Numerical simulation study of the blockage effect on the hydrodynamics of a Francis turbine at best efficiency point and partial load
Bibliographic record
Abstract
Hydropower plays a central role in energy decarbonization. As hydraulic turbines are more often used to balance production and demand on electrical grids, the reliability of hydropower installations becomes a critical issue beyond purely economic considerations, making efficient diagnostics essential. This research is part of the MD-Francis project, carried out at the Heki Hydropower Innovation Center at Université Laval. It is conducted in collaboration with a consortium of six industrial partners and four universities, and focuses on detection and diagnostic of anomalies in Francis turbines. Within MD-Francis, various anomalies will be implemented on a structurally homologous model of a Francis turbine. Detailed measurements related to fluid-structure interactions will be performed to identify correlations that could be used to identify and categorize anomalies. This research focuses on the issue of blockages in the inter-blade channels of Francis turbines. These blockages, caused by debris or natural foreign objects (tree trunks, rocks, etc.), can lead to flow imbalances, generating vibrations and affecting overall performance. The blockage causes a head loss, resulting in a reduction of power. Additionally, these vibrations and imbalances can, in turn, cause more significant damage, potentially leading to major shutdowns of the turbine-generator unit. The main objective is to analyze the impact of these blockages on hydrodynamics and performance at the best efficiency point (BEP) and part load (PL) to guide experimental investigations. Numerical flow simulations of the unobstructed Francis, using a RANS approach, are presented and validated against experimental data to form a comparison baseline. Different blockages are then modelled as porous domains located inside an inter-blade channel, allowing for a realistic representation of partial flow restrictions. URANS simulations are used to analyze the hydrodynamic effects of those blockages on the flow. The analysis presented includes the impact on turbine performance, the unbalanced flow distribution in the distributor and runner, the resultant radial forces on the runner, the torque applied to adjacent blades, the rotor-stator pressure signals, and the impact on vortex development in the draft tube.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".