Injection molding process control, a vital technology in modern manufacturing, has seen substantial advancements in recent years through the integration of Computer-Aided Engineering (CAE) technology and intelligent optimization algorithms. CAE technology plays a crucial role in optimizing process parameters and mold design by simulating key behaviors in the injection molding process, including flow, cooling, shrinkage, and warpage. However, complex process conditions and nonlinear material behaviors pose limitations on the control precision and real-time performance of traditional CAE methods. To address these challenges, intelligent optimization algorithms—such as machine learning, Genetic Algorithms (GAs), and neural networks—have been introduced into the field of injection molding process control, enhancing the accuracy and efficiency of parameter prediction, defect detection, and adaptive control. This paper reviews recent advancements in the application of CAE technology within injection molding, alongside developments in intelligent algorithms for process optimization, parameter control, and predictive model construction. We further discuss the impact and future trends of combining CAE technology and intelligent algorithms on injection molding process control.

To address the oil and gas industry’s need for soluble bridge plug materials with enhanced mechanical and degradation properties, this study investigates the reinforcement of polyglycolic acid (PGA) composites with glass fiber (GF). Experiments were conducted to assess the effects of GF content on the rheological behavior, thermal properties, and microstructure of PGA/GF composites, as well as on their mechanical and degradation properties. Results indicate that incorporating 35 wt% GF into PGA composites enhances tensile, flexural, and impact strengths to 170.82, 560.23 MPa, and 12.44 kJ/m 2 , respectively—representing increases of 2.04, 3.15, and 4.73 times over pure PGA. However, GF addition slows the degradation rate of PGA/GF composites. To address this, zinc chloride (ZnCl 2 ) was introduced as a catalyst to accelerate degradation. Analysis of varying ZnCl 2 contents revealed that while ZnCl 2 does increase the degradation rate, it also diminishes mechanical strength, particularly at higher concentrations. At an optimal ZnCl 2 content of 0.1 wt%, PGA/GF/ZnCl 2 composites achieve the highest degradation rate improvement with minimal mechanical strength reduction.

Type IV hydrogen storage tank liners must exhibit optimal appearance, stiffness, and lightweight construction to maximize hydrogen storage density while also serving as a platform for carbon fiber winding. However, the inherent weakness in stiffness, particularly in larger structures, necessitates the incorporation of localized reinforcements. Internal rib reinforcement is a key strategy for addressing this challenge. This study analyzes the effect of circumferential ribs on the performance of PA6-based liners, demonstrating a significant increase in the critical buckling load by up to 15.2%. Furthermore, the study introduces a novel in situ, temperature-controlled rotational molding (ITRM) platform that enables the one-step creation of local inner reinforcements. By precisely controlling both the temperature and heating rates, we successfully manufactured a PA6 liner with stainless-steel inserts and three reinforcing ribs, achieving a volume exceeding 600 L. The ITRM platform represents a significant advancement in addressing the weak stiffness of large-capacity liners and offers promising potential for further innovation in liner development.Highlights Development of in situ temperature-controlled rotational molding equipment Analysis of the impact of the position and number of ribs on the structural stiffness Proposed inner circumferential ribs design method in liners to enhance stiffness Manufactured large-diameter and thin-walled PA6 liner with stainless-steel insert

This study conducts a finite element analysis (FEA) to assess the sealing performance of type IV hydrogen storage vessels, focusing specifically on the viscoelastic properties of the liner material. The analysis aims to quantify the impact of key parameters, including sealing interface design, O-ring pre-compression, and liner thickness, on overall sealing integrity. Through detailed modeling of the interactions among the metal boss, polymer liner, and sealing ring, the study shows that ignoring the viscoelastic response of the polymer liner can result in a significant underestimation of radial deformation, by a factor of 0.4-0.5. Furthermore, the increasing thickness of the liner wall in the vessel mouth area intensifies deformation within the sealing zone, thereby increasing the potential for leakage. The presence of an annular groove at the interface between the metal seat and polymer liner is critical for effective sealing, generating contact stresses that meet the operational requirements at 52 MPa. Moreover, the O-ring's sealing effectiveness is highly sensitive to the initial compression rate, achieving optimal performance at rates above 16%. These findings offer valuable insights for enhancing the reliability of component joints under high-pressure conditions, critical for ensuring the safety and operational efficiency of type IV hydrogen storage vessels.

