Common Analytical Models Research Articles

Accurate identification of soil thermal parameters and groundwater flow from thermal response tests

The soil heat transfer parameters constitute the key information required for designing ground source heat pump (GSHP). Due to the simplification of the common analytical models, traditional methods are difficult to achieve accurate identification of soil thermal parameters and seepage velocity simultaneously. In this work, a high-precision method to simultaneously identify soil thermal conductivity, volumetric heat capacity, and seepage velocity based on deep neural network is proposed. Through the inversed orthogonal method, the training and validation samples are obtained from a large number of thermal response tests (TRTs) on a full-scale simulation platform. The accuracy of this method was verified by comparing identification results with the true values. Meanwhile, the uncertainty of identification results under different noise conditions was quantified, and the impact of test duration was discussed. The results showed that when the maximum random noise is 0.1 °C, the identification errors of the thermal conductivity, volumetric heat capacity, and seepage velocity are only 1.14 %, −4.34 %, and −3.08 %, respectively. The identification reliability can be improved by obtaining the average value of the results under multiple tests and extending the test duration. When the test duration increased from 50 to 100 h, the uncertainty of the identified parameters reduced by 54.57 %, 48.41 %, and 65.70 %, respectively.

Soot Measurements and a Simplified Analytical Formulation-Based Modeling in Laminar Counterflow Diffusion Flames

ABSTRACT The paper presents soot volume fraction measurements and a simplified soot formation model. Soot formation is a complex physicochemical process predominantly modeled using detailed chemistry and stochastic methods. The current work presents a simplified analytical function-based approach to calculate the net soot formation rate by coupling the local mixture-fraction and temperature fields. The validation experiments were carried out in a unique large-diameter (40 mm) counterflow burner for ethylene-air flames at various strain rates and normalized separation (L/D) distances. The soot volume fractions (fv) were determined using Laser Induced Incandescence (LII) technique calibrated by the Light Extinction (LE) method. Further model validations were carried out against the experimental measurements in the literature. The modeling work was performed on OpenFOAM®. The model predicted soot distributions for various peak flame temperatures, stoichiometric mixture-fractions, burner dimensions, fuel-oxidizer compositions, and strain rates with good accuracy. The study underscores the importance of considering two soot formation rate peaks, one at high temperature and one at low temperature, for accurate predictions, unlike a single peak employed in common analytical models. Furthermore, the effect of velocity boundary conditions on soot zone locations and the significance of providing realistic velocity conditions for the simulations are also discussed. Particle Image Velocimetry (PIV) measurements were performed to determine the actual nozzle-exit velocity profiles.

Back-Azimuth Estimation of Air-to-Ground Coupled Infrasound from Transverse Coherence Minimization

AbstractWe present the transverse coherence minimization method (TCM)—an approach to estimate the back-azimuth of infrasound signals that are recorded on an infrasound microphone and a colocated three-component seismometer. Accurate back-azimuth information is important for a variety of monitoring efforts, but it is currently only available for infrasound arrays and for seismoacoustic sensor pairs separated by 10 s of meters. Our TCM method allows for the analysis of colocated sensor pairs, sensors located within a few meters of each other, which may extend the capabilities of existing seismoacoustic networks and supplement operating infrasound arrays. This approach minimizes the coherence of the transverse component of seismic displacement with the infrasound wave to estimate the infrasound back-azimuth. After developing an analytical model, we investigate seismoacoustic signals from the August 2012 Humming Roadrunner experiment and the 26 May 2021 eruption of Great Sitkin Volcano, Alaska, U.S.A., at the ranges of 6.5–185 km from the source. We discuss back-azimuth estimates and potential sources of deviation (1°–15°), such as local terrain effects or deviation from common analytical models. This practical method complements existing seismoacoustic tools and may be suitable for routine application to signals of interest.

Fractal two-scale method for calculating the laser scattering distribution of asphalt pavement.

