Optimal Parameter Combination Research Articles

Experimental Study on Performance of Cotton Small Arch Shed Recovery Machine

Most of the small-arch-shed-recycling machines in China use manual disassembly and manual recycling, with low recycling efficiency and low mechanization. Therefore, this paper designs a small recovery machine for arch sheds, greatly improving the efficiency of the recycling of arch sheds, which can realize the lifting and collection of the arch shed rod and orderly recycling of the shed film. By performing univariate experimental studies in the field, on the basis of field experiments, we carried out an experimental analysis with machine speed and different soil moisture contents as the influencing factors and took the removal rate of the shed rod, the removal rate of the shed film, and the damage rate of seedlings as the test indexes. The test results show that the optimal parameter combination is a travel speed of 1.1 m/s, at which the operation effect is the best. The results show that under the optimal operation effect, the removal rate of the shed rod was 95.72%, the removal rate of the shed film was 98.63%, the seedling injury rate was only 2.11%, and the removal rate of the shed rod was only 4.01%, which met the requirements of the recovery operation of the arch shed and means that this approach is conducive to the recycling of the arch shed materials and the realization of sustainable development. In actual operation, the parameters should be adjusted according to the actual situation in the field to meet the different recovery needs of arch sheds.

Design and Testing of Key Components for a Multi-Stage Crushing Device for High-Moisture Corn Ears Based on the Discrete Element Method

To improve the crushing efficiency and crushing pass rate of high-moisture corn ears (HMCEs), a multi-stage crushing scheme is proposed in this paper. A two-stage crushing device for HMCEs is designed, and the ear crushing process is analyzed. Firstly, a simulation model for HMCEs was established in EDEM software (2018), and the accuracy of the model was verified by the shear test. Subsequently, single-factor simulation experiments were conducted, with the crushing rate serving as the evaluation index. The optimal working parameter ranges for the HMCE device were identified as a primary crushing roller speed of 1200–1600 revolutions per minute (r/min), a secondary crushing roller clearance of 1.5–2.5 mm, and a secondary crushing roller speed of 2750–3750 r/min. A Box–Behnken experiment was conducted to establish a multiple regression equation. With the objective of maximizing the qualified crushing pass rate, the optimal combination of parameters was revealed: a primary crushing roller speed of 1500 r/min, a secondary crushing roller clearance of 2.5 mm, and a secondary crushing roller speed of 3280 r/min. The pass rate of corn cob crushing in the simulation test was 98.2%. The physical tests, using the optimized parameter combination, yielded a qualified crushing rate of 97.5%, which deviates by 0.7% from the simulation results, satisfying the requirement of a qualified crushing rate exceeding 95%. The experimental outcomes validate the rationality of the proposed crushing scheme and the accuracy of the model, providing a theoretical foundation for subsequent research endeavors.

Optimal Design of Multilevel Composite Lubrication Structures on Sliding Guide Rail Surfaces

To optimize the crawling phenomenon of slides under circumstances of low speed and a heavy load, a composite lubrication structure is adopted to alleviate the crawling phenomenon. The response surface optimal-design method establishes a quadratic mathematical model for multistage composite lubrication structure parameters, including crawling time and average friction coefficient. The optimal combination parameters of multistage composite lubrication structures have been determined. The optimal ratio of lubricating oil to molybdenum disulfide (MoS2) has been identified, and a composite lubrication structure has been proposed to enhance the crawling phenomenon and friction performance of sliding guide rails under medium-speed and medium-load conditions. These research outcomes indicate that when low speed and a heavy load are present, the crawling time and friction coefficient initially diminish and subsequently augment as the width, spacing, and cycle length of the sinusoidal texture and the diameter of the hexagonal pit expand. The optimum configuration of multistage composite lubrication structures is as follows: The width of the sine-wave texture b amounts to 0.15 mm, the cycle length e is 2 mm, the spacing c is 1.5 mm, and the diameter of the hexagonal pit d is 0.2 mm. When the mass ratio of guide oil to MoS2 is 2:1, it exhibits supreme crawling resistance and antifriction attributes. In circumstances involving a medium load and speed, multistage composite lubrication structures manifest pre-eminent friction performance. These data can steer the design of multistage composite lubrication structures on the surface of slide rails.

