Articles de revista
http://hdl.handle.net/2117/347114
2024-03-29T09:36:47Z
2024-03-29T09:36:47Z
Magnetically induced gluing bifurcations of three-tori in spherical Couette flows
García González, Fernando
http://hdl.handle.net/2117/402800
2024-02-26T00:27:06Z
2024-02-22T13:51:01Z
Magnetically induced gluing bifurcations of three-tori in spherical Couette flows
García González, Fernando
The global dynamics of three-tori associated with homoclinic/heteroclinic global (infinite period) bifurcations are investigated for the magnetized spherical Couette problem, a paradigmatic model in geo- and astrophysical magnetohydrodynamics (MHD). A novel homoclinic bifurcation, involving collision between three-tori, is described. In addition, a heteroclinic bifurcation connecting two unstable two-tori with a stable three-torus is also analyzed. The role of the flow's spatial symmetries in this bifurcation scenario is also investigated. This bifurcation scenario gives rise to MHD flows that combine small with extremely large time scales.
2024-02-22T13:51:01Z
García González, Fernando
The global dynamics of three-tori associated with homoclinic/heteroclinic global (infinite period) bifurcations are investigated for the magnetized spherical Couette problem, a paradigmatic model in geo- and astrophysical magnetohydrodynamics (MHD). A novel homoclinic bifurcation, involving collision between three-tori, is described. In addition, a heteroclinic bifurcation connecting two unstable two-tori with a stable three-torus is also analyzed. The role of the flow's spatial symmetries in this bifurcation scenario is also investigated. This bifurcation scenario gives rise to MHD flows that combine small with extremely large time scales.
Flow regime analysis of high-pressure transcritical fluids in microducts
Bandarrinha Monteiro, Carlos Alexandre
Jofre Cruanyes, Lluís
http://hdl.handle.net/2117/402009
2024-02-15T12:50:17Z
2024-02-15T12:49:56Z
Flow regime analysis of high-pressure transcritical fluids in microducts
Bandarrinha Monteiro, Carlos Alexandre; Jofre Cruanyes, Lluís
Microduct flows are known for their inherent laminar regimes resulting from the characteristic small dimensions and low velocities. In this regard, direct numerical simulations are employed to investigate an innovative approach that harnesses the unique thermophysical properties of high-pressure transcritical fluids to achieve significantly higher rates of mixing and heat transfer in microduct geometries. The strategy is based on the sizeable changes in properties that supercritical fluids, at pressures and temperatures exceeding their critical value, undergo across the pseudo-boiling region. To this end, four different cases are considered, and systematically analyzed, in which the bulk pressure and temperature difference between walls are varied. The results obtained indicate that laminar flow prevails at low-pressure conditions, while flow regimes with turbulent characteristics can be achieved when operating at high-pressure conditions with a transversal temperature difference. The transition to the turbulence-like regime is assessed by quantifying variations in velocity and temperature profiles, accompanied by the observation of secondary flow motions. As a result, substantial increases in the Nusselt number of roughly 20×, indicative of enhanced heat transfer, are obtained at the hot wall in comparison to cases with same temperature differences at low pressure.
2024-02-15T12:49:56Z
Bandarrinha Monteiro, Carlos Alexandre
Jofre Cruanyes, Lluís
Microduct flows are known for their inherent laminar regimes resulting from the characteristic small dimensions and low velocities. In this regard, direct numerical simulations are employed to investigate an innovative approach that harnesses the unique thermophysical properties of high-pressure transcritical fluids to achieve significantly higher rates of mixing and heat transfer in microduct geometries. The strategy is based on the sizeable changes in properties that supercritical fluids, at pressures and temperatures exceeding their critical value, undergo across the pseudo-boiling region. To this end, four different cases are considered, and systematically analyzed, in which the bulk pressure and temperature difference between walls are varied. The results obtained indicate that laminar flow prevails at low-pressure conditions, while flow regimes with turbulent characteristics can be achieved when operating at high-pressure conditions with a transversal temperature difference. The transition to the turbulence-like regime is assessed by quantifying variations in velocity and temperature profiles, accompanied by the observation of secondary flow motions. As a result, substantial increases in the Nusselt number of roughly 20×, indicative of enhanced heat transfer, are obtained at the hot wall in comparison to cases with same temperature differences at low pressure.
