Augustine Benjamin Valerian Barboza

Background/Objectives: This study evaluates the effects of axial and inclined loading on dental implants modeled with different material properties, thread geometries, and micro-thread configurations to compare their relative effects on stress and deformation behavior in cortical and cancellous bone. Methods: Five implant materials—dentine, titanium, ZrO₂, PEEK, and CFR-PEEK—were analyzed. Each implant model incorporated one of three primary thread designs: buttress, V-thread, or reverse buttress, with and without micro-threads. A three-dimensional finite element model of the implant embedded in cortical and cancellous bone was developed and subjected to a 111.8 N load, representing typical human bite force, applied both axially and at an inclination using ANSYS Workbench 2023 R1. Results: Inclined loading generated substantially higher cortical stress and higher deformation in both cortical and cancellous bone compared to axial loading. Among the materials tested, PEEK exhibited the highest cortical stress concentration and the highest deformation, whereas CFR-PEEK produced the smallest stiffness mismatch with bone among the implant materials, giving intermediate peri-implant stress and deformation, particularly when combined with reverse buttress threads. The effect of micro-threads on cortical stress was material-dependent, increasing for the lower-modulus materials and decreasing slightly for titanium and zirconia. Conclusions: Within the assumptions of this model, CFR-PEEK with reverse buttress threads produced intermediate stress and deformation values between the stiff (titanium, zirconia) and compliant (PEEK) materials under the modelled conditions. Any localized stress change associated with micro-threads represents a change in the computed stress field only; any implication for bone adaptation or osseointegration is beyond the scope of this stress-based model. These findings represent comparative design tendencies that require experimental and clinical validation.

The postoperative microenvironment is a highly biologically dynamic environment that is associated with an increased risk of complications, including adhesions, fibrosis, infection, and delayed healing, which can cause significant inconvenience to patients. Conventional materials, such as cotton gauze and surgical sutures, primarily function as passive physical barriers, often lacking to address the multiple issues governing functional tissue repair. Electrospun nanofibers have been effective as dynamic regulators of the post-surgical microenvironment, facilitating simultaneous modulation of key biological events, such as immune modulation, macrophage phenotype switching, angiogenesis, collagen organization, and tissue regeneration, leading to faster and better healing. Overall, this review aims to provide a focused and mechanistic perspective on electrospun nanofibers as multifunctional, bioactive scaffolds capable of enabling functional tissue regeneration rather than merely serving as passive wound dressing and nominate it as a sustainable alternative for developing next-generation smart scaffolds intended for postsurgical healing.

The Garment manufacturing industry is facing several challenges in meeting its customer requirements due to uncertainties associated with production. Varieties of products that include many components to be produced on different machines having variations in terms of due dates and labour productivity which would make the job shop complicated for scheduling. Hence, an investigation is necessary to evaluate the influence of above underlying factors on the shop’s performance. The conceptual model was initially developed, that represents the problem entity followed by the development of a simulation model on a discrete event simulation platform. The resource capacity, process timings and other related data required for feeding the model were collected through process observation techniques. The model was then validated by conducting sensitivity analysis for evaluating the model structure, logic, and causal relationships. Artificial scenarios were generated to experiment with the model performance that mimics real time situations in terms of varying the fill rate and workload norms at distinct levels. Effectiveness of order release policies and priority dispatching rules were monitored by conducting 90 experiments determined through design of experiments. Influence of the workload control methods were evaluated through Analysis of Variance techniques to understand the percentage contribution of each variable on performance. The influence of these variables on different output measures was evaluated through Tukey tests. The experimentation revealed that flowtime is influenced to the extent of 59.72 percent by workload norms and order release methods have 59.2 percent influence on throughput.