Multi-Objective Optimization of the Forming Process Parameters of Disc Forgings Based on Grey Correlation Analysis and the Response Surface Method

This paper introduces a multi-objective optimization problem (MPO) for the forming process parameters of disc forgings using grey relational analysis (GRA) and the response surface methodology (RSM). Firstly, an experimental design based on the Box–Behnken design (BBD) principle was established, and simulations were performed in Deform to obtain response data. Secondly, GRA was used to transform the MPO into a grey relational degree (GRD) problem, and the entropic weight method was integrated to ascertain the influence weights of each variable on GRD. Then, a quadratic polynomial prediction model based on the RSM was constructed, and its accuracy was ensured through model validation. Finally, the optimal process parameter combination was determined through the particle swarm optimization algorithm, which included a friction coefficient of 0.3, an initial temperature of 1250 °C, and a downward pressing speed of 7.5 mm/s. The results of the experimental investigation indicate that optimized process parameters significantly reduce the forming load, equivalent stress, and damage value, effectively enhancing the overall quality of forged parts.

Research on the impact mechanism and parameter optimization of RTP structure layer fusion process

Fiber-reinforced thermoplastic composite pipes (RTP) possess a complex multilayer structure. Apart from the melting process of the reinforced layer, the melting process between the inner and outer layers and the reinforced layer is equally crucial. Factors such as heating time, heating temperature, and pipe diameter significantly influence the degree of tight bonding between these layers. The purpose of this study is to investigate the influence mechanism of the fusion process between the three main layers of RTP and to perform parameter optimization analysis. First, Box-Behnken response surface method and finite element analysis were used to obtain the softened layer thickness under different parameters and to couple the influence mechanism of process parameters on the softened layer thickness. Then, single parameter sensitivity analysis was used to reveal the influence mechanism of each parameter change on the softened layer thickness of the pipe, and then the coupling analysis of the process parameters was carried out. The analysis results show that the softened layer thickness is most sensitive to the change of heating temperature, followed by heating time and pipe diameter. Finally, the optimal parameter combination was obtained through the expected function method, and experiments were conducted on finished pipes.

In-depth research on fault diagnosis of turbine rotor utilizing NGSABO-optimized VMD and CNN-BiLSTM

Abstract To solve the problem of difficulty in extracting and identifying fault types during turbine rotor operation, a fault diagnosis method based on improved subtraction mean optimizer (NGSABO) algorithm to optimize variational mode decomposition (VMD) and CNN-BiLSTM neural network is proposed. Firstly, three improvements are made to the subtraction average optimizer algorithm. Secondly, the optimal VMD parameter combination of NGSABO adaptive selection mode decomposition number K and penalty factor is used to decompose the rotor fault signal, and the minimum sample entropy is used as the fitness function for feature extraction. Combining convolutional neural network and bidirectional long short-term memory network to identify and classify features. Compared with other methods, this method has outstanding performance in the diagnosis of single and coupled rotor faults. The accuracy of fault diagnosis reaches 98.5714%, which has good practical application value.

Study on the Properties of Sinusoidal Micro-Textured Ball End Milling Cutter for Milling Titanium Alloy

To improve the cutting performance when cutting hard alloys and achieve reasonable optimization of micro-texture parameters, this paper proposes a sinusoidal micro-textured tool, with four parameters set as micro-textured spacing, period, width, and amplitude. Establish three-dimensional models of non-micro-textured and micro-textured milling tools and simulate the milling process using finite element simulation. Study the effects of milling force and milling temperature on tool performance. Prepare micro-textured milling tools for orthogonal experiments, analyse the effects of milling force and the surface roughness of a titanium alloy workpiece, and study the impact of different micro-textured parameters on milling tool performance. Obtain the parameters that have the greatest impact on milling tool performance, and then use genetic algorithm to optimize three sets of parameter combinations. Use the optimized parameters to prepare milling tools for comparative experiments, and then determine the optimal parameter combination. The research results indicate that micro-textured tools can effectively improve the milling performance of the tool, and the spacing between sinusoidal micro-textures has the greatest effect on improving the milling performance of the tool. When the period of sinusoidal micro-texture is 2.87 and the amplitude is 25.13 μm, width is 79.89 μm, and spacing is 134.54 μm, the milling performance of the tool is optimal.