A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
Aguilar Plazaola, José Agustín
Chanal, Damien
Chamagne, Didier
Yousfi-Steiner, Nadia
Péra, Marie-Cécile
Husar, Attila Peter
Andrade-Cetto, Juan
http://hdl.handle.net/2117/401910
2024-02-18T21:55:49Z
2024-02-14T13:01:04Z
A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
Aguilar Plazaola, José Agustín; Chanal, Damien; Chamagne, Didier; Yousfi-Steiner, Nadia; Péra, Marie-Cécile; Husar, Attila Peter; Andrade-Cetto, Juan
The goal of increasing efficiency and durability of fuel cells can be achieved through optimal control of their operating conditions. In order to implement such controllers, accurate and computationally efficient fuel cell models must be developed. This work presents a hybrid (physics-based and data-driven), control-oriented model for approximating the output voltage of proton exchange membrane fuel cells (PEMFCs) while operating under dynamical conditions. First, a physics-based model, built from simplified electrochemical, membrane dynamics and mass conservation equations, is developed and validated through experimental data. Second, a data-driven, neural network (echo state network) is trained, fitted and tested with the same dataset. Then, the hybrid model is formed as a parallel structure, where the simplified physics-based model and the trained data-driven model are merged through an algorithm based on Gaussian radial basis functions. The merging algorithm compares the output of both single models and assigns weights for computing the prediction of the hybrid result. The proposed hybrid model structure is successfully trained, validated and tested with an experimental dataset originating from fuel cells within an automotive PEMFC stack. The hybrid model is assessed through the mean square error index, with the result of a low tracking error.
2024-02-14T13:01:04Z
Aguilar Plazaola, José Agustín
Chanal, Damien
Chamagne, Didier
Yousfi-Steiner, Nadia
Péra, Marie-Cécile
Husar, Attila Peter
Andrade-Cetto, Juan
The goal of increasing efficiency and durability of fuel cells can be achieved through optimal control of their operating conditions. In order to implement such controllers, accurate and computationally efficient fuel cell models must be developed. This work presents a hybrid (physics-based and data-driven), control-oriented model for approximating the output voltage of proton exchange membrane fuel cells (PEMFCs) while operating under dynamical conditions. First, a physics-based model, built from simplified electrochemical, membrane dynamics and mass conservation equations, is developed and validated through experimental data. Second, a data-driven, neural network (echo state network) is trained, fitted and tested with the same dataset. Then, the hybrid model is formed as a parallel structure, where the simplified physics-based model and the trained data-driven model are merged through an algorithm based on Gaussian radial basis functions. The merging algorithm compares the output of both single models and assigns weights for computing the prediction of the hybrid result. The proposed hybrid model structure is successfully trained, validated and tested with an experimental dataset originating from fuel cells within an automotive PEMFC stack. The hybrid model is assessed through the mean square error index, with the result of a low tracking error.
State machine-based architecture to control system processes in a hybrid fuel cell electric vehicle
Molavi, Ali
Husar, Attila Peter
Hjortberg, Hampus
Nilsson, Niclas
Kogler, Markus
Monreal, Juan Sanchez
Eldigair, Yousif
Serra, Maria
http://hdl.handle.net/2117/401666
2024-03-10T14:07:33Z
2024-02-09T16:10:53Z
State machine-based architecture to control system processes in a hybrid fuel cell electric vehicle
Molavi, Ali; Husar, Attila Peter; Hjortberg, Hampus; Nilsson, Niclas; Kogler, Markus; Monreal, Juan Sanchez; Eldigair, Yousif; Serra, Maria
This paper presents the development and implementation of a system supervisory controller in a hydrogen-based fuel cell electric vehicle. The controller's primary function is to ensure the safe control of the fuel cell system processes while facilitating coordination among various subsystems, including the balance of plant subsystems, vehicle control unit, diagnosis unit, and powertrain. The supervisory controller comprises of three primary parts: a State Machine, an Optimal Setpoint Generator, and a Power Limit Calculator. The State Machine, which serves as the central part of the supervisory controller, coordinates the fuel cell system's different operational states, including the complex processes of start-up and shutdown. To maximize the fuel cell system's efficiency and minimize the stack's degradation, the Optimal Setpoint Generator produces the subsystem's setpoints by solving an optimization problem and considering the manufacturer's requirements. The Power Limit Calculator assesses the stack's power output capability and calculates the current setpoint for the DC/DC converter. It then provides this data to the Energy Management System (EMS), which oversees the distribution of power between the fuel cell system and the batteries. The proposed fuel cell system supervisory controller is verified using the Worldwide Harmonized Light Vehicles Test Cycles (WLTC) in a real-world car. The designed control structure is implemented in a prototype hydrogen-based electric car at both PowerCell and CEVT facilities under the framework of the INN-BALANCE Horizon 2020 European project.
