User Guide

User Manual:

Open the PDF directly: View PDF .
Page Count: 45

Download
Open PDF In Browser	View PDF

PyVASCO
User guide

Patricia Ribes Metidieri
Ida Aichinger
Christina Yin Vallgren
TE-VSC
CERN - Geneva, Switzerland

Contents
Contents

About PyVASCO
1.1 Getting started . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2 Authors and contributors . . . . . . . . . . . . . . . . . . . . . . .
1.3 Contact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3
3
4
4

Basic concepts
2.1 Motivation and main advantages with respect to VASCO
2.2 Dynamic vacuum model . . . . . . . . . . . . . . . . . . .
2.3 Electron stimulated desorption . . . . . . . . . . . . . . .
2.4 Treatment of cryogenic surfaces . . . . . . . . . . . . . . .

5
5
5
6
9

.
.
.
.

Inputs of PyVASCO
12
3.1 ’Old’ Input format . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.2 ’New’ Input format . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.3 ESD curves format . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Layout and functionality
20
4.1 Menus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.2 Tabs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Extracting results with PyVASCO
39
5.1 Management and plot options . . . . . . . . . . . . . . . . . . . . 39
5.2 Exporting plots in different formats . . . . . . . . . . . . . . . . . 41

Benchmark with VASCO and Molflow+

Bibliography

43
45

Chapter 1
About PyVASCO
PyVASCO (VAcuum Stability COde written in Python) is a code integrally developed at CERN for the simulation of pressure profiles in cylindrical geometries considering beam induced effects.
The first version of this program was distributed under the name IdaVac.
This program constitutes an update of VASCO (presented in [1]) and seeks to
optimize the performance of the original code for large geometries [2].
This program has been integrally developed in Python 2.7 and tested on
Windows 10.

1.1 Getting started
Installation
This version of PyVASCO includes an installer, called ’setup.exe’. In order to
install PyVASCO in your machine, launch the installer and follow the specified instructions. Even if recommended, the installation using the setup is
not compulsory in order to launch PyVASCO. To launch the application without installing, enter in the folder PyVASCO and double-click on the application (’PyVASCO.exe’).

Developer tools
This version of PyVASCO is distributed together with its source code (in PyVASCO/
PyVASCO_Code/) and a portable python interpreter
PyVASCO/WinPython-64bit-2.7.6.4 with all the required dependencies already installed.
There’s also an API documentation available in web format in the directory docs/ under the name ’API.html’ or opening the program and selecting
the option ’Documentation’ in the menu Help or pressing the keyboard key
combination Ctrl+U.
3

CHAPTER 1. ABOUT PYVASCO
To build a stand-alone python application from the source code:

•

Make sure that Pyinstaller is installed in your computer:
– Open a command prompt and type pyinstaller.
– If you don’t have pyinstaller in your computer, in the same command prompt, type:
pip i n s t a l l p y i n s t a l l e r

•

Enter in the directory containing the source code (PyVASCO_Code/) and
open the file ’PyVASCO.spec’. Paste the full path of the location of the
directory PyVASCO_Code in the tag pathex and save the changes.

•

Open a command prompt in this directory and type:
p y i n s t a l l e r PyVASCO . spec

1.2 Authors and contributors
List of authors:

•

Ida Aichinger

•

Patricia Ribes Metidieri

List of contributors:

•

Christina Yin Vallgren

•

Giuseppe Bregliozzi

•

Simone Callegari

1.3 Contact
In case of problems,if a bug is detected or if you have suggestions for further
development, please send an emalil to the following addresses:

•

patricia.ribes.metidieri@cern.ch

Chapter 2
Basic concepts
2.1 Motivation and main advantages with respect
to VASCO
PyVASCO is an upgrade of a preexisting program at CERN: VASCO [1], and
it solves the same vacuum model. Even though this program is not as precise as other simulations tools for ultra high vacuum (UHV) based on Montecarlo techniques, its main advantages to are twofold: first, PyVASCO can
easily simulate several gas species at a time and cross-desorption between
gas species. Second, it solves the vacuum model in Eq. 2.1 analytically, which
allows to simulate large portions of an accelerator in minutes.
The original VASCO, however, didn’t allow for simulations with more than
around 40 segments. The reason is that, in order to solve a system of Nsegments
it holds in memory matrices of dimension 8· Ngas · Nsegments ×8· Ngas · Nsegments .
PyVASCO takes advantage of the sparse structure of the solving matrices to
store the information of the system in arrays of dimension 8 · Ngas · Nsegments ×
17. Thus, the memory storage is reduced from O (N 2 ) to O (N ). This step is
fundamental in order to simulate large geometries.
For more information on the computer implementation of PyVASCO, see
Ref. [2].

2.2 Dynamic vacuum model
PyVASCO uses the same vacuum model as presented in Ref. [1] and, as in Ref.
[1], PyVASCO solves the equations of the model analytically. The purpose of
this section is to give a fast overview of the equations solved by PyVASCO and
to present some of the limitations of this vacuum model.
The model used in PyVASCO assumes the the rate of change of molecules
per unit volume depends uniquely on:
5

CHAPTER 2. BASIC CONCEPTS
• molecular diffusion due to a density gradient;
• beam induced effects such as ion, photon and electron stimulated desorption;
• gas pumping through a distributed pumping (NEG of cryo-pumping)
or through lumped pumps located in the interconnection of segments;
• addition of gas to the system through lumped leaks and through thermal outgassing.