Experimental investigation on in-situ laser-assisted machining of single crystal silicon based on response surface methodology

Abstract In this paper, Response Surface Methodology (RSM) was utilized as a robust and convenient predictive tool to establish the correlation between process parameters in in situ laser-assisted machining and the surface roughness of single-crystal silicon. An optimized design of the diamond tool, a novel temperature field analysis method, and Response Surface Methodology (RSM) were utilized. The contribution rate of each process parameter on surface roughness was laser power > rotation speed > cutting depth > feed rate. The optimal process parameter combination is: rotation speed as 1001 r min−1, feed rate as 4.9 μm/r, cutting depth as 7.55 μm, and laser power as 28.81 W. Experimental validation of these optimal parameters compared surface roughness values obtained experimentally with those predicted. The surface roughness model showed a maximum relative error of 5.2%, with an average error of 4.8% across three experimental sets. These errors are within acceptable limits, indicating an alignment between predicted and experimental results.

A novel bionic lotus leaf channel liquid cooling plate for enhanced thermal management of lithium-ion batteries

Battery Thermal Management Systems (BTMS) are pivotal in safeguarding the safety, efficiency, and lifespan of electric vehicles. In this study, we propose a bionic lotus leaf (BLL) channel liquid-cooled plate to mitigate temperature accumulation issues observed during lithium-ion battery (LIB) discharge. The primary objective is to enhance heat dissipation and achieve uniform temperature distribution within LIBs. We investigated the impact of different interior configurations and mass flow rates on individual lithium-ion battery (LIB) temperatures using single-variable analysis. Our findings indicate that higher inlet mass flow rates effectively lower the temperature increase in individual LIBs, albeit at the cost of inducing a significant pressure drop.The optimal parameter combination is determined through orthogonal analysis. Specifically, the channel angle (α) and inlet mass flow rate (M) are found to significantly influence the maximum temperature (Tmax) of LIBs. The number of channels (N) is optimized to enhance temperature distribution and reduce maximum temperature variation (ΔTmax) within LIBs. Furthermore, adjusting the channel width (D) substantially mitigated pressure drop (ΔP) in the BLL channel liquid cooling plate, thereby improving hydraulic pump efficiency. The identified optimal combination (M = 1.0 g s-1, N = 4, D = 2.5 mm, α = 90°) ensures that Tmax remains below 29.732 °C even during a 5C discharge, a critical requirement. Compared to a traditional serpentine channel with equivalent heat transfer area and inlet mass flow, the optimized BLL channel showed a decrease in Tmax by 0.776 °C, ΔTmax reduction by 2.445 °C, and ΔP reduced to only 43.44 % of that in the serpentine channel. The BLL channel proposed in this research can serve as a valuable reference for BTMS.

Numerical simulation and experimental study of the influence of disk groove structure optimization on the air film flow field signature of an air-cushion sandwich belt conveyor

A new type of disk groove mechanism was developed and manufactured. The effects of the structural and operating factors of the disk groove on the air film loading performance were examined using single factor and orthogonal experimental methods. The results of numerical simulation and experimental studies showed that the air film loading performance correlated positively with the orifice diameter and inlet pressure, with the orifice spacing and diameter having the most significant effects, and that the belt speed boosted the air film uniformity. Meanwhile, a comparative analysis of the corresponding level values showed that an air film thickness of 0.8 mm, orifice diameter of 5 mm, orifice spacing of 30 mm, inlet pressure of 8000 Pa, and conveyor speed of 5 m/s were the optimal parameter combinations for the maximum loading capacity. To verify the accuracy of the model, a field experiment was conducted at Jiangmen Southern Conveying Machinery Engineering Co., Ltd. The air film pressure at the experimental position matched the numerical simulation results. In addition, when the number of rows was one and the air volume was 10 m3/h, the smallest value of traction resistance was obtained under minimum power consumption.

3D FEM forming simulation optimization and experiment on bevel thread-forming screw

Abstract This study adopts 3 forming passes and 1 thread rolling process as the multi-pass schedule of bevel thread-forming screw. The finite element simulation software is used to simulate the plastic behaviour of forming and thread rolling processes. The geometry shapes, the part dimensions of each pass, the effective stress, the effective strain, the forming force and the die stress of each pass can be reached via FEM simulation. Moreover, especially Taguchi method for the maximum force pass is conducted to optimize the forming processes. Considering 4 control factors such as A: head arc radius (rH), B: flange thickness (t), C: corner radius (r), and D: frictional factor(m) and 3 levels to establish the orthogonal array table for optimum forming force, the influence rank and the optimal parameters combination are obtained to carry out the realistic experiment for confirming the feasibility of FEM simulation optimization. In a word, the influence rank of control factors: flange thickness (t) > head arc radius (rH) > corner radius (r) > frictional factor (m), and the optimal parameters combination is A3B3C3D1 (rH=42 mm, t=1.3 mm, r=0.7 mm, and m=0.12).