© 2023 The Author(s). Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC. This is an open access article under the CC BY
license (http://creativecommons.org/licenses/by/4.0/).
2024-02-09T16:10:53Z
Molavi, Ali
Husar, Attila Peter
Hjortberg, Hampus
Nilsson, Niclas
Kogler, Markus
Monreal, Juan Sanchez
Eldigair, Yousif
Serra, Maria
This paper presents the development and implementation of a system supervisory controller in a hydrogen-based fuel cell electric vehicle. The controller's primary function is to ensure the safe control of the fuel cell system processes while facilitating coordination among various subsystems, including the balance of plant subsystems, vehicle control unit, diagnosis unit, and powertrain. The supervisory controller comprises of three primary parts: a State Machine, an Optimal Setpoint Generator, and a Power Limit Calculator. The State Machine, which serves as the central part of the supervisory controller, coordinates the fuel cell system's different operational states, including the complex processes of start-up and shutdown. To maximize the fuel cell system's efficiency and minimize the stack's degradation, the Optimal Setpoint Generator produces the subsystem's setpoints by solving an optimization problem and considering the manufacturer's requirements. The Power Limit Calculator assesses the stack's power output capability and calculates the current setpoint for the DC/DC converter. It then provides this data to the Energy Management System (EMS), which oversees the distribution of power between the fuel cell system and the batteries. The proposed fuel cell system supervisory controller is verified using the Worldwide Harmonized Light Vehicles Test Cycles (WLTC) in a real-world car. The designed control structure is implemented in a prototype hydrogen-based electric car at both PowerCell and CEVT facilities under the framework of the INN-BALANCE Horizon 2020 European project.
Experimental control of a methanol catalytic membrane reformer
Cifuentes López, Alejandro
Serra, Maria
Torres Cámara, Ricardo
Llorca Piqué, Jordi
http://hdl.handle.net/2117/399182
2024-01-16T05:07:26Z
2024-01-11T14:14:40Z
Experimental control of a methanol catalytic membrane reformer
Cifuentes López, Alejandro; Serra, Maria; Torres Cámara, Ricardo; Llorca Piqué, Jordi
A simple proportional integral (PI) controller with scheduled gain has been developed and implemented in a catalytic membrane reactor (CMR) to obtain pure hydrogen from a methanol steam reforming process. The controller is designed to track the setpoint of the pure hydrogen flow rate in the permeate side of the CMR via the manipulation of the fuel inlet flow rate. Therefore, the controller actuator is the liquid pump that provides the mixture of methanol and water to the reactor. Within the CMR, the catalytic pellets of PdZn/ZnAl2O4/Al2O3 have been used to facilitate the methanol steam-reforming reaction under stoichiometric conditions (S/C = 1), and Pd–Ag metallic membranes have been employed to simultaneously separate the generated hydrogen. The PI controller design is based on a mathematical model constructed using transfer functions acquired from dynamic experiments conducted with the CMR. The controller has been successfully implemented, and experimental validation tests have been carried out at 450 °C and relative pressures of 6, 8, 10, and 12 bar.