Polyether ether ketone (PEEK) has significant potential for aerospace radar protective covers. However, limitations in the foaming rate hinder the production of low dielectric PEEK via the microcellular injection molding process. In this study, foamed PEEK was fabricated by mold-opening microcellular injection molding (MOMIM) process with supercritical fluid. The results demonstrated that the MOMIM process facilitates cell nucleation and growth, increases the foaming rate, and improves the cell structure of the products. With increasing moldopening distance, the crystallinity of the foamed products rises gradually (up to 37.72 %), while the weight loss rate significantly increases (up to 52.63 %). Higher porosity and crystallinity effectively reduced the dielectric constant of PEEK foams, enabling them to meet the requirements of low dielectric media. To meet the demands of various applications in extreme environments, this study assessed the performance of PEEK foams at high-temperature through mechanical testing at 200 degrees C. The results indicated that PEEK foams exhibit hightemperature mechanical stability comparable to solid PEEK. In summary, PEEK foams fabricated by the MOMIM process exhibit low dielectric while maintaining excellent mechanical properties and high-temperature mechanical stability. This opens new possibilities for the application of foamed PEEK materials in airborne radar protective covers.

Type IV hydrogen storage vessels, equipped with lightweight, thin plastic liners provide a cost-effective solution to enhance the storage density of large-capacity road transport tanks. However, during rapid depressurization, the plastic liner may collapse and debond from the CFRP, compromising the structural integrity and load-bearing capability of the vessel. To address this critical issue, this study develops an innovative finite element simulation framework that dynamically models the collapse behavior of the liner and interfacial debonding under rapid decompression. The model reveals the sequential progression of liner collapse, which involves initial buckling deformation, CFRP debonding, wrinkling, and eventual partial collapse, leading to structural failure. A comprehensive parametric study was conducted to assess the sensitivity of collapse pressure to various influencing factors. The results indicate that the onset of liner collapse is highly sensitive to initial geometric imperfections. Furthermore, for large-capacity Type IV hydrogen storage vessels, a liner thickness-to-diameter ratio of (w/D = 0.01) significantly improves the liner's resistance to collapse. These findings provide valuable insights into optimizing the design of hydrogen storage vessels to enhance safety and performance.Highlights Dynamic process of buckling-debonding-collapse failure of plastic liner. The collapse failure of plastic liner is highly sensitive to initial defects. Thickness to diameter ratio of 0.01 boosts collapse resistance of plastic liner.

The material in the mold of the injection-molding machine releases significant latent heat of solidification during the cooling process. The efficient recovery and utilization of this waste heat is crucial for improving energy efficiency. A novel integrated energy management system for mold cooling/heat pump/material preheating is proposed in this paper. Taking the symmetrical thermodynamic performance of the heat pump components as the basis and optimizing the system configurations, four system configurations were investigated: MC/BHP/MPCC, MC/RHP/MPCC, MC/HP/MP-IEMS, and MC/DCHP/MP-IEMS, utilizing EBSILON software. The performance of the systems was evaluated through the coefficient of performance (COP) and whole cycle energy efficiency (η). The T-q, T-s, and P-h diagrams were analyzed. It was found that, under comparative operating conditions, both the MC/HP/MP-IEMS and MC/DCHP/MP-IEMS systems exhibited significantly higher COP and η than the MC/BHP/MPCC and MC/RHP/MPCC systems. MC/HP/MP-IEMS achieves a COP of 13.66 and η of 22.09. Similarly, MC/DCHP/MP-IEMS achieves a COP of 14.00 and η of 22.53. The paper optimizes the other three systems using MC/BHP/MPCC as the comparison condition. Optimal cycle performances are achieved with COP and η values of 9, 16, 16, and 9, 26, 25, respectively. A comparison of the thermodynamic performance of five different refrigerants revealed that R123 and R245fa have superior overall performance. This study provides theoretical support for the engineering implementation of integrated energy management systems for injection-molding machines.

High-strength and high-gas-barrier plastic packaging liners have emerged as competitive products with promising potential application in the field of Type IV hydrogen storage cylinders. Ternary composites, which contain PA6, organically modified montmorillonite (OMMT), and maleic anhydride grafted polyolefin elastomer (POE-g-MAH), have been proposed as possible material for this application. To achieve the goal of developing this material, the influence of material formulation on various properties such as mechanical, microstructure, gas barrier, thermal stability, and flow properties of the composites was investigated. The results show that the composites with 3 wt% OMMT had the best gas barrier and mechanical properties. Additionally, the effect of rotational molding process parameters on the wall thickness of the plastic liner was studied. Process parameter regulation methods were proposed to improve wall thickness consistency of the products. The investigation shows that the composites containing 3 wt% OMMT had the best wall thickness consistency of the products.

