Fracture load in double keyhole notch PLA-Cu2O nanocomposites manufactured via compression molding and 3D printing: An experimental and numerical study

Polylactic acid (PLA) polymer has garnered significant attention due to its biocompatibility. The incorporation of copper oxide (Cu2O) nanoparticles into this polymer is expected to enhance its antibacterial, electrical, and thermal properties. This modification can potentially improve the performance of PLA in the fields of prosthetics manufacturing or printed circuit fabrication. However, the current research is rather focused on the mechanical properties of the PLA-Cu2O nanocomposites. This research is thus aimed to analyze PLA-Cu2O (97-3 wt%) nanocomposites with a double keyhole notch configuration both experimentally and numerically. Scanning electron microscopy (SEM), X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX), X-ray mapping of elemental distribution(X-map), and thermogravimetric analysis (TGA) were employed to explore the morphology, crystallinity, homogeneity, purity, and thermal stability of the nanocomposite. The specimens were fabricated through two different processes: the classical method of compression molding and the innovative method of 3D printing. The results revealed the superior mechanical performance of the 3D-printed nanocomposite at a 0° raster angle, while the mechanical properties gradually decreased for raster angles of 45° and 90°. The experimental test also indicated a decline in the maximum fracture load of specimens with a double keyhole notch and constant notch inclination angle by raising the notch radius. This behavior was also observed by increasing the notch inclination angle at constant notch radius. The numerical results were similar to the experimental findings. Moreover, the nanocomposite manufactured through the classical method exhibited higher critical fracture load compared to their 3D-printed counterparts with the same geometry.

Using a Delphi Method Approach to Select Theoretical Underpinnings of Crowdsourcing and Rank Their Application to a Crowdsourcing App

INTRODUCTION

Since the catapult of online learning during the COVID-19 pandemic, most simulation laboratories are now completed virtually, leaving a gap in skills training and potential for technical skills decay. Acquiring standard, commercially available simulators is prohibitively expensive, but three-dimensional (3D) printing may provide an alternative. This project aimed to develop the theoretical foundations of a crowdsourcing Web-based application (Web app) to fill the gap in health professions simulation training equipment via community-based 3D printing. We aimed to discover how to effectively leverage crowdsourcing with local 3D printers and use these resources to produce simulators via this Web app accessed through computers or smart devices.

METHODS

First, a scoping literature review was conducted to discover the theoretical underpinnings of crowdsourcing. Second, these review results were ranked by consumer (health field) and producer (3D printing field) groups via modified Delphi method surveys to determine suitable community engagement strategies for the Web app. Third, the results informed different app iteration ideas and were then generalized beyond the app to address scenarios entailing environmental changes and demands.

RESULTS

A scoping review revealed 8 crowdsourcing-related theories. Three were deemed most suitable for our context by both participant groups: Motivation Crowding Theory, Social Exchange Theory, and Transaction Cost Theory. Each theory proposed a different crowdsourcing solution that can streamline additive manufacturing within simulation while applicable to multiple contexts.

CONCLUSIONS

Results will be aggregated to develop this flexible Web app that adapts to stakeholder needs and ultimately solves this gap by delivering home-based simulation via community mobilization.

Preliminary Design and Development of a Mechanical Ventilator Using Industrial Automation Components for Rapid Deployment During the COVID-19 Pandemic

The novel coronavirus disease 2019 (COVID-19) created a shortage of mechanical ventilators in the healthcare sector, resulting in rationed distribution, ethical dilemmas, and high mortalities. This technical report outlines the design and product outcome of a mechanical ventilator based on readily available off-the-shelf components, minimizing the dependence on manufacturing facilities. The ventilator was designed to operate in both hospitals and remote locations, having the ability to operate off various gas pressures and low voltage supplies. Due to the COVID-19 restrictions, the challenges of developing a device in an online setting with minimal manufacturing assistance were explored. Within a 10-day period, the team designed, prototyped, and conducted preliminary feasibility testing on the mechanical ventilator. The proposed design was not intended to replace, or be used as a medically approved ventilator, but demonstrates the ability to exploit off-the-shelf components to enable fast development and assembly. 

