Numerical assessment of miniaturized cold spray nozzle for additive manufacturing
Bibliographic record
Abstract
Purpose Application of cold spray technology may exhibit significant benefits for the additive manufacturing process, particularly for producing intricate objects. To ascertain the feasibility of such an application, this paper aims to present a numerical investigation of the effect of scaling down a convergent-divergent (de Laval) nozzle, which is typically used in the cold spray industry, on the compressible flow parameters and thermal characteristics. Design/methodology/approach The Navier–Stokes equations and energy equation governing compressible flow are numerically solved using a finite volume method with a coupled solver. The conjugate heat transfer technique is used to couple fluid and solid heat transfer domains and predict the local heat transfer coefficient between the solid and fluid. The use of various RANS turbulence models has also been investigated to quantify the effect of the turbulence model on the simulation. Findings The numerical results reveal that the flow and thermal characteristics are altered as the convergent-divergent nozzle is scaled down. The static pressure and temperature profiles at any section in the nozzle are shifted toward higher values, while the Mach number profile at any section in the nozzle is shifted toward a lower Mach number. The turbulent kinetic energy at the nozzle exit increases with the scaling down of the nozzle geometry. This study also provides convincing evidence that the adiabatic approach is still suitable even though the temperature of the nozzle wall is extremely high, as required for industrial application. Results indicate that it is feasible to use the available capabilities of the cold spray technology for additive manufacturing after scaling down the nozzle. Originality/value The idea of adopting cold spray technology for additive manufacturing is new and innovative. To develop this idea into a viable commercial product, a thorough understanding of the flow physics within a cold spray nozzle is required. The simulation results discussed in this paper demonstrate the effect that scaling down of a convergent-divergent nozzle has on the flow characteristics in the nozzle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".