PyVASCO assumes that the simulated vacuum system is made of cylindrical finite elements characterized with constant, time invariant parameters (material properties, radius, pumps...), and it can take into account the
cross- desorption of gas of one specie by ions of other gas species (mu. PyVASCO considers four gas species: H2 , CH4 , CO and CO2 , since these are the
dominant gas species in a backed ultra-high vacuum (UHV) system.
These assumptions allow to solve analytically the stationary equations
presented in 2.1 in 1-dimension.
As presented in Refs. [1] and [2], the main equation governing the stationary behavior of the vector volume density ~
n = (n H2 , nC H4 , nCO , nCO 2 ) is
∂2 ~
n
I
~
~
~
~d i s )~
~
~η i ~
~
~e ) +(2.1)
~
S cr yo (~
n −n
n −~
σi −I ~
n − (~
S w al l + C
n −~
0 =~
c spec 2 +~
σi −I ~
∂x
e
~
~η ph Γ̇ph +~
~η e Ṅe + a ~
qt h
The definition, dimension and units of the quantities in Eq. 2.1 are defined in Tab.

2.3 Electron stimulated desorption
The electron-stimulated desorption (ESD), the desorption process initiated
by electronic excitation, of atoms and molecules is an important factor in
determining the pressure profile under beam induced effects.
In order to empirically characterize this effect for different gases, the socalled ESD yield, η e is defined as:
ηe =

Ni
Ne

(2.2)

where Ni is the number of desorbed molecules of a given gas specie and Ne
is the number of incident electrons.

~e
n
~
~η ph
Γ̇ph
~
~η e
Ṅe
a
~
qt h
I
e

~
~d i s
C
~
~
S cr yo

w al l

~
~
c spec
~η i
~
~
~
σi −I
~
~
S

~
n

A
C

1
m2 s

1
ms

m
-

m2
s
m2
s
m2
s
−3

m−3
m4 /s
m2

4×1
1×1
1×1

Cryogenic pumping due to cryo-condensation, per unit length
Thermal equilibrium density
Photon stimulated desorption yield (diagonal matrix)
Photon flux to the wall per unit length
Electron stimulated desorption yield (diagonal matrix)
Electron flux to the walls per unit length
Surface area per unit length
Thermal outgassing. (The user introduces the thermal outgassing in mbar l/s)
Proton beam current
Charge of the electron

4× 4
4× 1
4× 4
1×1
4×4
1×1

a·v̄ i
4

Distributed pumping through holes per unit length

Distributed pumping speed per unit length due to NEG S iw al l = α(T )

Molecular density of the different gas species
Specific conductance. (Diagonal matrix)
Ion stimulated desorption yield
Ionization cross section of the gas-proton interaction

Definition

4× 4

4×1
4×4
4× 4
4× 4

Magnitude Units Dimension

2.3. ELECTRON STIMULATED DESORPTION
7

Table 2.1: Symbol, units and description of the magnitudes used in PyVASCO’s model.

CHAPTER 2. BASIC CONCEPTS

Figure 2.1: ESD curve for backed copper.

The ESD yields of different gases depend on the properties of the surface
where the molecules of the studied gases are adsorbed, on the temperature
and on gas specie.
The curve representing the ESD yields for a material as a function of the
accumulated electron dose is the ESD curve for that material, and it has been
observed that the ESD yields for different gases on materials relevant for UHV
systems decrease with the accumulation of incident electron dose (in electrons/cm2 ),
as presented in Fig. 2.1 for backed copper.
This phenomenon of decrease of the ESD with the accumulated electron
dose received in the walls is typically called conditioning effect (or scrubbing
effect).
This phenomenon is relevant for the vacuum performance of UHV systems under electron bombardment due to beam induced effects, like the
LHC, which performs dedicated scrubbing runs at the beginning of operation periods [3].

2.4. TREATMENT OF CRYOGENIC SURFACES

Figure 2.2: Equilibrium vapor pressure for different gases relevant in UHV.

2.4 Treatment of cryogenic surfaces
Basics concepts
The molecules of the gas species present in an UHV system mainly interact
with the surfaces of vacuum chambers through van der Waals forces.
The binding energies between the surface and the gas molecules increases
when the temperature of the system decreases, increasing the number of
adsorbed molecules. For sufficiently low temperatures, the surface coverage increases sufficiently for the van der Waals forces to start acting between
the molecules themselves. This regime is called cryocondensation. Once in
the cryocondensation regime at a fixed temperature, a dynamic equilibrium
might be reached between the adsorbed and desorbed molecules of a given
gas specie, which translates to an equilibrium pressure of the gas over its condensed phase, called the equilibrium vapor pressure (Fig. . 2.2).
The sticking coefficient for cryosorption and cryocondensation is defined
as
Number of molecules "sticking" on a surface
α=
(2.3)
Total number of molecules impinging on the surface
The sticking coefficient ignores the effects of the vapor pressure and it is
close to unity at sufficiently low temperatures.
A cold surface acts as a pump with the characteristic pumping speed pre-

CHAPTER 2. BASIC CONCEPTS

sented in Eq. 2.4:
A
v¯i ,
(2.4)
4
where the αi is the sticking coefficient for the gas specie i , A is the area of the
cold surface and v̄ i is the average molecular speed of the gas specie i .
cr yo

