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Nuclear Industry Applications of Si-Diode Based High Gamma Dose Rate Detectors

2012· article· en· W1965995084 on OpenAlexaff
Shijing Yue, B. Sur, Anuradha Das, G. Jonkmans, Liqian Li

Bibliographic record

VenueVolume 4: Codes, Standards, Licensing, and Regulatory Issues; Fuel Cycle, Radioactive Waste Management and Decommissioning; Computational Fluid Dynamics (CFD) and Coupled Codes; Instrumentation and Co · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsDetectorDiodeDose rateOptoelectronicsComputer scienceMaterials scienceNuclear engineeringPhysicsEngineeringMedical physicsTelecommunications

Abstract

fetched live from OpenAlex

AECL has developed and deployed several high gamma radiation field measurement and profiling systems based on commercial off-the-shelf (COTS) silicon diode sensors and components. These systems have been useful in a number of applications including radiation survey of a medical radioisotope production hot-cell, liquid level measurement in a highly radioactive tank, identification of waste location inside nuclear waste storage structures, imaging of reactivity devices inside a shut-down nuclear reactor, and for scanning and imaging highly radioactive reactor components inside a hot-cell in support of an industrial surveillance project. The measurements ranged from 100 uGy/h (10 mRad/h) to 10 kGy/h (1MRad/h), which covers typical radiation fields in hazardous nuclear facilities. This paper summarizes the development and characterization of the Si-diode based detector system, and describes its performance in a variety of applications.Copyright © 2012 by ASME

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.244
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueVolume 4: Codes, Standards, Licensing, and Regulatory Issues; Fuel Cycle, Radioactive Waste Management and Decommissioning; Computational Fluid Dynamics (CFD) and Coupled Codes; Instrumentation and CoSame topicRadiation Detection and Scintillator TechnologiesFrench-language works237,207