International Journal of Material Forming最新文献

{"title":"Influence of asymmetric strip tension on surface roughness transfer in skin-pass rolling with small roll radius under dry conditions","authors":"Mengmeng Zhang,&nbsp;Christopher Schulte,&nbsp;Emad Scharifi,&nbsp;Sebastian Stemmler,&nbsp;David Bailly","doi":"10.1007/s12289-026-01980-5","DOIUrl":"10.1007/s12289-026-01980-5","url":null,"abstract":"<div><p>Textured work rolls are utilized in skin-pass rolling to achieve the specific surface finish of the strip, affecting the product properties, such as friction coefficient and paintability. Therefore, to achieve effective property control, it is essential to control surface finish while maintaining geometric accuracy. However, both geometric accuracy and surface finish are influenced by the rolling force, necessitating decoupling for independent control. In this work, asymmetric strip tension is considered as an additional actuator, alongside the roll gap actuator, to investigate the potential to control the surface roughness without influencing the thickness reduction, thereby obtaining the desired product properties. For this purpose, a numerical study is conducted using a finite element multi-scale model with different thickness reductions and strip tensions. Results indicate that, compared to the mean roughness of 2.34 μm at the symmetric case with backward and forward tensions of 0.2 kN, the roughness increases by 7.7% with increasing the forward tension to 1.2 kN and decreases by 2.1% with increasing the backward tension to 0.6 kN, at 7% thickness reduction. This variation in roughness is attributed to the effect of strip tension on the relative movement between the work roll and the strip material. Therefore, applying asymmetric strip tension emerges as an effective strategy to ensure both surface finish and geometric accuracy simultaneously in skin-pass rolling.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12289-026-01980-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147737454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of tool diameter and step size on deformation and microstructural response in robot-assisted incremental sheet forming of AA3003-O","authors":"Radhe Shyam Bhasker,&nbsp;Ravi Prakash Singh,&nbsp;Parnika Shrivastava,&nbsp;Yogesh Kumar","doi":"10.1007/s12289-026-02006-w","DOIUrl":"10.1007/s12289-026-02006-w","url":null,"abstract":"<div>\u0000 \u0000 <p>Robot-assisted incremental sheet forming (RAISF) of AA3003-O aluminium sheets (0.56 mm) was investigated to quantify the combined influence of tool diameter and step size on geometric, mechanical and microstructural responses. Variable wall angle conical frusta (VWACF) were fabricated using three tool diameters (5, 10, 15 mm) and three step depths (0.1, 0.3, 0.5 mm). A software-based toolpath was generated in CATIA and executed via ROBOTDK on a six-axis industrial robot. Formability was assessed through limiting wall angle and forming limit curves obtained from circle-grid analysis; spring back was evaluated from the deviation between theoretical and measured cone depths; forming forces were recorded in situ using a dynamometer; surface roughness (Ra, Rq) was characterised by <b><i>scanning probe microscope</i></b> (SPM); and crystallite size evolution was quantified using <b><i>X-Ray diffraction (XRD)</i></b> with a Modified Scherrer Equation and Williamson–Hall analysis. The limiting wall angle increased with tool diameter (from 49–53° for 5 mm to 61–64° for 15 mm) and exhibited an optimum at ΔZ = 0.3 mm. Average vertical force increased with both tool diameter and step depth, reaching ~ 40 kgF for the 15 mm/0.5 mm condition. Surface roughness varied between Ra ≈ 0.23–0.53 μm depending on tool–step combination. XRD results showed crystallite refinement relative to the base material, with step depth and tool diameter jointly controlling the balance between strain hardening and dynamic recrystallisation.</p>\u0000 </div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12289-026-02006-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental and statistical optimization of process parameters for wear-resistant Al7075 surface composites","authors":"Neha Bhadauria,&nbsp;Prashant Vashishtha,&nbsp;Sunil Pandey,&nbsp;Pulak Mohan Pandey","doi":"10.1007/s12289-026-02005-x","DOIUrl":"10.1007/s12289-026-02005-x","url":null,"abstract":"<div>\u0000 \u0000 <p>Aluminium alloys are widely used in automotive and aerospace industries due to their low density, corrosion resistance, durability, and ease of processing. This study presents a novel and cost-effective surface modification technique for enhancing the wear resistance of Al7075 alloy through in-situ formation of Al₂O₃-reinforced surface composites using Gas Tungsten Arc Welding (GTAW). Alumina particles (625 mesh) were introduced between Al7075 substrate and cover sheet and dispersed