Time-dependent Flux Research Articles

Fabrication and separation performances of composite membranes containing copper ferrite photocatalysts on graphene oxide nanosheets

An innovative approach thatintegrates photocatalysis, adsorption, and membrane separation processes was presented to degrade pollutants simultaneously during the filtration process. Firstly, a one-pot method was employed to prepare 3D graphene oxide/carbon quantum dot/copper ferrite (G/CFQ) photocatalysts. Then, the M−G/CFQ membrane was fabricated by intercalating 3D G/CFQ photocatalysts between 2D graphene oxide (GO) nanosheets using a negative pressure filtration technique. The time-dependent flux and MB residual rate results revealed that the M−G/CFQ membrane exhibited superior photocatalytic capabilities, particularly in alkaline environments. Furthermore, M−G/CFQ, when used without reaching adsorption saturation and under illumination, displayed outstanding long-term operational catalytic degradation capabilities. For a 5 ppm methylene blue (MB) solution at pH of 7, 10, and 12, the filtrate residue rates were only 8.63 %, 4.44 %, and 1.61 % respectively within 6 h. The versatility, stability, and exceptional properties of M−G/CFQ make it a promising candidate for large-scale water treatment applications, contributing significantly to the conservation of clean water resources and environmental sustainability.

Thermal processes affected by carbon dioxide near ground surface

This study provides penetrative investigation of the effects of carbon dioxide concentration on time-dependent temperature and energy fluxes on the ground surface subject to solar irradiation. While global warming significantly impacts human life, the factors responsible remain controversial. This work considers unsteady one-dimensional heat conduction and radiative heat transfer, including collimated and diffuse components as functions of longitude, latitude, and altitude. Diffuse radiation depends on the different absorption bands of carbon dioxide and water vapor, as functions of wavelength, temperature, concentrations or pressure. The predicted results using COMSOL computer code show that the effects of carbon dioxide concentration on ground surface temperature are negligibly small, for example, over a 5-year period. Time-dependent ground surface temperature strongly depends on the absorption or dissipation of diffuse radiation and heat conduction. Diffuse radiation has a damping effect on temperature variation. Temperature changes due to solar irradiation absorption in the atmosphere are also negligibly small, despite solar irradiation being much greater than diffuse radiation and heat conduction. The absorption or dissipation of diffuse radiation depends on the dominant absorption bands centered at 4.3 and 15 μm of carbon dioxide at different times. This study, from the viewpoint of energy conservation, identifies diffuse radiation as a critical factor influencing the rate of temperature change at the ground surface, without assuming radiative or thermal equilibrium or modeling convection. Poor management of this radiation would hinder efforts to avoid droughts, water scarcity, severe fires, rising sea levels, flooding, catastrophic storms, and biodiversity loss.

Single-photon and multi-photon Fano lines for helium and neon using tRecX-haCC

Abstract Single-photon and multi-photon ionization of helium and neon atoms by ultrashort extreme ultraviolet radiation is studied. The wavelength of radiation is chosen to excite a set of doubly excited states. We analyse the lineshapes arising from the presence of doubly excited states and numerically demonstrate the sensitivity of the Fano q parameter to the order of multi-photon process. The computations were performed using the tRecX-haCC package developed by the authors. The tRecX-haCC package solves the time-dependent Schrödinger equation in the presence of a laser pulse and computes the photoelectron spectra including the narrow resonance peaks using the time-dependent surface flux method (tSurff) and iSurf techniques.

Evolution of low-mode asymmetries introduced by x-ray P2 drive asymmetry during double shell implosions on the SG facility

Abstract Double shell capsule can provide a potential low-convergence to fusion ignition at relatively low temperature (∼3 keV). One of the main sources of degrading double shell implosion performance is the low-mode asymmetries. Recently, the experiments on the evolution of low-mode asymmetries introduced by x-ray P2 drive asymmetry during double shell implosions were carried out on the SG facility, where the outer shell and inner shell shapes were measured through the backlit radiography, and the fuel shape near stagnation was measured by core x-ray self-emission imaging. The time-dependent x-ray flux symmetry was controlled by varying the inner cone fraction, defined as the ratio of the inner cone power to the total laser power, while keeping the drive temperature histories same across experiments. Both the hohlraum radiation and the capsule implosions were analyzed using a two-dimensional radiation-hydrodynamics code. Comparing the experimental radiographs and self-emission images to the simulations, it is found that the simulated outer shell, inner shell and hot spot shapes are in qualitative agreement with experiments, especially, the symmetry swings of the hot spot shape near stagnation are observed from both experimental and simulation results. Further, the effect of x-ray drive asymmetries on double shell implosion performance is preliminarily investigated using numerical simulations. We find that the azimuthal variations in radial velocity caused by drive asymmetries can generate azimuthal mass flow of the inner shell, thus kinetic energy of the inner shell would be not converted into fuel internal energy with high efficiency, and the mass-averaged ion temperature of the fuel at stagnation would be reduced.

