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Siti Farhana Shahwir

Bio: Siti Farhana Shahwir is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 7 citations.

Papers
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01 Jan 2016
TL;DR: The essential methodology of CFD as a reliable tool for researchers and medical scientist in understanding the physiology and pathophysiology of cardiovascular system and respiratory system through simulation is discussed.
Abstract: Computational Fluid Dynamics (CFD) is a widely adopted methodology of computer-based simulation in order to solve complex problems in many modern engineering fields as well as biomedical field. CFD is becoming a key component in developing updated designs and optimization through computational simulations, resulting in lower operating costs with enhanced efficiency. Even though biomedical application is pertaining to the complexity of human anatomy and human body fluid behaviour, the recent CFD in biomedical application is more accessible and practicable due to the availability of high performance hardware and software with advances in computer sciences. Many simulations and clinical results have been used to study the analyses in biomedical applications, particularly in blood flow and nasal airflow. The study of blood flow analysis includes the circulation of blood of ventricle function, coronary artery and heart valves. Meanwhile, the nasal airflow analysis consists of the basic airflow in human nose, drug delivery improvement and virtual surgery. Therefore, this review discusses the essential methodology of CFD as a reliable tool for researchers and medical scientist in understanding the physiology and pathophysiology of cardiovascular system and respiratory system through simulation. CFD plays a major role as a decision support prior to undertaking a real commitment to execute any medical design alterations and provide the direction to develop medical interventions.

8 citations


Cited by
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Journal ArticleDOI
TL;DR: The proposed mathematical modelling shows that the deteriorating WSS is an indicator for possible rupture and its value oscillates over a cardiac cycle as well as over different stress conditions, which provides good insight of TAA.
Abstract: An attempt has been made to evaluate the effects of wall shear stress (WSS) on thoracic aortic aneurysm (TAA) using Computational Fluid Dynamics (CFD). Aneurysm is an excessive localized swelling of the arterial wall due to many physiological factors and it may rupture causing shock or sudden death. The existing imaging modalities such as MRI and CT assist in the visualization of anomalies in internal organs. However, the expected dynamic behaviour of arterial bulge under stressed condition can only be effectively evaluated through mathematical modelling. In this work, a 3D aneurysm model is reconstructed from the CT scan slices and eventually the model is imported to Star CCM+ (Siemens, USA) for intensive CFD analysis. The domain is discretized using polyhedral mesh with prism layers to capture the weakening boundary more accurately. When there is flow reversal in TAA as seen in the velocity vector plot, there is a chance of cell damage causing clots. This is because of the shear created in the system due to the flow pattern. It is observed from the proposed mathematical modelling that the deteriorating WSS is an indicator for possible rupture and its value oscillates over a cardiac cycle as well as over different stress conditions. In this model, the vortex formation pattern and flow reversals are also captured. The non-Newtonian model, including a pulsatile flow instead of a steady average flow, does not overpredict the WSS (15.29 Pa compared to 16 Pa for the Newtonian model). Although in a cycle the flow behaviour is laminar-turbulent-laminar (LTL), utilizing the non-Newtonian model along with LTL model also overpredicted the WSS with a value of 20.1 Pa. The numerical study presented here provides good insight of TAA using a systematic approach to numerical modelling and analysis.

21 citations

Journal ArticleDOI
TL;DR: The results of this study indicated a tradeoff that exists between the attainable density and velocity of the microjet on the skin surface with variation in nozzle diameter; the optimum nozzle diameter was found to be within 200-250 μm under the present conditions.

