Coordinated Activities on Evaluation of Collisional Data for Fusion Applications

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Coordinated Activities on Evaluation of
Collisional Data for Fusion Applications

• H.-K. Chung and B. J. Braams
• Atomic and Molecular Data Unit, Nuclear Data
  Section
• Division of Physical and Chemical Sciences, IAEA,
  Vienna
• October 1-4, 2012
• ICAMDATA-8, Gaithersburg, MD

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Contributors to this presentation (direct)

• I. Murakami, D. Kato, T. Nakano, Y. Itikawa, Y.
  Nakamura, Alex M Imai, H. Takagi, T. Kato, F.
  Koike (Japan), G.W.F. Drake, D. R Schultz, A.
  Kramida, P. Krstic, E. Landi, C. Ballance (USA),
  J.-S. Yoon, M-Y. Song, H. Cho, C.-G. Kim, J.-O.
  Choi (Korea), J. Yan, G. Liang (China), M.
  O'Mullane, N. Mason, K. Aggarwal (UK), D. Reiter,
  D. Coster, J. Roth (Germany), V. Kumar (India),
  S. Buckman (Australia), V. Shevelko (Russia), G.
  Karwasz (Poland), S. Lisgo (ITER)

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Outline

• IAEA Atomic and Molecular Data Unit
• Needs of Evaluated Data for Fusion Applications
• IAEA Coordinated Activities on Evaluation of
  Collisional Data for Fusion Applications
• Future Activities

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IAEA atomic and molecular Data Unit

• Who we are and why we are here

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IAEA Accelerate and enlarge the contribution of
atomic energy to peace, health and prosperity

• Assists its Member States, in the context of
  social and economic goals, in planning for and
  using nuclear science and technology for various
  peaceful purposes, including the generation of
  electricity.

• IAEA AM Unit formed in 1977
• 1976 at Culham Laboratory, UK
• Review progress and achievements of AM/PSI data
  for Fusion program
• Stimulate international cooperation in
  measurement, compilation and evaluation of
  AM/PSI data for fusion

155 Member States 2200 Staffs
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International Coordination of AM/PSI Data
Research for Fusion
Consultants Meetings (CM)
Publications (INDC, APID, Bulletin)
Coordinated Research Projects (CRP)
Fusion Plasma Modelling
Theories
Measurements
Technical Meetings (TM)
Data Compilation
Data Production
Databases (AMBDAS, GENIE, ALADDIN, Wiki)
Data Evaluation
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Online AM/PSI Data Services http//www-amdis.iae
a.org
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Network Collaboration for AM/PSI Data for Fusion
Fusion Laboratories ITER EFDA JET,
UKAEA ASDEX-Upgrade, IPP TEXTOR, Jülich,
FZJ KSTAR, NFRI NIFS, JAEA PPPL, ORNL
Data Users
Data Centre Network ADAS, Summers H. CRAAMD,
Jun, Y. IAEA, Braams, B. J. JAEA, Nakano, T.
KAERI, Rhee, Y. Kurchatov, Martynenko, Yu.
NIFS, Murakami, I NIST, Wiese, W.L. NFRI, Yoon,
J ORNL, Schultz, D. R.
Code Centre Network Curtin Univ. I. Bray
Kitasato Univ. F. Koike Univ. Autonoma de
Madrid I. Rabadan Univ. PM. Curie, Paris, A.
Dubois Univ. of Bari, M. Capitelli Kurchatov
Institute, A. Kukushkin Lebedev Institute, L.
Vainshtein FZJ, D. Reiter Ernst-Moritz-Arndt
Univ, R. Schneider NIST, Y. Ralchenko PPPL,
D. Stotler LANL, J. Abdallah Jr. IAEA, B. J.
Braams HULLAC M. Klapisch CNEA, P.D.
Fainstein
Data Producers
Data Centres Evaluators
IAEA Coordination CRP Publications Knowledgebase
Databases Meetings
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Data Users Need Evaluated and recommended data

• Code Centre Network Meeting (October 2010)
• CCN is organized to improve Online Code
  Capabilities to provide needed data for Data
  Users, particularly, Plasma Modellers
• Data Users (D. Coster, D. Reiter, R. Schneider,
  D. Elder) participated to interact with the code
  producers
• Discussions
• Online Codes generate too many data sets without
  quality information
• Data Users need Complete sets and/or Recommended
  data
• At every meeting, data evaluation / quality was
  an issue
• IAEA Meetings
• VAMDC (Compilation Distribution) ? SUP_at_VAMDC

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Needs of Evaluated Data for Fusion Applications

• From users perspectives

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Typical edge transport code runtime (for same
model, same equations, same grid size)
ITER (R6.2 m), Cadarache, FRA
3 months
JET (R2.96 m), Oxford, UK
TEXTOR (R1.75 m) Jülich, GER
1-2 weeks
1 day
Because of more important plasma chemistry
(increased non-linearity, non-locality, in
sources).
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Requirement for Plasma Modelling Reliable data
sets for AMNS data

