Investigation of the Aerodynamic Performance of a DG808s UAS in Propeller Slipstream using Computational Fluid Dynamics

Unmanned Aerial Systems (UASs) are relatively affordable and immediately available compared to commercial aircraft. Hence, their aerodynamics and design accuracies are often based on extrapolating from design standards and procedures widely used in the aerospace industry for commercial aircraft with most often, acceptable results. Engineering level software such as Advanced Aircraft Analysis (AAA) use general aviation aircraft data and later extrapolate them onto UASs for aerodynamic and flight dynamics modeling but are limited by their platform repository and relatively high Reynolds number evaluations. UASs however, are aircraft which fly at comparatively low speeds and low Reynolds number with close proximities between the components wherein such standards may not hold good. This thesis focuses on evaluating the accuracy and impact of such industry standards on the aerodynamics and flight dynamics of UASs. A DG808s UAS is chosen for the study which was previously modeled using the AAA software at The University of Kansas by the Flight Systems Team. Using the STAR-CCM+ code, performance data were compared and assessed with AAA. Aerodynamic simulations were carried out for two different configurations viz., aircraft with and without propeller slipstream effects. Data obtained for the non-powered simulations were found to be in good agreement with the AAA model. For the powered flight however, discrepancies between the AAA model and CFD data were observed with large values for the vertical tail side-force coefficient. A comparison with the system identification data from the flight tests was made to confirm and validate this vertical tail behavior with the help of rudder deflection inputs. A relationship between the propeller RPM and the aerodynamic model was established by simulating two different propeller speeds. Based on the STAR-CCM+ data and the resulting comparisons with AAA, updates necessary to the UAS aerodynamic and flight dynamics models currently used in the industry were discussed and concluded with a stress on dependency on higher fidelity methods such as Computational Fluid Dynamics

Size-dependent dynamic characteristics of graphene based multi-layer nano hetero-structures

Carbon-based nano hetero-structures are receiving increasing attention due their ability in multi-synchronous modulation of a range of mechanical and other critically desirable properties. In this paper, the vibration characteristics of two different graphene based heterostructures, graphene-hexagonal boron nitride (hBN) and graphene-molybdenum disulfide (MoS2), are explored based on atomistic finite element approach. Such vibrational characteristics of nanostructures are of utmost importance in order to access their suitability as structural members for adoption in various nano-scale devices and systems. In the current analysis, the developed atomistic finite element model for nano-heterostructures is extensively validated first with the results available in literature considering elastic responses and natural frequencies. Thereafter a range of insightful new results are presented for the dynamic behaviour of various configurations of graphene-hBN and graphene-MoS2 heterostructures including their size, chirality and boundary dependence. The investigation of tunable vibrational properties along with simultaneous modulation of other mechanical, electronic, optical, thermal and chemical attributes of such nano-heterostructures would accelerate their application as prospective candidates for manufacturing nanosensors, electromechanical resonators, and a wide range of other devices and systems across the length-scales

Nasal septal angle deviation: effect on lateral wall in nasal obstruction

Background: Deviation of the nasal septum (DNS) refers to the convexity of the septum to one side disturbing the nasal physiology with obstructed nasal breathing leading to lateral nasal wall abnormalities and paranasal sinuses (PNS) mucosal disease. Knowledge of nasal morphological parameters plays an important role in planning successful nasal surgery. Our aim was to evaluate the angle of septal deviation (ASD) on CT scan and study its influence on the lateral nasal wall abnormalities and PNS mucosal disease.Methods: A prospective cross-sectional observational study was conducted on 130 patients with clinical evidence of DNS and chronic sinusitis. The direction and severity of DNS was recorded on CT scan along with evaluation of lateral nasal wall and sinus mucosal abnormalities.Results: Increasing ASD had statistically significant correlation with the lateral nasal wall abnormalities, most commonly, contralateral middle and inferior turbinate hypertrophy (p-value <0.0001). No significant association was found with the incidence of ipsilateral or contralateral osteomeatal complex (OMC) obstruction and sinus mucosal disease.Conclusions: The direction and severity of septal deviation has significant impact on contralateral middle and inferior turbinate hypertrophy. The analysis of these ancillary pathologies can be of great help to the surgeon in better management of patients with nasal obstruction

