About

Professor Yassin A. Hassan holds the Royce E. Wisenbaker’39 Chair in Engineering and serves as a Professor in both the Department of Nuclear Engineering and the Department of Mechanical Engineering at Texas A&M University. He leads research efforts within the thermal-hydraulic research community, collaborating with professional engineers, graduate, and undergraduate students in his laboratory. His work contributes to advancing knowledge and technology in thermal-hydraulics, a critical area in engineering that intersects nuclear and mechanical disciplines. Contact information provided includes his email y-hassan@tamu.edu and phone number 979-218-4417.

Research topics

• Mechanics
• Physics
• Computer Science
• Thermodynamics
• Materials science
• Composite material
• Optics
• Computational science
• Geometry
• Parallel computing
• Engineering
• Environmental science
• Mathematics
• Telecommunications
• Nuclear engineering
• Classical mechanics
• Mechanical engineering
• Aerospace engineering

Selected publications

• RELAP5-3D simulation of natural circulation start-up and station blackout benchmark for a NuScale-like iPWR

  Progress in Nuclear Energy · 2026-01-21

  articleSenior author
  PublisherDOI

• Study on the interaction between free surface and flow using PIV

  2026-02-18

  book-chapterSenior author

  The interaction between the free surface and flow was evaluated measuring the velocity distribution and surface movement simultaneously. The jet interacted with the free surface, causing the wavy free surface condition. The flow under the free surface was visualized by a laser light sheet and small tracer particles. With image processing techniques, the movement of the free surface and the movement of the particles were simultaneously measured from the recorded images, resulting in the velocity distributions and surface locations. Then, the interactions between the flow and free surface were evaluated using the form of turbulent energy and surface-related turbulent values. By increasing the turbulent energy near the free surface, the fluctuations of the free surface height and the inclination of the free surface were increased. The image processing technique is found to be very useful to evaluate the interaction between free surface and flow.

  PublisherDOI

• Mitigating airborne pathogen risks in a full-scale meat processing facility

  Total Environment Microbiology · 2025-07-15 · 2 citations

  articleOpen access

  Foodborne illnesses caused by Shiga toxin-producing Escherichia coli (STEC) and Salmonella represent a major public health concern, particularly in meat processing facilities where bioaerosols generated during processes like carcass spraying and dehiding can lead to contamination. In this study, we assessed airborne concentrations of STEC and Salmonella at multiple locations within a full-scale meat processing facility using quantitative polymerase chain reaction (qPCR) and Illumina MiSeq sequencing. Additionally, we utilized computational fluid dynamics (CFD) simulations to model airflow within the facility and evaluated the effectiveness of air curtains in mitigating the transfer of bioaerosols between high-risk (dehiding and tripe) and low-risk (chiller and fabrication) areas. qPCR results showed that pathogen concentrations in the dehiding rooms were 126 GCN/m³ for STEC and 105 GCN/m³ for Salmonella during spring, with levels rising significantly in summer (2198 GCN/m³ for STEC and 1799 GCN/m³ for Salmonella ). Simulated airflow patterns revealed that entrained bioaerosols could be transported from unclean to clean areas, increasing the risk of cross-contamination. The use of air curtains effectively reduced this spread by creating barriers between high- and low-risk areas. Our findings suggest that bacterial survivability and aerosolization was enhanced in summer, highlighting the critical role of environmental factors and airflow management in controlling contamination risks. This study demonstrates the value of integrating experimental data with CFD simulations to assess pathogen spread and identify effective mitigation strategies in meat processing facilities.

  PublisherDOI

• Experiments and CFD for Wire-Wrapped Fuel Assembly Blockages

  Nuclear Technology · 2025-08-25 · 2 citations

  articleSenior author
  PublisherDOI

• Advanced optical investigation of near-wall flow and heat transfer in a randomly packed pebble bed