Effect of Mg on the Microstructure, Mechanical Properties, and Surface Roughness of Functionally Graded A413 Composite: Machine Learning Approach at Wire‐Cut Electric Discharge Machining Zone

The present study assists the industrial sectors by implementing low‐weight high‐strength aluminium composite. The pristine magnesium as a reinforcement in three different weight percentages (3.5, 7, and 10.5) is utilized to fabricate the A 413 composite using centrifugal casting. The density analysis concludes a higher level of Mg inclusion prompts the material to save 3.9% of weight. Microstructural study of centrifugal casting specimens reveal a rich existence of hard phase Mg2Si in the outer zone, with its richness decreasing toward the inner zone. The tensile test result affirms the functionally graded nature of the material with the increasing trend of tensile strength from the inner to the outer. Fractured surface analysis concludes the existence of cracks and their propagation for the inner region specimen. The influence of magnesium on the surface finish of functionally graded composite at the wire cut electric discharge machining (WEDM) zone is predicted using a machine learning‐based random forest regressor (RFR) algorithm. The supervised learning algorithm declares that 10.5 wt% of Mg facilitates the minimal surface roughness of 0.229 µm with the optimal combination of parameters 6 A of current, 115 µs of pulse‐on time, 60 µs of pulse‐off time, and 8 N of wire tension.

SELECTION OF OPTIMAL TECHNOLOGICAL PARAMETERS FOR FORMING NOMINALLY FLAT SURFACES WITH LUBRICATING MICROCAVITIES

This article demonstrates a multi-step process for forming a nominally flat surface with circumferential lubricating microcavities on a tribological assembly of an Х38CrSi steel shaft. The process includes finish turning, preliminary strengthening burnishing, deformation profiling of microcavities by a honing stone and smoothing of microprotrusions. The study determines the optimal technological parameters for each of the transitions based on microhardness and oil absorption power maximization, as well as roughness and periodic impact minimization. The process optimization is conducted using the Tagichi experiment design method. The optimal combination of technological parameters for hardening burnishing was discovered to be: normal force F = 200 N; feed rate f = 0.025 mm/rev and three tool passes. These burnishing parameters practically eliminate the influence of periodic impacts at spatial frequencies determined by the tool feed rate and the number of spindle rotations during turning. We determined suitable honing stone grit parameters and application force that yield microcavities 3.8 to 8.1 μm in depth, as well as the optimal parameters for smoothing of microprotrusions, resulting in a bearing area roughness of Sa = 0.15 µm and oil absorption power of 13.74×10–5 mm3/mm2.

Experimental Study on Factors Influencing the Efficiency of Hot Water Injection in Offshore Heavy Oil Reservoirs

Abstract In response to the problem of low final recovery rate in conventional water flooding development of offshore heavy oil, the Bohai LD5 heavy oil field was taken as the target area. Through one-dimensional oil displacement efficiency experiments, the influence of crucial injection and production parameters on oil displacement efficiency, such as temperature, injection rate, injection production ratio, timing of hot water flooding, and injection medium, was studied. The key injection and production parameters were optimized, and the main controlling factors affecting the efficiency of hot water flooding after water flooding were identified through data analysis. Propose an optimization approach for thermal injection media and quantitatively evaluate the oil recovery efficiency under different injection and production parameters. Research has shown that for the Bohai LD5 heavy oil field, the optimal combination of injection and production parameters is: an injection rate of 2mL/min, injection temperature of 110°C, and timing of conversion to flooding at a recovery rate of 20% to 30% (water content of 55% to 70%). The hot water composite flue gas has the best oil recovery effect, considering both oil recovery efficiency and on-site construction conditions. The degree of influence of various factors on the efficiency of hot water flooding is as follows: temperature>timing of hot water flooding (recovery degree)>injection rate. Under low temperature (within 110 °C) conditions, temperature is the main factor affecting the efficiency of hot water flooding. The overall recovery rate of different injection media shows a trend of hot water composite>hot water>cold recovery.