into the molten pool through controlled arc stirring. A two-level half-factorial design (2⁴⁻¹) was employed to systematically investigate the effects of welding current (90–110 A), welding speed (10–20 cm/min), electrode diameter (4–6 mm), and gas flow rate (7.5–10 l/min). Surface composites exhibited significant improvement over base metal, with hardness reaching up to 301 HV and mass loss reduced by nearly threefold (minimum 0.007 g). Regression models demonstrated high predictive capability, explaining 95.34% variability in hardness and 96.09% in mass loss (R² &gt; 0.95). SEM confirmed uniform alumina dispersion and EDX validated reinforcement presence. The study establishes a statistically optimized, scalable GTAW-based surfacing route for developing high-performance wear-resistant aluminium surface composites without bulk composite processing.</p>\u0000 </div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on molten pool dynamics and porosity formation of 4J36 invar steel welded by K-TIG","authors":"Yanhong Hou,&nbsp;Fei Zhao,&nbsp;Shuili Gong,&nbsp;Lifeng Ma,&nbsp;Haiyan Zhao,&nbsp;Wei Zhang","doi":"10.1007/s12289-026-01998-9","DOIUrl":"10.1007/s12289-026-01998-9","url":null,"abstract":"<div><p>This study examines the K-TIG welding process for 5 mm-thick domestic 4J36 Invar steel, employing a combined approach of simulation analysis and high-speed photographic observation. The low fluidity of 4J36 Invar steel due to its high tensile strength results in a slow ascent rate of gas bubbles, exacerbating the formation of porosity defects. K-TIG welding shortens the molten pool residence time, significantly reducing gas incorporation. Additionally, gas bubbles can escape directly along the keyhole wall, thereby minimizing porosity defects. The study simulates molten pool flow behavior through numerical modeling and employs high-speed photography to observe the welding process in real time. It reveals the dynamics of the molten pool and the bubble escape mechanism during K-TIG welding, providing a theoretical basis for optimizing the K-TIG welding process for 4J36 Invar steel and reducing porosity defects. The results demonstrate that maintaining the welding current at 340–360 A, the arc voltage at 18–20 V, and the welding speed at 300–350 mm/min ensures the stability of the molten pool flow and keyhole formation, thereby facilitating melt flow and enhancing gas escape.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing wear resistance of 05Cr17Ni4Cu4Nb stainless steel via nanostructured ceramic particles-induced nano-copper precipitation","authors":"Jialiang Li,&nbsp;Shuan Ma,&nbsp;Yanli Su,&nbsp;Zhenjie Gu,&nbsp;Xiaohui Jia,&nbsp;Jianbo Lei","doi":"10.1007/s12289-026-02007-9","DOIUrl":"10.1007/s12289-026-02007-9","url":null,"abstract":"<div>\u0000 \u0000 <p>A strengthening strategy for 05Cr17Ni4Cu4Nb stainless steel was developed by laser directed energy deposition (L-DED) with nano-WC reinforcement. During L-DED, laser-induced decomposition of WC released W and C, promoting the precipitation of M₇C₃, M₂₃C₆, and NbC carbides. The nano-WC particles also acted as heterogeneous nucleation sites, facilitating the formation of nanoscale Cu-rich precipitates. The synergistic effect of carbides and Cu-rich phases effectively suppressed grain growth, strengthened grain boundaries, and impeded dislocation motion, thereby achieving microstructural refinement and enhanced resistance to deformation. Meanwhile, WC decomposition in the molten pool induced partial reverse transformation of martensite into retained austenite, which can dissipate frictional energy and reduce the spallation of brittle phases, further improving wear performance. Compared with the as-received 05Cr17Ni4Cu4Nb stainless steel, the composite with 16 wt. % WC showed an approximately 8.7% increase in microhardness and achieved a steady-state friction coefficient of 0.234. The superior wear resistance is mainly attributed to the synergistic precipitation-strengthening and dislocation-pinning effects of Cu-rich phases and nano-carbides, complemented by the toughening effect of retained austenite.</p>\u0000 </div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of surface roughness in boring of 1.2311 material using machine learning enhanced by virtual sampling methods","authors":"Aslan Akdulum,&nbsp;Yunus Kayir","doi":"10.1007/s12289-026-02004-y","DOIUrl":"10.1007/s12289-026-02004-y","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurate prediction of surface roughness is essential for quality assurance in boring operations. However, the long and slender structure of boring bars induces dynamic effects that make obtaining consistent surface quality challenging, while extensive experiments are costly and time-consuming. Traditional regression models fall short in predictive performance and cannot adequately capture the nonlinear interactions