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Record W2173730649 · doi:10.2495/dne-v8-n2-165-171

The force cone method: a new thinking tool for lightweight structures

2013· article· en· W2173730649 on OpenAlexvenueno aff
C. Mattheck, Stephan Haller

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2013
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsCone (formal languages)Computer scienceEngineeringMechanical engineeringStructural engineeringAlgorithm

Abstract

fetched live from OpenAlex

The force cone method developed by Claus Mattheck enables computer-free topology designing and offers a profound knowledge for lightweight structures. Thus, the recently developed method enhances the series of the so-called thinking tools. The method's basic idea is the force distribution of a single force in an elastic plane. The symmetrically placed cones appear in front of the force and behind it. These cones intersect with 90 angles at primary points that quickly lead to a structural design proposal. Furthermore, the method is very useful for the evaluation of structures and their lightweight potential. With the knowledge of the load case, it is easy to identify the main tension and compression paths leading to a deeper understanding of lightweight results. Natural structures such as trees can also be understood in another way, highlighting the structural principles at the root, leaf, treetop or even the entire tree. Nowadays, technical lightweight solutions can be found with different methods, including the soft kill option developed at the KIT 20 years ago. The method resembles that of the biological mineralization process of living bone and results in structures that can be seen as optimized lightweight design proposals. The comparisons of those structures with the state-of-the-art designs used in the industry and with those found by the force cone method indicate the high potential of the new method. For the confi rmation of the basic rules and principles, different assembly positions of force and supports as well as different types of supports, such as fi xed supports or torsion anchors, have been analyzed.

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 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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.572
Threshold uncertainty score0.340

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 head0.012
GPT teacher head0.287
Teacher spread0.275 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations4
Published2013
Admission routes1
Has abstractyes

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