Superposition Model Research Articles

Analysis of Crystal-Field Effects on the Energy Levels of Mn4+ Ions Doped in Different Photoluminescent Host Lattices, Exhibiting Lowering of Site Symmetry: Exchange Charge and Superposition Model Calculations, for Potential Applications

Analysis of Crystal-Field Effects on the Energy Levels of Mn4+ Ions Doped in Different Photoluminescent Host Lattices, Exhibiting Lowering of Site Symmetry: Exchange Charge and Superposition Model Calculations, for Potential Applications

Coordinated optimal control of active power of wind farms considering wake effect

In a large-scale wind farm, under the influence of the wake effect, the single-machine maximum power extraction control strategy would not be able to function at the ideal optimal value. It is important to study the coordinated operation strategy of the wind farm under the wake effect to improve the output power of wind farms and improve the economic benefit. In this paper, a practical wake model called the PARK model is used and a wake superposition model based on energy balance is derived. Based on these models, an optimization problem is formulated to maximize the output power of the wind farm considering the wake effect. Taking the Horns Rev offshore wind farm as an example, the stochastic points method, particle swarm optimization, and the pattern search algorithm are implemented and compared with the single-machine maximum power extraction algorithm. Test results show that the particle swarm optimization and the pattern search algorithm have better performance. The output power of the wind farm increases by about 10 percent. The particle swarm optimization requires less computation while the pattern search algorithm obtains better and more practical results. Finally, the pattern search algorithm is used to improve economic benefits under different wind conditions.

A diffuse-interface lattice Boltzmann method for fluid–particle interaction problems

In this paper, a diffuse-interface lattice Boltzmann method (DI-LBM) is developed for fluid–particle interaction problems. In this method, the sharp interface between the fluid and solid is replaced by a thin but nonzero thickness transition region named diffuse interface, where the physical variables change continuously. In order to describe the diffuse interface, we introduce a smooth function, which is similar to the order parameter in the phase-field model or the volume fraction of solid phase in the partially saturated lattice Boltzmann method (PS-LBM). In addition, to depict the fluid–particle interaction more accurately, a modified discrete force term is also proposed and included in the evolution equation of the DI-LBM. Some classical problems are used to test the DI-LBM, and the results are in good agreement with some available theoretical and numerical data. Finally, it is also found that the DI-LBM is more efficient and accurate than the PS-LBM with the superposition model.

Theoretical studies on the EPR parameters and local structure of Cu2+ center in [Co(nicotinamide)2(H2O)4](saccharinate)2 crystal

Local structure and electron paramagnetic resonance (EPR) parameters for Cu2+ center in [Co(nicotinamide)2(H2O)4](saccharinate)2 (CoNAS) crystal are theoretically investigated using high-order perturbation formulas for 3d9 ions in rhombically elongated octahedra. In the calculated formulas, the related molecular orbital coefficients are acquired from the superposition model which enables to correlate the crystal field parameters and hence the EPR parameters with the studied Cu2+ center, the admixtures of d-orbitals in the ground state wave function as well as the ligand orbital and spin–orbit coupling contributions are taken into account. Based on the studies, the [CuO4N2]12− cluster of the studied Cu2+ center are found to suffer the axial and perpendicular bond length variations Δz (≈ 0.0612 Å) along z-axis and δr (≈ 0.0360 Å) along x- and y-axes, respectively, due to the Jahn–Teller effect.

Influence of second-order wave force and focusing position on dynamic responses of tension leg platform under a freak wave

