Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning | Paper Citation Record

Observation c2edc1f7-2d5c-4424-899a-ce27119d29a7 · outbound

This paper cites A convolutional neural network- based multi-sensor fusion approach for in-situ quality monitoring of selective laser melting.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning A convolutional neural network- based multi-sensor fusion approach for in-situ quality monitoring of selective laser melting

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.265567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 879b6d9f-da63-4eec-bbf2-cb4f5c91f38d · outbound

This paper cites Implementation of the marangoni effect in an open-source software environment and the influence of surface tension modeling in the mushy region in laser powder bed fusion (lpbf).

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Implementation of the marangoni effect in an open-source software environment and the influence of surface tension modeling in the mushy region in laser powder bed fusion (lpbf)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.248855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c2e78e6c-237a-4d05-925c-8ca0c3bae34f · outbound

This paper cites On the use of spatter signature for in-situ monitoring of laser powder bed fusion.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning On the use of spatter signature for in-situ monitoring of laser powder bed fusion

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.232859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 372c6ac7-a0d2-4fe1-81f5-5211de55fe75 · outbound

This paper cites Data-driven prediction of future melt pool from built parts during metal additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Data-driven prediction of future melt pool from built parts during metal additive manufacturing

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.216964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c60df92e-2c3f-4a60-a3f9-b33bcea600c3 · outbound

This paper cites Integrating Multi-Physics Simulations and Machine Learning to Define the Spatter Mechanism and Process Window in Laser Powder Bed Fusion.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Integrating Multi-Physics Simulations and Machine Learning to Define the Spatter Mechanism and Process Window in Laser Powder Bed Fusion

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:20:41.308560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 714bf6ae-77f1-4e5c-a396-433170061d78 · outbound

This paper cites Building blocks for a digital twin of additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Building blocks for a digital twin of additive manufacturing

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.201222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1da46dbf-ac5c-4555-b25b-486b8402ef17 · outbound

This paper cites Digital twins for additive manufacturing: a state-of-the-art review.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Digital twins for additive manufacturing: a state-of-the-art review

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.185168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ffd0ec0a-a3a2-4fd9-85a7-b9549e0d343e · outbound

This paper cites Investigation into spatter particles and their effect on the formation quality during selective laser melting processes.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Investigation into spatter particles and their effect on the formation quality during selective laser melting processes

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.169295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 21c975d3-7ebc-4549-860e-2e5399a2d32b · outbound

This paper cites Inexpensive high fidelity melt pool models in additive manufacturing using generative deep diffusion.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Inexpensive high fidelity melt pool models in additive manufacturing using generative deep diffusion

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.152533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0c19bc7c-e1f7-494b-8424-6d5fb1034c05 · outbound

This paper cites Synchrotron-based x-ray microtomography characterization of the effect of processing variables on porosity formation in laser power-bed additive manufacturing of ti-6al-4v.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Synchrotron-based x-ray microtomography characterization of the effect of processing variables on porosity formation in laser power-bed additive manufacturing of ti-6al-4v

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.136278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fd8d165e-c8c3-4218-86a8-ff3eb4a7858a · outbound

This paper cites Melt pool morphology in directed energy deposition additive manufac- turing process.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Melt pool morphology in directed energy deposition additive manufac- turing process

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.120212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5d293184-5aa9-458b-95fa-276873b82d8f · outbound

This paper cites Laser- induced keyhole defect dynamics during metal additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Laser- induced keyhole defect dynamics during metal additive manufacturing

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.104558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cc927cff-0d36-43e1-960b-c305abc1df44 · outbound

This paper cites In-situ characterization and quantifi- cation of melt pool variation under constant input energy density in laser powder bed fusion additive 28 manufacturing process.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning In-situ characterization and quantifi- cation of melt pool variation under constant input energy density in laser powder bed fusion additive 28 manufacturing process

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.088829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d96e1a3b-7f83-4d23-92c5-2752b36604db · outbound

This paper cites The role of process parameters and printing position on meltpool variations in lpbf hastelloy x: Insights into laser-plume interaction.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning The role of process parameters and printing position on meltpool variations in lpbf hastelloy x: Insights into laser-plume interaction

