# Use of integrated models to interpret measurements

Anna Medvedeva

► To cite this version:

Anna Medvedeva. Use of integrated models to interpret measurements. Doctoral. 14th ITER International School, France. 2025, pp.47. [hal-05404636](https://hal.science/hal-05404636v1)

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https://hal.science/hal-05404636v1

Submitted on 8 Dec 2025

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<figure><img src="image_1.png" /></figure>

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# Use of integrated models to interpret measurements

<figure><img src="image_2.png" /></figure>

Anna Medvedeva Glasser – M2P2, Aix-Marseille University, École Centrale Méditerranée

ITER International School – Aix-en-Provence, 2025
# Why interpretation of measurements matters

<figure><img src="image_3.png" /><figcaption>Visualisation of plasma in a tokamak @2024 EPFL/Laboratory for Experimental Museology (EM+) – CC-BY-SA</figcaption></figure>

REALITY
Why interpretation of measurements matters

<figure><img src="image_4.png" /><figcaption>Visualisation of plasma in a tokamak @2024 EPFL/Laboratory for Experimental Museology (EM+) – CC-BY-SA</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>JET pulse visible range camera image</figcaption></figure>
Why interpretation of measurements matters

<figure><img src="image_6.png" /><figcaption>Visualisation of plasma in a tokamak @2024 EPFL/Laboratory for Experimental Museology (EM+) – CC-BY-SA</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>JET pulse visible range camera image</figcaption></figure>

Experimental diagnostics, numerical models and theoretical understanding often diverge
Challenges in
interpreting data

<figure><img src="image_8.png" /></figure>
Challenges in
interpreting data

<figure><img src="image_9.png" /></figure>

**CHALLENGE 1**
Measurements are not direct

**CHALLENGE 2**
Fusion devices are not transparent

**CHALLENGE 3**
Plasma physics includes complex multi-scale coupled processes
Use of integrated models to interpret measurements

<figure><img src="image_10.png" /></figure>

synthetic diagnostics
<figure><img src="image_11.png" /></figure>

1. Recognize the LIMITATIONS of experimental diagnostics

2. Learn what SYNTHETIC DIAGNOSTICS are

3. See how synthetic diagnostics help measurements INTERPRETATION
# Use of integrated models to interpret measurements

1. Recognize the **LIMITATIONS** of experimental diagnostics

2. Learn what **SYNTHETIC DIAGNOSTICS** are

3. See how synthetic diagnostics help measurements INTERPRETATION
# Use of integrated models to interpret measurements

## LIMITATIONS

### SYNTHETIC DIAGNOSTICS

### INTERPRETATION
# Diagnostics ecosystem: what they are...

## Electromagnetic:

* magnetic coils, flux loops, halo current sensors, interferometry,
* reflectometry, refractometry, polarimetry, electron cyclotron emission
# Diagnostics ecosystem: what they are...

## Electromagnetic:

magnetic coils, flux loops, halo current sensors, interferometry, reflectometry, refractometry, polarimetry, electron cyclotron emission

## Optical:

spectroscopy (visible, UV, VUV, X-ray, CXRS, MSE), H-alpha monitors, visible & IR cameras, Thomson scattering, X-ray detectors
# Diagnostics ecosystem: what they are...

## Electromagnetic:

magnetic coils, flux loops, halo current sensors, interferometry, reflectometry, refractometry, polarimetry, electron cyclotron emission

## Optical:

spectroscopy (visible, UV, VUV, X-ray, CXRS, MSE), H-alpha monitors, visible & IR cameras, Thomson scattering, X-ray detectors

## Particle-based:

Langmuir probes, neutron detectors & cameras, gamma-ray detectors, neutral particle analyzers, fast ion loss detectors, residual gas analyzers
# Diagnostics ecosystem: what they are...

