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Patient-specific cerebral aneurysms exhibit complex hemodynamics insights that influence thrombus formation, wall remodeling, and therapeutic delivery. The article presents a high-fidelity, multi-parametric CFD analysis of nine distinct aneurysm cases using 3-D model-resolved meshes, non-Newtonian Casson rheology, and steady-state flow conditions. Further, the Lagrangian particle tracking was employed to assess drug transport and hemodynamic metrics such as WSS and normalized residence time (NRT) were evaluated, along with vortex dynamics, indicators including helicity ( H ) and Q criterion to characterize rotational flow structures. Results reveal that narrowed neck models (m 1 , m 2 , m 5 , m 8 ) exhibit weak vortex structures and dominant axial washout (velocity magnitude < 0.10 m/s; NRT < 0.2), while sac-expanded geometries (m 3 , m 4 , m 6 , m 9 ) support robust helical vortices ( H  > 40 m²/s², Q  > 0) and elevated residence times. Regions of low WSS (τ w  < 0.5 Pa) spatially co-localize with high NRT and potential thrombogenicity, whereas high WSS (τ w  > 2.5 Pa) associates with jet impingement zones and possible endothelial damage. Notably, sharp WSS gradients are identified as destabilizing hemodynamic factors. Rheological analysis reveals a critical threshold at γ̇ ≈ 415 s⁻¹ ( µ  ≈ 6.4 mPa·s), distinguishing thrombosis-prone regions (low γ̇, high µ) from stable zones (high γ̇, low µ). Particle transport studies show that effective drug retention occurs in high-helicity, wide neck models for Stokes number (St = 0.1–1), while laminar-dominant aneurysmal flows demonstrate poor drug deposition due to axial convection. Overall, the findings underscore that aneurysm stability and therapeutic outcomes are governed by the interplay of aneurysm induced flow structures, WSS heterogeneity, non-Newtonian rheology, and vortex coherence are refining rupture risk assessments and optimizing endovascular drug delivery strategies.

The economic base of Jammu and Kashmir has turned so weak as a result of continued disturbances in the state that finances of the state are almost dependent on central grants in aids. However, there are huge opportunities in hydropower generation, transportation, tourism, pharmaceuticals, biotechnology, information technology, horticulture, sericulture, dairy products, food processing and real estate etc. but it could not be exploited in lack of private investment in the state's economy due to the law and order situation. If there is proper policy response from the government and the confidence of the private investors is restored, these opportunities can be exploited over short to medium span of time.As a result,not only centres like Srinagar and Jammu but many other centres likeAnantnag, Samba, Baramula and Pulwama would also be turned into hub for economic activities.

In this work, the development of an aircraft bracket through the laser powder bed fusion (LPBF) additive manufacturing process is presented. The numerical model developed in this study is employed to predict thermal stresses and displacement of parts throughout the additive manufacturing process. To achieve a reduction in volume and, subsequently, the design space of the aircraft bracket, a geometry optimization technique - Topology Optimization is implemented. Additionally, the 3D Printed Titanium alloy aircraft bracket is subjected to industry-standard loading for analysis. In the simulation model, new elements are activated for every layer to simulate the recoating of filament powder, and the thermal gradient, thermal stress, and displacement of parts associated with each layer are computed. Notably, the topology optimization of the geometry demonstrates a considerable reduction in residual stress generation and a significant decrease in mass. The Solid Isotropic Material with Penalization (SIMP) method is employed in this study for topology optimization. The quality of the printed part is notably influenced by the geometry of the bracket. The findings of this study contribute to advancing the understanding of the interplay between topology optimization and additive manufacturing and highlight their collective potential for shaping the future of aerospace equipment fabrication. A volume percentage ranging from 50 to 75% of the original mass was allocated to guide the optimization process. The optimized geometry at 75% volume demonstrates the greatest reduction in residual stress generation compared to the original implant. This improvement in stress distribution is significant for aerospace brackets, as it allows for the development of lighter, stronger brackets manufactured more affordably using the Laser Powder Bed Fusion (LPBF) process compared to conventional processes.

Building corporeal replicas, examples, workings, tools, and functional components from 3D data developed with a computer (CAD), by advanced geometry, utilising Additive Manufacturing - AM, which is difficult or impossible to do with traditional manufacturing processes, is likely. AM methods employ metals, ceramics, and polymers in the form of liquids, powders, wire, foil, and other materials to manufacture prototypes. However, there are several limitations, the most important of which being material selection. As a result, knowing material properties and how machine settings impact them is crucial, especially if the machine is creating functional components. The effect of component location in the build (in the X and Y directions) on the dimensional accuracy and mechanical quality of products produced using this SLS techniquewill be investigated in this research

This study presents the development of an aircraft bracket through the laser powder bed fusion (LPBF) additive manufacturing process. The investigation incorporates distinct critical process parameters, namely build orientation (X, Y and Z) and material properties such as stainless steel 316L, AlSilOMg and TI-6AI-4V. The primary focus is on assessing residual stresses and deformation, with the objective of determining the optimal process parameter combinations. Numerical simulations are conducted using Altair Inspire AM software. Certain demerits of deformation and residual stress-related cracking are identified as irreparable through post-processing interventions. An understanding of the inter dependencies among input process parameters yields insightful observations. Specifically, the study reveals a positive correlation between build orientation in Y-Direction and an increase in residual stresses. However, dimensional deformation remains relatively unaffected by any build orientation. Optimal results are observed when utilizing aluminium as the material, with X-Direction as the preferred build orientation. However, it's important to note that different materials should also be assessed according to their material properties and printing needs. These findings underscore the critical importance of parameter selection and process optimization within LPBF to address inherent challenges.

