This document describes a device simulation of a MOSFET capacitor. It specifies the mesh, regions, electrodes, doping, contacts, and materials of the simulation. It then solves for the initial conditions and applied bias over a range of voltages, plotting the potential and other quantities at each step. The goal is to simulate the MOSFET capacitor and analyze its behavior under varying voltages.
This document describes a device simulation of the capacitance of a MOSFET. It specifies the mesh, regions, electrodes, doping, contacts, and materials of the simulated MOSFET structure. It then performs simulations by solving for the initial conditions and applying a range of biases to the gate electrode to determine the potential distribution and output potential profiles to files.
This document contains the specifications and commands for simulating the capacitance of a MOSFET device using numerical device simulation software. It defines the mesh, regions, electrodes, doping, contacts, material properties, and models used in the simulation. It then commands the software to solve the device equations for different applied biases and output plots of the potential and other quantities along the device cross-section.
The document summarizes the results of solving a linear programming problem with 2 variables and 6 constraints. The optimal solution was found at the first step with an objective value of 660. The values of the variables X1 and X2 at the optimal solution are 70 and 90, respectively. Ranges for the objective coefficients and right-hand side values are provided where the basis remains unchanged.
The document describes a simulation of an NMOS transistor. It defines the mesh, regions, doping concentrations, materials, and electrical contacts. Initial results are plotted including potential, electric field, and carrier concentrations to analyze the transistor behavior. The gate voltage is then swept to model transistor operation and output current-voltage characteristics.
The document describes a simulation of an NMOS transistor. It defines the mesh, regions, doping concentrations, materials, and electrical contacts. It then performs the simulation, solving the device at different biases and extracting output parameters and plots.
This document provides the solutions manual for Trigonometry 10th Edition by Larson. It includes solutions for all exercises in Chapter 2 on Analytic Trigonometry. The chapter covers fundamental trigonometric identities, verifying identities, solving trigonometric equations, sum and difference formulas, and multiple-angle and product-to-sum formulas. The solutions provide step-by-step workings to arrive at the answers for each problem.
This document provides the solutions manual for Trigonometry 10th Edition by Larson. It includes solutions for all exercises in Chapter 2 on Analytic Trigonometry. The chapter covers fundamental trigonometric identities, verifying identities, solving trigonometric equations, sum and difference formulas, and multiple-angle and product-to-sum formulas. The solutions provide step-by-step workings to arrive at the answers for each problem.
This document describes a device simulation of the capacitance of a MOSFET. It specifies the mesh, regions, electrodes, doping, contacts, and materials of the simulated MOSFET structure. It then performs simulations by solving for the initial conditions and applying a range of biases to the gate electrode to determine the potential distribution and output potential profiles to files.
This document contains the specifications and commands for simulating the capacitance of a MOSFET device using numerical device simulation software. It defines the mesh, regions, electrodes, doping, contacts, material properties, and models used in the simulation. It then commands the software to solve the device equations for different applied biases and output plots of the potential and other quantities along the device cross-section.
The document summarizes the results of solving a linear programming problem with 2 variables and 6 constraints. The optimal solution was found at the first step with an objective value of 660. The values of the variables X1 and X2 at the optimal solution are 70 and 90, respectively. Ranges for the objective coefficients and right-hand side values are provided where the basis remains unchanged.
The document describes a simulation of an NMOS transistor. It defines the mesh, regions, doping concentrations, materials, and electrical contacts. Initial results are plotted including potential, electric field, and carrier concentrations to analyze the transistor behavior. The gate voltage is then swept to model transistor operation and output current-voltage characteristics.
The document describes a simulation of an NMOS transistor. It defines the mesh, regions, doping concentrations, materials, and electrical contacts. It then performs the simulation, solving the device at different biases and extracting output parameters and plots.
This document provides the solutions manual for Trigonometry 10th Edition by Larson. It includes solutions for all exercises in Chapter 2 on Analytic Trigonometry. The chapter covers fundamental trigonometric identities, verifying identities, solving trigonometric equations, sum and difference formulas, and multiple-angle and product-to-sum formulas. The solutions provide step-by-step workings to arrive at the answers for each problem.
This document provides the solutions manual for Trigonometry 10th Edition by Larson. It includes solutions for all exercises in Chapter 2 on Analytic Trigonometry. The chapter covers fundamental trigonometric identities, verifying identities, solving trigonometric equations, sum and difference formulas, and multiple-angle and product-to-sum formulas. The solutions provide step-by-step workings to arrive at the answers for each problem.
Integration is a reverse process of differentiation. The integral or primitive of a function f(x) with
respect to x is that function (x) whose derivative with respect to x is the given function f(x). It is
i. 0. dx = c
ii. 1.dx = x + c
iii. k.dx = kx + c (k R)
xn1
expressed symbolically as -
zf (x) dx (x)
iv. xn dx =
n 1
+ c (n –1)
v. z1 dx = log
x + c
Thus x e
vi. ex dx = ex + c
ax
The process of finding the integral of a function is called Integration and the given function is
vii. ax dx =
loge
a + c = ax loga e + c
called Integrand. Now, it is obvious that the operation of integration is inverse operation of differentiation. Hence integral of a function is also named as anti-derivative of that function.
Further we observe that-
viii. sin x dx = – cos x + c
ix. cos x dx = sin x + c
x. tan x dx = log sec x + c = – log cos x + c
d (x2 )
dx
2 x
xi. cot x dx = log sin x + c
d (x2 2) 2xV| 2xdx x2 constant
xii. sec x dx = log(secx + tanx) + c
dx = – log (sec x –tan x) + c
d 2
dx (x k) 2x|
= log tan
FGH xIJ+ c
So we always add a constant to the integral of function, which is called the constant of
xiii. cosec x dx = – log (cosec x + cot x) + c
Integration. It is generally denoted by c. Due to presence of this constant such an integral is called an Indefinite integral.
= log (cosec x – cot x) + c = log tan
xiv. sec x tan x dx = sec x + c
FGHxIJK+ c
If f(x), g(x) are two functions of a variable x and k is a constant, then-
(i) k f(x) dx = k f(x) dx.
(ii) [f(x) g(x)] dx = f(x)dx ± g(x) dx
(iii) d/dx ( f(x) dx) = f(x)
(iv) f(x)KJdx = f(x)
The following integrals are directly obtained from the derivatives of standard functions.
xv. cosec x cot x dx = – cosec x + c
xvi. sec2 x dx = tan x + c
xvii. cosec2 x dx = – cot x + c xviii. sinh x dx = cosh x + c
xix. cosh x dx = sinh x + c
xx. sech2 x dx = tanh x + c
xxi. cosech2 x dx = – coth x + c
xxii. sech x tanh x dx = – sech x + c
xxiii. cosech x coth x = – cosech x + c
1 1
FxI
eax
R 1FbI
xxiv. xxiv.
x2 + a2 dx =
a tan–1
GHa + c
= a2 b2
sin
STbx tan
GHaJK+ c
xxv. z 1
1
dx = log
FGx a + c
xxxv. zeax cos bx dx
x2 a2
2 a Hx aK
eax
xxvi. z 1
dx = 1 log FGa xIJ + c
= a2 b2
(a cos bx + b sin bx) + c
a2 x2
1
2 a Ha xK
FxI
= cos
STbx tan
1 b V+ c
xxvii. za2 x2 dx = sin–1
GHaJK+ c
FxI
Examples Integration of Function
xxviii. xxviii.
