BEER software requirements STAP meeting Phase 2 BEER

BEER software requirements STAP meeting – Phase 2

BEER software workshop • BEER team participated in diffraction and imaging DMSC workshops • Basic requirements were placed • Dedicated DMSC workshop for BEER is planned for Jan/2018 • Requirements based on experiences of other engineering instruments • Any input from STAP members is appreciated Instrument control and software platforms info: • Data reduction platform → Mantid (Engin-X, Poldi) • Instrument control platform → NICOS (Stress-Spec)

General BEER Software requirements • Common functionality with diffraction, SANS and imaging instruments • Detector readout and ICS control similar for other instruments • Special attention with the SE meta-data stream • Engineering specific • Sample coordination system positioning – 3 D scanning of sample objects • SE driven experiments – experiment can continue without the neutron beam • Data reduction and visualisation in recalculated values (Force → MPa, Displacement → Strain) • BEER specific • Data reduction of the modulation mode • Mc. Stas simulation for modulation setup optimization • Life data reduction and simple analysis for SE feedback control

Data display and visualisation • 2 D live raw counts data for each detector (X axis in λ, 2θ, To. F, d, Q) • 1 D live histogram display: integrated intensity over all detector area vs To. F (λ, d, Q) (for each detector) • 1 D live histogram of ROI with integrated counts vs To. F (λ, d, Q, 2θ) • 1 D live histogram of ROI in vertical direction - texture • Incident beam spectrum • Plot of SE parameters (temp, stress, position, etc. ) as a function of time • Visualization of the positioning system status • Transformation of engineering SE parameters to strain, stress, etc. • Way to compare histograms (fix display of pattern in specific state to see current change) • Correction of the live detector data for distortions, efficiency, calibration • …

Data reduction and analysis • • • Reduction od detectors area or ROI to 1 D pattern in d-spacing Peak search routine Peak fitting routine (Gaussian, pseudo-Voigt, …) Extraction of FWHM, position, intensity as a function of SE status Data reduction to 2 D map for structural refinement using advanced Rietveld programs as Full. Prof, GSAS, … Reduction of the peak intensity along vertical position – texture Reduced data tagged by SE status Fast data reduction and analysis for active SE feedback control Data reduction of the modulation mode data sets …

Instrument control CLI&GUI • • • Access to driving motors position, setting limits, offsets, … Reading and changing of SE parameters Counting for time, monitor, counts, charge Simplified experiment planning (experiment tree structure) Continuous driving while counting (sweep) Loops, if-then Script simulation Quick change of instrument setups (SE, high/low resolutions, multiplexing) Read of pre-measured 3 D coordinates and scanning path planning (ex. SScan. SS) Adjustment and visualization of positioning system (hexapod, robot, tables, etc. ) Experiment simulation for multiplexing (predict overlap, adjust the MC speed) …

List of BEER software requirements • List of requirements created based on DMSC template • BEER_software_requirements_bullets_v 4. docx • Any input from your experience is welcomed • List will be discussed in DMSC workshop

Modulation technique simulation Example: duplex steel as simulated in the modulation mode Beam structure at the sample produced by the modulation chopper 280 Hz, 8 slits x 4 o Sample diameter 7 mm, duplex steel rod in 45 o orientation, gauge volume 1 x 1 x 2 mm 3 • Performs conversion (2 q, time) -> dhkl • Requires a list of expected peaks with dhkl estimates: • Estimates the index of the nearest t 0 chopper window and corrects for its phase. • Only (2 q, time) – events along the expected lines can be processed, excluding overlapping stripes. Dt 3 ms ESS pulse width processed overlap empty

Modulation technique data analysis stress free e=-500 me s=500 me e=1000 me s=1000 me a-Fe(211) g-Fe(111) Simulated counts were scaled to 60 s exposure time at 5 MW power + Poisson noise added. Gaussian fits to selected peaks produced by the event based data (in usual units me = 10 -6) original fit Fe(211) fit Fe(111) peak shift -500 -471 (21) -506 (14) broadening 500 479 (60) 469 (90) peak shift 1000 1020 (42) 1016 (170) broadening 1000 1031 (140) 1053 (70) For strong peak broadening, sum of 3 equal peaks separated by the modulation period have to be taken as the fitting function. Simulation and analysis based on ICNS 2017 poster by Jan Šaroun saroun_ICNS_poster. pdf

Modulation technique point to discuss • Initial proposition – using 16 or 4 openings MCa chopper – Day-one Diameter: 700 mm Slit opening: 16 x 4° Slit distance: 22. 5° MCb chopper - upgrade Diameter: 700 mm Slit opening: 4 x 4° Slit distance: 90° • Proposed solution – using 8 or 16 or by combination also 4 MCa chopper – Day-one Diameter: 700 mm Slit opening: 8 x 4° Slit distance: 45° MCb chopper - upgrade Diameter: 700 mm Slit opening: 16 x 4° Slit distance: 22. 5°