Drift Trend Research Articles

Dynamic Characterization of Equatorial Plasma Bubble Based on Triangle Network‐Joint Slope Approach

AbstractThis paper introduces a Triangle Network‐Joint Slope (TN‐JS) approach to characterize the spatial and temporal dynamics of Equatorial Plasma Bubbles (EPBs) during geomagnetic storms. To collaboratively determine the EPB drift directions from multiple stations, a Delaunay triangle network is constructed, utilizing the distribution of Ionospheric Piercing Points (IPPs). The Time Difference of Arrival (TDOA) is extracted through cross‐correlating the Rate of Total Electron Content (ROT). The EPB drift direction can be approximately calculated by considering TDOA and IPP distances within each individual triangle of the network. This calculation is then refined through a joint statistical analysis. Using a reference station as the origin, the remaining stations within the network are projected along the estimated EPB drift direction. A spatial‐temporal color map illustrating regional ionospheric anomaly ROT observations is constructed. The EPB drift velocity among multiple stations can be collectively estimated by fitting the slope of this map, facilitating outlier exclusion. Accounting for satellite dynamic effects and the diverse orbit characteristics of GPS and BDS, corresponding IPP scan velocity compensation is performed and analyzed for EPB dynamic estimation. Using the geomagnetic storm event that occurred on September 8 as a case study, the spatial‐temporal kinetic properties of EPBs is characterized by analyzing Global Navigation Satellite System (GNSS) observations from 17 Hong Kong monitoring stations with the proposed TN‐JS approach. The results indicate during this magnetic event, that EPBs exhibit a westward drift trend with velocities ranging from a few tens to hundreds of meters per second in GPS and BDS observations.

The importance of hazard-consistency when estimating seismic residual drifts in steel moment frames

Residual drifts are routinely used to assess the post-earthquake safety of buildings. Despite their importance, studies on the probabilistic assessment of residual drifts in multi-storey buildings with Steel Moment Resisting Frames (SMRF) are far less common than those dealing with their transient peak drift counterpart. More seriously, although residual drift prediction models have been developed with a particular broad ground-motion type or soil condition in mind, all models proposed to date remain oblivious to the central issue of hazard consistency. Hence, missing the causal connection between the seismic hazard level and the ground-motion suite used and potentially compromising the meaningfulness of their results. This oversight is expected to introduce a bias in the estimation of residual drifts but its magnitude has not yet been properly evaluated. In this paper, we evaluate and quantify the significance of these effects. To this end, we use the Conditional Scenario Spectra framework, which provides a set of realistic earthquake spectra with assigned rates of occurrences based on their spectral shape and intensity, thus preserving the critical relationship of hazard consistency. Nonlinear Response History Analyses (NRHA) of 24 deteriorating SMRFs under 816 ground-motion records are performed to construct a database of residual drift demands. These NRHA results are used to examine the residual drift trends and to construct benchmark residual drift hazard curves. An extensive feature selection process employing several Machine Learning (ML) algorithms precedes the development of hybrid data-driven predictive models. Finally, we compare our hazard-consistent predictions with currently available models and quantify the massive under- and over-estimations associated with previously proposed non-hazard-consistent assumptions.