= – cos–1
1
dx = sinh–1
x2 a2
GHaJK+ c
FGxIJ+ c
Ex.1 Evaluate : zx–55 dx
Sol. x–55 dx
x54
= log (x +
) + c
= 54
+ c Ans.
xxix. z 1
dx = cosh–1
FGxIJ+ c
Ex.2 Evaluate :
zex2 1j2
x2 a2
= log (x +
HaK
) + c
Sol.
x
x4 2 x2 1
dx
x
xxx. xxx.
2 2 dx
= zx3 2x 1IJdx
za x
H xK
x4
= x +
2
a . sin–1
2
x + c
a
The document discusses trigonometric functions of angles. It defines the six trigonometric functions (sine, cosine, tangent, cotangent, secant and cosecant) in terms of positions in the Cartesian plane. It also discusses how the values of the trigonometric functions change for angles in different quadrants, and how to find reference angles. Examples are provided to demonstrate evaluating trigonometric functions using reference angles and special angle identities.
The document provides information about an engineering mathematics examination that will take place. It consists of 5 modules with multiple choice and long answer questions in each module. The exam will last 3 hours and students must answer 5 full questions by selecting at least 2 questions from each part. The document then lists the questions under each module.
1. The document provides examples of constructing influence lines for statically determinate beams and trusses. It defines influence lines and shows how to determine the influence line for reactions, shear, and bending moment at various points.
2. Example problems are worked out step-by-step to show how to construct influence lines for a simple beam and a beam with a hinge support. The influence lines provide the response of the structure due to a moving unit load.
3. Equilibrium equations are also used to determine influence lines by relating reactions, shears and moments. General expressions for shear and moment are developed for a beam with multiple spans.
1. The document provides examples of constructing influence lines for statically determinate beams and trusses. It defines influence lines and shows how to determine the influence line for reactions, shear, and bending moment at various points.
2. Example problems are worked out step-by-step to show how to construct influence lines for a simple beam and a beam with a hinge support. The influence lines provide the response of the structure due to a moving unit load.
3. Equilibrium equations are also used to determine influence lines by relating reactions, shears and moments. General expressions for shear and bending moment over a beam with multiple spans are presented.
Hand book of Howard Anton calculus exercises 8th editionPriSim
The document contains the table of contents for a calculus textbook. It lists 17 chapters covering topics such as functions, limits, derivatives, integrals, vector calculus, and applications of calculus. It also includes 6 appendices reviewing concepts in real numbers, trigonometry, coordinate planes, and polynomial equations.
Bat algorithm explained. slides ppt pptxMahdi Atawneh
[Important]
Some numbers in the example are not correct ( in iteration 3 and later), I used them to clarify the idea only.
For people who asked me about the random number that appears in the slide:
Overview:
As described in the paper and pseudo code.
We have two important variables ( ri,Ai) for each bat, these variables will be used to evaluate the bats( solutions).
When a bat becomes near the goal, “ri” value will be increased, and “Ai” will be decreased.
*** About the Random variable:
At each iteration,
- The algorithm will have the solutions population ( assume we have 10 bats ), these solutions(bats) values are near each other.
- To prevent the algorithm from falling at local minima, the algorithm at each iteration will generate a random solution (bat) to explore, this could in some cases jump to a new solution that is near the goal.
- So in the slides, the “rand” means the random solution. We will compare it to all other solutions. If the random solution “ri” value is the height we will put this bat in the best solutions array.
Bat algorithm
download the Powerpoint file pptx with animations
https://docs.google.com/presentation/d/0Bxij58M-C_RgY2gxOEFHSlZzWHM/edit?usp=sharing&ouid=117863559816378751483&resourcekey=0-94EJhpYOuJtlSGiJlRH3jQ&rtpof=true&sd=true
The original paper: https://www.researchgate.net/publication/45913690_A_New_Metaheuristic_Bat-Inspired_Algorithm
Hidden Markov models can be used to model sequential data and detect patterns. The document describes an HMM to detect CpG islands in DNA sequences. It has two states, "CpG island" and "not CpG island". Transition and emission probabilities are estimated from training data. The Viterbi, forward-backward, and Baum-Welch algorithms are used to find the most likely state sequence and re-estimate parameters when the true state sequence is unknown. The model can be extended to higher-order HMMs and different state duration distributions.
This document contains a chapter from an instructor's resource manual that reviews concepts related to rational numbers, dense sets, theorems, and problem sets involving algebraic expressions and operations with rational numbers. It provides examples and explanations of key concepts as well as worked problems and solutions.
This document contains a chapter from an instructor's resource manual that reviews concepts related to rational numbers, dense sets, theorems, and problem sets involving algebraic expressions and operations with rational numbers. It provides examples and explanations of key concepts as well as worked problems and solutions.
This document contains information about a computer aided engineering drawing examination, including instructions, questions, and diagrams. Question 1 involves drawing projections of points and lines. Question 2 involves drawing projections of hexagonal and frustum pyramids. Question 3 involves drawing isometric projections of a pentagonal pyramid or reducing a frustum of a square pyramid to development of its lateral surfaces. The examination tests skills in technical drawing, geometry, and spatial visualization.
Influence line for determinate structure(with detailed calculation)Md. Ragib Nur Alam
Influence Line of determinate beams and frames( Various types) are drawn using Brute force method with detailed calculation. Professor Dr. Tarif Uddin Ahmed, Dept. of CE, RUET asked us to solve 23 different sets of problems. I made a solution of these problems using Autocad by myself with all details that can be possibly shown. - Md. Ragib Nur Alam, CE -13, RUET. Copyright reserved.
The document provides a trigonometry diagnostic exam with 4 problems:
1) Find trig functions if sinθ = 3/5
2) Find trig functions if secM = 6/5
3) Find 6 trig functions of angle P
4) Solve a trig expression given sin, tan, cos values
The problems require finding trig functions based on a given value, expressing answers in simplest form. Students have 10 minutes to complete the problems.
This document contains a math lesson on summations. It provides formulas for calculating the sums of sequential integers from 1 to n, odd integers from 1 to 2n-1, and even integers from 2 to 2n. Several practice problems are worked through applying these formulas to calculate sums such as S = 1 + 2 + 3 + ... + 57 and S = 2 + 4 + 6 + ... + 222. The solutions are provided after each problem.
This document discusses trigonometric ratios and identities. It begins by defining angles, their measurement in different systems including degrees, radians and grades. It then defines trigonometric functions including sine, cosine, tangent etc and discusses their domains, ranges and signs in different quadrants. The document also covers trigonometric identities, ratios of compound angles and periodicity of trig functions.
This document contains the analysis of the forces in the reinforcing bars of several concrete beam structures. It determines the forces in each bar and whether they are in tension or compression. The analysis involves calculating the forces at each node by applying equations of equilibrium for the sum of forces in the x- and y- directions. The forces are then determined for each bar connected to that node. This is done for several nodes throughout the beams.
