Search Results (243)

Use of fly ash (FA), a by-product of coal-fired power stations, and basic oxygen furnace slag (BOFS), a by-product of steel production plants, in construction applications in Kazakhstan is limited due to their low quality and inherent problematic properties. For example, the concern with using BOFS as an aggregate in concrete is the volume expansion caused by the formation of calcium hydroxide (Ca(OH)₂) or magnesium hydroxide (Mg(OH)₂) in the concrete matrix generated by a chemical reaction between water and free calcium oxide (f-CaO) or free magnesium oxide (f-MgO) in BOFS. This issue can be addressed through geopolymerization and CO₂ curing (mineral sequestration). Moreover, the quality of FA does not meet ASTM Class F FA criteria (coarse particle sizes and low reactivity). This study investigated the physical, mechanical, microstructural, and durability properties of geopolymer mixtures composed of low-quality FA, ground granulated blast-furnace slag (GGBFS), and BOFS aggregates under various curing conditions. Six distinct curing regimes were assessed: air, water, 6 h steam, 12 h steam, 6 h steam combined with 6 h CO₂, and 6 h steam combined with 12 h CO₂ curing. The hardened properties, durability, and microstructural characteristics of geopolymer mixtures were mainly assessed by compressive strength, dielectric constant (DC), drying shrinkage, expansion (1 M NaOH solution and water expansions), X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM) images. Test results show that steam curing and combined steam and CO₂ curing significantly enhanced the performance of the mixtures containing BOFS aggregates. The combined steam and CO₂ curing accelerated the mineral sequestration of f-CaO in the BOFS aggregates, increasing the 28-day compressive strength by up to 27.7% and 19.2% (reaching 37.1 MPa) compared to air- and water-cured mixtures (29.1 and 31.1 MPa, respectively). While air (20.0 and 11.7), steam (28.7 and 12.4), and combined steam and CO₂ (23.6 and 12.6) curing at 1-day and 182-day yielded lower DC, water curing (30.5 and 32.2) had higher DC. The extended steam and CO₂ curing times further enhanced compressive strength growth (39.6 MPa) by 36.6% for air-curing and 27.1% for water curing, although curing duration did not significantly affect the dielectric constant. Importantly, the expansion of the BOFS aggregate in both water and 1 M NaOH solution was minimized up to 0.04% under combined curing, mitigating the inherent volumetric instability of the BOFS. Drying shrinkage was also reduced by 0.17% under combined curing conditions. Longer steam and CO₂ curing times reduced variability in dielectric constant, drying shrinkage, and the expansion characteristics. FTIR spectroscopy, SEM image, and XRD analyses confirmed that the mixture’s geopolymerization was more noticeable during the steam and CO₂ curing regimes than during water and air curing regimes. The longer steam and CO₂ curing times promoted extended hydration and the formation of stable carbonate compounds from the BOFS f-CaO, producing a significantly denser and microstructurally stable geopolymer matrix. Full article

Construction-stage bridge fires are seldom documented in detail, although they can change the behavior of an incomplete structural system. This paper records a 35 m span of a six-cell RC box girder at the Al-Sadreen intersection in Samawa, Iraq, damaged after the bottom slab and webs had been cast and before the top slab was completed. Burning timber formwork locally removed the temporary soffit support. The open-top section, therefore, shifted from the intended fixed–pin construction-stage response toward a pin–pin-like response, with sagging and vertical web cracks near the intended fixed support. A closed-form check showed that the required negative-restraint moment was about 5.3–5.9 times the cracking moment of the incomplete section. Visual inspection, Schmidt hammer, UPV, cores, and steel tests showed localized damage; 28 MPa was used as a representative residual concrete strength for the affected cast components. CSiBridge was used only for completed rehabilitated-state verification. The strengthened model gave maximum shear D/C ≈ 0.529 and flexural D/C < 1.0. Spreadsheet-guided jacking, top-slab reinforcement upgrading, sensitivity checks, and a 350-ton five-lane load test confirmed satisfactory service behavior and negligible residual response. Full article

