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Record W1544498952 · doi:10.5772/21578

Wire Robot Suspension Systems for Wind Tunnels

2011· book-chapter· en· W1544498952 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

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsnot available
FundersUniversität Duisburg-EssenCanadian Institute for Advanced Research
KeywordsSuspension (topology)Wind tunnelMarine engineeringRobotComputer scienceAerospace engineeringEngineeringGeologyEnvironmental scienceArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

In the past decade, the main focus in ship hydrodynamic simulation was the computation of the viscous flow around a ship at constant speed and parallel inflow to the ship longitudinal axis. Meanwhile, the numerical methods developed by extensive research allow to simulate the viscous flow around a maneuvering vessel. Having these methods at hand, experimental data are required for the validation of the applied simulation models. These data can be obtained e.g. by wind tunnel experiments. Here, particularly the velocity distribution around the body and forces of the flow during a predefined motion are of interest. The motion of the ship model can be realized by a superposition of longitudinal motion simulated through the inflow in the wind tunnel and a transverse or rotational motion of the ship realized by a suspension mechanism. Mechanisms for guiding a ship model along a predefined trajectory are known e.g. from towing tank applications. However, the design criteria for these mechanisms are totally different from a wind tunnel suspension system. In the towing tank, the weight of the studied vessel is compensated by the buoyancy force. On the other hand, the required forces to move the model along a trajectory are much higher due to the higher density and mass of the water in comparison with air. In the wind tunnel application, the mass of the model leads to gravity and inertia forces which have to be compensated by the suspension system. This chapter describes the development of a suspension system based on wire robot technology. Wire robots use wires for the suspension of their end effectors. In this application, this is very advantageous since wires have a relatively small aerodynamical footprint and allow for high loads. The system described within this chapter is installed at the Technical University Hamburg-Harburg, where ship models must be moved on defined trajectories within the wind tunnel, as described above (Sturm & Schramm, 2010). The application requires the motion of heavyweight payloads up to 100kg with a frequency of up to 0.5Hz for the translational degrees-of-freedom and up to 2.5Hz for the rotational degrees-of-freedom. Within this chapter, at first a short historical review of the very active wire robot research within the last years is given in section 2. Afterwards, an appropriate design of the wire robot system is discussed in section 3. Due to the adaptability of the wire robot concept, different geometries are possible. Based upon the mechatronic development process according to VDI (2004), two designs are investigated in section 3. Therefore, virtual prototypes using mathematical models and numerical simulation are developed in sections 3.1 and 3.2. Based on the simulation results, the two designs are compared in section 3.3. Using numerical 2

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.901
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 studies0.0000.000
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 head0.039
GPT teacher head0.230
Teacher spread0.191 · 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