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Record W2776142624 · doi:10.1088/1755-1315/95/4/042002

Nuclear Power as a Basis for Future Electricity Generation

2017· article· en· W2776142624 on OpenAlexaff
Igor Pioro, Sergey K. Buruchenko

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2017
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsRenewable energyElectricity generationWind powerEnvironmental scienceEnergy developmentNuclear powerFossil fuelElectricityGeothermal energyPhotovoltaic systemEnergy sourceThermal power stationEnergy independenceCoalSolar powerGeothermal gradientEngineeringWaste managementPower (physics)Electrical engineeringGeologyPhysics

Abstract

fetched live from OpenAlex

It is well known that electrical-power generation is the key factor for advances in industry, agriculture, technology and the level of living.Also, strong power industry with diverse energy sources is very important for country independence.In general, electrical energy can be generated from: 1) burning mined and refined energy sources such as coal, natural gas, oil, and nuclear; and 2) harnessing energy sources such as hydro, biomass, wind, geothermal, solar, and wave power.Today, the main sources for electrical-energy generation are: 1) thermal powerprimarily using coal and secondarily -natural gas; 2) "large" hydro power from dams and rivers and 3) nuclear power from various reactor designs.The balance of the energy sources is from using oil, biomass, wind, geothermal and solar, and have visible impact just in some countries.In spite of significant emphasis in the world on using renewables sources of energy, in particular, wind and solar, they have quite significant disadvantages compared to "traditional" sources for electricity generation such as thermal, hydro, and nuclear.These disadvantages include low density of energy, which requires large areas to be covered with wind turbines or photovoltaic panels or heliostats, and dependence of these sources on Mother Nature, i.e., to be unreliable ones and to have low (20 -40%) or very low (5 -15%) capacity factors.Fossil-fueled power plants represent concentrated and reliable source of energy.Also, they operate usually as "fast-response" plants to follow rapidly changing electrical-energy consumption during a day.However, due to combustion process they emit a lot of carbon dioxide, which contribute to the climate change in the world.Moreover, coal-fired power plants, as the most popular ones, create huge amount of slag and ash, and, eventually, emit other dangerous and harmful gases.Therefore, Nuclear Power Plants (NPPs), which are also concentrated and reliable source of energy, moreover, the energy source, which does not emit carbon dioxide into atmosphere, are considered as the energy source for basic loads in an electrical grid.Currently, the vast majority of NPPs are used only for electricity generation.However, there are possibilities to use NPPs also for district heating or for desalination of water.In spite of all current advances in nuclear power, NPPs have the following deficiencies: 1) Generate radioactive wastes; 2) Have relatively low thermal efficiencies, especially, watercooled NPPs; 3) Risk of radiation release during severe accidents; and 4) Production of nuclear fuel is not an environment-friendly process.Therefore, all these deficiencies should be addressed in the next generation or Generation-IV reactors.Generation-IV reactors will be hightemperature reactors and multipurpose ones, which include electricity generation, hydrogen cogeneration, process heat, district heating, desalination, etc. Current Status of Electricity Generation in the WorldIt is well known that electric-power generation usage is the key factor for advances in industry, agriculture and the socio-economic level of living (see Table 1 and Fig. 1) [1][2][3].Also, strong power

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.004

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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations10
Published2017
Admission routes1
Has abstractyes

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