SlideShare a Scribd company logo
Evaluation of Mathematical Models
for X-ray Spectrum Generation suitable for Industrial
             Radiography Applications




               Nityanand Gopalika, A. V. K Satish, V. Manoharan

                      Industrial Imaging and Modeling Lab
                              Imaging Technologies
                        John F. Welch Technology Centre
                                   Bangalore
Presentation Outline

 Different X-Ray generation models
 Validation approach:
       Variation of Photon Fluence / mR with Average
         Energy
       Relationship between Average Energy and kVp for
         different filters
       Half Value Layer (HVL) for different cases
       Dose validation with experiment
 Summary
Birch and Marshall model
Intensity produced in a solid target
 Governing Relationships dT
                Nρ
                       T                 −1
                               
                           v

         Iv =
                  A      ∫  dx 
                         T0
                            Q
                                
                                              dT   Physics
                                                       • Theoretical model
Effect of target absorption                            • Target absorption taken care
        T = (T02 − Cxρ ) 0.5                                   (improvement over Kramer's theory)

Substituting the above gives
                                                   −1
               Nρ
                    Tv
                           T0           dT                 µv
        Iv   =      ∫ 1 + m0C 2
                                      Q
                                         dx          exp(      (T 2 − T02 ) cot θ ) dT
                A   T0                                      Cρ

Characteristic Intensity
        I ch = K (U 0 − 1)1.63

                                      Drawbacks
                       Applicable only from 30-150 kV.
                       Small target angles greater error.
                       Back Scatter not considered.

                               Suited for medical applications
Ellery Storm Model
Thick target energy loss as an integral of thin target energy loss:
                     E0
                                dE               dE = Energy loss in thin strip of target
        I E0 ,K = ∫ I E0 ,k ,E          
                 E >k           −dE /dx          E = Initial electron energy at photon emission
Correction for electron backscatter losses, photon attenuation and target angle
                E0
                                dE 
    I E0 ,k =    ∫k
                E>
                    I E0 ,k ,E          (1−ηε E 0 ,k )*exp( −µ k x/ tanα )
                                −dE /dx 
Emission per unit solid angle in the photon energy
                                                   −3 k
                      11 ( E0 −k )(1−e          )  Ek                               1.0
    I E0 ,k ≅(           Z                        ) f E0 ,k ,α
                      4π              1      E0
                           ( k / E0 ) 3 (1−e Ek )
                                                                                          40 kV

                                                                                          60 kV
Photon Attenuation Correction Factor                                           C E0 , k

     f E0 ,k ,α ≅ exp(−0.2C E0 ,k ℜ E0 µ k / tan α )
                                                                                          100 kV
                                                                                    0.5

                                                                                          200kV
                                     E0  Initial Electron Energy
                                     Ek  K Edge Energy                                   300 kV

                                     K  Photon Energy                              0.0
                                                                                            10         20            40
                                     Z  Atomic Weight                                           Photon Energy (keV)


                                   Best suited for industrial applications
Photon Fluence /mR & Average Energy
                              Photon Fluence per Roentgen
Photon Fluence




                 4.E+10
                 3.E+10
     / mR




                 2.E+10
                 1.E+10
                                                                                              Photon Fluence /mR =
                                                                                                                            ∫Θ( E )*E*dE
                 0.E+00                                                                                                ∫Θ( E )*(µ ( E )/ ρ )*E*dE
                          0   50   100   150   200   250    300   350

                                    Average Energy

                                                                                                           Average energy

                                                                                         70
                                                                                         60


                                                                    Average energy kev
                                                                                                                                       no filter


                          Average Energy =
                                           ∫Θ( E )*dE                                    50
                                                                                         40
                                                                                                                                       1 mm aluminium
                                                                                                                                       2 mm aluminium

                                             ∫dE                                         30
                                                                                         20
                                                                                                                                       3 mm aluminium
                                                                                                                                       4 mm aluminium
                                                                                         10                                            5 mm aluminum
                                                                                         0
                                                                                              0       50         100          150
                                                                                                           kVP




                                         Literature data available below 150 kVp
Model Performance Verification
                                                 Average Energy Vs. kvp (Simulation)                                                                                Photon Fluence per roentgen Vs.
                                                                                                                                                                      Average Energy (Simulation)
                                  140
                                  120                                                                                                                    3.00E+05
                 Average Energy