This document summarizes research on defining and determining the properties of the human sleep homeostat. It discusses how slow wave activity (SWA) declines over the course of sleep and shows a rebound after extended wakefulness, supporting the concept of sleep homeostasis. It describes Achermann's elaboration of the two-process model, where the homeostatic process S is a separate regulatory process reciprocally related to SWA. The document also notes that SWA regulation varies across brain regions and is less efficient after sleep loss, implying SWA may have an upper threshold or be spread over multiple sleep cycles under strain.
College algebra real mathematics real people 7th edition larson solutions manualJohnstonTBL
This document contains information about the College Algebra Real Mathematics Real People 7th Edition Larson textbook including:
- A link to download the solutions manual and test bank for the textbook
- An overview of the content covered in Chapter 2 on solving equations and inequalities, including linear equations, identities, conditionals, and more.
- 51 example problems from Chapter 2 with step-by-step solutions.
This document discusses quadratic functions and their graphs. It begins by defining the general form of a quadratic function as f(x) = ax2 + bx + c, where a ≠ 0. It then explains how to identify the shape of a quadratic graph based on the sign of a, whether it is positive or negative. Examples are provided to show how to sketch graphs, find maximum and minimum values, axes of symmetry, and zeros. The document also covers using the discriminant to determine the number and type of roots, and completing the square to find the vertex of a quadratic function.
Integration is a reverse process of differentiation. The integral or primitive of a function f(x) with
respect to x is that function (x) whose derivative with respect to x is the given function f(x). It is
i. 0. dx = c
ii. 1.dx = x + c
iii. k.dx = kx + c (k R)
xn1
expressed symbolically as -
zf (x) dx (x)
iv. xn dx =
n 1
+ c (n –1)
v. z1 dx = log
x + c
Thus x e
vi. ex dx = ex + c
ax
The process of finding the integral of a function is called Integration and the given function is
vii. ax dx =
loge
a + c = ax loga e + c
called Integrand. Now, it is obvious that the operation of integration is inverse operation of differentiation. Hence integral of a function is also named as anti-derivative of that function.
Further we observe that-
viii. sin x dx = – cos x + c
ix. cos x dx = sin x + c
x. tan x dx = log sec x + c = – log cos x + c
d (x2 )
dx
2 x
xi. cot x dx = log sin x + c
d (x2 2) 2xV| 2xdx x2 constant
xii. sec x dx = log(secx + tanx) + c
dx = – log (sec x –tan x) + c
d 2
dx (x k) 2x|
= log tan
FGH xIJ+ c
So we always add a constant to the integral of function, which is called the constant of
xiii. cosec x dx = – log (cosec x + cot x) + c
Integration. It is generally denoted by c. Due to presence of this constant such an integral is called an Indefinite integral.
= log (cosec x – cot x) + c = log tan
xiv. sec x tan x dx = sec x + c
FGHxIJK+ c
If f(x), g(x) are two functions of a variable x and k is a constant, then-
(i) k f(x) dx = k f(x) dx.
(ii) [f(x) g(x)] dx = f(x)dx ± g(x) dx
(iii) d/dx ( f(x) dx) = f(x)
(iv) f(x)KJdx = f(x)
The following integrals are directly obtained from the derivatives of standard functions.
xv. cosec x cot x dx = – cosec x + c
xvi. sec2 x dx = tan x + c
xvii. cosec2 x dx = – cot x + c xviii. sinh x dx = cosh x + c
xix. cosh x dx = sinh x + c
xx. sech2 x dx = tanh x + c
xxi. cosech2 x dx = – coth x + c
xxii. sech x tanh x dx = – sech x + c
xxiii. cosech x coth x = – cosech x + c
1 1
FxI
eax
R 1FbI
xxiv. xxiv.
x2 + a2 dx =
a tan–1
GHa + c
= a2 b2
sin
STbx tan
GHaJK+ c
xxv. z 1
1
dx = log
FGx a + c
xxxv. zeax cos bx dx
x2 a2
2 a Hx aK
eax
xxvi. z 1
dx = 1 log FGa xIJ + c
= a2 b2
(a cos bx + b sin bx) + c
a2 x2
1
2 a Ha xK
FxI
= cos
STbx tan
1 b V+ c
xxvii. za2 x2 dx = sin–1
GHaJK+ c
FxI
Examples Integration of Function
xxviii. xxviii.
= – cos–1
1
dx = sinh–1
x2 a2
GHaJK+ c
FGxIJ+ c
Ex.1 Evaluate : zx–55 dx
Sol. x–55 dx
x54
= log (x +
) + c
= 54
+ c Ans.
xxix. z 1
dx = cosh–1
FGxIJ+ c
Ex.2 Evaluate :
zex2 1j2
x2 a2
= log (x +
HaK
) + c
Sol.
x
x4 2 x2 1
dx
x
xxx. xxx.
2 2 dx
= zx3 2x 1IJdx
za x
H xK
x4
= x +
2
a . sin–1
2
x + c
a
The document discusses trigonometric functions of angles. It defines the six trigonometric functions (sine, cosine, tangent, cotangent, secant and cosecant) in terms of positions in the Cartesian plane. It also discusses how the values of the trigonometric functions change for angles in different quadrants, and how to find reference angles. Examples are provided to demonstrate evaluating trigonometric functions using reference angles and special angle identities.
The document provides information about an engineering mathematics examination that will take place. It consists of 5 modules with multiple choice and long answer questions in each module. The exam will last 3 hours and students must answer 5 full questions by selecting at least 2 questions from each part. The document then lists the questions under each module.
1. The document provides examples of constructing influence lines for statically determinate beams and trusses. It defines influence lines and shows how to determine the influence line for reactions, shear, and bending moment at various points.
2. Example problems are worked out step-by-step to show how to construct influence lines for a simple beam and a beam with a hinge support. The influence lines provide the response of the structure due to a moving unit load.
3. Equilibrium equations are also used to determine influence lines by relating reactions, shears and moments. General expressions for shear and moment are developed for a beam with multiple spans.
1. The document provides examples of constructing influence lines for statically determinate beams and trusses. It defines influence lines and shows how to determine the influence line for reactions, shear, and bending moment at various points.
2. Example problems are worked out step-by-step to show how to construct influence lines for a simple beam and a beam with a hinge support. The influence lines provide the response of the structure due to a moving unit load.
3. Equilibrium equations are also used to determine influence lines by relating reactions, shears and moments. General expressions for shear and bending moment over a beam with multiple spans are presented.
Hand book of Howard Anton calculus exercises 8th editionPriSim
The document contains the table of contents for a calculus textbook. It lists 17 chapters covering topics such as functions, limits, derivatives, integrals, vector calculus, and applications of calculus. It also includes 6 appendices reviewing concepts in real numbers, trigonometry, coordinate planes, and polynomial equations.
Bat algorithm explained. slides ppt pptxMahdi Atawneh
[Important]
Some numbers in the example are not correct ( in iteration 3 and later), I used them to clarify the idea only.
For people who asked me about the random number that appears in the slide:
Overview:
As described in the paper and pseudo code.
We have two important variables ( ri,Ai) for each bat, these variables will be used to evaluate the bats( solutions).