= αi

Cryogenic surfaces in PyVASCO
As explained in Sec. 3.2, PyVASCO divides a simulation in a main input describing the geometry and in basic components of a vacuum system, i.e., Materials, Pumps and Gasources. In order to avoid confusion, the properties of
all materials are defined at room temperature and a cryogenic behavior is set
by default. In order to change the cryogenic behavior of a given material, see
...
IMPORTANT!: For temperatures below 100 K, PyVASCO doesn’t consider
thermal outgassing (it is set to zero). However, the value of the thermal outgassing is not changed with temperature. Therefore, in order to simulate a
system at a temperature considerably larger than room temperature, the user
has to modify the outgassing in the definition of the material or to define another material with the correct outgassing for the temperature of interest.
Below 100 K, PyVASCO computes the distributed pumping speed of the
cryogenic surfaces as in Eq. 2.4, using for the sticking factor the corresponding value as a function of the temperature set for the corresponding material
(in ...) . If this information is not provided, the following default options are
assumed:
• The dependence of the sticking factor with temperature for CH4 , CO
and CO2 are assumed to be the step functions presented in Fig.
• At temperatures below 20 K, the values of the sticking factor for H2 as a
function of the temperature are taken from Ref. [4]. Due to the scarce
experimental data concerning the sticking coefficient of H2 on technical surfaces at cryogenic temperatures, the choice of the reference has
been arbitrary.
As can be seen in Eq. , the cryogenic pumping speed used in the vacuum
model implemented in PyVASCO is modulated by the equilibrium density,
n e . This term takes into account the reduction of the efficiency of the cryogenic pumping due to the desorption of molecules from the considered surface. This term also implies that the cryogenic pumping becomes null when

2.4. TREATMENT OF CRYOGENIC SURFACES

Figure 2.3: Default dependence of the sticking coefficient with temperature
at low temperatures.
the computed gas density in the considered segment equals the equilibrium
density for the temperature of the segment.
For a given temperature, PyVASCO estimates the values of the equilibrium density for the considered gas species for using the curves of Fig. 2.2,
truncated at a certain pressure to ensure that n e is always smaller than the
computed density.

Chapter 3
Inputs of PyVASCO
3.1 ’Old’ Input format
As already mentioned, PyVASCO is based in VASCO, thus ’old’ input format
refers to VASCO’s input format, detailed in [1].
To ease the comparison between VASCO and PyVASCO, PyVASCO can accept CSV files written with the format of the first program, as mentioned in
Subsection 4.2 and transform this files to the native format of PyVASCO.

3.2 ’New’ Input format
Writing input simulation files with a large number of segments in VASCO’s
input format might be tedious and the it might be difficult to detect mistakes.
For this reason, PyVASCO uses a new input format, which seeks to make an
input file more readable.
A simulation in PyVASCO is built through a main simulation table plus
three different constituents: Materials, Pumps and Gas sources. These three
components are defined and stored as independent building blocks, making
it possible to reuse them in different simulations.

Main input file
A geometric model in PyVASCO is built by cylindrical segments stuck together. An example of input file with the new format is shown in Tab. 3.1.
Input files in this format can be written using the integrated Input editor (in the menu Add → Input file or by pressing Ctrl+I) or in spreadsheet
programs (like Excel) or in a plain text editor (like WordPad or Notepad). An
example of how a simple input file would look like when using the integrated
editor is shown in Fig. 3.1.
The new input format consists in:
12

3.2. ’NEW’ INPUT FORMAT

Figure 3.1: Input example written in the integrated editor.

Table 3.1: Example of input file written in the ’new’ format.

CHAPTER 3. INPUTS OF PYVASCO

•

Name of the simulation:
The name of the simulation must be written in the dedicated line edit
when using the integrated editor or, when using external editors like
Excel, it must be written in the first row, first column of the input file.

•

Columns, labeled S1 ...SN , for the defined segments:
Each column labeled S1 ...SN in the input file represents a segment in
the simulated geometry. For each segment the following information
has to be provided:
– d[mm]: The diameter of the segment (in mm), assumed to be
cylindrical.
– L[mm]: The length of the segment (in mm).
– T[k]: The average temperature of the segment.
– Material: Name of the material of the segment. The list of registered materials can be visualized in the menu File → Show Components or pressing Ctrl+S. (See Show components in Section 4.1
and Materials in Section 3.2 for more details).
– Pump: The pumps specified in the main input file are lumped
pumps located on the left side of the segment where they are indicated. The list of registered pumps can be visualized in the menu
File → Show Components or pressing Ctrl+S. In order to simulate
the union of two segments without a lumped pump in between,
P0 has to be written in the corresponding cell.
– Gas source: The gas sources in the main input file represent localized leaks in the interconnections between segments and, in particular, located on the left side of the segment where they are indicated.The list of registered pumps can be visualized in the menu
File → Show Components or pressing Ctrl+S. In order indicate to
PyVASCO that no leak exists in a certain location, G0 has to be
written in the corresponding cell.
– Photon flux: PyVASCO accepts an homogeneous, constant photon flux (in photons/m/s) impinging the walls of every segment.
– Electron flux An homogeneous, constant electron flux (in electrons/m/s) can be added to the different simulated segments.

•

End column:
This column is exclusively used to indicate the lumped pump and the
gas source located at the right side of the last simulated segment.