The Importance of Personal Protective Equipment Design and Donning and Doffing Technique in Mitigating Infectious Disease Spread: A Technical Report

During the current coronavirus pandemic, significant emphasis has been placed on the importance of mitigating nosocomial spread of coronavirus disease 2019 (COVID-19). One important consideration involves the appropriate use of effective personal protective equipment (PPE), which may reduce a healthcare provider's likelihood of becoming infected while simultaneously minimizing exposure to other patients that they care for. This may reduce demands placed on the healthcare system and help to preserve the workforce. First, the importance of PPE design cannot be underestimated, as the manufacturing process must strive to maximize protection of the user while ensuring adequate comfort. Second, it has been demonstrated that inadequate education and training can significantly impact compliance with PPE recommendations. Technique regarding donning and doffing of PPE is crucial to the protection of those who don it. The purpose of this technical report is two-fold: first, to describe some important considerations in the manufacturing and design process of face shields to maximize protection for healthcare providers, and second, to describe a simulation scenario that may be used to train healthcare workers in the appropriate donning and doffing of PPE. 

On the Validity Extent of Linear Viscoelastic Models of Human Brain

Characterization of human brain material properties in the form of computationally feasible mathematical models is a complex problem; especially when the models are used in complicated Finite Element simulations. Various models have been proposed to include the tissue’s hyper-viscoelasticity, most of which are quite complicated and therefore only suited to Software-based Finite Element methods. Use of linear material models simplifies the problem and saves much time and effort, allowing the researcher to verify the results of more sophisticated models with lower computational cost. However, the preciseness of the results from such models is subject to special conditions. This study proposes and validates a Generalized Maxwell linear viscoelastic model with five constants to be used as an acceptable computational method to simulate brain’s viscoelastic behavior at low strain rates. To this end, an explicit numerical integration scheme is used to simulate the single-DOF tissue response with a Generalized Maxwell viscoelastic model. Using the material constants of a previous hyper-viscoelastic model, the results are compared with those obtained from a previous experiment. The comparison shows that the linear GM viscoelastic model is predicting the low-strain-rate behavior of the brain tissue with acceptable error.

Experimental investigation on performance and exhaust emissions of castor oil biodiesel from a diesel engine

Biodiesel, produced from plant and animal oils, is an important alternative to fossil fuels because, apart from dwindling supply, the latter are a major source of air pollution. In this investigation, effects of castor oil biodiesel blends have been examined on diesel engine performance and emissions. After producing castor methyl ester by the transesterification method and measuring its characteristics, the experiments were performed on a four cylinder, turbocharged, direct injection, diesel engine. Engine performance (power, torque, brake specific fuel consumption and thermal efficiency) and exhaust emissions were analysed at various engine speeds. All the tests were done under 75% full load. Furthermore, the volumetric blending ratios of biodiesel with conventional diesel fuel were set at 5, 10, 15, 20 and 30%. The results indicate that lower blends of biodiesel provide acceptable engine performance and even improve it. Meanwhile, exhaust emissions are much decreased. Finally, a 15% blend of castor oil-biodiesel was picked as the optimized blend of biodiesel-diesel. It was found that lower blends of castor biodiesel are an acceptable fuel alternative for the engine.

Effect of sampling strategy on uncertainty and precision of flatness inspection studied by dynamic minimum deviation zone evaluation

Evaluation of geometric deviations for the purpose of determining compliance with specified form tolerances requires the acquisition of numerous measured data points and extensive computation to accurately characterize the inspected part’s geometry. If there are not enough data points measured or when the measured points are not distributed properly on the measured surface a high level of uncertainty in characterizing the inspected part’s geometry can be expected. However, increasing the number of data point also significantly increases the computational time and also increases computational uncertainty by adding to instability of the optimization process required to find the minimum deviation zone. Selections of number and location of the measured date points need to be performed by understanding the significance of these two sources of uncertainties. This paper discussed the effect of sampling procedure on uncertainty and precision of flatness inspection.