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.073343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4d21b4af-0a36-4012-aafd-8f35876248b1 · outbound

This paper cites Geo- metrical metrology for metal additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Geo- metrical metrology for metal additive manufacturing

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.058380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 00850675-b679-44fa-8772-340dc17d210e · outbound

This paper cites Effect of laser focal point position on porosity and melt pool geometry in laser powder bed fusion additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Effect of laser focal point position on porosity and melt pool geometry in laser powder bed fusion additive manufacturing

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.042349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6fdc615d-126f-4508-a125-4bb354b98fe4 · outbound

This paper cites Deep learning based reconstruction of transient 3d melt pool geometries in laser powder bed fusion from coaxial melt pool images.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Deep learning based reconstruction of transient 3d melt pool geometries in laser powder bed fusion from coaxial melt pool images

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.026435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 55680d15-c2d9-48f1-b2af-49829faa2392 · outbound

This paper cites Llm-3d print: Large language models to monitor and control 3d printing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Llm-3d print: Large language models to monitor and control 3d printing

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:42.010472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 72a2a59d-b34d-4d98-94f1-fa6672f2edff · outbound

This paper cites Melt pool geometry and morphology variability for the inconel 718 alloy in a laser powder bed fusion additive manufacturing process.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Melt pool geometry and morphology variability for the inconel 718 alloy in a laser powder bed fusion additive manufacturing process

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.994121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b0575d01-6dc7-45ee-8f10-ee810a61aa98 · outbound

This paper cites Review on thermal analysis in laser-based additive manufacturing.Optics & Laser Technology, 106:427– 441, 2018.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Review on thermal analysis in laser-based additive manufacturing.Optics & Laser Technology, 106:427– 441, 2018

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.977796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c1bf9e3e-8fff-4593-a6f6-0daa08627717 · outbound

This paper cites High-resolution melt pool thermal imaging for metals additive manufacturing using the two-color method with a color camera.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning High-resolution melt pool thermal imaging for metals additive manufacturing using the two-color method with a color camera

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.962322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3645549f-c0c9-4eee-960e-2988d1c261a1 · outbound

This paper cites Two-color thermal imaging of the melt pool in powder-blown laser-directed energy deposition.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Two-color thermal imaging of the melt pool in powder-blown laser-directed energy deposition

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.945861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d1e664a2-f89d-424a-be28-b45767cdc933 · outbound

This paper cites Vision-based defect detection in laser metal deposition process.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Vision-based defect detection in laser metal deposition process

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.930629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ff7c8bf0-d81f-4fcc-80a1-ffef3a4e9789 · outbound

This paper cites Relationship between solidifica- tion time and porosity with directed energy deposition of inconel 718.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Relationship between solidifica- tion time and porosity with directed energy deposition of inconel 718

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.916059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b2f83646-5c15-4ef7-9bd4-aa9fa7e9f990 · outbound

This paper cites Surrogate modeling of melt pool temperature field using deep learning.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Surrogate modeling of melt pool temperature field using deep learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.899864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b4946bfe-84ae-4c5e-af37-5867e602d4dd · outbound

This paper cites Dual process monitoring of metal-based additive manufacturing using tensor decomposition of thermal image streams.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Dual process monitoring of metal-based additive manufacturing using tensor decomposition of thermal image streams

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.884174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 895a7f42-c95d-43b9-98c2-ea9a157da0a7 · outbound

This paper cites Unveiling gas–liquid metal reactions in metal additive manufacturing: High-fidelity modeling validated with experiments.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Unveiling gas–liquid metal reactions in metal additive manufacturing: High-fidelity modeling validated with experiments

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.867702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2e9e5763-71b9-4585-a308-cfa7944e9afd · outbound

This paper cites Melt pool oxidation and reduction in powder bed fusion.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Melt pool oxidation and reduction in powder bed fusion

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.852158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 45a6be19-9aeb-40b2-b594-5da994940e6a · outbound

This paper cites Pressure dependence of the laser-metal interaction under laser powder bed fusion conditions probed by in situ x-ray imaging.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Pressure dependence of the laser-metal interaction under laser powder bed fusion conditions probed by in situ x-ray imaging

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.835224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 015a29a0-20c8-4044-b335-d56f9c63046a · outbound