14 citations

Book ChapterDOI
01 Jan 2020
TL;DR: CFD will become ubiquitous but will be buried inside digital twins/reduced order models so that it is usable by engineers, whereas CFD experts will be more engaged in creating them using high fidelity computations and of course, in extending the application of CFD into diverse areas of human activity.
Abstract: Computational Fluid Dynamics appears to be poised on the threshold of rapid advances powered by the recent developments in deep machine learning. Deep machine learning will be used to improve the speed, accuracy and, the user-friendliness of CFD software. The applications of CFD will expand beyond the usual aerospace and mechanical/thermal areas to include areas such as biomedical, sport, food processing, environmental, fire safety, buildings ventilation and energy efficiency, and a host of other areas of social relevance. Deep machine learning will be routinely used to generate digital twins/reduced order models which will have a profound impact on the way that CFD is utilized. Standardized interfaces will be developed to embed the digital twins into CAD/PLM software and even spreadsheets. This will enable engineers to rapidly assimilate these models into the product development process and thereby create optimal designs, without needing the services of a CFD expert. These models will also be used for optimal control. In addition, these models can be combined with experimental and field data using Internet-of-Things (IoT) to provide for real-time monitoring of the device and assessing the need for preventive maintenance, etc. This has profound implications for product safety in the field. The social benefits are obvious. In short, CFD will become ubiquitous but will be buried inside digital twins/reduced order models so that it is usable by engineers, whereas CFD experts will be more engaged in creating them using high fidelity computations and of course, in extending the application of CFD into diverse areas of human activity.

7 citations

Journal ArticleDOI
TL;DR: Dp16 mice can be a useful model to examine the pathophysiology of increased upper airway collapsibility of DS and to evaluate the efficacy of therapeutic interventions for breathing and sleep anomalies, according to a combination of computational fluid dynamics and micro-CT imaging.
Abstract: A high prevalence of obstructive sleep apnea (OSA) has been reported in Down syndrome (DS) owing to the coexistence of multiple predisposing factors related to its genetic abnormality, posing a challenge for the management of OSA. We hypothesized that DS mice recapitulate craniofacial abnormalities and upper airway obstruction of human DS and can serve as an experimental platform for OSA research. This study, thus, aimed to quantitatively characterize the upper airway as well as craniofacial abnormalities in Dp(16)1Yey (Dp16) mice. Dp16 mice demonstrated craniofacial hypoplasia, especially in the ventral part of the skull and the mandible, and rostrally positioned hyoid. These changes were accompanied with a shorter length and smaller cross-sectional area of the upper airway, resulting in a significantly reduced upper airway volume in Dp16 mice. Our non-invasive approach, a combination of computational fluid dynamics and high-resolution micro-CT imaging, revealed a higher negative pressure inside the airway of Dp16 mice compared to wild-type littermates, showing the potential risk of upper airway collapse. Our study indicated that Dp16 mice can be a useful model to examine the pathophysiology of increased upper airway collapsibility of DS and to evaluate the efficacy of therapeutic interventions for breathing and sleep anomalies.

6 citations

Journal ArticleDOI
TL;DR: In this paper , the authors have focused on unsteady nanofluid flow over a bidirectional stretching surface in the presence and absence of a magnetic field respectively and applied similarity transformation to convert the governing equations, from PDE to nonlinear ordinary type.
Abstract: This research has focused on unsteady nanofluid flow over a bidirectional stretching surface in the presence and absence of a magnetic field respectively. The direction of the magnetic field is vertically upwards. Nonlinear sort of thermal radiation has been considered here. Additionally, Brownian motion and thermophoresis are revealing an innovative way in this investigation. Moreover, we captured flow characteristics and temperature distribution along realistic thermal and mass convective boundary conditions. Similarity transformation is applied to convert the governing equations, from PDE to nonlinear ordinary type. Using RK4 shooting criteria through MAPLE 17 software we have solved numerically this transformed leading equation along with boundary conditions with the required accuracy rate. Upshots are explored with appropriate geometrical representation and tables. After those physical consignments as Sherwood number, Nusselt number also skin friction have been calculated. It has to remark from consequences that fluid velocity along x -axis, temperature, volume fraction are declined along with the positive increment of stretching parameter while the opposite impact is perceived for the velocity of nanofluid towards y − direction. The transportation of heat in nanoliquid increases for enlarging radiation factor also this effect turns advanced when magnetic force is neglected.

5 citations