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Epic
Story
OwnerDeliverables
Link
Validation

1) Re-run advanced IMs

2)Generate gcmt faults to find correct orientation

3) Srf generation Subduction specific behaviour for GCMT (Robin to add more info)

1) Jonney

2) James

  1. ?
  2. Plots generated and passed on to Robin


Ground Motion DB

1) Ground Motion Extraction

2) Hikurangi Geometry

3) Tectonic Classification

4) Mw Reconciliation (comparison : John Ristau vs international dataset)

5) Comparison with VH2017

1)Viktor

2) James

3) Mike /  James

4) ?

5) ?

  1. ?
  2. On hold for this sprint
  3. Mike continuing
Hikurangi surface geometry
Cybershake

1)Running 200m sims LF only - on Maui (until Maui comm allocation uses  500k)

  • Northern South Island

2) Empirical DS - DB calculation

3) Empirical / Cybershake / ratio hazard maps

Jason



Slurm Workflow
  1. Generalize hacks for KISTI
  2. CH estimation based on linear regression
  3. Integrate with pre-processing (starting with VM)
    1. Separate db creation out of install
    2. Create generic slurm for the rest of install, make install operate on each fault
    3. Create a generic slurm for VM generation
  4. Pre-processing - GCMT to realisation – add some conditional logic about tectonic type (Brendon / Robin to consult about conditional parameters)
  5. Near-real time Simulation plan
  6. Cybershake Workflow Improvements
  1. James
  2. Jason / Brendon
  3. Jonney
  4. James
  5. Jonney
  6. Jason / Jonney
  1. Work mostly complete. Final tests on Kisti underway. Checks on tacc yet to begin.
  2. ?
  3. ?
  4. Deferred

SeisTech
  1. GM Selection for Empirical
    1. Integrate workflow into seistech master
    2. Synthetic tests for GCIM between Empirical and Simulation (1 rupture, N ruptures)
    3. Testing, trial calculations
  2. Automate documentation
  3. Front-end


  1. Daniel / Claudio
  2. Background task (Jason)
  3. Andy


Roadmap (scientific functionality list)

Production - TODO (longer term tasks)

Frontend

IM Calc





Bug fixes



Seismic risk



Machine Learning
  1. NN - GMM
    1. Implement an initial basic pipeline with some NN config + flexible feature selection & preprocessing
    2. Add hypo-depth to NN GMM dataset
  2. GM Classifier – see link


Claudio
GM classifier - progess
Empirical engine



Vs30



Misc
  1. SimAtlas simulation+animation:
    1. Batch 5 - keeping continual work
  2. Data management policy
    1.  (classification of data importance)
    2. Plan to incorporate this as part of business as usual – what data do we need to keep and what can be regenerated as needed
  3. NoisePy
  4. Velocity Model basins
  5. Dashboard
    1. Add comm00213 as a separate allocation
    2. Changes of storage (TB): With Fortnightly update info added
    3. Zero point at the start of the allocation (graph doesn't start midway)
  6. Vs30 Server
  1. Sung/Jonney
  2. Sung
  3. Viktor
  4. Jason


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