3.2. ’NEW’ INPUT FORMAT

Figure 3.2: 3D model of the simulated geometry presented in Tab. 3.1. (For
aesthetic reasons, the geometry has been shrinked in the longitudinal direction).
Thus, the example of Fig. 3.1 and Tab. 3.1, is composed by 3 copper segments
of the same same length and increasing diameters of 10, 20 and 40 mm, respectively. The three segments are hold at room temperature and two lumped
pumps (called P16) are connected at the beginning of the first segment (left
side) and at the end of the third segment (right side). There are no lumped
pumps connected nor on the right side of the first segment nor on the right
side of the second segment, and there are no leaks along the geometry. A 3D
model of the described system can be seen in Fig. 3.2.
IMPORTANT!: If the user writes the main input in an external editor, the same
format as shown in Tab. 3.1 has to be used. The input file has to be saved in
CSV format.

Materials
The materials used in the main input file for the PyVASCO simulations have
to be defined previously to their usage. PyVASCO offers the possibility of
defining new materials in the dedicated Material editor, but the user can also
import a CSV file with the format shown in Tab. 3.2.
A material file defined in PyVASCO consists in:

•

Name of the material
The name with which this material will be called in the main input files.

CHAPTER 3. INPUTS OF PYVASCO

•

Colums:
A material file always have 4 data columns, corresponding to the behavior of the defined material with respect to the main dominant gases
in UHV, i.e. H2 , CH4 CO and CO2 .

•

Rows:
The different rows specified in the a materials file are:
– alpha: Sticking factor or sticking coefficient (adimensional).This
quantity represents the probability which each of the defined gases
have of sticking onto the surface of the segment. In the case of the
LHC, this parameter is used to represent the pumping due to NEG
in the warm sections and to physisorption (cryopumping) in the
cold sections.
IMPORTANT!: The sticking coefficient defined in this section
is always defined at room temperature! PyVASCO scales the
sticking coefficient with the temperature for the defined cryogenic behavior of the material (See , for more information).
~η I (in molecules/inci– eta_ion: Ion stimulated desorption yields ~
dent ion) at a chosen ion impact energy (4×4 matrix, occupying
from row 2 to row 5).
– eta_e: Electron stimulated desorption yields (in molecules/ incident electron) at a chosen impact energy.
– eta_ph: Photon stimulated desorption yields (in molecules/incident photon) at a chosen photon energy.
– Cbs: distributed pumping speed per unit length (in l· s−1 · m−1 ). In
the case of the LHC, this input parameter can be used to simulate
the pumping through pumping slots.
– Qth_total: Thermal outgassing rate per unit area at a chosen temperature (in mbar·l·s−1 ·cm−2 ).

IMPORTANT!: If the user writes a material file in an external editor (Excel, for
example) the name of the material written in the first row and column of the
material table has to match the name of the file. Moreover, the material file
has to be saved in CSV format.

3.2. ’NEW’ INPUT FORMAT

Table 3.2: Example of defined material in PyVASCO.

IMPORTANT!: All the properties defined for a certain material depend on the
temperature! For this reason it is important to register the same material held
at different temperatures as different entries by including the temperature in
the definition name. For example: use Cu@RT and Cu@5K to define copper
at room temperature and at 5 K, respectively.
IMPORTANT!: The outgassing rate of a given material is internally converted
to total outgassing by multiplying this quantity by the surface area of the
cylindrical segment considered. If you are trying to simulate a geometry
which considerably differs from a cylinder, it might turn out that the real outgassing area is much bigger than the computed area, and you should scale
the outgassing rate accordingly to give the real total outgassing when multiplied by the computed area.

Pumps
The lumped pumps used in the main input file for the PyVASCO simulations
have to be defined previously to their usage. The same pump in PyVASCO can
present different pumping speeds for different pressure ranges. PyVASCO
offers the possibility of defining new pumps in the dedicated Pump editor,
but the user can also import a CSV file with the format shown in Tab. 3.3.
However, in the later case only simple pumps (with pumping speeds for the
different considered gas species independent of the pressure range) can be
defined.
The pumping speed for each of the gas species has to be in l/s.

CHAPTER 3. INPUTS OF PYVASCO

Table 3.3: Example of a defined simple pump in PYVASCO.

Table 3.4: Example of a defined local gas release (gas source) in PyVASCO.

Gas sources
The gas sources used in the main input file for the PyVASCO simulations have
to be defined previously to their usage. PyVASCO offers the possibility of
defining new gas sources in the dedicated Gas source editor, but the user can
also import a CSV file with the format shown in Tab. 3.4.
The gas release for each of the gas species has to be in mbar l/s.

3.3 ESD curves format
In order to easily quantify the impact of the reduction of the ESD yields with
the accumulated electron dose, PyVASCO offers the possibility of solving the
dynamic vacuum model for different accumulated electron doses. (See Dynamic pressure due to ESD in Section 4.2, for more details on the simulation).
The ESD input files for PyVASCO must be CSV files containing 5 columns:

•

The first column must be labeled DOSe/cm2, and contain the accumulated electron dose (in electrons/cm2 ).

•

The second to fifth columns must include the ESD yields of H2 , CH4 ,
CO and CO2 , respectively.
An example of the format for a ESD curve in PyVASCO can be seen in
Tab. 3.5

3.3. ESD CURVES FORMAT

Table 3.5: Example of the format for an ESD curve required by PyVASCO.
IMPORTANT!: In order to properly run this simulation, all the materials used
in the geometry model must have an associated ESD curve. To associate an
ESD curve to a given material, select the option Add → ESD curve in PyVASCO
menus or press Ctrl+D. See ESD curve in Subsection 4.1 for more details on
how to use this option.