A front-fixing numerical method for a fluvio-deltaic sedimentation process with thespace fractional derivative and variable sediment flux

This paper centers around a space-fractional mathematical model for a fluvio-deltaic sedimentation process which involves a space-fractional derivative (Caputo derivative) and time dependent variable sediment flux to investigates the movement of shoreline in a sedimentary ocean basin. This model is a specific case of a basic shoreline model and analogous to a Stefan problem. The numerical solution to the problem is acquired by employing a front-fixing explicit finite difference method. The consistency, stability and convergence of the numerical scheme are theoretically analyzed. The effects of variable sediment flux on the movement of shoreline position and the height of sediments are also assessed for different cases.

Theoretical study of solidification phase change heat and mass transfer with thermal resistance and convection subjected to a time-dependent boundary condition

The solidification of phase-change materials (PCMs) is a key process that occurs commonly in materials science and metallurgy, such as in the casting of alloys and energy management systems. There is a lot of literature in this area that assumes the PCMs are in close contact with the heat source or sink. However, a non-freezing wall frequently encloses them in practical situations. This work presents a phase change problem that describes the solidification of a semi-infinite PCM with thermal resistance. We assume that time-dependent heat flux drives the solidification process. The PCM first convert into mush and then into solid, which leads to a three-region problem. The current study accounts for both conduction as well as convection heat transfer mechanisms. Unfortunately, the exact solution to such problems with time-dependent flux-type boundary conditions may not be possible. Thus, there is considerable interest in deriving the analytical solution. The space–time transformation yields the analytical solution to the problem. A numerical example of Al−Cu alloy with 5%Cu is presented to demonstrate the current study. Thermal resistance shows a pronounced impact on the temperature field. Lower thermal resistance offers faster solidification rate. It is found that as the heat transfer constant increases, the rate of propagation of solid–mush and mush–solid interfaces gets enhanced. In addition, the growth of thermal resistance is of linear nature, with variation in the value of Q. The solidified region has higher concentration than the mush region. The current study is applicable to both eutectic systems and solid solution alloys.

The hybrid anti-symmetrized coupled channels method (haCC) for the tRecX code

We present a new implementation of the hybrid antisymmetrized Coupled Channels (haCC) method in the framework of the tRecX (Scrinzi, 2022 [6]). The method represents atomic and molecular multi-electron functions by combining CI functions, Gaussian molecular orbitals, and a numerical single-electron basis. It is suitable for describing high harmonic generation and the strong-field dynamics of ionization. Fully differential photoemission spectra are computed by the tSurff method. The theoretical background of haCC is outlined and key improvements compared to its original formulation are highlighted. We discuss control of over-completeness resulting from the joint use of the numerical basis and Gaussian molecular orbitals by pseudo-inverses based on the Woodbury formula. Further new features of this tRecX release are the iSurff method, new input features, and the AMOS gateway interface. The mapping of haCC into the tRecX framework for solving the time-dependent Schrödinger equation is shown. Use, performance, and accuracy of haCC are discussed on the examples of high-harmonic generation and strong-field photo-emission by short laser pulses impinging on the Helium atom and on the linear molecules N2 and CO. Program summaryProgram title: tRecX — time-dependent Recursive indeXing (tRecX=tSurff+irECS)CPC Library link to program files:https://doi.org/10.17632/m9g2jc82sw.1Developer's repository link:https://gitlab.physik.uni-muenchen.de/AG-Scrinzi/tRecXLicensing provisions: GNU General Public License 2Programming language: C++External libraries: Eigen, arpack, lapack, blas, boost, FFTW (optional)Journal Reference of previous version: A. Scrinzi, Comp. Phys. Comm., 270:108146, 2022.Does the new version supersede the previous version: YesReasons for the new version: Major new functionality: haCC — hybrid antisymmetrized coupled channels methodSummary of revisions: Main additions are haCC and iSurff. Code usage and compilation were improved.Nature of problem: tRecX is a general solver for time-dependent Schrödinger-like problems, with applications mostly in strong field and attosecond physics. There are no technical restrictions on the spatial dimension of the problem with up to 6 spatial dimensions realized in the strong-field double ionization of Helium. Gaussian-based quantum chemical multi-electron atomic and molecular structure can be combined with the numerical basis. A selection of coordinate systems is available and any Hamiltonian involving up to second derivatives and arbitrary up to three dimensional potentials can be defined on input by simple scripts.Solution method: The method of lines is used with spatial discretization by a flexible combination of one dimensional basis sets, DVR representations, discrete vectors, expansions into higher-dimensional eigenfunctions of user-defined operators, and Gaussian based molecular orbitals. Multi-electron Gaussian-based CI (configuration interaction) functions for neutrals and ions are combined with the numerical basis. Photo-emission spectra are calculated using the time-dependent surface flux method (tSurff) in combination with infinite range exterior complex scaling (irECS) for absorption. The code is object oriented and makes extensive use of tree-structures and recursive algorithms. Parallelization is by MPI. Code design and performance allow use in production as well as for graduate level training.

Assisted Upscaling of Miscible CO2-Enhanced Oil Recovery Floods Using an Artificial Neural Network-Based Optimisation Algorithm

Due to the high computing cost of the fine-scale compositional simulations needed to effectively model miscible CO2 flooding, upscaling techniques are needed to approximate the behaviour of these fine-scale grids on more realistic coarse-scale models. The use of transport coefficients to better represent small-scale interactions, such as the time-dependent flux of the components within the hydrocarbon phases (molecular diffusion), and the pseudoisation of relative permeabilities to ensure the matching of large-scale effects, such as the volumetric fluxes of the phases, are two of these procedures. Most times, a mismatch between the phase fluxes of the integrated fine-scale and that of the coarse-scale is observed. By adjusting or calibrating some of the generated coarse-scale pseudo functions, such as the transport coefficients, absolute permeability, or relative permeability endpoints, the accuracy of the upscaling results can be improved. This procedure can be treated a reservoir history matching problem which is typically computationally expensive. In this study, we provide a framework for representing the dynamics of small-scale molecular diffusion and macro-scale heterogeneity-induced channelling related to miscible CO2 displacements on upscaled coarser grid reservoir models. The method used was based on the pseudoisation of relative permeability and transport coefficients and was applied to two benchmark reservoir models from the Society of Petroleum Engineers (SPE). Our results demonstrated that using effectively calibrated transport coefficients improved the upscaling results, so that the calculated pseudo-relative permeability functions can be ignored. We proposed a unique approach to upscaling miscible floods that utilised a genetic algorithm and a neural-network-based proxy model to minimise the associated computing cost. The data-driven approximation model considerably decreased the computing cost associated with the assisted tuning technique, and the optimisation algorithm was used to reduce the error between the predictions of the upscaled models. In conclusion, the methodology described in this study effectively captured the small- and large-scale behaviour related to the miscible displacements on upscaled coarse-scale reservoir models while reduced associated computational costs.

Thermal and structural analysis of the European water-cooled lithium lead breeding blanket concept in the L-H mode transition

The design of a breeding blanket system (BB) which reliably fulfils the prescribed requirements is pivotal for the construction of the EU DEMO fusion reactor. For this reason, the BB conceptual design activities require a tighter interaction with plasma physics modelling, so to employ relevant boundary conditions to compare, and then down-select, the BB design alternatives. The preliminary thermo-mechanical study herein reported highlights the importance to assess in deep the BB performance during plasma operational transients. In particular, analyses of the BB thermal and mechanical transients during plasma ramp-up have been carried out, with focus on the L-H transition. Attention has been paid to the Water-Cooled Lithium Lead (WCLL) BB concept, one of the two driver blanket candidates for the EU DEMO project. Adopting DEMO-relevant plasma configurations, the fusion power and the radiative power time evolutions during the plasma ramp-up phase have been modelled under different assumptions using the code ASTRA. The obtained power transients have been used to calculate the time-dependent nuclear power density and radiative heat flux the WCLL BB is subjected to, in order to perform the corresponding transient thermal analysis. Then, the structural analysis has been carried out in order to verify the fulfilment of the RCC-MRx structural design criteria in the most critical time steps. The performed thermo-mechanical analysis has been carried out adopting the Abaqus FEM code. Results obtained are presented and critically discussed, highlighting their importance for the EU DEMO integrated design.

Compact description of quantum phase slip junctions

Quantum circuit theory is a powerful tool to describe superconducting circuits. In its language, quantum phase slips (QPSs) are considered to be the exact dual to the Josephson effect. This duality renders the integration of QPS junctions into a unified theoretical framework challenging. As we argue, different existing formalisms may be inconsistent, and the correct inclusion of time-dependent flux driving requires introducing a large number of auxiliary, nonphysical degrees of freedom. We resolve these issues by describing QPS junctions as inductive rather than capacitive elements, and reducing the Hilbert space to account for a compact superconducting phase. Our treatment provides an approach to circuit quantization exclusively in terms of node-flux-node variables, and eliminates spurious degrees of freedom. Finally, the inductive treatment reveals the possibility of a voltage-dependent renormalization of the QPS amplitude, by accounting for spatial variations of the electric field built up across the junction.

Stable and accurate representation of species diffusion in multilayer composite electrodes using physics-informed neural networks

Stable and accurate reconstruction of species diffusion in Li-ion cell electrodes is a crucial problem, especially in modeling emerging composite electrode materials. Lithium-ion batteries are typically modeled using electrode theory coupled with various transport mechanisms that the solid-phase diffusion equation represents the main computational burden. In this paper, a computationally efficient representation for species transport in multilayer electrode is proposed based on the physics-informed neural networks (PINNs). A multi-objective loss function is constructed to obtain an accurate representation of field variables. It consists of the residual of solid-phase diffusion equation, associated initial/boundary conditions together with interface conditions. To deal with the problem of distinct material properties, the whole computational domain is divided into several subdomains where different neural networks for PINN are adopted. By using continuity conditions at interfaces, a whole network is established by combining subnetworks. By this way, the field variables can be obtained accurately by training and learning the neural networks. Li-ion concentrations in electrodes with single-layer and multilayer plate under the galvanostatic, potentiostatic, time-dependent flux, as well as time-dependent concentration charging are analyzed, and the results are validated against solutions obtained from finite element and analytical analysis. In terms of practical application, the galvanostatic voltage profiles of bi-layer (graphite-Si/SiOx) and tri-layer (graphite-Si/SiOx-graphite) electrodes are obtained using the Butler–Volmer kinetic equation and the performance is validated through good agreement with past experimental data. This study demonstrates for the first time the usefulness of the PINN to an electrochemical energy problem for designing multilayer electrode materials.

Effects of A-site potassium doping on oxygen permeability and intermediate-low temperature stability of Ba0.5Sr0.5Co0.8Fe0.2O3−δ membranes

Ba0.5Sr0.5Co0.8Fe0.2O3-δ (BSCF) perovskite membranes process excellent oxygen permeation flux at high temperature. However, the time-dependent flux degradation of BSCF restricts its industrial application at intermediate-low temperature. To address this issue, a series of K+ doped BSCF perovskite materials were prepared by EDTA-citric acid combined complexing method. The effect of K+ introduction on crystal structure, oxygen vacancy concentration, oxygen permeability and flux degradation of BSCF was systematically investigated. The results indicates that BSCF doped with K+ exhibits typical cubic perovskite structure and optimized oxygen permeability while the doping content of K+ is lower than 20%. Meanwhile, the oxygen permeability of BSCF can be significantly improved by introducing K+ ions, where the highest oxygen permeation flux of K0.05Ba0.45Sr0.5Co0.8Fe0.2O3-δ could reach up to 2.70 ml.min-1.cm-2. And a stable intermediate-low temperature oxygen permeation flux of 0.81 ml.min-1.cm-2 at 750 oC for 90 h can be realized for K0.1Ba0.4Sr0.5Co0.8Fe0.2O3-δ and no obvious flux degradation can be found.