2024-01-11T14:14:40Z
Cifuentes López, Alejandro
Serra, Maria
Torres Cámara, Ricardo
Llorca Piqué, Jordi
A simple proportional integral (PI) controller with scheduled gain has been developed and implemented in a catalytic membrane reactor (CMR) to obtain pure hydrogen from a methanol steam reforming process. The controller is designed to track the setpoint of the pure hydrogen flow rate in the permeate side of the CMR via the manipulation of the fuel inlet flow rate. Therefore, the controller actuator is the liquid pump that provides the mixture of methanol and water to the reactor. Within the CMR, the catalytic pellets of PdZn/ZnAl2O4/Al2O3 have been used to facilitate the methanol steam-reforming reaction under stoichiometric conditions (S/C = 1), and Pd–Ag metallic membranes have been employed to simultaneously separate the generated hydrogen. The PI controller design is based on a mathematical model constructed using transfer functions acquired from dynamic experiments conducted with the CMR. The controller has been successfully implemented, and experimental validation tests have been carried out at 450 °C and relative pressures of 6, 8, 10, and 12 bar.
Artificial compressibility method for high-pressure transcritical fluids at low Mach numbers
Abdellatif, Ahmed Mohammed Abdelfattah
Ventosa Molina, Jordi
Grau Barceló, Joan
Torres Cámara, Ricardo
Jofre Cruanyes, Lluís
http://hdl.handle.net/2117/398724
2024-01-02T10:06:00Z
2023-12-22T07:25:55Z
Artificial compressibility method for high-pressure transcritical fluids at low Mach numbers
Abdellatif, Ahmed Mohammed Abdelfattah; Ventosa Molina, Jordi; Grau Barceló, Joan; Torres Cámara, Ricardo; Jofre Cruanyes, Lluís
Supercritical fluids possess unique properties that makes them relevant in various scientific and engineering applications. However, the experimental investigation of these fluids is challenging due to the high pressures involved and their complex thermophysical behavior. To overcome these limitations, computational researchers employ scale-resolving methods, such as direct numerical simulation and large-eddy simulation to study them. Nonetheless, these methods require substantial computational resources, especially in the case of low-Mach-number regimes due to the disparity between acoustic and hydrodynamic/thermal time scales. This work, therefore, addresses this problem by extending the artificial compressibility method to high-pressure transcritical fluids. This method is based on decoupling the thermodynamic and hydrodynamic parts of the pressure field, such that the acoustic time scales can be externally modified without severely impacting the flow physics of the problem. In addition, the method proposed has two key characteristics: (i) the splitting method presents low computational complexity, and (ii) an automatic strategy for selecting the speedup factor of the approach is introduced. The effectiveness of the resulting methodology is demonstrated through comprehensive numerical tests of increasing complexity, showcasing its ability to accurately simulate a wide range of high-pressure transcritical flows including turbulence. The results obtained indicate that the approach proposed can readily lead to computational speedups larger than without significantly compromising the accuracy of the numerical solutions.
2023-12-22T07:25:55Z
Abdellatif, Ahmed Mohammed Abdelfattah
Ventosa Molina, Jordi
Grau Barceló, Joan
Torres Cámara, Ricardo
Jofre Cruanyes, Lluís
Supercritical fluids possess unique properties that makes them relevant in various scientific and engineering applications. However, the experimental investigation of these fluids is challenging due to the high pressures involved and their complex thermophysical behavior. To overcome these limitations, computational researchers employ scale-resolving methods, such as direct numerical simulation and large-eddy simulation to study them. Nonetheless, these methods require substantial computational resources, especially in the case of low-Mach-number regimes due to the disparity between acoustic and hydrodynamic/thermal time scales. This work, therefore, addresses this problem by extending the artificial compressibility method to high-pressure transcritical fluids. This method is based on decoupling the thermodynamic and hydrodynamic parts of the pressure field, such that the acoustic time scales can be externally modified without severely impacting the flow physics of the problem. In addition, the method proposed has two key characteristics: (i) the splitting method presents low computational complexity, and (ii) an automatic strategy for selecting the speedup factor of the approach is introduced. The effectiveness of the resulting methodology is demonstrated through comprehensive numerical tests of increasing complexity, showcasing its ability to accurately simulate a wide range of high-pressure transcritical flows including turbulence. The results obtained indicate that the approach proposed can readily lead to computational speedups larger than without significantly compromising the accuracy of the numerical solutions.