SLS (selective laser sintering) is a powder-based#rapid prototyping (RP) technique that involves selective sintering of powder layers using a CO2#laser. SLS is becoming more popular by way of a quick manufacturing technology for producing functional components in small numbers, especially in aerospace and rapid tooling. As a result, SLS prototypes must be extremely accurate in order to meet functional requirements. This research study demonstrates an effective strategy for determining the ideal SLS processing parameter in order to produce components with improved component integrity and lower overall costs. In this article, the factorial technique was used to create three input parameters for creating work components using the SLS process: layer thickness, orientation, and porosity(artificial porosity as honeycomb assembly). CL 20ES is the material that has been utilised (stainless steel-316). After creating work components, output metrics such as ultimate tensile strength (UTS), hardness, yield strength, elongation, and weight were used to test them. An study was conducted in order to determine the best parameter values for improved output

In recent years, the engineering implications of carbon nanotubes (CNTs) have progressed enormously due to their versatile characteristics. In particular, the role of CNTs in improving the tribological performances of various engineering materials is well documented in the literature. In this work, an investigation has been conducted to study the tribological behaviour of CNTs filled with glass-reinforced polymer (GFRP) composites in dry sliding, oil-lubricated, and gaseous (argon) environments in comparison to unfilled GFRP composites. The tribological study has been conducted on hardened steel surfaces at different loading conditions. Further, the worn surfaces have been examined for a particular rate of wear. Field-emission scanning electron (FESEM) microscopy was used to observe wear behaviours. The results of this study explicitly demonstrate that adding CNTs to GFRP composites increases wear resistance while lowering friction coefficient in all sliding environments. This has also been due to the beneficial strengthening and self-lubrication properties caused by CNTs on GFRP composites, according to FESEM research.

Purpose The purpose of this paper is to optimize the design of a hybrid tether using probabilistic approach considering inherent random variation in the stress developed and the strength it has. The variation in strength is mostly because of variation in diameter of the tether and the properties of the material along the length of the tether. As a result, classical design approach for the tether may not serve the purpose. For this purpose, a reliability-based design of hybrid tether is discussed in this paper. Design/methodology/approach A literature review was carried out on the design of tether and its operational reliability. It has been shown that the classical design approach does not serve the purpose, as the strategic operation has to be reliable enough, often requiring a measure of reliability required. A reliability-based approach has been presented to achieve the optimum design of a hybrid tether. Findings The optimization problem was carried out for different values of the safety factor to investigate the effect on the optimal design of tether. An analysis is carried out to show that one should not target a very high value of reliability or factor of safety, as it causes the self-weight of the tether to increase tremendously and its cost significantly. Research limitations/implications The present work has been carried out considering the limited data and can further be extended to determine more accurate reliability measures by considering more number of sample test data. The measured data is collected from limited required trials for demo; do not represent the exact population data. Originality/value Lab strength test and flight trials were conducted to acquire data for the present analysis. In field use, it was noticed that the tether degraded from top portion attached toward the balloon end because of maximum exposure and repeated usage.

The present research work explores the implementation of three smart hybrid predictive models based on the adaptive neuro-fuzzy inference system (ANFIS), ANFIS and genetic algorithm (GA), and ANFIS and particle swarm optimization (PSO). All such strategies have been used to determine and compare machining key elements including material removal rate (MRR) and surface roughness (SR) during the gas-assisted electrical discharge (GAEDM) process. In this study, inert gas-based EDM with a multi-hole rotating tool has been carried out. In this experimentation, pulse-on time, peak current, duty cycle, electrode rotation, and gas discharge pressure were selected as input factors. The proposed method is to upgrade ANFIS with GA and PSO techniques. The GA and PSO algorithms are used to enhance the accuracy of the ANFIS model. The models have been trained, tested, and validated with observational results. Statistical techniques were applied to assess the effectiveness of the predictive capability models established through the ANFIS, ANFIS-GA, and ANFIS-PSO techniques. The actual and predicated estimates of MRR and SR of the GAEDM, obtained by ANFIS, ANFIS-GA, and ANFIS-PSO, were observed to be as per one another. In addition, the ANFIS-PSO framework proved to be even more responsive when compared with the ANFIS and the ANFIS-GA system. In particular, the assertion of this work is that modified algorithms such as ANFIS-GA and ANFIS-PSO are an efficient and productive approach to accurate EDM response estimation.

There is almost a broad consensus that electric vehicles coupled with renewable energy are greener and sustainable mode of transportation for India. However India needs to tread carefully. There is need to put infrastructures like battery charging stations and batteries management facilities in place to make electric vehicles viable option in India. But prior to this, adequate policy response is needed from the government to update its laws which could accommodate Li-ion and other types of batteries into its ambit. Moreover Indian Government has allocated budget for promotion of electric vehicles but that wouldn’t be enough. To speed up this process, there is a need for the participation from the corporate sector. Corporate sector can participate either by investing in the business to earn profits or in form of corporate social responsibility to help build a sustainable world. Also India needs to be careful that the push to electric vehicles wouldn’t result into increase in child labour and violation of human rights.