Chapter 4
Layout and functionality
4.1 Menus
The current version of PyVASCO (2.0) presents 4 menus, named: File, Add,
Analysis and Help. In this section, a detailed description of the different
menus in PyVASCO and their functionality is provided.

File
The File menu of PyVASCO contains 4 options:

•

Load...:
This option reloads all the registered materials, pumps and gas sources
when selecting it or pressing the keyboard key combination Ctr+L.

•

Properties:
When selected or on pressing the keyboard key combination Ctr+P, this
option will launch the Properties window, shown in Fig. ??. The properties window allows to select the pressure unit (mbar or torr) of the
input. The native pressure unit of PyVASCO is mbar, while the input
pressure unit in VASCO is torr. This option was added in order to ease
the benchmark between both programs.
IMPORTANT! : Please note that changing the pressure unit in the Properties
window won’t change the pressure unit in the output of the simulation (the
results will still be given in mbar). Changing this value will only affect the
interpreted units of all the gas sources and the thermal outgassing and the
linear pumping of all materials.

Add and Edit
The Add menu of PyVASCO contains 5 options:
20

4.1. MENUS

Figure 4.1: Tab 1 of "My Simulations" window.

•

Simulation:
When this option is selected or the keyboard key combination Ctrl+I
is pressed, the My simualtions window will be launched. This window
allows the user to view and edit the preexisting simulations in the first
tab (Fig. 4.1 ) and to write a new input model in the second tab (Fig.
4.2).
a

List of the existing simulations. A single click on a list elements
makes that it appears in the table on the right. A double click on a
name makes it possible to rename a simulation.

Pressing the "button save changes" save the modifications done
in the simulation.

c Table showing the components of the simulation selected on the
right. The elements of the table can be manually edited and the
changes saved by pressing the Save button.

•

Defines the name of the simulation

Simulation components in the ’New format’ (see Section 3.2 for a
detailed explanation).

Allows to add a segment to the model.

Saves the new input under the name specified in a plus the suffix
"_New" .

Material:
When this option is selected or the keyboard key combination Ctrl+M
is pressed, the New Material window is launched. This window allows

CHAPTER 4. LAYOUT AND FUNCTIONALITY

Figure 4.2: Tab 2 of "My Simulations" window.

Figure 4.3: Tab 1 of the "New Material" window
the user to view the preexisting materials and to define a new material.
It contains 2 tabs:
– View and Edit: (Fig. 4.3) with this tab, the user can see all the
defined materials by selecting them in the list on the left, edit their
names by double-clicking them in the list and edit their properties
in the table. To save the changes done in a material, the user has
to press the button "Save changes".
– Write New Material: (Fig. 4.4) with this tab, the user can define a
new material in PyVASCO, which will be available for all the simulations once saved (pressing the ’Save’ button).

4.1. MENUS

Figure 4.4: Tab 2 of the "New Material" window

•

Pump:
When this option is selected or the keyboard key combination Alt+P is
pressed, the New Pump window will be launched. This window allows
the user to define a new pump. It contains 2 tabs:
– View and Edit: (Fig. 4.5) with this tab, the user can see all the
defined pumps by selecting them in the list on the left, edit their
names by double-clicking them in the list and edit their properties
in the table. To save the changes done in a material, the user has
to press the button "Save changes".
– Write New Pump: (Fig. 4.6) with this tab, the user can define a
new pump in PyVASCO, which will be available for all the simulations once saved (pressing the ’Save’ button). Different pumping
speeds can be associated to the same pumps for different pressure
ranges by writing a pressure value (in mbar) in the second line edit
and pressing the button ’Add pumping speed p [mbar]:’.

•

Gas source:
When this option is selected or the keyboard key combination Ctrl+G
is pressed, the New Gas Source window will be launched. This window
allows the user to view and edit preexisting gas sources and to define a
new gas source. It contains 2 tabs:
– Data: View and Edit: (Fig. 4.7) with this tab, the user can see all the
defined pumps by selecting them in the list on the left, edit their
names by double-clicking them in the list, and edit their proper-

CHAPTER 4. LAYOUT AND FUNCTIONALITY

Figure 4.5: Tab 1 of the "New Pump" window.

Figure 4.6: Tab 1 of the "New Pump" window.

4.1. MENUS

Figure 4.7: Tab 1 of the "New Gas SOurce" window.

Figure 4.8: Tab 2 of the "New Gas SOurce" window.
ties in the table. To save the changes done in a material, the user
has to press the button "Save changes".
– Write New Gas Source: (Fig. 4.8) with this tab, the user can define
a new gas source in PyVASCO, which will be available for all the
simulations once saved (pressing the ’Save’ button).

•

ESD curve:

CHAPTER 4. LAYOUT AND FUNCTIONALITY

Figure 4.9: New ESD curve window.
When this option is selected or the keyboard key combination Ctrl+D
is pressed, the New ESD curve window will be launched. This window,
shown in Fig. 4.9 links an existing material with the experimental data
of its corresponding ESD curve. See Section 3.3 for more information
on the format of this file.

Analysis
The Analysis menu of PYVASCO launches the Analysis menu window. This
window contains 3 tabs:

•

Analysis Configuration (Fig. 4.10) and Analysis and Comparison (Fig.
4.11):
These two tabs allow the user to upload two different simulation results
in CSV format and plot them together in the Analysis and Comparison
tab. In the Analysis Configuration tab, the user can select the result
files clicking on the buttons ’Directory to Upload...’, and has to manually indicate the format and units in those files using the format and
unit dopdowns, and pressing ’Run Analysis’.