Numerical simulation of a non-classical moving boundary problem with control function and generalized latent heat as a function of moving interface

Abstract In this paper, the work is concerned with the study of moving boundary based on non-classical heat equation that includes a time dependent heat flux and convection. The latent heat is represented as a function of the moving interface. Mathematical model accounts for a control function varying with heat flux. We have obtained the explicit solution of the given mathematical model in the presence of convection and a control function. The Legendre wavelet Galerkin approach (LWGA) is used to solve the mathematical problem. In a particular case, our numerical results were compared with previous results and found to be in excellent agreement. Moreover, the current numerical technique is more efficient and accurate in comparison to the previous available method. An extensive analysis of the problem parameters is presented. It is found that the control function offers a significant contribution during the melting or freezing of a PCM. A greater value of the heat flux accelerates the rate of propagation of interface. Convection heat transfer increases the speed of the interface. Results obtained from the current study are expected to improve the fundamental understanding of heat transfer and aid in sublimation and desorption like physical phenomena.

Dynamical behavior and transport coefficients of the pseudo hard-sphere fluid

In this work, we employ a recent approach to characterize the hard-sphere (HS) fluid by means of a continuous interaction potential, commonly referred to as pseudo hard-sphere potential, in order to determine HS transport coefficients as a function of the volume fraction for the three-dimensional mono disperse fluid. Using equilibrium molecular dynamics simulations, we determine time-dependent velocity, shear stress, and energy flux autocorrelation functions in order to use them within the Green–Kubo framework to compute the self-diffusion, shear viscosity, and thermal conductivity coefficients, respectively. Results are discussed as a function of the volume fraction and were compared to theoretical and simulations results previously reported by other authors. The main purpose of this work is twofold: first, testing the continuous approach of the HS fluid for the computation of dynamic properties and second, performing a systematic determination of aforementioned transport coefficients to analyze them as a function of fluid volume fraction. Furthermore, our results are used to provide a practical correction to the Chapman–Enskog equations for the HS self-diffusion, shear viscosity, and thermal conductivity predictions in a wide range of volume fractions.

Pre-ozonation for gravity-driven membrane filtration: Effects of ozone dosage and application timing on membrane flux and water quality

Gravity-driven membrane (GDM) filtration has been proposed as an alternative to sand filtration for drinking water treatment, but its low membrane flux and poor permeate quality hinder its widespread application. This study investigated the effect of pre-ozonation (with various dosages and application timings) on membrane flux, fouling layer characteristics, and permeate quality during GDM filtration of river water. Pre-ozonation with 3 mg/L ozone increased the mean membrane flux by 9–54%, resulting in approximately 30% increased water production and reduced dissolved organic carbon (DOC) and extracellular polymeric substance (EPS) production by 12–35% and 9–18%, respectively. The timing of pre-ozonation significantly affected the time-dependent flux behavior and morphological characteristics of the fouling layers. Pre-ozonation from the beginning of GDM filtration enhanced the initial flux because of organic fouling control but showed a gradual flux decline with time due to EPS accumulation and biologically inactive fouling layers. Pre-ozonation from the middle of GDM filtration period created heterogeneous and porous membrane fouling layers with high biological activity, showing increased membrane fluxes and improved permeate quality by removing DOC and assimilable organic carbon (AOC) via the combined action of ozone oxidation and biodegradation/sorption in the fouling layer. Overall, our results demonstrate pre-ozonation as a potential option to overcome the limitations of GDM filtration.

Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles

The thermodynamics of a solid are crucial in predicting thermal responses and fire behaviors, and they are commonly determined by inverse modeling and optimization algorithms at constant heat flux. However, in practical scenarios, the imposed heat flux frequently varies with time, and related thermodynamics determination methods are rarely reported. In this study, the particle swarm optimization (PSO) algorithm and a 1D numerical model were utilized to determine temperature-dependent thermal conductivity and specific heat of beech wood and polymethyl methacrylate (PMMA). Surface, 3 and 6 mm in-depth temperatures were measured in three sets of ignition tests where constant and time-dependent heat fluxes (HFs) were applied. In each set, PSO was implemented at individual HFs, and the average value was deemed as the final outcome. Reliability of the optimized thermodynamics was verified by comparing with the reported values in the literature and predicting the experimental measurements that were not employed during parameterization. The results showed that wood thermodynamics attained under constant and time-dependent HFs in agreement with previously reported ones. Similar optimization procedures were conducted for PMMA, and good agreement with literature values was found. Using the obtained thermodynamics of wood under constant HF, the numerical model successfully captured the surface temperature at time-dependent HFs. Meanwhile, comparisons using wood temperatures at constant HFs and PMMA temperatures at linear HFs also verified the feasibility of PSO.

