Besides promising implications as fertile nuclear materials, thorium carbonitrides are of great interest owing to their peculiar physical and chemical properties, such as high density, high melting point, good thermal conductivity. This paper reports first-principles simulation results on the structural, electronic and magnetic properties of cubic thorium carbonitrides $ThC_xN_{(1-x)}$ (X = 0.03125, 0.0625, 0.09375, 0.125, 0.15625) employing formalism of density-functional-theory. For the simulation of physical properties, we incorporated full-potential linearized augmented plane-wave (FPLAPW) method while the exchange-correlation potential terms in Kohn-Sham Equation (KSE) are treated within Generalized-Gradient-Approximation (GGA) in conjunction with Perdew-Bruke-Ernzerhof (PBE) correction. The structural parameters were calculated by fitting total energy into the Murnaghan's equation of state. The lattice constants, bulk moduli, total energy, electronic band structure and spin magnetic moments of the compounds show dependence on the C/N concentration ratio. The electronic and magnetic properties have revealed non-magnetic but metallic character of the compounds. The main contribution to density of states at the Fermi level stems from the comparable spectral intensity of Th (6d+5f) and (C+N) 2p states. In comparison with spin magnetic moments of ThSb and ThBi calculated earlier with LDA+U approach, we observed an enhancement in the spin magnetic moments after carbon-doping into ThN monopnictide.
In this study, ozone (O3) samples were prepared for investigating the heterogeneous reactions between O3 and tropospheric aerosols and were characterized by spectroscopic methods. O3 generated from an ozone generator was purified by selective adsorption on refrigerated silica gel, followed by transfer to a sample bulb. The amount of UV light (λ = 256 nm) absorbed by O3 was measured as a function of time at two different temperatures (room temperature and 50 ℃) and under different irradiation conditions. A correlation plot of 1/[O3] versus time showed that O3 decomposition follows the 2nd order reaction rate under a steady-state approximation. The initial concentration of O3, observed rate constants (kobs), and the half-life of O3 in the sample stored at room temperature were determined to be 2.74 [±0.14] × 1016 molecules·cm-3, 4.47 [±0.64] × 10-23 molecules-1·cm3·s-1, and 9.5 [±1.4] days, respectively. The evaluation of O3 stability under various conditions indicated that special care should be taken to prevent the exposure of the O3 samples to hightemperature environment and/or UV radiation. This study established a protocol for the preparation of highly purified O3 samples and confirmed that the O3 samples can be stored for a day after preparation for further experiments.
Garg, A.;Mukhopadhyay, T.;Chalak, H.D.;Belarbi, M.O.;Li, L.;Sahoo, R.
Steel and Composite Structures
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v.44
no.5
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pp.707-720
/
2022
In the present work, bending and free vibration analyses of multilayered functionally graded (FG) graphene platelet (GPL) and fiber-reinforced hybrid composite beams are carried out using the parabolic function based shear deformation theory. Parabolic variation of transverse shear stress across the thickness of beam and transverse shear stress-free conditions at top and bottom surfaces of the beam are considered, and the proposed formulation incorporates a transverse displacement field. The present theory works only with four unknowns and is computationally efficient. Hamilton's principle has been employed for deriving the governing equations. Analytical solutions are obtained for both the bending and free vibration problems in the present work considering different variations of GPLs and fibers distribution, namely, FG-X, FG-U, FG-Λ, and FG-O for beams having simply-supported boundary condition. First, the matrix is assumed to be strengthened using GPLs, and then the fibers are embedded. Multiscale modeling for material properties of functionally graded graphene platelet/fiber hybrid composites (FG-GPL/FHRC) is performed using Halpin-Tsai micromechanical model. The study reveals that the distributions of GPLs and fibers have significant impacts on the stresses, deflections, and natural frequencies of the beam. The number of layers and shape factors widely affect the behavior of FG-GPL-FHRC beams. The multilayered FG-GPL-FHRC beams turn out to be a good approximation to the FG beams without exhibiting the stress-channeling effects.
Tomasz Kwiatkowski;Michal Jedrzejczyk;Afaque Shams
Nuclear Engineering and Technology
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v.56
no.4
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pp.1310-1319
/
2024
The reactor cavity cooling system (RCCS) is a passive reactor safety system commonly present in the designs of High-Temperature Gas-cooled Reactors (HTGR) that removes heat from the reactor pressure vessel by means of natural convection and radiation. It is one of the factors responsible for ensuring that the reactor does not melt down under any plausible accident scenario. For the simulation of accident scenarios, which are transient phenomena unfolding over a span of up to several days, intermediate fidelity methods and system codes must be employed to limit the models' execution time. These models can quantify radiation heat transfer well, but heat transfer caused by natural convection must be quantified with the use of correlations for the heat transfer coefficient. It is difficult to obtain reliable correlations for HTGR RCCS heat transfer coefficients experimentally due to such a system's size. They could, however, be obtained from high-fidelity steady-state simulations of RCCSs. The Rayleigh number in RCCSs is too high for using a Direct Numerical Simulation (DNS) technique; thus, a Reynolds-Averaged Navier-Stokes (RANS) approach must be employed. There are many RANS models, each performing best under different geometry and fluid flow conditions. To find the most suitable one for simulating an RCCS, the RANS models need to be validated. This work benchmarks various RANS models against three experiments performed on the HTTR RCCS Mockup by the Japanese Atomic Energy Agency (JAEA) in 1993. This facility is a 1/6 scale model of a vessel cooling system (VCS) for the High Temperature Engineering Test Reactor (HTTR), which is operated by JAEA. Multiple RANS models were evaluated on a simplified 2d-axisymmetric geometry. They were found to reproduce the experimental temperature profiles with errors of up to 22% for the lowest temperature benchmark and 15% for the higher temperature benchmarks. The results highlight that the pragmatic turbulence models need to be validated for high Rayleigh natural convection-driven flows and improved accordingly, more publicly available experimental data of RCCS resembling experiments is needed and indicate that a 2d-axisymmetric geometry approximation is likely insufficient to capture all the relevant phenomena in RCCS simulations.