The degradation of steel used in the oil industry has become a serious problem due to the high costs associated with material loss from corrosion. Applying thin layers of corrosion-resistant material promises to be a viable alternative for extending the service life of pipelines. ERCuAl-A2 electrode claddings were applied to API X70 carbon steel using the MIG brazing process with direct current (DC) and pulsed current (P). The cladding was applied under three conditions: base material (BM) at room temperature, BM preheated to 120 °C, and Ni-buttered BM. Microhardness profiles and Charpy impact tests were performed on the MB and all cladding conditions. The API X70 carbon steel showed a microhardness value of 186.95 ± 11.17 Vickers, while the microhardness profiles of the ERCuAl A2 cladding showed values that differed in the intermetallic zone generated by the welding process. Likewise, the impact behavior of the base material and the applied claddings was ductile, except for conditions C2PF and C3PF, which showed a brittle–ductile behavior. The highest values of absorbed energy obtained from the tests were found in the conditions applied with DC, with values of approximately 50 MJm-3, due to the transfer mode of application of the cladding and/or the position in which the notch was made. Full article

Electrical resistance measurements can provide supplementary information for the characterization of carbon steels, since resistivity is influenced by composition, microstructure, geometry, processing history, and temperature. This work presents an experimental methodology for the electrical resistance-based characterization of AISI 1045 carbon steel specimens using controlled current injection and parameter estimation. The proposed system integrates a DC-modulated excitation stage, a four-terminal measurement configuration, voltage, current, and temperature acquisition, signal preprocessing, and offline resistance estimation using Python 3 scripts. Ten cylindrical specimens were evaluated through 10 repeated characterization experiments per sample, yielding 100 characterization records, each containing 100,000 voltage, current, and temperature measurements. The sample resistance is estimated using a least-squares formulation based on synchronized voltage–current data and is compared with a mean-based estimator derived from instantaneous resistance values. The results show that the least-squares estimator produced repeatable resistance values concentrated within a narrow interval, from approximately $443.43\mathrm{\mu }\mathrm{\Omega }$ to $445.55\mathrm{\mu }\mathrm{\Omega }$, with interquartile ranges below $4.46\mathrm{\mu }\mathrm{\Omega }$ for all specimens. In contrast, the mean-based estimator exhibited larger resistance values and substantially higher dispersion. The least-squares resistance-derived resistivity values ranged from $1.823\times {10}^{-7}$ to $2.263\times {10}^{-7}\mathrm{\Omega }·$m, which is consistent with the expected order of magnitude for AISI 1045 steel when compared with temperature-dependent theoretical reference values. The corresponding relative differences ranged from 1.94% to 11.00%, with most specimens remaining below 6%. These findings indicate that controlled current injection, combined with four-terminal sensing, signal preprocessing, and least-squares estimation, provides a reproducible framework for the low-resistance characterization of carbon steel specimens. Although the present study focuses on AISI 1045 steel, the methodology may be adapted to other metallic specimens, steel grades, heat-treated samples, or controlled thermal-cycle experiments, provided that geometry, temperature, calibration, and material-specific reference conditions are properly considered. Full article

This study investigates the effect of low-temperature pulsed DC plasma nitriding on the surface properties of AISI 304 stainless steel for homogenizer valve-seat components. Plasma nitriding was performed in an ammonia atmosphere at 400, 440 and 480 °C for 8 h. The treatment led to the formation of expanded austenite at 400 °C, while higher temperatures promoted the formation of Fe-N and CrN-containing phases. The thickness of the modified layer increased from approximately 36 μm at 400 °C to 65 μm at 480 °C. Surface microhardness increased from 203 HV0.1 for the untreated steel to 652.6, 806.0 and 961.8 HV0.1 after nitriding at 400, 440 and 480 °C, respectively. The wear rate decreased markedly, reaching 1.92 × 10⁻⁵ mm³/(N·m) for DCPN480 compared with 30.65 × 10⁻⁵ mm³/(N·m) for the untreated sample. Among the nitrided samples, DCPN440 showed the most favorable corrosion behavior in 3.5 wt.% NaCl solution, indicating a balance between surface hardening and preservation of corrosion resistance. Numerical modeling confirmed that the strengthened surface layer can withstand equivalent homogenizer valve-seat loading without local plastic deformation. The results demonstrate that pulsed DC plasma nitriding can significantly improve the hardness and wear resistance of AISI 304 stainless steel while maintaining acceptable corrosion performance under optimized treatment conditions. Full article

