Data · dataset · 2026
Monte Carlo Simulation Dataset of Neutron Resonance Transmission for Low-content Uranium with Self-shielding and Matrix Effects Considered
Listed in ScienceDB
Description
This dataset is generated from a neutron transport model established with Geant4 10.07.p03, using SiO₂ as the uranium ore matrix and ²³⁸U as the target nuclide, simulating neutron resonance transmission spectra from 0.001 eV to 3 MeV under sample thicknesses of 0.01–2.00 cm and uranium mass fractions of 0.8%–99%. Distinct from conventional purely simulated datasets, the core value of this contribution lies in its systematic integration of algorithmic inversion records.
Beyond the full-energy original transmission spectra and observed transmission values at the 20.8 eV characteristic resonance, the dataset comprehensively archives the convergence histories of Newton iteration for solving optical thickness and uranium mass fraction (including iteration step sizes, residuals, and convergence criteria), as well as the inversion results and relative errors derived from four analytical models: the conventional thin‑target model, the thick‑target self‑shielding correction model, the single‑element model, and the coupled multi‑element matrix model.
Read the rest (1 more)
Supplementary materials encompass simulation geometry parameters, nuclear cross‑section data, all iterative calculation codes, and plotting scripts for manuscript figures. This dataset not only quantifies the coupled nonlinear systematic errors induced by self‑shielding and silicate matrix attenuation in centimeter‑scale samples, and determines the optimal thickness range of 1.5–2.0 cm, but also provides comprehensive benchmarking data for algorithm selection, convergence validation, and error tracing in future NRTA quantitative experiments based on the accelerator‑driven neutron source at East China University of Technology, with broad applicability to nondestructive uranium quantification in resource evaluation and nuclear safeguards.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00186.01193 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Geochemistry 69% · Simulation 75%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00186.01193 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3703 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (69%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |