Article
Environmental Sciences
Gullnaz Shahzadi, Azzeddine Soulaimani
Summary: This study evaluates the impact of constitutive soil parameters on the behavior of rockfill dams through uncertainty analysis and global sensitivity analysis. A Finite Element code is used for structure analysis, and surrogate models are built to approximate the relationship between input soil parameters and displacements, reducing computational costs. Polynomial chaos expansion and deep neural networks are used to compute Sobol indices and identify the impact of soil parameters on dam behavior.
Article
Engineering, Multidisciplinary
Alexander Henkes, Ismail Caylak, Rolf Mahnken
Summary: This work focuses on uncertainty quantification of homogenized effective properties for composite materials with complex, three dimensional microstructure. Uncertainties in material parameters and fiber volume fraction are considered using multivariate random variables and an efficient surrogate model based on pseudospectral polynomial chaos expansion and artificial neural networks. The proposed method is able to predict central moments of interest while being much faster to evaluate than traditional approaches.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Engineering, Industrial
Wen Yao, Xiaohu Zheng, Jun Zhang, Ning Wang, Guijian Tang
Summary: This paper proposes an adaptive arbitrary polynomial chaos (aPC) method and combines it with a deep neural network (DNN) to propose a semi-supervised deep adaptive arbitrary polynomial chaos expansion (Deep aPCE) method. The Deep aPCE method reduces the training data cost by using a small amount of labeled data and abundant unlabeled data, and improves the accuracy of uncertainty quantification by dynamically fine-tuning the adaptive expansion coefficients using DNN. Additionally, the Deep aPCE method can construct accurate surrogate models of high dimensional stochastic systems.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Metallurgy & Metallurgical Engineering
Marks Legkovskis, Peter J. Thomas, Michael Auinger
Summary: Uncertainty quantification is crucial in steel reheating simulations due to input uncertainties in defining surface properties and furnace conditions. The study uses polynomial chaos expansion to reduce computational effort and presents a comprehensive uncertainty quantification analysis of a walking-beam reheat furnace. The analysis reveals the significant influence of parameters related to emissivity and oxide scale growth on slab temperature and identifies the transition in importance of oxide scale growth inputs.
STEEL RESEARCH INTERNATIONAL
(2023)
Article
Engineering, Marine
Ming Chen, Xinhu Zhang, Kechun Shen, Guang Pan
Summary: This study investigates the high-dimensional uncertainty quantification of critical buckling pressure for a composite cylindrical shell with geometric and material uncertainties using sparse polynomial chaos expansion (PCE). The results show that the uncertainty of the longitudinal modulus has a massive influence on the critical buckling pressure, while the uncertainties of other parameters have a weak influence.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Civil
Z. P. Xu, Y. P. Li, G. H. Huang, Z. Y. Shen
Summary: In this study, a PCE-ANOVA-RF method is developed to analyze the effects of multiple uncertain parameters in the SWAT model and generate probabilistic forecasts of daily streamflow. The proposed method not only reveals the impact of parameter uncertainty and saves computation time, but also expands PCE's ability to predict future streamflow processes. The feasibility and applicability of the method are verified in the Amu Darya River Basin in Central Asia.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Multidisciplinary
Arash Mohammadi, Koji Shimoyama, Mohamad Sadeq Karimi, Mehrdad Raisee
Summary: An efficient surrogate model based on POD and compressed sensing is developed for affordable representation of high-dimensional stochastic fields, showing potential in engineering applications.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Mathematics, Applied
Xiang Sun, Jung-Il Choi
Summary: The proposed method utilizes POD and PCE to model spacetime-dependent parameterized problems, effectively estimating low-order moments and accuracy loss under uncorrelated or correlated input parameters.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2021)
Article
Mathematics, Applied
Y. Wei, F. Vazeille, Q. Serra, E. Florentin
Summary: PCE is a powerful metamodeling technique, but requires exponentially increasing training samples with problem dimensionality. PGD has emerged as a popular solution with linear complexity growth based on separate representations. This work introduces a hybrid technique called PGD-PCE, utilizing orthonormal polynomial functions, demonstrating good accuracy and computational efficiency in handling large problems.