                                                                                                     Thick = 1mm




                                                                                                                                   Photon Fluence / mR
                                  100                                                                Thick = 2mm                                         2.50E+05
                                                                                                                                                                                                                     Thick = 1mm
                                   80                                                                Thick = 3mm                                         2.00E+05                                                    Thick = 2mm
                                   60                                                                Thick = 4mm                                         1.50E+05                                                    Thick = 3mm
                                   40                                                                Thick = 5mm                                         1.00E+05                                                    Thick = 4mm
                                   20                                                                                                                                                                                Thick = 5mm
                                                                                                                                                         5.00E+04
                                    0                                                                                                                    0.00E+00
                                        0          100            200           300          400       500                                                          0     20   40    60    80   100 120 140
                                                                        kvp                                                                                                    Average Energy


                                                          Average Energy Vs. kvp                                                                                        Photon Fluence / mR Vs. Average Energy
                                                          (Simulation & Liturature)                                                                                            (Simulation & Literature)
                      140                                                                                                                          3.E+05




                                                                                                                      Photon Fluence / mR
                      120                                                                                                                          3.E+05
Average Energy




                      100                                                                                                                          2.E+05
                       80                                                             Thick = 5mm, Simulation                                      2.E+05
                       60
                                                                                      Thick = 5mm, Literature                                      1.E+05                                       Thick = 5mm, Simulation
                       40                                                                                                                                                                       Thick = 5mm, Experimental
                                                                                                                                                   5.E+04
                       20
                        0                                                                                                                          0.E+00
                                                                                                                                                             0           20     40        60      80       100       120    140
                                   0        50      100     150     200         250    300     350     400      450
                                                                          kvp                                                                                                         Average Energy




                                                                          High accuracy in the range of 30 – 150 kVp
HVL Study: Comparison with NIST Data
        Tube                                                                         HVL      Dose     Dose
      Potential Inherent                                                            (mm) -   Before    After
Cases (KvP)       Filter                     Added Filter                    Object NIST     Object   Object   % Error
  1      100    1 mm Be                   % Difference in HVL
                                            1.98 mm Al                         Al    2.77    12.668    6.744   -6.475
  2      100    3 mm Be                         5 mm Al                        Al    5.02     6.080    3.043   -0.106
  3      100
              8 3 mm Be                    4 mm Al + 5.2 mm Cu                 Al    13.5     0.025    0.012   2.393
  4      100 6 3 mm Be                     4 mm Al + 5.2 mm Cu                Cu     1.14     0.025    0.012   3.496
  5      120    3 mm Be                        6.87 mm Al                      Al    6.79     6.887    3.440   0.100
  6      150 4 3 mm Be                    5 mm Al + 0.25 mm Cu                 Al    10.2     8.405    4.177   0.610
         % Difference




  7      150    3 mm Be                   5 mm Al + 0.25 mm Cu                Cu     0.67     8.405    4.125   1.851
  8      150  2 3 mm Be             4 mm Al + 4 mm Cu + 1.51 mm Sn             Al     17      0.187    0.092   2.147
  9      150    3 mm Be             4 mm Al + 4 mm Cu + 1.51 mm Sn            Cu      2.5     0.187    0.087   7.005
 10      200  0 3 mm Be                  4.1 mm Al + 1.12 mm Cu                Al    14.9     9.782    4.831   1.217
 11      200    3 mm Be                  4.1 mm Al + 1.12 mm Cu               Cu     1.69     9.782    4.785   2.169
 12      200
             -2 3 mm Be      4 mm Al + 0.6 mm Cu + 4.16 mm Sn + 0.77 mm Pb     Al    19.8     0.141    0.070   1.665
 13      200 -4 3 mm Be      4 mm Al + 0.6 mm Cu + 4.16 mm Sn + 0.77 mm Pb    Cu      4.1     0.141    0.068   4.188
 14      250    3 mm Be                    5 mm Al + 3.2 mm Cu                 Al    18.5     9.624    4.740   1.504
 15      250 -6 3 mm Be                    5 mm Al + 3.2 mm Cu                Cu      3.2     9.624    4.695   2.425
 16      250    3 mm Be      4 mm Al + 0.6 mm Cu + 1.04 mm Sn + 2.72 mm Pb     Al     22      0.206    0.101   2.119
 17      250 -8 3 mm Be      4 mm Al + 0.6 mm Cu + 1.04 mm Sn + 2.72 mm Pb    Cu      5.2     0.206    0.102   0.613
 18      300    3 mm Be
                75                125 4 mm Al + 6.5 mm Sn
                                                    175            225         Al
                                                                                   27522      4.395    2.169
                                                                                                      325      1.280
 19      300    3 mm Be                    4 mm Al + 6.5 mm Sn                Cu      5.3     4.395    2.201   -0.149
 20      300    3 mm Be
                                                           kVp
                                     4.1 mm Al + 3 mm Sn + 5 mm Pb             Al     23      0.164    0.083   -0.839
 21      300    3 mm Be              4.1 mm Al + 3 mm Sn + 5 mm Pb            Cu      6.2     0.164    0.086   -4.415