• Data needs to be verified by an expert
• Data needs to be robust
• Data needs to be comprehensive
• Data needs to be easy to use
• Version control know what data was used for a
  particular run, and which runs used a particular
  version of the data
• Needs to be efficient
• Needs to be able to address special needs

Require a Recommended Internationally Agreed
Library for Atomic, Molecular, Nuclear, Surface
Data
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IAEA Activities on evaluation and recommendation

• A series of meeting to organize community efforts
  for evaluation and recommendation of AM/PSI Data

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Data Centre Network Meeting (2011)

• Data Evaluation Tasks are Difficult
• Lack-of man-power Experts retiring or leaving
  the field
• No young people get in the field (no publication,
  no funding)
• Evaluation requires multiple sets Too many or
  too few
• Very few benchmark experiments for collisional
  data
• Even fewer uncertainty estimates for theoretical
  data
• Conclusions
• Data should be first collected and available for
  evaluation
• Evaluation activities should be organized in the
  community
• Evaluation guidelines should be established in
  the community
• A list of recommended data sets should be
  available as a final product
• Current status
• NIST Critical evaluation of atomic structure and
  transition probabilities
• NFRI/KRISS National efforts to establish
  standard data sets
• NIFS/JAEA Evaluated data libraries,
  Collaboration
• IAEA/ORNL ALADDIN, individual consultancies

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Coordination Meetings for Evaluationhttp//www-am
dis.iaea.org/DCN/Evaluation/
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IAEA-NFRI TM on Data Evaluationhttp//www-amdis.
iaea.org/meetings/NFRI2012/

• 24 Presentations (2.5 days) and 1 day Technical
  Discussions
• Topics (Focused on Reaction Data)
• Current Evaluated Databases (Kramida, Landi,
  Mason)
• Evaluation Methods and Experiences (Itikawa,
  Kumar, Cho, Karwasz)
• Error Propagation and Sensitivity Analysis
  (OMullane, Ballance, Reiter, Krstic)
• Theoretical Data Evaluation (Aggarwal, Liang,
  Takagi, Song)
• Experimental Data Evaluation (Nakamura, Buckman,
  Shevelko, Imai)
• Data Centres Evaluation Activities (Yoon,
  Murakami, Mason, Chung)
• Participants from Australia, China, Germany,
  India, Japan, Korea, Poland, Russia, UK, USA and
  IAEA.

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Summary of Discussions

• Community Role
• Involve the community in data evaluation
• Engage young generation for transfer of knowledge
• Define terminology and vocabulary used in
  evaluation
• Define common workflow guidelines
• Technical Issues
• Assessment for theoretical data
• Assessment of experimental data
• Error propagation and Sensitivity Analysis

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Community Role Consensus Building

• Change of notions Databases ? Data research
• Engage young generation (in early career)
• Culture should teach that data evaluation is a
  critical part of scientific work
• Publication Issues Review publications are good
  for career development
• Funding Issues Evaluation leads to the gap of
  understanding of the field and finds interesting
  problems
• Disseminate materials to train students and
  researchers with the Critical Analysis Skills
• Disseminate the standard definitions of
  terminologies adopted by international
  organizations (IAEA, IUPAC, IUPAP, BIPM, ISO,
  WHO, FAO, etc)
• Agree on the procedure of evaluation towards a
  standard reference data

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Define Terminology Uncertainty ApproachIts NOT
AN ERROR but AN UNCERTAINTY

• Terminology in metrology
• VIM (Vocabulaire International de Métrologie,
  Bureau Int. des Poids et Measures) 2007
• GUM (guide to the expression of uncertainty in
  measurement) 2008
• Measurement and uncertainty
• The objective of a measurement is to determine
  the value of the measurand (GUM)
• In general, a measurement has imperfections that
  give rise to an error in its result.
• Error 1 Measurement result True value (Error
  approach)
• True value value consistent with the definition
  of a given particular quantity
• Error 2 Measured value Reference value
  (Uncertainty approach)
• Reference value (Assigned value) The reference
  quantity value can be a true quantity value of
  the measurand, in which case measurement error
  is unknowable, or an appropriate, known quantity
  value such as a conventional quantity value or a
  specified target quantity value to be realized
  in a production process.

uncertainty
value
value and uncertainty
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Any measurement has an uncertainty
Value and uncertainty
Time, method, place, person, procedure
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Uncertainty Approach based on VIM GUM The
true value lies within the uncertainty range
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Common Workflow Guidelines for Evaluation of
Collisional data

• Advantages
• Easier to expand the evaluators network
  including early career researchers.
• Introduce more rigorous procedures for evaluation
  and increases the dependability of the
  evaluation.
• Disadvantages
• The quality of evaluation critically depends on
  the experiences of the evaluators.
• It is possible that different people may reach at
  different conclusions using the same guidelines
  and the results may not be reproducible.
• Solutions
• Collaborations can help reducing the
  disadvantages.
• Evaluation activities by scientific advisors and
  editorial panels will be a great mechanism to
  produce the evaluated data library.