This paper cites The effect of powder oxidation on defect formation in laser additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning The effect of powder oxidation on defect formation in laser additive manufacturing

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.818970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0614a102-96a9-43c1-b085-5d9b7ee0434c · outbound

This paper cites In situ moni- toring the effects of ti6al4v powder oxidation during laser powder bed fusion additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning In situ moni- toring the effects of ti6al4v powder oxidation during laser powder bed fusion additive manufacturing

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.803122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1c8c560d-80de-4ba6-9b25-af2476506db7 · outbound

This paper cites Meltpoolnet: Melt pool characteristic prediction in metal additive manufactur- ing using machine learning.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Meltpoolnet: Melt pool characteristic prediction in metal additive manufactur- ing using machine learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.787515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 30719742-75db-4e6a-b9f2-0da1162c0ffe · outbound

This paper cites Machine learning based prediction of melt pool morphology in a laser-based powder bed fusion additive manufacturing process.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Machine learning based prediction of melt pool morphology in a laser-based powder bed fusion additive manufacturing process

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.772136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2dec14b8-3d62-4b81-a3cd-f3e4f187b7d2 · outbound

This paper cites Sub-surface thermal measurement in additive manufacturing via machine learning- enabled high-resolution fiber optic sensing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Sub-surface thermal measurement in additive manufacturing via machine learning- enabled high-resolution fiber optic sensing

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.757034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 93b8e6ca-d114-484f-8123-e69226e34ea2 · outbound

This paper cites Using machine learning to identify in-situ melt pool signatures indicative of flaw formation in a laser powder bed fusion additive manufacturing process.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Using machine learning to identify in-situ melt pool signatures indicative of flaw formation in a laser powder bed fusion additive manufacturing process

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.739534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d991f245-8222-434d-bd4b-59c72642d9f1 · outbound

This paper cites Spatter formation in selective laser melting process using multi-laser technology.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Spatter formation in selective laser melting process using multi-laser technology

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.722758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 608594a6-c1e3-48b0-82fa-89d3e1b8a784 · outbound

This paper cites A study on the effect of energy input on spatter particles creation during selective laser melting process.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning A study on the effect of energy input on spatter particles creation during selective laser melting process

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.707193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 48f382da-6098-41d4-b33a-269dc8ba5865 · outbound

This paper cites Laser powder bed fusion of nickel alloy 625: Experimental investigations of effects of process parameters on melt pool size and shape with spatter analysis.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Laser powder bed fusion of nickel alloy 625: Experimental investigations of effects of process parameters on melt pool size and shape with spatter analysis

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.691668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5c46109d-3568-4e1c-a3cb-6719892d0626 · outbound

This paper cites On the effect of spatter particles distribution on the quality of hastelloy x parts made by laser powder-bed fusion additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning On the effect of spatter particles distribution on the quality of hastelloy x parts made by laser powder-bed fusion additive manufacturing

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.675069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5eeb4915-5d15-4b54-a58f-b6f2659e7726 · outbound

This paper cites Fatigue crack initiation from defects at weld toes in steel.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Fatigue crack initiation from defects at weld toes in steel

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.658010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c4f109ea-a636-4ff3-aa7b-824f5707116a · outbound

This paper cites The investigation of plume and spatter signatures on melted states in selective laser melting.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning The investigation of plume and spatter signatures on melted states in selective laser melting

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.640763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2e44be2e-70a3-4480-905d-1845c65af1e8 · outbound

This paper cites Deep learning object detection for optical monitoring of spatters in l-pbf.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Deep learning object detection for optical monitoring of spatters in l-pbf

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.624767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8a22f8f1-3db1-42ac-bc18-ca664f8c5a32 · outbound

This paper cites Real-time tracking method for motion spatter in high-power laser welding of stainless steel plate based on a lightweight deep learning model.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Real-time tracking method for motion spatter in high-power laser welding of stainless steel plate based on a lightweight deep learning model

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.607218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 78d5fccd-75e8-4b79-8cdc-ee3886d8f79f · outbound

This paper cites Online detection of powder spatters in the additive manufac- turing process.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Online detection of powder spatters in the additive manufac- turing process

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.590835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 95b51e88-551b-4467-8743-7c3ba71820d2 · outbound

