Optimization studies on pgnaa coal analysis improvement for patent development
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Optimization Studies on PGNAA Coal Analysis Improvement for Patent Development. Jiaxin Wang and Robin P. Gardner . Oct 6 th 2011, CEAR at NC State University, Raleigh, NC. Agenda. 1. Overview 2. Detector Response Function 3. Code CEARCPG 4. Prompt Gamma-ray Modeling

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Optimization Studies on PGNAA Coal Analysis Improvement for Patent Development

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Optimization studies on pgnaa coal analysis improvement for patent development

Optimization Studies on PGNAA Coal Analysis Improvement for Patent Development

JiaxinWang and Robin P. Gardner

Oct 6th 2011, CEAR at NC State University, Raleigh, NC


Agenda

Agenda

1. Overview

2. Detector Response Function

3. Code CEARCPG

4. Prompt Gamma-ray Modeling

5. Simulation Results

6. Mc(do)lls Quantitative Analysis

7. Conclusions and Future work


Overview pgnaa

Overview-PGNAA

Pb

S

Ca

Hg

Excited level

Pb

C

S

Hg

O

Mg

Pb

C

S

C

O

Mg

Ground level

Ca

Neutron Source

Ca

S

Hg

S

O

Bulk sample

3


Overview pgnaa1

Overview-PGNAA

  • Disadvantages

    • Inherently large background

      • Interference from the neutron excitation source.

      • Natural background

      • Structure materials

      • Detector activation (NaI)

      • Summing and pulse pile-up effect

      • Hydrogen Peak

  • Advantages:

    • Nondestructive

    • Simultaneous

    • In Situ

    • Quantitative

    • sensitive to the entire periodic table.

    • shape of the sample are relatively unimportant.


Overview cpgnaa

Overview-CPGNAA

  • Solution: introduce gamma – gamma coincidence technique

  • Advantages

    • Increase the signal – to – noise ratio

    • Reduce the interference of background

    • Eliminate the hydrogen prompt gamma-ray peak

  • Disdvantages

    • The coincidence response is about 2 order of magnitude lower than single response

    • Long measurement time


Overview cpgnaa1

Overview-CPGNAA

  • Source  Bulk Sample  Detector

  • Reach maximum prompt gamma ray/coincidence prompt gamma ray counting rates under certain neutron source (cf-252) strength


Overview mc simulation

Overview-MC Simulation

MCNP5

The general purpose Monte Carlo simulation

parameter study, distribution maps

CEARCPG

Specified code for prompt gamma and coincidence prompt gamma

Pulse height spectra, elemental library spectra

Computation power

CEAR ‘Spectral’ cluster with 41 running nodes, each with a Quad-core CPU.


Overview mc simulation1

Overview-MC Simulation

  • Detector response function-> More scintillators, more shapes, more size, etc.

    -> New DRF generation code – CEARDRFs

  • CEARCPG was written for serial computation only

    -> Parallel feature implement of CEARCPG

  • MCLLS Quantification

    -> Differential Operator implement in CEARCPG


Overview quantification

Overview-Quantification

  • Peak analysis

    • Matrix effect?

    • Detector resolution (NaI, BGO, or HPGE)?

  • Monte Carlo Library Least Square


Overview quantification1

Overview-Quantification

MCLLS - procedure

Compositions of a unknown sample are assumed and the PGNAA measurement is simulated

Elemental library spectra are generated with the simulation

Least-squares fit for the experimentally measured sample spectrum to obtain compositions of it.

Compare calculated values with the originally assumed ones, if not close enough, repeat the process from step 1.


Agenda1

Agenda

1. Overview

2. Detector Response Function

3. Code CEARCPG

4. Prompt Gamma-ray Modeling

5. Mc(do)lls Quantitative Analysis

6. Conclusions and Future work


Drf mc simulation

DRF-MC simulation

Because the same detector has been repeatedly used under different situations, the particle-transport inside the detector (DRF) could be pre-calculated through MC simulation to improve future simulation speed and accuracy.

MCNP5

General purpose for neutron, photon and electron transport

G03

Specific for Cylindrical NaI detector

*CEARDRFs

For more shapes, more scintillation detector: BGO, plastic, etc.


Drf advantages

DRF-Advantages

  • (1) on the order of one-half of the calculations per history can be omitted by the use of a DRF

  • (2) use of the DRF has a natural smoothing effect which reduces the number of histories necessary for the desired accuracy by a factor of about 100

  • (3) use of the DRF yields better accuracy in spectral simulations because they can be more accurate than calculations of particle transport with existing physics inside the detector.


Drf simulation vs exp

DRF-Simulation VS Exp

  • Compton Edge

  • Flat continuum

  • X-ray escape peaks from BGO


Drf simulation vs exp1

DRF-Simulation VS Exp


Drf accuracy and speed

DRF-Accuracy and Speed

The DRFs generated by CEARDRFs have much better agreement with experiments than commonly used MCNP5

The speed of CEARDRFs is very fast. It costs 69 seconds for 2.754 MeV energy and 29 seconds for 0.662 MeV, which almost hundreds of times faster than original MCNP5. Thus, a complete set of DRF could be simulated in a reasonable time.


