J
Jacopo Buongiorno
Researcher at Massachusetts Institute of Technology
Publications - 179
Citations - 14455
Jacopo Buongiorno is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Boiling & Nanofluid. The author has an hindex of 40, co-authored 170 publications receiving 12125 citations. Previous affiliations of Jacopo Buongiorno include Electric Power Research Institute & Tokyo Electric Power Company.
Papers
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Feasibility Study of Supercritical Light Water Cooled Fast Reactors for Actinide Burning and Electric Power Production Progress Report for Year 1, Quarter 2 (January - March 2002)
TL;DR: The use of light water at supercritical pressures as the coolant in a nuclear reactor offers the potential for considerable plant simplification and consequent capital and O&M cost reduction compared with current light water reactor (LWR) designs as mentioned in this paper.
Measurement and Model Correlation of Specific Heat Capacity of Water-Based Nanofluids With Silica, Alumina and Copper Oxide Nanoparticles
TL;DR: In this paper, the specific heat capacities of water-based silica, alumina, and copper oxide nanofluids were measured using differential scanning calorimetry, and the results were in excellent agreement with Model II, while the predictions of Model I deviate very significantly from the data.
Proceedings ArticleDOI
Energy and water, no carbon: integrated nuclear power and large-scale desalination at diablo canyon
Journal ArticleDOI
Insights in the safety analysis of an early microreactor design
TL;DR: In this article , a safety analysis of a transportable, plug-and-play, heat-pipe-cooled microreactor designed at MIT is presented, where the analysis makes use of a recently proposed methodology that integrates i) System-Theoretic Accident Model and Processes (STAMP) to guide a qualitative exploration of the NB threats and hazards, ii) Modeling and Simulation (M&S) to investigate the NB dynamic behavior during accident scenarios, and iii) Goal-Tree Success-Tree Master Logic Diagram (GTST-MLD) to assess risk quantitatively.