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Record W2263084481

AECL's Waste Management and Decommissioning Program

2006· article· en· W2263084481 on OpenAlexaboutno aff
Wch Kupferschmidt, ME Stephens

Bibliographic record

VenuePacific Basin Nuclear Conference 2006 · 2006
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear decommissioningRadioactive wasteWaste managementSpent nuclear fuelEngineeringPort (circuit theory)Nuclear powerHazardous wasteHigh-level waste
DOInot available

Abstract

fetched live from OpenAlex

Canada has developed significant expertise in radioactive waste management since the mid 1940's, when the Canadian nuclear program commenced activities at Chalk River Laboratories (CRL). Created as a Federal Crown Corporation in 1952, AECL continues to manage wastes from those early days, as well as other radioactive wastes that Canadian hospitals, universities, and industry continue to produce, together with wastes from AECL's own ongoing operations. To support AECL's operations, serve the Canadian power reactor utilities and manage the federal nuclear legacy liabilities, AECL conducts RandD programs investigating technical and engineering matters on the handling, storage and disposal of the radioactive wastes associated with the CANDU reactor. Canada's historical low-level radioactive wastes, for which the federal government has taken responsibility, are being managed by the Low-Level Radioactive Waste Management Office (LLRWMO). The LLRWMO, managed by AECL since 1982, is now in the preparatory stages of establishing new long-term waste management facilities at Port Hope and Port Granby, Ontario that will receive wastes associated with past uranium refining activities in the area. To facilitate both the short- and long-term management of radioactive wastes at CRL, several major waste management initiatives are being underway. The Liquid Waste Transfer and Storage (LWTS) Project will recover highly radioactive liquid wastes that are currently stored in underground tanks that, in some cases, date back to the initial operations at the site. The Fuel Packaging and Storage (FPS) Project, will recover and condition degraded used research reactor fuel that is currently stored in below-ground standpipes of an early design. Development work is also under way to increase the storage density of AECL's MACSTORTM modular dry storage for used fuel, and to extend its application to the storage of intermediate-level radioactive waste arising from upcoming reactor refurbishment activities in Canada and overseas. Under contract to Ontario Power Generation (OPG), AECL also continues RandD on deep geologic repository technology in support of the long-term management of Canada's nuclear fuel waste. Many of the facilities first established at CRL in the 1940s and 1950s are now redundant and need to be safely dismantled and the resulting wastes managed. Several such decommissioning projects are now under way. Whiteshell Laboratories is AECL's second Nuclear Research and Test Establishment located near Winnipeg, Manitoba. WL has been operated by AECL since the early 1960s, and the entire site is now in the first stage of decommissioning. In 2005 in conjunction with the Canadian government, AECL established a Liability Management Unit (LMU) to manage the decommissioning and waste management liability associated with AECL sites. Decommissioning activities at AECL's sites will accelerate significantly with the announcement by the federal government in 2006 June of increased funding for this work over the next five years. This paper provides an overview and selected examples of AECL's current waste management and decommissioning activities, and provides references to papers where additional details may be found.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.755
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.008
GPT teacher head0.197
Teacher spread0.190 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2006
Admission routes1
Has abstractyes

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