Cost vs accuracy: DNS of turbulent flow over a sphere using structured immersed-boundary, unstructured finite-volume, and spectral-element methods
Capuano, Francesco
Beratlis, Nikolaos
Zhang, Fengrui
Peet, Yulia
Squires, Kyle
Balaras, Elias
http://hdl.handle.net/2117/398006
2023-12-17T05:43:51Z
2023-12-14T13:08:29Z
Cost vs accuracy: DNS of turbulent flow over a sphere using structured immersed-boundary, unstructured finite-volume, and spectral-element methods
Capuano, Francesco; Beratlis, Nikolaos; Zhang, Fengrui; Peet, Yulia; Squires, Kyle; Balaras, Elias
We report a comparative study of three numerical solvers for the direct numerical simulation of the flow over a sphere at Re = 3700. A high-order spectral-element code (Nek5000), a general purpose, unstructured finite-volume solver (OpenFOAM) and an in-house Cartesian solver using the immersed-boundary method (IBM) are employed for the analysis; results are compared against previous numerical and experimental data. Numerical results show that Nek5000 and the IBM code operate within a similar computational performance range, in terms of cost-vs-accuracy analysis, for both global parameters as well as local flow features. On the other hand, OpenFOAM needed a significantly higher number of degrees of freedom (and, overall, a higher cost) to match some of the basic features of the flow, such as the length of the recirculation bubble forming downstream the sphere. For the finest grid resolutions, the three codes are in good agreement for most of the analyzed flow metrics. Overall, our results suggest that high-order methods and second-order, energy-conserving approaches based on the IBM may be both viable options for high-fidelity scale-resolving simulations of turbulent flows with separation.
2023-12-14T13:08:29Z
Capuano, Francesco
Beratlis, Nikolaos
Zhang, Fengrui
Peet, Yulia
Squires, Kyle
Balaras, Elias
We report a comparative study of three numerical solvers for the direct numerical simulation of the flow over a sphere at Re = 3700. A high-order spectral-element code (Nek5000), a general purpose, unstructured finite-volume solver (OpenFOAM) and an in-house Cartesian solver using the immersed-boundary method (IBM) are employed for the analysis; results are compared against previous numerical and experimental data. Numerical results show that Nek5000 and the IBM code operate within a similar computational performance range, in terms of cost-vs-accuracy analysis, for both global parameters as well as local flow features. On the other hand, OpenFOAM needed a significantly higher number of degrees of freedom (and, overall, a higher cost) to match some of the basic features of the flow, such as the length of the recirculation bubble forming downstream the sphere. For the finest grid resolutions, the three codes are in good agreement for most of the analyzed flow metrics. Overall, our results suggest that high-order methods and second-order, energy-conserving approaches based on the IBM may be both viable options for high-fidelity scale-resolving simulations of turbulent flows with separation.
Kinetic-energy- and pressure-equilibrium-preserving schemes for real-gas turbulence in the transcritical regime
Bernades, Marc
Jofre Cruanyes, Lluís
Capuano, Francesco
http://hdl.handle.net/2117/393532
2024-01-25T08:28:50Z
2023-09-15T08:03:23Z
Kinetic-energy- and pressure-equilibrium-preserving schemes for real-gas turbulence in the transcritical regime
Bernades, Marc; Jofre Cruanyes, Lluís; Capuano, Francesco
Numerical simulations of compressible turbulent flows governed by real-gas equations of state, such as high-pressure transcritical flows, are strongly susceptible to instabilities. In addition to the inherent multi-scale nature of the flow, the presence of a pseudo-interface can generate spurious pressure oscillations when conventional schemes are utilized. This study proposes a general framework to derive and analyze discretization methods that are able to preserve kinetic energy by convection, and simultaneously maintain pressure equilibrium in discontinuity-free compressible real-gas flows. The formal analysis reveals that the discrete pressure-equilibrium condition can be fulfilled at most to second-order accuracy, as it requires the spatial differential operator to satisfy a discrete chain rule when total, or internal energy, are directly discretized. A novel class of schemes based on the solution of a pressure equation is thus proposed, which preserves mass, momentum, kinetic energy and pressure equilibrium, but not total energy. Extensive numerical tests of increasing complexity confirm the theoretical predictions, and show that the proposed scheme is capable of providing non-dissipative, stable and oscillation-free simulations, unlike existing methods tailored for the transcritical regime.