119 Pedigree and Population-Based Genomic Inbreeding Trends Over Time in Five Commercial Swine Breeding Populations

Abstract Controlling inbreeding within a population is critical to maintain additive genetic variance and reduce negative consequences such as inbreeding depression in small, closed herds. Some breeding programs may utilize subjective standard operating procedures (SOPs) such as setting the minimum number of boars, limiting the number of matings per boar, and limiting the relationships among active boars. Software programs such as Matesel can control inbreeding within a population more precisely using evolutionary algorithms by optimizing the mating and selection process to constrain inbreeding at a given target degree or other metric specified (e.g., coancestry). The main problem has been the choice of what relationship matrix to use in constraining inbreeding in these programs. Furthermore, there are many different genomic inbreeding metrics that can be used to quantify inbreeding rates over time. The objective of the current research was to investigate the trends in the pedigree [PED, (A diagonal – 1) * 100] and two population-based genomic inbreeding metrics. One based on expected homozygosity (2pq, Ghom) and one based on drift (squared allele frequency changes, Gdrift). Data included nucleus animals born from 2017 through 2022 from five different genetic lines (lines A-E). Most parents and male selection candidates were genotyped using the commercial 50k SNP panel from GeneSeek. Pedigree was traced back at least 3 generations. A total of 80k animals were sampled from the total number of genotyped animals for computational reasons across line and birth year. Results show that in general, the maternal lines (A and B) showed the least rate of inbreeding over time (0.30 and 0.43% / year for A and B, respectively), while terminal lines were greater, especially line D (0.36 to 0.76% / year). Pedigree inbreeding in 2022 was between 1.48% (line A) to 3.80% (line D) after subtracting the average pedigree inbreeding in 2017. Population-based genomic measures of inbreeding showed a very small difference in line A (0.09%), larger Gdrift than Ghom in line B (1.37%), and larger Ghom than Gdrift in lines C, D, and E (2.87% to 4.38%). In general, the trend for PED and Gdrift was very similar for all lines, while Ghom tended to increase rapidly out of control in the three terminal lines (C-E) in later years. Future research will focus on integrating results from the diagonals of a variety of G matrices on an individual basis (e.g., VanRaden 1 and 2, runs-of-homozygosity, and a linkage-analysis matrix). Results showed the pedigree and genomic drift trends over time were similar, however, the genomic homozygosity trend was much greater in terminal lines.

Prediction of the drift trend in piezoelectrically actuated MEMS mirror by 2D reliability modelling

One of the most prominent applications of piezoelectric materials is in microelectromechanical systems (MEMS). A current challenge in piezo-MEMS is the prediction of the reduction in efficiency of piezoelectric materials towards the end of their lifespan. In this research, we assess the reliability of piezoelectrically actuated micromirrors (piezo-mirrors) and estimate the parametric drift, such as the drift of the opening angle, during the specified lifetime. We accomplish this assessment and evaluation by considering the impacts of both temperature and driving voltage. In this study, the analytical relationship between micromirror performance, driving voltage, temperature, and operative time has been described and predicted by using a 2D reliability model based on a characteristic function that explains the PZT stability. The operative time acceleration associated with distinct test conditions has been considered by using a power law model for voltage dependency and an Arrhenius model to describe the relationship between the temperature and its acceleration effect on the drift of the piezo-mirror performance. Micromirrors were subjected to experimental tests, and the results were employed to validate the reliability model presented in this work. Therefore, the model parameters were fine-tuned using experimental data from High-Temperature Operative Life (HTOL) test, and the reliability model was validated by comparing the experimental data from HTOL test performed under different test conditions.

Finite element analysis of RC moment-resisting frames to assess effective slab width; a parametric study

In reinforced concrete (RC) moment-resisting frames (MRFs) with cast-in-situ slabs, the slab action as tension flange during lateral loading enhances the flexural capacity of beams in negative moments. This enhancement may lead to strong beam-weak column unfavorable failure mode in these structures. Field observations of RC MRFs during strong ground motion indicated that the effective slab width values considered by the seismic provisions of the design codes are not adequate to guarantee the achievement of the design method of weak beam-strong column. An accurate estimation of effective slab width needs to assess factors such as geometrical characteristics of connection, continuity of models, and imposed story drift level. A 3D spatial two-story RC MRF was developed using finite element analysis (FEA) to explore the effect of mentioned factors on effective slab width. For finite element (FE) modeling of RC MRF, the concrete damaged plasticity (CDP) model is applied. The CDP model parameters are defined using a mesh-independent methodology introduced in the literature. Comparing the FEA results and results obtained from three half-scale RC MRFs, tested under reversed cyclic loading conditions showed an excellent correlation. The results predicted by the FE model in terms of lateral load–displacement response, reinforcement yielding sequence, crack patterns, and failure modes had a considerable agreement with test observations. The validated FE model was used to develop the other models to conduct a parametric study in the next step. Geometric parameters studied in this paper through numerical modeling were longitudinal and transverse beam length and height, and cross-sectional column dimension. Results of the parametric study showed that the effect of the ratio of transverse beam length to height is significantly more than the ratio of longitudinal beam length to height. The trend of effective slab width versus story drift depends on connection geometry, especially the ratio of transverse beam length to transverse beam height. Finally, an equation was driven to predict the effective slab width using linear regression analysis.

