Current Status and Future Developments in Nuclear-Power Industry of the World
Bibliographic record
Abstract
It is well known that electrical-power generation plays the key role in advances in industry, agriculture, technology, and standard of living. Also, strong power industry with diverse energy sources is very important for a country's independence. In general, electrical energy can be mainly generated from: (1) nonrenewable energy sources (75.5% of the total electricity generation) such as coal (38.3%), natural gas (23.1%), oil (3.7%), and nuclear (10.4%); and (2) renewable energy sources (24.5%) such as hydro, biomass, wind, geothermal, solar, and marine power. Today, the main sources for electrical-energy generation are: (1) thermal power (61.4%)—primarily using coal and secondarily using natural gas; (2) “large” hydro-electric plants (16.6%); and (3) nuclear power (10.4%). The balance of the energy sources (11.6%) is from using oil, biomass, wind, geothermal, and solar, and has visible impact just in a few countries. This paper presents the current status of electricity generation in the world, various sources of industrial electricity generation and role of nuclear power with a comparison of nuclear-energy systems to other energy systems. A comparison of the latest data on electricity generation with those several years old shows that world usage of coal, gas, nuclear, and oil has decreased by 1–2%, but usage of renewables has increased by 1% for hydro and 2% for other renewable sources. Unfortunately, within last years, electricity generation with nuclear power has decreased from 14% before the Fukushima Nuclear Power Plant (NPP) severe accident in March 2011 to about 10%. Therefore, it is important to evaluate current status of nuclear-power industry and to make projections on near (5–10 yr) and far away (10–25 yr and beyond) future trends.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".