This paper cites Characteristics 31 of droplet spatter behavior and process-correlated mapping model in laser powder bed fusion.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Characteristics 31 of droplet spatter behavior and process-correlated mapping model in laser powder bed fusion

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.573963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7768a543-ce12-4643-8acb-793c3ad3fe44 · outbound

This paper cites Compu- tational analysis and experiments of spatter transport in a laser powder bed fusion machine.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Compu- tational analysis and experiments of spatter transport in a laser powder bed fusion machine

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.555961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ae54b38-1d4f-48ec-8468-51fff59d5bb9 · outbound

This paper cites Controlling process instability for defect lean metal additive manufacturing.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Controlling process instability for defect lean metal additive manufacturing

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.538055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1439145f-e5ab-457a-bbb1-bd1fc6d27680 · outbound

This paper cites Computational investigation of melt pool process dynamics and pore formation in laser powder bed fusion.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Computational investigation of melt pool process dynamics and pore formation in laser powder bed fusion

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.519214Z

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Observation 61f33bbb-8aeb-4b4f-91b8-6c026eb4d862 · outbound

This paper cites Cfd simulation of fluid flow during laser metal wire deposition using openfoam: 3d printing, 2019.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Cfd simulation of fluid flow during laser metal wire deposition using openfoam: 3d printing, 2019

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.503396Z

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Observation 8577babb-00fb-441c-887b-467a4ce946ea · outbound

This paper cites Openfoam documentation.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Openfoam documentation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.487663Z

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Observation 6552f0ae-c557-4a9a-b235-6339e10ad75f · outbound

This paper cites Convolutional neural networks for melt depth prediction and visualization in laser powder bed fusion.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Convolutional neural networks for melt depth prediction and visualization in laser powder bed fusion

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.469973Z

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Observation 213e21f5-aa22-48b3-9e6f-fca0275c2ac2 · outbound

This paper cites Simulation of melt pool behaviour during additive manufactur- ing: Underlying physics and progress.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Simulation of melt pool behaviour during additive manufactur- ing: Underlying physics and progress

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.453146Z

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Observation aac21624-3a02-4fcb-9f66-83784d03ad91 · outbound

This paper cites Random forests.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Random forests

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T20:20:41.061209Z

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Observation 9291fa2e-fb39-47c7-855b-225d5ce9ed38 · outbound

This paper cites The elements of statistical learning: data mining, inference, and prediction, 2009.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning The elements of statistical learning: data mining, inference, and prediction, 2009

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T20:20:41.066022Z

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This paper cites Classification and regression by randomforest.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Classification and regression by randomforest

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.415214Z

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Observation dca1381d-b2c9-40eb-bfc0-fb66cebb1d4d · outbound

This paper cites Extremely randomized trees.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Extremely randomized trees

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.398933Z

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Observation 0f82658a-33eb-4e7d-a6ce-4e47511596b0 · outbound

This paper cites Scikit-learn: Machine learning in python fabian.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Scikit-learn: Machine learning in python fabian

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.382781Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ae15234d-10fd-482c-acc3-e4ce5b235a54 · outbound

This paper cites Bagging predictors.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Bagging predictors

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.367444Z

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Observation c1e2a982-2cef-4f91-944d-e977126e29bc · outbound

This paper cites An introduction to kernel and nearest-neighbor nonparametric regression.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning An introduction to kernel and nearest-neighbor nonparametric regression

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.352408Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fa85312d-7cf3-44f1-a348-9a18a5a2e937 · outbound

This paper cites Nearest neighbor pattern classification.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Nearest neighbor pattern classification

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:41.337046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 672fc31b-a1e7-4480-b820-a0008e2e3925 · outbound

This paper cites Greedy function approximation: a gradient boosting machine.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Greedy function approximation: a gradient boosting machine

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T20:20:41.099949Z

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Observation 4c5599de-e787-4fe4-b634-8728f91494fc · outbound

This paper cites Gradient boosting machines, a tutorial.

Discovery of Spatter Constitutive Models in Additive Manufacturing Using Machine Learning Gradient boosting machines, a tutorial

Reference 62

Resolution: verified exact; raw_fallback, observed 2026-08-10T20:20:41.286184Z

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