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Melt-casting parameters optimization of energetic materials for minimizing shrinkage and solidification time via adaptive clustering local Kriging and NSGA II-MOHHO 基于自适应聚类局部Kriging和NSGA II-MOHHO的含能材料熔铸参数优化研究
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-28 DOI: 10.1016/j.jmapro.2026.01.068
Xiaocheng Tian , Yufeng Li , Youshuo Zhang , Yan He
Optimizing the process parameters of the melt-casting solidification process for energetic materials (MCSPEM) is crucial for improving the quality and efficiency of melt-casting forming systems. The influence of melt-casting process parameters on shrinkage volume (SV) and solidification time (ST) exhibited a highly nonlinear correlation, with significant interactive effects among variables. However, existing process parameters control primarily relies on manual experience, lacking quantitative characterization and co-optimization of MCSPEM parameters concerning SV and ST, leading to inconsistent quality and low efficiency. Therefore, this paper proposed a multi-objective optimization approach to identify the optimal MCSPEM parameters based on adaptive clustering local Kriging (ACLK) and NSGA II-MOHHO algorithm. Firstly, the nonlinear associations of MCSPEM parameters (i.e., pouring temperature, mold preheating temperature, riser insulation temperature and time, jacket insulation temperature and time) with SV and ST were accurately established using the ACLK model. Secondly, a bi-objective optimization model involving SV and ST was established under the process constraints. Thirdly, a hybrid NSGA II-MOHHO algorithm was developed to tackle the bi-objective optimization model, integrating NSGA II's strengths in solution diversity with MOHHO's advantages in adaptive exploration-exploitation switching. Finally, the EWM-TOPSIS method was applied to obtain the optimal MCSPEM parameters from the Pareto front. Case results show that compared with the empirical scheme, the proposed method reduced SV and ST by 54.02% and 16.68%, respectively. This method can recommend the optimal configuration of MCSPEM process parameters and provide quantitative SV and ST information to guide technicians in accurately optimizing and controlling forming defects and efficiency.
优化含能材料熔铸凝固工艺参数对提高熔铸成形系统的质量和效率至关重要。熔铸工艺参数对收缩体积(SV)和凝固时间(ST)的影响呈高度非线性相关,变量之间存在显著的交互作用。然而,现有的工艺参数控制主要依靠人工经验,缺乏对SV和ST的MCSPEM参数的定量表征和协同优化,导致质量不一致,效率低。为此,本文提出了一种基于自适应聚类局部Kriging (ACLK)和NSGA II-MOHHO算法的多目标优化方法来识别最优MCSPEM参数。首先,利用ACLK模型精确建立了MCSPEM参数(浇注温度、模具预热温度、冒口保温温度和时间、夹套保温温度和时间)与SV和ST之间的非线性关系。其次,在工艺约束下建立了SV和ST的双目标优化模型;第三,结合NSGA II在解多样性方面的优势和MOHHO在自适应探索开发切换方面的优势,提出了一种NSGA II-MOHHO混合算法来解决双目标优化模型。最后,应用EWM-TOPSIS方法从Pareto前沿得到最优MCSPEM参数。实例结果表明,与经验方案相比,该方法分别减少了54.02%的SV和16.68%的ST。该方法可以推荐MCSPEM工艺参数的最优配置,并提供定量的SV和ST信息,指导技术人员准确优化和控制成形缺陷和效率。
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引用次数: 0
Machine learning prediction of recoater damage topography deviations 重涂器损伤形貌偏差的机器学习预测
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-28 DOI: 10.1016/j.jmapro.2026.01.060
Caroline E. Massey , Christopher J. Saldaña
In-situ monitoring in laser powder bed fusion (PBF-LB) presents a paradigm for progress towards born qualified parts. This technology has proven useful in many applications such as monitoring for geometric error, layer-wise part defects, and spreading defects. The significance of spreading defects is particularly understudied, especially in the experimental domain. Recoater damage can be particularly detrimental to mechanical performance, as it lends to topography deviations in the build, which could cause porosity, geometric inaccuracies, and potential build failure. Yet, prior literature has not addressed machine learning's ability to predict the severity of recoater damage. This work used multiple feature-based and image-based machine learning algorithms combined with in-situ layer-wise monitoring to predict the amount of topography deviation within recoater damaged sections. The height and width of the topography deviations were measured after the spread profile was exposed to multiple different sizes of recoater wear at different recoater spread speeds and layer thicknesses. The acquired images had different image filtering methods applied to see if a particular image filtering method can increase prediction performance. Ultimately, the image-based machine learning methods showed the best performance when combined with noising filters. In all, this work seeks to find the ideal configuration for the prediction of topography height and width deviations when the powder bed is exposed to recoater damage.
