Maha's Overleaf conciseness recommendations#245
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rebeccamccabe
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Jun 10, 2026
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check what version this is
| WEC-Sim runs utilize hydrodynamic coefficients obtained with the WAMIT BEM for dynamics, and control coefficients calculated with MDOcean for consistency. | ||
| MDOcean is run with MEEM as usual, and separately also run with the WAMIT coefficients to distinguish differences caused by disparate hydrodynamic coefficients from those caused by the underlying dynamics. | ||
| \else | ||
| Two MDOcean configurations are compared against WEC-Sim: one using MEEM hydrodynamic coefficients (the default) and one using WAMIT BEM coefficients matching WEC-Sim's, to separate dynamics-model error from hydrodynamic-coefficient error. |
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For both diss and paper:
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| Two MDOcean configurations are compared against WEC-Sim: one using MEEM hydrodynamic coefficients (the default) and one using WAMIT BEM coefficients matching WEC-Sim's, to separate dynamics-model error from hydrodynamic-coefficient error. | |
| To separate dynamics modeling error from hydrodynamic coefficient error, we compare two MDOcean configurations against WEC-Sim: one using MEEM hydrodynamic coefficients (the default) and one using WAMIT BEM coefficients matching WEC-Sim's. | |
| WEC-Sim uses identical control coefficients to MDOcean for consistency. |
| \end{figure} | ||
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| Results reveal that the drag describing function and MEEM hydrodynamic coefficients have a minor effect assuming a 1-DOF system (9.7\% and 2.7\% error on the average power and maximum amplitude respectively) but a major effect on the 2-DOF system (38.2\% and 28.6\% respectively). | ||
| The extremely low errors in the 2-DOF system enforcing the same hydrodynamic coefficients as WEC-Sim and with zero drag (0.2\% and 1.9\% in power and amplitude respectively) indicate that this is not an error in the 2-DOF dynamic model itself, but in the way that a 2-DOF model amplifies errors in drag and hydrodynamic coefficients due to the importance of the phase of motion between each DOF. |
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bring this sentence back
| \label{fig:error-histogram} | ||
| \end{figure} | ||
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| Results reveal that the drag describing function and MEEM hydrodynamic coefficients have a minor effect assuming a 1-DOF system (9.7\% and 2.7\% error on the average power and maximum amplitude respectively) but a major effect on the 2-DOF system (38.2\% and 28.6\% respectively). |
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bring this sentence back, but talk about only the 2DOF results instead of both 1 and 2 DOF
| The detailed error breakdown across drag-on/drag-off and MEEM/WAMIT coefficient configurations is provided in \appendixname~\ref{sec:appendix-dynamic-validation}, revealing that the dominant error sources are interactions between drag, hydrodynamic-coefficient mismatch, and the inter-body phase relationship in the 2-DOF model. | ||
| \appendixname~\ref{sec:appendix-dynamic-validation} also validates the describing-function approximation itself, showing total harmonic distortion below 1\% in the worst sea state and excellent agreement between the assumed and actual drag force waveforms at all four corners of the JPD. | ||
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| These errors are deemed acceptable for the purposes of this study, since the goal is to demonstrate the value of simultaneously analyzing multiple disciplines and the ability to quickly evaluate a large number of design options. |
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| These errors are deemed acceptable for the purposes of this study, since the goal is to demonstrate the value of simultaneously analyzing multiple disciplines and the ability to quickly evaluate a large number of design options. | |
| These errors are deemed acceptable for the purposes of this study, since the goal is to demonstrate the value of simultaneously analyzing multiple disciplines and the ability to quickly evaluate many designs. |
| \end{figure} | ||
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| The dynamics and controls module takes the next longest (\resultsAOR[pctRuntimeDynamics], enlarged in \figureautorefname~\ref{fig:runtime-dynamics}), with contributions from force saturation, spar analysis, drag linearization, and evaluation of the motion transfer function. | ||
| This represents a three-order-of-magnitude improvement over the equivalent regular-wave WEC-Sim simulation run in parallel. |
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| This represents a three-order-of-magnitude improvement over the equivalent regular-wave WEC-Sim simulation run in parallel. | |
| In \resultsAOR[runtimeDynamics] (non-parallelized), MDOcean solves the full constrained optimal control problem, representing a three-order-of-magnitude improvement over the parallelized WEC-Sim runtime to evaluate a single fixed controller. | |
| Both simulate all sea states as regular waves. |
| This represents a three-order-of-magnitude improvement over the equivalent regular-wave WEC-Sim simulation run in parallel. | ||
| Simplifying the dynamics to a single degree of freedom (DOF) achieves another order of magnitude speedup, although the optimization and benchmarking results presented here utilize the 2-DOF model. | ||
| \ifdefined\DISSERTATION | ||
| Simplifying the dynamics to a single degree of freedom (DOF) achieves another order of magnitude speedup, although the optimization and benchmarking results presented here utilize the 2-DOF model. |
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add sentence about how early sims had even faster runtimes that could be obtained with even more simplifying assumptions, as in a multi-fidelity optimization.
