Optimal Design and Portfolio Risk Management for Groups of Structures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present paper addresses the problem of optimal design of portfolios of fixed offshore structures. A new framework for design is developed where the effect of dependency in the performance of structures subject to common extreme load events is taken into account in the design by inclusion of the follow-up consequences resulting from the simultaneous failure of several structures in the portfolio. First the special aspects of optimal design subject to follow-up consequences are addressed from the perspective of structures portfolio risk management. Thereafter the problem of optimal design of groups of structures is defined with special considerations to the assessment of the relation between the design, the probability density function of the life cycle benefits and the number of structures considered (in a group). Using this model basis the optimum design of fixed steel offshore platforms where the capacity of the structures against extreme wave loads can be expressed as function of the Reserve Strength Ratio (RSR) is considered. Thereafter parametric studies are conducted to illustrate the significance of the number of structures considered in a group, the correlation between the extreme loads acting on the different structures and the significance of including the follow-up consequences into the design optimization problem.
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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 | 0.001 | 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 | 0.000 | 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