## Electromagnetic:

magnetic coils, flux loops, halo current sensors, interferometry, reflectometry, refractometry, polarimetry, electron cyclotron emission

## Optical:

spectroscopy (visible, UV, VUV, X-ray, CXRS, MSE), H-alpha monitors, visible & IR cameras, Thomson scattering, X-ray detectors

## Particle-based:

Langmuir probes, neutron detectors & cameras, gamma-ray detectors, neutral particle analyzers, fast ion loss detectors, residual gas analyzers

## Calorimetric:

bolometry, calorimetry, thermocouples, calorimetric neutron monitors
# Diagnostics ecosystem: ...and what they tell us

## Magnetic diagnostics (coils, loops,...)

- Determine plasma equilibrium and current distribution

- Used for real-time control of shape and position

- Estimate stored magnetic energy
# Diagnostics ecosystem: ...and what they tell us

## Magnetic diagnostics (coils, loops,...)

- Determine plasma equilibrium and current distribution

- Used for real-time control of shape and position

- Estimate stored magnetic energy

## Neutron & fusion product diagnostics (monitors, detectors)

- Measure fusion power output

- Diagnose fast ion behavior and losses
# Diagnostics ecosystem: ...and what they tell us

## Magnetic diagnostics (coils, loops,...)

- Determine plasma equilibrium and current distribution

- Used for real-time control of shape and position

- Estimate stored magnetic energy

## Neutron & fusion product diagnostics (monitors, detectors)

- Measure fusion power output

- Diagnose fast ion behavior and losses

## Plasma-Facing & operational diagnostics (Langmuir probes, IR, RGAs,...)

- Monitor wall and divertor temperatures, erosion, and tritium retention

- Aid in machine protection and safe operation
# Diagnostics ecosystem: ...and what they tell us

## Bolometric systems

- Measure radiated power from plasma and walls

- Sensitive to impurity content and detachment behavior
# Diagnostics ecosystem: ...and what they tell us

## Bolometric systems

- Measure radiated power from plasma and walls

- Sensitive to impurity content and detachment behavior

## Spectroscopy & Neutral Particle Analysis (NPA)

- Assess impurity composition and plasma fueling

- Measure ion temperature, plasma rotation and current density

- Track particle fluxes, ionization, and edge emissions
# Diagnostics ecosystem: ...and what they tell us

## Bolometric systems

- Measure radiated power from plasma and walls

- Sensitive to impurity content and detachment behavior

## Spectroscopy & Neutral Particle Analysis (NPA)

- Assess impurity composition and plasma fueling

- Measure ion temperature, plasma rotation and current density

- Track particle fluxes, ionization, and edge emissions

## Microwave diagnostics

- Electron temperature profiles (ECE) and density profiles (reflectometry)

- Contribute to plasma position and transport studies
# From echoes and shadows: diagnostics limitations

## Indirect:

- Diagnostics measure consequences (light, particles), not direct plasma state

- Plasma and machine geometry restrict access and distort signals

## Integrated:

- Many measurements are line- or volume-integrated

## Inferred:

- Diagnostic interpretation relies on simplified or idealized models
# Phase shifted truths

## Interferometry limitations:

* Measures line-integrated electron density → requires inversion and assumptions for profiles

* Sensitive to density fluctuations, path-integrated turbulence

* Assumes known geometry and refractive index model (cold plasma approximation)

<figure><img src="image_12.png" /></figure>

from laser room 30m to detectors 30m

JET far IR interferometer, Boboc 2024 PPCF
# Untangling the radiation web

## Bolometry limitations:

* Line-integrated radiated power instead of local emissivity

* Interpretation depends on:

* View geometry

* Assumptions (for tomography) on emission distribution

* Detector spectral sensitivity

* Multiple emitters (impurity species, bremsstrahlung, reflections)

<figure><img src="image_13.png" /><figcaption>ITER bolometry system ©Adam Pataki IPP</figcaption></figure>
# Line of sight, layers of assumptions

## Spectroscopy limitations:

* Sensitive to:

* Instrument function
  (spectral/spatial resolution)

* Atomic models
  (excitation, ionization rates)

* Viewing geometry

* Often assumes coronal equilibrium, may not hold

* Emission often integrated along complex lines of sight

<figure><img src="image_14.png" /><figcaption>ASDEX Upgrade CXRS system ©Athina Kappatou IPP</figcaption></figure>
# Direct contact, distorted truth

## Langmuir probes limitations:

* Perturbs local plasma (especially in high-temperature regions)

* Interpreted via Debye sheath theory, assumes:

* Maxwellian electrons

* Collisionless sheaths

* Mostly used in edge/SOL where assumptions are already strained

<figure><img src="image_15.png" /><figcaption>KSTAR Langmuir probes</figcaption></figure>
Fragmented measurements → coherent understanding

Experimental data: indirect, integrated, inferred

Diagnostic signals require:

* Modeling of diagnostic response

* Inversion to retrieve physical quantities

* Cross-validation across diagnostics

Direct interpretation can mislead
without careful analysis

→ This is where synthetic diagnostics become essential

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>
# Use of integrated models to interpret measurements

LIMITATIONS
SYNTHETIC DIAGNOSTICS
INTERPRETATION
# What are synthetic diagnostics?

<figure><img src="image_18.png" /></figure>
Using SD to build, guide and understand

* **Build:** to optimize the design and performance of the diagnostics

* **Guide:** to support the development of control algorithms needed for the plasma control system design

* **Understand:** to support the physics interpretation and analysis, e.g. to predict the diagnostic performance in specific scenario contexts or validate a theoretical assumption
# The spectrum of synthetic diagnostic complexity

<figure><img src="image_19.png" /><figcaption>SIMULATION INPUT</figcaption></figure>
# Challenges of synthetic diagnostics

<figure><img src="image_20.png" /></figure>

* Temporal limitations

<figure><img src="image_21.png" /></figure>

* High computational cost

<figure><img src="image_22.png" /></figure>

* Spatial constraints

<figure><img src="image_23.png" /></figure>

* Incomplete physics of simulation input

<figure><img src="image_24.png" /></figure>

* Simplified models

<figure><img src="image_25.png" /></figure>

* Lack of self-consistency

<figure><img src="image_26.png" /></figure>

* Scenario specificity
# Use of integrated models to interpret measurements

LIMITATIONS
SYNTHETIC DIAGNOSTICS
INTERPRETATION
# Lesson from a 'simple' diagnostic

* TIP synthetic interferometer: developed for ITER, adapted to WEST via IMAS

* TIP integrates electron density along lines of sight with relativistic corrections

* Good match between METIS-based (OD transport, 1D current diffusion, 2D equilibrium) synthetic signals and WEST measurements

* Edge discrepancies due to optical path and SOL density, not modeled
  → question your models!

<figure><img src="image_27.png" /></figure>

Medvedeva 49th EPS 2023, Artaud NF 2018
Spectrometry on JET

○ To follow detachment, electron density and temperature are measured at the strike-point on the LFS divertor target

○ Direct values from EDGE2D or SOLPS simulations ≠ line-averaged quantities inferred from spectroscopy

○ A better comparison:
via SD based on Cherab that calculates
- line-averaged density
(Balmer-δ Stark broadening)
- line-averaged temperature
(Balmer continuum)

Cherab: V Neverov PPCF 2020, M Carr 44th EPS 2017
https://www.cherab.info/ https://www.raysect.org/

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

<figure><img src="image_30.png" /></figure>
Bolometry on WEST

○ WEST full discharge is simulated by 2D
fluid transport integrated model
SOLEDGE3X-HDG for D plasma

○ Synthetic bolometer signals (Cherab)
don't match WEST experimental data

○ Missing impurity physics (no W, no O)
leads to underestimation of radiation
and poor agreement with experiments!

<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>

Giorgiani NME 2019
Romazanov Phys. Scr. 2017
Kudashev AS 2022, JINST 2023
Bolometry on WEST

○ W transport added by coupling
SOLEDGE-HDG + ERO2.0 (+O trace
fraction to mimic W cooling physics)

○ Synthetic signals now closely match
experimental measurements

○ To reproduce diagnostic signals
reliably, simulations must include all
relevant physics

<figure><img src="image_33.png" /></figure>

<figure><img src="image_34.png" /></figure>

Giorgiani NME 2019
Romazanov Phys. Scr. 2017
Kudashev AS 2022, JINST 2023
# Interpret fast ion behavior on JET

* Neutral Particle Analysis detects charge-exchanged neutrals escaping from the plasma and measures fluxes and energy spectra

* Combining integrated modeling with synthetic diagnostic allows to bridge simulation and measurement with high confidence