Best practices for machine learning strategies aimed at process parameter development in powder bed fusion additive manufacturing

AbstractThe process parameters used for building a part utilizing the powder-bed fusion (PBF) additive manufacturing (AM) system have a direct influence on the quality—and therefore performance—of the final object. These parameters are commonly chosen based on experience or, in many cases, iteratively through experimentation. Discovering the optimal set of parameters via trial and error can be time-consuming and costly, as it often requires examining numerous permutations and combinations of parameters which commonly have complex interactions. However, machine learning (ML) methods can recommend suitable processing windows using models trained on data. They achieve this by efficiently identifying the optimal parameters through analyzing and recognizing patterns in data described by a multi-dimensional parameter space. We reviewed ML-based forward and inverse models that have been proposed to unlock the process–structure–property–performance relationships in both directions and assessed them in relation to data (quality, quantity, and diversity), ML method (mismatches and neglect of history), and model evaluation. To address the common shortcomings inherent in the published works, we propose strategies that embrace best practices. We point out the need for consistency in the reporting of details relevant to ML models and advocate for the development of relevant international standards. Significantly, our recommendations can be adopted for ML applications outside of AM where an optimum combination of process parameters (or other inputs) must be found with only a limited amount of training data.

Experimental study on spheroidal morphology of palladium coated copper wire with different palladium layer thickness

Palladium (Pd) coated copper (PCC) wire is an emerging bonding wire that has been widely researched. In this paper, the effects of electronic flame-off (EFO) current and EFO time on the free air ball (FAB) morphology of four PCC wires with Pd layer thicknesses of 60, 80, 100, and 120 nm, respectively, are first investigated. The larger the EFO current or the longer the EFO time, the larger the FAB diameter. The EFO time or EFO current setting is either too high or too low to form a FAB with good morphology. Taking the ratio of FAB diameter to wire diameter as 2 as the standard, the EFO current of 48 mA and the EFO time of 700 μs are selected as the optimal EFO parameter combination. Under this parameter combination, the symmetry, roundness, and surface smoothness of the FAB of the four PCC wires are all at a better level. It is found that the FAB surface Pd coverage of PCC wire with 120 nm Pd layer thickness is higher through the corrosion test. The Pd transfer law on the FAB at different EFO times under optimal EFO current is also studied. The results show that with the prolongation of the EFO time, the Pd on the FAB surface is gradually transferred from the neck to the middle and lower parts. This study can provide technical reference for the selection of Pd layer thickness and EFO parameters of PCC wire.

Large amplitude and small size ultrasonic milling for BT40 tool holders

Abstract The current ultrasonic milling tool holders are relatively long in structure, and the tool is susceptible to generating detrimental radial vibrations during high-speed rotation. To achieve high-quality milling of difficult-to-machine materials, a longitudinal-torsional ultrasonic oscillator suitable for BT40 tool holders has been proposed, which can generate a large amplitude while maintaining a compact length. A longitudinal vibration ultrasonic transducer with an exponential front cover is designed using the analytical method. Based on the principle of acoustic wave reflection, four spiral grooves are introduced on the exponential variable cross-section bar to convert the longitudinal vibration into longitudinal-torsional composite vibration. The effects of groove width, groove depth, and spiral angle on the longitudinal-torsional resonance were analyzed using the single-factor method in finite element software, and the optimal spiral groove parameter combination was determined. The longitudinal-torsional ultrasonic transducer is assembled with the BT40 tool holder to construct a longitudinal-torsional ultrasonic tool holder model, and modal analysis was performed. The resonant frequency was determined to be 22, 845 Hz. An experimental platform was established to carry out impedance analysis and amplitude testing on the longitudinal-torsional ultrasonic tool holder. The results show that its resonant frequency is 22, 152 Hz, which is slightly different from the simulation value. The tool holder’s maximum longitudinal amplitude is 11.2 μm, and the maximum torsional amplitude is 4.3 μm, with a torsional-to-longitudinal ratio of 0.38. The performance of the longitudinal-torsional ultrasonic tool holder meets the processing requirements of most ultrasonic milling applications, and the correctness of the design method is verified.

Discrete element parameter calibration during cottonseed crushing process

In order to address the current deficit in research on discrete elements within the context of the cotton seed pressing process, a combination of physical tests and simulation experiments were conducted on Xinluzao 84 cottonseed. The Plackett-Burman experimental design was employed to identify the parameters that had a significant impact on the accumulation angle. Subsequently, the Box-Behnken design was employed to establish a second-order regression model for the accumulation angle and the significant parameters. This resulted in the optimal parameter combination for the maximum friction coefficient, minimum sliding friction coefficient and critical shear stress being 0.207, 0.388, and 5×10⁶ Pa, respectively. In order to calibrate the cottonseed bonding parameters, a Box-Behnken test was designed based on the results of the cottonseed particle crushing test. The optimal parameter combinations of normal stiffness, tangential stiffness, and bond radius were obtained as 1.25×10⁹ N/m², 7.57×10⁸ N/m², and 0.727 mm, respectively. The obtained parameters were verified by the simulation of stacking angle and the crushing test simulation. The relative error was 0.84% and 0.46%, respectively. This serves to validate the cottonseed bonding model and simulation parameters, thereby providing a foundation for optimising the core structural parameters of the cottonseed shelling machine.