Physics-informed deep neural network for inverse heat transfer problems in materials

Recently, physics-informed neural networks have shown great promise in providing fast, elegant solutions for inverse problems. In this work, a physics-informed neural network was developed to solve an inverse heat transfer problem through a plane wall of a conductive material where one side is subjected to unknown heat flux, while the other side is thermally insulated. Using our deep neural network, we were able to predict the temperature profiles across the whole material domain and estimate the unknown thermo-physical parameters such as the material’s thermal diffusivity as well as boundary conditions (i.e., heat flux) at the inaccessible side with high accuracy. Furthermore, the method was extended to estimate time-dependent heat flux on the inaccessible side. The predicted temperatures and estimated parameters obtained from our inverse technique are in good agreement with their corresponding exact or true values. For both time-independent and dependent heat flux at the inaccessible side, our model was shown to be very robust in predicting the unknown material properties and/or boundary conditions even from noisy experimental data. The sensitivity of the model’s predictions on the model hyperparameters has also been reported to demonstrate the capability of the proposed method. This method can be utilized for the estimation of multiple thermo-physical parameters using only a few measured data in many practical materials processing involving heat transfer.

Strong-field nonsequential double photoionization using virtual-detector theory with path summation

We present an ab initio study of the nonsequential strong-field ionization dynamics of a model two-electron atom with helium character. Single- and double-ionization events are characterized and displayed using detector signals extracted at different points in the two-electron two-dimensional space. The double photoelectron momentum distribution is calculated via coherent path-summation over virtual-particle trajectories. A comparison is made between the momentum distributions obtained with the virtual-detector method, the Schr\"odinger wave function, and the time-dependent surface flux method developed by Tao and Scrinzi [New J. Phys. 14, 013021 (2012)]. Insights into different ionization and electron recollision pathways are gained from detailed virtual-particle tracking and energy-time readouts. This study demonstrates the extension of virtual-detector theory to strong-field multielectron quantum dynamics and highlights the importance of the evolving quantum phase in quasiclassical electron propagation.

Simultaneous estimation of time-varying boundary heat flux and temperature-dependent thermophysical and optical parameters of grey translucent medium

A hybrid optimization method, which combines unscented Kalman smoothing (UKS) technique and sequential quadratic programming (SQP) algorithm, is proposed to estimate the time-dependent boundary heat flux and temperature-dependent optical and thermophysical parameters (such as absorption coefficient, refractive index and thermal conductivity) of grey translucent medium simultaneously. The transient coupled radiative and conductive problem in grey translucent medium is solved by finite volume method (FVM) in forward model. In inverse problem, the measured signals consist of the temperature and radiative intensity on the boundaries of the medium. The effects of model parameters (such as the number of future time step and process noise covariance) and different incident heat fluxes on the reconstructed results are studied by the UKS-SQP technique. The results indicate that the proposed hybrid optimization technique is accurate and effective for determining the time-varying boundary heat flux, temperature-dependent optical and thermophysical parameters of grey translucent medium even with the measurement error.

Near real-time prediction of thermophysical parameters and time-dependent boundary heat flux of participating medium

The scattering coefficient (κs), absorption coefficient (κa), thermal conductivity (λ) and time-varying boundary heat flux (q(t)) of 1D participating medium are simultaneously determined in near real time. The forward problem of coupled conductive and radiative heat transfer is solved by finite volume method (FVM). The unscented Kalman filter (UKF) and corresponding smoothing technique (UKS) are employed to estimate the q(t), λ, κa and κs. To achieve non-intrusive detection, the measured signals on boundaries of the medium (such as radiative intensity on right boundary and temperatures on boundaries) are employed as inputs in the inverse problem. The effects of measurement error covariance, process error covariance, future measured signals, sampling interval and thermophysical properties on estimation results are thoroughly investigated. The UKS algorithm, when compared to the UKF algorithm, can improve the stability and accuracy of estimated q(t), λ, κa and κs. It is found that the UKS algorithm is efficient and accurate to solve the near real-time prediction of thermophysical parameters and boundary heat flux of participating medium even with measurement errors.