerical Approach ◽  
Moisture Diffusivity ◽  
Convective Drying ◽  
Chi Square ◽  
Experimental Conditions ◽  
Liquid Diffusion ◽  
Air Temperatures ◽  
C 50 ◽  
Volume Method

Abstract This article uses several liquid diffusion models to describe convective drying of bananas cut into cylindrical pieces. A two-dimensional numerical solution of the diffusion equation with boundary condition of the third kind, obtained through the finite volume method, was used to describe the process. The cylindrical pieces were cut into the following dimensions: length of about 21 mm and average radius of 15 mm. Drying air temperatures were 40°C, 50°C, 60°C and 70°C. In order to determine the process parameters, an optimizer was coupled with the numerical solution. A model that considers the shrinkage and variable effective moisture diffusivity well describes drying for all the experimental conditions, and enables to predict the moisture distributions at any given time. For this model, the determination coefficient has varied from 0.99937 (70°C) to 0.99995 (40°C), while the chi-square ranged from 3.41 × 10−4 (40°C) to 4.15 × 10−3 (70°C).

scholarly journals Ganglioside incorporation and release by the isolated perfused rat liver

1991 ◽  
Vol 274 (2) ◽  
pp. 581-585 ◽  
Author(s):  
S C Kivatinitz ◽  
A Miglio ◽  
R Ghidoni
Keyword(s):  
Rat Liver ◽  
The Other ◽  
Regulatory Role ◽  
Isolated Perfused Rat Liver ◽  
Order Kinetic ◽  
Perfused Rat Liver ◽  
Ganglioside Gm1 ◽  
First Order ◽  
Pseudo First Order

The fate of exogenous ganglioside GM1 labelled in the sphingosine moiety, [Sph-3H]GM1, administered as a pulse, in the isolated perfused rat liver was investigated. When a non-recirculating protocol was employed, the amount of radioactivity in the liver and perfusates was found to be dependent on the presence of BSA in the perfusion liquid and on the time elapsed after the administration of the ganglioside. When BSA was added to the perfusion liquid, less radioactivity was found in the liver and more in the perfusate at each time tested, for up to 1 h. The recovery of radioactivity in the perfusates followed a complex course which can be described by three pseudo-first-order kinetic constants. The constants, in order of decreasing velocity, are interpreted as: (a) the dilution of the labelled GM1 by the constant influx of perfusion liquid; (b) the washing off of GM1 loosely bound to the surface of liver cells; (c) the release of gangliosides from the liver. Process (b) was found to be faster in the presence of BSA, probably owing to the ability of BSA to bind gangliosides. The [Sph-3H]GM1 in the liver underwent metabolism, leading to the appearance of products of anabolic (GD1a, GD1b) and catabolic (GM2, GM3) origin; GD1a appeared before GM2 and GM3 but, at times longer than 10 min, GM2 and GM3 showed more radioactivity than GD1a. At a given time the distribution of the radioactivity in the perfusates was quite different from that of the liver. In fact, after 60 min GD1a was the only metabolite present in any amount, the other being GM3, the quantity of which was small. This indicates that the liver is able to release newly synthesized gangliosides quite specifically. When a recirculating protocol was used, there were more catabolites and less GD1a than with the non-recirculating protocol. A possible regulatory role of ganglioside re-internalization on their own metabolism in the liver is postulated.

scholarly journals Pancreatic secretion and pressure biomechanics in pancreatic acinus

2020 ◽  
Vol 19 (1) ◽  
pp. 6-12
Author(s):  
G. Ya. Kostyuk ◽  
O. G. Kostyuk ◽  
M. V Burkov ◽  
I. A. Golubovsky ◽  
M. P. Bulko ◽  
...  
Keyword(s):  
Flow System ◽  
Dynamic Pressure ◽  
Excretory Duct ◽  
The Other ◽  
Duct System ◽  
First Order ◽  
Pancreatic Acinus ◽  
Mercury Column ◽  
The Mathematical Model ◽  
Oddi Sphincter