Laser brazing is commonly used for joining visible automotive body panels where both mechanical integrity and surface quality are required. The present work addresses optimization of a robotic laser brazing workstation intended for prototype vehicle production. During initial commissioning, irregular braze formation was associated with unstable filler wire feeding. Therefore, the wire feeding system was modified and subsequently evaluated together with the influence of laser power and wire feed speed on joint quality under a constant robot travel speed. Experimental joints were produced from electrolytically galvanized DC06 steel using CuSi3Mn1 filler wire. Joint performance was assessed by tensile testing and metallographic examination. Tensile strengths between 293 and 314 MPa were obtained, while fracture occurred exclusively in the base material outside the brazed region. Metallographic observations revealed regular braze geometry for parameter sets A, B and D, whereas excessive thermal input resulted in blowhole formation, zinc coating degradation and enlargement of the heat-affected zone. Quantitative evaluation showed a nearly linear increase in the HAZ area with increasing delivered energy (R² = 0.982). The results indicate that stable brazing conditions can be achieved through an appropriate balance between laser power and wire feed speed under constant robot travel speed conditions. The proposed parameter limits may serve as a practical guideline for robotic laser brazing of thin galvanized automotive sheets under prototype production conditions. Full article

TiN/TiAlN coatings were deposited on 40Cr steel substrates by DC magnetron sputtering to improve the surface tribological performance of the steel. The influence of sputtering power (80, 100, 120, 140, 160 and 180 W) on coating morphology, phase structure, adhesion strength and wear behavior was evaluated using SEM, EDS, XRD, Vickers microhardness testing, scratch testing and ball-on-disk tribological testing. The coatings were dense and relatively smooth, with only a small number of submicron particles. Increasing sputtering power increased the coating thickness, and the EDS results suggested an increase in Al content of up to 160 W, whereas the crystallite size of the TiAlN (200) phase first decreased and then increased. XRD analysis showed that the coatings were dominated by face-centered cubic TiAlN, accompanied by weak TiN and AlN diffraction peaks. Among the tested samples, the coating deposited at 140 W showed the most favorable measured combination of adhesion and tribological properties within the tested series, with a thickness of 1.76 μm, a Vickers microhardness of 906.35 HV0.25, an adhesion strength of 45.6 N, an average friction coefficient of 0.322 and a specific wear rate of 28.37 × 10⁻⁷ mm³ N⁻¹ m⁻¹. These measured trends are consistent with the dense morphology, refined crystallites, high microhardness and higher measured adhesion observed at moderate sputtering power. In contrast, excessive sputtering power was associated with particle coarsening and coating defects, accompanied by higher measured friction and wear. Full article

To improve the efficiency of TIG (Tungsten Inert Gas) welding, our team developed a novel fast-frequency pulsed twin-TIG welding power source and matched welding procedures to overcome the drawbacks of conventional high-efficiency TIG welding. After parameter optimization, stable, high-efficiency and high-quality welding of 316L stainless steel can be realized. Compared with traditional DC TIG welding, the mechanical properties of joints are greatly improved: the weld grain size is refined by 38% under moderate current, while tensile strength, elongation and microhardness rise by 13.6%, 26% and 10% respectively, which achieves simultaneous improvement in strength and ductility. Numerical simulations were carried out to analyze the evolution of molten pool temperature field and velocity vector flow field. The simulation results are highly consistent with experimental data, which verifies the reliability of the model and lays a foundation for the study of molten pool behavior. Combined with molten pool flow characteristics and weld microstructure, the evolution mechanism of microstructure and texture as well as grain refinement in this welding process is revealed. Full article