FINITE ELEMENTS IN ANALYSIS AND DESIGN
(2022)
Article
Engineering, Industrial
Mishal Thapa, Samy Missoum
Summary: This paper presents a framework for uncertainty quantification (UQ) and global sensitivity analysis (GSA) of composite wind turbine blades using polynomial chaos expansion (PCE) with l(1)-minimization. The framework is capable of handling a large number of random parameters and can assess the relative importance of these parameters using Sobol Indices. It also allows for arbitrary distributions of random inputs and spatial variations of material and geometric properties. The presented framework is applied to three composite wind turbine blade problems, and results are compared to Monte Carlo simulations.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Aerospace
Loic Brevault, Mathieu Balesdent
Summary: The early design phase of launch vehicles often involves low fidelity models with high levels of modeling uncertainties. These uncertainties need to be propagated throughout the design process to ensure robustness, which can be computationally costly due to trajectory optimization and uncertainty quantification.
Article
Engineering, Industrial
Xiaohu Zheng, Wen Yao, Yunyang Zhang, Xiaoya Zhang
Summary: This paper proposes a consistency regularization-based deep polynomial chaos neural network method, which parameterizes the expansion coefficients into learnable weights for iterative learning, reducing the need for labeled data while maintaining the accuracy of high-order PCE models.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Multidisciplinary
Jingfei Liu, Chao Jiang
Summary: In this paper, a deep kernel polynomial chaos expansion (DKPCE) is proposed as a surrogate model for high dimensional uncertainty propagation. The novel network model connects deep neural network (DNN) and polynomial chaos expansion (PCE), allowing control of the PCE layer's input dimensionality by restricting the number of neurons in the feature layer. The back-propagation algorithm is employed for computing all the parameters of DKPCE, enabling dimension reduction and modeling process simultaneously. A data-driven method is implemented during the modeling process to compute the orthogonal polynomial bases within the PCE layer.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Engineering, Aerospace
John A. Schaefer, Andrew W. Cary, Mori Mani, Thomas A. Grandine, Christopher J. Roy, Heng Xiao
Summary: In recent years, there has been a substantial increase in demand for stochastic engineering results, with advancements in computing technology and statistical methods making uncertainty quantification studies feasible. While uncertainty can be quantified at specific locations, the challenge remains to interpolate or extrapolate this information to predict uncertainty at untested locations.
Article
Engineering, Electrical & Electronic
Yiwei Qiu, Jin Lin, Xiaoshuang Chen, Feng Liu, Yonghua Song
Summary: This paper proposes an efficient and nonintrusive method for quantifying uncertainty in dynamic power systems subject to stochastic excitations. The method accurately and efficiently quantifies the probability distribution and high-order moments of system dynamic response and performance index using Ito process and adaptive sparse probabilistic collocation method. Based on commercial simulation software, this method is easy to use for power utility companies.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Chemistry, Physical
Haiyi Wu, N. R. Aluru
Summary: In this study, a deep learning-based quasi-continuum theory was developed to predict the structural properties of water and simple fluids confined in nanometer scale pores and channels. By combining the deep learning model with continuum theory, the DL-QT model can accurately predict the concentration and potential profiles of confined fluids.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Mohan Teja Dronadula, N. R. Aluru
Summary: In this paper, we investigated the properties of graphene-supported lipid monolayers through molecular dynamics simulations, and explored the influence of substrate curvature on these interfaces. The results reveal significant differences between supported monolayers and free-standing bilayers, and provide insights into the tuning of lipid properties.
