A second-order continuity domain-decomposition technique based on integrated Chebyshev polynomials for two-dimensional elliptic problems

This paper presents a second-order continuity non-overlapping domain decomposition (DD) technique for numerically solving second-order elliptic problems in two-dimensional space. The proposed DD technique uses integrated Chebyshev polynomials to represent the solution in subdomains. The constants of integration are utilized to impose continuity of the second-order normal derivative of the solution at the interior points of subdomain interfaces. To also achieve a C2 (C squared) function at the intersection of interfaces, two additional unknowns are introduced at each intersection point. Numerical results show that the present DD method yields a higher level of accuracy than conventional DD techniques based on differentiated Chebyshev polynomials

A stable and accurate control-volume technique based on integrated radial basis function networks for fluid-flow problems

Radial basis function networks (RBFNs) have been widely used in solving partial differential equations as they are able to provide fast convergence. Integrated RBFNs have the ability to avoid the problem of reduced convergence-rate caused by differentiation. This paper is concerned with the use of integrated RBFNs in the context of control-volume discretisations for the simulation of fluid-flow problems. Special attention is given to (i) the development of a stable high-order upwind scheme for the convection term and (ii) the development of a local high-order approximation scheme for the diffusion term. Benchmark problems including the lid-driven triangular-cavity flow are employed to validate the present technique. Accurate results at high values of the Reynolds number are obtained using relatively-coarse grids

Secrecy performance of TAS/SC-based multi-hop harvest-to-transmit cognitive WSNs under joint constraint of interference and hardware imperfection

In this paper, we evaluate the secrecy performance of multi-hop cognitive wireless sensor networks (WSNs). In the secondary network, a source transmits its data to a destination via the multi-hop relaying model using the transmit antenna selection (TAS)/selection combining (SC) technique at each hop, in the presence of an eavesdropper who wants to receive the data illegally. The secondary transmitters, including the source and intermediate relays, have to harvest energy from radio-frequency signals of a power beacon for transmitting the source data. Moreover, their transmit power must be adjusted to satisfy the quality of service (QoS) of the primary network. Under the joint impact of hardware imperfection and interference constraint, expressions for the transmit power for the secondary transmitters are derived. We also derive exact and asymptotic expressions of secrecy outage probability (SOP) and probability of non-zero secrecy capacity (PNSC) for the proposed protocol over Rayleigh fading channel. The derivations are then verified by Monte Carlo simulations.Web of Science195art. no. 116

A continuum-microscopic method based on IRBFs and control volume scheme for viscoelastic fluid flows

A numerical computation of continuum-microscopic model for visco-elastic flows based on the Integrated Radial Basis Function (IRBF) Control Volume and the Stochastic Simulation Techniques (SST) is reported in this paper. The macroscopic flow equations are closed by a stochastic equation for the extra stress at the microscopic level. The former are discretised by a 1D-IRBF-CV method while the latter is integrated with Euler explicit or Predictor-Corrector schemes. Modelling is very efficient as it is based on Cartesian grid, while the integrated RBF approach enhances both the stability of the procedure and the accuracy of the solution. The proposed method is demonstrated with the solution of the start-up Couette flow of the Hookean and FENE dumbbell model fluids

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A spectral collocation technique based on integrated Chebyshev polynomials for biharmonic problems in irregular domains

In this paper, an integral collocation approach based on Chebyshev polynomials for numerically solving biharmonic equations [N. Mai-Duy, R.I. Tanner, A spectral collocation method based on integrated Chebyshev polynomials for biharmonic boundary-value problems, J. Comput. Appl. Math. 201 (1) (2007) 30–47] is further developed for the case of irregularly shaped domains. The problem domain is embedded in a domain of regular shape, which facilitates the use of tensor product grids. Two relevant important issues, namely the description of the boundary of the domain on a tensor product grid and the imposition of double boundary conditions, are handled effectively by means of integration constants. Several schemes of the integral collocation formulation are proposed, and their performances are numerically investigated through the interpolation of a function and the solution of 1D and 2D biharmonic problems. Results obtained show that they yield spectral accuracy