Friction at the drawbead in metal forming operations directly affects the quality of drawpieces. However, identifying the complex effect of friction process parameters on the coefficient of friction (CoF) is difficult based on experimental results. The aim of this paper is to analyze the results of a drawbead simulator test using various machine learning (ML) methods to select the most appropriate algorithm and to analyze in detail the feature importance, permutation importance, and cumulative Shapley additive explanation values of predictors. The test material was DC04 low-carbon steel sheet. Experimental tests were conducted for varying friction process conditions. Of the three different ML algorithms (support vector machine, regression trees, and ensemble tress), the support vector machine (SVM) algorithm with a cubic kernel function provided the lowest root mean square error (0.0085) and the highest correlation coefficient R² (0.9657) for the test data. The predictors in descending order of permutation importance are friction conditions, drawbead height, sample width, Sa of countersamples, and sample orientation. A combined swarm-box chart presenting Shapley values for an SVM model with a cubic kernel function indicates that a low value of the drawbead height predictor has a strong, increasing effect on CoF. However, low values of the remaining explanatory parameters (sample width, mean roughness of countersamples, and sample orientation) have a decreasing effect on CoF. Full article

Ultra-high-performance concrete (UHPC) is known for its exceptional compressive strength and durability; however, its brittle nature requires fiber reinforcement to improve toughness and tensile performance. This study investigates the synergistic effects of triple fiber reinforcement, including desized and sized carbon fibers (0.2–1.0 vol%), steel fibers (1.0 vol%), and polypropylene fibers (0.2 vol%) on the fresh, mechanical, durability, microstructure, and fire resistance properties of UHPC. The experimental program included workability, compressive and flexural strength, load-deflection behavior, electrical resistivity, dynamic modulus of elasticity, SEM analysis, and fire resistance at elevated temperatures (425 and 900 °C). The results showed that desized carbon fibers performed better than sized fibers by improving workability, fiber dispersion, flexural behavior, and fiber–matrix bonding. The optimal triple-fiber composition, DC1.0P0.2S1.0, achieved the highest flexural strength of 24 MPa while maintaining compressive strength above 141 MPa. The triple-fiber system provided effective multi-scale crack control, where PP fibers prevented explosive spalling, carbon fibers bridged meso-crack control, and steel fibers enhanced macro-crack load transfer and ductility. SEM analysis further confirmed better dispersion and stronger interfacial bonding of desized carbon fibers. Overall, the optimized triple-fiber system significantly improved flexural performance, toughness, workability, and fire resistance without notably reducing compressive strength, demonstrating strong potential for advanced structural applications. Full article

The transition from sinusoidal to pulse width-modulated (PWM) voltage excitation introduces high-frequency ripple, generating small remagnetization cycles within the main magnetization cycle and increasing total iron losses. Soft magnetic materials are essential for constructing many electrical devices, and accurate loss data are critical for reliable design and thermal dimensioning. However, magnetic material data are typically available only under sinusoidal excitation, and there is no generally accepted method for calculating PWM-induced losses during the design phase. To address this issue, loss measurements under DC-biased magnetization were performed on laminated ring cores, and the data were collected in the form of three-dimensional (3D) loss maps defined by the variables $\Delta B$, ${\displaystyle \frac{\mathrm{d}B}{\mathrm{d}t}}$ and $B_{\mathrm{bias}}$. Based on these maps, a method referred to as 3DLMB is proposed to calculate the contribution of PWM-induced losses to total iron losses by comparing minor-loop variables obtained from AC excitation with those measured under DC bias conditions. The method is experimentally validated on three ring cores with different geometrical parameters, showing agreement between calculated and measured total AC losses within ±5% over a range of switching frequencies. The reported agreement applies to the investigated M400-50A material, ring-core geometries, and operating range, while applying it to other materials or geometries requires constructing the corresponding DC-bias 3D loss map. Full article

