Search Results (415)

This paper presented an optimization and material enhancement framework for improving the efficiency of a 1 HP Permanent Split Capacitor (PSC) motor toward IE2/IE3 efficiency classes. The proposed approach integrated Design of Experiments (DOE) using the Taguchi method with loss-based analysis to investigate the influence of key design parameters, including stator stack height, capacitor value, and silicon steel grade on PSC motor efficiency. Taguchi L8 and L9 orthogonal arrays were applied to evaluate parameter interactions and identify dominant factors affecting motor performance. To enhance predictive capability, a Response Surface Methodology (RSM) model was developed based on experimental data to establish the relationship between design variables and motor efficiency within the investigated operating range. The resulting efficiency map was used to identify high-efficiency operating regions and support practical PSC motor design evaluation. Experimental validation under multi-load operating conditions confirmed that the optimized motor achieved an efficiency improvement from 76.1% to 80.4% (4.6% absolute increase), with less than 2% deviation between simulation and experimental results. The optimized motor also demonstrated improved operating behavior across varying speed and load conditions while maintaining practical operating stability. The proposed framework provided a practical and simplified approach for PSC motor efficiency improvement under the investigated operating conditions and offers an alternative to computationally intensive optimization approaches for industrial motor applications. Full article

Spectrophotometry offers the advantage of low cost and less time consumption, making it still attractive as a method of analysis, especially when coupled with multivariate calibration models. This enhancement solves the majority of the drawbacks of UV–VIS spectrophotometry, which have to do with the entangled spectra of complex mixtures. In this study, a multivariate model was developed and validated for the determination of perindopril erbumine, amlodipine besylate and indapamide, addressing previously unresolved challenges by systematically covering three fixed-dose combinations with differing component ratios and by achieving accuracy suitable for the assay determination. The experimental plan involved a Taguchi orthogonal array design with three factors at five levels. In order to create multivariate calibration models, principal component regression, partial least squares and concentration residual augmented least squares regression algorithms were tested. Principal component regression combined with a genetic algorithm for feature selection was chosen as the optimal model based on prediction performance estimated by nested cross-validation with cluster-based sample splitting. The developed method was also evaluated for its environmentally friendly potential while the analytical method validation procedure confirmed its applicability for the assay testing of the fixed-dose drug combination. Full article

Three-dimensional scaffolds based on triply periodic minimal surfaces (TPMSs) have attracted growing interest in bone tissue engineering because of their high interconnectivity and ability to combine high porosity with mechanical integrity. However, in fused deposition modeling (FDM), printed architecture may systematically deviate from the nominal design, thereby affecting structural fidelity and mechanical performance. This study investigated the influence of FDM processing parameters and nozzle diameter on the effective microarchitecture and compressive elastic modulus of polycaprolactone (PCL) gyroid scaffolds. First, a Taguchi L18 design was used to evaluate the effects of extrusion temperature, printing speed, and flow rate on pore size for two nozzle diameters (0.4 and 0.3 mm). In a second experimental stage, prismatic specimens fabricated at three nominal porosity levels were compression-tested to determine the elastic modulus (E), and measured porosity (ϕ) was quantified by densimetric measurements. A systematic mismatch was observed between the nominal design and the printed scaffold architecture, with both pore size and measured porosity consistently lower than their intended values. The dominant process parameter associated with pore-size variability was nozzle-specific: extrusion temperature contributed most for the 0.4 mm nozzle, whereas printing speed contributed most for the 0.3 mm nozzle. In compression, E decreased with increasing measured porosity, and statistical analysis showed that the E–ϕ relationship was nozzle-dependent. Overall, these findings support a process–structure–property interpretation based on the effective printed microarchitecture rather than on nominal design parameters alone. The experimental stiffness ranges obtained here also provide an exploratory mechanical contextualization relative to reported trabecular bone domains, without implying site-specific scaffold selection. Full article