Non-return valve (NRV) is one of the key components in determining the consistency of the quality of the products molded by injection molding machine. Wear on the NRV affects the quality of the molded product. Nevertheless, detecting wear on the NRV can be challenging and disassembly of the machine is the only diagnostic method, which can have a negative impact on productivity. In this paper, a data-driven fault diagnosis method is proposed, which uses Stacked Auto Encoder (SAE) to analyze the pressure, torque, and displacement signals of the injection molding machine and combined with XGBoost (Extreme Gradient Boosting) to diagnose the faults of the NRV. The experimental results indicate that the SAE-XGBoost method accurately predicts NRV failures. Compared to using only XGBoost for prediction, the accuracy has improved from 97.5% to 99.6%. Eventually, the SAE-XGBoost model is integrated into the control program of the injection molding machine in the form of functional modules. Throughout the production process, the model adeptly monitors and identifies the production profile, promptly dispatching warning messages to users when diagnosing NRV wear. This facilitates intelligent diagnosis of the service status of injection molding machine components, which will have a positive influence on improving the production efficiency and intelligence of injection molding machines. The results of this study represent a synergistic application of artificial intelligence and time-domain statistical features in the realm of fault diagnosis for injection molding machines. This has the potential to significantly broaden the scope of AI utilization within the domain of injection molding processes, thereby advancing the intelligent technology associated with injection molding machines.

Injection molding is one of the most important polymer processing methods, and the traditional injection molding process cannot meet the high repeatability requirements necessary for the production of optical lenses. The impact of melt flow behavior and non-return valve closing behavior on injection molding repeatability is studied in this paper. A strategy of adjusting the closure behavior of the non-return valve is proposed, which can improve the repeatability of injection molding without the need for specific modifications to the injection molding machine. In this paper, variables such as the reversal action, reversal speed, forward movement action, and forward speed of the screw were investigated. It was found that the reversal action and forward movement action had the most significant impact on the closure stability of the NRV. Through the implementation of this process, injection molding repeatability can reach 0.019

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Investigation of Wall Thickness Design Method of Anti-Buckling Liner of Type IV Hydrogen Storage Tanks 14 Pages Posted: 24 Feb 2024 See all articles by Xiulei WangXiulei WangBeijing University of Chemical TechnologyYaoyi DuBeijing University of Chemical TechnologyYan ZhaBeijing University of Chemical TechnologyYitao MaBeijing University of Chemical TechnologyJinzhao XieBeijing University of Chemical TechnologyPengcheng XieBeijing University of Chemical TechnologyWeimin YangBeijing University of Chemical Technology Abstract The plastic liner is a key component of Type IV hydrogen storage tanks, which are lightweight and resistant to hydrogen embrittlement. The liner's structural design technique, however, remains uncertain. The liner's major dimensions are determined by the installation space of the tanks, the water capacity of each tank, and the CFRP winding requirements. The thickness of the liner wall, which directly affects the tank's service performance and hydrogen density, is determined through empirical or passive cycle verification and testing procedures. The design expenses increase, and more constraints need to be fulfilled. Using a 52 MPa hydrogen storage tank as an example, the study examines current mainstream wall thickness assessment methods, tests representative data, and develops a minimum permissible theoretical wall thickness calculation method by considering the correlation between the liner and the CFRP in discharge buckling failure. Keywords: Type IV hydrogen storage tanks Liner, Wall thickness, Buckling, Permeability Coefficient, Carbon fiber reinforced composites, Pressure Suggested Citation: Suggested Citation Wang, Xiulei and Du, Yaoyi and Zha, Yan and Ma, Yitao and Xie, Jinzhao and Xie, Pengcheng and Yang, Weimin, Investigation of Wall Thickness Design Method of Anti-Buckling Liner of Type IV Hydrogen Storage Tanks. Available at SSRN: https://ssrn.com/abstract=4737797 Xiulei Wang Beijing University of Chemical Technology ( email ) 15 N. 3rd Ring Rd EChaoyang, Beijing, 201204China Yaoyi Du Beijing University of Chemical Technology ( email ) 15 N. 3rd Ring Rd EChaoyang, Beijing, 201204China Yan Zha Beijing University of Chemical Technology ( email ) 15 N. 3rd Ring Rd EChaoyang, Beijing, 201204China Yitao Ma Beijing University of Chemical Technology ( email ) 15 N. 3rd Ring Rd EChaoyang, Beijing, 201204China Jinzhao Xie Beijing University of Chemical Technology ( email ) 15 N. 3rd Ring Rd EChaoyang, Beijing, 201204China Pengcheng Xie (Contact Author) Beijing University of Chemical Technology ( email ) 15 N. 3rd Ring Rd EChaoyang, Beijing, 201204China Weimin Yang Beijing University of Chemical Technology ( email ) 15 N. 3rd Ring Rd EChaoyang, Beijing, 201204China Download This Paper Open PDF in Browser Do you have negative results from your research you’d like to share? Submit Negative Results Paper statistics Downloads 0 Abstract Views 9 28 References PlumX Metrics Feedback Feedback to SSRN Feedback (required) Email (required) Submit If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday.