  Physics of Fluids · 2025-09-01 · 1 citations

  articleSenior author

  This study employs time-resolved particle image velocimetry (TR-PIV) and laser-induced fluorescence (LIF) to experimentally investigate near-wall flow and heat transfer dynamics in a randomly packed pebble bed under both isothermal and non-isothermal conditions. A cylindrical borosilicate glass test section is packed with glass pebbles at a bed-to-sphere diameter ratio of 4.84 and includes two stainless-steel pebbles heated using an induction coil. By matching the refractive index of the working fluid, D-Limonene, with that of the glass, high-fidelity velocity and temperature measurements are obtained. Three-dimensional reconstruction of the randomly packed geometry validates computational domain fidelity for future numerical simulations. The TR-PIV data reveal that heated spheres induce buoyancy-driven flow features, altering local turbulence, vortex formation, and thermal mixing in the voids between pebbles and the wall. The proper orthogonal decomposition and vortex identification techniques confirm the vortex and circulation in non-isothermal conditions. Complementary LIF measurements captured temperature distributions around the heated spheres, which showed buoyancy-driven effects that varied with Reynolds number and flow direction. Notably, higher Reynolds numbers dispersed heat more effectively throughout the interstitial pores, while lower Reynolds numbers showed localized heating near the spheres. These results furnish comprehensive datasets for the validation of computational fluid dynamics models and offer deeper insight into reactor core design considerations for next-generation high-temperature gas-cooled reactor systems.

  PublisherDOI

• Sensitivity Analysis and Uncertainty Quantification of a Digital Twin-Based Simulator for Small Modular and Microreactors

  2025-04-09 · 1 citations

  articleOpen access

  Abstract For a digital twin (DT) to be effective, it must accurately represent the system it models. Sensitivity Analyses (SA) and Uncertainty Quantification (UQ) are crucial for enhancing the adaptability and reliability of DTs under system variations and uncertainties. This paper presents a comprehensive SA and UQ of a DT-based simulator for Advanced Small-scale (Gen IV) Reactors, focusing on a conceptual 4.5 MWth Small Modular Lead-cooled Fast Reactor (LFR). The simulator integrates design aspects from the main LFR families and seamlessly connects with instrumentation and control (I&C) systems via an advanced human-machine interface (HMI), enabling real-time visualization of reactor transients to enhance operational safety and efficiency. The Sobol global sensitivity analysis was employed to rank influential parameters affecting reactor performance, focusing on first-order and total sensitivity indices. Results showed that at full operating power, key contributors to output variance included coolant heat capacity, core inlet/outlet temperatures, initial (nominal) power, and structural parameters like fuel pitch and radius. Neutron decay fractionswere significant at full power but diminished at lower powers. Time-dependent analysis revealed coolant heat capacity as the dominant factor, while derived parameters had minimal impact. UQ findings indicated that coolant bulk temperature exhibited the highest variability, while cladding temperature had the lowest.Based on these results, optimizations were made to enhance the DT framework’s robustness and effectiveness in simulating reactor dynamics while adhering to safety standards. This research underscores the importance of incorporating advanced SA and UQ techniques in digital twin technologies, vital for risk management and model validation. These findings could inform future design and operational decisions in reactor technology, impacting regulatory practices and industry standards to support the safe and efficient deployment of next-generation nuclear technologies

  PublisherOA PDFDOI

• Conditions for bubble recirculation in a molten salt natural circulation loop and heater failure effect on loop conditions and argon bubble dynamics

  Nuclear Engineering and Design · 2025-09-18 · 1 citations

  articleOpen accessSenior author

  Off-gas systems employing bubble injection have been proposed as an effective method for removing gaseous fission products in molten salt reactors (MSRs). In a semi-closed loop, bubbles may remain entrained in the fluid even after the gas has passed the point where the bubble should escape the fluid, and then recirculates through the loop. Bubble recirculation poses risks to reactivity control and flow stability in the operation of the off-gas systems of MSRs. The longer the bubble is in the reactor the higher the concentration of fission products in the bubble. This can cause changes in local reactivity and power profiles. This study experimentally investigates the mechanisms behind bubble recirculation in a natural circulation molten salt loop under degraded thermal conditions. Advanced flow diagnostics such as Particle image velocimetry (PIV), particle tracking velocimetry (PTV), and proper orthogonal decomposition (POD) were employed to characterize bubble trajectories, slip velocities, and associated flow structures. A downcomer heater failure created asymmetric heating, leading to partial salt freezing and flow stagnation, while the blocked expansion tank prevented bubble venting. Over time, recirculating bubbles coalesced, increasing in size and altering local flow behavior. Measured slip velocities diverge significantly from drift-flux model predictions, underscoring the limitations under off-normal conditions. POD analysis revealed dominant wake structures and vortex interactions, and temporal cross-correlations revealed a sequence of flow phenomena induced by bubble motion. These findings underscore the need to maintain thermal uniformity and suggest refinements to computational models of off-gas systems in MSRs. • Bubble recirculation observed in molten-salt natural circulation loop. • Slip velocities diverged from drift-flux predictions under off-normal conditions. • Downcomer heater failure caused asymmetric heating and salt freezing. • POD revealed coherent wake structures and Kármán-like vortex interactions.

