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Record W1865051965

Nuclear Energy Complexes: Prospects for Development and Cooperation

2008· article· en· W1865051965 on OpenAlexaboutno aff
Evgeny Vinokurov

Bibliographic record

VenueMunich Personal RePEc Archive (Ludwig Maximilian University of Munich) · 2008
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessChinaNuclear powerCorporationEnriched uraniumCompetition (biology)UraniumState (computer science)KazakhInternational tradePolitical scienceEconomyEconomic policyFinanceEconomics
DOInot available

Abstract

fetched live from OpenAlex

1.\t2005–2006 was a critical period in the development of the nuclear complexes of Russian Federation and the Republic of Kazakhstan. These years have ushered in a “nuclear renaissance”. Russia’s nuclear sector was subject to a total systemic review; the Federal Target Program (FTP) allocated to it funds totaling more than USD 55 billion. A decision was taken to consolidate all nuclear assets within one state corporation. Kazakhstan implemented the “15000 tons uranium by 2010” state development program. Its development programs for reactors and nuclear power plants are worked out jointly with Russia. Closer cooperation is also being pursued with other leaders in the field, primarily Japanese companies. Cooperation agreements between the two countries were adopted. The foundation of three joint ventures (JV) was the first tangible outcome of above agreements.\n\n2.\tMeanwhile Kazakh uranium has become a focus of attention and fierce competition between the world’s largest consumers, including France, Canada, USA, Japan, China, South Korea, and Russia. Early this decade, Russia’s substantial production capacity and highly competitive uranium ore conversion technologies added to calls for the country to renew its economic links with Kazakhstan in the uranium mining and nuclear industries. Given Russia’s ambitious plans to develop nuclear energy, and the fact that its uranium stocks are practically depleted, the benefits of closer cooperation with Kazakhstan are clear. However, Russia will have to compete with well-established players on Kazakhstan’s uranium market.\n\n3.\tKazakhstan has aspirations to become a world leader in uranium mining and to focus production at the highly processed end of the nuclear fuel cycle. This was the backdrop for a recent transaction which will have a significant impact on the country’s nuclear industry. In the autumn of 2007, KazAtomProm purchased Toshiba’s 10% share in Westinghouse Electrics, a leading producer of nuclear reactors, for USD 540 million. This transaction has secured a permanent nuclear alliance between KazAtomProm, Toshiba and Westinghouse Electrics. For Kazakhstan, this creates new opportunities to develop a hi-tech nuclear industry and to market its output in the West. Supplying high-end nuclear products to Western markets is one of KazAtomProm’s development priorities, along with continued cooperation with Russia in supplying Soviettype reactors.\n\n4.\tThe need to integrate the nuclear power complexes of Kazakhstan and Russia along the entire production chain is a logical response to their urgent need to reduce their energy deficit, and to the synergies which exist between their production capacities and technologies at each stage of the nuclear fuel production chain: (1) uranium mining, (2) uranium enrichment, (3) production of fuel pellets and fuel elements, (4) reactor design and production, primarily 300 MW VBER-300 power reactors, (5) construction and operation of nuclear power plants, and (6) nuclear waste processing and disposal.\n\n5.\tKazakhstan has plans to develop its own nuclear power industry and is likely to base this on 300 MW Russian-Kazakh reactors and, in the longer-term, 1000 MW Westinghouse reactors.\n\n6.\tThe development of this capital-intensive sector will require extensive financing based on credit from a number of sources. International and national development banks are one promising potential source of such funding. The ability to secure this capital from international and national development banks rests entirely upon the nuclear energy industry’s potential for development, innovation, diversification and integration. The Eurasian Development Bank, VEB (Russian Development Bank) and the Development Bank of Kazakhstan have indicated their recognition of this. E.g., the EDB has extended credit to the Russian-Kazakh Zarechnoye JV.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score1.000

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 studies0.0010.001
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 head0.024
GPT teacher head0.204
Teacher spread0.180 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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