Worn roller mill roll shafts made of Steel 45 require cost-effective surface restoration; plasma transferred arc (PTA) deposition of Ni–Cr–B–Si + WC composite coatings is a promising approach, yet the effect of arc current on coating quality remains insufficiently characterised for this substrate. Six coatings were deposited from PS-12NVK-01 powder (65 wt.% PG-10N-01 + 35 wt.% WC) at arc currents of 50–100 A on Steel 45 substrates using a ZTW3501DC PTA system; coatings were characterised by SEM, EDS mapping, XRD (HighScore Plus, PDF-2), Vickers microhardness profiling, and ball-on-flat tribological testing. EDS analysis revealed that compositional dilution increases from 18.1% at 60 A to 46.6% at 100 A; XRD identified WC + Cr₃C₂ + Ni₃B + Ni₂B + (Fe,Ni)γ at 50 A, transitioning through Cr₇C₃ + W₂C dominance at 80 A to an Fe₀.₆₄Ni₀.₃₆ matrix at 100 A; and coating thickness peaked at 2.70 mm at 80 A. The 60 A coating yielded the highest surface hardness (887 ± 76 HV, >4× the substrate), the lowest specific wear rate (4.00 × 10⁻⁶ mm³/(N·m), ~22× lower than uncoated Steel 45), and minimum dilution (18.1%), identifying 60 A as the most favourable deposition current for the restoration of roller mill roll shafts under the process parameters employed. Full article

Manual arc welding is highly dependent on operator skill, leading to variability in weld quality and an increased risk of defects; therefore, reliable monitoring methods for Shielded Metal Arc Welding (SMAW) are required, particularly in manual environments where process variability and environmental noise are inherent. This study proposes a monitoring approach for classifying SMAW process parameters using airborne acoustic signals generated by the welding arc. Welding experiments were conducted on carbon steel plates of different thicknesses (3, 6, and 12 mm) using E6010, E6011, E6013, and E7018 electrodes under Alternating Current (AC) and Direct Current (DC) configurations; acoustic signals were recorded in real time and processed using Mel-Frequency Cepstral Coefficients (MFCCs) and deep audio embeddings from pre-trained VGGish and YAMNet models as inputs to artificial neural network classifiers for multi-output classification of welding process parameters. Model performance was evaluated using per-target metrics (accuracy and macro F1-score) and joint multi-output metrics (Exact Match and Hamming Accuracy). MFCC-based models significantly outperformed embedding-based approaches, achieving up to 94.51% Exact Match and 97.88% Hamming Accuracy, while reducing computational costs. These results demonstrate the feasibility of SMAW monitoring using arc sound, suggesting that spectral features are an effective solution for welding-process monitoring and a promising foundation for future weld-quality monitoring systems. Full article

Validation testing of a liquid-based rheostat confirmed its efficacy in mitigating DC arc faults in photovoltaic systems by exceeding critical resistance and voltage–current thresholds. Experimental characterization of electrode immersion depth, separation, and electrolyte concentration identified zinc-galvanized steel to copper in NaHCO₃ as the optimal configuration, achieving a dynamic range factor of 39.10. Further analysis prioritized high minimum resistance (R_MIN) for arc extinction, favouring stable electrode pairs like copper to brass with a 10 g solute concentration. A unified piecewise resistance model validated arc suppression through a load line analysis, demonstrating non-intersection with the Mayr extinction boundary. These findings support scaling the device to a 5 kW, 250 V_DC rating for electric geysers, utilizing 200 mm × 50 mm electrodes and increased electrolyte volume to ensure operational stability. Full article

Accurate and interpretable weld-quality assessment is essential for ensuring the reliability of resistance spot welding in industrial production. This study develops a data-efficient classification framework that integrates dual-interval mean discretization (DIMD) of dynamic-resistance signals with gradient-boosting models. The proposed DIMD method applies fine discretization during the rapid heating–melting and coarse discretization during the subsequent slow-evolving period, effectively preserving the peak–valley morphology of resistance curves while reducing feature dimensionality. Using these compact features, XGBoost and CatBoost classifiers were trained on a dataset of DC01 low-carbon steel, covering five weld conditions. CatBoost achieved the highest accuracy of 98.9%, attributed to its ordered-boosting mechanism and symmetric-tree structure. Validation on an independent 198-sample dataset confirmed the generalization capability of the proposed approach. SHapley Additive exPlanations (SHAP)-based interpretability analysis further revealed that resistance-peak characteristics and energy-related descriptors dominate model decisions, aligning with the physical process of nugget formation and expulsion. Experimental results demonstrate that the DIMD–CatBoost framework provides a physically consistent, interpretable, and high-accuracy solution for intelligent weld-quality inspection. Full article