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Dataset for: Deep-Learning-Based Digital Twin Method for Personalized Optimization and Health Monitoring of Electric Vehicles
Aug 21, 2024 - LYU Chen
Lyu, Chen, 2024, "Dataset for: Deep-Learning-Based Digital Twin Method for Personalized Optimization and Health Monitoring of Electric Vehicles", https://doi.org/10.21979/N9/1GX2YP, DR-NTU (Data), V1
Dataset for Project "Deep-Learning-Based Digital Twin Method for Personalized Optimization and Health Monitoring of Electric Vehicles"
GMM_Cruise_City.mat
Aug 21, 2024 - Dataset for: Deep-Learning-Based Digital Twin Method for Personalized Optimization and Health Monitoring of Electric Vehicles
MATLAB Data - 1.2 KB - MD5: bbb0eaab7cab04c77e757876924aeb93
GMM_Cruise_Highway.mat
Aug 21, 2024 - Dataset for: Deep-Learning-Based Digital Twin Method for Personalized Optimization and Health Monitoring of Electric Vehicles
MATLAB Data - 1.2 KB - MD5: 13f11ee466b61d0322fb98620576e56a
GMM_Cruise_Rural.mat
Aug 21, 2024 - Dataset for: Deep-Learning-Based Digital Twin Method for Personalized Optimization and Health Monitoring of Electric Vehicles
MATLAB Data - 1.2 KB - MD5: f23ce02ac384fd56c2a3e5e79c692e24
Supersonic Impinging Jet Flat Wall OpenFOAM
Aug 19, 2024 - Rion YOU
You, Rion Guang Yi, 2024, "Supersonic Impinging Jet Flat Wall OpenFOAM", https://doi.org/10.21979/N9/NDJUSJ, DR-NTU (Data), V1
Supersonic Impinging Jet Ma = 1.45 NPR = 4 H = 1.5D Medium Mesh 16M Cells OpenFOAM V2112
alphat.gz
Aug 19, 2024 - Supersonic Impinging Jet Flat Wall OpenFOAM
Gzip Archive - 56.2 MB - MD5: 1c0ba1920bc4a20e8745b4334ed16914
alphat.gz
Aug 19, 2024 - Supersonic Impinging Jet Flat Wall OpenFOAM
Gzip Archive - 56.8 MB - MD5: 506a1157e6374106133551cb0834021a
alphat.gz
Aug 19, 2024 - Supersonic Impinging Jet Flat Wall OpenFOAM
Gzip Archive - 55.3 MB - MD5: 9e26e309fa475ea24ba70b8f17e056a4
alphat.gz
Aug 19, 2024 - Supersonic Impinging Jet Flat Wall OpenFOAM
Gzip Archive - 57.2 MB - MD5: caa38f72447df03f3f0c21643047677a
alphat.gz
Aug 19, 2024 - Supersonic Impinging Jet Flat Wall OpenFOAM
Gzip Archive - 57.6 MB - MD5: 493be33bfde7e99f2268a2f24c05244d
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