MétaCan
Menu
Back to cohort
Record W2732925592 · doi:10.4050/f-0073-2017-12088

Integrated Hybrid Structural Management System (IHSMS) - Aircraft Impact Monitoring

2017· article· en· W2732925592 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor Technologies Research
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsSystems engineeringComputer scienceRemote sensingEnvironmental scienceAerospace engineeringEngineeringGeology

Abstract

fetched live from OpenAlex

The Future Naval Capabilities Integrated Hybrid Structural Management System (IHSMS) program is developing Structural Health Management (SHM) capabilities for rotorcraft to move from conventional flight-hour based maintenance to reliability-based maintenance. A key element of IHSMS is to develop automated methods for impact detection, localization, and characterization. By their nature, impacts to rotor and airframe are random events that can trigger extensive inspections based solely on vague descriptions of the event by the aircraft crew. Operators must rely on numerous inspections to determine condition and ensure airworthiness, resulting in significant maintenance burden, both scheduled and unscheduled. The IHSMS program matured research originating at the Purdue Center for Systems Integrity (PCSI) at Purdue University and continued by the Laboratory for Systems Integrity and Reliability (LASIR) at Vanderbilt University, which uses a combination of physical sensors (accelerometers) and an algorithm to identify the location and estimate the force of impacts for both main rotor blade and airframe applications. This paper focuses on the outcomes of full-scale CH-53K main rotor blade and CH-53E airframe demonstration tests.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.649

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.306
Teacher spread0.284 · 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

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Sensor Technologies ResearchFrench-language works237,207