The laser scattering characteristic of pavement is one of the important factors that affect the detection performance of optical sensors such as lidars. Because the wavelength of laser does not match the roughness of the asphalt pavement, the common analytical approximation model of electromagnetic scattering is not applicable in this case, so it is difficult to calculate the laser scattering distribution of the pavement accurately and effectively. According to the self-similarity of the asphalt pavement profile, a fractal two-scale method (FTSM) based on fractal structure is proposed in this paper. We used the Monte Carlo method to obtain the bidirectional scattering intensity distribution (SID) and the back SID of the laser on the asphalt pavement with different roughness. Then we designed a laser scattering measurement system to verify the simulation results. We calculated and measured the SIDs of s-light and p-light of three asphalt pavements with different roughness (σ=0.34 mm; 1.74 mm; 3.08 mm). The results show that, compared with the traditional analytical approximation methods, the results of FTSM are closer to the experimental results. Compared with the single-scale model based on the Kirchhoff approximation, FTSM has a significant improvement in computational accuracy and speed.

Comparison of Common Classical Analytical Models for Mesoporous Adsorption

Comparison of Common Classical Analytical Models for Mesoporous Adsorption

Simple Growth-Metabolism Relations Are Revealed by Conserved Patterns of Heat Flow from Cultured Microorganisms.

Quantitative analyses of cell replication address the connection between metabolism and growth. Various growth models approximate time-dependent cell numbers in culture media, but physiological implications of the parametrizations are vague. In contrast, isothermal microcalorimetry (IMC) measures with unprecedented sensitivity the heat (enthalpy) release via chemical turnover in metabolizing cells. Hence, the metabolic activity can be studied independently of modeling the time-dependence of cell numbers. Unexpectedly, IMC traces of various origins exhibit conserved patterns when expressed in the enthalpy domain rather than the time domain, as exemplified by cultures of Lactococcus lactis (prokaryote), Trypanosoma congolese (protozoan) and non-growing Brassica napus (plant) cells. The data comply extraordinarily well with a dynamic Langmuir adsorption reaction model of nutrient uptake and catalytic turnover generalized here to the non-constancy of catalytic capacity. Formal relations to Michaelis–Menten kinetics and common analytical growth models are briefly discussed. The proposed formalism reproduces the “life span” of cultured microorganisms from exponential growth to metabolic decline by a succession of distinct metabolic phases following remarkably simple nutrient–metabolism relations. The analysis enables the development of advanced enzyme network models of unbalanced growth and has fundamental consequences for the derivation of toxicity measures and the transferability of metabolic activity data between laboratories.

Comparison of Common Classical Analytical Models for Microporous Adsorption

Comparison of Common Classical Analytical Models for Microporous Adsorption

A new method for simulating multiple wind turbine wakes under yawed conditions

Counter-rotating vortices generated in wake steering not only deform the turbine wake, but also can make the wake trajectory of a non-yawed downwind turbine deviate from its rotor centerline, referred to as “secondary wake steering” phenomenon. Recent studies have also shown that the vortex interactions become clearer when the wind farm includes multiple turbines. However, in the common analytical models for active yaw control, the effects of these vortices are not considered. Evidently, this omission can lead to a decrease in model prediction accuracy. To compensate for it, a new analytical wind farm model is proposed. It adopts a physical-based momentum conserving wake superposition method to deal with the interaction of multiple wakes, in which, not only combining the streamwise velocity deficit of each individual yawed wind turbine, but also the transverse velocity from different wakes. Additionally, an “added yaw angle” is defined for a downwind turbine operating in upstream yawed turbine wakes, to reflect the change in local wind direction it perceives. For validation purposes, the LES wind field obtained from the SOWFA tool is used as a reference, and the newly proposed model is found to agree well with LES results and outperforms the representative conventional analytical model in almost all test cases. The new model can successfully reproduce the “secondary wake steering” phenomenon in the overlapped wake, and provides significant improvements in predicting power production of wind turbines.