As a semicompliant and semirigid column group structure, both second-order sum-frequency and diff-frequency wave forces and focusing positions are important for tension leg platforms (TLPs) under freak waves. The double-wave train superposition model is widely used to generate freak waves; however, multiple trials are inevitable for freak wave generation owing to the uncertainty in parameter selection, which may decrease the simulation efficiency. In this study, the effects of the energy ratio of the focused wave train, number of constituent waves, and parameters of the JONSWAP wave spectrum on the generation probability of freak waves are studied, and the generation probability of the freak wave is fitted by a Γ cumulative probability density function. The advantage of the fitted formula is that the generation probability of a freak wave is quantified, and an appropriate number of constituent waves can be determined for a given energy ratio of the focused wave to increase the simulation efficiency. Furthermore, the dynamic responses of a TLP in a freak wave considering the influences of second-order wave forces and focusing positions are simulated and discussed. Two main findings are that the second-order diff-frequency wave force may cause large-amplitude low-frequency motion in the surge direction and set-down motion in the heave direction, which are 3.71 and 4.08 times the first-order surge and heave responses, respectively, whereas the second-order sum-frequency wave force may cause high-frequency oscillation in the pitch direction, the amplitude of which is 3.9 times the amplitude of the first-order pitch response. The response of the TLP is significantly increased under the freak wave, especially when the second-order wave force is considered. The apparent focusing position of the maximum response changes with the spectral peak period owing to the nonrepeatability of the freak wave and phase difference of the columns. The maximum predicted errors of surge, heave, and pitch motion reached 42.0%, 41.1%, and 98.9%, respectively, when the freak wave acts on the front column, center of the platform, and back column, which may significantly underestimate the dynamic response. Therefore, the effects of the focusing position should be considered when calculating the response of a TLP under a freak wave.

Tunable acoustic insulation characteristics of membrane-type acoustic metamaterials array with compact magnets

This paper presents membrane-type acoustic metamaterials array with compact magnets (MAMMs array) for acoustic insulation. The proposed MAMMs array consist of four cells. Every cell is realized by placing a membrane with a centered magnet in a magnetic field. The magnetic fields of each cell do not affect each other. To clarify the tunable sound insulation characteristics of the MAMMs array, a mode superposition model and the corresponding finite element analysis model were established to predict the transmission loss (TL) of the MAMMs array. Experiments were performed in an impedance tube, and the experimental results agree well with the predicted ones. This research demonstrates that each cell of the MAMMs array is individually adjustable and the enhanced tension of the membrane due to the increased magnetic force leads to the upward shifting of the TL peak frequency and TL peak enlargement in each cell. By optimizing different cells of the MAMMs array, the TL curve of the MAMMs array can produce multiple TL peaks, and the noise isolation of multiple frequency bands can be realized.

Radiative properties of porous fly ash particles based on the particle superposition model

Research on the radiative properties of porous fly ash particles is highly important for accurately assessing the radiative impact of particles and their remote-sensing measurements. We develop a general porous particle model based on the particle superposition model for flexibly constructing variations in the particle shape, size parameters, porosity, pore size, and pore dispersed distribution. Concentrated, dispersed, and cratered surface porous particle models are constructed to consider the effect of the distribution of pores on the radiative properties of porous particles. The radiative properties of porous fly ash particles are computed using the discrete dipole approximation (DDA) method. The effects of the porosity, pore size, pore dispersed distribution, and overall particle size on the radiative properties are analyzed. Generally, the increase of pore size promotes forward scattering intensity and weakens backward scattering intensity. The more dispersed pore distribution promotes stronger backward scattering intensity and stronger oscillations of the degree of linear polarization. Measurement of the Mueller matrix element S11 in different scattering angle regions can be descriptive of the pore distribution. The dispersed pore distribution promotes the extinction cross sections. The asymmetry parameter decreases with the increase of porosity and increases with increasing pore size. In addition, it is necessary to consider both the particle size and pore dispersed distribution for investigating the effect of porosity and pore size on the single-scattering albedos of porous fly ash particles.

Radiative heat transfer calculation for mixture of gases using full spectrum k-distribution method

The full spectrum k-distribution method is used to obtain radiative heat flux and divergence of radiative heat flux for two test cases, containing mixture of CO 2 and H 2 O at different concentration and temperature keeping pressure constant. The k-distribution for mixture of gases is obtained from individual gas k-distribution using three different mixing models, viz., superposition, multiplication and hybrid model. Further, the radiative transfer equation (RTE) is solved by the finite volume discrete ordinate method (FVDOM) to obtain the radiative flux and the radiation source term. The results obtained were compared with the FSK from spectral addition and LBL method. The multiplication mixing model provides better accuracy compared to other mixing models considered in the present study.

