School of Mechanical and Aerospace Engineering (MAE)

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1 to 10 of 49 Results

Replication Data for: Electrostatically driven micromolding of viscous functional materials for fabricating complex architecturess Sep 21, 2026 - CHEN Geng Chen, Geng, 2026, "Replication Data for: Electrostatically driven micromolding of viscous functional materials for fabricating complex architecturess", https://doi.org/10.21979/N9/YJDV53, DR-NTU (Data), V4, UNF:6:NN/eGaKuXX1Io4VASiBxaQ== [fileUNF] This dataset provides the original data for figures in the manuscript
FO pore formation - Ti-6Al-4V EB-PBF Sep 3, 2026 - NGIAM Chao Xiang Ngiam, Chao Xiang, 2026, "FO pore formation - Ti-6Al-4V EB-PBF", https://doi.org/10.21979/N9/GJ5PGY, DR-NTU (Data), V1, UNF:6:ETxO9y/ZgKDTvy83znCMyg== [fileUNF] This dataset contains information relating to the investigation of FO pore retention in high layer thickness printing of electron beam powder bed fusion with Ti-6Al-4V
AI4ATM-ADS-B-Singapore-FIR-2024-04-01 Aug 5, 2026 - Bizhao PANG Pang, Bizhao, 2026, "AI4ATM-ADS-B-Singapore-FIR-2024-04-01", https://doi.org/10.21979/N9/FPEAO4, DR-NTU (Data), V1, UNF:6:s3mSeU49QuIxCyFn5u8mRA== [fileUNF] Sample ADS-B trajectory data from the Singapore Flight Information Region, including aircraft movement information used for traffic analysis and model validation.
AI4ATM-Weather-Radar-Image_Singapore-FIR-20240401 Aug 5, 2026 - Bizhao PANG Pang, Bizhao, 2026, "AI4ATM-Weather-Radar-Image_Singapore-FIR-20240401", https://doi.org/10.21979/N9/NDWOS6, DR-NTU (Data), V1 Sample weather radar images over Singapore airspace, used to represent convective weather conditions and support weather-aware trajectory planning.
AI4ATM-Wind-Field-Singapore-FIR-20240401 Aug 5, 2026 - Bizhao PANG Pang, Bizhao, 2026, "AI4ATM-Wind-Field-Singapore-FIR-20240401", https://doi.org/10.21979/N9/AGDTOA, DR-NTU (Data), V1, UNF:6:/xfh7wc6MMp9Oao0FdF1UA== [fileUNF] Sample wind-field data for the Singapore Flight Information Region, used to model wind effects in aircraft trajectory prediction and rerouting experiments.
RF-MatID Frequency-domain Dataset Apr 15, 2026 - YANG Jianfei Chen, Xinyan, 2026, "RF-MatID Frequency-domain Dataset", https://doi.org/10.21979/N9/YLDFJM, DR-NTU (Data), V1 We introduce RF-MatID, a comprehensive dataset and benchmark designed to bridge the gap in robust material identification. RF-MatID is the largest and most diverse dataset of its kind, featuring: - 16 fine-grained categories derived from 5 superclasses (e.g., Plastic, Metal, Wood...
RF-MatID Time-domain Dataset Apr 15, 2026 - YANG Jianfei Chen, Xinyan, 2026, "RF-MatID Time-domain Dataset", https://doi.org/10.21979/N9/ZJ50DD, DR-NTU (Data), V1 We introduce RF-MatID, a comprehensive dataset and benchmark designed to bridge the gap in robust material identification. RF-MatID is the largest and most diverse dataset of its kind, featuring: - 16 fine-grained categories derived from 5 superclasses (e.g., Plastic, Metal, Wood...
TandemFoilSet: Datasets for Flow Field Prediction of Tandem-Airfoil Through the Reuse of Single Airfoils Feb 25, 2026 - Airfoils Datasets For Deep Learning (AI4Science) Lim, Wei Xian; Chan, Wai Lee; Kong, Wai-Kin Adams; Jessica, Loh Sher En, 2026, "TandemFoilSet: Datasets for Flow Field Prediction of Tandem-Airfoil Through the Reuse of Single Airfoils", https://doi.org/10.21979/N9/KTXSCU, DR-NTU (Data), V1 Accurate simulation of flow fields around tandem geometries is critical for engineering design but remains computationally intensive. Existing machine learning approaches typically focus on simpler cases and lack evaluation on multi-body configurations. To support research in thi...
Data used for: Extremely stiff and lightweight auxetic metamaterial designs enabled by asymmetric strut cross-sections Jul 18, 2025 - Cost-Effective and Versatile Method of Additively Manufacturing 3D Metal Structures Seetoh, Peiyuan Ian; Lai, Chang Quan, 2025, "Data used for: Extremely stiff and lightweight auxetic metamaterial designs enabled by asymmetric strut cross-sections", https://doi.org/10.21979/N9/DSILXC, DR-NTU (Data), V1, UNF:6:/XPpccthazACMum1Ub6yMQ== [fileUNF] Data used in the journal publication "Extremely stiff and lightweight auxetic metamaterial designs enabled by asymmetric strut cross-sections"
Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields Jun 11, 2025 - Airfoils Datasets For Deep Learning (AI4Science) Lim, Wei Xian; Chan, Wai Lee, 2025, "Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields", https://doi.org/10.21979/N9/9OYSTD, DR-NTU (Data), V1 The field of computational fluid dynamics (CFD) is integral to engineering disciplines, particularly for designing systems that operate under complex fluid flow conditions. Accurate simulation of flow fields is essential for optimizing performance across a variety of applications...