  PublisherDOI

• Experimental Study on Near-Wall Flow Dynamics of a Pebble Bed With Advanced Measurement Techniques

  ASME Journal of Heat and Mass Transfer · 2025-09-15 · 1 citations

  articleSenior author

  Abstract We performed a controlled laboratory campaign to map the velocity field inside a randomly packed pebble bed facility using particle image velocimetry (PIV). The optically transparent borosilicate duct was loaded with 30 mm glass spheres, giving a bed-to-sphere diameter ratio of 4.84. This arrangement enabled nonintrusive interrogation of near-wall flow dynamics for both upward- and downward-directed isothermal flows. Using d-Limonene with matched index of refraction (MIR) techniques, we captured high-resolution velocity maps and reconstructed the three-dimensional (3D) randomly packed pebble configuration. The PIV results produced first- and second-order statistical measures of the flow, including assessments of mean velocity magnitude, velocity fluctuations, Reynolds stresses revealing jet, recirculation, and bypass flow structures within the interstitial voids of the randomly packed pebble bed. These structures change in position and intensity as the bulk flow direction is reversed. Proper orthogonal decomposition (POD) and multiscale vortex-identification algorithms further exposed turbulent coherent structures and regions of high vorticity. The resulting high-fidelity database will support future validation of computational fluid dynamics (CFD) models for pebble bed reactor cores (PBR). Ultimately, the insights gained here help refine the design envelope of pebble-bed reactor cores and related energy storage systems.

  PublisherDOI

• Large language model-assisted digital twin for remote monitoring and control of advanced reactors

  Progress in Nuclear Energy · 2025-12-10 · 1 citations

  article
  PublisherDOI

• Critical Heat Flux Prediction and Uncertainty Quantification with Bayesian Optimized Deep Ensemble

  2025-04-09

  articleOpen access

  Abstract Understanding Critical Heat Flux (CHF) is crucial for the safe operation of water-cooled nuclear reactors. Advancements in machine learning (ML) offer new opportunities to improve CHF predictions. The US Nuclear Regulatory Commission (USNRC) released the NRC CHF database, which contains approximately 25,000 data points. These data are noisy and influenced by various sources of uncertainty, as they originate from multiple experiments. To understand the limitations of any neural network applied to this data, it is crucial to estimate the uncertainty associated with the inherent noise, known as aleatoric uncertainty, as well as the epistemic uncertainty, which arises from the model’s limited knowledge. To generate data-driven models with Uncertainty Quantification (UQ) capability, we applied the Deep Ensemble (DE) method combined with Bayesian Optimization (BO), named BODE, to optimize an ensemble of deep neural networks (DNNs) trained on the NRC CHF database, focusing on estimating both aleatoric and epistemic uncertainties. The approach improves predictive accuracy and uncertainty quantification. The optimized model exhibited improved predictive accuracy and reduced uncertainties when compared to the baseline model. The results of the BODE, and a comparison of the BODE and baseline ensemble models are presented, focusing on key metrics such as RMSPE, MAPE, and EQ2.

  PublisherOA PDFDOI

Frequent coauthors

• Rodolfo Vaghetto

  Electric Power Research Institute

  94 shared

• Elia Merzari

  Argonne National Laboratory

  76 shared

• Saya Lee

  Pennsylvania State University

  58 shared

• Thien Nguyen

  Oak Ridge National Laboratory

  49 shared

• N. K. Anand

  45 shared

• Javier Ortíz-Villafuerte

  40 shared

• Joseph Seo

  39 shared

• Victor M. Ugaz

  Texas A&M University

  36 shared

Labs

• THRLabPI

  In our laboratory, professors, professional engineers, and graduate and undergraduate students work together to contribute to the thermal-hydraulic research community worldwide.

Awards & honors

• Research Impact Award, Texas A&M Engineering Experiment Stat…
• Association of Former Students Distinguished Research Award…
• American Nuclear Society Seaborg Medal – 2008
• James N. Landis Medal, American Society of Mechanical Engine…
• Inaugural Flow Visualization Competition and Prize, Fluids E…