      % Difference in HVL between NIST and simulation is within +/- 8%
Experimental Dose Measurement
Experimental Conditions:                                                               Simulation Conditions:
   X-Ray Tube:                                                                            Target Voltage : 20 < kV < 420 kVp
                                                                                          Current : 1 mA
                          1.    KM16010E-A MicroFocus                                     Target Material – W
                         2. Seifert ISOVOLT 420/10
                                                          Dose = 1.828*10-11∑φ(E).(µ(E)/ρ) air.E.dE
                     Dosimeter: Keithley 35050A Dosimeter

                          % Difference in Dose : Kevex, SDD = 1m                                                  % Difference in Dose: Seifert, SDD = 1m
                               (Experimental and Simulated)                                                            (Experimental and Simulated)
                6                                                                                     8
                                                                                                                                                      0.4 mm Cu Filter
                4                                                                                     6
                                                                                                                                                      9 mm Al Filter
                                                                                                      4




                                                                                       % Difference
                2
 % Difference




                                                                                                      2
                0
                                                                                                      0
                -2
                                                                                                      -2
                -4                                              0.4 mm Cu Filter                      -4
                -6                                              9 mm Al Filter                        -6
                -8                                                                                    -8
                     30   50      70       90      110        130     150        170                       30        130           230               330               430
                                                                                                                            Tube Potential (kvp)
                                       Tube Potential (kvp)



                           KM16010E-A MicroFocus                                                                Seifert ISOVOLT 420/10
                      Less than 7% difference is observed between simulation and experiments
Summary



 Ellery Storm Model best suited for X-ray Spectrum Generation
 Model performance metrics:
       Accuracy for Photon Fluence / mR > 95%
       Error in Average Energy < 5%
       Deviation in HVL < 8%
       Simulated Dose is in good agreement with Experiments
Nityanand gopalika   spectrum validation - nde 2003
Nityanand gopalika   spectrum validation - nde 2003

More Related Content

What's hot

A Mechanism Of Electron Pairing Relating To Supperconductivity
A Mechanism Of Electron Pairing Relating To SupperconductivityA Mechanism Of Electron Pairing Relating To Supperconductivity
A Mechanism Of Electron Pairing Relating To Supperconductivity
Qiang LI
 
Energy Harvesting Conference Boston Nov. 2011
Energy Harvesting Conference  Boston Nov. 2011Energy Harvesting Conference  Boston Nov. 2011
Energy Harvesting Conference Boston Nov. 2011
Eric Summers
 
Electromagnetic Wave
Electromagnetic WaveElectromagnetic Wave
Electromagnetic WaveYong Heui Cho
 
Mit6 007 s11_lec20
Mit6 007 s11_lec20Mit6 007 s11_lec20
Mit6 007 s11_lec20Bipin Kujur
 
R05010501 B A S I C E L E C T R I C A L E N G I N E E R I N G
R05010501  B A S I C  E L E C T R I C A L  E N G I N E E R I N GR05010501  B A S I C  E L E C T R I C A L  E N G I N E E R I N G
R05010501 B A S I C E L E C T R I C A L E N G I N E E R I N G
guestd436758
 
Math Project
Math ProjectMath Project
Math Project
turtlemonvh
 
Presentación de productos SEOUL
Presentación de productos SEOULPresentación de productos SEOUL
Presentación de productos SEOULGonzalo Guerrero
 
Shading v02
Shading v02Shading v02
Design, Simulation and Verification of Generalized Photovoltaic cells Model U...
Design, Simulation and Verification of Generalized Photovoltaic cells Model U...Design, Simulation and Verification of Generalized Photovoltaic cells Model U...
Design, Simulation and Verification of Generalized Photovoltaic cells Model U...
IDES Editor
 
Colorimetry: LED Fundamentals
Colorimetry: LED FundamentalsColorimetry: LED Fundamentals
Colorimetry: LED Fundamentals
LED Light Site by OSRAM Opto Semiconductors
 
ENGINEERING PHYSICS -SEMICONDUCTING MATERIALS PROBLEMS KEYS
ENGINEERING PHYSICS -SEMICONDUCTING MATERIALS PROBLEMS KEYSENGINEERING PHYSICS -SEMICONDUCTING MATERIALS PROBLEMS KEYS
ENGINEERING PHYSICS -SEMICONDUCTING MATERIALS PROBLEMS KEYSsunmo
 