In this work, honeycomb-like SiOx coating was successfully prepared on steel surface by atmospheric pressure low temperature plasma jet. The surface morphology, corrosion resistance and stability of the coating were systematically analyzed. In addition, the growth mechanism of the coating was discussed. The analysis revealed that the coatings were primarily composed of Si-O-Si and Si-OH groups, with a minor presence of Si-CH3 moieties. The coating obtained after two deposition cycles exhibits the highest level of uniformity and density, with minimal porosity and superior corrosion resistance. The increase in deposition cycles led to particle aggregation, augmented particle dimensions and porosity, which adversely affected the coating's performance. The dense SiOx coating resulted in a significant reduction in the corrosion current density of the alloy steel, and showed no significant corrosion defects when exposed to the crude oil simulant in 25 C-o. The coating simultaneously enhanced the hydrophilicity and oil transfer of the steel surface. Finally, the coating exhibited self-cleaning properties, stability and high potential for safeguarding steel pipes against low-viscosity crude oil contamination. This study provides a general surface modification method for the preparation of corrosion-resistant coatings on metal surfaces under mild conditions.

In this study, a desktop-class dual-axis rotational molder was employed to mold PA6 products. Notably, the morphology of the plastic powder during the rotational molding process was examined through visualization techniques. The research also aimed to delineate the causes of wall thickness variation in the products, while proposing a process method to enhance the uniformity of wall thickness. The implementation of a two-stage mold temperature setting method for the ends of the mold improved wall thickness uniformity of the products. Furthermore, the interrelationships between crystallinity, tensile strength, and impact strength of the products were explored by comparing different cooling rate conditions. Increasing the cooling rate resulted in a decrease in both crystallinity and tensile strength, while concurrently boosting the impact strength of the products.Highlights A desktop-class, two-axis rotational molding equipment is designed. A method for visualizing the rotational molding process is conducted. Mold temperature and rotational speed affect product wall thickness. Two-stage mold temperature improves wall thickness uniformity. Mold cooling rate affects the tensile and impact strength of the product.

AbstractPolymers are advantageous in increasing hydrogen storage density of tanks due to their lightweight. Moreover, a uniform aggregate structure can enhance their advantages. However, achieving such as structure solely through screw extrusion can be challenging in liner moldings. This study reported a micro‐nano torsional laminated extrusion equipment that can be used before the die to effectively improve the composite orientation and reduce intercrystalline defects through divides, laminated thinning, and biaxial stretching of the melt with a strong drag flow field. The resulting HDPE/PA6 achieved a reduced helium permeation coefficient by up to 20.1% with a more pronounced effect on the diffusion than that on the dissolution. The mechanical property tests demonstrated an improvement in strength by up to 24.5% and modulus by up to 49.1% with the expanded range of toughness fracture. However, PA6 and HDPE exhibited limitations in terms of the moldable size and storage ability owing to their melt strength and gas barrier properties, respectively. Based on the analysis of the melt strength thresholds of HDPE/PA6, the PA6 content in the composites should be <70 wt% for blow molding and <50 wt% for welding. This study provides a novel approach for forming large‐diameter and thin‐walled liner billets through extrusion and welding.

Injection molding (IM) is one of the most essential forming methods for plastics. However, some potential risks which influence part quality may occur in the molding process. A non-return valve (NRV) is a major component on the screw head whose function is to seal during the injection process to prevent the backflow of the melt. The NRV will wear in this process and cause fluctuations in parameters and quality but the wear states of NRVs cannot be monitored without the disassembly of the injection barrel. In this study, we proposed an optimization method to compensate for the wear damage of the NRVs. The V/P switchover point in each molding cycle was recalculated and output to stabilize the part quality. As a result, the wear damage of the NRV on the current machine was able to be predicted and the part quality could be initially optimized in the condition that the NRV had a degree of wear. The experimental results reveal that our proposed compensation algorithm can monitor the type of wear of NRV online, and at the same time, it can compensate the axial wear of NRV and finally improve the consistency of product weight, which established a fundamental for further research in the future.