激光粉末床熔合(PBF-LB)的现场监测为生产合格零件提供了一种范式。该技术已被证明在许多应用中是有用的,例如监测几何误差、分层零件缺陷和扩展缺陷。对于扩展缺陷的重要性,特别是在实验领域的研究尤其不足。重接器损坏对机械性能尤其有害,因为它会导致构造中的地形偏差,从而导致孔隙度、几何不精确和潜在的构造失败。然而,之前的文献并没有提到机器学习预测重涂器损伤严重程度的能力。这项工作使用了多种基于特征和基于图像的机器学习算法,并结合现场分层监测来预测重涂器损坏截面内的地形偏差量。在不同涂布速度和涂布层厚度下,涂布轮廓暴露于多种不同尺寸的涂布磨损后,测量了形貌偏差的高度和宽度。获取的图像采用不同的图像滤波方法,以观察特定的图像滤波方法是否可以提高预测性能。最终,基于图像的机器学习方法在与噪声滤波器相结合时表现出最佳性能。总之,这项工作旨在找到理想的配置,以预测地形高度和宽度偏差,当粉末床暴露在重涂器损坏。
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引用次数: 0
An unsupervised welding quality detection method based on high-quality condition-guided diffusion reconstruction 基于高质量状态引导扩散重构的无监督焊接质量检测方法
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-27 DOI: 10.1016/j.jmapro.2026.01.059
Xin Chen , Bin Zi , Kai Tang , Wenjun Tang , Yuan Li
Radiographic testing of welds plays a critical role in ensuring the quality of welded manufacturing, because X-ray imaging technology can clearly reveal the internal structure of the weld area. However, existing mainstream detection methods rely on manual inspection or supervised detection, both of which are susceptible to limitations imposed by subjective factors and model generalization capabilities, respectively. Therefore, this paper proposes a two-stage unsupervised detection framework based on reconstruction to achieve fast and accurate detection of welding quality. First, an algorithm for generating simulated defects based on real welding defect characteristics is designed. A dataset encompassing multiple defect types is constructed, and image quality is further optimized through data augmentation algorithms. Second, a high-quality diffusion model (H-DiffuM) based on residual learning is proposed, which achieves accurate reconstruction of weld defect images through a residual-guided noise scheduling mechanism. Finally, by combining the gated mechanism with frequency domain features of X-ray images, a multi-scale frequency domain attention fusion module (MFDAFM) is designed and embedded into the discriminative network (Seg-net), thereby enhancing detection accuracy. The final experimental results demonstrated that the proposed method achieved 97.80% in pixel-level AUROC and 93.34% in AP, which surpassed the current state-of-the-art unsupervised detection approaches. Meanwhile, the inspection method described in this paper offers the advantages of rapid detection speed and high precision, demonstrating its potential for application in the rapid assessment of welding quality.