When a bat becomes near the goal, “ri” value will be increased, and “Ai” will be decreased.
*** About the Random variable:
At each iteration,
- The algorithm will have the solutions population ( assume we have 10 bats ), these solutions(bats) values are near each other.
- To prevent the algorithm from falling at local minima, the algorithm at each iteration will generate a random solution (bat) to explore, this could in some cases jump to a new solution that is near the goal.
- So in the slides, the “rand” means the random solution. We will compare it to all other solutions. If the random solution “ri” value is the height we will put this bat in the best solutions array.
Bat algorithm
download the Powerpoint file pptx with animations
https://docs.google.com/presentation/d/0Bxij58M-C_RgY2gxOEFHSlZzWHM/edit?usp=sharing&ouid=117863559816378751483&resourcekey=0-94EJhpYOuJtlSGiJlRH3jQ&rtpof=true&sd=true
The original paper: https://www.researchgate.net/publication/45913690_A_New_Metaheuristic_Bat-Inspired_Algorithm
Hidden Markov models can be used to model sequential data and detect patterns. The document describes an HMM to detect CpG islands in DNA sequences. It has two states, "CpG island" and "not CpG island". Transition and emission probabilities are estimated from training data. The Viterbi, forward-backward, and Baum-Welch algorithms are used to find the most likely state sequence and re-estimate parameters when the true state sequence is unknown. The model can be extended to higher-order HMMs and different state duration distributions.
This document contains a chapter from an instructor's resource manual that reviews concepts related to rational numbers, dense sets, theorems, and problem sets involving algebraic expressions and operations with rational numbers. It provides examples and explanations of key concepts as well as worked problems and solutions.
This document contains a chapter from an instructor's resource manual that reviews concepts related to rational numbers, dense sets, theorems, and problem sets involving algebraic expressions and operations with rational numbers. It provides examples and explanations of key concepts as well as worked problems and solutions.
This document contains information about a computer aided engineering drawing examination, including instructions, questions, and diagrams. Question 1 involves drawing projections of points and lines. Question 2 involves drawing projections of hexagonal and frustum pyramids. Question 3 involves drawing isometric projections of a pentagonal pyramid or reducing a frustum of a square pyramid to development of its lateral surfaces. The examination tests skills in technical drawing, geometry, and spatial visualization.
Influence line for determinate structure(with detailed calculation)Md. Ragib Nur Alam
Influence Line of determinate beams and frames( Various types) are drawn using Brute force method with detailed calculation. Professor Dr. Tarif Uddin Ahmed, Dept. of CE, RUET asked us to solve 23 different sets of problems. I made a solution of these problems using Autocad by myself with all details that can be possibly shown. - Md. Ragib Nur Alam, CE -13, RUET. Copyright reserved.
The document provides a trigonometry diagnostic exam with 4 problems:
1) Find trig functions if sinθ = 3/5
2) Find trig functions if secM = 6/5
3) Find 6 trig functions of angle P
4) Solve a trig expression given sin, tan, cos values
The problems require finding trig functions based on a given value, expressing answers in simplest form. Students have 10 minutes to complete the problems.
This document contains a math lesson on summations. It provides formulas for calculating the sums of sequential integers from 1 to n, odd integers from 1 to 2n-1, and even integers from 2 to 2n. Several practice problems are worked through applying these formulas to calculate sums such as S = 1 + 2 + 3 + ... + 57 and S = 2 + 4 + 6 + ... + 222. The solutions are provided after each problem.
This document discusses trigonometric ratios and identities. It begins by defining angles, their measurement in different systems including degrees, radians and grades. It then defines trigonometric functions including sine, cosine, tangent etc and discusses their domains, ranges and signs in different quadrants. The document also covers trigonometric identities, ratios of compound angles and periodicity of trig functions.
This document contains the analysis of the forces in the reinforcing bars of several concrete beam structures. It determines the forces in each bar and whether they are in tension or compression. The analysis involves calculating the forces at each node by applying equations of equilibrium for the sum of forces in the x- and y- directions. The forces are then determined for each bar connected to that node. This is done for several nodes throughout the beams.
This document summarizes research on defining and determining the properties of the human sleep homeostat. It discusses how slow wave activity (SWA) declines over the course of sleep and shows a rebound after extended wakefulness, supporting the concept of sleep homeostasis. It describes Achermann's elaboration of the two-process model, where the homeostatic process S is a separate regulatory process reciprocally related to SWA. The document also notes that SWA regulation varies across brain regions and is less efficient after sleep loss, implying SWA may have an upper threshold or be spread over multiple sleep cycles under strain.
College algebra real mathematics real people 7th edition larson solutions manualJohnstonTBL
This document contains information about the College Algebra Real Mathematics Real People 7th Edition Larson textbook including:
- A link to download the solutions manual and test bank for the textbook
- An overview of the content covered in Chapter 2 on solving equations and inequalities, including linear equations, identities, conditionals, and more.
- 51 example problems from Chapter 2 with step-by-step solutions.
This document discusses quadratic functions and their graphs. It begins by defining the general form of a quadratic function as f(x) = ax2 + bx + c, where a ≠ 0. It then explains how to identify the shape of a quadratic graph based on the sign of a, whether it is positive or negative. Examples are provided to show how to sketch graphs, find maximum and minimum values, axes of symmetry, and zeros. The document also covers using the discriminant to determine the number and type of roots, and completing the square to find the vertex of a quadratic function.
Similar to MOSFET Capacitance Simulation(16FEB2012) (20)
Update 22 models(Schottky Rectifier ) in SPICE PARK(APR2024)Tsuyoshi Horigome
This document provides an inventory update of 6,747 parts at Spice Park as of April 2024. It lists the part numbers, manufacturers, and quantities of various semiconductor components, including 1,697 Schottky rectifier diodes from 29 different manufacturers. It also includes details on passive components, batteries, mechanical parts, motors, and lamps in the inventory.
The document provides an inventory update from April 2024 of the Spice Park collection which contains 6,747 electronic components. It includes tables listing the types of semiconductor components, passive parts, batteries, mechanical parts, motors, and lamps in the collection along with their manufacturer and quantities. One of the semiconductor components, the general purpose rectifier diode, is broken down into a more detailed table with 116 entries providing part numbers, manufacturers, thermal ratings, and remarks.
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The document provides an inventory update from March 2024 of parts in the Spice Park warehouse. It lists 6,725 total parts across various categories including semiconductors, passive parts, batteries, mechanical parts, motors, and lamps. The semiconductor section lists 652 general purpose rectifier diodes from 18 different manufacturers with quantities ranging from 2 to 145 pieces.
This document provides an inventory list of parts at Spice Park as of March 2024. It contains 3 sections - Semiconductor parts (diodes, transistors, ICs etc.), Passive parts (capacitors, resistors etc.), and Battery parts. For Semiconductor parts, it lists 36 different part types and provides the quantity of each part. It then provides further details of Diode/General Purpose Rectifiers, listing the manufacturer and quantity of 652 individual part numbers.