Summary x ray
Summary x raySummary x ray
External Thermal Resistance - Substrates: LED Fundamentals
External Thermal Resistance - Substrates: LED FundamentalsExternal Thermal Resistance - Substrates: LED Fundamentals
External Thermal Resistance - Substrates: LED Fundamentals
LED Light Site by OSRAM Opto Semiconductors
 
Plastica flessibile
Plastica flessibilePlastica flessibile
Plastica flessibilebuffociccio
 

What's hot (18)

A Mechanism Of Electron Pairing Relating To Supperconductivity
A Mechanism Of Electron Pairing Relating To SupperconductivityA Mechanism Of Electron Pairing Relating To Supperconductivity
A Mechanism Of Electron Pairing Relating To Supperconductivity
 
Energy Harvesting Conference Boston Nov. 2011
Energy Harvesting Conference  Boston Nov. 2011Energy Harvesting Conference  Boston Nov. 2011
Energy Harvesting Conference Boston Nov. 2011
 
Electromagnetic Wave
Electromagnetic WaveElectromagnetic Wave
Electromagnetic Wave
 
Mit6 007 s11_lec20
Mit6 007 s11_lec20Mit6 007 s11_lec20
Mit6 007 s11_lec20
 
R05010501 B A S I C E L E C T R I C A L E N G I N E E R I N G
R05010501  B A S I C  E L E C T R I C A L  E N G I N E E R I N GR05010501  B A S I C  E L E C T R I C A L  E N G I N E E R I N G
R05010501 B A S I C E L E C T R I C A L E N G I N E E R I N G
 
Math Project
Math ProjectMath Project
Math Project
 
Phy electro
Phy electroPhy electro
Phy electro
 
Presentación de productos SEOUL
Presentación de productos SEOULPresentación de productos SEOUL
Presentación de productos SEOUL
 
Electromagnetics
ElectromagneticsElectromagnetics
Electromagnetics
 
Shading v02
Shading v02Shading v02
Shading v02
 
Design, Simulation and Verification of Generalized Photovoltaic cells Model U...
Design, Simulation and Verification of Generalized Photovoltaic cells Model U...Design, Simulation and Verification of Generalized Photovoltaic cells Model U...
Design, Simulation and Verification of Generalized Photovoltaic cells Model U...
 
Colorimetry: LED Fundamentals
Colorimetry: LED FundamentalsColorimetry: LED Fundamentals
Colorimetry: LED Fundamentals
 
Chapter 7
Chapter 7Chapter 7
Chapter 7
 
Ao24271274
Ao24271274Ao24271274
Ao24271274
 
ENGINEERING PHYSICS -SEMICONDUCTING MATERIALS PROBLEMS KEYS
ENGINEERING PHYSICS -SEMICONDUCTING MATERIALS PROBLEMS KEYSENGINEERING PHYSICS -SEMICONDUCTING MATERIALS PROBLEMS KEYS
ENGINEERING PHYSICS -SEMICONDUCTING MATERIALS PROBLEMS KEYS
 
Summary x ray
Summary x raySummary x ray
Summary x ray
 
External Thermal Resistance - Substrates: LED Fundamentals
External Thermal Resistance - Substrates: LED FundamentalsExternal Thermal Resistance - Substrates: LED Fundamentals
External Thermal Resistance - Substrates: LED Fundamentals
 
Plastica flessibile
Plastica flessibilePlastica flessibile
Plastica flessibile
 

Similar to Nityanand gopalika spectrum validation - nde 2003

Parameters for Classical Force Fields, E. Tajkhorshid
Parameters for Classical Force Fields, E. TajkhorshidParameters for Classical Force Fields, E. Tajkhorshid
Parameters for Classical Force Fields, E. TajkhorshidTCBG
 
Photoelectron Spectroscopy for Functional Oxides
Photoelectron Spectroscopy for Functional OxidesPhotoelectron Spectroscopy for Functional Oxides
Photoelectron Spectroscopy for Functional Oxides
nirupam12
 
RBS
RBSRBS
ECNG 3015 Power System Protection
ECNG 3015    Power System ProtectionECNG 3015    Power System Protection
ECNG 3015 Power System Protection
Chandrabhan Sharma
 
Ennaoui cours rabat part ii
Ennaoui cours rabat part iiEnnaoui cours rabat part ii
Ennaoui cours rabat part ii
Prof. Dr. Ahmed Ennaoui
 
Energy and nanotechnology
Energy and nanotechnologyEnergy and nanotechnology
Energy and nanotechnologyStar Gold
 
