Vishwas Mahesh

Rotating machinery is vulnerable to catastrophic failure when shaft cracks and rotor mass variations remain undetected, yet systematic studies of their combined influence within a controlled benchmark rotor remain limited. This work develops a physics-based computational–experimental framework that integrates finite-element modelling in ANSYS, a Jeffcott rotor test rig and a Taguchi L9 design with ANOVA to quantify how disk mass, crack number and crack depth affect the first-mode vibration frequency. A nonlinear breathing-crack FE model with time-varying stiffness was formulated and then reduced to an equivalent static notch representation for efficient frequency prediction, and its natural-frequency predictions were validated against experiments on nine crack–mass configurations. Taguchi response tables and ANOVA identify disk mass as the statistically dominant factor governing frequency, while crack parameters primarily manifest through 2X harmonic content and orbit distortion in the experimental spectra. The optimized configuration yields a predicted first-mode frequency near 24.7 Hz with a mean absolute experimental error of about 0.5 Hz and regression fits with R ² ≥ 0.9856, indicating highly reliable estimation over the investigated design space. Rather than proposing a new rotor model or crack signature, the study provides a validated benchmark-level framework for quantifying interacting fault effects in a Jeffcott rotor and supports future extension towards more realistic multi-disk industrial systems, condition-based maintenance schemes and structural health monitoring strategies.

This study investigates the influence of cenosphere and graphene nanoplatelet (GNP) reinforcements on the physical, mechanical, and dimensional accuracy characteristics of PLA-based composites fabricated using Fused Filament Fabrication (FFF). The incorporation of cenospheres effectively reduced the composite density from 1.25 g/cm ³ for neat PLA to 1.19 g/cm ³ and 1.14 g/cm ³ for 5 wt% and 10 wt% cenosphere additions, respectively, demonstrating the lightweighting capability of hollow ceramic fillers. The void content increased progressively with reinforcement loading due to increased melt viscosity, particle agglomeration, and localized air entrapment during processing, with values ranging from 2.14% to 8.09% for the reinforced composites. Despite the increase in porosity, graphene nanoplatelets improved the overall stiffness and stress transfer efficiency of the composites through enhanced interfacial interaction and restriction of polymer chain mobility. Mechanical characterization revealed substantial enhancement in hardness, reaching a maximum value of 91.5 Shore D for the hybrid PCG-5 composite, attributed to the synergistic reinforcement effect of rigid cenospheres and high-stiffness graphene nanoplatelets. Dimensional accuracy analysis identified layer thickness as the most influential processing parameter, contributing nearly 79% of the total variation, with lower layer heights consistently improving geometric fidelity. Statistical analyses using Taguchi design, ANOVA, contour mapping, and regression modeling confirmed this trend, while Random Forest regression further validated the experimental findings with a high prediction accuracy (R ² = 0.94) and minimal prediction error. Feature importance analysis also established layer thickness as the dominant governing factor, followed by printing speed and raster angle. Overall, the integration of experimental optimization and machine learning provides an effective framework for improving dimensional precision and mechanical performance in additively manufactured PLA hybrid composites intended for lightweight engineering applications.

Fused Filament Fabrication (FFF) is a highly sought-after manufacturing method that builds parts layer by layer using thermoplastic and/or composite filaments. However, it is characterised by weak interlayer adhesion, resulting in low interlaminar strength in printed structures. Recent research suggests that post-processing heat treatments can address this issue by lowering internal thermal stresses and increasing interlayer bonding, thereby improving part properties. This study investigates the effect of annealing heat treatment on a composite consisting of glycol-modified polyethylene terephthalate (PETG) and organically modified montmorillonite nanoclay (OMMT-NC). The annealing temperature was set at 90°C, and the time duration was varied to 60, 120, and 180 minutes. The mechanical, morphological and surface properties of the OMMT-NC reinforced PETG composite were compared with those of pure PETG. Also, annealing effect on the glass transition temperatures was determined by differential scanning calorimetry (DSC). Atomic Force Microscopy (AFM) was used to investigate the change in surface roughness resulting from annealing. The experimental results show that PETG reinforced with 3 wt.% OMMT nanoclay improved the tensile, compression, flexural, and impact strength by 6.9%, 22.9%, 30.3%, and 87.5%, respectively, after annealing. The hardness also increased across all PETG composites by at least 5%, due to improved interlayer adhesion. Morphological studies were conducted to correlate the deformation behaviour and assess the impact of annealing. The findings of this work indicate that PETG/OMMT-NC composites are a potential candidate for structural applications.