Update 29 models(Solar cell) in SPICE PARK(FEB2024)Tsuyoshi Horigome
The document provides an inventory update from February 2024 of Spice Park, which contains 6,694 total pieces of electronic components and parts. It lists 36 categories of semiconductor devices, 11 categories of passive parts, 10 types of batteries, 5 mechanical parts, DC motors, lamps, and power supplies. It provides the most detailed listing for solar cells, with 1,003 total pieces from 51 manufacturers listed with part numbers.
The document provides an inventory update from February 2024 of Spice Park, which contains 6,694 electronic components. It lists the components by type (e.g. semiconductor), part number, manufacturer, thermal rating, and quantity on hand. For example, it shows that there are 621 general purpose rectifier diodes from manufacturers such as Fairchild, Fuji, Intersil, Rohm, Shindengen, and Toshiba. The detailed four-page section provides further information on the first item, general purpose rectifier diodes, including 152 individual part numbers and specifications.
This document discusses circuit simulations using LTspice. It describes driving a circuit simulation by inserting a 250 ohm resistor between the output terminals. It also describes simulating a 1 channel bridge circuit where the DUT1 and DUT2 resistors are both set to 100 ohms and the input voltage is set to either 1V or 5V.
This document discusses parametric sweeps of external and internal resistance values Rg for circuit simulation in LTspice. It also references outputting a waveform similar to a report on fall time characteristics for a device modeling report with customer Samsung.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
9. Mesh statistics :
Total grid points = 900
Total no. of elements = 1196
Min grid spacing (um) = 1.7841E-07
Max grid spacing (um) = 5.5372E-01 (r= 3.1036E+06)
Obtuse elements = 0 ( 0.0%)
Material Definitions
Index Name Regions
1 sio2 1
2 silicon 2
Constants :
Boltzmanns k = 8.61700E-05
charge = 1.60200E-19
permittivity = 8.85400E-14
electron mass= 9.10950E-31
Ambient temperature = 300.000
Thermal voltage = 0.025851
Material data
num r-perm Egap Affinity Ec offset Bulk qf k-therm Gen con
1 3.90 9.0000E+00 9.0000E-01 -3.2700E+00 0.0000E+00 2.5000E-01 0.0000E+00
2 11.80 1.1200E+00 4.1700E+00 0.0000E+00 0.0000E+00 1.4500E+00
4.0000E+13
Semiconductor data
num stats ni An** Ap** Nc Nv
10. 2 Boltz 9.963E+09 1.100E+02 3.000E+01 3.200E+19 2.030E+19
num gcb edb gcv eab w2d H-alphn H-alphp
2 2.000E+00 5.000E-02 4.000E+00 4.500E-02 1.000E-03 3.000E-05
2.000E-07
Model flags :
Incomp. ionization = F
Band-gap narrowing = F
SRH recombination =T
Conc-dep lifetime =F
Auger recombination = F
Deep level traps =F
Radiative recomb =F
Impact ionization =F
Band-to-band tunnel = F
Trap-assist tunnel = F
Stimulated emission = F
Carrier-carr. scat. = F
Neutral imp. scat. = F
Ion-impurity scat. = T
Field dep. mobil =T
Gate fld dep mobil = F
Field dep. diff =F
Thermoelectric curr = T
ET ebal formulation = F
Model Types:
mat # II-scat CC-scat Fld mob Vsat Gate mob
11. 2 n Analytic Dorkel Caughey Exponent SGS
p Analytic Dorkel Caughey Power SGS
mat # D(E) Energy Ce(T) BGN
2 n Lincut Const. P Slotboom
p Lincut Const. P Slotboom
Driving forces :
Mobility, parallel field = qfb
Mobility, gate field = exj
Diffusivity = qfb
Impact ionization = eoj
Default low-field mobilities/relax-times, vsat, w-kappa
mat # mobl0 tauw vsat(T0) kappa
2 n 1390. 2.0000E-13 1.0349E+07 1.500
p 470.0 2.0000E-13 8.3700E+06 1.500
Trap level data
mat # Type Et-Ei (eV) tau0 (n) tau0 (p) Ntrap
2 0 0.00 1.000E-09 1.000E-09 0.00
Velocity saturation coefficients
mat # coef 1 coef 2 coef 3 coef 4 coef 5
2 n 2.400E+07 0.800 0.500 0.00 0.00
p 8.370E+06 0.800 -0.520 0.00 0.00
Lattice scat. mobility coefficients
mat # coef 1 coef 2 coef 3 coef 4 coef 5
2 n 1.390E+03 -2.30 0.00 0.00 0.00
p 470. -2.20 0.00 0.00 0.00
12. Ion-impurity mobility coefficients
mat # coef 1 coef 2 coef 3 coef 4 coef 5
2 n 55.2 1.072E+17 0.733 -2.55 -0.570
p 49.7 1.606E+17 0.700 -2.55 -0.570
Field mobility coefficients
mat # coef 1 coef 2 coef 3 coef 4 coef 5
2 n 2.00 0.00 0.00 0.00 0.00
p 1.00 0.00 0.00 0.00 0.00
Field mobility coefficients (cont.)
mat # coef 6 coef 7 coef 8 coef 9 coef 10
2 n 0.00 0.00 0.00 0.00 0.00
p 0.00 0.00 0.00 0.00 0.00
Energy relaxation coefficients
mat # coef 1 coef 2 coef 3 coef 4 coef 5
2 n 1.00 0.00 0.00 0.00 0.00
p 1.00 0.00 0.00 0.00 0.00
Energy relaxation coefficients (cont.)