Workflow of critical evaluation of data on
wavelengths and energy levels (NIST)
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Evaluation by Editorial Board Panel

• Evaluation and recommendation require the
  community consensus with an endorsement from the
  IAEA or other international authorities
• Establishment of the evaluation guidelines will
  evolve with time and experience with broad
  collaborations from the community
• Group Evaluation 4-5 panelists including young
  and senior people like the editorial board for a
  journal with the broad backgrounds
  (experimentalists, theoreticians, producers and
  users)
• Self-Evaluation Data producers with a deep
  knowledge in some cases. May work better for
  theoretical data sets.
• Merits of Group Evaluation
• Facilitate the knowledge transfer to younger
  generation
• Review papers can be written for the evaluation
  work
• Make the data research project visible to the
  Community

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An example of evaluation towards a Standard
Reference Data Evaluation (NFRI)
Final Evaluation (Panel Decision)
1st evaluation (experts)
Data Compilation
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Summary of Discussions

• Community Role
• Involve the community in data evaluation
• Engage young generation for transfer of knowledge
• Define terminology and vocabulary used in
  evaluation
• Define common workflow guidelines
• Technical Issues
• Assessment for theoretical data
• Assessment of experimental data
• Error propagation and Sensitivity Analysis

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Theoretical Data Evaluation

• No criteria of assessments for theoretical data
• A Critical need guidelines for uncertainty
  estimates of theoretical data
• Should not try to give a straight recipe for
  assessing uncertainties, however, there are still
  several to start with.
• There are prescriptions such as energy grids for
  resonances and partial waves.
• One may take a model to see a convergence and
  estimate uncertainties based on assumptions
  within the model.
• Comparisons with experiments this can be
  dangerous.
• Comparisons among different theories if some
  theories are better than another, it may be given
  a benchmark status.
• For scattering data maybe we should aim for
  ideas or suggestions rather than
  guidelines.
• Theoreticians may have an idea of uncertainty
  estimates already
• Journal policies can change the culture PRA
  policies

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Experimental Data Evaluation

• Check Lists
• Uncertainty estimates or error assessment
  critical
• Self-consistencies checked
• Experimental techniques evaluated.
• Reputation of the data producer considered
• Anomalies in some experimental processes
  (ro-vibrational / metastable)
• Wish Lists
• Evaluation by a group of established experts
  with broad expertise
• Provide Recommended values where possible
• Include a comparison with theory and an
  assessment of overall status
• Evaluation will lead to the understanding of the
  gaps of the field
• Establish benchmarks where possible

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Error Propagation and Sensitivity Analysis
Uncertainties in Data Data Processing
Toolbox ?

• Atomic structure
• collision codes
• fundamental data
• Processed data (rate coef.)
• CR transition matrix A
• A_excitation A_radiative
• A_ionization A_recombination
• A_charge-exchange .
• effective rates,
• population coefficients
• cooling rates,
• beam stopping rates,.

experimental data
Velocity distribution Boltzmann
solver, Maxwellian
Monte Carlo
Linear algebra, ODE solvers
Sensitivity,error propagation to final model
results PDEq, IDEq, leave to modelers, spectrosc
opists
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Future activities

• Need the community feedback and support

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Near-term goals

• Priorities for evaluation
• Electron scattering on Beq. (IAEA CRP)
• Electron scattering on CH4. (NFRI group)
• Charge exchange and electron loss for H on Beq.
• Action Items
• Developing an evaluators network Key people
  identified
• Inventorise datasets that are now used by fusion
  plasma modellers
• Sketch out guidelines for uncertainty assessment
  of theoretical data
• Organize a workshop (SUP_at_VAMDC)
• NFRI to organize a data evaluation group for
  demonstration
• The ITER project should recognize the need of
  standard reference data (SRD) for AM processes
  used in the design

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Long-term goal.
Global Network towards the Internationally Agreed
Data Library for Fusion and other Plasma
Applications
Data Needs
Data Users
Data Compilation, Evaluation and Recommendation
Data Evaluators
Experimental and Theoretical Data Production
Data Producers
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The development of a standard library Document
data sets used by the fusion community

• Priority List of Critically Needed Data
• Database of Available Data for Evaluation
• Basis of Evaluated Data Library

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Evaluation of evaluated data setsa prototype of
evaluated data library
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Summary

• The series of IAEA meetings including the Joint
  IAEA-NFRI TM on Data Evaluation were highly
  successful in drawing consensus from participants
  on the coordinated data evaluation activities by
  the community.
• Disseminate the concepts of VIM3 (International
  Vocabulary of Metrology), GUM (Guide to the
  expression of Uncertainty in Measurement) and
  Critical Assessment Skills
• Engage younger generation in the process
• Collaborate with colleagues in the community
• Change the culture about data research with
  publications
• IAEA AM Data Unit will actively participate in
  organizing and coordinating the community effort
  in the data evaluation activities, ultimately
  towards the standard data library for fusion
  applications.
• Assess the needs of user communities
• Collaborate with SUP_at_VAMDC
• We urge you, the community to join us in the data
  evaluation activities that will benefit data
  users, producers and evaluators in the future.