焊缝的射线检测对于保证焊接制造质量起着至关重要的作用,因为x射线成像技术可以清晰地显示焊缝区域的内部结构。然而,现有的主流检测方法依赖于人工检测或监督检测,这两种方法都容易受到主观因素和模型泛化能力的限制。为此,本文提出了一种基于重构的两阶段无监督检测框架,以实现对焊接质量的快速准确检测。首先,设计了一种基于实际焊接缺陷特征的模拟缺陷生成算法。构建了包含多种缺陷类型的数据集,并通过数据增强算法进一步优化了图像质量。其次,提出了一种基于残差学习的高质量扩散模型(H-DiffuM),该模型通过残差引导的噪声调度机制实现焊缝缺陷图像的精确重建。最后,将门控机制与x射线图像的频域特征相结合,设计了多尺度频域注意力融合模块(MFDAFM),并将其嵌入到判别网络(Seg-net)中,从而提高了检测精度。最终的实验结果表明,该方法在像素级AUROC上达到97.80%,在AP上达到93.34%,超过了目前最先进的无监督检测方法。同时,本文所描述的检测方法具有检测速度快、精度高的优点,在焊接质量的快速评估中具有应用潜力。
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引用次数: 0
Femtosecond laser bonding of transparent polycarbonate: a study on the weld seam quality and strength 透明聚碳酸酯飞秒激光粘接:焊缝质量和强度的研究
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-27 DOI: 10.1016/j.jmapro.2026.01.070
Soheil Alee Mazreshadi , Pol Vanwersch , Tim Evens , Sylvie Castagne
Reliable bonding of transparent polymers is essential for microfluidic and biomedical devices. Ultrashort laser welding provides localized energy deposition with minimal heat-affected zones, but nonlinear absorption introduces challenges in achieving consistent weld quality. This study investigates femtosecond laser bonding of transparent polycarbonate using a 1030 nm source, focusing on the effects of fluence per pulse, scanning speed, and repetition rate. Two degradation mechanisms are identified: excessive cumulative fluence and high per-pulse fluence, both defining operational limits. At optimized fluence values, pre-focal absorption before the focus causes a focal offset between the intended and actual weld location. Even after refocusing on the interface, the gap between plates and the distorted beam profile produce a non-uniform fluence distribution, compromising weld quality. Simulations confirm that such offsets distort beam shape and fluence delivery. To overcome this, a low-fluence with high-overscan strategy is proposed, mitigating offset effects. Uniform welds are achieved at a repetition rate of 1 MHz with scanning speeds ranging from 10 to 30 mm/s and fluences of 0.08–0.17 J/cm², with more than five overscans. FTIR measurements are performed to monitor potential chemical changes in the bonded regions. The optimized process has a maximum shear strength of 30.2 ± 5 N/mm², corresponding to 48% of pristine polycarbonate. Weibull analysis identifies a highest modulus of 5.2, confirming process reliability. Devices withstand leakage tests up to 1 bar. This approach establishes a reproducible femtosecond welding strategy for transparent polymers, resulting in stronger, and more reliable fabrication of microfluidic and biomedical systems.
透明聚合物的可靠结合对于微流体和生物医学设备至关重要。超短激光焊接提供了局部能量沉积和最小的热影响区,但非线性吸收给实现一致的焊接质量带来了挑战。本研究使用1030nm光源研究透明聚碳酸酯的飞秒激光键合,重点研究了每脉冲影响、扫描速度和重复率的影响。确定了两种降解机制:过量的累积通量和高的每脉冲通量,两者都确定了操作极限。在优化的通量值下,焦点前的焦前吸收会导致预期和实际焊接位置之间的焦偏移。即使重新聚焦在界面上,板材之间的间隙和扭曲的光束轮廓也会产生不均匀的流量分布,从而影响焊接质量。模拟证实了这种偏移会扭曲光束的形状和能量的传递。为了克服这一问题,提出了一种低通量高过频策略,以减轻抵消效应。在1 MHz的重复频率下实现均匀焊接,扫描速度范围为10至30 mm/s,影响范围为0.08-0.17 J/cm²,超过5次扫描。FTIR测量用于监测键合区的潜在化学变化。优化工艺的最大抗剪强度为30.2±5 N/mm²,相当于原始聚碳酸酯的48%。威布尔分析确定了最高模量5.2,确认了过程的可靠性。设备可承受高达1bar的泄漏测试。这种方法为透明聚合物建立了一种可重复的飞秒焊接策略,从而产生更强、更可靠的微流体和生物医学系统制造。
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引用次数: 0
Integrating mechanism and data-driven approaches in pre-aged hardening warm forming: Performance prediction and process parameters deduction 预时效硬化热成形的综合机理与数据驱动方法:性能预测与工艺参数推导
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-27 DOI: 10.1016/j.jmapro.2026.01.075