Drf usage

MC simulation outside detector (CEARCPG)

DRF-Usage

Convolute the incident gamma flux with DRF

Simulated pulse height spectra

Elemental analysis

DRF generation (CEARDRF)

Experimental spectra

1. A complete set of DRF needs to be generated by MC simulation, i.e. CEARDRFs. For example, an energy range from 0 to 11 MeV in 1024 channels.

2. Build up the model of surrounding geometry of detector, run the MC simulation to record the photon energy flux reaching the detector surface and its path length.

3. Adjust the photon weight according to the path length and convolute the recorded energy flux with DRF to get the final simulated spectra.


Agenda2

Agenda

1. Overview

2. Detector Response Function

3. Code CEARCPG

4. Prompt Gamma-ray Modeling

5. Simulation Results

6. Mc(do)lls Quantitative Analysis

7. Conclusions and Future work


Cearcpg overview

CEARCPG-Overview

CEARCPG (Han, 2005) was developed as the first specific code that can be used to simulate both the single and coincidence spectrum of coincidence PGNAA, including relatively complicated neutron and photon transportation.

The most important contribution of CEARCPG is a new algorithm is developed to sample the neutron-produced coincidence gamma-rays following nuclear structure.


Cearcpg parallel implement

CEARCPG-Parallel implement

Random seeds generated and distributed to slave nodes

File I/O path preparation

Master node collects recorded data from each slave nodes


Cearcpg do

CEARCPG-DO

The Differential Operator method is very powerful tool for measurement sensitivity study and system optimization. The basic idea of the differential operator technique is, if the magnitude of perturbation is very small, the ratio of changed response can be found by using Taylor series expansion.


Cearcpg comparison

CEARCPG-comparison


Agenda3

Agenda

1. Overview

2. Detector Response Function

3. Code CEARCPG

4. Prompt Gamma-ray Modeling

5. Simulation Results

6. Mc(do)lls Quantitative Analysis

7. Conclusions and Future work


Prompt gamma ray modeling

Prompt Gamma-ray Modeling

Source

Moderator

Bulk sample

Detector 1

Detector 2

  • General optimization

  • Moderator

  • Neutron distribution

  • Prompt gamma-ray distribution

  • Detector

    • Cross-section

    • Detector Efficiency

    • Neutron response

    • Plastic detector setup

  • Geometry arrangement

    • Lab sample

    • Large sample


  • Modeling neutron maps

    Modeling-Neutron Maps

    Neutron capture rate

    Thermal neutron

    Fast neutron(1-10MeV)

    Radioactive capture reaction happens all through the coal sample with highest production in the center area, if the source is placed under the sample

    Thus, it is better to place the source under the large size bulk sample. No moderator is needed as the self moderation of sample is enough for 252Cf neutron source


    Modeling photon maps

    Modeling-Photon Maps

    • Photon flux spatial distribution maps around the large rectangular shape coal sample and the conveyor belt shape coal sample.

    In coincidence detection, it is better to place the detectors facing the top and bottom surfaces separately if possible. Otherwise, placing the two detectors together on the opposite side of neutron source is also a good arrangement.


    Modeling geometry

    Modeling-Geometry

    Lab size sample (55cm x 9.7cm x 6.7 cm)

    6”x6” NaI Cylindrical detector

    2”x4”x16” Slab NaI detector


    Modeling geometry1

    Modeling-Geometry


    Modeling geometry2

    Modeling-Geometry


    Modeling geometry3

    Modeling-Geometry

    Thinner paraffin (7.3cm)will increase the overall detector response about a factor of 4.3 and3.4for single andcoincidence, respectively.

    Changing the 6”x6” detectors position from bottom to left-right sides can further increase the overall detector response another factor around 1.6 and 3.8.

    Two slab detectors replacing the 6”x6” cylindrical NaI detectors can gain another increase of a factor around 9.5 and 17.2.

    In sum, the slab detector left-right arrangement can detect around 65 and 223 times more gamma-ray events than the reference setup.

    The ratio of increase (ROI) for different setup as a function of energy: Higher efficiency for higher energy


    Modeling geometry4

    Modeling-Geometry

    * All ROI values are calculated based on reference setup


    Modeling geometry5

    Modeling-Geometry

    Large size sample (25cm x 100cm x 100 cm)

    6”x6” NaI Cylindrical detector

    2”x4”x16” Slab NaI detector

    70cm x 50cm x 10cm plastic detector


    Modeling geometry6

    Modeling-Geometry


    Modeling geometry7

    Modeling-Geometry


    Modeling geometry8

    Modeling-Geometry

    Replacing the two 6”x6” cylindrical detectors with two 2”x4”x16” slab NaI detectors could gain the ROI of 1.6 and 6.2 in single response and coincidence response, respectively

    The plastic/NaI special setup could gain the ROI of 2.5 and 1.7.