Paper formats of graphene and CNT: Multiscale simulations

Carbon-based nanostructures are receiving increasing attention over the past two decades due to their outstanding multi-functional features. However, the macro-scale structural applications of these nanostructures have not yet come to full fruition due to the involvement of complex multi-scale computations and manu-facturing. Recently, the research community has started investigating macroscopic paper formats of graphene and carbon nanotubes(PFGCN). The PFGCNs include graphene paper and buckypaper. The buckypaper is a membrane composed of a network of bundles of single-wall carbon nanotubes (SWCNT), multi-wall carbon nanotubes (MWCNT), or a mixture of both. The graphene paper is also a macro-scopic membrane composed of a network of graphene nanosheets. The current thesis thrives on advancing the science and technology of PFGCN by focusing on three goals. The first goal is to perform a thorough statistical analysis of the mechanical properties of PFGCN. The second goal is to conduct a computa-tional bridging of different length scales involving six levels in the range of nano to macro-scale behaviour concerning PFGCN composites. The third goal is to demonstrate the compatibility of the PFGCN with an engineering product. The statistical analysis has reviewed 600 research papers to examine the mechanical properties of PFGCN and its associated composite materials. The data spanning 20 years of research has been quantitatively and qualitatively presented here, with the aid of statistical tabulations and Ashby plots. Mainly, the influence of geome-try and chemistry of PFGCN on mechanical properties has been investigated. To address the second goal, the multi-length scale simulations consider sequential car-bon derivatives at six levels, involving graphene, SWCNT, MWCNT, CNT bundle, buckypaper and buckypaper composite automotive components. The multi-scale simulations are based on a coupled atomistic-continuum modelling approach for multilevel simulations. At the macro-scale, an industry-relevant multi-material composite automotive component has been investigated, wherein the buckypa-per is proposed to be embedded involving sheet moulding compound (SMC) and carbon prepreg. The simulations have led to the determination of mechanical properties at each carbon-based material level and their mutual dependence. To address the third goal, a detailed numerical analysis as per the industry regu-lations has been carried out on the PFGCN embedded automotive component. The numerical results demonstrate that a buckypaper composite can enhance the durability and vibrational performance with respect to conventional monolithic metallic designs while reducing the component weight. Such outcomes lead to the realization that carbon-based nanostructural derivative in the form of buckypa-per can significantly improve the mechanical properties of advanced lightweight structural components as reinforcements for the next generation of aerospace and automotive structures

Advances in finite element modelling of graphene and associated nanostructures

Graphene and its associated nanostructures (GANS) have been widely investigated by means of experimental and numerical approaches over the last decade. GANS and GANS reinforced composite materials show exceptional promise towards superior mechanical and thermal properties along with limitless opportunity to tailor, control, design, modify and manipulate such properties. These attributes make graphene and its associated nanostructures as one of the most important future material technologies in aerospace, automotive, medical, civil and military sectors of the 21st century. Among the various numerical methods used to analyse GANS and GANS reinforced composite materials, the finite element method (FEM) plays a prominent role. The FEM has been the standard analysis and simulation method for conventional structural and mechanical problems over the past half a century. However, its growing role and impact in atomistic-scale numerical simulation in general, and GANS, in particular, is not well known within the wider scientific and engineering modelling and simulation research community. There is a compelling need to document the expansive use of the finite element method, its advantages, shortcomings, relevance and purpose in a way which is pertinent to both material science and numerical simulation researchers. This paper serves this need by discussing the current state of the art of finite element methodologies available to study GANS and GANS reinforced composites in the most comprehensive manner. A detailed description of the popular space frame based numerical simulation strategy widely used to represent GANS is given. An extensive survey is conducted on more than 600 research papers in order to examine the finite element predictions of the mechanical and thermal properties of graphene and its associated composite materials. These properties are selected in view of their direct relevance to crucial future technologies, such as high-performance automotive components, aerospace and bioengineering systems, energy technologies, and advanced therapeutic and surgical devices. Omissions of some fundamental mechanical and thermal modelling issues for GANS have been identified and insightful guidance towards future research directions to comprehensively address them is given. By reviewing a significant breadth of publications across several academic disciples, a large scatter in the numerical predictions of essential material constants arising from the differences in fundamental assumptions and approximations has been reported. The origin of such discrepancies has been identified, analysed and established. The paper further focuses on the idealization of nanostructures and nanocomposites by means of representative volume elements (RVEs). The need for this multiscale modelling strategy to mature in order to include the simultaneous description of different material length scales within multiphysics simulation problems has been discussed. This paper will serve as standalone reference material for future research works and will pave the way for novel investigations in the context of atomistic simulations and their potential applications to the development of next-generation engineering devices and cutting-edge technological applications

Human protein reference database as a discovery resource for proteomics

The rapid pace at which genomic and proteomic data is being generated necessitates the development of tools and resources for managing data that allow integration of information from disparate sources. The Human Protein Reference Database (http://www.hprd.org) is a web-based resource based on open source technologies for protein information about several aspects of human proteins including protein–protein interactions, post-translational modifications, enzyme–substrate relationships and disease associations. This information was derived manually by a critical reading of the published literature by expert biologists and through bioinformatics analyses of the protein sequence. This database will assist in biomedical discoveries by serving as a resource of genomic and proteomic information and providing an integrated view of sequence, structure, function and protein networks in health and disease

Development of Human Protein Reference Database as an Initial Platform for Approaching Systems Biology in Humans

Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization were extracted from the literature for a nonredundant set of 2750 human proteins. Almost all the information was obtained manually by biologists who read and interpreted >300,000 published articles during the annotation process. This database, which has an intuitive query interface allowing easy access to all the features of proteins, was built by using open source technologies and will be freely available at http://www.hprd.org to the academic community. This unified bioinformatics platform will be useful in cataloging and mining the large number of proteomic interactions and alterations that will be discovered in the postgenomic era