2023-09-15T08:03:23Z
Bernades, Marc
Jofre Cruanyes, Lluís
Capuano, Francesco
Numerical simulations of compressible turbulent flows governed by real-gas equations of state, such as high-pressure transcritical flows, are strongly susceptible to instabilities. In addition to the inherent multi-scale nature of the flow, the presence of a pseudo-interface can generate spurious pressure oscillations when conventional schemes are utilized. This study proposes a general framework to derive and analyze discretization methods that are able to preserve kinetic energy by convection, and simultaneously maintain pressure equilibrium in discontinuity-free compressible real-gas flows. The formal analysis reveals that the discrete pressure-equilibrium condition can be fulfilled at most to second-order accuracy, as it requires the spatial differential operator to satisfy a discrete chain rule when total, or internal energy, are directly discretized. A novel class of schemes based on the solution of a pressure equation is thus proposed, which preserves mass, momentum, kinetic energy and pressure equilibrium, but not total energy. Extensive numerical tests of increasing complexity confirm the theoretical predictions, and show that the proposed scheme is capable of providing non-dissipative, stable and oscillation-free simulations, unlike existing methods tailored for the transcritical regime.
A review of thermal exposure and fire spread mechanisms in large outdoor fires and the built environment
Filkov, Alexander I.
Tihay-Felicelli, Virginie
Masoudvaziri, Nima
Rush, David
Valencia, Andrés
Wang, Yu
Blunck, David L.
Valero Pérez, Mario Miguel
Kempna, Kamila
Smolka, Jan
De Beer, Jacques
Campbell-Lochrie, Zakary
Centeno, Felipe Roman
Ibrahim, Muhammad Asim
Lemmertz, Casila Katiuscia
Tam, Wai Cheong
http://hdl.handle.net/2117/393255
2023-09-11T02:21:08Z
2023-09-08T06:35:39Z
A review of thermal exposure and fire spread mechanisms in large outdoor fires and the built environment
Filkov, Alexander I.; Tihay-Felicelli, Virginie; Masoudvaziri, Nima; Rush, David; Valencia, Andrés; Wang, Yu; Blunck, David L.; Valero Pérez, Mario Miguel; Kempna, Kamila; Smolka, Jan; De Beer, Jacques; Campbell-Lochrie, Zakary; Centeno, Felipe Roman; Ibrahim, Muhammad Asim; Lemmertz, Casila Katiuscia; Tam, Wai Cheong
Due to socio-economic and climatic changes around the world, large outdoor fires in the built environment have become one of the global issues that threaten billions of people. The devastating effects of them are indicative of weaknesses in existing building codes and standard testing methodologies. This is due in part to our limited understanding of large outdoor fire exposures, including the ones from wildland to communities and within communities. To address this problem, the Ignition Resistance Committee (IRC) of the International Association of the Fire Safety Science working group ‘Large Outdoor Fires and the Built Environment’ was established. This manuscript is the result of one of the IRC's initiatives to review current knowledge on exposures associated with large outdoor fires, identify existing knowledge gaps, and provide recommendations for future research. The article consists of two sections: the wildland fire exposure to the built environment and the settlement fire exposure to structures. Each section presents a comprehensive review of experimental and numerical studies of exposure mechanisms (flame contact and convection, radiation, and firebrands). The review concludes with a discussion on data consistency and existing knowledge gaps to highlight future directions for each of the three fire exposure mechanisms.
2023-09-08T06:35:39Z
Filkov, Alexander I.
Tihay-Felicelli, Virginie
Masoudvaziri, Nima
Rush, David
Valencia, Andrés
Wang, Yu
Blunck, David L.
Valero Pérez, Mario Miguel
Kempna, Kamila
Smolka, Jan
De Beer, Jacques
Campbell-Lochrie, Zakary
Centeno, Felipe Roman
Ibrahim, Muhammad Asim
Lemmertz, Casila Katiuscia
Tam, Wai Cheong
Due to socio-economic and climatic changes around the world, large outdoor fires in the built environment have become one of the global issues that threaten billions of people. The devastating effects of them are indicative of weaknesses in existing building codes and standard testing methodologies. This is due in part to our limited understanding of large outdoor fire exposures, including the ones from wildland to communities and within communities. To address this problem, the Ignition Resistance Committee (IRC) of the International Association of the Fire Safety Science working group ‘Large Outdoor Fires and the Built Environment’ was established. This manuscript is the result of one of the IRC's initiatives to review current knowledge on exposures associated with large outdoor fires, identify existing knowledge gaps, and provide recommendations for future research. The article consists of two sections: the wildland fire exposure to the built environment and the settlement fire exposure to structures. Each section presents a comprehensive review of experimental and numerical studies of exposure mechanisms (flame contact and convection, radiation, and firebrands). The review concludes with a discussion on data consistency and existing knowledge gaps to highlight future directions for each of the three fire exposure mechanisms.