Processing parameters play a key role in the mechanical, thermo-mechanical and creep-recovery properties of unidirectional carbon fiber reinforced thermoplastic polypropylene (CF/PP) composites because of high matrix viscosity, which governs their impregnation and interfacial bonding. This study systematically investigates the effects of molding temperature (190~210 °C), pressure (1~3 MPa), and holding time (5~15 min) on its short beam strength (SBS), storage modulus, loss modulus, tan δ, creep strain, strain recovery, and crystallinity using a Taguchi experimental design. The results presented that processing parameters have a huge effect on CF/PP composites’ SBS, and through the experimental design, the SBS could be improved by 68.1% (21.3~35.8 MPa). Holding time is the most influential parameter for SBS and damping performance, while temperature and pressure interact strongly, highlighting the importance of parameter synergy. There was a strong negative correlation between the crystallinity degree and the SBS of CF/PP composites, and a higher crystallinity degree means a sharper and higher melting peak. Creep-recovery tests reveal near-complete recovery (87~102%) at 30 °C, which decreases to 71~79% at 80 °C due to increased matrix mobility. Finally, it was confirmed that the relatively low SBS of CF/PP composites comes from the void and incomplete matrix impregnation of fibers. The above results advance the design of high-performance, sustainable thermoplastic composites for civil and structural engineering applications. Full article

Hot-rolled A283 Gr C carbon steel/A240 TP 316L stainless steel-clad plates are widely used in structural applications. However, the hot-rolling process introduces residual stresses and microstructural heterogeneities near the interface, which can adversely affect mechanical performance. This study aims to optimize stress-relief annealing parameters for hot-rolled A283 Gr C/A240 TP 316L-clad steel in order to enhance toughness while preserving microstructural integrity. A Taguchi experimental design based on an L9 orthogonal array was employed to evaluate the effects of holding temperature, holding time, and heating/cooling velocity on Charpy impact toughness. Signal-to-noise (S/N) ratio analysis and ANOVA were used to identify the most influential parameters. Microstructural observations, microhardness profiling, and Charpy impact testing were conducted before and after heat treatment. The results indicate that stress-relief annealing does not alter the base microstructures of either the carbon steel substrate or the austenitic stainless steel-clad layer, nor does it induce carbide precipitation or secondary phase formation in the A240 TP 316L stainless steel. A noticeable reduction in the thickness of the decarburized ferrite zone near the interface was observed, suggesting improved interfacial stability. Microhardness measurements revealed a moderate decrease in hardness near the interface, accompanied by a significant increase in Charpy impact toughness under optimized conditions. ANOVA results show that holding temperature is the dominant factor influencing toughness, followed by heating/cooling velocity, while holding time has a minor effect. The optimal stress-relief annealing conditions were identified as 550 °C for 45 min, with a heating/cooling velocity of 100 °C/h. These findings demonstrate that the Taguchi method is an effective approach for optimizing heat treatment parameters and improving the mechanical integrity of hot-rolled stainless steel-clad plates. Full article

This study investigates the optimization of the building envelope parameters of a duplex residential building in Elazig, Türkiye, in line with nearly-zero energy building (nZEB) requirements. The annual energy performance of the case study building was calculated using national BEP-TR version 2.0 software authorized by the Turkish Ministry of Environment, Urbanization, and Climate Change. Wall, roof, floor, and window overall heat transfer coefficients (U-values) were selected as design parameters, and experiments were conducted using the Taguchi method, a well-known experimental design approach, based on an L9 orthogonal array. The results obtained from the Taguchi design were then evaluated using analysis of variance (ANOVA) and grey relational analysis (GRA) to assess energy savings, total initial investment cost, and payback period simultaneously. In accordance with the Türkiye nZEB regulation, photovoltaic (PV) systems were also incorporated to supply at least 10% of the annual energy demand, and their investment cost was included in the economic analysis. The results showed that the wall U-value was the most influential parameter affecting annual energy savings, with a contribution ratio of 49.98%, whereas the window U-value had the dominant effect on total initial investment cost and payback period, with contribution ratios of 93.30% and 95.44%, respectively. The optimum multi-performance combination obtained by GRA was A3B2C1D1, corresponding to wall, roof, floor, and window U-values of 0.25, 0.19, 0.28, and 1.7 W/m²K. These findings offer a practical framework for balancing energy efficiency, investment costs, and regulatory compliance in the design of residential nZEBs in cold-climate conditions. Full article