Younes Sina's presentation on Nuclear reaction analysis
Younes Sina's presentation on  Nuclear reaction analysisYounes Sina's presentation on  Nuclear reaction analysis
Younes Sina's presentation on Nuclear reaction analysis
Younes Sina
 
Science Cafe Discovers a New Form of Alternative Energy
Science Cafe Discovers a New Form of Alternative EnergyScience Cafe Discovers a New Form of Alternative Energy
Science Cafe Discovers a New Form of Alternative Energy
EngenuitySC
 
Chapter2 dosimetric principles, quantities and units
Chapter2 dosimetric principles, quantities and unitsChapter2 dosimetric principles, quantities and units
Chapter2 dosimetric principles, quantities and units
Jeju National University
 
Nernst Equation 3.ppt
Nernst Equation 3.pptNernst Equation 3.ppt
Nernst Equation 3.ppt
TenzinNamgayNidrup
 
Workshop problems solving
Workshop problems solvingWorkshop problems solving
Workshop problems solving
Prof. Dr. Ahmed Ennaoui
 
3-Phase AC Motor Model(PSpice Model)
3-Phase AC Motor Model(PSpice Model)3-Phase AC Motor Model(PSpice Model)
3-Phase AC Motor Model(PSpice Model)
Tsuyoshi Horigome
 
Ch34 ssm
Ch34 ssmCh34 ssm
Ch34 ssm
Marta Díaz
 
[L'angolo del PhD] Alessandro Palma - XXII Ciclo - 2009
[L'angolo del PhD] Alessandro Palma - XXII Ciclo - 2009[L'angolo del PhD] Alessandro Palma - XXII Ciclo - 2009
[L'angolo del PhD] Alessandro Palma - XXII Ciclo - 2009
accatagliato
 
Introduction to electron microscope
Introduction to electron microscope Introduction to electron microscope
Introduction to electron microscope
Antilen Jacob
 
2014 st josephs geelong physics lecture
2014 st josephs geelong physics lecture2014 st josephs geelong physics lecture
2014 st josephs geelong physics lecture
Andrew Smith
 

Similar to Nityanand gopalika spectrum validation - nde 2003 (20)

Parameters for Classical Force Fields, E. Tajkhorshid
Parameters for Classical Force Fields, E. TajkhorshidParameters for Classical Force Fields, E. Tajkhorshid
Parameters for Classical Force Fields, E. Tajkhorshid
 
Photoelectron Spectroscopy for Functional Oxides
Photoelectron Spectroscopy for Functional OxidesPhotoelectron Spectroscopy for Functional Oxides
Photoelectron Spectroscopy for Functional Oxides
 
RBS
RBSRBS
RBS
 
ECNG 3015 Power System Protection
ECNG 3015    Power System ProtectionECNG 3015    Power System Protection
ECNG 3015 Power System Protection
 
Ennaoui cours rabat part ii
Ennaoui cours rabat part iiEnnaoui cours rabat part ii
Ennaoui cours rabat part ii
 
Energy and nanotechnology
Energy and nanotechnologyEnergy and nanotechnology
Energy and nanotechnology
 
Younes Sina's presentation on Nuclear reaction analysis
Younes Sina's presentation on  Nuclear reaction analysisYounes Sina's presentation on  Nuclear reaction analysis
Younes Sina's presentation on Nuclear reaction analysis
 
Science Cafe Discovers a New Form of Alternative Energy
Science Cafe Discovers a New Form of Alternative EnergyScience Cafe Discovers a New Form of Alternative Energy
Science Cafe Discovers a New Form of Alternative Energy
 
Chapter2 dosimetric principles, quantities and units
Chapter2 dosimetric principles, quantities and unitsChapter2 dosimetric principles, quantities and units
Chapter2 dosimetric principles, quantities and units
 
non linear optics
non linear opticsnon linear optics
non linear optics
 
Basic i
Basic iBasic i
Basic i
 
Nernst Equation 3.ppt
Nernst Equation 3.pptNernst Equation 3.ppt
Nernst Equation 3.ppt
 
Workshop problems solving
Workshop problems solvingWorkshop problems solving
Workshop problems solving
 
3-Phase AC Motor Model(PSpice Model)
3-Phase AC Motor Model(PSpice Model)3-Phase AC Motor Model(PSpice Model)
3-Phase AC Motor Model(PSpice Model)
 
Ch34 ssm
Ch34 ssmCh34 ssm
Ch34 ssm
 
[L'angolo del PhD] Alessandro Palma - XXII Ciclo - 2009
[L'angolo del PhD] Alessandro Palma - XXII Ciclo - 2009[L'angolo del PhD] Alessandro Palma - XXII Ciclo - 2009
[L'angolo del PhD] Alessandro Palma - XXII Ciclo - 2009
 