Huijuan Ma , Xiaoying Wei , Peiliao Wang , Zhiang Gong , Zhili Hu , Lin Hua
Pre-aged hardening warm forming (PHF) technology enables precise control of process parameters, allowing pre-hardened sheet to achieve superior formability compared to the O-temper condition. During subsequent forming stages, this process utilizes synergistic control of deformation and phase transformation, enabling the final component to attain mechanical properties comparable to the T6 temper. By employing pre-hardened technology in conjunction with warm forming process, the post-forming solution heat treatment and aging steps can be eliminated, thereby significantly reducing the component manufacturing cycle. However, as an emerging technique, past experience has limited guidance on excavating the mechanism and deducting the parameters of PHF process. Here, the Long Short-Term Memory network (LSTM) model of 7075 aluminum alloy (AA7075) is firstly established, which innovatively facilitates bidirectional prediction between process parameters and mechanical properties. Crucially, a constitutive model of PHF process based on dynamic precipitation and dislocation strengthening is proposed, considering the direct phase precipitation from the solid solution and the inherited precipitation from GPII zones to η' phases based on microstructure characterization utilizing the HRTEM, DSC, SAXS and the XRD. Moreover, the accuracy of the LSTM model is further improved through a novel pre-training approach that assimilates knowledge from the AA7075 constitutive model, followed by fine-tuning with experimental dataset. Embracing a “mechanism + data” fusion-driven approach, the mechanical properties prediction and the process parameters deduction of high-strength aluminum alloy components formed under the PHF process are achieved. Additionally, rapid and accurate deduction of process parameters for 7050 aluminum alloy (AA7050) with similar phase evolution is realized by transfer learning from the AA7075 LSTM model using little experimental data. This study not only accelerates the development of higher-performance aluminum alloy components, but also establishes a foundational framework for swiftly determining the process window under the cooperative control of deformation and phase transformation.
预时效硬化热成形(PHF)技术可以精确控制工艺参数,使预硬化板材与o回火条件相比具有更好的成形性。在随后的成形阶段,该工艺利用变形和相变的协同控制,使最终部件获得与T6回火相当的机械性能。通过采用预硬化技术与热成形工艺相结合,可以消除成型后的固溶热处理和时效步骤,从而大大缩短了部件的制造周期。然而,作为一种新兴技术,以往的经验对于挖掘PHF工艺的机理和推导工艺参数的指导作用有限。本文首次建立了7075铝合金(AA7075)的长短期记忆网络(LSTM)模型,创新地实现了工艺参数与力学性能之间的双向预测。基于HRTEM、DSC、SAXS和XRD的微观结构表征,考虑了固溶的直接相析出和GPII区向η′相的继承析出,提出了基于动态析出和位错强化的PHF过程本构模型。此外,通过一种新的预训练方法,吸收AA7075本构模型的知识,然后与实验数据集进行微调,进一步提高了LSTM模型的准确性。采用“机制+数据”的融合驱动方法,实现了PHF成形高强铝合金构件的力学性能预测和工艺参数推导。此外,利用少量实验数据,通过对AA7075 LSTM模型的迁移学习,实现了相演化相似的7050铝合金(AA7050)工艺参数的快速准确推导。该研究不仅加速了高性能铝合金部件的开发,而且为快速确定变形与相变协同控制下的工艺窗口建立了基础框架。
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引用次数: 0
An error-controlled G3-continuous oriented toolpath optimization algorithm and modified speed planning for five-axis machining 误差控制的g3连续定向五轴加工刀路优化算法及修正速度规划
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-27 DOI: 10.1016/j.jmapro.2026.01.066
Tao Wu , Yong Zhang , Yongfei Wang , Bin Hu , Chen Li