This study centred on the parametric optimisation and performance prediction of NiCr/WC-Co coatings produced by high-velocity oxygen fuel (HVOF) spraying. An L18 orthogonal experimental design based on the Taguchi method and the response surface method (RSM) was adopted to examine how key process parameters affect the microstructure, phase composition and hardness of the coatings. The results revealed that analysis of variance (ANOVA) indicated that travel speed, methane flow rate, powder feed rate, and stand-off distance were the primary parameters affecting coating hardness, collectively accounting for 76.25% of the total variance. Also, the RSM model established in this study demonstrates remarkably high predictive accuracy, with a coefficient of determination (R²) of 0.985 and an average prediction error of just 1.16%. Verification experiments were also conducted under optimal conditions. The measured hardness was 1352.7 ± 75 HV, in close agreement with the predicted value of 1365 HV. The coating, which was applied using HVOF spraying, had a dense layered structure and low porosity, and the decarburisation of the tungsten carbide was extremely minimal. In addition, interfacial bonding is improved and structural defects are reduced by the addition of a NiCr intermediate layer. It is demonstrated by the results that the Taguchi-RSM method is reliable for the optimization of HVOF spraying parameters and the prediction of coating hardness. Full article

This study investigates the mechanical behavior and durability performance of kaolin clay stabilized using a hybrid system composed of Xanthan Gum biopolymer, polypropylene fibers, and Trivoltherm waste fibers. Experimental studies were designed according to the Taguchi L16 orthogonal array to evaluate the effects of different additive combinations. Unconfined compressive strength tests were performed after curing periods of 7, 28, and 90 days, while durability behavior was assessed through 5 and 10 freeze–thaw cycles. In addition, scanning electron microscopy analyses were conducted to investigate the microstructural characteristics of the stabilized soils. The results indicated that strength increased significantly with curing time, reaching a maximum value of 1186 kPa after 90 days. Statistical analyses showed that Xanthan Gum was the dominant parameter affecting strength development, contributing approximately 57–63% to the unconfined compressive strength behavior. Fiber additives also improved ductility, crack resistance, and freeze–thaw durability through reinforcement and crack-bridging mechanisms. The best-performing mixtures exhibited markedly lower strength losses under freeze–thaw conditions compared with untreated soil specimens. Analysis of variance results confirmed that the investigated parameters were statistically significant (p < 0.05), and the developed models showed high prediction accuracy (R² > 85%). Overall, the findings demonstrate that the synergistic interaction between the biopolymer matrix and fiber reinforcement system provides an effective and sustainable hybrid stabilization approach for improving the engineering performance of clay soils. Full article

The global transition toward carbon-neutral energy solutions has established Solid Oxide Fuel Cells (SOFCs) as a key technology for next-generation power generation. This work presents a comprehensive numerical study and multi-factor statistical analysis of an anode-supported SOFC fueled by synthetic diesel. A three-dimensional computational fluid dynamics model, validated against experimental data, was integrated with a Taguchi L₂₇ orthogonal array to systematically evaluate the influence of six key parameters: temperature, fuel mass flow rate, operating pressure, current load, flow channel configuration, and methane molar fraction. Statistical analysis through the signal-to-noise ratio and analysis of variance identified the operating current as the most significant factor affecting cell voltage, followed by the fuel mass flow rate and temperature. The experiments showed that the highest levels of all factors (except for the current, which had the lowest level) maximize electrochemical performance while maintaining a steam-to-carbon ratio (S/C) within a range of 0.83 to 0.92, calculated based on total carbon content, ensuring sufficient humidification for internal reforming across all tested fuel compositions. Furthermore, a multiple linear regression model was developed as a computationally efficient surrogate, demonstrating exceptional predictive accuracy with an R² of 0.9954 and a mean relative error of 1.76% across independent validation cases. These results provide a robust methodology for rapid design and sensitivity analysis of internal-reforming SOFCs, offering a precise tool for optimizing fuel utilization in high-temperature electrochemical systems. Full article

