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Record W2999847649 · doi:10.1061/9780784480304.022

Applied Wave Modelling for Harbor Improvements: An Opportunity for Boussinesq Model Advancement

2017· article· en· W2999847649 on OpenAlexaff
P. B. Blackmar, R. McPherson, H. N. Smith

Bibliographic record

VenueCoastal Structures and Solutions to Coastal Disasters 2015 · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsVancouver Coastal Health
Fundersnot available
KeywordsBoussinesq approximation (buoyancy)Computer scienceMeteorologyPhysics

Abstract

fetched live from OpenAlex

St. George Island is one of the Pribilof Islands of the State of Alaska located in the Bering Sea. The small island has a single harbor that provides the community’s primary opportunity for generating revenue through the thriving local fishery as well as the only mode of delivering critical supplies and fuel to the remote locale. However, large breaking waves at the harbor entrance and significant oscillations within the harbor create unsafe conditions for harbor users. The Alaska Department of Transportation & Public Facilities (DOT&PF) and HDR Inc. (HDR) are designing improvements to provide a safer, more functional harbor. The small size of the harbor, extreme wave conditions, and high cost of construction in this remote and hazardous location present significant design challenges. BOUSSINESQ wave modeling using BOUSS-2D and FUNWAVE was employed to simulate waves approaching and entering the harbor, capturing wave shoaling and breaking, diffraction and refraction past the harbor structures, and infra-gravity waves within the harbor. These models were applied to analyze both the existing and proposed harbor configurations.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.273
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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