Converting micro-segment toolpaths into high-order curves can significantly enhance the stability of five-axis CNC machining processes. However, conventional toolpath optimization approaches tend to simultaneously cause both undercutting and overcutting on the workpiece surfaces. Overcutting leads to irreversible morphological damage to the workpiece, thereby resulting in scrapped parts. Furthermore, the asynchronous variation between speed limit trends and speed planning curves undermines the effectiveness of conventional speed planning strategies in the machining of complex structural workpieces. To achieve effective control over machining stability and accuracy in five-axis CNC machining of complex workpieces, this work proposed an error-controllable G3-continuous oriented toolpath optimization algorithm. Based on the G3-continuous quartic symmetric Bezier curve, the toolpath was directionally offset according to the viewing-angle theorem. To ensure toolpath reachability, the Sobolev seminorm method and CVE method were subsequently employed to further optimize toolpath stability. Additionally, an enhanced speed planning strategy with an extra verification mechanism was designed. By incorporating adaptive quintic Gauss-Legendre quadrature and S-shaped speed model, a numerical model was established to characterize the relationships among curvature radius, arc length, and motion time. The activation conditions for the verification mechanism were derived using quartic non-uniform difference formulas. The secant method was applied to dynamically adjust local snap parameters of current toolpath segments for speed profile modulation. Five-axis machining experiments on dentures were conducted to validate the effectiveness of optimization algorithms. Experimental results demonstrated that, compared with traditional strategies, the modified toolpath optimization and speed look-ahead algorithms reduced machine tool vibration by 6.62% and 19.46%, respectively, while increasing dimensional compliance rates by 283.79% and 439.774%, respectively. This work successfully mitigates the challenges of overcutting, machine chatter, and accuracy drift in the five-axis CNC machining of complex structural components, thereby offering theoretical support for the development of high-precision and stable machining technologies for such components.
将微段刀具轨迹转换成高阶曲线,可以显著提高五轴数控加工过程的稳定性。然而,传统的刀具轨迹优化方法往往会同时引起工件表面的过切和下切。过切会对工件造成不可逆的形态损伤,从而导致零件报废。此外,速度限制趋势与速度规划曲线之间的异步变化破坏了传统速度规划策略在复杂结构工件加工中的有效性。为了有效控制复杂工件五轴数控加工的加工稳定性和加工精度,本文提出了一种误差可控的g3连续导向刀路优化算法。基于g3 -连续四次对称Bezier曲线,根据视角定理对刀具轨迹进行方向偏移。为了保证刀具路径的可达性,随后采用Sobolev半正规方法和CVE方法进一步优化刀具路径的稳定性。此外,设计了一种具有额外验证机制的增强速度规划策略。结合自适应五次Gauss-Legendre正交和s形速度模型,建立了曲率半径、弧长和运动时间之间关系的数值模型。利用四次非均匀差分公式推导了验证机构的激活条件。采用割线法动态调整当前刀路段的局部卡扣参数,实现速度剖面调制。通过义齿五轴加工实验验证了优化算法的有效性。实验结果表明,与传统策略相比,改进的刀具路径优化和速度预测算法分别使机床振动降低了6.62%和19.46%,尺寸顺应率分别提高了283.79%和439.774%。本工作成功地解决了复杂结构件五轴数控加工中存在的过切削、机床颤振和精度漂移等问题,为该类零件高精度稳定加工技术的发展提供了理论支持。
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引用次数: 0
Retraction notice to “The role of defect structure and residual stress on fatigue failure mechanisms of Ti-6Al-4V manufactured via laser powder bed fusion: Effect of process parameters and geometrical factors” [Journal of Manufacturing Processes 102 (2023) 549–563] “缺陷结构和残余应力在Ti-6Al-4V激光粉末床熔合疲劳失效机制中的作用:工艺参数和几何因素的影响”[j] .制造工艺学报,102(2023):549-563。
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-27 DOI: 10.1016/j.jmapro.2025.12.069
Seyed Mehrab Hosseini , Ehsan Vaghefi , Elham Mirkoohi
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引用次数: 0
Filament-assisted combined pulse laser ablation of metal targets: Mechanistic insights, efficiency enhancement, and spatial tolerance 细丝辅助联合脉冲激光烧蚀金属目标:机理见解,效率提高,和空间公差