Carbon fiber-reinforced thermoplastic composite drilling is a secondary manufacturing process because the quality of drilled holes affects assembly system performance, structure, and sustainability. This paper compares all drill coating types and cutting conditions for PEEK-CF30 composite drilling utilizing a hybrid experimental–statistical method. DLC-, TiN-, and TiCN-coated HSS drills, as well as cutting speed and feed rate were tested using the Taguchi L27 design. Performance indicators were measured by including thrust force, surface roughness, drilling torque, and energy consumption. Experimental results showed that increasing cutting speed and feed rate increased the thrust force while decreasing torque and energy consumption. Smearing on the hole surface, chip adhesion, and short fiber adhesion/pull were identified as indicators of poor surface quality, and these occurrences increased with increasing drill coating removal at high cutting parameters. In terms of overall performance, the TiCN-coated drill created the lowest thrust force (50.85 N), surface roughness (1.038 µm), torque (17.54 Ncm), and energy consumption (136.45 J) at high feed conditions. Taguchi-based gray relational analysis methodology revealed that the TiCN-coated drill, a cutting speed of 40 m/min, and a feed rate of 0.1 mm/rev are the optimum parameters. Second-order prediction models developed for all responses proved to have high predictive capabilities with coefficients of determination above 94%. Ultimately, drill coating quality considerably affected surface integrity and drilling energy consumption performance in drilling PEEK-CF30. A hybrid optimization and modeling framework demonstrates that the drill quality cutting parameter will allow for optimum selection to ensure efficient processing of advanced thermoplastic composites. Full article

Honeycomb composites are extensively utilized in critical applications where weight is a concern in a structure, due to their high efficiency in stiffness-to-weight ratio. In this study, the effective elastic orthotropic behavior of honeycomb composites is analytically expressed as a function of the elastic properties of the constituent sheet material and the geometric parameters of the representative unit cell. Closed-form expressions based on classical beam theory and plate theory are evaluated and systematically validated against a high-fidelity finite element analysis FE-based homogenization benchmark constructed from a representative unit cell with in-plane periodic kinematic constraints. The analytical predictions exhibit generally good agreement with the FE results, with plate-theory-based formulations capturing most elastic constants with higher accuracy. To further support the fidelity of the numerical benchmark, the predicted normalized in-plane moduli are additionally compared with published experimental measurements for aluminum honeycombs, demonstrating close agreement for representative specimens. To quantify the influence of the geometric parameters, a Taguchi-style design-of-experiments (DOE) study reveals that relative density and internal cell angle jointly govern the majority of elastic moduli and Poisson’s ratios, while cell height plays a minor role. Furthermore, dedicated parametric studies confirm the cubic thickness-scaling of in-plane moduli ($E_1$, $E_2$, $G_{12}$), demonstrating the dominant role of bending-controlled deformation. Together, these results establish a validated, high-fidelity FE homogenization benchmark for assessing analytical formulations and providing design-level constitutive data for optimizing honeycomb core sandwich structures. Full article

This research evaluates the feasibility of using a lignocellulosic biosorbent prepared from mature leaves of Asplenium scolopendrium (produced through simple mechanical processing of the leaves, without applying any chemical modification or heat treatment) for the removal of methylene blue from water. Before and after adsorption the material was characterized using SEM technique and color analysis. Subsequently, the adsorption behavior was analyzed by examining equilibrium, kinetic, and thermodynamic aspects of the process. The equilibrium data were best represented by the Sips isotherm model, while the adsorption rate followed the Avrami model. Thermodynamic evaluation indicated that the retention of the dye occurs predominantly through a physical adsorption mechanism, while a minor contribution from chemisorption may be present, slightly enhancing the overall dye uptake. Process optimization was performed using the Taguchi experimental design, which also allowed the identification of the most significant operational variable. In addition, analysis of variance (ANOVA) was applied to quantify the contribution of each factor affecting dye removal efficiency. Among the investigated variables, time showed the strongest influence (72.65%), whereas temperature had a negligible effect (1.33%). The maximum adsorption capacity reached 174.1 mg/g, surpassing the performance of several comparable biosorbents reported in the literature. Overall, the findings demonstrate that Asplenium scolopendrium (hart’s-tongue fern) leaves represent an inexpensive, sustainable, and efficient material for eliminating methylene blue from aqueous solutions. Full article

