Ultrasound examination of the abdominal aorta was performed on 100 patients with cardiovascular disease and a control group of 100 subjects. The objectives were to define the normal aortic size of Malaysians, to screen for aneurysms and to compare the aorta size of the different population groups. In the study group the mean anteroposterior (AP) diameter of the non-aneurysmal aortas at the level of the renal arteries was 1.82 cm (range 0.9-2.6 cm) in men and 1.83 cm (range 1.5-2.3 cm) in women. This compares with 1.61 cm (range 1.1-2.2 cm) in men and 1.50 cm (range 0.8-2.4 cm) in women in the control group. The dimensions of the infrarenal aorta show a similar relationship between the two groups. These AP diameters were significantly smaller than the published figures from studies done on Western populations and are consistent with the smaller stature of Malaysians. Five aneurysms and one ectasia were found (mean size 5 cm, range 3.5-6.0 cm), all in men aged 50-75 years in the study group, and none in the control group. All the aneurysms were easily palpable in these patients who were thinner than the average Caucasian. Given the lower incidence of aortic aneurysms in Malaysians there is no role for routine ultrasound screening of the population. High risk groups can be adequately screened by clinical examination alone.
Myxomas are uncommon primary cardiac tumours that usually affect the left atrium. We herein report the case of a patient who presented with right heart failure and proteinuria, leading to the diagnosis of atrial myxoma. Surgical resection resulted in resolution of the patient's symptoms.
Because transseptal catheterization is felt to be contraindicated in patients with severe kyphoscoliosis, there have been no reports of percutaneous transvenous mitral commissurotomy performed in such patients. This report describes percutaneous transvenous mitral commissurotomy in three patients with severe thoracic kyphoscoliosis, with special emphasis on the transseptal puncture technique. Biplane right atrial angiography and the contrast septal flush method are very useful in landmark selection for a safe transseptal puncture.
Optimum ultrasonication time will lead to the better performance for heat transfer in addition to preparation methods and thermal properties of the nanofluids. Nano particles are dispersed in base fluids like water (water-based fluids), glycols (glycol base fluids) &oils at different mass or volume fraction by using different preparation techniques. Significant preparation technique can enhance the stability, effects various parameters & thermo-physical properties of fluids. Agglomeration of the dispersed nano particles will lead to declined thermal performance, thermal conductivity, and viscosity. For better dispersion and breaking down the clusters, Ultrasonication method is the highly influential approach. Sonication hour is unique for different nano fluids depending on their response to several considerations. In this review, systematic investigations showing effect on various physical and thermal properties based on ultrasonication/ sonication time are illustrated. In this analysis it is found that increased power or time of ideal sonication increases the dispersion, leading to higher stable fluids, decreased particle size, higher thermal conductivity, and lower viscosity values. Employing the ultrasonic probe is substantially more effective than ultrasonic bath devices. Low ultrasonication power and time provides best outcome. Various sonication time periods by various research are summarized with respect to the different thermophysical properties. This is first review explaining sonication period influence on thermophysical properties of graphene nanofluids.
Friction and wear are the main factors in the failure of the piston in automobile engines. The objective of this work was to improve the tribological behaviour and lubricant properties using hybrid Cellulose Nanocrystal (CNC) and Copper (II) oxide nanoparticles blended with SAE 40 as a base fluid. The two-step method was used in the hybrid nanofluid preparation. Three different concentrations were prepared in a range of 0.1% to 0.5%. Kinematic viscosity and viscosity index were also identified. The friction and wear behavior were evaluated using a tribometer based on ASTM G181. The CNC-CuO nano lubricant shows a significant improvement in term of viscosity index by 44.3-47.12% while for friction, the coefficient of friction (COF) decreases by 1.5%, respectively, during high and low-speed loads (boundary regime), and 30.95% during a high-speed, and low load (mixed regime). The wear morphologies results also show that a smoother surface was obtained after using CNC-CuO nano lubricant compared to SAE 40.