Replication Data for: Electrostatically driven micromolding of viscous functional materials for fabricating complex architecturess

Sep 21, 2026 - CHEN Geng

Chen, Geng, 2026, "Replication Data for: Electrostatically driven micromolding of viscous functional materials for fabricating complex architecturess", https://doi.org/10.21979/N9/YJDV53, DR-NTU (Data), V4, UNF:6:NN/eGaKuXX1Io4VASiBxaQ== [fileUNF]

This dataset provides the original data for figures in the manuscript

FO pore formation - Ti-6Al-4V EB-PBF

Sep 3, 2026 - NGIAM Chao Xiang

Ngiam, Chao Xiang, 2026, "FO pore formation - Ti-6Al-4V EB-PBF", https://doi.org/10.21979/N9/GJ5PGY, DR-NTU (Data), V1, UNF:6:ETxO9y/ZgKDTvy83znCMyg== [fileUNF]

This dataset contains information relating to the investigation of FO pore retention in high layer thickness printing of electron beam powder bed fusion with Ti-6Al-4V

AI4ATM-ADS-B-Singapore-FIR-2024-04-01

Aug 5, 2026 - Bizhao PANG

Pang, Bizhao, 2026, "AI4ATM-ADS-B-Singapore-FIR-2024-04-01", https://doi.org/10.21979/N9/FPEAO4, DR-NTU (Data), V1, UNF:6:s3mSeU49QuIxCyFn5u8mRA== [fileUNF]

Sample ADS-B trajectory data from the Singapore Flight Information Region, including aircraft movement information used for traffic analysis and model validation.

AI4ATM-Weather-Radar-Image_Singapore-FIR-20240401

Aug 5, 2026 - Bizhao PANG

Pang, Bizhao, 2026, "AI4ATM-Weather-Radar-Image_Singapore-FIR-20240401", https://doi.org/10.21979/N9/NDWOS6, DR-NTU (Data), V1

Sample weather radar images over Singapore airspace, used to represent convective weather conditions and support weather-aware trajectory planning.

AI4ATM-Wind-Field-Singapore-FIR-20240401

Aug 5, 2026 - Bizhao PANG

Pang, Bizhao, 2026, "AI4ATM-Wind-Field-Singapore-FIR-20240401", https://doi.org/10.21979/N9/AGDTOA, DR-NTU (Data), V1, UNF:6:/xfh7wc6MMp9Oao0FdF1UA== [fileUNF]

Sample wind-field data for the Singapore Flight Information Region, used to model wind effects in aircraft trajectory prediction and rerouting experiments.

RF-MatID Frequency-domain Dataset

Apr 15, 2026 - YANG Jianfei

Chen, Xinyan, 2026, "RF-MatID Frequency-domain Dataset", https://doi.org/10.21979/N9/YLDFJM, DR-NTU (Data), V1

We introduce RF-MatID, a comprehensive dataset and benchmark designed to bridge the gap in robust material identification. RF-MatID is the largest and most diverse dataset of its kind, featuring: - 16 fine-grained categories derived from 5 superclasses (e.g., Plastic, Metal, Wood...

RF-MatID Time-domain Dataset

Apr 15, 2026 - YANG Jianfei

Chen, Xinyan, 2026, "RF-MatID Time-domain Dataset", https://doi.org/10.21979/N9/ZJ50DD, DR-NTU (Data), V1

TandemFoilSet: Datasets for Flow Field Prediction of Tandem-Airfoil Through the Reuse of Single Airfoils

Feb 25, 2026 - Airfoils Datasets For Deep Learning (AI4Science)

Lim, Wei Xian; Chan, Wai Lee; Kong, Wai-Kin Adams; Jessica, Loh Sher En, 2026, "TandemFoilSet: Datasets for Flow Field Prediction of Tandem-Airfoil Through the Reuse of Single Airfoils", https://doi.org/10.21979/N9/KTXSCU, DR-NTU (Data), V1

Accurate simulation of flow fields around tandem geometries is critical for engineering design but remains computationally intensive. Existing machine learning approaches typically focus on simpler cases and lack evaluation on multi-body configurations. To support research in thi...

Data used for: Extremely stiff and lightweight auxetic metamaterial designs enabled by asymmetric strut cross-sections

Jul 18, 2025 - Cost-Effective and Versatile Method of Additively Manufacturing 3D Metal Structures

Seetoh, Peiyuan Ian; Lai, Chang Quan, 2025, "Data used for: Extremely stiff and lightweight auxetic metamaterial designs enabled by asymmetric strut cross-sections", https://doi.org/10.21979/N9/DSILXC, DR-NTU (Data), V1, UNF:6:/XPpccthazACMum1Ub6yMQ== [fileUNF]

Data used in the journal publication "Extremely stiff and lightweight auxetic metamaterial designs enabled by asymmetric strut cross-sections"

Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields

Jun 11, 2025 - Airfoils Datasets For Deep Learning (AI4Science)

Lim, Wei Xian; Chan, Wai Lee, 2025, "Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields", https://doi.org/10.21979/N9/9OYSTD, DR-NTU (Data), V1

The field of computational fluid dynamics (CFD) is integral to engineering disciplines, particularly for designing systems that operate under complex fluid flow conditions. Accurate simulation of flow fields is essential for optimizing performance across a variety of applications...

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