between cutting parameters. This study presents a machine learning-based methodology to estimate the surface roughness of 1.2311 plastic mold steel during boring on a milling machine. The primary objective is to model the connection between boring variables and hole quality under limited data conditions (72 data points). To overcome insufficient samples, the proposed framework integrates feature augmentation, principal component analysis (PCA), and virtual sampling (VSG) (0 to 500 in increments of 50) with different interpolation techniques. Results indicate that weighted interpolation-based VSG after feature space expansion significantly improves prediction accuracy by strengthening the representation of cutting parameter–Ra relationships. The highest-performing model, combining the Decision Tree algorithm with weighted interpolation and augmented features, achieved a minimum a Root Mean Square Error (RMSE) of 0.28 μm and Mean Absolute Percentage Error (MAPE) of 12.42%. Compared to models trained solely on real experimental data, prediction accuracy improved by 61.9% in MAPE and 34.88% in RMSE, demonstrating the effectiveness of the proposed virtual sampling and feature engineering strategy under limited experimental data conditions. The findings highlight how structured data enhancement can improve surface roughness prediction in milling-based boring and support more reliable process planning.</p>\u0000 </div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12289-026-02004-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147606717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing accuracy in simulation of sheet metal forming by modelling elasticity of tools","authors":"Diogo Neto,&nbsp;Daniel J. Cruz,&nbsp;Jonas Reuter,&nbsp;Apostolos Aslanidis,&nbsp;Marta Oliveira,&nbsp;Bernd Engel,&nbsp;Abel D. Santos,&nbsp;Peter Frohn-Sörensen","doi":"10.1007/s12289-026-02002-0","DOIUrl":"10.1007/s12289-026-02002-0","url":null,"abstract":"<div>\u0000 \u0000 <p>The first ESAFORM Benchmark was dedicated to the cylindrical cup drawing test and involved the participation of 11 laboratories worldwide. Despite the wide variety of computational models adopted, several experimental results were not accurately predicted, and no conclusive explanation for the observed discrepancies was identified, motivating further investigation. Using the same benchmark configuration, the present study examines the influence of modelling tools as rigid or elastic on the accuracy of sheet metal forming simulations. The effect of the elasticity of tools is quantified and related to discrepancies previously reported in the benchmark. Different process conditions, including variations in blank thickness and diameter were analysed for two materials: AA6016 aluminium alloy and DC06 steel. The results demonstrate that considering the elasticity of tools significantly improves the prediction of punch force evolution, cup wall thickness, and earing profile, particularly in processes involving ironing. Elastic deflection of the tools modifies the contact pressure distribution under the blank-holder and increases the effective punch–die gap, leading to more accurate predictions of ironing forces and wall thickness. These findings help explain discrepancies observed in the first ESAFORM Benchmark and highlight that incorporating the elasticity of tools is essential for high-fidelity sheet metal forming simulations, particularly when ironing occurs.</p>\u0000 </div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12289-026-02002-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147607382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new upper bound solution for axisymmetric direct extrusion considering Coulomb friction and generalized work functions","authors":"Sergei Alexandrov,&nbsp;Stanislav Strashnov,&nbsp;Yeau-Ren Jeng","doi":"10.1007/s12289-026-02003-z","DOIUrl":"10.1007/s12289-026-02003-z","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper provides a new upper bound solution for axisymmetric extrusion through a conical die. The most important distinguishing features of this solution, compared to available solutions, are the use of Coulomb friction and generalized work functions. In particular, a unified procedure is developed for evaluating the extrusion force for the work functions that yield the von Mises yield criterion, yield criteria closely approximating the Hershey-Hosford yield criteria, and a yield criterion that accounts for the strength-differential effect. The trial velocity field is intentionally chosen to be simple enough to emphasize the technique for constructing trial velocity fields that allow the extrusion force to be evaluated in the case of Coulomb friction. The possibility of a rigid region appearing in the die is taken into account. The numerical part of the solution reduces to evaluating an ordinary integral. The effect of various geometric and other process parameters on the extrusion force is revealed. Possible extensions of the solution are discussed.