Extending a Grid of Hydrodynamic Planetary Upper Atmosphere Models

Abstract In this research note, we outline the extension of the grid of upper atmosphere models first presented in Kubyshkina et al. The original grid is based on a 1D hydrodynamic model and consists of about 7000 models covering planets of a size ranging from that of Earth to twice that of Neptune at orbits corresponding to equilibrium temperatures between 300 and 2000 K around solar-like (0.4 to 1.3 solar mass) stars. The extended and revised grid of models consists of 10,235 points and covers a planetary mass range of up to 109 Earth masses, which allows one to outline the transition between low- and high-gravity hot planets in in short period orbits. We prepared the interpolation tool allowing one to use the grid to define the mass-loss of a planet that falls into the parameter range of the grid. We provide a comparison of our results to common analytical models.

Uncovering design principles for amorphous-like heat conduction using two-channel lattice dynamics

The physics of heat conduction puts practical limits on many technological fields such as energy production, storage, and conversion. It is now widely appreciated that the phonon-gas model does not describe the full vibrational spectrum in amorphous materials, since this picture likely breaks down at higher frequencies. A two-channel heat conduction model, which uses harmonic vibrational states and lattice dynamics as a basis, has recently been shown to capture both crystal-like (phonon-gas channel) and amorphous-like (diffuson channel) heat conduction. While materials design principles for the phonon-gas channel are well established, similar understanding and control of the diffuson channel is lacking. In this work, in order to uncover design principles for the diffuson channel, we study structurally-complex crystalline Yb14 (Mn,Mg)Sb11, a champion thermoelectric material above 800 K, experimentally using inelastic neutron scattering and computationally using the two-channel lattice dynamical approach. Our results show that the diffuson channel indeed dominates in Yb14MnSb11 above 300 K. More importantly, we demonstrate a method for the rational design of amorphous-like heat conduction by considering the energetic proximity phonon modes and modifying them through chemical means. We show that increasing (decreasing) the mass on the Sb-site decreases (increases) the energy of these modes such that there is greater (smaller) overlap with Yb-dominated modes resulting in a higher (lower) thermal conductivity. This design strategy is exactly opposite of what is expected when the phonon-gas channel and/or common analytical models for the diffuson channel are considered, since in both cases an increase in atomic mass commonly leads to a decrease in thermal conductivity. This work demonstrates how two-channel lattice dynamics can not only quantitatively predict the relative importance of the phonon-gas and diffuson channels, but also lead to rational design strategies in materials where the diffuson channel is important.

A New Method for Imputing Censored Values in Crossover Designs with Time-to-Event Outcomes Using Median Residual Life.

Crossover designs are commonly applied in research due to efficiency and subject parsimony compared to parallel studies. Baseline measurements would improve the power of comparison. For time to event outcomes, the sample size is reduced due to censorship, if they are ignored; thus, applying traditional regression models will be limited. A logical solution is to impute the censored observation and apply common analytical models for analyzing the data. Nevertheless, techniques to impute censored data in time-to-event outcomes in crossover designs are not practiced as much. Accordingly, we propose a method to impute the censored observation using median residual life regression and then analyze the data using analyses of covariance (ANCOVA), considering the difference of period-specific baselines as covariate. We used simulation to show the favorable performance of our method relative to a recently proposed method, multiple imputation with model averaging and ANCOVA (MIMI). Specifically, the censored observations were multiply-imputed using prespecified parametric event time models, and then, the methods were applied to a real data example.

Horizontal and radial collector wells: simple tools for a complex problem

The capture of groundwater by horizontal wells (HWs) is an old but often overlooked technique. Practically all modeling techniques available in groundwater hydrology have been applied to HWs. This work compares analytical models with field data and investigates the influence of nonuniform screen inflow. The usefulness of a vertical well approximation is studied. A new MATLAB application, HORI, is presented for common analytical models. Analytical methods are found to reproduce drawdown around two radial collector wells (RCWs). Beyond the direct vicinity of the caisson, in particular, drawdown around an RCW can be approximated with a vertical well model.

