Actual Morphology Research Articles

Hydrogeological insights from groundwater ice formation on the Niagara Escarpment, Hamilton, Canada

Groundwater discharges from Silurian bedrock exposures at the Niagara Escarpment have been documented using photography. It is demonstrated that patterns of groundwater discharges are best discernible from ice formation during sub-zero winter conditions. The photographs indicate that discharges at natural exposures tend to follow hydrostratigraphic boundaries, with point seeps indicating channelized preferential flow. At anthropogenic exposures, the groundwater discharges appear more closely related to the actual exposure morphology with vertical fracturing causing vertical flow and bypass of aquitards, as well as aquifers with groundwater discharge occurring at local topographical lows. The associated seeps at anthropogenic exposures may approximate planar preferential horizontal flow horizons if competent beds are encountered.

A new biomechanical model of the mammal jaw based on load path analysis.

The primary function of the tetrapod jaw is to transmit jaw muscle forces to bite points. The routes of force transfer in the jaw have never been studied but can be quantified using load paths - the shortest, stiffest routes from regions of force application to support constraints. Here, we use load path analysis to map force transfer from muscle attachments to bite point and jaw joint, and to evaluate how different configurations of trabecular and cortical bone affect load paths. We created three models of the mandible of the Virginia opossum, Didelphis virginiana, each with a cortical bone shell, but with different material properties for the internal spaces: (1) a cortical-trabecular model, in which the interior space is modeled with bulk properties of trabecular bone; (2) a cortical-hollow model, in which trabeculae and mandibular canal are modeled as hollow; and (3) a solid-cortical model, in which the interior is modeled as cortical bone. The models were compared with published in vivo bite force and bone strain data, and the load paths calculated for each model. The trabecular model, which is preferred because it most closely approximates the actual morphology, was best validated by in vivo data. In all three models, the load path was confined to cortical bone, although its route within the cortex varied depending on the material properties of the inner model. Our analysis shows that most of the force is transferred through the cortical, rather than trabecular bone, and highlights the potential of load path analysis for understanding form-function relationships in the skeleton.

Brain tumor image segmentation method using hybrid attention module and improved mask RCNN

To meet the needs of automated medical analysis of brain tumor magnetic resonance imaging, this study introduces an enhanced instance segmentation method built upon mask region-based convolutional neural network. By incorporating squeeze-and-excitation networks, a channel attention mechanism, and concatenated attention neural network, a spatial attention mechanism, the model can more adeptly focus on the critical regions and finer details of brain tumors. Residual network-50 combined attention module and feature pyramid network as the backbone network to effectively capture multi-scale characteristics of brain tumors. At the same time, the region proposal network and region of interest align technology were used to ensure that the segmentation area matched the actual tumor morphology. The originality of the research lies in the deep residual network that combines attention mechanism with feature pyramid network to replace the backbone based on mask region convolutional neural network, achieving an improvement in the efficiency of brain tumor feature extraction. After a series of experiments, the precision of the model is 90.72%, which is 0.76% higher than that of the original model. Recall was 91.68%, an increase of 0.95%; Mean Intersection over Union was 94.56%, an increase of 1.39%. This method achieves precise segmentation of brain tumor magnetic resonance imaging, and doctors can easily and accurately locate the tumor area through the segmentation results, thereby quickly measuring the diameter, area, and other information of the tumor, providing doctors with more comprehensive diagnostic information.

Acoustic emission-based weld crack leakage monitoring via FGI and MCCF-CondenseNet convolutional neural network

Online monitoring of weld crack leakage in pressure pipelines of nuclear power ship based on acoustic emission (AE) technology is of great significance for maintaining the safe and stable operation of the system. However, most of the current leakage studies are conducted through artificially designed pipeline hole types, which deviate from the actual crack morphology and are weakly online, with low identification accuracy and slow monitoring speed. Therefore, a convolutional network of FGI and multi-scale channel information cross fusion based on AE technology is proposed in this paper. First, the FBank feature of the AE signal of pipeline weld leakage are extracted. On this basis, the Gini Index (GI) preference feature is used to filter the useless information in the FBank feature. Then, a multi-scale channel information cross fusion module is designed to improve the feature learning ability of the network through the interaction and fusion of different channel information. Finally, the superiority of the proposed FGI feature extraction method and the effectiveness of the proposed multi-scale channel information cross fusion CondenseNet (MCCF-CondenseNet) convolutional neural network are verified by the pipeline leakage AE monitoring experiments under three crack morphologies. The results show that the identification accuracy of the proposed method is as high as 96.42 %, and the identification speed is significantly faster than other state-of-the-art approaches under the premise of ensuring the identification accuracy. This work provides a new method for the online leakage monitoring of nuclear power pressure pipelines, and has important supporting significance for the online leakage monitoring of other large and complex equipment.