JOURNAL OF PHYSICAL CHEMISTRY B
(2022)
Article
Materials Science, Multidisciplinary
Shaofeng Yue, Yuhang Jing, Yi Sun, Runze Huang, Zhaoyang Wang, Junqing Zhao, N. R. Aluru
Summary: This paper presents a multi-scale numerical method to study the mechanical behavior of BaZrO3 (BZO) and reveals the fracture mechanism of BZO by comparing different scale calculations. The study not only enhances our understanding of the properties of BZO, but also provides a new approach for material design and applications through the development of a multi-scale method that allows for large-scale calculations.
APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING
(2022)
Article
Materials Science, Multidisciplinary
Thanh Chinh Nguyen, N. R. Aluru
Summary: The on-surface synthesis method is a promising technology for producing nanometer-wide graphene nanoribbons with well-preserved edge structures. This study investigates the surface-assisted synthesis of 7-armchair graphene nanoribbons using a multiscale simulation method. The effect of monomer coverage and substrate type on the polymerization process is studied, and a mathematical model is developed for predicting the percentage of long nanoribbons.
COMPUTATIONAL MATERIALS SCIENCE
(2023)
Article
Chemistry, Physical
A. Moradzadeh, H. Oliaei, N. R. Aluru
Summary: Water plays a crucial role in various processes and understanding its phases is important for nanodevice engineering. Our study develops a graph neural network method to directly distinguish water phases from data. We compare this approach with conventional order parameter methods to study phase transitions in different water systems.
JOURNAL OF PHYSICAL CHEMISTRY C
(2023)
Article
Chemistry, Multidisciplinary
Samuel Faucher, Matthias Kuehne, Hananeh Oliaei, Rahul Prasanna Misra, Sylvia Xin Li, Narayana R. Aluru, Michael S. Strano
Summary: Recent measurements have shown that fluids under extreme confinement, such as water in narrow carbon nanotubes, deviate significantly from theoretical descriptions. In this study, precise replicas of carbon nanotubes filled with water were generated and analyzed using Raman spectroscopy. The results revealed the presence of submicron vapor-like and liquid-like domains in partially filled nanodroplet states, and a Clausius-Clapeyron-type model was used to calculate the heats of condensation of water inside different diameter carbon nanotubes. The findings suggest the potential of molecular engineering of nanoconfined liquid/vapor interfaces for water treatment or membrane distillation.
Review
Chemistry, Multidisciplinary
Narayana R. Aluru, Fikret Aydin, Martin Z. Bazant, Daniel Blankschtein, Alexandra H. Brozena, J. Pedro de Souza, Menachem Elimelech, Samuel Faucher, John T. Fourkas, Volodymyr B. Koman, Matthias Kuehne, Heather J. Kulik, Hao-Kun Li, Yuhao Li, Zhongwu Li, Arun Majumdar, Joel Martis, Rahul Prasanna Misra, Aleksandr Noy, Tuan Anh Pham, Haoran Qu, Archith Rayabharam, Mark A. Reed, Cody L. Ritt, Eric Schwegler, Zuzanna Siwy, Michael S. Strano, YuHuang Wang, Yun-Chiao Yao, Cheng Zhan, Ze Zhang
Summary: Confined fluids and electrolyte solutions in nanopores exhibit rich and surprising physics and chemistry that impact the mass transport and energy efficiency in many important natural systems and industrial applications. Exploiting these effects presents myriad opportunities in both basic and applied research that stand to impact a host of new technologies. In this review article, the progress on nanofluidics of single-digit nanopores (SDNs) is summarized, with a focus on the confinement effects. The recent development of precision model systems, transformative experimental tools, and multiscale theories in this field are reviewed.
Article
Chemistry, Multidisciplinary
Fanfan Chen, Yunhong Zhao, Anshul Saxena, Chunxiao Zhao, Mengdi Niu, Narayana R. Aluru, Jiandong Feng
Summary: Classical nanofluidic frameworks focus on confined fluid and ion transport at solid-liquid interface under an electrostatic field, but overlook the electronic property of the solid. We discovered a nanofluidic analogy of Coulomb drag at the liquid-graphene interface, which effectively couples ion and electron dynamics. Our experiments and calculations reveal that the induced electric current in graphene by ionic flow is a result of confined ion-electron interactions through the nanofluidic Coulomb drag mechanism. This finding opens up new possibilities for nanofluidics and transport control by ion-electron coupling.