</p>\u0000 </div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12289-026-02003-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147607066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-driven strength prediction and design of recycled fine-aggregate cementitious composites","authors":"Rishabh Tyagi,&nbsp;Pradeep Kumar Goyal","doi":"10.1007/s12289-026-01997-w","DOIUrl":"10.1007/s12289-026-01997-w","url":null,"abstract":"<div>\u0000 \u0000 <p>The accelerated expansion of the construction industry has heightened the demand for concrete and the production of construction-demolition waste, prompting the utilisation of recycled fine aggregate (RFA) to preserve natural sand resources. This work experimentally assesses the compressive strength of GGBS-blended concrete using 0-100% RFA (by mass of fine aggregate) across three curing environments: normal water, 3% HCl, and 5% H₂SO₄, over curing durations of up to 90 days. The compressive strength improved with curing age across all mixtures; an optimal replacement of 60% RFA resulted in the highest strength, exhibiting an increase of up to 6.44% at 90 days (normal water) relative to the control. Conversely, higher replacement levels (80–100%) resulted in a decrease in strength due to increased porosity and diminished interfacial bonding. To generalise these findings and minimise further testing, machine-learning models utilising Regression Trees (RT), Support Vector Machines (SVM), and Gene Expression Programming (GEP) were created to predict compressive strength based on mix proportions and curing parameters; the GEP model exhibited superior performance (R² = 0.990, RMSE = 1.207, MAE = 0.974, MAPE = 2.426%) and offers an equation for design-oriented applications within the examined parameter space. The model is calibrated on the current experimental database; thus, its use should be confined to tested ranges, and transferability was assessed using grouped k-fold cross-validation. The research indicates that up to 60% RFA can be used into GGBS-blended concrete, and that interpretable machine learning models can proficiently assist in the mix design of RFA concretes.</p>\u0000 </div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147561169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelisation and numerical simulation on the residual stress induced by cold expansion of fastener holes located in nickel based superalloy aircraft engine disks","authors":"Moad Fatmi,&nbsp;Manuel François,&nbsp;Carl Labergere,&nbsp;Emmanuel Fessler,&nbsp;Stéphane Pierret","doi":"10.1007/s12289-026-01996-x","DOIUrl":"10.1007/s12289-026-01996-x","url":null,"abstract":"<div><p>High pressure turbine disks are critical components of aeroengines. The failure of such component is strictly forbidden for safety reasons. This component must meet the certification requirements in terms of fatigue life to initiation as well as crack growth life via damage tolerance approach. Fastener holes are highly stressed areas. The cold expansion process is used in aeronautical industry on fastener holes in order to introduce compressive residual stress around the hole up to 4 mm beneath the surface. This residual stress will prevent early crack initiation and reduce the crack growth rates. The residual stress field must be characterized and modeled in order to take into account the beneficial effect of cold expansion on the crack growth rates. Two different models including a three dimensional finite element model and a reconstructed residual stress model by the eigenstrain theory have been created. Indeed, these models aim to study the distribution of the residual stress field around an <i>Inconel718</i> cold expanded hole. The three dimensional finite element model was established to simulate the actual split-sleeve cold expansion process and the reaming/chamfering operations. The results reveal that the residual stress varies through the thickness at different cross sections perpendicular to the hole axis of the sample. The eigenstrain study was applied to the same sample, subject to cold expansion treatment. The eigenstrain distribution was calculated using limited experimental strain measurement by neutron diffraction. The results reveal that the distribution of the residual stress field along the radial direction of the expanded hole is in good agreement with the numerical model, however, this simplified model is, by essence, unable to predict the residual stress variation through the thickness of the sample. Finally, the experimental data obtained by neutron diffraction were compared with those derived from simulation approaches.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147561170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}