    NaI detector in the special setup has a better efficiency to high energy gamma-rays in single response while the slab detectors setup has better efficiency to high energy gamma-rays in coincidence response


    Agenda4

    Agenda

    1. Overview

    2. Detector Response Function

    3. Code CEARCPG

    4. Prompt Gamma-ray Modeling

    5. Simulation Results

    6. Mc(do)lls Quantitative Analysis

    7. Conclusions and Future work


    Results

    Results

    Through CEARCPG, the 2D coincidence spectrum of these setups has been simulated with a coal sample (H-2.892%, C-5.28%, N-%1.4, O-5.487%, Na-1.121%, Al-2.38%, Si-1.943%, S-5.6%, Cl-1.729, Hg-2.168%).

    Three setups: slab detectors for lab and large sample, the special setup with plastic detector.


    Results1

    Results


    Results plastic projection

    Results-Plastic Projection


    Results interference

    Results-Interference

    Fission gamma and prompt gamma-rays from structure materials still contribute to true coincidence.


    Results interference1

    Results-Interference

    Everything source of gamma-rays could be included in the coincidence response through chance coincidence.

    When , The chance coincidence counting rate is only 2% of the true coincidence rate.

    However, when the single detector counting rate increases to 105/s the chance coincidence counting rate is 20% of the true coincidence rate


    Results dose rate

    Results-Dose Rate

    MCNP5 F4 mesh tally and FM card (flux-to-dose conversion factor for human)

    For neutron and photon separately.

    If a 10 microgram (μg) source is used, it is allowed to stay close the device behind the shielding material for 2000 hours annually, even under the public limits


    Agenda5

    Agenda

    1. Overview

    2. Detector Response Function

    3. Code CEARCPG

    4. Prompt Gamma-ray Modeling

    5. Simulation Results

    6. Mc(do)lls Quantitative Analysis

    7. Conclusions and Future work


    Mc do lls

    MC(DO)LLS

    Two coal samples

    Two set of libraries


    Mc do lls do results

    MC(DO)LLS-DO results


    Mc do lls fitting results

    MC(DO)LLS-Fitting Results

    • Sample 2, the results of both sulfur and mercury are improved through Q-value projection.

    • Sample 1, the result of sulfur is improved while the result of mercury has degradation.

    • This result is reasonable since there is little interference in the high-energy window. The reason of mercury result in sample 1 is that the 8-9 MeV windows is too close to Mercury Q-value to include the whole peaks.

    • When the concentration of Mercury is low as in sample 1, the benefited of less interference might be canceled out by the drop of signal due to energy window projection.


    Agenda6

    Agenda

    1. Overview

    2. Detector Response Function

    3. Code CEARCPG

    4. Prompt Gamma-ray Modeling

    5. Simulation Results

    6. Mc(do)lls Quantitative Analysis

    7. Conclusions and Future work


    Conclusions

    Conclusions

    1. A new code named CEARDRFs has been developed to generate pretty accurate detector response function at a very fast speed to improve accuracy and efficiency of CEARCPG.

    2. Parallel computation feature has been implemented in CEARCPG by a simple script approach, which dramatically simplified the job while keeping all the original features and could nearly reach the ideally linear speed-up feature.

    3. With derivatives to second order Taylor expansion, the DO has also been implemented into CEARCPG and validated, including the consideration of collision kernel, transportation kernel and variance reduction kernel.


    Conclusions1

    Conclusions

    4. For lab size sample, replacing the detectors with two 2”x4”x16” slab NaI detectors could gain the ROI of 66.5 and 223.7 for single and coincidence response, with higher efficiency for higher energy gamma-rays.

    5. For large size sample, two 2”x4”x16” slab NaI detectors setup could gain the ROI of 1.6 and 6.2 in single response and coincidence response, respectively and the special setup of plastic VS NaI could gain the ROI of 2.5 and 1.7. The NaI detector in the special setup has a better efficiency to high energy gamma-rays in single response while the slab detectors setup has better efficiency to high energy gamma-rays in coincidence response


    Conclusions2

    Conclusions

    6. The simulated 2D coincidence spectra show the feasibility of using the plastic detector as a trigger to another detector that has better energy resolution.

    7. Among all the interference, in the total coincidence spectra, the fission gamma remains the major factor while the interference from structure material still contributes.

    8. Q-value projection on the 2D spectra could further suppress the interference. The MCLLS analysis on the Q-value projected spectra shows better accuracy than using the total coincidence spectra.

    9. With proper shielding, the dose rate around the analyzer is pretty low.


    Future works

    Future Works

    1. Validate the results with benchmark experiments,

    2. New elemental analysis method is also need to be developed with elemental libraries, eg. Restraind LLS, true 2D LLS.

    3. Other neutron sources like D-T generator are worth a look.

    4. Looking for more complete nuclear structure data, especially angular correlations between prompt gamma-rays

    5. The light transport in large size detector is also an interesting area to look.


    Thank you

    Thank you!

    The authors are also grateful for the financial support of CEAR through the Associates Program for Nuclear Techniques in Oil Well Logging presently supported by Baker Hughes, Weatherford, EXXON Mobil, Halliburton, Pathfinder, and Los Alamos National Laboratory

    Questions and comments?


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