Article
Physics, Applied
Yechan Noh, N. R. Aluru
Summary: In this study, the impact of vibrational coupling on atomic transport was examined using molecular dynamics simulations. The findings showed that atomic transport can be activated when the natural frequency of the atomic slit is close to the natural frequency of the atom being transported. Fluctuating forces induced by vibrational coupling were observed, with higher amplitudes observed when the coupling is strong. The high force fluctuations allow the atom to temporarily surpass the transport barrier of the slit, leading to transport activation. These findings provide a foundation for further exploration of vibrational coupling in mass transport.
APPLIED PHYSICS LETTERS
(2023)
Article
Chemistry, Physical
Chenxing Liang, Archith Rayabharam, N. R. Aluru
Summary: In this study, the structural and dynamical properties of water and heavy water under nanoscale confinement were investigated using path integral molecular dynamics simulations. It was found that under nanoscale confinement, the bond length and bond angle of both water and heavy water were smaller compared to the bulk state. The number of hydrogen bonds decreased, indicating a weakened hydrogen bond interaction. Heavy water had a higher dipole moment and stronger hydrogen bonding than water.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)
Article
Chemistry, Multidisciplinary
Matthew J. Coupin, Yi Wen, Sungwoo Lee, Anshul Saxena, Colin Ophus, Christopher S. Allen, Angus I. Kirkland, Narayana R. Aluru, Gun-Do Lee, Jamie H. Warner
Summary: Defects in crystalline lattices cause modulation of the atomic density, leading to variations in the associated electrostatics at the nanoscale. Four-dimensional scanning transmission electron microscopy (4D-STEM) was used to measure electric fields near point dislocations in a monolayer, overcoming the challenges of traditional phase contrast imaging. The increased electric field magnitude near the (1,0) edge dislocation core in graphene is shown to arise from long-range interactions beyond the nearest atomic neighbor. These results provide insights into using 4D-STEM for quantifying electrostatics and mapping potential variations in thin materials.
Article
Chemistry, Multidisciplinary
Archith Rayabharam, Haoran Qu, YuHuang Wang, N. R. Aluru
Summary: The study demonstrates that nanosized pores with controlled pore sizes can separate ethanol-water mixtures through molecular sieving at room temperature and pressure, eliminating the need for energy-intensive and expensive distillation. A selectivity ratio as high as 6700 for water/ethanol separation was achieved with a (6,4) nanotube, which diminishes as the pore size increases beyond 0.306 nm.
Article
Chemistry, Multidisciplinary
Yechan Noh, Narayana R. Aluru
Summary: Ion transport is crucial for cell proliferation, energy conversion, and homeostasis in living systems. This mechanism has inspired various nanofluidic applications, such as electricity harvesting, molecular sensors, and molecular separation. Through extensive molecular dynamics simulations, we investigated ion conduction across flexible 2D nanoporous membranes and found that the microscopic fluctuations of these membranes significantly increase ion conductance. Our analysis revealed that when the membrane fluctuated within a specific frequency range, the ion hydration was destabilized, leading to improved ion conduction. The dynamic coupling between the fluctuating membrane and ions plays a crucial role in ion conduction across 2D nanoporous membranes.
Article
Chemistry, Multidisciplinary
Matthew T. Gole, Mohan T. Dronadula, Narayana R. Aluru, Catherine J. Murphy
Summary: Understanding the adsorption behavior of proteins on rough and wrinkled surfaces is crucial for biosensor and flexible biomedical device applications. This study investigates the nanoscale adsorption behavior of immunoglobulin M (IgM) and immunoglobulin G (IgG) on wrinkled and crumpled surfaces using atomic force microscopy (AFM). The results show that the presence of negative curvature on the wrinkled surface reduces protein surface coverage, mainly due to geometric hindrance and reduced binding energy, while smaller IgG molecules are not affected by this degree of curvature.