Introduction to electron microscope
Introduction to electron microscope Introduction to electron microscope
Introduction to electron microscope
 
Semiconductor lasers
Semiconductor lasersSemiconductor lasers
Semiconductor lasers
 
2014 st josephs geelong physics lecture
2014 st josephs geelong physics lecture2014 st josephs geelong physics lecture
2014 st josephs geelong physics lecture
 
Lect26 handout
Lect26 handoutLect26 handout
Lect26 handout
 

More from Nityanand Gopalika

Nityanand gopalika digital radiography performance study
Nityanand gopalika   digital radiography performance studyNityanand gopalika   digital radiography performance study
Nityanand gopalika digital radiography performance study
Nityanand Gopalika
 
Nityanand gopalika digital detectors for industrial applications
Nityanand gopalika   digital detectors for industrial applicationsNityanand gopalika   digital detectors for industrial applications
Nityanand gopalika digital detectors for industrial applications
Nityanand Gopalika
 

More from Nityanand Gopalika (9)

Nityanand gopalika digital radiography performance study
Nityanand gopalika   digital radiography performance studyNityanand gopalika   digital radiography performance study
Nityanand gopalika digital radiography performance study
 
Nityanand gopalika digital detectors for industrial applications
Nityanand gopalika   digital detectors for industrial applicationsNityanand gopalika   digital detectors for industrial applications
Nityanand gopalika digital detectors for industrial applications
 
Patents by nityanand gopalika
Patents by nityanand gopalikaPatents by nityanand gopalika
Patents by nityanand gopalika
 
Nityanand gopalika Patent3
Nityanand gopalika Patent3Nityanand gopalika Patent3
Nityanand gopalika Patent3
 
Nityanand gopalika Patent2
Nityanand gopalika Patent2Nityanand gopalika Patent2
Nityanand gopalika Patent2
 
Nityanand gopalika Patent1
Nityanand gopalika Patent1Nityanand gopalika Patent1
Nityanand gopalika Patent1
 
Nityanand gopalika
Nityanand gopalikaNityanand gopalika
Nityanand gopalika
 
Nityanand gopalika
Nityanand gopalikaNityanand gopalika
Nityanand gopalika
 
Nityanand gopalika
Nityanand gopalikaNityanand gopalika
Nityanand gopalika
 

Recently uploaded

Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Albert Hoitingh
 
Elevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object CalisthenicsElevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object Calisthenics
Dorra BARTAGUIZ
 
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Elizabeth Buie - Older adults: Are we really designing for our future selves?Elizabeth Buie - Older adults: Are we really designing for our future selves?
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Nexer Digital
 
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdfFIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance
 
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
Sri Ambati
 
The Metaverse and AI: how can decision-makers harness the Metaverse for their...
The Metaverse and AI: how can decision-makers harness the Metaverse for their...The Metaverse and AI: how can decision-makers harness the Metaverse for their...
The Metaverse and AI: how can decision-makers harness the Metaverse for their...
Jen Stirrup
 
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofszkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
Alex Pruden
 
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing DaysClimate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
Kari Kakkonen
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Prayukth K V
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
SOFTTECHHUB
 
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
91mobiles
 
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdfFIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
Alan Dix
 
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
James Anderson
 
By Design, not by Accident - Agile Venture Bolzano 2024
By Design, not by Accident - Agile Venture Bolzano 2024By Design, not by Accident - Agile Venture Bolzano 2024
By Design, not by Accident - Agile Venture Bolzano 2024
Pierluigi Pugliese
 
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfSAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
Peter Spielvogel
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
BookNet Canada
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
KAMESHS29
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
Alpen-Adria-Universität
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
ControlCase
 

Recently uploaded (20)

Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
 
Elevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object CalisthenicsElevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object Calisthenics
 
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Elizabeth Buie - Older adults: Are we really designing for our future selves?Elizabeth Buie - Older adults: Are we really designing for our future selves?
Elizabeth Buie - Older adults: Are we really designing for our future selves?
 
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdfFIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
 
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
 
The Metaverse and AI: how can decision-makers harness the Metaverse for their...
The Metaverse and AI: how can decision-makers harness the Metaverse for their...The Metaverse and AI: how can decision-makers harness the Metaverse for their...
The Metaverse and AI: how can decision-makers harness the Metaverse for their...
 
