A comprehensive review of radiation shielding concrete: Properties, design, evaluation, and applications
Bibliographic record
Abstract
Abstract This review paper provides a comprehensive analysis of radiation shielding concrete, covering its properties, design, evaluation, and applications. It begins with an introduction, stating the objective and scope. The paper explores radiation shielding basics, including ionizing radiation, shielding principles, and materials used for shielding. Concrete's properties relevant to shielding, radiation attenuation mechanisms, and factors affecting its efficiency are discussed. Different types of radiation shielding concrete are examined, along with their applications. The design and formulation of shielding concrete, including mix proportions, optimization techniques, and quality control, are presented. Evaluation methods and standards are discussed. Lastly, challenges, future directions, and emerging technologies are outlined. This review paper serves as a valuable resource for professionals involved in radiation shielding. The review on radiation shielding concrete highlighted its effectiveness in attenuating ionizing radiation, emphasizing material composition, density, and thickness as key design factors. Evaluation methods, such as gamma spectroscopy and Monte Carlo simulations, are discussed, demonstrating its versatile applications in nuclear facilities, healthcare, and space exploration.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".