Today, orthopedic surgeons have been continuously focusing on bone tissue engineering for regenerating damaged bone through the use of biomimetic scaffolds and innovative materials. Hence, this study presents a comprehensive investigation into the optimization of PLA + 3D printed lattice scaffolds for bone tissue engineering applications, emphasizing the role of geometric configuration and processing parameters on mechanical performance. Three distinct lattice geometries such as Lidinoid, Diamond, and Gyroid were developed with varying wall thicknesses (1.0 mm, 1.5 mm, and 2.0 mm) and subjected to compressive loads of 3 kN, 6 kN, and 9 kN. A Taguchi L₂₇ Orthogonal Array was employed to evaluate key mechanical responses, including displacement and strain. Among these configurations, the Gyroid lattice exhibited superior mechanical integrity, demonstrating the least displacement (0.36 mm) and strain (1.2 × 10⁻²) at 3 kN with 2.0 mm thickness, whereas the Lidinoid structure showed the highest deformability. A Back-propagation Artificial Neural Network (BPANN) model was developed to predict scaffold behavior with remarkable accuracy (R² = 0.9991 for displacement, R² = 0.9954 for strain), further Finite Element Analysis (FEA) was conducted to validate both experimental and predicted results. The novelty of this work lies in its integrative, multi-modal approach that synergizes experimental design, machine learning-based predictive modeling, and simulation. The focus of this study is to define a robust framework for optimizing scaffold architecture, with significant implications for enhancing mechanical strength and biological performance in bone healing applications.

The L5-S1 segment of the spine is highly susceptible to injury, frequently causing low back pain. The segment has gained a lot of scientific interest, leading to many experimental works that can be found describing its biomechanical characteristics. But, there is a lack of work focusing on its computational studies, which can significantly aid its further studies. In the current study, a subject-specific single-segment finite element model of the L5-S1 unit was developed from a T2-mapped MRI scan. This study is mainly intended to probe the requirements for modelling the annulus of the disc and also attempts to understand the role of ligaments exclusive to the L5-S1 spinal unit to establish its validated finite element model. The annulus was represented by two different forms of hyperelastic material models (isotropic and anisotropic) for which the constants were determined from experimental data found in the literature. Their ability to impart the required characteristic was tested for the finite element model to mimic the experimental responses during sagittal and lateral moment loads. A comparison of results with the two material models is also discussed for other valuable parameters like contact pressure at the facets, maximum von-Mises stresses in the vertebrae, ligament strains, and midplane Tresca shear stresses of the annulus. The anisotropic Gasser-Ogden-Holzapfel (GOH) model was observed to deliver a response that consistently showed good compliance with the experimental response and hence, it is recommended for the computational studies of this segment.

Low back pain is a serious health concern prevalent in majority of the people around the world, especially in case of the elderly. The root cause for this is mostly observed to be the development of lesions/ tears complemented by degenerative effects in the intervertebral disc of L4-L5 and L5-S1 segments. This study aims to analyse the effects of disc degeneration and tears on the mechanical responses of the L5-S1 spinal unit, which has not been investigated. The annulus is represented by an anisotropic hyperelastic Gasser-Ogden-Holzapfel (GOH) model wherein the effect of degeneration is defined by varying the constants responsible for the behaviour of the material in different strain-ranges. A systematic approach is proposed for modelling the effects of disc degeneration in the annulus. Further, the commonly found anterior circumferential tear is modelled to understand its combined effects with degeneration of the annulus. The damaging effect of the tear was limited only to extension movement, causing critical stress variations in its vicinity. However, degeneration had a significant influence on both stress and range of motion of the spinal unit across all types of movements. This study highlights the complex relationship of the physiological movements with pathogenesis of tear and degeneration leading to discogenic pain thus enabling clinicians to develop conservative treatment strategies for specific age groups.

Digital twin (DT) technology has emerged as a cornerstone of Industry 4.0, facilitating real-time synchronization between physical assets and virtual models to drive operational excellence. Unlike prior surveys that address singular industrial domains, presenting qualifications in general terms without paradigm-to-task mapping, this review uniquely synthesizes DT architectural maturation across Technology Readiness Levels (TRLs) 1 through 9, quantitative performance outcomes from 39 documented industrial implementations spanning 10 sectors, and an explicit algorithmic taxonomy mapping distinct AI paradigms to specific functional DT requirements. By synthesizing empirical data across the aerospace, automotive, and manufacturing sectors, this study evaluates the quantitative impact of DT implementation, highlighting significant gains in predictive maintenance, production efficiency, and design cycle reduction. This research further examines the synergistic role of Machine Learning (ML) paradigms integrated within DT systems, specifically, physics-informed neural networks (PINNS), generative adversarial networks (GANs), deep transfer learning, reinforcement learning, and federated learning, in enhancing diagnostic accuracy and enabling autonomous decision-making. Despite these advancements, this review identifies critical barriers in data interoperability, cybersecurity, and workforce expertise that impede widespread adoption. This paper concludes by outlining future research directions, emphasizing the necessity for standardized data protocols and secure, distributed DT ecosystems to unlock the full potential of cyber-physical integration in a data-driven industrial landscape.

Multi-grooved water-lubricated bearings (MGWLBs) are widely used in marine stern tube applications, where hydrodynamic performance is strongly influenced by groove geometry and operating conditions. This study presents a combined experimental and computational investigation of water film lubrication characteristics in MGWLBs with different groove geometries. An experimental test setup redesigned to replicate the operational behavior of MGWLBs was employed to record the circumferential film pressure variations under varying rotational speeds and applied loads. Detailed experimental tests were performed on a MGWLBs with filleted V-shaped grooves, where the film pressures at the bearing midplane were measured using a flush-mounted diaphragm pressure sensor mounted on a hollow shaft. The experimental results revealed a transition from localized, non-uniform pressure generation at low speeds to stable and circumferentially continuous hydrodynamic pressure fields at higher speeds and loads. CFD simulations were also conducted to analyze the influence of groove geometry on pressure distribution and flow behavior. An increase in rotational speed was shown to significantly enhance pressure magnitude, circumferential continuity, and film stability under moderate to high loading conditions. Filleted V-shaped, semicircular, and short V-shaped groove models were analyzed for a speed range of 400 to 6000 RPM. Filleted V-shaped grooves produced smooth pressure development with moderate gradients, while semicircular grooves improved pressure and velocity uniformity by limiting localized intensification. In contrast, short V-shaped grooves generated higher peak pressures due to enhanced flow acceleration at groove–land interfaces. The findings provide design guidance for selecting groove geometry and operating conditions to enhance the hydrodynamic performance of marine water-lubricated bearings.