OBT Drift Trend Analysis and P-OBT Drift Setting Automation to Improve Geometrical Accuracy for GK2A Meteorological Image

OBT Drift Trend Analysis and P-OBT Drift Setting Automation to Improve Geometrical Accuracy for GK2A Meteorological Image

Evaluation and correction of injection order effects in LC-MS/MS based targeted metabolomics

For large-scale and long-term metabolomics studies that involve a large batch or multiple batches of analyses, batch effects cause nonbiological systematic biases that may lead to false positive or false negative findings. Quantitative monitoring and correction of batch effects is critical to the development of reproducible and robust metabolomics platforms either for untargeted or targeted analyses. To achieve sufficient retention and separation of a broad range of metabolites with diverse chemical structures and physicochemical properties, LC-MS/MS based targeted metabolomics often involves 3 complemented chromatographic separation methods, including reversed-phase liquid chromatography (RP-LC), hydrophilic interaction liquid chromatography (HILIC), and ion-pair liquid chromatography (IP-LC). The purpose of this study is to quantitatively evaluate intra-batch variations or injection order effects of the RP-LC, HILIC, and IP-LC methods for targeted metabolomics analyses, and develop strategies to minimize intra-batch variations and correct injection order effects for problematic metabolites. Both RP-LC and HILIC methods exhibit robust intra-batch reproducibility in 0.2 µM standard mix QC, with ∼96 % of the measured metabolites showing acceptable intra-batch variations (<20 %); whereas, the intra-batch reproducibility for some metabolites in cell matrix QC may be compromised due to stability issue, suboptimal chromatographic retention, and/or matrix effects causing ionization suppression and/or retention instability. The IP-LC method exhibits significant injection order effects, which could be effectively corrected by the developed exponential models of signal drift trends as a function of injection order for individual targeted metabolites.

Reliable Low Voltage Selector Device Technology Based on Robust SiNGeCTe Arsenic-Free Chalcogenide

Modern data-centric computing applications are increasingly demanding in terms of memory density and performance. The cross-point memory architecture based on the two-terminal one-selector/one-resistor memory cell is an attractive solution for high-density and 3D-compatible embedded memory. In this letter, we introduce a new arsenic-free chalcogenide material, namely SiNGeCTe, for low voltage selector applications, and we report on its remarkable reliability characteristics. The inclusion of the Si dopant allows for an enhanced material robustness in terms of stable high current operation and extended thermal stability (≥450°C, 30 min), and reduces the First Fire impact on the subthreshold conduction. We investigate the threshold voltage drift and reveal a marked trend of the drift slope with the thickness of the chalcogenide layer. Finally, based on the reported drift trend, the optimized device with 5 nm thickness is highlighted for low threshold voltage and low drift applications, demonstrating low threshold voltage drift with slope <30 mV/dec. The optimized device proves an excellent cycling endurance ≥1e10 cycles.

DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation

In many real-world scenarios, we often deal with streaming data that is sequentially collected over time. Due to the non-stationary nature of the environment, the streaming data distribution may change in unpredictable ways, which is known as the concept drift in the literature. To handle concept drift, previous methods first detect when/where the concept drift happens and then adapt models to fit the distribution of the latest data. However, there are still many cases that some underlying factors of environment evolution are predictable, making it possible to model the future concept drift trend of the streaming data, while such cases are not fully explored in previous work. In this paper, we propose a novel method DDG-DA, that can effectively forecast the evolution of data distribution and improve the performance of models. Specifically, we first train a predictor to estimate the future data distribution, then leverage it to generate training samples, and finally train models on the generated data. We conduct experiments on three real-world tasks (forecasting on stock price trend, electricity load and solar irradiance) and obtained significant improvement on multiple widely-used models.

Application of A.M. Obukhov’s theory of correlation of vectors for scientific research and engineering calculations of ice drift in the Arctic Ocean.

The theory of vectors correlation of Obukhov was used to describe an ice drift in the Arctic Ocean. The main features are defined by an area. The tracks tortuosity in Beaufort Gyre and Transarctic current varies threefold: 1.5 and 4.5. Year to year and seasonal variations indicate the position of the Beaufort Gyre and the speed of the Transarctic drift. The average speed does not exceed 10 cm/s. The drift increases in summer, and in winter it intensifies in Fram Strait. In Fram Strait the velocity month–over–month increases from June to December–March from 2.5 to 6.5 cm/s. Overall correlation drift and wind is 0.95 and 0.85 for ice fields and icebergs. The non-wind drift reproduces the cyclonic circulation between Frantz Josef Land and Novaya Zemlya. The wind drift specifies the coefficients and angles of drift evasion from the wind. The coefficient for total drift is 0.14–0.18, fore wind drift 0.10–0.15, and the angles are 15–30° and 10–15° in the Barents Sea. In the Fram Strait the drift and wind directions are stable, the trend considers the modulus and direction. The drift trend has the direction towards the south. It decreases to 5 % of variance in June and increases to 15% from December to March.