Wind farm layout optimization for levelized cost of energy minimization with combined analytical wake model and hybrid optimization strategy

Wind farm layout optimization is a crucial stage for wind farm projects. Most of previous studies aim to maximize the power generation by optimizing turbine locations using analytical wake models and heuristic optimization techniques. However, the performance of analytical wake models was not properly evaluated before being applied on the layout optimization, which may lead a large discrepancy. The efficiency of strategies to solve this optimization problem also needs to be improved with the increasing scale of wind farm. Moreover, the minimization of levelized cost of energy of wind farm is considered to be a more appropriate optimization objective than the power maximization. In this study, the combined analytical wake model considering wake loss, added turbulence and wake superposition model is presented and evaluated by comparing with numerical simulation data. A hybrid optimization strategy assembling genetic algorithm and particle swarm optimization is proposed and used to minimize the levelized cost of energy under different scenarios. The results show that the power generation is underestimated by up to 31% if neglecting the added turbulence model and the combined analytical wake model has an averaged error of 3%. The levelized cost of energy is decreased by 1.9% and the annual energy production, capacity factor and efficiency are improved by 2.3%, 2.3% and 1.3% respectively after the layout optimization for the full various wind scenario with 49 wind turbines. The proposed hybrid optimization strategy increases the optimization effect by up to 0.9% compared with the individual genetic algorithm strategy and improves the efficiency by up to 26% than the individual particle swarm optimization strategy.

Experimental analysis of high temperature flow boiling heat transfer and pressure drop in a plate heat exchanger

• High temperature flow boiling of seven working fluids is experimentally analyzed. • Two heat transfer mechanisms are identified among different working fluids. • A superposition model is developed for the heat transfer coefficient prediction. • The heat transfer coefficient of propane is up to 152% higher than that of R236fa. • Isobutane has the lowest frictional pressure drop among the seven working fluids. Organic Rankine cycle technology has gained worldwide acceptance as an efficient way to utilize low-grade heat sources. Plate heat exchangers are the most common type of heat exchanger employed as evaporators in small-scale organic Rankine cycle units, in which a high saturation temperature is the prevailing working condition. However, there is a lack of research on high temperature flow boiling in plate heat exchangers. This paper presents an experimental analysis on flow boiling heat transfer and pressure drop characteristics in a plate heat exchanger, and the development of prediction methods for the heat transfer coefficient and frictional pressure drop. Seven working fluids, R134a, R236fa, R245fa, R1234ze(E), R1233zd(E), propane and isobutane, were tested at the reduced pressures of 0.45, 0.55 and 0.65, corresponding to saturation temperatures ranging from 55 °C to 141 °C, and various mass fluxes. Two heat transfer mechanisms, nucleate boiling and thin-film evaporation, were identified in the heat transfer processes of the different working fluids, due to the diversity in their thermo-physical properties. Moreover, the results indicate that propane and isobutane have higher heat transfer coefficients than the other working fluids, while R236fa has the lowest heat transfer coefficient. The frictional pressure drops show the same characteristics for all the working fluids, increasing with the increase of the vapor quality and mass flux and the decrease of the saturation temperature. A superposition model presented in the paper achieves a good prediction for the heat transfer data, with a 12.8% mean absolute percentage deviation. A correlation developed in a previous work by the authors enables a prediction with an 11.1% mean absolute percentage deviation for the pressure drop data. The prediction methods presented in the paper will facilitate the modelling and design of plate heat exchanger evaporators in organic Rankine cycle units.