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofszkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
 
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing DaysClimate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
 
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
 
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdfFIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
 
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
 
By Design, not by Accident - Agile Venture Bolzano 2024
By Design, not by Accident - Agile Venture Bolzano 2024By Design, not by Accident - Agile Venture Bolzano 2024
By Design, not by Accident - Agile Venture Bolzano 2024
 
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfSAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
 

Nityanand gopalika spectrum validation - nde 2003

  • 1. Evaluation of Mathematical Models for X-ray Spectrum Generation suitable for Industrial Radiography Applications Nityanand Gopalika, A. V. K Satish, V. Manoharan Industrial Imaging and Modeling Lab Imaging Technologies John F. Welch Technology Centre Bangalore
  • 2. Presentation Outline  Different X-Ray generation models  Validation approach:  Variation of Photon Fluence / mR with Average Energy  Relationship between Average Energy and kVp for different filters  Half Value Layer (HVL) for different cases  Dose validation with experiment  Summary
  • 3. Birch and Marshall model Intensity produced in a solid target Governing Relationships dT Nρ T −1   v Iv = A ∫  dx  T0 Q  dT Physics • Theoretical model Effect of target absorption • Target absorption taken care T = (T02 − Cxρ ) 0.5 (improvement over Kramer's theory) Substituting the above gives −1 Nρ Tv  T0   dT  µv Iv = ∫ 1 + m0C 2  Q   dx  exp( (T 2 − T02 ) cot θ ) dT A T0    Cρ Characteristic Intensity I ch = K (U 0 − 1)1.63 Drawbacks  Applicable only from 30-150 kV.  Small target angles greater error.  Back Scatter not considered. Suited for medical applications
  • 4. Ellery Storm Model Thick target energy loss as an integral of thin target energy loss: E0  dE  dE = Energy loss in thin strip of target I E0 ,K = ∫ I E0 ,k ,E   E >k  −dE /dx  E = Initial electron energy at photon emission Correction for electron backscatter losses, photon attenuation and target angle E0  dE  I E0 ,k = ∫k E> I E0 ,k ,E  (1−ηε E 0 ,k )*exp( −µ k x/ tanα )  −dE /dx  Emission per unit solid angle in the photon energy −3 k 11 ( E0 −k )(1−e ) Ek 1.0 I E0 ,k ≅( Z ) f E0 ,k ,α 4π 1 E0 ( k / E0 ) 3 (1−e Ek ) 40 kV 60 kV Photon Attenuation Correction Factor C E0 , k f E0 ,k ,α ≅ exp(−0.2C E0 ,k ℜ E0 µ k / tan α ) 100 kV 0.5 200kV E0  Initial Electron Energy Ek  K Edge Energy 300 kV K  Photon Energy 0.0 10 20 40 Z  Atomic Weight Photon Energy (keV) Best suited for industrial applications
  • 5. Photon Fluence /mR & Average Energy Photon Fluence per Roentgen Photon Fluence 4.E+10 3.E+10 / mR 2.E+10 1.E+10 Photon Fluence /mR = ∫Θ( E )*E*dE 0.E+00 ∫Θ( E )*(µ ( E )/ ρ )*E*dE 0 50 100 150 200 250 300 350 Average Energy Average energy 70 60 Average energy kev no filter Average Energy = ∫Θ( E )*dE 50 40 1 mm aluminium 2 mm aluminium ∫dE 30 20 3 mm aluminium 4 mm aluminium 10 5 mm aluminum 0 0 50 100 150 kVP Literature data available below 150 kVp