VIRTUAL IMPINGEMENT TESTS IN 113 PATIENTS UNDERGOING TOTAL HIP ARTHROPLASTY

Hip precautions following total hip arthroplasty (THA) limits flexion, adduction and internal rotation, yet these precautions cause unnecessary psychological stress. This study aims to assess bony and implant impingement using virtual models from actual patient's bony morphology and spinopelvic parameters to deduce whether hip precautions are necessary with precise implant positioning in the Asian population.Individualized sitting and standing sacral slope data of robotic THAs performed at two tertiary referral centers in Hong Kong was inputted into the simulation system based on patients’ pre-operative sitting and standing lumbar spine X-rays. Three-dimensional dynamic models were reconstructed using the Stryker Mako THA 4.0 software to assess bony and implant impingement both anteriorly and posteriorly, with default cup placement at 40° inclination and 20° anteversion. Femoral anteversion followed individual patient's native version. A 36mm hip ball was chosen for all cups equal or above 48mm and 32mm for those below. Anterior impingement was assessed by hip flexion and posterior impingement was assessed by hip extension.113 patients were included. At neutral rotation and adduction, no patients had anterior implant impingement at hip flexion of 100°. 1.7% had impingement at 110°, 3.5% had impingement at 120°, 9.7% had impingement at 130°. With 20° of internal rotation and adduction, 0.8% had anterior implant impingement at hip flexion of 90°, 7.1% had impingement at 100° and 18.5% had impingement at 110°. With the hip externally rotated by 20°, 0.8% of patients had posterior implant impingement, and 8.8% bony impingement at 0° extension.With enabling technology allowing accurate component positioning, hip precautions without limiting forward flexion in neutral position is safe given precise implant positioning and adequate osteophyte removal. Patients should only be cautioned about combined internal rotation, adduction with flexion.

Assessment of Trees’ Structural Defects via Hybrid Deep Learning Methods Used in Unmanned Aerial Vehicle (UAV) Observations

Trees’ structural defects are responsible for the reduction in forest product quality and the accident of tree collapse under extreme environmental conditions. Although the manual view inspection for assessing tree health condition is reliable, it is inefficient in discriminating, locating, and quantifying the defects with various features (i.e., crack and hole). There is a general need for investigation of efficient ways to assess these defects to enhance the sustainability of trees. In this study, the deep learning algorithms of lightweight You Only Look Once (YOLO) and encoder-decoder network named DeepLabv3+ are combined in unmanned aerial vehicle (UAV) observations to evaluate trees’ structural defects. Experimentally, we found that the state-of-the-art detector YOLOv7-tiny offers real-time (i.e., 50–60 fps) and long-range sensing (i.e., 5 m) of tree defects but has limited capacity to acquire the patterns of defects at the millimeter scale. To address this limitation, we further utilized DeepLabv3+ cascaded with different network architectures of ResNet18, ResNet50, Xception, and MobileNetv2 to obtain the actual morphology of defects through close-range and pixel-wise image semantic segmentation. Moreover, the proposed hybrid scheme YOLOv7-tiny_DeepLabv3+_UAV assesses tree’s defect size with an averaged accuracy of 92.62% (±6%).