Acting law of in-hole initiation position on distribution of blast vibration field

In rock drilling and blasting, the in-hole initiation position determines the propagation direction of the explosive detonation wave, and thereby affects the distribution of blast vibration field (BVF). In this study, the acting mechanism of the initiation position was investigated via the comprehensive analysis of the distribution of the detonation products, the explosion energy as well as BVF of the cylindrical charge. Then, the distribution law of BVF under different initiation positions was analyzed using the Heelan’s short-column-solution based superposition model of an extended charge. At last, the acting effect of the initiation position on the distribution of BVF was demonstrated by the onsite blasting experiment. Results indicate that the acting mechanism of the initiation position lies in the axial non-uniform distribution of the explosive energy and the phase delay effect of the superposition of BVF. The in-hole initiation position has the adjustment effect on the distribution of BVF, due to which, the blast vibration amplitude is strengthened at the forward direction of the detonation wave. It needs to be pointed that the non-uniformity of the distribution of BVF is under some control of the explosive length and the explosive velocity of detonation. For the common initiation modes, the field test results indicate that the ground peak particle velocities under the bottom are larger than those under the top and mid-point initiations, and the top initiation is the smallest. Besides, the blast vibration differences becomes more obvious as the blast-hole depth increases, but the vibration difference gradually vanishes with distance.

Wind turbine power prediction considering wake effects with dual laser beam LiDAR measured yaw misalignment

Accurate power prediction of a wind turbine under wake is important for wake suppression control, which is of great significance to reduce the energy loss of a wind farm. The power output of a wind turbine affected by wake is determined by yaw misalignment angle, equivalent inflow wind speed and the size of wake area imposed. However, with current techniques, it is difficult to measure the yaw misalignment angle of a wind turbine under wake that hinders the calculation of its equivalent inflow wind speed. By exploring the interference mechanism of the wake effects to the measurement of yaw misalignment angle with dual laser beam wind LiDAR an approach to calculate realistic yaw misalignment angle of a wind turbine under wake is proposed. Based on this and combined with the wake superposition model, the equivalent inflow wind speed of the wind turbine under wake can be determined. This enables a model to predict the power output of a wind turbine under wake effects. The model is verified by comparisons between prediction results and the data collected in Supervisory Control And Data Acquisition system from a wind farm with five inline wind turbines. It shows that with the wake compensation, the predicted equivalent wind speeds have achieved higher than 90% of accuracy and the output power predictions have maximum 7% accuracy improvements. The proposed calculation method of yaw misalignment angle with wind LiDAR and the power output prediction model of wind turbines under wake provide important basis for wind farm wake control.

Superposition model of mode shapes composed of travelling torsional guided waves excited by multiple circular transducer arrays in pipes

In pipe inspection using ultrasonic guided wave technique, the current commercial transmitters are designed for the unidirectional guided wave excitation using multiple circular piezoelectric transducers arrays in the axial direction. However, the source with many individual transducer elements in arrays has difficulty in achieving an axisymmetric loading perfectly for defect detection. Therefore, a quasi-axisymmetric wave is formed due to many undesired wave modes are launched instead of a pure axisymmetric wave at a given excitation frequency. In this paper, a realistic superposition model of axial multiple transducer arrays is proposed. The model has many potential applications; one example is investigating the source influence on the generated quasi-axisymmetric wave effect. The analytical model is employed to achieve the predictions for investigating a transmitter’s influence for the unidirectional enhancement of torsional T(0,1) guided wave mode excitation in a pipe inspection system composing of three piezoelectric transducer ring arrays. The excitation function with variable power levels among transducers in arrays is also introduced. The predictive results using the analytical model for the distribution of circumferential displacement amplitudes over time are verified using the finite element method and a CLV-3D laser vibrometry measurement on a 219.1-mm-outer-diameter steel pipe without defect. A comparison between calculated and test results has been analysed quantitatively. The respective results are in good agreement. Thus, predictions for the superposed wavefield can be used to analyse the realistic characterisation of the excitation function in axial multiple transducer arrays. Additionally, a sensitivity analysis for part-circumferential crack detection using the quasi-axisymmetric torsional modes generated is also evaluated using finite element modelling.