An abdominal aortic aneurysm (AAA) is an enlarging dilation of the abdominal aorta at signifi-cant risk of rupture and death. During normal physiological conditions, pulsa-tile blood flow in the abdominal aorta displays largely laminar patterns, albeit localized disturbances due to branching vessels and geometric variations. The existence of an aneurysm also distorts vascular structure, leading to sophisticated flow dynamics that could foster disease progression. In the present study, haemodynamics in three-dimensional AAA models were studied with the help of computational fluid dynamics (CFD). Idealized aneurysm geometries with four extreme proximal neck angulations were taken into consideration with laminar flow and rigid arterial wall assumption. Simulations were carried out over the entire cardiac cycle to preserve the pulsatile flow's unsteadi-ness. Post-processing methods were used to analyse velocity distribution, pressure fields, streamlines, and wall shear stress (WSS). The findings showed that marked angu-lation of the proximal aortic neck caused asymmetric flow patterns, turbulence, and blood recirculation in the aneurysm sac, especially during diastole. Low and oscillatory WSS regions were mapped, which are implicated to cause endothelial dysfunction and wall degeneration, whereas zones of high WSS indicated possible localized vascular weaken-ing. These results illustrate that vessel angulation greatly enhances disturbed hemody-namics in AAA, thus augmenting the risk of wall weakening and rupture. This study out-lines the promise of CFD-based simulations to deliver mechanistic insights into aneu-rysm behavior and progression and to provide a non-invasive means of assessing rup-ture risk and to guide clinical decision-making.

The rotor blade manufacturing industry struggles to devise precise planning and scheduling approaches due to uncertainties in production situations. Bottleneck workloads, process time variations and re-entrant flows with varied arrival frequencies would interrupt production schedules and adversely affect the shop’s performance. Hence, an attempt has been made to study the significant impact of disproportionate workloads and the influence of innovative order release methods integrated with capacity adjustment features to enhance performance. The rotor blade manufacturing process has been thoroughly observed to incorporate the uncertain events that cause disturbance in production. A simulation model was created on a discrete event simulation platform incorporating problem phenomena through the conceptualization phase. The randomness present in the process was assessed using an input modelling approach which has resulted in probabilistic equations. The model has been verified and validated to ensure accuracy and was then subjected to 576 experimentations representing different scenarios that occur in a flow shop. Relevant workload control policies are executed to judge their effectiveness followed by Analysis of Variance Techniques. In addition, order release methods were ranked with the help of Tukey’s tests for contribution computation. Outcomes of experimentations revealed that order release methods have a major share of 80.2 percent to the throughput and 42.84 percent to flow time performance indicating the benefits of workload control strategies in decision-making during uncertain situations.

The increase in pollution levels in recent years has increased the prevalence of pulmonary diseases. The accumulation of pollutant particles in the pulmonary tract is speculated to be one of the major reasons for the increase in chronic cases. This necessitates the study of the mechanism of particle deposition in human airways to develop better drug delivery systems. Aerosolized forms of drugs are commonly used to treat pulmonary diseases. The current study employed computational fluid dynamics (CFD) and discrete element method (DEM) techniques to study airflow patterns and particle deposition phenomena. An idealized 3D CAD model was developed based on available literature. A discretized finite-volume model was tested to ensure an independent solution. A user-defined function (UDF) was used to simulate realistic breathing dynamics for the respiration cycle. The aerosol particles of the calculated volume were mixed into the airflow domain. The analysis was conducted using ANSYS FLUENT CFD solver. This study found several regions of high turbulence in the upper human airways, with secondary flow structures exhibiting bifurcations and the glottal region. The study also found that the oral cavity and oropharynx regions with higher turbulence intensity had a concentrated deposition of particles. Most of the aerosol particles (5μm) were transported into the alveolar sacs, where they were absorbed into the bloodstream. The oral cavity and oropharynx have the highest pressure and particle deposition efficiency, while the trachea plays a crucial role in particle deposition during inhalation due to weak oscillatory flows and turbulence, especially in the tracheal region and lower respiratory tract. The oral cavity has the highest efficiency at 7.32%, while the trachea has the lowest at 0.4%. The overall deposition efficiency across all regions is 9.078%.This study did not account for the breakup of aerosol particles. Aerosol particles can break apart due to airflow and collisions, affecting their size and deposition efficiency. Ignoring this breakup could lead to inaccurate results, making accurate dosimetry essential for inhalation studies

