1,898 research outputs found

    Method for the determination of the three-dimensional aerodynamic field of a rotor-stator combination to compressible flow

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    Using the lifting surface theory and the acceleration potential method for the flow field of an axial turbocompressor stage, a recursive and a direct method are presented that make use of the eigenfunction solutions of the isolated rotor and stator to solve for the rotor-stator interaction problem. The net pressure distribution on the rotor and stator blades is represented by modified Birnbaum series, whose coefficients are determined using a matrix procedure and satisfying the boundary conditions on the surface of the blades. The relation between the matrix operators of the recursive and the direct methods is also shown. Expressions have been given for the blade circulation, the axial and tangential forces on the blade, the rotor power required, and the induced upwash velocity of the stage

    Flexible polyaniline-bacterial nanocellulose conducting composites

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    Development of new greener material for conducting paper is sought for applications such as security paper, actuators, and anti-static packaging. It is required that the material for these applications possess low density and good mechanical integrity. This work presents a way to produce bacterial nanocellulose (BC) - polyaniline (PANI) nanocomposites by in situ polymerization in suspension of cellulose nanowhiskers. The advantages of using BC over filter paper are its ultrafine network structure, sufficient porosity, high purity and crystallinity, good mechanical properties, great water holding capability and low environmental impact. The BC/PANI composites formed by optimized synthesis of PANI within cellulose nanowhiskers are expected to possess good electrical conductivity in addition to excellent mechanical properties and flexibility. The material has been characterized using Fourier Transform Infra-Red Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM)

    Quantum Image Representation Methods Using Qutrits

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    Quantum Image Processing (QIP) is a recent highlight in the Quantum Computing field. All previous methods for representing the images as quantum states were defined using qubits. One Quantum Image Representation (QIR) method using qutrits is present in the literature. Inspired by the qubit methods and the higher state-space available for qutrits, multiple QIR methods using qutrits are defined. First, the ternary quantum gates required for the representations are described and then the implementation details for five qutrit-based QIR methods are given. All the methods have been simulated in software, and example circuits are provided.Comment: 8 pages, 11 figures, 1 tabl

    Fabrication of bio-inspired hydrophobic self-assembled electrospun nanofiber based hierarchical structures

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.In this letter, we present a facile approach to fabricate hydrophobic surfaces based on electrostatic field assisted self-assembly of fibers onto conductive micropillars. Hydrophobic patterns fabricated in this work are inspired by an underwater fern Salvinia molesta. Hydrophilic cellulose acetate nanofibers were electrospun on a conducting micro-patterned surface to create a hierarchical structure. The water contact angle increased from just below 70° (hydrophilic) on the micro-patterned structures to ∼140° (hydrophobic) for the hierarchical structures. Introduced hydrophobicity is due to the pinning of the water droplet to suspended hydrophilic nanofibers and a reduced solid-water interface.This work is supported by DST-UKIERI (IND/CONT/E/14-15/370 & DST/INT/UK/P-92/14) project. MK acknowledges assistance with the use of FESEM facility at the University of Exeter. Authors acknowledge IIT Hyderabad for providing research facilities required for carrying out experiment

    On Modifying the Variational Quantum Singular Value Decomposition Algorithm

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    In this work, we discuss two modifications that can be made to a known variational quantum singular value decomposition algorithm popular in the literature. The first is a change to the objective function which hints at improved performance of the algorithm and decreases the depth of the circuits. The second modification introduces a new way of computing expectation values of general matrices, which is a key step in the algorithm. We then benchmark this modified algorithm and compare the performance of our new objective function with the existing one.Comment: 8 pages, 10 figures, 2 table

    Eikonal solutions to optical model coupled-channel equations

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    Methods of solution are presented for the Eikonal form of the nucleus-nucleus coupled-channel scattering amplitudes. Analytic solutions are obtained for the second-order optical potential for elastic scattering. A numerical comparison is made between the first and second order optical model solutions for elastic and inelastic scattering of H-1 and He-4 on C-12. The effects of bound-state excitations on total and reaction cross sections are also estimated

    Planning in answer set programming while learning action costs for mobile robots

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    For mobile robots to perform complex missions, it may be necessary for them to plan with incomplete information and reason about the indirect effects of their actions. Answer Set Programming (ASP) provides an elegant way of formalizing domains which involve indirect effects of an action and recursively defined fluents. In this paper, we present an approach that uses ASP for robotic task planning, and demonstrate how ASP can be used to generate plans that acquire missing information necessary to achieve the goal. Action costs are also incorporated with planning to produce optimal plans, and we show how these costs can be estimated from experience making planning adaptive. We evaluate our approach using a realistic simulation of an indoor environment where a robot learns to complete its objective in the shortest time

    Low power memristive gas sensor architectures with improved sensing accuracy

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    A comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak

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    AbstractIn blasting operation, the aim is to achieve proper fragmentation and to avoid undesirable events such as backbreak. Therefore, predicting rock fragmentation and backbreak is very important to arrive at a technically and economically successful outcome. Since many parameters affect the blasting results in a complicated mechanism, employment of robust methods such as artificial neural network may be very useful. In this regard, this paper attends to simultaneous prediction of rock fragmentation and backbreak in the blasting operation of Tehran Cement Company limestone mines in Iran. Back propagation neural network (BPNN) and radial basis function neural network (RBFNN) are adopted for the simulation. Also, regression analysis is performed between independent and dependent variables. For the BPNN modeling, a network with architecture 6-10-2 is found to be optimum whereas for the RBFNN, architecture 6-36-2 with spread factor of 0.79 provides maximum prediction aptitude. Performance comparison of the developed models is fulfilled using value account for (VAF), root mean square error (RMSE), determination coefficient (R2) and maximum relative error (MRE). As such, it is observed that the BPNN model is the most preferable model providing maximum accuracy and minimum error. Also, sensitivity analysis shows that inputs burden and stemming are the most effective parameters on the outputs fragmentation and backbreak, respectively. On the other hand, for both of the outputs, specific charge is the least effective parameter

    Evaluation of efficacy and safety of doxofylline 800mg sustained release tablet in treatment of patients with COPD: an open label, prospective and RCT

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    Background: COPD is a major cause of health care burden worldwide and leading cause of death that is increasing in prevalence. Methylxanthines are used in the treatment of patients with asthma and COPD. Doxofylline (methylxanthine) shows improved disease control, reduced total daily dose of inhaled b2 agonists and improved patient compliance.Methods: This was a prospective, open labelled, randomized, two-arm, parallel group, controlled, clinical trial. 115 patients were randomized to two groups. Patients in group A received tablet doxofylline 400mg BD whereas patients in group B received tablet doxofylline 800mg SR for 4 weeks. Primary outcome measure of trial was change in FEV1 and secondary outcome measure were change in FVC/FEV1, change in symptoms score, effect on health-related quality of life (HRQOL) and safety of study medication.Results: At 4 week the FEV1increase by 13.028% and 17.647% in group A and B respectively. In group A FEV1/FVC increase by 5.79% and in group B it increases by 9.57% at 4 weeks. The symptom score of cough decrease by 77.35% and 97.43% in group A and group B respectively at 4 weeks. In group A shortness of breath decrease by 77.60% and in group B it decreases by 95.90% at 4 weeks. Tightness in chest decrease by 86.29% and 98.40% in group A and group B respectively at 4 weeks.Conclusions:Doxofylline 800mg sustained release tablet provided significantly greater improvement in FEV1, symptomatic control and health related quality of life compared to doxofylline 400mg.
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