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Record W4283747891 · doi:10.3389/fmech.2022.830104

Thermal Conductivity of Ti-6Al-4V in Laser Powder Bed Fusion

2022· article· en· W4283747891 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

VenueFrontiers in Mechanical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsC-Therm Technologies (Canada)
FundersBundesministerium für Wirtschaft und Energie
KeywordsThermal conductivityMaterials scienceThermalFusionRealization (probability)Particle (ecology)Composite materialThermodynamicsPhysicsMathematics

Abstract

fetched live from OpenAlex

With increasing maturity of the laser powder bed fusion (PBF-LB/M) process, the related products are becoming more complex. The more conventional parts are integrated into one design, the more requirements regarding local material properties arise. This concerns for instance products with high demands regarding temperature management. Here, different thermal conductivities within the part enable the control of the temperature distribution as well as the direction of heat flows. The realization of those local properties poses a challenge, though, as the use of multiple materials in PBF-LB/M is not broadly available. However, the different states of material in PBF-LB/M, i.e. bulk and powder material, provide the opportunity to create thermal metamaterials with locally varied thermal conductivities. To enable part design utilizing the bulk material as well as enclosed powder, this study investigates the respective thermal conductivities of Ti-6Al-4V. Powder and printed samples were measured at RT by the Modified Transient Plane Source method, resulting in an effective thermal conductivity of 0.13 W/mK for powder and 5.4 W/mK for bulk material (compared to 6.5 W/mK in prior experiments). For complete assessment of the powder material, because of the many uncertainties due to the particle size distribution and powder application, a computational model following the network modeling approach is created. The model is used to create a data set of 60 different powder bed configurations, which is then statistically evaluated to provide a description independent from powder packing. Finally, the application of the investigations to achieve thermal metamaterials capable of local temperature management with a single material is presented in a numerical study. Here, the use cases of thermal shielding as well as the concentration of heat flow is demonstrated.

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 score0.599
Threshold uncertainty score0.709

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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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