Prediction of Silicon Direct Nitridation Kinetic By An Efficient and Simple Predictive Model Based on Group Method of Data Handling

In the present study, a soft computing method namely the group method of data handling (GMDH) is applied to develop a new and efficient predictive model for prediction of conversion percentage of silicon. A comprehensive database is obtained from experimental studies in literature. Several effective parameters like time, temperature, nitrogen percentage, pellet size and silicon particle size are considered. The performance of the model is evaluated through statistical analysis. Moreover, the silicon nitridation was performed in 1573 k and results were evaluated against model results for validation of the model. Furthermore, the performance and efficiency of the GMDH model is confirmed against the two most common analytical models. The most effective parameters in estimating the conversion percentage are determined through sensitivity analysis based on the Gamma Test. Finally, the robustness of the developed model is verified through parametric analysis.

In vitro bactericidal and drug release properties of vancomycin-amino surface functionalized bioactive glass nanoparticles

Bioactive glass has been used clinically in bone repair applications for bone grafting because of its prominent physiochemical and osteogenic properties. Various attempts have been made to enhance bioactive glass efficiency in combination with other biomaterials such as antibiotics and growth factors. In present study, we developed a modification of bioactive glass nanoparticles that insured long term antibacterial effect. Bioactive glass nanoparticles (BGNs) were functionalized with (3-Aminopropyl) triethoxysilane (APTS), then vancomycin (VAN) was immobilized onto BGNs-APTS via EDC/NHS cross-linking process. Another study group namely BGNs-VAN was synthesized as a control group without any cross-linking process. The nanoparticles were analyzed by FTIR, Zetasizer, XRD, and SEM instruments. FTIR and Zetasizer results confirmed the functionalization and immobilization processes. Drug release was evaluated by UV–Vis spectroscopy in a phosphate buffered saline (PBS) solution. BGNs-APTS-VAN had a long term release profile with a different release kinetics formulation. The release profile of vancomycin didn't fit with common analytical models. A new mathematical model was suggested. Minimum bactericidal concentration (MBC) of nanoparticles against MRSA bacteria was obtained at 1.25 mg/mL. Vancomycin burst release in BGNs-VAN made a delay in the ALP enzyme secretion from MC3T3 cells, while in BGNs-APTS-VAN, the burst release decreased and consequently the delay in ALP enzyme secretion decreased.

Complex industrial automation data stream mining algorithm based on random Internet of robotic things

ABSTRACTIn recent years, with the continuous development of computer application technology, network technology, data storage technology, and the large amount of investment in information technology, enterprises have accumulated a large amount of data while transforming and improving enterprise management modes and means. How to mine useful data, discover important knowledge and extract useful information has become a hot topic of current research. Industrial big data is significantly different from traditional big data. The traditional big data is based on the Internet environment. Although the data has a high degree of discretization and distribution, its association is relatively simple. The collection of industrial process data is relatively easy, but the mathematical and physical and chemical mechanism models involved make the inherent relationship of data complex, so it is difficult to use common analytical models and methods for processing. In this paper, we propose a complex industrial automation data stream Mining algorithm based on random internet of robotic things, and experimental results show that the proposed algorithm has higher data mining efficiency and robustness.

An Analytical Method for Calculating the Natural Frequencies of a Motor Considering Orthotropic Material Parameters

In this paper, a novel analytical method is proposed for calculating the natural frequencies of a motor to reduce the large natural frequency calculation errors produced by common isotropic analytical models. First, a theoretical model of the equivalent cylindrical shell is established with five orthotropic material parameters by considering the simple-support boundary condition, the effect of the axial length, and the orthotropic characteristics of the motor. Then, the density of the equivalent cylindrical shell is obtained, and the composite material theory is employed to estimate the equivalent orthotropic material parameters. Finally, we find that the natural frequencies and the modal shapes obtained by the proposed analytical model are in good agreement with those of the experimental results, verifying the accuracy of the proposed model.