Flow physics of a subcritical carbon dioxide jet in a multiphase ejector

Existing literature on ejectors, different researchers utilized different turbulence models by their choice, neither analyzing the physics of turbulence nor providing any sufficient optical diagnostics of the flow field. In this article, the physics captured by the Unsteady Reynolds Averaged Navier–Stokes (URANS) and Large Eddy Simulation (LES) are compared based on well-posed boundary conditions obtained experimentally from a carbon dioxide (CO2) vapor compression cycle with an error ≤2.5%. The experimental results utilized for this study are at Reynold’s number (Re) 1.2e5 at the high-pressure inlet (motive flow) maintaining CO2 in subcritical state. The low-pressure inlet (suction flow) is maintained at Re = 9.8e4 with CO2 in vapor state, providing a pressure lift ratio of 1.2 at the diffuser outlet. Comparison of flow topologies with different URANS models reveals that only standard, Shear Stress Transport (SST) k−ω, and Reynold’s Stress Model-Shear Stress Gradient (RSM-SSG) are the suitable URANS models capturing a linearly increasing anisotropy tensor component with increasing strain in the flow. LES also predicted the similar physics. However, standard k−ω overpredicted the suction pressure beyond the acceptable uncertainty limits, which made it inapplicable. For the first time, a spatio-temporal representation of the flow topology with LES revealed the actual jet morphology of a CO2 ejector. Specifically, finger-like structures are key features to entrain more surrounding warm fluid into the colder dense core fluid at the cost of destabilizing and breaking up the jet by stretching the streamwise vortices and obstructing the increase in pressure-lift ratio.

Chatter and Surface Waviness Analysis in Oerlikon Face Hobbing of Spiral Bevel Gears

A vectorized analytical model for the cutting dynamics in the spiral bevel gear face hobbing process has been developed, which is based on machine tool kinematics and vibration vectorization. The structural modal parameters of the cutter head spindle system are obtained through experimental modal analysis with hammer impact testing. The analytical model is utilized to simulate the generation of simulated vibration acceleration signals during spiral bevel gear hobbing. A wavelet threshold denoising method is applied to process the simulated vibration signals of the spiral bevel gear face hobbing with added white noise. Signal processing methods, including short-time Fourier transform are employed for time-domain analysis, frequency-domain analysis, and time–frequency-domain analysis of measured signals and simulated signals, thereby extracting the corresponding statistical features. In addition to the results of the experimental modal analysis, the causes of chatter in spiral bevel gear hobbing are discussed in detail, revealing that the main factor is cutter head vibration in the Y direction of the Hunan ZDCY CNC EQUIPMENT YKA2260 machine tool used in this research. The error in the time-domain characteristic parameters between simulated signals and measured vibration acceleration signals is within 15%, with a difference of 3.5% in spectral peak values. The predicted tooth surface morphology from simulation matches the actual morphology on the workpiece, comprehensively validating the reliability of the cutting dynamics model for the spiral bevel gear face hobbing process. Another conclusion drawn from numerical simulation experiments is that the amount of tooth surface waviness of the spiral bevel gears is the ratio of tool chatter frequency to cutting fundamental frequency.

Mathematical Modeling of Transient Submerged Entry Nozzle Clogging and Its Effect on Flow Field, Bubble Distribution and Interface Fluctuation in Slab Continuous Casting Mold

Submerged entry nozzle (SEN) clogging will affect the production efficiency and product quality in the continuous casting process. In this work, the transient SEN clogging model is developed by coupling the porous media model defined by the user-defined function (UDF) and the discrete phase model (DPM). The effects of the transient SEN clogging process on the flow field, the distribution of argon gas bubbles and the fluctuation of the interface between steel and slag in the concave bottom SEN in the continuous casting slab mold with a cross-section of 1500 mm × 230 mm are studied by coupling transient SEN clogging model, DPM and volume of fluid (VOF) model. The results show that the actual morphology and thicknesses of SEN clogging are in good agreement with the numerical simulation results. The measurement result of the surface velocity is consistent with the numerical simulation result. With increasing the simulation time, the degree of SEN clogging increases. The flow velocities of molten steel flowing from the outlet of the side hole increase, because the flow space is occupied with the clogging inclusions, which leads to the increased number of argon gas bubbles near the narrow wall. The steel–slag interface fluctuation near the narrow walls also increases, resulting in the increased risk of slag entrapment.

Parametric Modeling and Numerical Simulation of a Three-Dimensional Random Aggregate Model of Lime–Sand Piles Based on Python–Abaqus