Cardiovascular disease (CVD) is one major cause of morbidity caused by the progress of atherosclerosis without any symptoms and has a high risk of Transient Ischemic Stroke (TIS). The carotid bifurcation and bulb are the region where the blood flow is irregular, which may lead to the progression of the plague. The flow disruption due to stenosis in idealised carotid artery has been extensively investigated using Fluid Structure interaction (FSI). However, the haemodynamic of patient specific carotid artery has been intensively studied. In this study, a comparison of blood flow in healthy and stenosed (80% blockage in the carotid bulb region) was carried out using Two- way FSI analysis considering non-Newtonian blood viscosity and isotropic property for vessel wall. Haemodynamic parameters such as velocity streamline, pressure, vorticity, helicity, Time-Averaged Wall shear stress (TAWSS) and Oscillatory Shear Index (OSI) were analysed along with structural parameters such as wall displacement and von Mises stress. The comparison between healthy and stenosed arteries reveals that stenosis significantly increases the velocity magnitude due to the reduced flow area caused by plaque buildup. This narrowing also results in elevated pressure upstream of the stenosis. In both healthy and stenosed arteries, maximum deformation occurs near the bifurcation at the left and right lateral sections, with the highest von Mises Stress located near the internal wall of the flow divider. In stenosed arteries, the stress magnitude is six times higher than in healthy arteries, illustrating the profound effect stenosis has on haemodynamic. Overall, the analysis emphasizes how stenosis disrupts normal blood flow and alters bio-fluid dynamics in the carotid artery

Aircraft cabins have high occupant densities and may introduce the risk of COVID-19 contamination. In this study, a segment of a Boeing 767 aircraft cabin with a mixing type of air distribution system was investigated for COVID-19 deposition. A section of a Boeing 737-300 cabin, featuring four rows with 28 box-shaped mannequins, was used for simulation. Conditioned air entered through ceiling inlets and exited near the floor, simulating a mixed air distribution system. Cough droplets were modeled using the Discrete Phase Model from two locations: the centre seat in the second row and the window seat in the fourth row. These droplets had a mean diameter of 90 µm, an exhalation velocity of 11.5 m/s and a flow rate of 8.5 L/s. A high-quality polyhedral mesh of about 7.5 million elements was created, with a skewness of 0.65 and an orthogonality of 0.3. The SIMPLE algorithm and a second-order upwind finite volume method were used to model airflow and droplet dynamics. It was found that the ceiling accounted for the maximum concentration followed by the seats. The concentration of deposits was almost 50% more when the source was at window as compared to the centre seat. The Covid particles resided for longer duration when the source was at the centre of the cabin than when it was located near the widow.

The re-entrant flow with an unpredictable nature of arrival would apparently harm production plans and schedules in flow type of shops. The re-entrant flow with varied arrival frequencies in rotor blade manufacturing is quite complicated and results in disproportionate workloads. Hence, an attempt has been made to study the significant influence of disproportionate workloads and research on an innovative order release method to enhance performance. The manufacturing process was observed thoroughly to incorporate the uncertain events that cause disturbance in the production. A simulation model was developed on a discrete event simulation platform by analysing problem phenomena right from the conceptualization phase. The model has been verified and validated to ensure the accuracy. The model was subjected to 288 experiments representing different scenarios that a flow shop undergoes in reality. The factors considered in the experimentation were re-entrant frequency, re-entrant proportions, order release methods and priority dispatching rules. A refined load release policy for disproportionate loads has been proposed to judge its effectiveness in terms of profit computation by comparing it with other relevant policies. Results of the experiment revealed that the order release methods contribute 95.93% to throughput performance, in addition, the use of the new re-entrant method policy in the above scenario was productive in improving the overall shop performance.