Application of a superposition model to evaluate surface asymmetric settlement in a mining area with thick bedrock and thin loose layer

Surface subsidence caused by underground mining is a complicated spatiotemporal process. This study establishes a novel mining subsidence superposition model using variable mining thickness of coal seam by combining two models based on rock rheology theory and the Weibull subsidence method. This model better characterises the surface subsidence mechanism under geological conditions of thick bedrock and thin loose layer, and the prediction results are close to actual measurements. The bedrock and loose layer are considered viscoelastic beam and homogeneous body, respectively. The bedrock and loose layer are analysed using the theories of mechanical movement and mathematical models, respectively. Based on actual geological conditions of a mine in East China, the mechanical parameters were substituted into the Weibull composite subsidence prediction model (WCSPM) and the probability integral composite subsidence prediction model (PICSPM), and the predictions of surface subsidence movement parameters were obtained. The prediction results of the WCSPM are closer to the measured surface subsidence values, thereby verifying the applicability of the theoretical model in engineering practice. This model enables the construction of structures in mining-induced subsidence areas with confidence.

Two human antibodies to a meningococcal serogroup B vaccine antigen enhance binding of complement Factor H by stabilizing the Factor H binding site.

Microbial pathogens bind host complement regulatory proteins to evade the immune system. The bacterial pathogen Neisseria meningitidis, or meningococcus, binds several complement regulators, including human Factor H (FH). FH binding protein (FHbp) is a component of two licensed meningococcal vaccines and in mice FHbp elicits antibodies that inhibit binding of FH to FHbp, which defeat the bacterial evasion mechanism. However, humans vaccinated with FHbp develop antibodies that enhance binding of FH to the bacteria, which could limit the effectiveness of the vaccines. In the present study, we show that two vaccine-elicited antibody fragments (Fabs) isolated from different human subjects increase binding of complement FH to meningococcal FHbp by ELISA. The two Fabs have different effects on the kinetics of FH binding to immobilized FHbp as measured by surface plasmon resonance. The 1.7- and 2.0-Å resolution X-ray crystal structures of the Fabs in complexes with FHbp illustrate that the two Fabs bind to similar epitopes on the amino-terminal domain of FHbp, adjacent to the FH binding site. Superposition models of ternary complexes of each Fab with FHbp and FH show that there is likely minimal contact between the Fabs and FH. Collectively, the structures reveal that the Fabs enhance binding of FH to FHbp by altering the conformations and mobilities of two loops adjacent to the FH binding site of FHbp. In addition, the 1.5 Å-resolution structure of one of the isolated Fabs defines the structural rearrangements associated with binding to FHbp. The FH-enhancing human Fabs, which are mirrored in the human polyclonal antibody responses, have important implications for tuning the effectiveness of FHbp-based vaccines.

Development of an Inverse Plume Model for Mass Eruption Rate in Unsteady Conditions

Abstract Following volcanic eruptions, forecasters need accurate estimates of mass eruption rate (MER) to appropriately predict the downstream effects. Most analyses use simple correlations or models based on large eruptions at steady conditions, even though many volcanoes feature significant unsteadiness. To address this, a superposition model is developed based on a technique used for spray injection applications, which predicts plume height as a function of the time-varying exit velocity. This model can be inverted, providing estimates of MER using field observations of a plume. The model parameters are optimized using laboratory data for plumes with physically relevant exit profiles and Reynolds numbers, resulting in predictions that agree to within 10% of measured exit velocities. The model performance is examined using historic eruptions with well-documented unsteadiness, again providing MER estimates of the correct order of magnitude. This method can provide a rapid alternative for real-time forecasting of small, unsteady eruptions.

Dynamical Modeling of Galaxies and Supermassive Black Holes: Axisymmetry in Triaxial Schwarzschild Orbit Superposition Models

Abstract We present a detailed analysis of the behavior of the triaxial Schwarzschild orbit superposition method near the axisymmetric limit. Orbit superposition modeling is the primary method used to determine dynamical masses of supermassive black holes (M BH) in nearby galaxies; however, prior studies have reported conflicting results when comparing the outcome from axisymmetric orbit codes with that from a triaxial orbit code in the axisymmetric limit. We show that in order to achieve (oblate) axisymmetry in a triaxial code, care needs to be taken to axisymmetrize the short-axis tube orbits and to exclude both the long-axis tube and box orbits from the orbit library. Using up to 12 Gauss–Hermite moments of the line-of-sight velocity distributions as constraints, we demonstrate the effects of orbit types on the best-fit M BH in orbit modeling of the massive elliptical galaxy NGC 1453 reported in Liepold et al. In addition, we verify the efficacy of our updated code on a mock galaxy data set. We identify a subset of slowly precessing quasi-planar orbits for which the typical integration times can be insufficient to fully capture the equilibrium orbital behavior in both axisymmetric and triaxial systems with central black holes. Further investigation is needed for a more reliable treatment of these orbits.