A lime–sand pile is a three-phase particle composite material composed of a lime matrix, sand, and a loess aggregate at the meso level. Establishing a random aggregate model that can reflect the actual aggregate gradation, content, and morphology is the premise of numerical simulations of the meso-mechanics of lime–sand piles. In this paper, the secondary development of Abaqus 2022 is realized by writing Python 3.12 scripts, and a parameterized three-phase mixed lime–sand pile random meso-spherical aggregate model is obtained. A meso-modeling idea of lime–sand piles is creatively proposed, the integrated-generation algorithm of a spherical aggregate of different materials is written, and the material’s properties and mesh generation are given by the algorithm. Finally, a numerical simulation of temperature–expansion statics is carried out using an established mesoscopic model. Under different mixing ratios, the expansion force increases with an increase in the lime proportion. The increase in the expansion force is approximately 45% of that without an increased lime proportion. The simulated expansion forces are 8.81 kN, 12.61 kN, and 18.89 kN, respectively, which are similar to the experimental results for laboratory specimens, and the relative error is less than 3%. In the case of different height ratios, with increases in height, the change in the expansion force is very small, and the relative error between the simulated value and the experimental value is less than 2%, which further verifies the reliability of the mesoscopic random model of lime–sand piles. The model can be used to guide the practical application of engineering.

Distinctive hydrodynamic properties and ecological responses of multi-thread rivers under different degrees of multiplicity in the Upper Yellow River

Alluvial rivers that exhibit multi-thread patterns are common in nature and can be the dominant channel morphology in large rivers. However, their ecological properties in response to diverse and dynamic channel morphology has gained limited attention and remained poorly understood. In this study, we adopted an eco-hydraulic model by integrating a hydrodynamic, a sediment-transport, and a habitat-suitability model to assess habitat quality for fish species (Schizopygopsis pylzovi and Platypharodon extremus) in three anabranching reaches with each exhibiting a distinct anabranching morphology in the Upper Yellow River, eastern Qinghai-Tibet Plateau. Based on the hydrologic data and actual channel morphology, we modeled the hydrodynamic and sediment-transport conditions for a period spanning ten years, and simulated habitat conditions under a potentially changing environment with different flow magnitudes and frequencies. The results indicated that the average flow velocity in the low and mid-order anabranching reaches is higher than that in the high-order, complex anabranching reaches. Meanwhile, the bedload transport rate was higher in the high and mid-order anabranching reaches than that in the low-order anabranching reach, demonstrating a greater transport efficiency of multi-thread systems with a greater multiplicity. Consequently, the habitat suitability shows a deteriorating trend over the ten-year modeling period and Schizopygopsis pylzovi shows better habitat status than Platypharodon extremus. The flow magnitudes and frequency also have a significant impact on the distribution of high habitat suitability index among the different river patterns in Upper Yellow River. This study can provide valuable information to optimize ecological outcomes and provide valuable insights for future dam operation strategies and consideration efforts aimed at preserving and restoring riverine ecosystems.

Local–overall buckling behavior of corroded intermediate compression-bending H-section steel columns

The primary aim of this paper is to assess the impact of corrosion damage on intermediate H-section steel columns subjected to combined compression and bending about the strong axis. The study conducted a comprehensive investigation into the corrosion-induced transition in the buckling behavior of steel columns through experimental and numerical analyses. Six H-section Q355 steel intermediate columns were designed, with five undergoing an artificial spray-accelerated corrosion process. The three-dimensional scanning technology was employed to quantify the general corrosion and corrosion pits. Eccentric compression tests were carried out on intermediate H-section steel columns to investigate the effect of the different corrosion levels on the failure mode and load-displacement curves, as well as to determine local buckling load based on the load-strain curves. The test results showed that the corrosion characteristic parameters of each cross-section of the steel column exhibited irregularity and variation in all locations, reflecting the heterogeneity of corrosion. The density of corrosion pits exhibited a decreasing trend with increased corrosion duration. Corrosion remarkably reduced both the ultimate carrying capacity and local buckling capacity, with the most severely corroded specimen exhibiting an average cross-sectional area loss rate of 37 %, resulting in a 43 % and 51 % reduction in ultimate load and buckling load compared to the uncorroded specimen. Furthermore, the corrosion features substantially influenced the failure mode, resulting in a transition from overall buckling to local buckling or local-global interaction buckling. A numerical methodology was developed to incorporate the actual surface morphology of corrosion, and the reliability of the modeling method was validated through comparison with experimental results, further revealing the failure mechanism of corroded intermediate H-section steel columns under compression and bending about the strong axis.

