Using system dynamics simulation for assessment of hydropower system safety
Bibliographic record
Abstract
Abstract Hydropower infrastructure systems are complex, high consequence structures which must be operated safely to avoid catastrophic impacts to human life, the environment, and the economy. Dam safety practitioners must have an in‐depth understanding of how these systems function under various operating conditions in order to ensure the appropriate measures are taken to reduce system vulnerability. Simulation of system operating conditions allows modelers to investigate system performance from the beginning of an undesirable event to full system recovery. System dynamics simulation facilitates the modeling of dynamic interactions among complex arrangements of system components, providing outputs of system performance that can be used to quantify safety. This paper presents the framework for a modeling approach that can be used to simulate a range of potential operating conditions for a hydropower infrastructure system. Details of the generic hydropower infrastructure system simulation model are provided. A case study is used to evaluate system outcomes in response to a particular earthquake scenario, with two system safety performance measures shown. Results indicate that the simulation model is able to estimate potential measures of system safety which relate to flow conveyance and flow retention. A comparison of operational and upgrade strategies is shown to demonstrate the utility of the model for comparing various operational response strategies, capital upgrade alternatives, and maintenance regimes. Results show that seismic upgrades to the spillway gates provide the largest improvement in system performance for the system and scenario of interest.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".