<figure><img src="image_35.png" /></figure>

<figure><img src="image_36.png" /></figure>

Varje JINST 2017
# Validating turbulence signatures with FeDoT synthetic reflectometry

GYSELA simulation

<figure><img src="image_37.png" /></figure>

UFSR measurement (Tore Supra)

<figure><img src="image_38.png" /></figure>

FeDoT synthetic diagnostic validation

<figure><img src="image_39.png" /></figure>

Spontaneous organisation
of weak transport barriers: ExB staircase

Dif-Pradalier NF 2017, Hornung NF 2017, Glasser PPCF 2025

Precise turbulence modeling can unlock new diagnostic insights
# Toward a real-time digital twin

<figure><img src="image_40.png" /></figure>

Medvedeva 49th EPS 2023

Generate synthetic signals from integrated simulations to validate models, interpret data and move toward real-time plasma control
## SOLEDGE-HDG + TWINTOK: full-discharge synthetic view

<figure><img src="image_41.png" /></figure>

0.00 s

<figure><img src="image_42.png" /></figure>

Courtesy I. Kudashev, F. Schwander, E. Serre, D. Zarzoso, M. Scotto D'Abusco, G. Ciraolo, F. Clairet, G. Dif-Pradalier, N. Fedorczak, P. Ghendrih, S. Hacquin, A. Jamann, P. Abreu, M. Schneider, ITER, SOLEDGE and WEST teams

### Dα emission

<figure><img src="image_43.png" /></figure>

<figure><img src="image_44.png" /></figure>

### Bolometry

<figure><img src="image_45.png" /></figure>

<figure><img src="image_46.png" /></figure>

### Interferometry

<figure><img src="image_47.png" /></figure>

<figure><img src="image_48.png" /></figure>

### Visible emission

Synthetic camera

<figure><img src="image_49.png" /></figure>

### Tomographic analysis:

2D radiation map from bolometers signals

<figure><img src="image_50.png" /></figure>

### Turbulence analysis via reflectometry

<figure><img src="image_51.png" /></figure>

<figure><img src="image_52.png" /></figure>
# Broader perspectives

## Advanced uncertainty quantification
→ propagating model and diagnostic uncertainties consistently

*Riva PhD Thesis 2017, Ricci PoP 2011, Coster NME 2022*

## Data fusion across diagnostics
→ combining signals in Integrated Data Analysis (IDA) frameworks

*Fischer FST 2010*

## Synthetic design studies for future machines
→ predicting diagnostic performance in future scenarios (e.g., ITER, DEMO)

*Walsh IEEE 2011, Kajita PFR 2019, Meister SOFE 2023*

## Machine learning integration
→ synthetic datasets support training of AI for interpretation and control

*Citrin NF 2015, Brunet FED 2023, Pavone PPCF 2023*
Takeaway messages

* Integrated modeling is essential to understand plasma measurements
Takeaway messages

* Integrated modeling is essential to understand plasma measurements

* We don't measure plasma

* Measurements are indirect, integrated and inferred
Takeaway messages

* Integrated modeling is essential to understand plasma measurements

o We don't measure plasma

o Measurements are indirect, integrated and inferred

* Synthetic diagnostics connect model predictions with experimental signals
Takeaway messages

* Integrated modeling is essential to understand plasma measurements

o We don't measure plasma

o Measurements are indirect, integrated and inferred

* Synthetic diagnostics connect model predictions with experimental signals

o Synthetic diagnostics help to compare apples to apples
Takeaway messages

* Integrated modeling is essential to understand plasma measurements

* We don't measure plasma

* Measurements are indirect, integrated and inferred

* Synthetic diagnostics connect model predictions with experimental signals

* Synthetic diagnostics help to compare apples to apples

* They bridge theory and reality, improve validation and guide ITER-era fusion
Takeaway messages

* Integrated modeling is essential to understand plasma measurements

* We don't measure plasma

* Measurements are indirect, integrated and inferred

* Synthetic diagnostics connect model predictions with experimental signals

* Synthetic diagnostics help to compare apples to apples

* They bridge theory and reality, improve validation and guide ITER-era fusion

* This is actually true