Thermodynamics-informed neural network for recovering supercritical fluid thermophysical information from turbulent velocity data
Masclans Serrat, Núria
Vázquez-Novoa, Fernando
Bernades, Marc
Badia Sala, Rosa Maria
Jofre Cruanyes, Lluís
http://hdl.handle.net/2117/393209
2023-12-24T01:11:10Z
2023-09-07T09:46:54Z
Thermodynamics-informed neural network for recovering supercritical fluid thermophysical information from turbulent velocity data
Masclans Serrat, Núria; Vázquez-Novoa, Fernando; Bernades, Marc; Badia Sala, Rosa Maria; Jofre Cruanyes, Lluís
Recent research has highlighted the potential of supercritical fluids under high-pressure transcritical conditions to achieve microconfined turbulence as a result of the thermophysical properties they exhibit in the vicinity of the pseudo-boiling region. This has led to increased interest in understanding their hybrid thermophysical properties when operating near the pseudo-boiling transitioning region. However, despite the potential benefits of microfluidic systems working under transcritical conditions, limited experimental data is available due to the inherent challenges of performing experiments at high-pressure conditions. In addition, traditional experimental methods, such as particle image velocimetry and particle tracking velocimetry, are inadequate for measuring thermophysical properties under such conditions, since they are primarily designed for velocity-related data acquisition. In this regard, this work introduces an efficient thermodynamics-informed neural network framework for reconstructing thermophysical information from velocity data in high-pressure turbulent transcritical regimes. The proposed model incorporates thermophysical constraints through a thermodynamics-informed loss function consisting of the residual of the real-gas equation of state and integrates boundary conditions into the network’s architecture to ensure their satisfaction. The performance of the proposed framework is evaluated through the analysis of two test cases and compared against non-physically informed models. The results demonstrate the superior accuracy, robustness, and satisfaction of physical constraints achieved by the proposed model, as well as its ability to reconstruct averaged thermophysical profiles and preserve bulk quantities with a relative error reduction of approximately 2×. In addition, the physically-consistent predictions provided by the model enable a more accurate reconstruction of dependent thermophysical properties.
2023-09-07T09:46:54Z
Masclans Serrat, Núria
Vázquez-Novoa, Fernando
Bernades, Marc
Badia Sala, Rosa Maria
Jofre Cruanyes, Lluís
Recent research has highlighted the potential of supercritical fluids under high-pressure transcritical conditions to achieve microconfined turbulence as a result of the thermophysical properties they exhibit in the vicinity of the pseudo-boiling region. This has led to increased interest in understanding their hybrid thermophysical properties when operating near the pseudo-boiling transitioning region. However, despite the potential benefits of microfluidic systems working under transcritical conditions, limited experimental data is available due to the inherent challenges of performing experiments at high-pressure conditions. In addition, traditional experimental methods, such as particle image velocimetry and particle tracking velocimetry, are inadequate for measuring thermophysical properties under such conditions, since they are primarily designed for velocity-related data acquisition. In this regard, this work introduces an efficient thermodynamics-informed neural network framework for reconstructing thermophysical information from velocity data in high-pressure turbulent transcritical regimes. The proposed model incorporates thermophysical constraints through a thermodynamics-informed loss function consisting of the residual of the real-gas equation of state and integrates boundary conditions into the network’s architecture to ensure their satisfaction. The performance of the proposed framework is evaluated through the analysis of two test cases and compared against non-physically informed models. The results demonstrate the superior accuracy, robustness, and satisfaction of physical constraints achieved by the proposed model, as well as its ability to reconstruct averaged thermophysical profiles and preserve bulk quantities with a relative error reduction of approximately 2×. In addition, the physically-consistent predictions provided by the model enable a more accurate reconstruction of dependent thermophysical properties.