An experimental investigation into the behaviour of destructured chalk under cyclic loading

Low-to-medium-density chalk can be destructured to soft putty by high-pressure compression, dynamic impact or large-strain repetitive shearing. These process all occur during pile driving and affect subsequent static and cyclic load-carrying capacities. This paper reports undrained triaxial experiments on destructured chalk, which show distinctly time-dependent behaviour as well as highly non-linear stiffness, well-defined phase transformation and stable ultimate critical states under monotonic loading. The chalk's response to high-level undrained cyclic loading invokes both contractive and dilative phases that lead to pore pressure build-up, leftward effective stress path drift, permanent strain accumulation, cyclic stiffness losses and increasing damping ratios that resemble those of silts. These outcomes are relatively insensitive to consolidation pressures and are distinctly different to those of the parent intact chalk. The maximum number of cycles that can be sustained under given combinations of mean and cyclic stresses are expressed in an interactive stress diagram which also identifies conditions under which cycling has no deleterious effect. Empirical correlations are proposed to predict the number of cycles to failure and mean effective stress drift trends under the most critical cyclic conditions. Specimens that survive long-term cycling present higher post-cyclic stiffnesses and shear strengths than equivalent ‘virgin’ specimens.

Numerical predictions of observed failure modes on non-ductile reinforced concrete frames

This manuscript reports on numerical predictions of documented failure modes on two dynamic experimental datasets involving nonductile reinforced concrete (RC) frames. The numerical models are created using available methodologies in the Open System for Earthquake Engineering Simulation (OpenSEES). Failure mode limits are applied to the components' responses to identify flexural, shear on beam-column joints, pullout, and bond-slip failure modes observed in the experimental studies. The experimental datasets available are used in the assessment of the numerical predictions. The assessment of predictions indicated that the numerical models reproduce well the failure modes, global and local responses of the RC frames on the experimental datasets. The results demonstrate that (i) failure mechanisms involving pullout and bond-slip could dominate the collapse mechanisms on nonductile frames, and (ii) the underestimation of bond deformations on numerical analysis could overestimate section stiffness. The validated modeling methods are used to study the effects of the ground motion characteristics on the predicted failure modes. The results of numerical analysis of a 3-story frame under two sets of near-field and far-field ground motions highlighted the need to include modeling tools that capture bond-slip, pullout, and shear on joints. The formation of bond-slip under near-field motions is highly correlated to the motion's peak ground velocity levels, this correlation is less evident for far-field motions. Peak drift trends resemble the peak ground velocity trends for the near-field and far-field sets.

Research on Information Fusion Technology of MEMS Gyro Array

The measurement accuracy of MEMS gyroscope is relatively low. Starting from the software level, the multi-sensor information fusion technology of MEMS gyroscope array (MGA) is used to reduce the drift of MEMS gyroscope. Firstly, a signal acquisition and processing system for communicating with ADXRS810 gyroscope based on field-programmable gate array (FPGA) is designed. Secondly, the collected drift data of the gyroscope array is preprocessed. long-term drift trend terms are obtained by ensemble empirical mode decomposition (EEMD) and the linear function fitting, and the trend terms are filtered out to obtain a smooth and normal drift signal. Then, the data fusion model based on time series analysis is built for the gyroscope array and the error analysis is performed by Allan variance. Finally, based on the AR (1) model, the moving horizon optimization Kalman filter method is used to filter the drift data of the gyroscope array. The experiment shows that when the time domain length N=3, the bias instability of gyroscope 1, 2, 3 and 4 decreases from 9.716 o/h, 8.5682 o/h, 13.484 o/h and 26.414 o/h to 1.2922 o/h, 0.61147 o/h, 1.4184 o/h and 1.6964 o/h, respectively, and the average noise coefficient decreases by more than 85%. Compared with the ordinary Kalman filter method, the bias instability has been significantly improved.