mat # coef 6 coef 7 coef 8 coef 9 coef 10
2 n 0.00 0.00 0.00 0.00 0.00
p 0.00 0.00 0.00 0.00 0.00
Misc energy trans coefficients
mat # coef 1 coef 2 coef 3 coef 4 coef 5
2 n 0.00 0.00 0.00 0.00 0.00
p 0.00 0.00 0.00 0.00 0.00
22. 2 1 1.2520E-01 R( 1)
1 0 1.1018E-13 1.2136E-19 2.2354E-15 R( 0)
1 1 1.0915E-15 1.1446E-15 1.1015E-15 U( 1)
1 1 1.1031E-13 1.4526E-18 3.4702E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -0.8000 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -2.93067E-31 -5.88191E-22 -5.88191E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 1.47597E-17 0.00000E+00 0.00000E+00
2 -3.51749E-32 0.00000E+00 -5.88191E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for bias point = 0.2000
Total cpu time = 1.4000
Solution for bias:
V1 = -1.0000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 7.0788E-01 R( 0)
1 1 7.6857E+00 U( 1)
1 1 7.3523E-04 R( 1)
1 2% 5.1382E-01 U( 5)
1 2% 1.2416E-04 R( 1)
24. Total cpu time for Newton equation assembly = 0.1333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for bias point = 0.2000
Total cpu time = 1.6000
Solution for bias:
V1 = -1.2000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 7.0527E-01 R( 0)
1 1 7.6742E+00 U( 1)
1 1 4.3991E-04 R( 1)
1 2* 2.9633E-01 U( 4)
1 2* 4.6584E-05 R( 1)
1 3* 3.5949E-02 U( 4)
1 3* 6.1880E-07 R( 1)
1 4* 4.6597E-04 U( 4)
1 4* 1.0771E-10 R( 1)
1 5* 7.8880E-08 U( 4)
1 5* 1.0066E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 9.4764E-15 U( 1)
1 1 1.5812E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 4.2472E-15 U( 1)
1 1 5.9911E-02 R( 1)
2 0 1.0400E-10 R( 0)
2 1 5.4691E-15 U( 1)
2 1 1.4176E-10 R( 1)
2 0 1.0000E+00 R( 0)
25. 2 1 7.3817E-15 U( 1)
2 1 1.4061E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 1.8465E-15 U( 1)
2 1 2.3273E-01 R( 1)
1 0 1.3723E-13 6.7214E-21 3.0250E-15 R( 0)
1 1 1.7757E-15 1.5771E-15 1.3014E-15 U( 1)
1 1 1.3723E-13 7.5624E-20 3.7540E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -1.2000 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.27248E-31 7.48865E-33 -1.19759E-31
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -9.27876E-17 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -1.19759E-31
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for bias point = 0.1667
Total cpu time = 1.7667
Solution for bias:
V1 = -1.4000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 7.0227E-01 R( 0)
27. 1 -1.54142E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -1.16591E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for bias point = 0.2000
Total cpu time = 1.9667
Solution for bias:
V1 = -1.6000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 6.9909E-01 R( 0)
1 1 7.6651E+00 U( 1)
1 1 1.8662E-04 R( 1)
1 2* 9.0573E-02 U( 4)
1 2* 6.1574E-06 R( 1)
1 3* 3.0699E-03 U( 4)
1 3* 7.4800E-09 R( 1)
1 4* 3.5783E-06 U( 4)
1 4* 1.6471E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 8.5614E-15 U( 1)
1 1 1.3943E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 3.3332E-15 U( 1)
1 1 6.7534E-02 R( 1)
2 0 7.3228E-11 R( 0)
2 1 5.0231E-12 U( 1)
28. 2 1 4.1510E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 9.2495E-15 U( 1)
2 1 1.5281E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 3.1629E-15 U( 1)
2 1 2.1855E-01 R( 1)
1 0 9.4211E-14 2.3852E-21 3.6508E-15 R( 0)
1 1 4.6795E-15 4.6948E-15 3.6807E-15 U( 1)
1 1 1.2528E-13 2.7265E-20 3.5087E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -1.6000 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -1.16591E-22 -1.16591E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -2.17538E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -1.16591E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for bias point = 0.2000
Total cpu time = 2.1667
Solution for bias:
V1 = -1.8000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
30. 1 -2.82160E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.0667
Total cpu time for Newton linear solves = 0.1000 ( 0.1000)
Total cpu time for bias point = 0.1667
Total cpu time = 2.3333
Solution for bias:
V1 = -2.0000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 6.9251E-01 R( 0)
1 1 7.6622E+00 U( 1)
1 1 1.3046E-04 R( 1)
1 2* 3.8741E-02 U( 4)
1 2* 1.7349E-06 R( 1)
1 3* 5.5244E-04 U( 4)
1 3* 3.7407E-10 R( 1)
1 4* 1.1859E-07 U( 4)
1 4* 7.6737E-13 R( 1)
1 0 1.0000E+00 R( 0)
1 1 1.0115E-14 U( 1)
1 1 1.6390E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 3.9134E-15 U( 1)
1 1 6.0024E-02 R( 1)
2 0 2.1555E-11 R( 0)
2 1 6.2223E-15 U( 1)
31. 2 1 6.0544E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 8.8694E-15 U( 1)
2 1 1.5096E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 1.6930E-15 U( 1)
2 1 2.4066E-01 R( 1)
1 0 2.1955E-13 1.9879E-21 3.7240E-15 R( 0)
1 1 3.6782E-15 2.0744E-15 2.2446E-15 U( 1)
1 1 1.9654E-13 2.1254E-20 4.9150E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -2.0000 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -3.47583E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for bias point = 0.2000
Total cpu time = 2.5333
Solution for bias:
V1 = -2.2000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
33. 1 -4.13569E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1333
Total cpu time for Newton linear solves = 0.0667 ( 0.0667)
Total cpu time for bias point = 0.2000
Total cpu time = 2.7333
Solution for bias:
V1 = -2.4000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 6.8582E-01 R( 0)
1 1 7.6609E+00 U( 1)
1 1 1.0637E-04 R( 1)
1 2% 2.0816E-02 U( 4)
1 2% 7.4204E-07 R( 1)
1 3* 1.5886E-04 U( 2)
1 3* 4.5621E-11 R( 1)
1 4% 9.9227E-09 U( 3)
1 4% 1.9136E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 8.6235E-15 U( 1)
1 1 1.8438E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 3.6649E-15 U( 1)
1 1 3.8513E-02 R( 1)
2 0 3.9306E-11 R( 0)
2 1 6.5710E-15 U( 1)
34. 2 1 5.3454E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 7.6996E-15 U( 1)
2 1 2.1647E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 2.2120E-15 U( 1)
2 1 1.9207E-01 R( 1)
1 0 2.6767E-13 1.7969E-21 3.4669E-15 R( 0)
1 1 6.7300E-15 3.2849E-15 3.1561E-15 U( 1)
1 1 2.0902E-13 2.0309E-20 7.6267E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -2.4000 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -4.79967E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = 0.0000 ( 0.0000)
Total cpu time for bias point = 0.1667
Total cpu time = 2.9000
Solution for bias:
V1 = -2.6000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
36. 1 -5.46681E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1333
Total cpu time for Newton linear solves = 0.0667 ( 0.0667)
Total cpu time for bias point = 0.2000
Total cpu time = 3.1000
Solution for bias:
V1 = -2.8000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 6.7912E-01 R( 0)
1 1 7.6602E+00 U( 1)
1 1 9.1607E-05 R( 1)
1 2* 1.2839E-02 U( 3)
1 2* 3.9137E-07 R( 1)
1 3* 6.0369E-05 U( 3)
1 3* 9.2254E-12 R( 1)
1 4* 1.4401E-09 U( 4)
1 4* 1.8325E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 7.9934E-15 U( 1)
1 1 1.6456E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 4.6188E-15 U( 1)
1 1 5.9356E-02 R( 1)
2 0 2.9732E-11 R( 0)
2 1 8.0909E-15 U( 1)
37. 2 1 2.3759E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 7.7434E-15 U( 1)
2 1 2.3809E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 1.8422E-15 U( 1)
2 1 2.3869E-01 R( 1)
1 0 1.5211E-13 1.9249E-21 4.4557E-15 R( 0)
1 1 6.9985E-15 2.2901E-15 2.4868E-15 U( 1)
1 1 1.5239E-13 1.8950E-20 9.2082E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -2.8000 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -6.13644E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = -0.0000 ( -0.0000)
Total cpu time for bias point = 0.1667
Total cpu time = 3.2667
Solution for bias:
V1 = -3.0000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
39. 1 -6.80807E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for bias point = 0.2000
Total cpu time = 3.4667
Solution for bias:
V1 = -3.0000000E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 2.4585E-11 R( 0)
1 1 1.9899E-14 U( 1)
1 1 2.4501E-11 R( 1)
1 0 1.0000E+00 R( 0)
1 1 4.5704E-15 U( 1)
1 1 2.7447E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 2.4880E-15 U( 1)
1 1 5.4712E-02 R( 1)
2 0 2.4501E-11 R( 0)
2 1 6.8994E-15 U( 1)
2 1 2.4498E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 5.6458E-15 U( 1)
2 1 2.8232E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 1.1964E-15 U( 1)
40. 2 1 3.0275E-01 R( 1)
1 0 1.7401E-13 1.9661E-21 3.8911E-15 R( 0)
1 1 6.9165E-15 1.7704E-15 2.1586E-15 U( 1)
1 1 1.7401E-13 1.8016E-20 8.0365E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -3.0000 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -6.80807E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1333
Total cpu time for Newton linear solves = 0.0000 ( 0.0000)
Total cpu time for bias point = 0.1667
Total cpu time = 3.6333
Ac analysis :
Ac voltage = 2.585100E-03
Frequency = 1.000000E+00 Hz
Electrode # 1
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 -7.53395E-27 -5.46168E-18
2 2.46273E-18 5.46168E-18 -4.88307E-28 2.20183E-28
Element Total Current Conductance Capacitance
41. (Amps) (Siemens) (Farads)
Y11 -7.53395E-27 -5.46168E-18 -2.91438E-24 -3.36255E-16
Y21 2.46273E-18 5.46168E-18 9.52662E-16 3.36255E-16
Electrode # 2
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 7.53395E-27 5.46168E-18
2 -5.00280E-17 -5.46168E-18 4.88307E-28 -4.47280E-27
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y12 7.53395E-27 5.46168E-18 2.91438E-24 3.36255E-16
Y22 -5.00280E-17 -5.46168E-18 -1.93524E-14 -3.36255E-16
Total cpu time for Newton equation assembly = 0.0333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for ac analysis = 0.0667
Total cpu time = 3.7000
Solution for bias:
V1 = -2.9389345E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 8.3069E-01 R( 0)
1 1 2.3387E+00 U( 1)
1 1 2.8422E-05 R( 1)
42. 1 2* 8.7591E-04 U( 3)
1 2* 7.9229E-09 R( 1)
1 3* 2.7285E-07 U( 3)
1 3* 8.9715E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 1.2870E-14 U( 1)
1 1 1.6740E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 7.4405E-15 U( 1)
1 1 6.5205E-02 R( 1)
2 0 3.3767E-11 R( 0)
2 1 2.7293E-14 U( 1)
2 1 2.6152E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 8.7446E-15 U( 1)
2 1 2.1132E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 2.3424E-15 U( 1)
2 1 3.8155E-01 R( 1)
1 0 1.8015E-13 1.9136E-21 4.8360E-15 R( 0)
1 1 3.6493E-15 1.9591E-15 2.8974E-15 U( 1)
1 1 2.0801E-13 1.7985E-20 8.6538E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -2.9389 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -6.60281E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = -0.0000 ( -0.0000)
43. Total cpu time for bias point = 0.1667
Total cpu time = 3.8667
Ac analysis :
Ac voltage = 2.585100E-03
Frequency = 1.000000E+00 Hz
Electrode # 1
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 -7.52269E-27 -5.45748E-18
2 3.46230E-18 5.45748E-18 -4.87932E-28 3.09550E-28
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y11 -7.52269E-27 -5.45748E-18 -2.91002E-24 -3.35997E-16
Y21 3.46230E-18 5.45748E-18 1.33933E-15 3.35997E-16
Electrode # 2
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 7.52269E-27 5.45748E-18
2 -1.91631E-17 -5.45748E-18 4.87932E-28 -1.71329E-27
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y12 7.52269E-27 5.45748E-18 2.91002E-24 3.35997E-16
Y22 -1.91631E-17 -5.45748E-18 -7.41290E-15 -3.35997E-16
44. Total cpu time for Newton equation assembly = 0.0333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for ac analysis = 0.0667
Total cpu time = 3.9333
Solution for bias:
V1 = -2.8778690E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 8.2687E-01 R( 0)
1 1 2.3387E+00 U( 1)
1 1 2.8670E-05 R( 1)
1 2* 9.2805E-04 U( 3)
1 2* 8.4590E-09 R( 1)
1 3* 3.0596E-07 U( 3)
1 3* 8.3324E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 1.0464E-14 U( 1)
1 1 1.6061E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 6.3595E-15 U( 1)
1 1 5.4065E-02 R( 1)
2 0 3.2516E-11 R( 0)
2 1 4.3515E-14 U( 1)
2 1 4.7055E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 7.6370E-15 U( 1)
2 1 2.0200E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 1.3495E-15 U( 1)
45. 2 1 1.9959E-01 R( 1)
1 0 3.1408E-13 1.9924E-21 3.5815E-15 R( 0)
1 1 7.4053E-15 3.0611E-15 3.5880E-15 U( 1)
1 1 3.1490E-13 1.9027E-20 7.7703E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -2.8779 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -6.39772E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for bias point = 0.1667
Total cpu time = 4.1000
Ac analysis :
Ac voltage = 2.585100E-03
Frequency = 1.000000E+00 Hz
Electrode # 1
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 -7.51076E-27 -5.45304E-18
2 3.23867E-18 5.45304E-18 -4.87534E-28 2.89557E-28
Element Total Current Conductance Capacitance
46. (Amps) (Siemens) (Farads)
Y11 -7.51076E-27 -5.45304E-18 -2.90540E-24 -3.35723E-16
Y21 3.23867E-18 5.45304E-18 1.25282E-15 3.35723E-16
Electrode # 2
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 7.51076E-27 5.45304E-18
2 3.34473E-17 -5.45304E-18 4.87534E-28 2.99039E-27
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y12 7.51076E-27 5.45304E-18 2.90540E-24 3.35723E-16
Y22 3.34473E-17 -5.45304E-18 1.29385E-14 -3.35723E-16
Total cpu time for Newton equation assembly = 0.0333