Applying System Dynamics of Discrete Supported Track to Analyze the Rail Corrugation Causation on Curved Urban Railway Tracks

Urban rail corrugation on curved tracks with small radii causes strong howling during operation, which has been bothering subway operating companies for many years. Therefore, revealing its causes and growth is important for the comfort and safety of subway operation. Current studies believe that the occurrence of rail corrugation is largely due to the resonant vibration of the wheel-rail system. However, little attention has been paid to the key causes of the track resonance and the practical prediction of the occurrence probability of rail corrugation on the certain track. This paper intends to solve these above issues. Firstly, the practical model of predicting the rail corrugation growth is proposed based on the wheel-rail coupling interaction, the key causes of corrugation are investigated, and the sensitivity analysis is carried out, while the corrugation superposition model is introduced to the analyze the corrugation evolution as well as to validate the corrugation growth from the aspect of material friction and wear. Secondly, the impact of the key causes on the initiation and development of the rail corrugation is investigated based on the cosimulation. Finally, case studies validate the proposed theory model and method. The results show that the practical prediction model for the rail corrugation growth proposed in this paper is able to estimate the occurrence possibility of rail corrugation on a specific track, and the superharmonic resonance of the track directly excited by passing vehicles eventually leads to rail corrugation. It is also found that shortwave corrugation develops more rapidly, and adjusting the support stiffness or sleeper spacing leads to fluctuations in the corrugation wavelength and its wear rate.

The lithofacies superposition patterns of oil-bearing reservoir of different productivity levels of the Lower Fourth Member of Eocene Shahejie Formation in Dongying Sag, Bohai Bay Basin

Based on core observation and well logs, the paper reveals the lithofacies superposition patterns of oil-bearing reservoir of different productivity levels of the Lower Fourth Member of Eocene Shahejie Formation in Dongying Sag, Shengli Oilfield. The reservoir is divided to three types according to its productivity levels. Type A: natural productivity > 10 tons per day; Type B: 5 tons per day <natural productivity ≤10 tons per day and Type C: natural productivity ≤5 tons per day. Their corresponding lithofacies superposition patters are “thin bedded sandstone + mudstone superposition model”, “multi-stage superposition of thick-bedded conglomerate and pebbled sandstone” and “superposition of medium thick pebbled sandstone, coarse-grained sandstone and medium-grained sandstone”.

The area localized coupled model for analytical mean flow prediction in arbitrary wind farm geometries

This work introduces the area localized coupled (ALC) model, which extends the applicability of approaches that couple classical wake superposition models and atmospheric boundary layer models to wind farms with arbitrary layouts. Coupling wake and top–down boundary layer models is particularly challenging since the latter requires averaging over planform areas associated with turbine-specific regions of the flow that need to be specified. The ALC model uses Voronoi tessellation to define this local area around each turbine. A top–down description of a developing internal boundary layer is then applied over Voronoi cells upstream of each turbine to estimate the local mean velocity profile. Coupling between the velocity at hub-height based on this localized top–down model and a wake model is achieved by enforcing a minimum least-square-error in mean velocity in each cell. The wake model in the present implementation takes into account variations in wind farm inflow velocity and represents the wake profile behind each turbine as a super-Gaussian function that smoothly transitions between a top-hat shape in the region immediately following the turbine to a Gaussian profile downstream. Detailed comparisons to large-eddy simulation (LES) data from two different wind farms demonstrate the efficacy of the model in accurately predicting both wind farm power output and local turbine hub-height velocity for different wind farm geometries. These validations using data generated from two different LES codes demonstrate the model's versatility with respect to capturing results from different simulation setups and wind farm configurations.