Low-Cost and Efficient Thermal Calibration Scheme for MEMS Triaxial Accelerometer

In view of the large thermal drift of microelectromechanical system (MEMS) triaxial accelerometer and the high cost of traditional calibration schemes, this article proposes a low-cost and efficient thermal drift calibration scheme combining the parameter-correction method and the proposed least squares method based on the nine-parameter model. In this scheme, first, the parameter-correction method is applied to the data collected under the heating condition to obtain the thermal drift of calibrated parameters with constant error. The least squares method is then used to obtain the parameters at a temperature T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> . Then, the two sets of parameters are combined, and the constant offset error is removed. Finally, higher precision thermal drift curves of the parameters are obtained after smoothing and filtering. One thousand simulations show that the previously proposed parameter-correction method has consistent accuracy and can obtain accurate drift trends of the triaxial accelerometer parameters. The actual triaxial accelerometer thermal drift calibration experiment shows that when the temperature rises by 22 °C, the sensor data converted by the parameters obtained by the proposed scheme can effectively reduce the drift. The drifts of x- and y-axes are reduced from -19.2 and 11.6 mg to -0.7 and -0.6 mg, respectively. The Z-axis drift is reduced from -23.9 to 3.5 mg. This proves the feasibility of the method and scheme proposed in this article.

Space–time variations of sea ice in Bohai Sea in the winter of 2009–2010 simulated with a coupled ocean and ice model

Sea ice variations in the severe winter of 2009–2010 in the Bohai Sea are simulated with a coupled ocean and ice model. The modelled ice coverage shows good agreement with satellite observations. Integrated over three sub-regions [the extended Liaodong Bay (LDB), Bohai Bay, and Laizhou Bay], the temporal variations of ice volume and surface air temperature are well correlated at time scales of 5–15 days and longer than 15 days. In LDB, at time scales of 5–15 days, the maximum ice volume lags the minimum surface air temperature by 42 h on average. In LDB, a significant amount of ice formed in the northern part is advected southward and then melts, and the trajectories of the positions of “ice centroids” further demonstrate the distinct trend of southward ice drift in this area. The impacts of winds are obvious during strong wind events. The results of multiple linear regression suggest that the hourly ice drift variations are mainly due to surface currents with significant tidal signals, and the daily ice drift variations can be mostly attributed to surface winds and secondly to surface ocean currents.

Geochemical Characteristics and Productivity Response of Produced Water from Coalbed Methane Wells in the Yuwang Block, Eastern Yunnan, China

Coalbed methane (CBM) well-produced water contains abundant geochemical information that can guide productivity predictions of CBM wells. The geochemical characteristics and productivity responses of water produced from six CBM wells in the Yuwang block, eastern Yunnan, were analyzed using data of conventional ions, hydrogen and oxygen isotopes, and dissolved inorganic carbon (DIC). The results showed that the produced water type of well L-3 is mainly Na-HCO3, while those from the other five wells are Na-Cl-HCO3. The isotope characteristics of produced water are affected greatly by water-rock interaction. Combined with the enrichment mechanisms of isotopes D and 18O, we found that the water samples exhibit an obvious D drift trend relative to the local meteoric water line. The 13C enrichment of DIC in the water samples suggests that DIC is mainly produced by the dissolution of carbonate minerals in coal seams. The concentration of HCO3-, D drift trend, and enrichment of 13CDIC in produced water are positively correlated with CBM production, which can be verified by wells L-4 and L-6.

Temperature drift modeling and compensation of micro-electro-mechanical system gyroscope based on improved support vector machine algorithms

This article suggested two methods to compensate for the temperature drift of the micro-electro-mechanical system gyroscopes, which are support vector machine method and C-means support vector machine. The output of X axis which was ranged from −40°C to 60°C based on the micro-electro-mechanical system gyroscope is reduced and analyzed in this article. The results showed the correctness of the two methods. The final results indicate that when the temperature is ranged from −40°C to 60°C, the factor of B is reduced from 0.424 [Formula: see text] to 0.02194 [Formula: see text], and when the temperature is ranged from 60°C to −40°C, the factor of B is reduced from 0.1056 [Formula: see text] to 0.0329 [Formula: see text], and the temperature drift trend and noise characteristics are improved clearly.