Solar-powered unmanned aerial vehicles(SPUAV), which are being actively developed domestically and internationally, generally feature high aspect ratio(AR) wings. These high AR wings necessitate a lightweight design as their weight increases, rendering them susceptible to flutter. Consequently, flutter analysis is critical from the initial design phase. Typically, flutter analysis is conducted using a standard section wing or more precisely through a 3D model. However, due to the extended analysis time required by 3D models, this study opts for a 2D aircraft model. The 2D model computes faster than the 3D model and intuitively secures the flutter boundary. In this study, a structural/aerodynamic force model of the 2D aircraft was established, and the findings were compared with those from a 3D half model. The results showed that the flutter analysis between the 2D model and the 3D half model was similar, within about a 3% margin, thus validating the proposed 2D model's effectiveness.
Journal of the Earthquake Engineering Society of Korea
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v.14
no.1
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pp.25-34
/
2010
A method is presented for evaluating the seismic failure probability of bridge structures which show a nonlinear hysteretic dynamic behavior. Bridge structures are modeled as a bilinear dynamic system with a single degree of freedom. We regarded that the failure of bridges will occur when the displacement response of a deck level firstly crosses the predefined limit state during a duration of strong motion. For the estimation of the first-crossing probability of a nonlinear structural system excited by earthquake motion, we computed the average frequency of crossings of the limit state. We presented the non-Gaussian closure method for the approximation of the joint probability density function of response and its derivative, which is required for the estimation of the average frequency of crossings. The failure probabilities are estimated according to the various artificial earthquake acceleration sets representing specific seismic characteristics. For the verification of the accuracy and efficiency of presented method, we compared the estimated failure probabilities with the results evaluated from previous methods and the exact values estimated with the crude Monte-Carlo simulation method.
According to the recent reports the bulk bcc Rh is ferromagnetic with a small difference of energy compared to paramagnetic state. In this study, the electronic structure and magnetism for bcc Rh(001) surface are investigated by means of the all-electron full potential linearized augmented plane wave method within the generalized gradient approximation. It is found that the surface ferromagnetic state is preferable over the paramagnetic one. For unrelaxed system, the magnetic moment of the surface layer, $0.48{\mu}B$, is slightly increased comparing with the bulk value, $0.41{\mu}B$ while the value of the subsurface layer, $0.23{\mu}B$, is much smaller than the bulk value. The total energy and atomic force calculations show that the surface layer is relaxed downward and the subsurface layer moves upward to reduce the layer distance between the surface and subsurface layers by 7.0 %. The relaxation effect leads to weakening the surface magnetic properties. Specifically, the value of the magnetic moment of the surface atom is decreased to $0.36{\mu}B$. Since the spin polarization of the subsurface layer is only $0.14{\mu}B$, it is concluded that the bcc Rh(001) surface is rather weakly ferromagnetic.
For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.
Horizontal consolidation characteristics of Busan marine clay were investigated by computing coefficient of horizontal consolidation from Piezocone data and comparing their results with those of standard consolidation test. It is well known that current prediction models of $c_h$ for high plastic soils have large uncertainties, and show a great difference between the predicted and the measured values. However, the spherical models and expanding cavity theory of Torstensson(1977), and Burns & Mayne(1998) based on modified Cam-Clay model with critical limit state concepts have relative reliability in estimating $c_h$ and good applicability in highly plasticity soils. In this paper, a normalization technique was used to evaluate $c_h$ using the Burns and Mayne's method based on the dissipation test, and their normalized consolidation curves give 0.015 of time factor($T_{50}$) when 50% degree of consolidation is completed. Comparison study using Piezocone data obtained at other similar ground site shows 1.5 times less systematicality than that of standard consolidation test, which indicates considerable approximation with the measured values because standard consolidation test gives the difference of three to few times compared with the measured values. In addition, design chart for estimating $c_h$ based on the chart from Robertson et al.(1992) and using the other method of the direct prediction from the of dissipation test was newly proposed. It is judged that new proposed chart is very applicable to Korean marine soils, especially in very high plastic soils.
Journal of the Institute of Electronics Engineers of Korea TC
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v.43
no.3
s.345
/
pp.49-58
/
2006
In this paper, a curve-fitting channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) system in a time-varying frequency-selective fading channel. The method can greatly improve channel state information (CSI) estimation accuracy by performing smoothing and interpolation through consecutive curve-fitting processes in both time domain and frequency domain. It first evaluates least-squares (LS) estimates using pilot symbols and then the estimates are approximated to a polynomial with proper degree in the LS error sense, starting from one preferred domain in which pilots we densely distributed. Smoothing, interpolation, and prediction are performed subsequently to obtain CSI estimates for data transmission. The channel estimation processes are completed by smoothing and interpolating CSI estimates in the other domain once again using the channel estimates obtained in one domain. The performance of proposed method is influenced heavily on the time variation and frequency selectivity of channel and pilot arrangement. Hence, a proper degree of polynomial and an optimum approximation interval according to various system and channel conditions are required for curve-fitting. From extensive simulation results in various channel environments, we see that the proposed method performs better than the conventional methods including the optimal Wiener filtering method, in terms of the mean square error (MSE) and bit error rate (BER).
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