MétaCan
Menu
Back to cohort
Record W2087006712 · doi:10.4043/23773-ms

Hull Structural Performance Monitoring System for Ships Operating

2012· article· en· W2087006712 on OpenAlexaff
Han Yu, Aleksandr Iyerusalimskiy, Yong‐Sung Kim, James A. St John

Bibliographic record

VenueOTC Arctic Technology Conference · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsConocoPhillips (Canada)
FundersSamsungConocoPhillips
KeywordsCrewHullMarine engineeringNaval architectureProcess (computing)Focus (optics)IcebergComputer scienceJoint (building)EngineeringAeronauticsSea iceMeteorologyCivil engineering

Abstract

fetched live from OpenAlex

Abstract Research on measuring the ice impact pressure on icebreaker hulls began inthe late 1970's, and its focus was to determine the magnitude of the impactpressures and to obtain long-term statistics of the impacts. Increasedcomputing power in the 1980's allowed the recording of time-histories onmultiple sensors that led to the development of the pressure-contact arearelationship. The aim of these systems, however, was to understand theice impact process and to provide guidance to design engineers. Thispaper presents a new hull structure monitoring system that can benefit both theship designers and operators for ships operating in ice-covered waters. With this system, the ice load monitoring system can measure and process theice impact loads immediately after each impact in near real-time. Theimpact measurements are used to estimate the resulting stresses on the hullstructures which are then compared to the allowable stresses. This systemcan provide meaningful near real-time feedback to the ship's crew of thestresses due to ice impact compared to the allowable stress. Thisinformation can assist the ship's crew in making informed decisions for safeand efficient operations in ice. The main focus of this paper is on themethodology for assessing the hull structural responses under ice impact andthe presentation of this information to the ship's crew. Introduction The state-of-the-art ice load monitoring and alarm system (ILMS) has beeninstalled on the Arctic shuttle tanker Timofey Guzhenko. The workassociated with the development, design, installation of the system, datacollection and analysis is a joint venture between ABS, ConocoPhillips, andSamsung Heavy Industries (SHI) with vessel owner cooperation [1]. This systemis designed to measure and record ice pressures and loads as well as computeice-induced responses of the hull structure at highly loaded locations on thehull. Stresses resulting from the ice loads are compared with allowablestresses in near real-time and the margin of safety in the structure isdisplayed on a bridge monitor. The system was commissioned in April 2009with the intent of long-term unmanned operation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.023
GPT teacher head0.228
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueOTC Arctic Technology ConferenceSame topicArctic and Antarctic ice dynamicsFrench-language works237,207