Velocity-attenuation model from check-shot drift trends in North Sea well data

Seismic attenuation distorts phase and narrows bandwidth in seismic surveys. It is also an exploration attribute, as, for example, gas or overpressure, may create attenuation anomalies. Compensating attenuation in imaging requires accurate models. Detailed attenuation models may be obtained using full-waveform inversion (FWI) or attenuation tomography, but their accuracy benefits from reliable starting models and/or constraints. Seismic attenuation and velocity dispersion are necessarily linked for causal linear wave propagation such that higher frequencies travel faster than lower frequencies in an attenuative medium. In publicly released well data from the Norwegian North Sea, we have observed systematic positive linear trends in check-shot drift when comparing (lower frequency) time-depth curves with (higher frequency) integrated sonic transit times. We observe velocity dispersion consistent with layers having constant seismic attenuation. Adapting a previously published method, and assuming an attenuation-dispersion relationship, we use drift gradients, measured over thick stratigraphic units, to estimate interval P-wave attenuation and tentatively interpret its variation in terms of porosity and fluid mobility. Reflectivity modeling predicts a very low attenuation contribution from peg-leg multiples. We use the attenuation values to develop a simple regional relationship between P-wave velocity and attenuation. Observed low drift gradients in some shallower units lead to an arch-shaped model that predicts low attenuation at both low and high velocities. The attenuation estimates were broadly comparable with published effective attenuation values obtained independently nearby. This general methodology for quickly deriving a regional velocity-attenuation relationship could be used anywhere that coincident velocity models are available at seismic and sonic frequencies. Such relationships can be used for fast derivation (from velocities) of starting attenuation models for FWI or tomography, constraining or linking velocity and attenuation in inversion, deriving models for attenuation compensation in time processing, or deriving background trends in screening for attenuation anomalies in exploration.

Demethylation and derepression of genomic retroelements in the skeletal muscles of aged mice.

Changes in DNA methylation influence the aging process and contribute to aging phenotypes, but few studies have been conducted on DNA methylation changes in conjunction with skeletal muscle aging. We explored the DNA methylation changes in a variety of retroelement families throughout aging (at 2, 20, and 28 months of age) in murine skeletal muscles by methyl‐binding domain sequencing (MBD‐seq). The two following contrasting patterns were observed among the members of each repeat family in superaged mice: (a) hypermethylation in weakly methylated retroelement copies and (b) hypomethylation in copies with relatively stronger methylation levels, representing a pattern of “regression toward the mean” within a single retroelement family. Interestingly, these patterns depended on the sizes of the copies. While the majority of the elements showed a slight increase in methylation, the larger copies (>5 kb) displayed evident demethylation. All these changes were not observed in T cells. RNA sequencing revealed a global derepression of retroelements during the late phase of aging (between 20 and 28 months of age), which temporally coincided with retroelement demethylation. Following this methylation drift trend of “regression toward the mean,” aging tended to progressively lose the preexisting methylation differences and local patterns in the genomic regions that had been elaborately established during the early period of development.

Levitation Height Drifts of HTS Bulks under a Long-Term External Disturbance

High-temperature superconducting (HTS) maglev owns the capability of passive stabilization and has the potential to operate at a high speed with low energy consumption. However, the excitation caused by the irregular surface and inhomogeneous magnetic field of the permanent magnet guideway (PMG) will result in vibration between the superconductors and PMG, which could lead to some stability problems such as drift. To study the reliability of HTS maglev systems under a long-term disturbance, a tailored experimental device composed of a vibration table, a fixture, and HTS maglev model was employed. The effects of field-cooling height (FCH), external excitation frequencies, and amplitudes on the levitation height drift were investigated. It is found that under the same operating conditions, large excitation amplitude, high frequency, and low FCH would lead to a greater levitation height drift. There are three kinds of drift trends, i.e., downward, upward, or downward at first and then upward, and the phenomenon of drifting upward is more likely to occur under small excitation amplitude, high frequency, and low FCH conditions. Meanwhile, two simulation models employing the flux flow model and the flux flow and creep model were applied respectively. The simulation results show that the flux flow and creep model are more consistent with the experimental phenomena and the flux flow has a greater influence on the drift in the initial time period, while the flux creep has a slighter impact on the drift for a long time. These researches reveal the levitation height drift rules of the HTS maglev system and introduce proper simulation model for levitation height drift so that this work provides a reference for the design and safe operation of HTS maglev vehicles.