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-26 DOI: 10.1016/j.jmapro.2026.01.050
Zhou Li , Junyang Xu , Yuyang Chen , Kai Li , Lu Zhang , Xianshi Jia , Cong Wang , Ji'an Duan
Filament-assisted combined pulse laser (CPL) ablation, coupling a millisecond laser with a nanosecond-laser-induced air filament, is demonstrated to achieve high-efficiency metal ablation under near-on-target power densities of 103-104 W/cm2. An integrated diagnostic system, combining transient temperature measurement and time-resolved imaging, enables direct identification of the coupled processes of melting and filament-driven expulsion, with the assistance of post-process three-dimensional morphology analysis. The filament assistance yields nearly an order-of-magnitude enhancement in ablation volume and material removal rate compared with millisecond laser irradiation alone. Crater depth is increased by more than a factor of two, while smaller and more stable laser-supported combustion waves are maintained. Moreover, CPL exhibits pronounced spatial tolerance, sustaining significant efficiency gains even under deliberate lateral misalignment and thereby confirming its robustness for non-ideal and long-range conditions. These findings highlight both mechanistic insight and performance advancement, consolidating filament-assisted CPL as a robust and scalable strategy for efficient, stable, and spatially tolerant ablation in high-energy laser damage.
在接近目标的功率密度为103-104 W/cm2的情况下,将毫秒激光与纳秒激光诱导的空气灯丝耦合在一起的灯丝辅助组合脉冲激光(CPL)烧蚀可以实现高效率的金属烧蚀。一个集成的诊断系统,结合瞬态温度测量和时间分辨成像,可以直接识别熔融和细丝驱动的排出耦合过程,并辅以加工后的三维形态分析。与单独的毫秒激光照射相比,灯丝辅助在烧蚀体积和材料去除率方面几乎提高了一个数量级。弹坑深度增加了两倍以上,同时保持了更小、更稳定的激光支持燃烧波。此外,CPL表现出明显的空间容忍度,即使在故意的横向不对准下也能保持显著的效率提高,从而证实了其在非理想和远程条件下的稳健性。这些发现强调了机理的洞察和性能的进步,巩固了细丝辅助CPL作为高效、稳定和空间容忍度高的高能激光损伤烧蚀的稳健和可扩展策略。
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引用次数: 0
Revealing the sintering behavior of H13 steel in semi-solid additive manufacturing through the correlation of shrinkage and porosity 通过缩孔关系揭示H13钢在半固态增材制造中的烧结行为
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-26 DOI: 10.1016/j.jmapro.2026.01.076
Shuhan Li , Xinqiang Lan , Zemin Wang
Extrusion-based additive manufacturing of powder-binder feedstocks offers a cost-effective route for indirectly fabricating metallic components. However, the sintering step remains a major bottleneck, typically requiring lengthy, powder-specific optimization that can exceed the effort spent on printing parameter tuning. This study overcomes this challenge by establishing a direct correlation between macroscopic shrinkage and microscopic porosity, enabling rapid assessment of sintering quality. For H13 steel, densification proceeds through solid-phase sintering at 1000–1350 °C and liquid-phase sintering at 1400–1450 °C. Thermodynamic analysis and experimental results confirm that by increasing the sintering temperature and avoiding excessive liquid-phase sintering (1300–1400 °C), both SSAM-5 and SSAM-10 powders (with medium particle size of 5.3 μm and 11.8 μm) can achieve ideal porosities of 0.45% and 0.96% after 1–3 h of holding. Macroscopic shrinkage was observed after sintering and approached a theoretical limit as porosity decreased. A quantitative model linking shrinkage to porosity was developed, enabling the immediate assessment of internal densification using easily accessible macroscopic data.