•

TDIS:
This tab was used to carry out the study on the TDIS presented in [5],
and has been kept in order to ease the generation of the this results.

Help
The Help menu of PyVASCO contains 2 options:

•

User’s guide:
When this option is selected or the keyboard key combination Ctrl+H

4.1. MENUS

Figure 4.10: Analysis window, Analysis Configuration tab.

Figure 4.11: Analysis window, Analysis and Comparison tab.

CHAPTER 4. LAYOUT AND FUNCTIONALITY

Figure 4.12: Analysis window, TDIS tab.

is pressed, the current document (PyVASCO User’s guide) is launched
and shown in the default web browser.

•

Documentation:
When this option is selected or the keyboard key combination Ctrl+U is
pressed, the API documentation is launched in the default web browser.

4.2 Tabs
The current version of PyVASCO (2.0) contains 4 tabs, named: Data, Simulation, Critical Current and Dynamic pressure due to ESD, respectively. In
this section, a detailed description of the different tabs in PyVASCO and their
functionality is provided.

4.2. TABS

Data

Figure 4.13: Data tab of PyVASCO.
The numbers in Fig. 4.13 represent:
1

Name of the simulation:
The name of the simulation is automatically set to the name of the input file selected in 4 , and can be manually modified by the user. This
name is used for the automatic saving in CSV format in the directory
specified in 5 if option 8 is selected.

’Old’ format input file:
As mentioned in Chapter 1 and Chapter 3, PyVASCO is based in VASCO,
but the format of the input files has been changed in order to ease the
writing of the input files for large simulations. However, it is still possible to upload a CSV input file written in the same format as the input
in VASCO [1] with this option.

CHAPTER 4. LAYOUT AND FUNCTIONALITY
3

Transform to new format:
After selecting an input file written with the same format as used in
VASCO (see [1] and Chapter 3 for more details) in 2 , this option allows
to generate a new input file written in the native PyVASCO format containing the same information as the one previously selected and named
as the old file with the suffix "_New". The new input file is saved in the
default input directory of PyVASCO, i.e., Data/Input/.

’New’ format input file:
Upload an input file in the native format of PyVASCO (see Chapter 3 for
more details).

Default output directory:
If option 8 is selected, the result of the simulation will be automatically saved in the directory selected using this option under the name
specified in 1 .

Upload data from gauges:
This option allows to upload experimental data from different gauges
and plot it together with the simulation results in Simulation (see for
more details on the format of the gauges data).

Shift the data from gauges:
Typically, PyVASCO assumes that the geometry starts in x = 0 m, while
the data from gauges extracted from, for example, the LHC, might start
at a longitudinal coordinate (s) different from 0 m, depending on the
reference point used. In order to effectively compare the simulation
results with the experimental data in the tab Simulation, his option allows to shift horizontally the experimental data uploaded in 6 . The
number indicated in this slot corresponds to the shift in meters to the
right (if the value is positive) or to the left (if the value is negative).

Save results in CSV format:
If this option is selected, the results of the simulation, i.e., the molecular density of the different considered gas species considered (in m−3 )
will be automatically saved in CSV format in the directory indicated in
5 under the name indicated in 1 .

Print a 3D sketch of the geometry:
If this option is selected, a 3D sketch of the simulated geometry will be
saved in PNG format under the name indicated in 1 in the directory
Data/.

4.2. TABS

10 Plotting quality:
This option specifies the number of points with which the density profile for the different gas species is calculated and presented in tab Simulation.
11 Logarithmic scale:
If selected, the Y axis of the density profile plot in tab Simulation is set
to logarithmic scale.
12 Move horizontally:
Similarly to 7 , this option shifts horizontally the simulated density
profile and the geometry. Thus, if a value different than 0 m is indicated, the geometry and the simulated density profile will be assumed
to start at the indicated x coordinate (in m).
13 Gas species:
This option allows to select the gas species to simulate and their ionization cross section (in m2 ). The default values indicated for the ionization cross sections of the different gas species correspond to those
calculated in [6] for a proton beam at 7 TeV.
14 Sensitivity factor:
If option 15 is selected, the total pressure is computed using the specified sensitivity factors for each gas specie.
15 Total of all gas species:
If this option is selected, the total pressure is computed using the sensitivity factors specified in 14 and plotted in the tab Simulation.
16 Variable pumping speed: If this option is selected, the change in pumping speed of ion pumps for different pressure ranges will be taken into
account. After performing an initial simulation with the nominal (maximum after saturation) pumping speed for the different gases, the pumping speed of the ion pumps located along the geometry is recalculated
and the gas density is recomputed.
17 Beam current:
Current of the circulating proton beam (in A). The default value is 0.582 A,
which corresponds to the nominal average beam current in the LHC
[7].

CHAPTER 4. LAYOUT AND FUNCTIONALITY

Figure 4.14: Simulation tab of PyVASCO.
18 Compute critical current :
If selected, the critical current for the selected model will be computed
and plotted in the tab Critical Current. PyVASCO looks for a divergence
in the gas density as a function of the beam current from the indicated
initial current and increases the test beam current as indicated by precision for the indicated number of steps.
19 Start simulation:
Pressing this button will launch the simulation with the setup specified
above. The results of the simulation are shown in the tabs Simulation
and Critical Current (if option 18 has been selected).

