University of Nottingham Ningbo China Showcase

This dataset contains the experimental data supporting the findings of the study on the fabrication of high-resolution conductive carbon architectures via DLP-based additive manufacturing using a polymer-derived SiOC scaffold. The dataset includes data related to resin formulation optimization, photopolymerization characterization, thermal conversion, structural evolution, electrical conductivity, Joule heating performance, and electrochemical properties of the pyrolyzed SiOC-derived carbon structures. These data provide comprehensive support for understanding the relationship between processing parameters, microstructural evolution, and functional properties of the printed conductive architectures.

A feature-based machine learning training data

simulated release curve of four multi-material designs

Data and Codes

dataset for YOLOv8 based dead fish UAV detection in aquaculture

The dataset of the paper "Integrating 3D Printed Grinding Tools and Closed-Loop Temperature Management for Optimal Surgical Outcomes".

Boosting the Vat Photopolymerization Fidelity through a Machine Learning based Boundary Prediction

single nozzle based multi-material direct ink writing

datda for paper A 2-in-1 osteonecrosis treatment strategy enabled by additive manufactured hollow drill bit.

This dataset contains thermocouple temperature data in °C obtained from Fire Dynamic Simulation (FDS) of a 5MW HRR polyurethane GM27 fire in a multi-storey Double Skin Façade (DSF) building with Venetian blinds. The Excel spreadsheet has temperature data obtained from thermocouples installed on the glazing surfaces in the DSF cavity for floors 2, 3 and 4 (see Physical Model and Thermocouple Map). The data is presented for the scenarios where there is no Venetian blind installed in the DSF cavity to when the Venetian blind is 0.5m away from the inner glazing, Middle and 0.5m away from the outer glazing in the DSF cavity. In these scenarios the dataset also shows the glazing surface temperatures for various Venetian blind slat angle openings of 135°, 90°, 45° and 0° in the three Venetian blind positions in the DSF cavity. The simulation was carried out at 100s per scenario. The dataset also contains the input and output data files obtained from the National Institute of Standards and Technology’s (NIST) Fire Dynamic Simulator (FDS) software used for the investigations. A PDF of the Physical Model and Thermocouple Position Map is also provided in this dataset to provide clarity for users of this dataset. The input and output source codes are provided in folders labelled Fire in DSF with Venetian Blind - Input Data and Fire in DSF with Venetian Blind - Output Data respectively. The dataset also includes the model validation data. The model validation data includes the surface temperatures in °C obtained from two thermocouples labelled TC 59 installed at a height of 1.6m representing the thermocouple on the upper floor and TC 63 installed at a height of 4.8m representing the thermocouple on the lower floor. The input source code for the simulation for the model validation is also included and labelled ‘Validation-Input’. A thermocouple map labelled Thermocouple Map-Validation Model is also included to provide users with clarity. Further information and details related to this dataset can be found in: Huang Y, Yeboah S, Shao J. Numerical investigation of fire in the cavity of naturally ventilated double skin façade with venetian blinds. Building Services Engineering Research and Technology. 2022;0(0). doi:10.1177/01436244221129763. https://journals.sagepub.com/doi/10.1177/01436244221129763