The article highlights the mechanism of the mathematical model of acinus, the components of the formation of pressure in its cavity and the formation of pancreatic juice. It has been established that the mechanism for creating pressure in the acinus cavity is similar to the intraductal one. In this case, the question remains open about the causes of such high pressure, which is measured in several hundred millimeters of a mercury column, especially since, as histologically established, the pancreas and its ducts do not have muscle structures, and those rudiments of myofibrils, which are noted in some places of the flow system, of course, cannot ensure the development of such pressure. The increase in pressure in the cavity of the acinus is associated with the phenomenon of osmosis in its cells. Since cell membranes have the property of conductivity, as a result of osmosis, water through the membrane first passes from the blood to the cell, then from the cell through the membrane into the acinus cavity. In addition to the mechanism of osmosis through the membrane, in the cells of the acinus epithelium, there is a filtering mechanism through the pores of the layer of connective tissue to the lymph channel. It has now been established that, together with simple osmosis, the phenomenon of electroosmosis takes place in secreting cells and organs of excretion, not only accelerates the transfer of substances, but also increases the pressure on the other side of the membrane against the gradient by almost several first-order units. Thus, the outflow of fluid from the acinus cavity proceeds continuously, but only with a change in the speed of movement, it is determined by the pressure drop in the acinus – tubule – excretory duct system, the opening of the Oddi sphincter and the pulse of the cardiovascular wave, which creates dynamic pressure in the capillary. This whole mechanism, as a result, leads to the filling of the cavity of the acinus and the creation of a certain pressure in it.

scholarly journals Use of Jacobians for inverse kinematics of articulated robots : a study on approximate solutions

2020 ◽  
Author(s):  
◽  
Uriel Jacket Tresor Demby's
Keyword(s):  
Numerical Solution ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Numerical Solutions ◽  
Fuzzy Inference ◽  
Numerical Approach ◽  
Data Driven ◽  
Approximate Methods ◽  
Inference System ◽  
First Case

In the context of articulated robotic manipulators, the Forward Kinematics (FK) is a highly non-linear function that maps joint configurations of the robot to poses of its endeffector. Furthermore, while in the most useful cases these functions are neither injective (one-to-one) nor surjective (onto), depending on the robot configuration -- i.e. the sequence of prismatic versus revolute joints, and the number of Degrees of Freedom (DoF) -- the associated Inverse Kinematics (IK) problem may be practically or even theoretically impossible to be solved analytically. Therefore, in the past decades, several approximate methods have been developed for many instances of IK problems. The approximate methods can be divided into two distinct categories: data-driven and numerical approaches. In the first case, data-driven approaches have been successfully used for small workspace domains (e.g., task-driven applications), but not fully explored for large ones, i.e. in task-independent applications where a more general IK is required. Similarly, and despite many successful implementations over the years, numerical solutions may fail if an improper matrix inverse is employed (e.g., Moore-Penrose generalized inverse). In this research, we propose a systematic, robust and accurate numerical solution for the IK problem using the Unit-Consistent (UC) and the Mixed (MX) Inverse methods to invert the Jacobians derived from the Denavit-Hartenberg (D-H) representation of the FK for any robot. As we demonstrate, this approach is robust to whether the system is underdetermined (less than 6 DoF) or overdetermined (more than 6 DoF). We compare the proposed numerical solution to data driven solutions using different robots -- with DoF varying from 3 to 7. We conclude that numerical solutions are easier to implement, faster, and more accurate than most data-driven approaches in the literature, specially for large workspaces as in task-independent applications. We particularly compared the proposed numerical approach against two data-driven approaches: Multi-Layer Perceptron (MLP) and Adaptive Neuro-Fuzzy Inference System (ANFIS), while exploring various architectures of these Neural Networks (NN): i.e. number of inputs, number of outputs, depth, and number of nodes in the hidden layers.

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