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Record W3017054166 · doi:10.1002/nme.6366

Simultaneous topology and build orientation optimization for minimization of additive manufacturing cost and time

2020· article· en· W3017054166 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

VenueInternational Journal for Numerical Methods in Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicTopology Optimization in Engineering
Canadian institutionsQueen's University
Fundersnot available
KeywordsMinificationTopology optimizationNetwork topologyVolume (thermodynamics)Orientation (vector space)Mathematical optimizationComputer scienceSensitivity (control systems)Component (thermodynamics)Multi-objective optimizationManufacturing costIndustrial engineeringTopology (electrical circuits)EngineeringMechanical engineeringMathematicsFinite element methodElectronic engineeringStructural engineering

Abstract

fetched live from OpenAlex

Summary The ever‐present demand for increased performance in mechanical systems, and reduced cost and manufacturing time, has led to the adoption of computational design tools and innovative manufacturing methods. One such tool is topology optimization (TO), which often produces designs that are impracticable to manufacture. However, recent developments in additive manufacturing (AM) have made production of such complex designs feasible. Therefore, integration of these technologies has the potential to innovate the design and manufacture of mechanical components. This work presents a novel mathematical methodology for multiobjective minimization of structural compliance and AM cost and time, in simultaneous build orientation and density‐based TO. Component surface area and support volume were implemented in this method as the physical factors influencing AM cost and time. A new methodology was produced to approximate support volume throughout TO with variable build orientation, enabling direct minimization of support volume in the proposed optimization. The methodology allows derivation of sensitivity expressions, thereby permitting the use of efficient gradient‐based optimization solvers. Three numerical examples demonstrated that the proposed methodology can efficiently produce optimum build orientations and topologies, which significantly reduce structural compliance and AM cost and time.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.139
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.013
GPT teacher head0.322
Teacher spread0.309 · 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