Polyoxymethylene dimethyl ethers (PODEn, n = 1-8) as an oxygenated fuel are a promising alternative fuel with a high oxygen concentration, a low C:H ratio, and no C-C bonds in their chemical structure. This could lead to smoke-free combustion. In this study, we chose to focus on PODE1 because of its lower cetane number, which makes it more suitable for use in spark ignition (SI) engines. However, its lower boiling point and octane number remain challenges. A low boiling point may lead to high vapour pressure and require storage and handling comparable to gaseous fuels. We investigated the effect of adding PODE1 to gasoline-ethanol blends (E10) on fuel properties, including distillation curve, octane number, phase stability, C/O/H ratio, heat of combustion, kinematic viscosity, and density. Our results showed that the blended fuels of E10 and PODE1 are stable up to 10 % PODE1, and there was no phase separation. Additionally, up to 10 % PODE1 additive had no significant side effect on the fuel properties of E10, particularly boiling point and octane number. Thus, work offers creative points by proposing a new candidate for additive fuel to gasoline-ethanol blends, which contributes to reducing the soot emission of GDI engines.
Fused Deposition Modelling (FDM) is one of the additive manufacturing (AM) techniques that have emerged as the most feasible and prevalent approach for generating functional parts due to its ability to produce neat and intricate parts. FDM mainly utilises one of the widely used polymers, polylactic acid, also known as polylactide (PLA). It is an aliphatic polyester material and biocompatible thermoplastic, with the best design prospects due to its eco-friendly properties; when PLA degrades, it breaks down into water and carbon dioxide, neither of which are hazardous to the environment. However, PLA has its limitations of poor mechanical properties. Therefore, a filler reinforcement may enhance the characteristics of PLA and produce higher-quality FDM-printed parts. The processing parameters also play a significant role in the final result of the printed parts. This review aims to study and discover the properties of PLA and the optimum processing parameters. This review covers PLA in FDM, encompassing its mechanical properties, processing parameters, characterisation, and applications. A comprehensive description of FDM processing parameters is outlined as it plays a vital role in determining the quality of a printed product. In addition, PLA polymer is highly desirable for various field industrial applications such as in a medical, automobile, and electronic, given its excellent thermoplastic and biodegradability properties.
Response surface methodology (RSM) is used in this study to optimize the thermal characteristics of single graphene nanoplatelets and hybrid nanofluids utilizing the miscellaneous design model. The nanofluids comprise graphene nanoplatelets and graphene nanoplatelets/cellulose nanocrystal nanoparticles in the base fluid of ethylene glycol and water (60:40). Using response surface methodology (RSM) based on central composite design (CCD) and mini tab 20 standard statistical software, the impact of temperature, volume concentration, and type of nanofluid is used to construct an empirical mathematical formula. Analysis of variance (ANOVA) is applied to determine that the developed empirical mathematical analysis is relevant. For the purpose of developing the equations, 32 experiments are conducted for second-order polynomial to the specified outputs such as thermal conductivity and viscosity. Predicted estimates and the experimental data are found to be in reasonable arrangement. In additional words, the models could expect more than 85% of thermal conductivity and viscosity fluctuations of the nanofluid, indicating that the model is accurate. Optimal thermal conductivity and viscosity values are 0.4962 W/m-K and 2.6191 cP, respectively, from the results of the optimization plot. The critical parameters are 50 °C, 0.0254%, and the category factorial is GNP/CNC, and the relevant parameters are volume concentration, temperature, and kind of nanofluid. From the results plot, the composite is 0.8371. The validation results of the model during testing indicate the capability of predicting the optimal experimental conditions.
In the realm of internal combustion engines, there is a growing utilization of alternative renewable fuels as substitutes for traditional diesel and gasoline. This surge in demand is driven by the imperative to diminish fuel consumption and adhere to stringent regulations concerning engine emissions. Sole reliance on experimental analysis is inadequate to effectively address combustion, performance, and emission issues in engines. Consequently, the integration of engine modelling, grounded in machine learning methodologies and statistical data through the response surface method (RSM), has become increasingly significant for enhanced analytical outcomes. This study aims to explore the contemporary applications of RSM in assessing the feasibility of a wide range of renewable alternative fuels for internal combustion engines. Initially, the study outlines the fundamental principles and procedural steps of RSM, offering readers an introduction to this multifaceted statistical technique. Subsequently, the study delves into a comprehensive examination of the recent applications of alternative renewable fuels, focusing on their impact on combustion, performance, and emissions in the domain of internal combustion engines. Furthermore, the study sheds light on the advantages and limitations of employing RSM, and discusses the potential of combining RSM with other modelling techniques to optimise results. The overarching objective is to provide a thorough insight into the role and efficacy of RSM in the evaluation of renewable alternative fuels, thereby contributing to the ongoing discourse in the field of internal combustion engines.