粉末粘合剂原料的挤压增材制造为间接制造金属部件提供了一种经济有效的途径。然而,烧结步骤仍然是一个主要的瓶颈,通常需要长时间的粉末特定优化,这可能超过了在打印参数调整上所花费的精力。本研究通过建立宏观收缩和微观孔隙率之间的直接关联来克服这一挑战,从而能够快速评估烧结质量。对于H13钢,通过1000 ~ 1350℃固相烧结和1400 ~ 1450℃液相烧结进行致密化。热力学分析和实验结果证实,提高烧结温度,避免过度液相烧结(1300 ~ 1400℃),保温1 ~ 3 h后,SSAM-5和SSAM-10(中粒径分别为5.3 μm和11.8 μm)的孔隙率均可达到0.45%和0.96%的理想孔隙率。烧结后观察到宏观收缩,随着孔隙率的降低接近理论极限。开发了将收缩与孔隙度联系起来的定量模型,可以使用易于获取的宏观数据立即评估内部致密性。
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引用次数: 0
Electro-magnetic coupled field-assisted laser-directed energy of Ni-based WC composite coatings: Defect suppression, microstructural evolution, and tribological behavior 电磁耦合场辅助激光定向能制备镍基WC复合涂层:缺陷抑制、微观组织演变和摩擦学行为
IF 6.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-26 DOI: 10.1016/j.jmapro.2026.01.069
Wanyang Li , Weiwei Liu , Huanqiang Liu , Junjie Tan , Haojun Yang , Baimao Lei , Qiang Chen , Jianrong Song , Zongyu Ma , Tao Li , Yulin Wang , Fengtao Wang , Hongchao Zhang
In this study, laser-directed energy deposition (LDED) assisted by an electromagnetic coupled field (EMF) was employed to systematically investigate the effects of current intensity and direction on melt pool dynamics, defect evolution, microstructural evolution, and tribological behavior of composite coatings. The coupled field reshaped melt pool flow patterns and effectively suppress pores and cracks, reducing the defect density to 0.075%. Electromagnetic stirring effect enhanced solute redistribution and grain morphology transformation, unveiling a coupled mechanism of “grain-boundary transformation-defect accumulation-strain release”. EBSD and TEM analyses revealed a microstructural transition from a “WC/W2C-dominated” state to a “γ-Ni matrix-Cr carbide co-dominated” configuration, which regulated interfacial carbon activity, promoted stable Cr7C3 precipitation, and facilitated the formation of Ni3Si + γ-Ni(Fe,Cr) eutectics. An appropriate current intensity further facilitated particle redistribution, suppressed fatigue spalling, and enhanced wear resistance by nearly 64.70%. These findings demonstrate that the external coupled field regulates microstructural evolution and wear behavior, providing new processing pathways for tailoring the performance of high-performance composite coatings.
在本研究中,采用电磁场辅助下的激光定向能沉积(LDED)技术,系统地研究了电流强度和方向对复合涂层熔池动力学、缺陷演变、微观组织演变和摩擦学行为的影响。耦合场重塑了熔池流动模式,有效抑制了气孔和裂纹,将缺陷密度降低到0.075%。电磁搅拌效应增强了溶质重分布和晶粒形貌转变,揭示了“晶界转变-缺陷积累-应变释放”的耦合机制。EBSD和TEM分析表明,微观结构从“WC/ w2c主导”状态转变为“γ-Ni基体-Cr碳化物共同主导”结构,这一结构调节了界面碳活性,促进了Cr7C3的稳定析出,并促进了Ni3Si + γ-Ni(Fe,Cr)共晶的形成。适当的电流强度进一步促进了颗粒的再分布,抑制了疲劳剥落,耐磨性提高了近64.70%。这些发现表明,外部耦合场调节了微观组织演变和磨损行为,为定制高性能复合涂层的性能提供了新的加工途径。
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Journal of Manufacturing Processes
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