Numerical analysis and prediction of the effect of debris initial configurations on their dispersion during extreme-hydrodynamic events
Why this work is in the frame
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Bibliographic record
Abstract
Tsunamis and other extreme hydrodynamic events have the potential to transport large debris that, along with the flow, are capable of causing severe damage to coastal structures and infrastructures. Therefore, modelling such processes is essential when assessing the multiple hazards associated to this type of events. In harbour areas, transport inland of shipping containers and subsequent impacts are relevant examples of waterborne debris hazards. The present work addresses two gaps in the scientific research of this problem using numerical methods; the understanding of the effect of containers initial layouts and that of the flow impact angle on the transport and diffusion. To fill these gaps a numerical study was carried out using idealised flow conditions. To this end a Smoothed Particles Hydrodynamics solver (DualSPHysics), coupled with a Discrete Element Method model (Project CHRONO), was used and initially validated with experiments published in the literature. Subsequently, four layouts commonly used in shipping containers yards were simulated, including incident flow depth and impact angle variability, resulting in 76 total simulations. The results were analysed in terms of normalised standard deviation and normalised range differences with respect to the initial values of both parameters. These parameters were related to the flow impact angle, water depth to containers height ratio D h R , and normalised displacement of the container clusters centroids. Standard deviation and range are shown to reach, for almost all results, a quasi-steady state by the end of the simulations. It is shown that the standard deviation and range are more sensitive to the impact angle for D h R ≤ 1 . 7 . In this case, the configurations with flow impacting orthogonally to one of the containers axes show larger values of the two parameters than for intermediate angles. For larger values, D h R drives the standard deviation and range, independently from the impact angle. D h R is shown to be a physical parameter that well describes the relative importance of dispersion and advection of containers transported in extreme hydrodynamic events. Finally, existing relationships, that assume an infinite growth of the range, are shown to overestimate numerical results at the stage in which dispersion does not grow further. Two new regression formulae are numerically derived to predict the dispersion parameters at this stage. They include the effects of the cluster layout, impact angle α and D h R making them a valid alternative to existing relationships. • The effects of layout, flow depth and impact angle on containers dispersion are analysed. • 76 container configurations were simulated with a SPH solver, coupled with a DEM-P solver. • Water Depth to debris height Ratio (DhR) is a relevant parameter to predict debris dispersion. • The influence of impact angle and layout on dispersion is larger for smaller DhR values. • We propose new formulae to predict debris lateral range and standard deviation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it