Different origins of magnetic disturbances during substorm growth and expansion phases and insufficiency of the AL index as their sole measure

The paper examines the relationship between the PC index, characterizing the solar wind energy input into the magnetosphere, and the AL index, characterizing the magnetic substorm intensity for the expansion phase of isolated substorms recorded in 1998–2017. Magnetic disturbances in the course of the expansion phase are produced by the DP11 current system with a powerful westward electrojet disposed in the midnight auroral zone. It is generally accepted that this electrojet is generated by the “substorm current wedge” system of fieldaligned currents (SCW FAC) providing closure of the magnetotail plasma sheet currents through the auroral ionosphere. As this takes place, magnetic disturbances in the course of the substorm growth phase are produced by the DP12 current system with westward and eastward electrojets located, correspondingly, in the morning and evening sectors of the auroral zone, with the electrojets generated by the R1/R2 FAC system operating in the inner (closed) magnetosphere. The intensity of R1 currents is determined by the “coupling function” EKL, which represents the optimal combination of all geoeffective solar wind parameters affecting the magnetosphere. The DP2 magnetic disturbances generated by the R1 FAC system in polar caps forms the basis for estimating the PC index, which strongly follows the EKL field changes and correlates well with the development of magnetic substorms. Analyses performed in AARI revealed the principally distinctive character of the relationships between the PC index and AL index in the course of the substorm growth (DP12 disturbances) and explosive (DP11 disturbances) phases. The DP12 disturbances, generated by FAC systems in the closed magnetosphere, are developed in strong relation to the PC index. The DP11 disturbances, generated by the SCW FAC system, related to the magnetotail plasma sheet, show quite irregular character of relationship between the PC and AL values: the sudden jumps of the substorm intensity (ALpeaks) might occur, time and again, at any value of the PC index and with quite different delay times relative to sudden substorm onset. It means that the processes in the tail plasma sheet, leading to the formation of a “substorm current wedge” are determined by the state of the magnetotail plasma sheet itself. The solar wind influence (evaluated by the PC index) affects but does not control the processes in the magnetotail, unlike those in the inner magnetosphere. It should be noted in this connection that the intensity of magnetic DP12 and DP11 disturbances, observed in the course of the substorm growth and explosive phases, is estimated by a single AL index, in spite of the different origin of these disturbances (R1/R2 and SCW FAC systems). It is necessary to employ two separate indices characterizing DP12 and DP11 disturbances in order to allow for the effects of the solar wind on the processes in the inner magnetosphere and in the magnetotail.

Preparation, Mechanical and Thermal Insulation Properties of Graphene Oxide/Polydopamine/Polyurethane Foam‐Based Tunnel Insulation Liner Material

This article designs a novel tunnel insulation liner material based on polyurethane foam (PUF), aiming to improve the liner material's mechanical properties, hydrophobicity, thermal insulation properties and to reduce the self‐weight of the material. Firstly, PUF is self‐made using a one‐step method, and the optimal parameter combination is optimized through the single‐parameter (SP) method. Secondly, based on the optimal parameter combination of PUF, a new process is employed to prepare polydopamine (PDA)/graphene oxide (GO)/PUF. Compression experiments and contact angle tests are conducted to assess the physical mechanical properties of PDA/GO/PUF. Infrared thermography and combustion experiments are employed to characterize the thermal insulation performance of PDA/GO/PUF. Microscopic mechanisms are explained through thermogravimetric analysis (TG), scanning electron microscopy (SEM), and Fourier‐transform infrared spectroscopy (FTIR). The results show that: the optimal parameter combination of tin(II) bis(2‐ethylhexanoate) (TEH), water (H2O), and toluene‐2,4‐diisocyanate (TDI) content optimized by the SP method is 4 parts, 2.8 parts, and 19 parts. PUF prepared based on the optimal parameter combination exhibits a dense and uniform cell structure with low density. Under cyclic loading, PDA/GO/PUF composite material exhibits excellent mechanical stability and fatigue resistance; the hydrophobicity, thermal insulation, and thermal stability of PDA/GO/PUF are significantly improved compared to PUF.