  • 6. Model Performance Verification Average Energy Vs. kvp (Simulation) Photon Fluence per roentgen Vs. Average Energy (Simulation) 140 120 3.00E+05 Average Energy Thick = 1mm Photon Fluence / mR 100 Thick = 2mm 2.50E+05 Thick = 1mm 80 Thick = 3mm 2.00E+05 Thick = 2mm 60 Thick = 4mm 1.50E+05 Thick = 3mm 40 Thick = 5mm 1.00E+05 Thick = 4mm 20 Thick = 5mm 5.00E+04 0 0.00E+00 0 100 200 300 400 500 0 20 40 60 80 100 120 140 kvp Average Energy Average Energy Vs. kvp Photon Fluence / mR Vs. Average Energy (Simulation & Liturature) (Simulation & Literature) 140 3.E+05 Photon Fluence / mR 120 3.E+05 Average Energy 100 2.E+05 80 Thick = 5mm, Simulation 2.E+05 60 Thick = 5mm, Literature 1.E+05 Thick = 5mm, Simulation 40 Thick = 5mm, Experimental 5.E+04 20 0 0.E+00 0 20 40 60 80 100 120 140 0 50 100 150 200 250 300 350 400 450 kvp Average Energy High accuracy in the range of 30 – 150 kVp
  • 7. HVL Study: Comparison with NIST Data Tube HVL Dose Dose Potential Inherent (mm) - Before After Cases (KvP) Filter Added Filter Object NIST Object Object % Error 1 100 1 mm Be % Difference in HVL 1.98 mm Al Al 2.77 12.668 6.744 -6.475 2 100 3 mm Be 5 mm Al Al 5.02 6.080 3.043 -0.106 3 100 8 3 mm Be 4 mm Al + 5.2 mm Cu Al 13.5 0.025 0.012 2.393 4 100 6 3 mm Be 4 mm Al + 5.2 mm Cu Cu 1.14 0.025 0.012 3.496 5 120 3 mm Be 6.87 mm Al Al 6.79 6.887 3.440 0.100 6 150 4 3 mm Be 5 mm Al + 0.25 mm Cu Al 10.2 8.405 4.177 0.610 % Difference 7 150 3 mm Be 5 mm Al + 0.25 mm Cu Cu 0.67 8.405 4.125 1.851 8 150 2 3 mm Be 4 mm Al + 4 mm Cu + 1.51 mm Sn Al 17 0.187 0.092 2.147 9 150 3 mm Be 4 mm Al + 4 mm Cu + 1.51 mm Sn Cu 2.5 0.187 0.087 7.005 10 200 0 3 mm Be 4.1 mm Al + 1.12 mm Cu Al 14.9 9.782 4.831 1.217 11 200 3 mm Be 4.1 mm Al + 1.12 mm Cu Cu 1.69 9.782 4.785 2.169 12 200 -2 3 mm Be 4 mm Al + 0.6 mm Cu + 4.16 mm Sn + 0.77 mm Pb Al 19.8 0.141 0.070 1.665 13 200 -4 3 mm Be 4 mm Al + 0.6 mm Cu + 4.16 mm Sn + 0.77 mm Pb Cu 4.1 0.141 0.068 4.188 14 250 3 mm Be 5 mm Al + 3.2 mm Cu Al 18.5 9.624 4.740 1.504 15 250 -6 3 mm Be 5 mm Al + 3.2 mm Cu Cu 3.2 9.624 4.695 2.425 16 250 3 mm Be 4 mm Al + 0.6 mm Cu + 1.04 mm Sn + 2.72 mm Pb Al 22 0.206 0.101 2.119 17 250 -8 3 mm Be 4 mm Al + 0.6 mm Cu + 1.04 mm Sn + 2.72 mm Pb Cu 5.2 0.206 0.102 0.613 18 300 3 mm Be 75 125 4 mm Al + 6.5 mm Sn 175 225 Al 27522 4.395 2.169 325 1.280 19 300 3 mm Be 4 mm Al + 6.5 mm Sn Cu 5.3 4.395 2.201 -0.149 20 300 3 mm Be kVp 4.1 mm Al + 3 mm Sn + 5 mm Pb Al 23 0.164 0.083 -0.839 21 300 3 mm Be 4.1 mm Al + 3 mm Sn + 5 mm Pb Cu 6.2 0.164 0.086 -4.415 % Difference in HVL between NIST and simulation is within +/- 8%
  • 8. Experimental Dose Measurement Experimental Conditions: Simulation Conditions: X-Ray Tube: Target Voltage : 20 < kV < 420 kVp Current : 1 mA 1. KM16010E-A MicroFocus Target Material – W 2. Seifert ISOVOLT 420/10 Dose = 1.828*10-11∑φ(E).(µ(E)/ρ) air.E.dE Dosimeter: Keithley 35050A Dosimeter % Difference in Dose : Kevex, SDD = 1m % Difference in Dose: Seifert, SDD = 1m (Experimental and Simulated) (Experimental and Simulated) 6 8 0.4 mm Cu Filter 4 6 9 mm Al Filter 4 % Difference 2 % Difference 2 0 0 -2 -2 -4 0.4 mm Cu Filter -4 -6 9 mm Al Filter -6 -8 -8 30 50 70 90 110 130 150 170 30 130 230 330 430 Tube Potential (kvp) Tube Potential (kvp) KM16010E-A MicroFocus Seifert ISOVOLT 420/10 Less than 7% difference is observed between simulation and experiments
  • 9. Summary  Ellery Storm Model best suited for X-ray Spectrum Generation  Model performance metrics:  Accuracy for Photon Fluence / mR > 95%  Error in Average Energy < 5%  Deviation in HVL < 8%  Simulated Dose is in good agreement with Experiments