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Record W7092293096 · doi:10.5957/smc-2025-097

Accelerating heavy lift and transport design and analysis for the Polar Icebreaker

2025· article· W7092293096 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSNAME Maritime Convention · 2025
Typearticle
Language
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsShipbuildingShipyardBARGEModular designLift (data mining)YardProcess (computing)Naval architecture

Abstract

fetched live from OpenAlex

Abstract This paper presents the development and review of shipyard heavy lift and transport design and analysis at Seaspan Vancouver Shipyard, located in the Canadian Pacific. With larger projects that require higher demands in movement in the yards, several challenges arose, such as design, process, and physical constraints. The state of design and analysis of rigging and structural analysis is discussed and compared to industry methods. Seaspan has updated its design and analysis process to create safe and efficient production operations. Case studies of common analysis techniques and challenges are also discussed. INTRODUCTION Seaspan is currently building the heaviest ship ever constructed in Canada, the CCGS Arpatuuq (also known as the Polar Icebreaker). Since the inception of the National Shipbuilding Strategy (NSS) in 2011, Seaspan has been instrumental in revitalizing Canadian shipbuilding expertise, successfully launching five ships. Notably, three of these are first-of-class vessels, and each successive ship has grown substantial in size and complexity. Building the Protecteur-Class vessel (JSS) to Arpatuuq will result in approximately a 75% increase in weight, pushing facility, planning, and engineering process limits. Figure 1 illustrates the increase in both maximum displacement and lightship weight. One of the complex challenges that comes with building a larger first-of-class vessel is in the block handling operations. This includes overhead crane lifts and turns, transportation by Self-Propelled Modular Transporter (SPMT), and by barge between works sites and within the yard facilities. While Seaspan is a world-class shipyard with state-of-the- art facilities, its location within a major metropolitan area creates challenges with space limitations. The limited space necessitates a high volume of block movement, and this presents a unique challenge for engineers, as making efficient plans is critical to maintaining the schedule and therefore the build budget. To reduce the cost of ship construction to the customer, a heavy engineering focus is on simplifying deliverables without sacrificing safety, accelerating the engineering analysis, and reducing movement and production effort. This paper aims to explore the methods Seaspan has used to overcome the challenges and streamline the design and analysis of lifts and transports by incorporating global best practices in the maritime industry.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.237
Teacher spread0.222 · 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