Influence Of Design Parameters Research Articles

On the role of local reinforcement in an adhesively bonded AL/CFRP energy absorber under axial loading: A theoretical investigation and optimization

AbstractThis paper aims to develop a novel theoretical model that incorporates the effects of local composite reinforcement using adhesive bonding on the energy absorption of aluminum structures under axial loading. The goal is to optimize energy absorption prior to any connection failures and to prevent uneven structural deformation. Moreover, it strives to reduce the structure's weight and material usage, achieving superior results compared to traditional global reinforcement techniques. The theoretical model was validated through experimental testing and finite element analysis, demonstrating good agreement with the predicted results. The results reveal that increasing the CFRP fiber angle, layer thickness, and number of layers generally leads to improved energy absorption capacity. An optimization analysis was performed to determine the optimal design parameters, yielding a fiber angle of 80°–90°, composite thickness of 1.5 mm, and aluminum thickness of 2.5 is the best configuration, offering the highest specific energy absorption and adequate peak load capacity for maximized energy absorption. The proposed model offers significant improvements over existing approaches, enhancing the predictive capabilities and practical applicability of energy absorption predictions in engineering design.Highlights A novel theoretical model for energy absorption in locally reinforced hybrid AL/CFRP structures. The influence of design parameters, such as CFRP layer count, fiber orientation, and thickness ratio. Optimization to maximize the average crushing force while meeting weight and geometric constraints. Findings can inform the design of safer and more efficient energy‐absorbing structures in various applications.

Experimental Investigation of the Axial Load Capacity of Bilateral Helix-Stiffened Cement Mixing Piles in Soft Marine Soil

Bilateral helix-stiffened cement mixing piles (BHCMPs) are a new type of robust composite pile. In this paper, the influence of design parameters, such as the diameter of inner helix plates and the number and size of outer mixing helix plates, on the vertical bearing performance of the pile foundation and the behavior of the pile diameter are investigated through laboratory model tests. The results indicate that incorporating a reverse-mixing process in the pile formation of helix-stiffened cement mixing piles can enhance the overall ultimate bearing capacity and strengthen the soil-cement of the piles. In the case of the same double-blade inner drill pipe, for every 22 mm increase in the blades, its ultimate compressive load-bearing capacity was increased by 10% to 25%, and its pullout load-bearing capacity was increased by 15% to 45%. With further increases in the blades, the percentage increase in the compressive and pullout load-bearing capacity was reduced. With an increase in the number of external mixing blades, its compressive load capacity increased in the range of 5% to 20%, and the elevation load capacity increased in the range of 10% to 25%. Increasing the number of reverse-mixing helix plates on the outer casing enhances the soil-cement strength of the pile body by approximately 15–20% for each additional plate. The average strength of the pile-body soil-cement for each additional plate is estimated to be 1 to 1.4 times that of the previous set, indicating that increased mixing iterations can enhance the perimeter soil-cement strength of the pile. The average bond diameter of soil-cement piles with double-blade internal drilling rods could be seen from the diameter of the piles formed, which was 1.02 to 1.21 times the diameter of the blades.

Study on the Design Method of High-Resolution Volume-Phase Holographic Gratings.

Volume-phase holographic gratings are suitable for use in greenhouse gas detection imaging spectrometers, enabling the detection instruments to achieve high spectral resolution, high signal-to-noise ratios, and high operational efficiency. However, when utilized in the infrared wavelength band with high dispersion requirements, gratings struggle to meet the demands for low polarization sensitivity due to changes in diffraction performance caused by phase delays in the incidence of light waves with distinct polarization states, and current methods for designing bulk-phase holographic gratings require a large number of calculations that complicate the balance of diffraction properties. To overcome this problem, a design method for transmissive bulk-phase holographic gratings is proposed in this study. The proposed method combines two diffraction theories (namely, Kogelnik coupled-wave theory and rigorous coupled-wave theory) and establishes a parameter optimization sequence based on the influence of design parameters on diffraction characteristics. Kogelnik coupled-wave theory is employed to establish the initial Bragg angle range, ensuring that the diffraction efficiency and phase delay of the grating thickness curve meet the requirements for incident light waves in various polarization states. Utilizing rigorous coupled-wave theory, we optimize grating settings based on criteria such as a center wavelength diffraction efficiency greater than 95%, polarization sensitivity less than 10%, maximum bandwidth, and spectral diffraction efficiency exceeding 80%. The ideal grating parameters are ultimately determined, and the manufacturing tolerances for various grating parameters are analyzed. The design results show that the grating stripe frequency is 1067 lines per millimeter, and the diffraction efficiencies of TE and TM waves are 96% and 99.89%, respectively. The diffraction efficiency of unpolarized light is more than 88% over the whole spectral range with an average efficiency of 94.49%, an effective bandwidth of 32 nm, and a polarization sensitivity of less than 7%. These characteristics meet the performance requirements for dispersive elements based on greenhouse gas detection, the spectral resolution of the detection instrument is up to 0.1 nm, and the signal-to-noise ratio and working efficiency are improved by increasing the transmittance of the instrument.

Autoinjector optimization through cavitation response and severity minimization

Abrupt acceleration of the syringe of an autoinjector (AI) upon rod-plunger impact may induce undesired severe cavitation events and impose extraneous stresses upon the device, leading to device failure. Cavitation results from a rapid and significant pressure drop in a liquid, leading to the formation and growth of small vapor-filled cavities. Upon collapse, these cavities generate an intense shock wave that may lead to protein aggregation and device container damage and shatter. Since the maximum acceleration of the syringe depends upon the operating conditions of the AI, the severity of cavitation will likewise depend on the operating conditions of the AI. Likewise, injection time and ensuring proper needle displacement before drug release also depend on operating conditions, making optimization of the autoinjector a multiobjective optimization problem.Therefore, in this study, optimization of an autoinjector to limit cavitation severity is pursued via an experimentally validated computational model for cavitation in spring-driven autoinjectors. Our goal is to locate AI design configurations that balance maximizing device performance and patient comfort and minimizing the risks of device damage and severe cavitation upon actuation.Relevant parameters of interest are the drive spring force, air gap height, solution viscosity, friction between the rod and spring, frictional force on the plunger, rates of change of frictional force on the plunger, elasticity of plunger, viscosity of the plunger, and initial displacement between the plunger and the driving rod. The kinematics of the syringe barrel, needle displacement (travel distance) at the start of drug delivery, and injection time are gathered using an experimentally validated autoinjector kinematics model. At the same time, cavitation bubble dynamics are resolved using an experimentally validated cavitation model that takes the temporal displacement of the syringe and temporal air gap pressure as inputs.We use our experimentally validated models to explore the parameter space and understand the driving factors of our desired outcomes. Subsequently, we pose the design problem as a multi-objective optimization problem and develop a deep neural network surrogate model supplemented with iterative learning to speed up optimization. A variance-based sensitivity analysis was performed to determine the sensitivity and influence of design parameters on the outcomes, and the main contributors to the outcomes of interest were isolated. Using a multi-objective optimization framework, we located 300 + successful candidates and evaluated them through uncertainty analysis to identify three promising candidates that meet all criteria for drug viscosities of interest. Finally, we show that this methodology can be used to conduct hypothesis testing, leading to novel design configurations.

Influence of design parameters on heat production of a multilateral butted closed loop geothermal system

To efficiently develop hot dry rock and other geothermal energy, a multilateral butted closed loop geothermal system (MBCLGS) is presented in this paper to replace the U-shaped closed-loop geothermal system (UCLGS). Besides, a casing-cement-formation transient heat transfer model is established to investigate the influences of key factors on the heat production of MBCLGS. After thermal-fluid-structural coupling analysis, we can find that higher injected rate and lower fluid temperature can improve heat power but reduce output temperature. In addition, the output temperature and heat power do not increase continuously with the increasing of branch well number. There is an optimal value of branch well number. Longer well pair distance can improve both output temperature and heat power. Considering the drilling technology level and design purpose, the recommended injected flow rate of MBCLGS is 90 m3/h, the injected fluid temperature is 42.5 °C, the number of branch wells is 10 and the well pair distance is 200m. Finally, by comparing MBCLGS and UCLGS, it is found that MBCLGS has a lower temperature decline rate and higher output temperature than UCLGS under the same conditions. It works more stable and has better economy. Overall, the proposal of MBCLGS is expected to promote the efficient development of deep geothermal resources.

Slot-Loaded Vivaldi Antenna for Biomedical Microwave Imaging Applications: Influence of Design Parameters on Antenna's Dimensions and Performances.

This paper demonstrates the design steps of a slot-loaded Vivaldi antenna for biomedical microwave imaging applications, showing the influence of the design parameters on the antenna's dimensions and performances. Several antenna miniaturization techniques were taken into consideration during the design: reduction in the electromagnetic wavelength by using a high-permittivity substrate material (relative permittivity ϵr=10.2), the placement of the antenna inside a coupling medium (ϵr=23), and the elongation of the current path by etching slots on each side of the radiator to reduce the antenna's lowest resonant frequency without increasing its physical dimensions. Moreover, an analysis of different antenna slot design scenarios was performed considering different slot lengths, inclination angles, positions, and numbers. Considering the frequency range of microwave imaging (i.e., about 500 MHz-5 GHz) and the array arrangement typical of microwave imaging, the best design was chosen. Finally, the antenna was fabricated and its performances in the coupling medium were characterized. The simulation and measurement results showed good agreement between each other. In comparison with literature antennas, the one developed in this work shows wide bandwidth and compact dimensions.

To the problem of the shielding systems efficiency in constructions of extra-high voltage electrical apparatus

In the article, the authors proposed a method for estimating the electric load parameters to calculate the distribution of the electric field strength of the solid insulating structure of gas-filled high-voltage devices with axial symmetry. This structure consists of a support and insulating busbar filled with SF6 gas as an internal insulating medium. This technique allows to evaluate the parameters of the electrical load (voltage and field strength) depen-ding on the design features of the device and the shielding system used to equalize the electric field. The proposed methodology allows to evaluate the effectiveness of the influence of design parameters of the protection system for gas-filled high-voltage equipment (instrument transformers, arresters, surge arresters, etc.) when designing and improving individual design solutions. The calculation results are in good agreement with the data of experimental studies and statistical information obtained as a result of monitoring the operation of insulating structures, taking into account actual operating conditions and the influence of external factors. The implementation of this technique allows us to take into account the influence of external factors and operational characteristics inherent in instrument transformers and surge suppressors. In the proposed methodology, as an example, we consider a supporting insulating coating that is in operation under the most unfavorable conditions, such as external pollution, moisture and their combination, overvoltage of various origins, etc. The theoretical conclusions are confirmed by the results of calculations using the example of the support-insulating cover of the surge suppressor of the OПН-500 series. A more accurate determination of the effectiveness of the proposed methodology for predicting the field strength distribution parameters under the influence of a shielding system can be achieved by conducting an additional series of calculations and experimental tests of specific insulating structures. Thus, it was concluded that the obtained results can be used to evaluate the external insulation characteristics of both surge suppressors and gas-filled instrument transformers, as well as similar high-voltage equipment of switchgears and transformer substations in conditions of ultra- and transformer substations ultra-high voltages

Influence of design parameters on natural convection heat transfer in additively manufactured body centered cubic lattice structures

The natural convection heat transfer mechanism of the body centered cubic (BCC) lattice structure needs to be clarified for its application in passive cooling thermal management. The BCC lattice heat sinks with various design parameters, such as strut diameter and unit cell length, were fabricated using the laser powder bed fusion process. Subsequently, the thermal performance was experimentally determined for variations in design parameters. The thermal performance tended to be maximized when the relative density of the lattice heat sink constituted approximately 10 %. The numerical analysis was performed to figure out the heat transfer mechanism and investigate the effects of inclination angles. According to numerical results, a lattice heat sink with a smaller strut diameter at the given unit cell length entrains more air than one with a larger strut diameter. However, decreasing strut diameter led to a negative impact on conduction and radiation heat transfer due to the reduction in solid region and surface area. Depending on the inclination angle, thermal performance of a lattice heat sink proportionally decreases. The main cause of performance degradation was the hindrance of plume motion by the base of the heat sink.

Full analysis and deep learning optimization of a sustainable and eco-friendly power plant to generate green hydrogen and electricity; A zero-carbon approach

Among alternative energy sources for fossil fuels, hydrogen has emerged as a promising candidate; however, its production methods, reliant on fossil fuels, constrain its widespread adoption as a sustainable energy source. To transcend this limitation, researchers have proposed the concept of green hydrogen production, leveraging renewable energy sources, as a viable solution. This study presents a comprehensive techno-economic analysis that seeks to evaluate the feasibility of establishing a multi-generation green power plant in Iran. Extensive climate data from diverse locations across Iran were collected to determine the most influential design parameters. A mathematical model was developed to simulate the entire system, and an innovative neural network algorithm was employed to optimize the objective functions, given the substantial computational time required for the optimization process. The results of the optimization revealed Qeshm island as the optimal location for the green power plant, considering its favorable annual average temperature, wind speed, and solar radiation intensity. Remarkably, the proposed green power plant boasts a robust power generation capacity of 10.1 MW, enabling the production of 250 tons of hydrogen per year, exhibiting a 10 % improvement in exergy efficiency, and a 6 % reduction in LCOE, in comparison to similar studies. Furthermore, it exhibits an impressive total exergy efficiency of 41.6 %, resulting in a substantial annual income of $3.9 million and achieving a commendable payback period of 1.8 years.

Influence of geometric parameters on aerodynamic characteristics of serpentine convergent-divergent nozzle

The serpentine convergent-divergent nozzle represents an optimal configuration for next-generation fighter aircraft characterized by low detectability and high thrust-to-weight ratio. In contrast to the serpentine convergent nozzle, such configuration offers increased design flexibility with additional parameters, leading to heightened interactions among these parameters. As such, it is crucial to reveal the influence of design parameters on the aerodynamic performance of the serpentine convergent-divergent nozzle and the multifactor interaction, as well as its mechanism. Therefore, the influence, interaction and sensitivity of parameters on the aerodynamic performance of the nozzle were numerically investigated using the orthogonal test method. Additionally, the influence mechanism of the convergence angle, throat aspect ratio, and axial length to inlet diameter on the flow characteristics of the nozzle was investigated in detail. The results show that the convergence angle is identified as the main factor affecting the aerodynamic parameters of the nozzle. As the convergence angle increases, the thrust coefficient, total pressure recovery coefficient and discharge coefficient gradually decrease. The interaction between throat aspect ratio and other parameters is obvious. Different design parameters affect the local loss and the friction loss by affecting the curvature and wetted perimeter area, resulting in different aerodynamic characteristics of serpentine convergent-divergent nozzle.

Probabilistic evaluation of spectral acceleration demands on light secondary systems supported by partially self-centering structures

Partially self-centering structures are promising seismic resilient structural systems by reducing residual inter-story drifts with low initial construction costs. Comprehensive studies focused on structural design and performance evaluation, but no research was conducted to investigate the design of nonstructural components in partially self-centering structures. This research focuses on developing the probabilistic spectral acceleration demands for the nonstructural design in partial self-centering structures. 320 near-fault recorded ground motions were adopted for considering the uncertainties of seismic excitations. The spectral accelerations of the light nonstructural component were obtained through comprehensive dynamic analyses. The logarithmic normal distribution can be used for describing the probabilistic distribution of floor spectra for partially self-centering structures under earthquakes, validating through the Anderson-Darling test. The influences of design parameters (including structural period, hysteretic parameters, structural damping, the ratio of the structural period to the nonstructural period, and nonstructural damping) on the probabilistic distribution of floor spectra were investigated through parametric dynamic analysis results. Artificial neural network (ANN) models were developed for predicting the probabilistic floor spectra for partially self-centering structures. The analysis results indicate that ANN models can achieve excellent accuracy with a coefficient of determination larger than 0.99. Comparative analysis results reveal that the ASCE method may underestimate the acceleration demand of light secondary systems supported by partially self-centering structures. The developed ANN models were interpreted using the shapely additive explanations. It has been found that the fundamental periods of the main structure and nonstructural components and the response modification factor show significant effects on the median and deviation of the probabilistic floor spectra for partially self-centering structures. The software FloorSpecPS was established to predict the probabilistic floor spectra for partially self-centering structures using the developed ANN models in practical application.

A Morris sensitivity analysis of an office building's thermal design parameters under climate change in sub-Saharan Africa

Sub-Saharan Africa faces severe overheating problems during hot periods due to substandardly constructed buildings and high-priced energy services. Global warming is expected to aggravate the situation. Although literature addresses the effects of climate change on buildings in different world regions, how it will impact the Sub-Saharan region is still being determined, particularly in terms of design parameters and how they will vary. This study assesses the influence of design parameters on the cooling energy demand of a small-scale office building in Lagos and Kano, Nigeria. A Morris sensitivity analysis was carried out to rank and compare the influence of different design parameters on energy consumption, determined using EnergyPlus for present-day typical weather and the SSP5-8.5 scenario. The future scenario was generated using the Future Weather Generator, a morphing tool. The results show that, in 2080, the cooling load will increase from 1551 kWh/a to 2612 kWh/a (68.4 %) in Kano and from 1931 kWh/a to 3093 kWh/a (60.1 %) in Lagos. The cooling load in Lagos will generally be higher than in Kano by 18.4 % (596 kWh/a). The results indicate that reductions in the thermal conductivity of the east wall and decreases in the solar absorptance of the east wall, roof, and west wall elements will be the most significant factors affecting cooling in Kano. In Lagos, reductions in the thermal conductivity of the east wall and decreases in solar absorptance of both the east wall and roof elements will be the most influential.

Investigating the influence of design parameters on the flow characteristics of a rectangular gas-solid fluidized bed with non-spherical particles

Investigating the influence of design parameters on the flow characteristics of a rectangular gas-solid fluidized bed with non-spherical particles

Manufacture and structural performance of modular hybrid FRP–timber thin-walled beams

Developed to fulfil the rising societal demand for sustainable constructions, Modular Hybrid Fibre-reinforced polymer-Timber (MHFT) thin-walled sections are lightweight timber-based composite structures manufactured through a modular assembly method. Motivated by prior research on MHFT columns characterized by efficient load-carrying capacity, this paper conducted a thorough investigation into the manufacture and structural performance of MHFT beams. Experimental, analytical and numerical studies were conducted for beams subjected to four-point bending load, with parametric analyses of four distinct beam types to investigate design parameter influence on flexural performance. The experimental study demonstrated the structural efficacy of MHFT beams, as evidenced by increased moment of inertia and enhanced resistance to edge split failures, as compared to previously studied folded HFT beams. MHFT beams also exhibited a comparable strength-to-weight ratio compared to their structural steel counterparts. Both numerical and analytical methods provided acceptable predictions for flexural strength and material failure modes of MHFT beams, with strength predictions varying by less than 22% compared to experimental averages. The numerical method reliably predicted flexural stiffness and load–displacement responses, with discrepancies within 12%. The parametric analyses further revealed that the thickness of glass fibre-reinforced polymer (GFRP) layers and cross-sectional geometric profile were most strongly influenced beam parameters. Specifically, the use of 3-layer GFRP material resulted in a strength increase of over 17% and a stiffness increase of over 19% compared to 1-layer material, effectively mitigating the occurrence of local buckling and edge split failures.

Deep neural network model for predicting thermal-hydraulic performance of a solar air heater with artificial roughness: Sensitivity, generalization capacity, and computational efficiency

A novel coupled computational fluid dynamics-deep neural network approach is proposed to accurately predict the performance of an artificially roughened solar air heater. Computational fluid dynamics data sets are used to develop an optimized neural network model for the prediction of thermal-hydraulic performance factor. The optimized neural network model with softmax transfer function in hidden layers has an architecture of 3‐37‐37‐1 and it predicts the thermal-hydraulic performance factor of the artificially roughened solar air heater with maximum, mean, and minimum error of 2.54 %, 0.245 %, and 0.0009 %, respectively. The concept of Shapley values is adopted to evaluate the global sensitivity analysis of the optimized deep neural network model and it is found that rib height is the most influential design parameter for the artificially roughened solar air heater. The generalization capacity of the neural network model is evaluated by comparing its predictions with experimental data, demonstrating superior predictive performance over traditional computational fluid dynamics simulations. The optimized artificial neural network model achieves a computational time gain of approximately 100 % against computational fluid dynamics.

Influence of design parameters on sustained drug release properties of 3D-printed theophylline tablets

The application of three-dimensional printing (3DP) in the pharmaceutical industry brings a broad spectrum of benefits to patients by addressing individual needs and improve treatment success. This study investigates the sustained release properties of 3DP tablets containing Theophylline (TPH), which is commonly used to treat respiratory diseases and recently having a comeback due to its potential in the treatment of conditions like Covid-19. Since TPH is a narrow therapeutic window (NTW) drug with serious side effects in the event of overdose, the release properties must be observed particularly closely. We employed a state-of-the-art single screw extrusion 3D printer, which is fed with granules containing the drug. By employing a Taguchi orthogonal array design of experiments (DOE), tablet design parameters and factor related process stability were sought to be evaluated fundamentally. Following this, examinations regarding tailored TPH dosages were undertaken and a relationship between the real printed dose of selected tablet designs and their sustained drug release was established. The release profiles were analyzed using different mathematical model fits and compared in terms of mean dissolution times (MDT). Finally, in-vivo/in-vitro correlation (IVIVC) and physiologically based pharmacokinetic (PBPK) modeling showed that a paradigm patient group could be covered with the dosage forms produced.

Comparative Analysis of Influencing Factors on Heat Extraction Performance of Multi-Type Shallow Borehole Heat Exchangers

In this paper, the influence of design parameters and geological parameters on the heat extraction capacity of common coaxial type, single U-type, and double U-type borehole heat exchangers(BHEs) in shallow ground source heat pump system is analyzed, and the heat extraction performance of different types of BHEs is further compared. The results show that with the increase in borehole depth and ground temperature gradient, the outlet temperature of the three types increases at the end of the heating season, and the single U-type BHE increases most significantly. The increase in inlet flow rate will decrease the outlet temperature of the three BHEs, and the U-type is the most obvious decrease. The increase in inlet temperature will reduce the temperature difference between inlet and outlet of the three types BHEs. Given the same design parameters, coaxial-type BHE obtains the maximum heat.

Influence of Design Parameters on Adjacent Track Interference in Heated-Dot Magnetic Recording

Influence of Design Parameters on Adjacent Track Interference in Heated-Dot Magnetic Recording

Effects of internal wall design on cross-ventilation of an isolated building

Poorly designed internal walls deter natural ventilation of buildings, causing poor indoor air quality and exorbitant energy costs when mechanical ventilation systems are used. Although one can design internal walls with minimum adverse effects on natural ventilation by controlling height, width, location, and porosity of internal walls, less research has been done to date. This study investigated how these four parameters individually and collectively influence the cross-ventilation of buildings using Reynolds-average Navier–Stokes equation-based computational fluid dynamics simulations and the local and global sensitivity analysis. When considering individual parameters, the local sensitivity analysis revealed the positive correlation between internal walls' porosity and cross-ventilation, similar to previous studies. However, the global sensitivity analysis identified the location as the most influential design parameter for cross-ventilation. Furthermore, the global sensitivity analysis revealed nonlinear, non-monotonic, and interactive relations between cross ventilation and all parameters but porosity, highlighting the importance of evaluating all design parameters together and the difficulty in extrapolating the findings for idealized to actual internal wall designs. Based on the findings, this study proposes narrow internal walls with high porosities built away from ventilation openings as a basic internal wall design to maximize the cross-ventilation of buildings.

Numerical investigation of disk bypass pipeline inspection gauge with hole in disk

Bypass Pipeline Inspection Gauges (PIGs) are widely employed as the most effective and economical devices for pipeline cleaning, maintenance, and inspection operations. The speed of these bypass PIGs significantly impacts the operational activities of pipelines. Very high or low PIG speeds may cause damage to the pipeline and the PIG itself. Therefore, it is important to control the speed of the PIG for better pigging operations. This study focuses on the influencing parameters and their impact on PIG speed. The approach of Computational Fluid Dynamics (CFD) has been utilized to model fully turbulent flow around a sample of a disk bypass PIG with a hole in the disk section for four different cases. PIG speed and pressure loss coefficient are measured to evaluate the effectiveness of the PIG. Meanwhile, two dimensionless groups are introduced based on the influencing design parameters for the movement of the disk bypass PIG, with and without a hole, to measure the optimal design parameters. The results show that a disk bypass PIG with a hole in the disk provides 5%-7% better results in terms of PIG speed and 6%-9% for the pressure loss coefficient around the PIG section. Among the four cases of a disk bypass PIG with a hole in the disk section, case-1 shows better pigging operation, with a dimensionless group value of 0.24. However, case-1 exhibits a 2.7%-22% reduction in PIG speed and a 12%-72% reduction in the pressure loss coefficient compared to other cases. Additionally, the lowest value of the presented dimensionless group indicates better pigging operation, and the optimal value of the dimensionless group is 0.24 for the design consideration of the PIG. This study holds directional significance for the design of the structural parameters of the PIG, which are useful for pipeline clean-up, inspection, and operational maintenance, and it provides reference value for related researches.