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Design and Operation of Autonomous Underground Freight Transportation Systems

2019· article· en· W2969594434 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.

fundA Canadian funder is recorded on the work.
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

VenueJournal of Pipeline Systems Engineering and Practice · 2019
Typearticle
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsnot available
FundersUniversity of MissouriInfrastructure CanadaTexas Department of Transportation
KeywordsTransport engineeringPipeline transportTruckPort (circuit theory)PalletRail freight transportFreight trainsEngineeringTransit (satellite)Systems designAutomotive engineeringTrainPublic transportSystems engineering

Abstract

fetched live from OpenAlex

Despite the increases in freight transportation demand, options for increasing capacity of the overground freight transportation infrastructure system are limited. This paper investigated the design and operation of an underground freight transportation (UFT) system that uses space below highways. Underground freight transportation is a class of automated transportation system in which individual vehicles carry freight through tunnels and pipelines between intermodal terminals. This paper presents attributes for schematic designs and operations for two UFT scenarios: a long-haul system which transports standard shipping containers between the Port of Houston and a terminal near Dallas, and a short-haul system which carries pallet-size freight between the Port of Houston and a satellite terminal near Houston. The appropriate design details were determined by the size of the freight, the types of vehicles and tunnels, and the propulsion system. In addition, operational attributes such as operating speed, headway, line capacity, and associated fleet sizes were addressed. Design sketches and operational equations presented in this paper are generally independent of the freight sizes and route lengths and this case study can be used as guidance for the design and operation of other freight tunnels and pipelines.

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 categoriesnone
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 score0.957
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.207
Teacher spread0.189 · 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