Practical Engineering Applications Research Articles

An engineering applicable method for multiaxial fatigue under proportional and non-proportional loads based on the octahedral plane projection

Present multiaxial fatigue models have achieved satisfactory performance in predicting multiaxial fatigue life of different loading paths; however, many of them require critical plane calculations and additional material constants. In this study, a novel multiaxial fatigue life prediction model based on octahedral shear strain energy is proposed. In the proposed model, the maximum octahedral shear strain energy serves as the damage parameter without requiring any additional material parameters. All material constants in this model can be derived from material strength constants and uniaxial fatigue constants, greatly simplifying the life prediction process. Moreover, based on the actual physical phenomenon of non-proportional additional hardening, the multiaxial non-proportional correction factor is incorporated into the plastic stage of the life equation, aligning more closely with fundamental principles in physics. Then, by utilizing the experimental data from the literature for four materials, a comparison is made between the prediction results of the novel model and those of four commonly employed models. The findings demonstrate that the new model exhibits superior simplicity and accuracy. Subsequently, through life prediction outcomes for DZ411 material across various paths, the stability and precision of the octahedral energy model are substantiated, rendering it suitable for practical engineering applications.

Research of dust removal performance and power output characteristics on photovoltaic panels by longitudinal high-speed airflow

Photovoltaic (PV) panels' photoelectric conversion efficiency will decrease as dust deposition on their surface. An approach to dust removal on the PV panel's surface by longitudinal high-speed airflow was investigated to increase the output power. In this paper, commercial CFD software was used to numerically simulate the characteristics of dust removal by longitudinal high-speed airflow. The PV panels' output characteristic model under the action of dust removal by high-speed airflow is established by Simulink software, and the influence of high-speed airflow on the output characteristic is studied. Firstly, the dust removal mechanism of the PV panel under high-speed airflow is studied. Secondly, the impact of different tilt angles of the PV panel, dust particle size, airflow velocity, and blowing time on the dust removal effect of the PV panel surface were studied. The optimal airflow velocity and blowing time were obtained according to the airflow velocity and blowing time and their influence on the dust removal rate. Finally, the effect of high-speed airflow dust removal on PV power generation's efficiency and output characteristics is studied. The findings demonstrate that as the tilt angle increases, so does the dust removal rate increases continuously. In addition, the rate at which dust is removed increases with airflow velocity and blowing time. When the tilt angle is 30°, the best airflow velocity of dust removal is 5 m/s, and the best blowing time is 8 s. When the tilt angle is 45°, the best airflow velocity of dust removal is 10 m/s, and the best blowing time is 5 s. With the increase in airflow velocity and blowing time, the output power of PV panels continues to increase. When the airflow velocity is 10 m/s, and the blowing time is 5 s, 7.5 s, 12.5 s, and 15 s, the maximum output power after dust removal is increased by 15.44 %, 23.05 %, 23.38 %, and 23.39 %. This paper's research results can guide the design of the practical engineering application of longitudinal blowing high-speed airflow in the dust removal of PV panels.

Research on Fatigue Performance of Fast-Melting SBS/Epoxy Resin Composite-Modified Asphalt

A high-performance composite modifier ER-SBS-T was prepared through the mixing of epoxy resin with a fast-melting styrene–butadiene–styrene modifier (SBS-T) to enhance material properties. This study evaluated the fatigue characteristics of ER-SBS-T-modified asphalt using a linear amplitude sweep test, and 70# base asphalt, SBS-modified asphalt, and SBS-T-modified asphalt were used as control groups. The fatigue life of ER-SBS-T-modified asphalt was determined according to viscoelastic continuous damage (VECD) theory. The findings indicated that as the ER-SBS-T modifier content increased, both the maximum value and the cumulative damage limit value increased, while the rate of change of decreased. At strain levels of 2.5% and 1%, the fatigue life of the modified asphalt improved with increasing ER-SBS-T content. However, at a strain level of 5%, the modified asphalt exhibited no significant trend in fatigue life across different ER-SBS-T contents. ER-SBS-T-modified asphalt with a modifier content of >10% demonstrated favorable fatigue performance suitable for practical engineering applications.

Research on Advanced Prediction of Major Equipment Fatigue Load Based on Deep Learning

Abstract The fatigue life of complex service structures is predicted in real-time according to dynamic random loads. Real-time monitoring of stress/strain in structure key parts is important for practical engineering. Based on the deep learning theory, this paper proposes a long and short-term memory convolutional neural network (CNN- LSTM) prediction model with attention mechanism by using the actual workload data set of key components in major equipment. Firstly, convolutional neural networks (CNN) is used to extract the high-dimensional abstract representation from the preprocessed data, and attention mechanism is added to give each channel different attention scores. Then, long and short-term memory (LSTM) is used to process the time series data and output the final prediction results. In this study, data points in the future are predicted, and the final predicted results are root mean square error (RMSE) of 33.2626 and mean absolute percentage error (MAPE) of 15.3768, which can well fit the future load change trend. At the same time, the multi-condition identification module is added to the code, which can better adapt to the changing load of mechanical equipment in the actual service process. Finally, this paper also designed an ablation experiment, which proved the effectiveness of the overall structure of the prediction model designed in this study and the necessity of the three parts of CNN, ECA-Net and LSTM. It provides theoretical support and practical engineering application for real-time monitoring and predicting the fatigue life of important equipment.

A numerical study on a winglet floating breakwater: Enhancing wave dissipation performance

Box-type floating breakwaters (FBs), widely used for marine protection, face challenges in their wave dissipation capabilities. Although the effectiveness of the winglet-type floating breakwater in improving wave dissipation has been recognized, the specific mechanisms involved are not fully understood. This research presents an innovative winglet breakwater design, featuring three unique winglet configurations: 4-wings, Down-wings, and Up-wings. The study examines its performance against both regular and irregular waves using the Smooth Particle Hydrodynamics (SPH) method, taking into account factors such as the wave period, FB immersion depth, and FB relative density. Numerical simulations indicate a marked enhancement in wave dissipation for the FB equipped with four winglets compared to a baseline model without winglets. The Response Amplitude Operator (RAO) amplitude for the winglet-equipped FB is notably lower, approximately half that observed in the baseline scenario. Notably, the winglet FB's performance in irregular waves outperforms that in regular wave conditions. The insights gained from the design of these winglets provide significant contributions to practical engineering applications.

Breakdown of PFOA in a hydrodynamic cavitation-activated persulfate system: Comparative roles of sulfate and hydroxyl radicals in degradation process and mechanistic insights

Perfluorooctanoic acid (PFOA) remains a persistent organic pollutant within aquatic ecosystems. Activated persulfate (PS) technology has been widely used because it can effectively destroy the stable structure of PFOA. However, this technology still has some restrictive problems, such as the large amount of PS required for the reaction and the high SO42- concentration in the wastewater after the reaction. In this study, we used the advantages of hydrodynamic cavitation to activate PS, such as promoting mass transfer and oxidant utilization. After 3 hours of treatment, the HC/PS system showed outstanding performance in that 93.6% of PFOA was degraded, and 31.09% of PFOA was defluorinated under optimal conditions with smaller PS dosage and lesser SO42- generation. The different inhibitory effects of coexisting substances (Cl-, CO32-, F-, NO3-, SO42-, HA) on the system were emphasized. The contribution rates of sulfate radicals (SO4•-, 84.4%) and hydroxyl radicals (·OH, 10.9%), which are the main active substances in the HC/PS system, were calculated during the degradation of PFOA. The potential degradation pathways of PFOA were proposed based on the intermediates identified through LC-MS/MS. PFOA gradually lost CF2 units, forming shorter-chain intermediates (PFHpA, PFHxA, PFPeA, PFBA) and F-, ultimately converting to H2O and CO2. Above all, this study provides valuable insights into the future wastewater treatment process for PFOA pollution and has important guiding significance for practical engineering applications.

A Simplified Theoretical Method for Estimating the Effect of Capsule Grouting Expansion Technology on Controlling Pile Deformation

Deep excavation and shield tunneling processes often induce significant deformation in adjacent existing pile foundations, posing risks to the safety of superstructures. To address this issue, capsule grouting expansion technology has emerged as an efficient and economical technology to actively control pile deformation during such construction activities. This technology has been applied in some engineering projects aimed at safeguarding nearby buildings or facilities. However, theoretical research on capsule grouting expansion technology is limited and lags behind its practical engineering application. This paper proposed a simplified theoretical approach for estimating the effect of capsule grouting expansion technology on the deformation of neighboring pile foundations. Initially, virtual image technology was employed to obtain an analytical solution for the lateral displacement of soil resulting from the expansion of a cylindrical cavity with infinite height. The pile was considered as an Euler–Bernoulli beam on a Winkler foundation, allowing for the calculation of the loading response of the existing pile foundation. Utilizing the two-stage method, the theoretical analytical method of the lateral deformation of the pile shaft caused by capsule expansion was obtained. The reliability of the proposed theoretical method was verified by comparing the measured and calculated results. Further investigation into the controlling effect of the capsule grouting expansion technology on the deformation of the pile foundation was conducted through parametric analyses. These analyses encompass capsule radius, the distance between the capsule and pile foundation, the depth of the capsule, the length of the capsule, and the pile base constraints.

Research and Application of Two-Dimensional Time-Delayed Tri-Stable Stochastic Resonance System for Bearing Fault Detection

The time-delayed feedback term can improve the output of a system, while the two-dimensional stochastic resonance (SR) system has a stronger signal amplification capability. To improve the output signal-to-noise ratio (SNR) of the system, this paper proposes a two-dimensional time-delayed tri-stable stochastic resonance system (TDTDTSR) based on the advantages of the above two systems. First, the steady-state probability density function (SPD), the mean first-pass time (MFPT), and the output SNR are derived under adiabatic approximation theory, and the effects of different system parameters on them are investigated. Next, TDTDTSR and the classical two-dimensional tri-stable stochastic resonance system (CTDTSR) system are simulated numerically. The results show that the mean signal-to-noise gain (MSNRG) of TDTDTSR system is higher than that of the CTDTSR system. Finally, the system parameters are optimized using a genetic algorithm, and the application of TDTDTSR to bearing fault detection is compared with CTDTSR and the novel piecewise symmetric two-dimensional tri-stable stochastic resonance (NPSTDTSR) systems. The experimental results demonstrate that TDTDTSR system has better performance, providing valuable theoretical support and practical engineering applications for the system in subsequent analyses.

Analysis of the dynamic response for Kirchhoff plates by the element-free Galerkin method

Dynamic response analysis involves examining structural behavior under dynamic loading conditions. Transient dynamic analysis emerges as a method employed to assess the responses of deformable bodies. Due to the depth analysis of transient responses for thin plates, the associated error analysis work becomes particularly important. In this work, we conduct stability and convergence analysis of the element-free Galerkin (EFG) method for the dynamic response of Kirchhoff plate model. We start by discretizing the thin plate dynamics using the EFG method for the spatial domain and the central difference scheme for the temporal domain. Stability and convergence analysis for transient responses, including deflection and moment responses, are derived similarly to those in two-dimensional transient structural dynamic analysis. The key to the analysis is transforming the governing equations and clamped boundary conditions into a weak formulation with penalty terms using the penalty method. The main results demonstrate a significant correlation between the error estimate and both nodal spacing and time step size. Additionally, the continuity of the approximation functions and the selection of penalty factors significantly affect numerical accuracy. To validate the theoretical results, we conduct numerical experiments involving clamped square and L-shaped plates with uniform and nonuniform node distributions, as well as a perforated plate model. Furthermore, we investigate the impact of node influence domains and penalty factors on numerical accuracy, facilitating parameter selection for practical engineering applications.

Computational insights into flame development and emission formation in an ammonia engine with hydrogen-assisted pre-chamber turbulent jet ignition

Ammonia, as a promising green fuel for achieving carbon neutrality and zero-carbon emissions, encounters obstacles in practical engine applications due to its intrinsic combustion properties like low burning velocity and high autoignition temperature. Hydrogen-assisted pre-chamber turbulent jet ignition (TJI) technology has recently demonstrated great potential in extending the lean limits and enhancing the stability of ammonia combustion. As such, this study conducts a comprehensive analysis on the flame development and emission formation processes under the active pre-chamber TJI mode fueled with ammonia and hydrogen using computational fluid dynamics (CFD) modeling integrated with detailed chemical kinetics, particularly focusing on the effects of hydrogen energy ratio and spark timing. It is found that the active ammonia-hydrogen TJI engine is typically characterized by four primary physical processes involving H2 mixture preparation in the pre-chamber, flame kernel formation and development within the pre-chamber, the formation and ejection of hot jet across the orifices, and the turbulent flame initiation and propagation in the main chamber. Hydrogen injection holds a scavenging effect on the residuals in the pre-chamber while forms fuel stratification near the spark plug, enhancing the ignition stability. Besides, the current combustion mode is commonly characterized by two-stage heat release in the main chamber, but exhibits a three-stage heat release as increasing the premixed H2 ratio. The first stage is dominated by a hot jet flame, the second stage is characterized by turbulent flame propagation or autoignition, and the third stage is induced by a secondary jet ejected from the pre-chamber, which becomes more prominent as the H2 ratio increases. Hydrogen blending could not only facilitate the turbulent flame propagation of NH3-air mixture in the main chamber but also enhance the initiation of flame kernel in the pre-chamber, thereby promoting the overall combustion process and potentially improving the thermal efficiency. The N2O emission is produced in two distinct stages, wherein N2O is generated and undergoes conversion during the main combustion phase, while unburned crevice gases mix with burned gases and convert into N2O during the expansion stroke. Increasing the premixed hydrogen ratio leads to an increased in-cylinder temperature, which in turn facilitates a reduction in N2O emissions and mitigates unburned ammonia. Furthermore, optimization of the spark timing is required after implementing the hydrogen addition into the intake manifold to achieve desirable combustion phasing and further improve the thermal efficiency. Finally, a novel combustion concept, denoted as TJI assisted compression ignition mode, is proposed for achieving high thermal efficiency in ammonia engines via adopting high compression ratio and premixed ammonia-hydrogen charge under the TJI strategy.

A Dual-Polarization Programmable Metasurface for Green and Secure Wireless Communication.

Dual-polarization programmable metasurfaces can flexibly manipulate electromagnetic (EM) waves while providing approximately twice the information capacity. Therefore, they hold significant applications in next-generation communication systems. However, there are three challenges associated with the existing dual-polarization programmable metasurfaces. This article aims to propose a novel design to address them. First, the design overcomes the challenge of element- and polarization-independent controls, enabling more powerful manipulations of EM waves. Second, by using more energy-efficient tunable components and reducing their number, the design can be nearly passive (maximum power consumption of 27.7mW), leading to a significant decrease in the cost and power consumption of the system (at least two orders of magnitude lower than the power consumption of conventional programmable metasurfaces). Third, the design can operate in a broad bandwidth, which is attractive for practical engineering applications. Both the element and array of the metasurface are meticulously designed, and their performance has been carefully studied. The experiments demonstrate that 2D wide-angle beam scanning can be realized. Moreover, secure communication based on directional information modulation can be implemented by exploiting the metasurface and an efficient discrete optimization algorithm, showing its programmable, multiplexing, broadband, green, and secure features.

A super-efficient gel adsorbent with over 1000 times the adsorption capacity of activated carbon

It was observed that a super-efficient gel adsorbent system (RRQG@CDC) could be obtained when a matrix material of polyquaternium gel with a flat distribution (RRQG) was loaded onto a skeleton material of cyclodextrin carbide (CDC). The results showed that the adsorption capacity of RRQG@CDC towards dyes was 1250 times higher than that of commonly used activated carbon, enabling highly efficient purification of dyeing wastewater through superior adsorption. In addition, RRQG@CDC demonstrated adaptability to a range of different pH values and salinity conditions, showing super-efficient adsorption abilities towards various types of dyes. Moreover, simulated scale-up tests confirmed the feasibility of this super-efficient adsorbent for practical engineering applications. An enhanced quasi-planar electrostatic adsorption mechanism model was established, which has changed the traditional understanding of adsorption mechanisms. Furthermore, the waste residues of RRQG@CDC, after dye adsorption, can be directly utilized as high-calorific fuels, showcasing the resourcefulness of these residues while eliminating the risk of secondary pollution. In conclusion, this study achieved a remarkably efficient and resource-based purification of dyeing wastewater by developing a highly effective adsorbent system.

Influence of dry density and wetting–drying cycles on the soil–water retention curve of compacted loess: experimental data and modeling

AbstractIn this paper, the EC-5 water sensor and the MPS-6 water potential sensor were used to measure water content and suction, respectively, to investigate the evolution of soil–water retention properties of compacted loess samples prepared at different dry densities and subjected to different numbers of wetting–drying cycles. The water retention data were integrated with a detailed microstructural investigation, including morphological analysis (by scanning electron microscopy) and pore size distribution determination (by nuclear magnetic resonance). The microstructural information obtained shed light on the double porosity nature of compacted loess, allowing the identification of the effects of compaction dry density and wetting–drying cycles at both intra- and inter-aggregate levels. The information obtained at the microstructural scale was used to provide a solid physical basis for the development of a simplified version of the water retention model presented in Della Vecchia et al. (Int J Numer Anal Meth Geomech 39: 702–723, 2015). The model, adapted for engineering application to compacted loess, requires only five parameters to capture the water retention properties of samples characterized by different compaction dry densities and subjected to different numbers of wetting–drying cycles. The comparison between numerical simulations and experimental results, both original and from the literature, shows that only one set of parameters is needed to reproduce the effects of dry density variation, while the variation of only one parameter allows the reproduction of the effects of wetting and drying cycles. With respect to the approaches presented in the literature, where ad hoc calibrations are often used to fit density and wetting–drying cycle effects, the model presented here shows a good compromise between simplicity and predictive capabilities, making it suitable for practical engineering applications.

Adaptive Neural Network Prescribed Time Control for Constrained Multi-Robotics Systems with Parametric Uncertainties

This study designed an adaptive neural network (NN) control method for a category of multi-robotic systems with parametric uncertainties. In practical engineering applications, systems commonly face design challenges due to uncertainties in their parameters. Especially when a system’s parameters are completely unknown, the unpredictability caused by parametric uncertainties may increase control complexity, and even cause system instability. To address these problems, an adaptive NN compensation mechanism is proposed. Moreover, using backstepping and barrier Lyapunov functions (BLFs), guarantee that state constraints can be ensured. With the aid of the transform function, systems’ convergence speeds were greatly improved. Under the implemented control strategy, the prescribed time control of multi-robotic systems with parametric uncertainties under the prescribed performance was achieved. Finally, the efficacy of the proposed control strategy was verified through the application of several cases.

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.

Experimental study of phase change energy pile based on Gum Arabic and Polyethylene Glycol 600 under multiple Thermal-Cold cycles

Temperature fluctuations cause energy piles to experience thermomechanical responses that affect their structural stability. The current trend in innovative energy pile technology is the application of phase change concrete to mitigate adverse thermomechanical responses. The exceptional feature of this research is that phase change concrete (GPC) based on Gum Arabic (GA) and Polyethylene glycol 600 (PEG-600) was used to cast phase change energy piles (GPEP). During five thermal-cold cycles, an indoor model test compared the GPEP to a traditional energy pile (TEP). The results demonstrated that the heat exchange efficiency of GPEP was 46.8 % (thermal cycle) and 27.1 % (cold cycle) higher than that of TEP. In addition, GPEP exhibited a lower pile temperature response and temperature fluctuation than TEP. GPEP exhibited a smaller perimeter soil influence range (2.0D) than TEP. GPEP exhibited a lower additional temperature stress variation than TEP (maximum shrinkage of 50.91 %). After five thermal-cold cycles, GPEP and TEP experienced subsidence accumulation, but GPEP exhibited 77.24 % less accumulated subsidence than TEP. This study provides a reference for the practical engineering applications of GPEP.

Seismic performance of shuttle-shaped double-restrained buckling-restrained brace: Experimental investigation and numerical analysis

To solve the problems of excessive cross-section size and self-weight and buckling instability of super-long buckling-restrained brace, a new lightweight shuttle-shaped double-restrained BRB (SDR-BRB) is proposed in this study. Firstly, cyclic loading experiments are conducted on three SDR-BRB specimens to investigate their failure mode and seismic performance. Then, a finite element model considering geometric, material, and contact nonlinearity is established and verified by experimental results. Finally, the effect of the restraining ratio on the hysteretic performance of SDR-BRB is studied by parameter analysis, and the restraining ratio requirement of the energy-dissipation type of SDR-BRB that meets the ductility requirements is obtained. The results show that SDR-BRB has stable and plump hysteretic curves, excellent energy-dissipation capacity, and low cycle fatigue performance, exhibiting obvious strain-strengthening characteristics. The restraining ratio is an important factor affecting the overall stability and failure mode of SDR-BRB, and it is recommended that the restraining ratio requirements of the SDR-BRB should be 2.25. The above research can provide a design reference for the practical engineering application of SDR-BRB.

Open set transfer learning for bearing defect recognition based on selective momentum contrast and dual adversarial structure

Data-driven rotating machinery fault diagnosis methods gradually enter people’s vision due to their fast and accuracy. However, in practical engineering applications, the unpredictability of machine failure modes and the appearance of new defect types can severely disrupt the diagnostic task with closed set defect recognition data-driven methods. Addressing this concern, this paper delves into the defect transfer diagnosis of rolling bearings in an open-set context and introduces the Momentum Contrastive Dual Adversarial (MCDA) domain adaptive method. This novel approach leverages instance-based difference comparison for unsupervised clustering and implements Negative Samples Selection Optimization (NSSO) via K Nearest Neighbor across all domains. It features intra-module adversarial learning for domain adaptation between source and target domains, and inter-module adversarial learning where encoders and feature extractors across different modules share weights. The methodology prioritizes the separation of private classes during the initial phase of contrastive learning, ensuring the isolation of target private classes. Concurrently, it aligns shared classes in the subsequent phase through semi-supervised training for domain adaptation. Our experiments on the Paderborn Dataset and Railway Freight Wheel-set Bearing (RFWB) Dataset demonstrate the effectiveness of this method.

Simultaneous improvement in surface quality and hardness of laser shock peened Zr-based metallic glass by laser polishing

Laser shock peening (LSP) is an effective method to improve the plasticity of metallic glasses (MGs) but it also deteriorates the surface quality and decreases the surface hardness, which in turn hinders the applications of MGs. Accordingly, this study was attempted to achieve the simultaneous improvement in surface quality and hardness of LSPed Zr-based MG by nanosecond pulsed laser polishing. LSP of the MG was firstly performed by using a high-energy pulsed laser to prepare the LSPed MG samples, and then laser polishing of the LSPed MG surface was conducted by using nanosecond pulsed laser. The effects of laser polishing parameters (i.e., average laser power, scanning speed, overlap rate, and number of irradiation cycle) on the surface quality and hardness of the LSPed MG were investigated in detail. The experimental results showed that after laser polishing under specific conditions, a 90% reduction in surface roughness and a 11 % increase in surface hardness could be achieved for the LSPed MG surface. This study provides a simple and effective method to simultaneously improve the surface quality and hardness of LSPed MGs, which would be of great significance for the practical engineering applications of MGs.

Finite Element Simulation Analysis of the Influence of Pile Spacing on the Uplift Bearing Performance of Concrete Expanding-Plate Pile Groups

Concrete expanding-plate piles (CEP piles) represent a novel type of variable cross-section concrete cast-in-place pile, wherein one or more bearing plates are added to the pile body to enhance its load-bearing capacity. Compared to traditional uniform-diameter uplift piles, the bearing plates of CEP uplift piles provide additional resistance against uplift, substantially increasing the pile’s uplift bearing capacity. CEP piles exhibit a wide range of application potential in structures such as high-rise buildings, cable-stayed bridges, and offshore platforms. However, due to changes in the load-bearing mechanism, the pile–soil interaction of CEP piles significantly differs from that of straight-shaft piles. Theories applicable to the group effect of straight-shaft piles cannot be directly applied to CEP piles, which has led to imperfections in the theoretical framework for designing CEP piles in practical engineering applications, hindering their broader adoption. Therefore, this paper employs a finite element simulation analysis to study the failure modes of three groups of symmetrically arranged CEP pile groups. The effects of pile spacing on the uplift bearing capacity of CEP pile groups are investigated, leading to a revision of the formula for calculating the uplift bearing capacity of CEP pile groups. This study enhances the theoretical understanding of the load-bearing behavior of CEP pile groups, providing a theoretical basis for their practical engineering applications.