The study focuses on the abrasive wear characteristics of epoxy composites incorporating agricultural waste-surface treated coconut shell powder (CSP) as filler. To determine the effect of surface modifications on wear resistance, three different filler CSP conditions were used: untreated, alkali-treated, and silane-treated. It was found that surface treatment greatly improves the adhesion between the matrix and the filler, improving wear performance. The improvement in alkali treatment was caused by stronger mechanical interlocking due to the removal of superficial deposits: it was found that silane treatment using 3-aminopropyltriethoxysilane resulted in the greatest improvement, yielding 35% lower wear rates than untreated composites at optimal 20 wt.% filler loading. The wear modes under the micro-ploughing dominant regime underwent change to severe cutting and delamination with increasing loads from (10N to 30N) with silane treated composites outperforming all other conditions. This change occurred prematurely in silane composites. SEM analysis backed these results with images showing silane-treated samples having few signs of particle pullout and features of ductile wear. Statistical analysis performed using ANOVA and Tukey’s test proved the hypothesis concerning surface treatment having an effect was true, showing silane treated CSP composites are a viable candidate for applications with critical wear conditions.

This study investigates the influence of key additive manufacturing parameters on the mechanical performance of polyethylene terephthalate glycol (PETG) and carbon fiber-reinforced PETG (CF-PETG) composites fabricated through fused filament fabrication (FFF). Eighteen specimens were printed with varying infill densities (50%, 75%, 90%), infill patterns (gyroid, cubic, triangle), printing speeds (40–50 mm/s), and layer thicknesses (0.1–0.3 mm). Mechanical testing showed that CF-PETG printed at 90% infill, triangular pattern, 45 mm/s speed, and 0.1 mm layer thickness achieved superior compressive strength, recording 47.21 MPa at 10% and 61.56 MPa at 50% deformation-a 42% improvement over the best PETG counterpart. Flexural strength of CF-PETG printed at 75% infill, cubic pattern, 50 mm/s, and 0.1 mm layer thickness increased by 23%, reaching 59.2 MPa, while tensile strength gains remained marginal. In contrast, PETG printed at 90% infill, triangular pattern, 45 mm/s, and 0.1 mm layer thickness exhibited higher impact strength (2.55 kJ/m ² ) than CF-PETG (1.44 kJ/m ² ), reflecting a stiffness–toughness trade-off. Design of Experiments analysis identified infill density as the most influential factor for both materials. PETG performance improved with increasing infill and pattern complexity, whereas CF-PETG reached optimal properties at moderate speeds and simpler patterns, likely due to sensitivity in fiber dispersion and matrix bonding. Interaction plots showed that parameter combinations significantly affect tensile and flexural behaviour, with CF-PETG exhibiting more irregular responses due to complex fibre–matrix interactions. Optimization using desirability functions produced composite desirability values of 0.8518 for PETG and 0.9872 for CF-PETG, confirming the superior performance potential of fibre-reinforced systems when appropriately tuned. Overall, carbon fiber reinforcement enhances mechanical properties, especially compression and modifies process-property relationships, requiring more precise control of FFF parameters for structural applications.

Syntactic foams reinforced with industrial waste-derived cenospheres and rubber crumb fillers present a promising pathway for developing lightweight, impact-resistant materials. However, a comprehensive comparison of their energy absorption characteristics under low velocity impact (LVI) loading remains underexplored. This study investigates the LVI response of syntactic foams with varying volume fractions (20%, 40%, and 60%) of cenospheres (SFC) and rubber crumb (SFR), benchmarked against neat epoxy (NE). The key findings indicate that rubber crumb-reinforced foams (SFR60) exhibit the highest absorbed energy of 16.75 J at an impact energy of 118.82 J, surpassing the NE (6.46 J), indicating superior impact dissipation. Cenosphere-based foams (SFC60) achieve the highest specific energy absorption (SEA) of 0.0115 Jm³/kg, a 117% improvement over NE (0.0053 Jm³/kg), due to their lower density and increasing filler content from 20% to 60% significantly enhances both absorbed energy and SEA, with cenosphere-reinforced foams exhibiting higher efficiency per unit mass. These findings highlight the performance trade-offs between energy absorption capacity and material efficiency, providing valuable insights for designing sustainable syntactic foams for aerospace, automotive, and protective applications.

The study investigates the relationship between rubber crumb particle size and the abrasive behavior of polymer composites, using statistical optimization techniques. Polymer composites with different rubber crumb sizes were synthesized and subjected to abrasion tests. Taguchi’s L18 orthogonal array was employed to analyze the effects of filler particle size (2 levels), filler weight percentage, load, and time (3 levels each) on the specific wear rate of the developed composites. Analysis of variance (ANOVA) revealed that particle size significantly influenced abrasion resistance, with a P-value of 0.073 and an F-value of 3.8 from Taguchi’s Design of Experiments (DOE). Smaller particles exhibited milder abrasion, characterized by smoother surface interactions and lower material removal, while larger particles caused more aggressive abrasion due to rougher surfaces, larger contact areas, and higher stress concentrations. The findings highlight the pivotal role of rubber crumb particle size in tailoring the abrasive properties of polymer composites. This study provides a framework for optimizing material performance, offering significant potential for applications in sectors requiring durable and wear-resistant composites, such as automotive, construction, and aerospace.