NANOSCALE ADVANCES
(2023)
Article
Chemistry, Physical
Jae Hyun Park, Sungyeb Jung, Puji Lestari Handayani, Narayana Aluru, Taehoon Kim, Sang Bok Lee, U. Hyeok Choi, Jaekwang Lee
Summary: Solid-state aqueous polymer electrolytes (SAPEs) are a mixture of hydrophilic polymers and an appropriate amount of water, which can produce high Li-ion conductivity while maintaining a solid state and overcome the limitations of normal solid electrolytes. This study reports that the very high SAPE ionic conductivity is closely correlated with a low energy barrier originating from water-filled ion passages in the medium.
JOURNAL OF PHYSICAL CHEMISTRY C
(2022)
Article
Thermodynamics
Mahsa Taghavi, Swapnil Sharma, Vemuri Balakotaiah
Summary: This study investigates the natural convection effects in the insulation layers of spherical storage tanks and their impact on the tanks' performance. The permeability and Rayleigh number of the insulation material are considered as key factors. The results show that as the Rayleigh number increases, new convective cells emerge and cause the cold boundary to approach the external hot boundary. In the case of large temperature differences, multiple solutions may coexist.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Jinyang Xu, Fangjun Hong, Chaoyang Zhang
Summary: This study introduces a self-induced jet impingement device for enhancing pool boiling performance in high power electronic cooling. Through visualization and parametric investigations, the effects of this device on pool boiling performance are studied, revealing the promotion of additional liquid supply and vapor exhausting. The flow rate of the liquid jet is found to positively impact boiling performance.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Wenchao Ke, Yuan Liu, Fissha Biruke Teshome, Zhi Zeng
Summary: Underwater wet laser welding (UWLW) is a promising and labor-saving repair technique. A thermal multi-phase flow model was developed to study the heat transfer, fluid dynamics, and phase transitions during UWLW. The results show that UWLW creates a water keyhole, making the welding environment similar to in air laser welding.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Xingrong Lian, Lin Tian, Zengyao Li, Xinpeng Zhao
Summary: This study investigates the heat transfer mechanisms in natural fiber-derived porous structures and finds that thermal radiation has a significant impact on the thermal conductivity in low-density regions, while natural convection rarely occurs. Insulation materials derived from micron-sized natural fibers can achieve minimum thermal conductivity at specific densities. Strategies to lower the thermal conductivity include increasing porosity and incorporating nanoscale pores using nanosize fibers.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Yasir A. Malik, Kilian Koebschall, Stephan Bansmer, Cameron Tropea, Jeanette Hussong, Philippe Villedieu
Summary: Ice crystal icing is a significant hazard in aviation, and accurate modeling of sticking efficiency is essential. In this study, icing wind tunnel experiments were conducted to quantify the volumetric liquid water fraction, sticking efficiency, and maximum thickness of ice layers. Two measurement techniques, calorimetry and capacitive measurements, were used to measure the liquid water content and distribution in the ice layers. The experiments showed that increasing wet bulb temperatures and substrate heat flux significantly increased sticking efficiency and maximum ice layer thickness.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Jinqi Hu, Tongtong Geng, Kun Wang, Yuanhong Fan, Chunhua Min, Hsien Chin Su
Summary: This study experimentally examined the heat dissipation of vibrating fans and demonstrated its inherent mechanism through numerical simulation. The results showed that the flow fields induced by the vibrating blades exhibited pulsating features and formed large-scale and small-scale vortical structures, significantly improving heat dissipation. The study also identified the impacts of different blade structures and developed a trapezoidal-folding blade, which effectively reduced the maximum temperature of the heat source and alleviated high-temperature failure crisis.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Dan-Dan Su, Xiao-Bin Li, Hong-Na Zhang, Feng-Chen Li
Summary: The boiling heat transfer of low-boiling-point working fluid is a common heat dissipation technology in electronic equipment cooling. This study analyzed the interfacial boiling behavior of R134a under different conditions and found that factors such as the initial thickness of the liquid film, solid-liquid interaction force, and initial temperature significantly affect the boiling mode and thermal resistance.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Jinyi Wu, Dongke Sun, Wei Chen, Zhenhua Chai