Pyrolysis of refuse-derived fuel (RDF) is a promising waste-to-energy route, but its use in higher-value applications remains limited by tar carryover, benzene, toluene, ethylbenzene, and xylenes (BTEX), heteroatom-containing compounds, and pollutant accumulation in recirculated scrubber water. This study evaluated operating windows for RDF pyrolysis coupled with direct wet scrubbing and closed-loop water reuse, with the aim of identifying regimes suitable for different end-use tiers. A Taguchi L27 design of experiments (DOE), i.e., an orthogonal array comprising 27 experimental runs, was applied to evaluate the effects of pyrolysis temperature, residence time, scrubber liquid-to-gas ratio, and scrubber-water temperature, while sequential reuse of the same scrubber-water inventory was evaluated at 5, 10, and 15 cycles. Cleaned-gas pollutants were quantified by compound-resolved gas chromatography–mass spectrometry (GC–MS) after solid-phase adsorption (SPA) sampling, while phenolics and polycyclic aromatic hydrocarbons (PAHs) in scrubber water were determined by extraction followed by GC–MS. Feasibility within each end-use tier was defined as simultaneous satisfaction of tier-specific cleaned-gas thresholds (C_tar, C_BTEX, I_N, and I_S) and the corresponding water-loop hazard limit (I_tox), using literature-informed engineering screening criteria. The results showed that stronger scrubbing reduced gas-phase tar and BTEX burdens, whereas extended water reuse caused systematic accumulation of phenolics and PAHs and increased the composite water-loop hazard index. Boiler-grade operation remained feasible across a broad operating range, with 23 of the 27 tested conditions remaining robust, whereas internal combustion engine combined heat and power (ICE-CHP) feasibility was restricted to a narrow robust regime, and no robust microturbine-grade condition was identified. These findings show that operating windows for RDF pyrolysis must be defined jointly by gas cleanliness and water-loop management constraints. Full article

To address the challenges associated with laser powder bed fusion (LPBF) of overhanging structures—namely warping deformation, powder adhesion, and inadequate forming accuracy—this study investigates the optimization of the support–part contact interface using Inconel 625 alloy. The objective is to achieve high-quality part formation with minimal support structures. A Taguchi experimental design was employed to systematically evaluate the effects of key block support parameters—tooth height, tooth top length, tooth base length, and tooth base spacing—on the forming performance of overhanging structures, with forming accuracy and support removability as the optimization targets. The results reveal that tooth top length significantly influences both the forming accuracy of overhanging specimens and the ease of support removal. Specifically, an increase in tooth top length leads to a rapid reduction in specimen deformation, but simultaneously increases the difficulty of support removal. When the tooth top length was set to 0.1 mm, all overhanging specimens failed to form successfully. Tooth base length also plays a critical role in support removability, with removal difficulty initially decreasing and then stabilizing as the tooth base length increases. Based on the trade-off between forming quality and support removability, the optimal parameter combination was identified as: tooth height of 0.4 mm, tooth top length of 0.7 mm, tooth base length of 1.0 mm, and tooth base spacing of 0.3 mm. A validation experiment conducted using this optimized configuration demonstrated good forming accuracy in the support contact area, with a deformation value of −0.208 mm, confirming the effectiveness and reliability of the proposed parameters. This study not only provides a theoretical foundation for the optimal design of block supports in LPBF but also offers experimental data and practical guidance for selecting support parameters in the fabrication of overhanging structures. Full article

This study aims to investigate the effect of manufacturing parameters on the mechanical properties of PC-ABS samples produced by the Fused Deposition Modeling (FDM) additive manufacturing method and to model these relationships using machine learning methods. In the study, the parameters of printing speed, infill density, and raster angle were determined according to the Taguchi L16 experimental design, and tensile, bending, and impact tests were performed on the produced samples. Experimental results showed that the infill density parameter resulted in an increase in tensile strength of approximately 62% (from 25.10 MPa to 40.71 MPa) and an increase in flexural strength of approximately 46% (from 45.13 MPa to 66.13 MPa). Furthermore, an improvement in impact energy of approximately 45% (from 1.698 J to 2.467 J) was achieved under optimum printing speed conditions. Mechanistic properties were predicted using Decision Tree, Random Forest, K-Nearest Neighbors, and Multilayer Perceptron models with a dataset generated from experimental data. Comparing the model performances, the Random Forest algorithm was found to provide the highest prediction performance with accuracy in the R² range of 0.94–0.99 and RMSE values below 0.5, demonstrating strong generalization capabilities. The results showed that infill density is the most decisive parameter on both tensile and flexural strength, and that printing speed has a significant effect, especially on impact energy. ANOVA analyses revealed that all main parameters have statistically significant effects on mechanical properties. In the performance comparison of the machine learning models, the Random Forest algorithm provided the highest prediction accuracy, demonstrating that mechanical properties can be reliably predicted. In conclusion, it has been shown that the mechanical performance of PC-ABS parts produced by the FDM method can be optimized by using the correct selection of production parameters and machine learning-based modeling approaches. Full article