Simulation
The numbers in Fig. 4.14 represent:

4.2. TABS

20 Density:
If selected, the plot in 22 will show the density profile of the different
gas species selected in the tab Data in molecules/m3 .
21 Pressure:
If selected, the plot in 22 will show the pressure profile of the different
gas species selected in the tab Data in mbar and the total pressure computed using the sensitivity factors in 14 (if the option 15 is selected).
22 Density/Pressure plot:
This plot shows the simulated density or pressure profile, if the option
20 or 21 is selected, respectively.
23 Geometry plot:
This plot shows a block diagram of the simulated system. Different colors correspond to different materials.

Critical Current
Ion stimulated desorption in the presence of a high intensity proton beam
can lead to the so-called ion induced pressure instability [8]. Above a certain
beam current, the so called the critical current, IC , the pressure in the system
diverges. PyVASCO allows to simulate the evolution of the pressure for different beam currents, and to estimate the value of the critical current when a
divergence in the pressure of the system is found.
The numbers in Fig. 4.15 represent:
24 Critical current value:
Computed value of critical current for the simulated system.
25 Total density profile plot:
This plot shows the total molecular density profile for the different computed beam currents.
26 Dynamic current plot :
This plot shows the maximum density of the different gas species as a
function of the beam current.
In order to compute the critical current for the simulated system for an
explanation on the critical current), the dynamic vacuum model presented

CHAPTER 4. LAYOUT AND FUNCTIONALITY

Figure 4.15: Critical Current tab of PyVASCO.

in [1, 2] and summarized in Section 2.2 is solved for different tested beam
currents. The first value of the beam current used for the computation is the
value set in the box ’Initial current [A]’ in 18 . The subsequent used values of
current are computed by repeatedly increasing the initial value by the indicated precision until the number of steps entered by the user is reached. If a
divergence in the density has been found for a given beam current, this value
± the precision are set as the critical current. If the divergence is found in the
first step of the computation (the current set in ’Initial current [A]’ in 18 ),
the shown critical current value will be ≤ Initial current. On the opposite, if
a divergence in the density is not found after the indicated number of steps,
the value of critical current shown in this tag will be ≥ than the last tried beam
current.

4.2. TABS

Dynamic pressure due to ESD
The tab Dynamic pressure due to ESD of PyVASCO allows to perform two different simulations varying the ESD of the materials used in the simulation.
The different setups of this tab are shown in Figs. 4.16 and 4.17, and the numbers in these figures indicate:
27 Open Directory:
Select the input file (in the native PyVASCO format).
28 ESD from accumulated electron dose:
This option uses the ESD yields of the different UHV gas species for the
selected accumulated electron dose while solving the dynamic vacuum
model for the input file selected in 27 . If option 28 is selected, the
slider 29 will appear in the box ’Simulation parameters’.
29 Estimated electron dose:
This slider allows the user to set the accumulated electron dose received homogeneously along the simulated geometry.
30 Start simulation:
Launches the simulation.
31 Scrubbing Plot:
This plot shows the density profile of the different selected gas species
for the accumulated electron dose selected in 29 if option 28 is selected. On the contrary, if option 32 is selected, the plot will show the
total density profile for the different accumulated electron doses set in
33 .
32 Scan ESD for different accumulated electron doses:
This option solves the dynamic vacuum model presented in Section 2.2
for a range of accumulated electron doses specified in 33 .
33 Electron dose values:
These 3 boxes allow the user to introduce the range of accumulated
electron doses of interest for the simulation.

CHAPTER 4. LAYOUT AND FUNCTIONALITY

Figure 4.16: Dynamic pressure due to ESD tab of PyVASCO, layout for the simulation after receiving a fix accumulated electron doses.

4.2. TABS

Figure 4.17: Dynamic pressure due to ESD tab of PyVASCO, layout for the simulation of the conditioning effect.

CHAPTER 4. LAYOUT AND FUNCTIONALITY
IMPORTANT! : Please note that this simulation will be properly performed
if an ESD curve for each of the materials used in the simulation has already
been defined. If this is not the case, please link the concerned materials with
an ESD curve pressing on the menu Add → ESD curve.

Chapter 5
Extracting results with PyVASCO
By right-clicking on any plot of PyVASCO, the menu in Fig. 5.1 will appear.
This menu allows the user to directly modify some properties of the presented plot and to export it in several formats. In this chapter, a fast overview
of the relevant options available for the extraction of data from PyVASCO will
be given.

5.1 Management and plot options
The plot menu contains the following options:

•

View All : This option centers the plotted data and adjusts the axis
scale to optimize the occupied space in the plot. Selecting this option
is equivalent to press the A which appears in the left-down corner in
every plot.

•

XAxis and YAxis: Selecting these option will open the menus in Figs.
5.2a and 5.2b, respectively. The first and second cell under the option
Manual allow to set the minimum and maximum values in the x and y
axis, respectively.

•

Mouse Mode: In 3 button, the left mouse button pans the view and the
right button scales. In 1 button mode, the left button draws a rectangle
which updates the visible region (this mode is more suitable for singlebutton mice).

•

Plot options: Several options are available. The most relevant are Log
X and Log Y (under the Plot options > Transforms), which allows to
change the scales in both the X and Y axis from linear to log and vice
versa, andGrid, which allows to show, hide and modulate the intensity
of the plot grid in both x and y axes.
39

CHAPTER 5. EXTRACTING RESULTS WITH PYVASCO

Figure 5.1: Plot menu (by right-clicking anywhere in the plot).