Summary: A unified lattice Boltzmann-phase field scheme is proposed to simulate dendrite growth of binary alloys in the presence of melt convection. The effects of various factors on the growth are investigated numerically, and the model is validated through comparisons and examinations.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Shaokun Ge, Ya Ni, Fubao Zhou, Wangzhaonan Shen, Jia Li, Fengqi Guo, Bobo Shi
Summary: This study investigated the temperature distribution of main cables in a suspension bridge during fire scenarios and proposed a prediction model for the maximum temperature of cables in different lane fires. The results showed that vehicle fires in the emergency lane posed a greater thermal threat to the cables.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Shuang-Ying Wu, Shi-Yao Zhou, Lan Xiao, Jia Luo
Summary: This paper investigates the two-phase flow and heat transfer characteristics of low-velocity jet impacting on a cylindrical surface. The study reveals that the heat transfer regimes are non-phase transition and nucleate boiling with the increase of heat transfer rate. The effects of jet impact height and outlet velocity on local surface temperatures are pronounced at the non-phase transition stage. The growth rates of heat transfer rate and liquid loss rate increase significantly from the non-phase transition to nucleate boiling stage.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Emad Hasani Malekshah, Wlodzimierz Wlodzimierz, Miros law Majkut
Summary: Cavitation has significant practical importance and can be controlled by air injection. This study investigates the natural to ventilated cavitation process around a hydrofoil through numerical and experimental methods. The results show that the location and rate of air injection have a meaningful impact on the characteristics of cavitation.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Feriel Yahiat, Pascale Bouvier, Antoine Beauvillier, Serge Russeil, Christophe Andre, Daniel Bougeard
Summary: This study explores the enhancement of mixing performance in laminar flow equipment by investigating the generation of chaotic advection using wall deformations in annular geometries. The findings demonstrate that the combined geometry can achieve perfect mixing at various Reynolds numbers.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Hui He, Ning Lyu, Caihua Liang, Feng Wang, Xiaosong Zhang
Summary: This study investigates the condensation, frosting, and defrosting processes on superhydrophobic surfaces with millimeter-scale structures. The results reveal that the structures can influence the growth and removal of frost crystals, with the bottom grooves creating a frost-free zone and conical edges promoting higher frost crystal heights. Two effective methods for defrosting are observed: hand-lifting the groove and airfoil retraction contraction on protruding structures. This research provides valuable insights into frost formation and defrosting on millimeter-structured superhydrophobic surfaces, with potential applications in anti-frost engineering.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Thiwanka Arepolage, Christophe Verdy, Thibaut Sylvestre, Aymeric Leray, Sebastien Euphrasie
Summary: This study developed two thermal concentrators, one with a 2D design of uniform thickness and another with a 3D design, using the coordinate transformation technique and metamaterials. By structuring the thermal conductor, the desired local density-heat capacity product and anisotropic thermal conductivities were achieved. The homogenized thermal conductivities were obtained from finite element simulations and cylindrical symmetry consideration. A 3D concentrator was fabricated using 3D metal printing and characterized using a thermal camera. Compared to devices that solely consider anisotropic conductivities, the time evolution characteristics of the metadevice designed with coordinate transformation were closer to those of an ideal concentrator.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Thermodynamics
Liangyuan Cheng, Qingyang Wang, Jinliang Xu
Summary: In this study, we investigated the supercritical heat transfer of CO2 in a horizontal tube with a diameter of 10.0 mm, covering a wide range of pressures, mass fluxes, and heat fluxes. The study revealed a non-monotonic increase in wall temperatures along the flow direction and observed both positive and negative wall temperature differences between the bottom and top tube. The findings were explained by the thermal conduction in the solid wall interacting with the stratified-wavy flow in the tube.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)