Total cpu time for Newton linear solves = -0.0000 ( -0.0000)
Total cpu time for ac analysis = 0.0667
Total cpu time = 4.1667
Solution for bias:
V1 = -2.8168034E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 8.2304E-01 R( 0)
1 1 2.3388E+00 U( 1)
1 1 2.8930E-05 R( 1)
47. 1 2* 9.8491E-04 U( 3)
1 2* 9.0491E-09 R( 1)
1 3* 3.4420E-07 U( 3)
1 3* 8.5359E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 8.6584E-15 U( 1)
1 1 1.7014E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 4.5488E-15 U( 1)
1 1 4.6070E-02 R( 1)
2 0 3.4573E-11 R( 0)
2 1 4.9783E-14 U( 1)
2 1 2.0745E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 7.4241E-15 U( 1)
2 1 2.0190E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 2.4151E-15 U( 1)
2 1 3.2410E-01 R( 1)
1 0 1.3403E-13 1.9469E-21 5.2241E-15 R( 0)
1 1 6.9269E-15 2.6462E-15 4.4503E-15 U( 1)
1 1 1.4196E-13 2.0184E-20 7.8751E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -2.8168 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -6.19280E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = -0.0000 ( -0.0000)
48. Total cpu time for bias point = 0.1667
Total cpu time = 4.3333
Ac analysis :
Ac voltage = 2.585100E-03
Frequency = 1.000000E+00 Hz
Electrode # 1
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 -7.49810E-27 -5.44832E-18
2 3.65049E-18 5.44832E-18 -4.87112E-28 3.26376E-28
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y11 -7.49810E-27 -5.44832E-18 -2.90051E-24 -3.35432E-16
Y21 3.65049E-18 5.44832E-18 1.41213E-15 3.35432E-16
Electrode # 2
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 7.49810E-27 5.44832E-18
2 -1.55270E-17 -5.44832E-18 4.87112E-28 -1.38821E-27
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y12 7.49810E-27 5.44832E-18 2.90051E-24 3.35432E-16
Y22 -1.55270E-17 -5.44832E-18 -6.00636E-15 -3.35432E-16
49. Total cpu time for Newton equation assembly = 0.0333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for ac analysis = 0.0667
Total cpu time = 4.4000
Solution for bias:
V1 = -2.7557379E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 8.1922E-01 R( 0)
1 1 2.3388E+00 U( 1)
1 1 2.9200E-05 R( 1)
1 2* 1.0471E-03 U( 3)
1 2* 9.6999E-09 R( 1)
1 3* 3.8853E-07 U( 3)
1 3* 5.1351E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 9.1257E-15 U( 1)
1 1 1.9346E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 4.8432E-15 U( 1)
1 1 7.1527E-02 R( 1)
2 0 2.1610E-11 R( 0)
2 1 5.9003E-14 U( 1)
2 1 2.1515E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 8.7210E-15 U( 1)
2 1 2.1472E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 1.1421E-15 U( 1)
50. 2 1 2.0638E-01 R( 1)
1 0 1.3441E-13 1.7327E-21 3.7783E-15 R( 0)
1 1 5.1811E-15 2.6836E-15 2.3482E-15 U( 1)
1 1 1.3438E-13 1.9465E-20 7.5747E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -2.7557 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -5.98806E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = -0.0000 ( -0.0000)
Total cpu time for bias point = 0.1667
Total cpu time = 4.5667
Ac analysis :
Ac voltage = 2.585100E-03
Frequency = 1.000000E+00 Hz
Electrode # 1
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 -7.48466E-27 -5.44329E-18
2 2.91127E-18 5.44329E-18 -4.86663E-28 2.60285E-28
Element Total Current Conductance Capacitance
51. (Amps) (Siemens) (Farads)
Y11 -7.48466E-27 -5.44329E-18 -2.89531E-24 -3.35123E-16
Y21 2.91127E-18 5.44329E-18 1.12617E-15 3.35123E-16
Electrode # 2
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 7.48466E-27 5.44329E-18
2 -3.94305E-18 -5.44329E-18 4.86663E-28 -3.52533E-28
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y12 7.48466E-27 5.44329E-18 2.89531E-24 3.35123E-16
Y22 -3.94305E-18 -5.44329E-18 -1.52530E-15 -3.35123E-16
Total cpu time for Newton equation assembly = 0.0333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for ac analysis = 0.0667
Total cpu time = 4.6333
Solution for bias:
V1 = -2.6946724E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 8.1541E-01 R( 0)
1 1 2.3388E+00 U( 1)
1 1 2.9483E-05 R( 1)
52. 1 2* 1.1152E-03 U( 3)
1 2* 1.0420E-08 R( 1)
1 3* 4.4014E-07 U( 3)
1 3* 5.1483E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 9.8557E-15 U( 1)
1 1 1.9486E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 5.8186E-15 U( 1)
1 1 5.7035E-02 R( 1)
2 0 2.2537E-11 R( 0)
2 1 8.0990E-14 U( 1)
2 1 4.9760E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 8.7428E-15 U( 1)
2 1 1.9264E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 2.2097E-15 U( 1)
2 1 1.8849E-01 R( 1)
1 0 3.0025E-13 1.8464E-21 3.8313E-15 R( 0)
1 1 7.1379E-15 3.1978E-15 2.4370E-15 U( 1)
1 1 3.4515E-13 1.9118E-20 7.7212E-14 R( 1)
Electrode Voltage Electron Current Hole Current Conduction Current
(Volts) (Amps) (Amps) (Amps)
1 -2.6947 0.00000E+00 0.00000E+00 0.00000E+00
2 0.0000 -1.67168E-31 -2.33182E-22 -2.33182E-22
Electrode Flux Displacement Current Total Current
(Coul) (Amps) (Amps)
1 -5.78351E-16 0.00000E+00 0.00000E+00
2 -1.51177E-32 0.00000E+00 -2.33182E-22
Convergence criterion completely met
Total cpu time for Newton equation assembly = 0.1667
Total cpu time for Newton linear solves = -0.0000 ( -0.0000)
53. Total cpu time for bias point = 0.1667
Total cpu time = 4.8000
Ac analysis :
Ac voltage = 2.585100E-03
Frequency = 1.000000E+00 Hz
Electrode # 1
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 -7.47034E-27 -5.43795E-18
2 2.84201E-18 5.43795E-18 -4.86185E-28 2.54093E-28
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y11 -7.47034E-27 -5.43795E-18 -2.88977E-24 -3.34794E-16
Y21 2.84201E-18 5.43795E-18 1.09938E-15 3.34794E-16
Electrode # 2
Electrode Conduction Current Displacement Current
(Amps) (Amps)
1 -0.00000E+00 -0.00000E+00 7.47034E-27 5.43795E-18
2 2.08364E-18 -5.43795E-18 4.86185E-28 1.86289E-28
Element Total Current Conductance Capacitance
(Amps) (Siemens) (Farads)
Y12 7.47034E-27 5.43795E-18 2.88977E-24 3.34794E-16
Y22 2.08364E-18 -5.43795E-18 8.06019E-16 -3.34794E-16
54. Total cpu time for Newton equation assembly = 0.0333
Total cpu time for Newton linear solves = 0.0333 ( 0.0333)
Total cpu time for ac analysis = 0.0667
Total cpu time = 4.8667
Solution for bias:
V1 = -2.6336069E+00 V2 = 0.0000000E+00
Previous solution used as initial guess
o-itr i-itr psi-error n-error p-error
1 0 8.1159E-01 R( 0)
1 1 2.3388E+00 U( 1)
1 1 2.9779E-05 R( 1)
1 2* 1.1900E-03 U( 3)
1 2* 1.1219E-08 R( 1)
1 3* 5.0049E-07 U( 3)
1 3* 6.8101E-12 R( 1)
1 0 1.0000E+00 R( 0)
1 1 1.1173E-14 U( 1)
1 1 2.0680E-02 R( 1)
1 0 1.0000E+00 R( 0)
1 1 5.6334E-15 U( 1)
1 1 4.6519E-02 R( 1)
2 0 3.1048E-11 R( 0)
2 1 9.7343E-14 U( 1)
2 1 3.4818E-11 R( 1)
2 0 1.0000E+00 R( 0)
2 1 8.1540E-15 U( 1)
2 1 1.6872E-02 R( 1)
2 0 1.0000E+00 R( 0)
2 1 1.9045E-15 U( 1)