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Juliana Pacheco Duarte

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Assistant Professor

University of Wisconsin-Madison

United States

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About

Juliana Pacheco Duarte is an Assistant Professor at the University of Wisconsin-Madison, USA. Her research focuses on fire dynamics, natural circulation phenomena, and the application of machine learning to complex thermal systems. Recent articles include studies on heat release rates in electrical cabinet fires, density wave instabilities, and the effects of nanofluids on critical heat flux, showcasing her expertise in both experimental and computational modeling within nuclear engineering and fire safety domains.

Recent Grants

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Identifying Needed Fire Input Data to Reduce Modeling Uncertainty

Open Date: 2019-10-01

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Articles (22)

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Collaborators (1)

Brian Lattimer

Professor

Virginia Tech

UNITED STATES

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Juliana Pacheco Duarte

Research Interests

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About

Recent Grants

Articles (22)

Quantifying the Influence of Parameters on Heat Release Rate in Electrical Cabinet Fires

A recurrent neural network for modeling natural circulation density wave instabilities

Development of HRR Distributions in Electrical Enclosure Fire Scenario Through Machine Learning

TRACE assessment of density wave instability onset with void reactivity feedback under natural circulation

Modeling of quenching temperature with the effects of axial conduction resulting from quench front propagation

TRACE Assessment for Simulating Density Wave Oscillations in a Full-Scale BWR Rod Bundle Under Natural Circulation

Uncertainty quantification of unconfined spill fire data by coupling Monte Carlo and artificial neural networks

Analysis of the Effects of Different Nanofluids on Critical Heat Flux Using Artificial Intelligence

Assessing spill fire characteristics through machine learning analysis

Discrete-Time Bayesian Networks Applied to Flexible Coping Strategies of Nuclear Power Plant Systems

Analysis of historic fires to determine most frequent challenging events

High-resolution pre diction of quenching b ehavior using machine learning based on optical fiber temperature measurement

Physics-informed machine learning-aided framework for prediction of minimum film boiling temperature

Analysis of historic fires to determine most frequent challenging events

High-resolution prediction of quenching behavior using machine learning based on optical fiber temperature measurement

Physics-informed machine learning-aided framework for prediction of minimum film boiling temperature

Implementation of fiber optic temperature sensors in quenching heat transfer analysis

Implementation of fiber optic temperature sensors in quenching heat transfer analysis

Flow boiling heat transfer coefficient of DI water and nanofluids inside microscale channels under conditions near the critical heat flux (CHF)

Flow boiling heat transfer coefficient of DI water and nanofluids inside microscale channels under conditions near the critical heat flux (CHF)

Full-scale dryout/rewet instability tests in a BWR rod bundle and TRACE assessment

Full-scale dryout/rewet instability tests in a BWR rod bundle and TRACE assessment

Collaborators (1)

Brian Lattimer

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