塑料机械是现代制造业的"生产母机",塑机行业同时也是高分子材料产业链中资金密集、人才密集和技术密集的"钻石产业".为满足我国高速发展的塑料机械行业对于高端专业人才的迫切需求,探索建立企业高度参与的创新人才培养新模式,中国塑料机械工业协会与北京化工大学启动"中国塑机创新专业人才培养计划",建设"中国塑机创新人才培养基地".该教学实践针对机械设计制造及其自动化学科,以创新应用性强的机械创新设计课程为例,依托于"中国塑机创新人才培养基地"多种多样的工程教育资源,以注塑机"五点斜排肘杆式"注塑机合模机构的方案创新设计为题,应用项目化教学方法,在理论教学的同时,使学生们带着工程实践问题进行学习、思考、分析和研究,鼓励学生将多门机械类专业基础课程所学知识进行创新结合与灵活运用,有效地促进学生们创新创造能力的发展,探索培育应用型创新人才的新模式.

针对新工科建设背景下机械类专业实践教学现状及存在的问题,根据现代制造业高速发展对工科人才实践创新能力培养的新要求,北京化工大学提出了实践教学从金工实习向高工实习转型升级的新思路,制定了高工实习的基本手段和实施方案,分析了高工实习的实施情况及效果.教学实践表明,高工实习的开展能有效提升工程人才培养的内驱力,实现工程实践教育的良性循环.

Conductive polymer composites (CPCs) have demonstrated significant potential in the aerospace, electronics, and communications industries. In this study, polypropylene (PP)/multiwalled carbon nanotubes (MWCNTs) binary composites and in situ fiber reinforced multicomposites made from PP/MWCNTs were fabricated by microcellular injection molding. In addition to crystallization behavior, foam morphology, mechanical properties, dielectric properties, and electromagnetic shielding properties of the composites were analyzed. According to the results, microporous structures can facilitate the distribution of conductive fillers, thereby enhancing the electromagnetic shielding performance and mechanical properties of the composite. In situ microfiber networks display a heterogeneous nucleation effect, resulting in an increase in foam density, which improves composite performance. In situ fiber-reinforced microporous multicomposites are capable of exhibiting higher elongation at break and electromagnetic shielding properties than binary systems, and the multicomposites can achieve greater electromagnetic shielding effectiveness (SE) with fewer conductive fillers. Ultimately, fiber-reinforced microporous composites with an elongation at break of 194.40%, an electromagnetic shielding effect of > 20 dB, and an absorption mechanism are produced. A feasible method is presented in this study for preparing CPCs that produce light weight, excellent mechanical properties, and high electromagnetic SE at low filler levels.

The metal-plastic combination is widely used in frontier fields such as energy storage technology and aerospace. This study proposes two metal surface treatment processes for metal-plastic composite injection molding. The first only involves the chemical treatment, whose interfacial bonding strength reaches 10.24 MPa. In the second, the plasma treatment is added to the chemical treatment process to increase the interface bonding strength to 17.58 MPa. The characterization result shows that the plastic is injected into the undercut microstructures to form a physical bolting force due to the countless microstructures after the metal surface treatment. Through the step-by-step study of the surface treatment process, it is found that hydrochloric acid solution causes a large-scale microstructure to appear on the metal surface, and the undercut nanostructure is obtained through the plasma treatment. This multilevel microporous undercut structure of micro-nano bonding is beneficial to the formation of physical bolting force at the interface, thereby achieving high bonding strength of the interface. At the same time, we also confirmed the relationship between the injection process, annealing parameters, and interfacial bonding strength. When the plastic was injected into the multilevel microporous undercut structure at an injection pressure of 110 MPa and annealed at 110 degrees C for 4 h after molding, the maximum interface bonding strength of 17.58 MPa would be obtained. This process provides a new solution for engineering applications in metal-plastic bonding.

In this research, a recommendation system was designed for optimizing the injection molding process parameters. The system incorporates the utilization of process windows, eXtreme Gradient Boosting (XGBoost), and genetic algorithms. Computer-aided engineering (CAE) simulations were conducted to generate process window data and simulation data. Automatic hyperparameter optimization of the XGBoost was performed using grid search and cross-validation methods. The system employs 5 injection molding feature parameters as input and one product feature as output, and the strengthen elitist genetic algorithms (SEGA) was used for predicting the optimal injection molding process parameters. The performance of the prediction model was evaluated using an RMSE of 0.0202 and an R 2 of 0.9826. The accuracy of the system was verified by conducting real production. The deviation of the product weight obtained from real production from the desired weight is 0.22%, which means that the prediction model achieves a correct rate of 99.78%. This recommendation system has a significant application value in reducing production costs and cycle time, as it can provide initial injection process parameter suggestions solely through the mold’s digital data.