5.2. EXPORTING PLOTS IN DIFFERENT FORMATS

(a)

(b)

Figure 5.2: Options XAxis and YAxis in the plot menu.

5.2 Exporting plots in different formats
Pressing the option Export in the plot menu of Fig. 5.1 will launch the menu
in Fig. 5.3.
The Export menu allows the user to save the plots in PyVASCO in different formats, listed in the frame Export format in Fig. 5.3. It is interesting to
mention the following formats:

•

Image File: The user can export any plot in PyVASCO as an image file.
This options allows for the manual modification of the size of the resulting file and the background color.

•

Scalable Vector Graphics: The advantage of this option is that the resulting plot can be opened and edited directly in programs like InkScape.

•

Matplotlib Window: Matplotlib is one of the most used plotting libraries in Python. This option allows the user to further customize the
plot changing, for instance, the width, shape and markers of the lines,
the labels in both axis, etc.

•

CSV: The data from all PyVASCO plots can be exported to CSV format
with this option.
IMPORTANT!: If the X or Y scale in the plot to export to CSV data is in logarithmic scale, only the logarithm of the real value will be exported. The real
values can be recovered by doing 10exported values .
Alternatively, the data of the pressure profile in the Tab Simulation of
PyVASCO is automatically saved in CSV format in the directory selected
in 5 of Tab Data if option 8 in the same tab is selected.

CHAPTER 5. EXTRACTING RESULTS WITH PYVASCO

Figure 5.3: Export menu.

Chapter 6
Benchmark with VASCO and Molflow+
We have benchmarked PyVASCO with two other programs: VASCO and Molflow+
[9] for the simple case of a single segment of length 100 cm and a radius of
1 cm, with lumped pumps of 5 l/s connected in the extremes. Fig. 6.1 shows
the 3D model built in Molflow+ for this simulation and Figs. 6.2 and 6.3 show
a comparison between the results of PyVASCO and Molflow+ and PyVASCO
and VASCO, respectively, for this simple model.
IMPORTANT! : Please note that more complex tests for comparing PyVASCO
with other simulation tools have not been done due to lack of time.

Figure 6.1: Molflow+ model for benchmark with PyVASCO.
43

CHAPTER 6. BENCHMARK WITH VASCO AND MOLFLOW+

Figure 6.2: Comparison between the results obtained with Molflow+ and PyVASCO.

Figure 6.3: Comparison between the results obtained with VASCO and PyVASCO.

Bibliography
[1] A. Rossi, “VASCO (VAcuum Stability COde): multi-gas code to calculate
gas density profile in a UHV system,” Tech. Rep. LHC-Project-Note-341.
CERN-LHC-Project-Note-341, CERN, Geneva, Mar 2004.
[2] I. Aichinger, G. Larcher, and R. Kersevan, “Vacuum Simulations in High
Energy Accelerators and Distribution Properties of Continuous and Discrete Particle Motions,” 2017. Presented 2017.
[3] O. Bruning, F. Caspers, I. R. Collins, O. Grobner, B. Henrist, N. Hilleret, J. .
Laurent, M. Morvillo, M. Pivi, F. Ruggiero, and X. Zhang, “Electron cloud
and beam scrubbing in the lhc,” in Proceedings of the 1999 Particle Accelerator Conference (Cat. No.99CH36366), vol. 4, pp. 2629–2631 vol.4, March
1999.
[4] C. Day, “Basics and applications of cryopumps,” 01 2006.
[5] P. Ribes Metidieri, C. Yin Vallgren, G. Skripka, G. Iadarola, and
G. Bregliozzi, “TDIS pressure profile simulations after LS2,” tech. rep.,
CERN, Geneva, 2018.
[6] A. G. Mathewson and S. Zhang, “Beam-gas ionisation cross sections at 7.0
TeV,” Tech. Rep. LHC-VAC/AGM. Vacuum-Technical-Note-96-01, CERN,
Geneva, Jan 1996.
[7] Brüning, Oliver Sim and Collier, Paul and Lebrun, P and Myers, Stephen
and Ostojic, Ranko and Poole, John and Proudlock, Paul, LHC Design Report. CERN Yellow Reports: Monographs, Geneva: CERN, 2004.
[8] E. Fischer and K. Zankel, “The stability of the residual gas density in the
ISR in presence of high density proton beams,” Tech. Rep. CERN-ISR-VA73-52. ISR-VA-73-52, CERN, Geneva, Nov 1973.
[9] M. Ady and R. Kersevan, “Molflow+ user guide,” tech. rep., CERN, Geneva,
June 2014.

Source Exif Data:

File Type                       : PDF
File Type Extension             : pdf
MIME Type                       : application/pdf
PDF Version                     : 1.5
Linearized                      : No
Page Count                      : 45
Page Mode                       : UseOutlines
Author                          : 
Title                           : 
Subject                         : 
Creator                         : LaTeX with hyperref package
Producer                        : pdfTeX-1.40.17
Create Date                     : 2018:09:24 09:28:58Z
Modify Date                     : 2018:09:24 09:28:58Z
Trapped                         : False
PTEX Fullbanner                 : This is pdfTeX, Version 3.14159265-2.6-1.40.17 (TeX Live 2016/Debian) kpathsea version 6.2.2

EXIF Metadata provided by EXIF.tools

User Guide

Navigation menu

Versions of this User Manual:

Views

Navigation