| We emphasize that the model is not intended to replace detailed models for final design and analysis, but rather to enable rapid design space exploration and optimization in the early stages of design. | ||
| Since the values without scale factors are of the correct order of magnitude and the trends are reasonable, the use of scale factors to resolve discrepancies in the force, power, and mass models is deemed acceptable for the purposes of this study. | ||
| \ifdefined\DISSERTATION | ||
| \Cref{sec:validation-benchmarking} demonstrates that MDOcean achieves accuracies generally within single-digit-percent JPD-weighted annual average power under realistic conditions, despite worst-case per-sea-state errors that can be larger due to drag and inter-body phase sensitivity in the 2-DOF model %within 10\% of established models and benchmarks both at the individual subsystem level and at the system level. |
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| \Cref{sec:validation-benchmarking} demonstrates that MDOcean achieves accuracies generally within single-digit-percent JPD-weighted annual average power under realistic conditions, despite worst-case per-sea-state errors that can be larger due to drag and inter-body phase sensitivity in the 2-DOF model %within 10\% of established models and benchmarks both at the individual subsystem level and at the system level. | |
| \Cref{sec:validation-benchmarking} demonstrates that MDOcean achieves accuracies generally within single-digit-percent JPD-weighted annual average power and maximum amplitude under realistic conditions, despite worst-case per-sea-state errors that can be larger due to drag and inter-body phase sensitivity%within 10\% of established models and benchmarks both at the individual subsystem level and at the system level. |
| We emphasize that the model is not intended to replace detailed models for final design and analysis, but rather to enable rapid design space exploration and optimization in the early stages of design. | ||
| Since the values without scale factors are of the correct order of magnitude and the trends are reasonable, the use of scale factors to resolve discrepancies in the force, power, and mass models is deemed acceptable for the purposes of this study. | ||
| \else | ||
| MDOcean reproduces the dynamics of an established time-domain solver within a few percent under matched modeling assumptions and within single-digit-percent JPD-weighted annual average power under realistic conditions, despite worst-case per-sea-state errors that can be larger due to drag and inter-body phase sensitivity in the 2-DOF model. |
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| MDOcean reproduces the dynamics of an established time-domain solver within a few percent under matched modeling assumptions and within single-digit-percent JPD-weighted annual average power under realistic conditions, despite worst-case per-sea-state errors that can be larger due to drag and inter-body phase sensitivity in the 2-DOF model. | |
| MDOcean reproduces the dynamics of an established time-domain solver within 0.2\% under matched modeling assumptions and within single-digit-percent JPD-weighted annual average power under realistic conditions, despite worst-case per-sea-state errors that can be larger due to drag and inter-body phase sensitivity. |
| \else | ||
| MDOcean reproduces the dynamics of an established time-domain solver within a few percent under matched modeling assumptions and within single-digit-percent JPD-weighted annual average power under realistic conditions, despite worst-case per-sea-state errors that can be larger due to drag and inter-body phase sensitivity in the 2-DOF model. | ||
| Three scale factors are used to tune force, power, and mass outputs across disciplines for consistency with the reference model report. | ||
| The \resultsAOR[simRuntime] runtime is 1-3 orders of magnitude faster than established software, enabling multidisciplinary optimization workflows that would otherwise be prohibitive. |
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| The \resultsAOR[simRuntime] runtime is 1-3 orders of magnitude faster than established software, enabling multidisciplinary optimization workflows that would otherwise be prohibitive. | |
| The \resultsAOR[simRuntime] full-simulation runtime is 1-3 orders of magnitude faster than established software, enabling multidisciplinary optimization workflows that would otherwise be prohibitive. |
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