Physics of Luminous Transient Light Curves: A New Relation between Peak Time and Luminosity

Abstract Simplified analytic methods are frequently used to model the light curves of supernovae and other energetic transients and to extract physical quantities, such as the ejecta mass and amount of radioactive heating. The applicability and quantitative accuracy of these models, however, have not been clearly delineated. Here we carry out a systematic study comparing certain analytic models to numerical radiation transport calculations. We show that the neglect of time-dependent diffusion limits the accuracy of common Arnett-like analytic models, and that the widely applied Arnett’s rule for inferring radioactive mass does not hold in general, with an error that increases for models with longer diffusion times or more centralized heating. We present new analytic relations that accurately relate the peak time and luminosity of an observed light curve to the physical ejecta and heating parameters. We further show that recombination and spatial distribution of heating modify the peak of the light curve and that these effects can be accounted for by varying a single dimensionless parameter in the new relations. The results presented should be useful for estimating the physical properties of a wide variety of transient phenomena.

A general mathematical model for two-parameter generating machining of involute cylindrical gears

• A general mathematical model for two-parameter generating machining of involute gears is developed. • A general discrete assisted model for two-parameter generating machining is proposed. • The instant contact line is derived by implicated information during discrete enveloping. • The engaged cutting edge segments can be distinguished when multiple-cutting edge are adopted. Instead of the common analytical model for involute gears machining, a general mathematical model for two-parameter generating machining is developed in this study with adopting discrete enveloping to increase its robustness and generality for machined profile calculation and instant contact analysis. The geometric parameters and motion relationships are integrated according to the cross-axis gear meshing at first, and the enveloping theory for two-parameter generating process is analyzed briefly with involving middle gear rack. By transforming the multiple cutting edges relative to the gear blank according to the generating motions, a numerical algorithm is proposed to distinguish the external enveloping profile on the shaft section, then the derivation of instant contact points via the implied time sequences of profile points is introduced. Finally, the coordinate transformations for the spatial trajectory of instant contact points identifying and the engaged cutting edge segments distinguishing are investigated. At last, a non- involute profile skiving is performed to verify the generality and the robustness of proposed method, and several typically generating machining operations for cylindrical involute gear are simulated numerically to proof the accuracy of the proposed model by finding the deviations from the standard involute curves and the geometries of the instant contact points.

Comparison of Analytical Approaches Predicting the Compressive Strength of Fibre Reinforced Polymers.

Common analytical models to predict the unidirectional compressive strength of fibre reinforced polymers are analysed in terms of their accuracy. Several tests were performed to determine parameters for the models and the compressive strength of carbon fibre reinforced polymer (CFRP) and glass fibre reinforced polymer (GFRP). The analytical models are validated for composites with glass and carbon fibres by using the same epoxy matrix system in order to examine whether different fibre types are taken into account. The variation in fibre diameter is smaller for CFRP. The experimental results show that CFRP has about 50% higher compressive strength than GFRP. The models exhibit significantly different results. In general, the analytical models are more precise for CFRP. Only one fibre kinking model’s prediction is in good agreement with the experimental results. This is in contrast to previous findings, where a combined modes model achieves the best prediction accuracy. However, in the original form, the combined modes model is not able to predict the compressive strength for GFRP and was adapted to address this issue. The fibre volume fraction is found to determine the dominating failure mechanisms under compression and thus has a high influence on the prediction accuracy of the various models.

No-load iron loss model for a fractional-slot surface-mounted permanent magnet motor based on magnetic field analytical calculation

The common analytical models for the no-load iron loss of permanent magnet(PM) motors usually neglect the iron loss caused by the rotating magnetic field in the tooth tips and the harmonics of the magnetic fields in the teeth and yokes. This paper presents an analytical model for no-load iron loss of a fractional-slot surface-mounted permanent magnet motor. According to the existing analytical model of the magnetic field distribution in the slotted air gap, the magnetic flux densities considering the harmonics of the stator tooth and yoke are both derived based on the continuity of magnetic flux. Due to the complexity of the magnetic field in the tooth tip, the tangential flux density of the tooth tip is approximated by an equivalent sine wave and the radial component is regarded to be the same as that of the corresponding tooth. After obtaining the magnetic fields in stator different regions, the analytical iron loss is calculated by using the Bertotti model and the orthogonal decomposition model. A 20-pole/24-slot PM synchronous motor is taken as an example. The maximum error between the analytical model and finite element model(FEM) is 5.46%, which verifies the validity of the proposed method.