Pore structure characterization and effective thermal conductivity modeling of fibrous building thermal insulation materials based on X-ray tomography

The existing structural characterization methods of building materials as well as thermal conductivity calculation models can not be directly applied when considering fibrous building thermal insulation materials with intricate skeletons. In this study, rock wool is considered the research object, and the X-ray tomography method is used to characterize the pore structure and extract structural parameters. Based on the actual pore morphology of the material, the pores in the representative elementary volume (REV) are reasonably assumed to be cubic. Additionally, considering the contact thermal resistance of fibers and the randomness of pore distribution, the curved pattern of heat conduction pathway with the ever-changing diameter is reasonably simplified into a series-parallel form of the curved heat chain with the same diameter. On this basis, the fractal models of effective thermal conductivity are established in horizontal and vertical directions. Finally, a modified formula for the effective thermal conductivity calculation of fiber thermal insulation materials is proposed, taking into account the influence of fiber orientation on the material thermal conductivity. It was shown that the relative deviation between the calculated correction value and the experimental value of the effective thermal conductivity is all less than 16.13%.

Virtual simulation of weld morphology for V-groove multi-layer welding

In order to study the virtual simulation of weld morphology for V-groove multi-layer welding, the prediction of characteristic parameters for weld morphology was realized by constructing the neural network models between the characteristic parameters and process parameters of different layers. At the same time, the virtual models of different layers were established according to the characteristic parameters of weld morphology and the structure parameters of V-groove. Combined with the prediction model and the virtual model, the process parameters were associated with the weld morphology, and the virtual simulation of weld morphology was realized. In the process of establishing the virtual model, first of all, the virtual model of root weld is established. Then, the virtual model of filling layer is established based on the root layer, and the virtual model of weaving layer is established based on the filling layer. Finally, validation experiments were carried out to verify the accuracy of the model. Verification results show that the prediction model can effectively predict the characteristic parameters of each layer, and the average relative errors of melting depth and width were less than 8%. The virtual simulation morphology has a high consistency with the actual morphology, and the average relative error of cross section area was less than 10%.

Engineering hydrophobicity and high-index planes of gold nanostructures for highly selective electrochemical CO2 reduction to CO and efficient CO2 capture

In current study, we demonstrate a strategy for improving the catalytic performance of gold (Au) for carbon dioxide reduction reaction (CO2RR), specifically enhancing selectivity for CO over hydrogen evolution reaction (HER) and increasing low-level CO2 capture efficiency. This involved controlling nanostructures without any further modification. Au nanostructures having four different morphologies (i.e., degree of roughness) were fabricated via electrodeposition at varied deposition potential, resulting in different intrinsic surface hydrophobicity and exposure of high-index planes depending on the actual morphology. The roughest Au, with its combination of the most hydrophobic feature and abundant high-index planes, generated greater partial current density (jCO) and faradaic efficiency for CO (FECO) than the other Au deposits within a tested potential region: The roughest Au showed 6-fold higher FECO (95.8 %) and 327-fold higher jCO (normalized to electrode geometric surface area) at −0.75 VRHE compared to the smoothest Au. Moreover, the roughest Au exhibited excellent CO2 capture ability even at low CO2 concentration, confirmed with scanning electrochemical microscopy. These improvement at hierarchical Au for CO2RR could be ascribed to two factors. Firstly, the morphology-driven hydrophobicity provides an optimal gas–liquid-solid triple-phase interfaces, increasing the local CO2 concentration near the Au catalyst surface due to its superb CO2 capture ability. Secondly, the abundant high-index planes serve as stable active sites for CO2RR, expediting the reaction rates. Remarkably, Au with the highest hydrophobicity and enriched high-index planes, even without any chemical modification, showed excellent CO2RR catalytic performance comparable to or even better than the other previously reported Au-based catalysts.

Synthesis of C3-symmetric star shaped amphiphiles for drug delivery applications.

C 3-symmetric star-shaped aromatic compounds are known to possess unique characteristics which facilitate their industrial and biomedical applications. Herein, we report the design, synthesis, self-assembly and drug/dye delivery capabilities of C3-symmetric, hexa-substituted benzene-based amphiphiles. The synthesis of the hexa-substituted C3-symmetric core involves C-acetylation of phloroglucinol to yield the corresponding tri-acetyl derivative. This was further subjected to O-propargylation, followed by the carbonyl reduction of acetyl groups to yield the central core. Various hydrophilic (mPEG) and lipophilic units were then incorporated into this core via click and esterification reactions, respectively, to produce a new type of star shaped amphiphiles. So the obtained amphiphilic architectures have a tendency to aggregate in an aqueous medium forming nanosized assemblies with an inner hydrophobic core, allowing the substituents to control the tension-active properties. The critical aggregation concentration of the amphiphiles was evaluated by fluorescence measurement using the dye Nile red as a fluorescent probe. The hydrodynamic diameter of self-assembled aggregates in aqueous solution was studied by dynamic light scattering, while the actual size and morphology were determined by cryo-transmission electron microscopy (cryo-TEM) analysis. The physicochemical properties of the amphiphiles suggested their suitability for exploring their drug delivery applications. In this endeavor, the amphiphiles were utilized for the encapsulation of model hydrophobic entities and studying their subsequent release from their hydrophobic core in a controlled manner. The transport potential of the synthesised amphiphiles was explored for transdermal drug delivery. Furthermore, cytotoxicity studies were conducted using MCF7 and HeLa cells, which indicated that the nanocarriers had no toxic effect on the cells.

Pycnometric-Additive Determining of the Degree of Coating of High-Strength Synthetic Diamond Grinding Powders using the Actual 3D Morphology of their Grains

The methodological components of direct and indirect analytical determining of the degree of coating of synthetic diamond grinding powders are analyzed. It has been established that the weight method most used in practice for determining this technological property of grinding powder is not universal for different methods of applying the coating. More universal in this regard, as the review of publications showed, is the well-known indirect-analytical method based on the pycnometric-additive approach. An improved variant of this method is proposed, aimed at application to high-strength synthetic diamond grinding powders. The method takes into account the peculiarities of the 3D morphology of the grains of such powders. Using the example of grinding powder AC300 500/400, the grains of which were coated with a solution of a mixture of boron oxide, sodium silicate, and titanium carbide, the advantages of using the proposed method are illustrated. The results of a comparison of determining the degree of coating by a known method and its improved variant are presented.

An improved mixed lubrication model for revealing the mechanism of high speed and frictional heat on sealing performance

This study presents a numerical model that incorporates the actual micro morphology of sealing lip and rotating shaft to elucidate the sealing behavior in high-speed rotating lip seals operating under mixed lubrication conditions. The model explores the intricate interplay between hydrodynamics at the interface, macro-scale solid mechanics, micro-contact mechanics of surfaces, and the heat generated by friction at the lip. Based on this model, this paper quantitatively predicts the leakage rates and friction torque under various operating conditions and lip seal structural parameters, shedding light on the influence of high-speed frictional heat on sealing performance.

Human body numerical simulation: An accurate model for a thigh subjected to a cold treatment

This article presents the development of a digital twin model of a thigh portion subjected to various thermal treatments. Two scenarios are investigated: cold water immersion (CWI) and whole body cryotherapy (WBC), for which the comparison of numerical results with experimental measurements validates the consistency of the developed model. The use of real geometry on a first subject demonstrates the high heterogeneity of the temperature field and the need for accurate geometry. A second subject with thicker adipose tissue highlights the impact of the subject’s actual morphology on the validity of the treatment and the necessity to work with real geometry in order to optimize cold modalities and develop personalized treatments.

Effect of pad surface morphology on the surface shape of the lapped workpiece

Double-sided lapping is currently the mainstream manufacturing method for obtaining plane-parallel optical workpieces with high surface shape accuracy, and the fixed abrasive lapping pad is the main machining tool. However, the effect of pad surface morphology on the workpiece surface shape has rarely been studied, and its formation mechanism has not yet been revealed. In this paper, based on probabilistic statistics and contact mechanics, an analytical model that takes into account the pad surface morphology for predicting the workpiece surface shape evolution is developed. Notably, this model considers the cross-scale relationship between the formation of lapped surface shape and the scratching process of a single abrasive grain in material removal for the first time. Furthermore, the real-time dynamical contact relationship between the workpieces and the measured actual pad surface morphology is also considered. The surface shape and peak-to-valley value of the workpiece under different parameters were simulated and analyzed, and the influence mechanism of the local profile and macro shape of the lapping pad on the lapped workpiece surface shape are clarified. Moreover, the double-sided lapping trial experiments were performed to validate the theoretical model, and the experimental results demonstrated good agreement with the simulation results. The maximum error of the surface shape evolution prediction model is less than 14.6 %. This result verifies the correctness and validity of the established model. This work not only provides new ideas for controlling the workpiece surface but also forms the theoretical basis for understanding the double-sided lapping process.