WALL EFFECT OF A PACKED BED WITH PELLET PARTICLES

Fluid flow profile is a dominate role in the performance of packed bed reactor. In small ratio of column-to-particle diameter, velocity pattern is strongly affected by voidage distribution, which depends on radial coordinate, flow rate and bed height. In this study, effects of voidage distribution to gas velocity profile in a packed bed with pellet particles was empirically investigated. Uniformity of local velocity at the top of the bed was clearly observed with decreasing of bed height and flow rate. For 400 mm of bed height, the measured velocities are a well fitting to Fahien and Stankovich model for any expected flow rate

Exploring land use land cover change to understand urban warming effect in Hanoi inner city, Vietnam

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesRecently, urbanization is occurring rapidly in Hanoi, the second largest city in Vietnam. The process is profoundly reflected in Hanoi inner city where the socio-economic development is faster than in other areas. This has led to the acquisition of agricultural land that in turn, has resulted in land use changes, and subsequently increasing the residential, commercial and industrial land. The transformation between different land use types especially the urban expansion will crucially influence the land surface temperature pattern (LST). This will severely affect to the community in relation to people’s health and energy consumption. Exploring land use land cover (LULC) change to understand urban warming effect is a necessary work for community and local government. The research can be used as a scientific basis for urban planners in urban planning and management as well as to increase the community awareness in urban warming effect. The purpose of this research is to determine and analyze the relationship between LULC change and LST pattern. To achieve the research goal, we need to accomplish a series of specific objectives. First, we perform supervised maximum likelihood classification method and change detection to determine the patterns and rate of change, and land cover and land use transformation within and around Hanoi inner city. Then we explore the relationship between land surface temperature and a) vegetation, b) man-made features, and c) crops land using normalized vegetation, and built-up indices within each LULC type. After that, we employ a Markov chains model to simulate future LULC change using different environmental and planning scenarios. Finally, we apply linear and non- linear regression to predict future urban climate patterns in Hanoi inner city using the predicted land cover and land use change

Association Of Diurnal Temperature Range With Pediatric Influenza Hospitalization Rates In The United States, 2009 – 2019

Introduction: Climate change may have a negative impact on respiratory illnesses, such as influenza. Diurnal temperature range (DTR), an indicator of climate change, is the difference between the maximum and minimum temperature within a day or a week. As the climate warms, global DTR decreases, though there might be regions where DTR increases instead. Previous literature conducted in non-U.S. regions found both positive and negative associations between DTR and influenza infections. A group especially vulnerable to the effects of DTR are children less than 5 years of age due to their less-developed thermoregulation capability. This study thus aimed to explore the association of DTR with pediatric influenza hospitalization rates in different U.S. states from 2009 to 2019 to further understand this relationship. Methods: Utilizing weekly influenza hospitalization rates from the Center for Disease Control and Prevention (CDC)’s FluSurv-NET surveillance system and meteorological data from the National Oceanic and Atmospheric Administration (NOAA), we employed a distributed non-linear lag model and a generalized additive model using a quasi-Poisson distribution to examine the complex non-linear relationship between the two variables, adjusting for relative humidity, mean temperature, and precipitation. Results: New York’s Albany and Rochester, Michigan, and California exhibited positive associations between DTR and pediatric influenza hospitalization rate (relative risk at maximum DTR was 3.06 (95% confidence interval (CI): 1.532 – 5.893), 1.97 (95% CI: 1.018 –3.812), 2.07 (95% CI: 1.185 – 3.601), and 1.69 (95% CI: 1.054 – 2.707), respectively). Additionally, there was a respective 1,403% (p = 0.007), 475% (p = 0.045), 569% (p = 0.011), and 344% (p=0.030) change in hospitalization rate for every 1°C increase in DTR. Conclusions: Our results can be used to inform the development of an early warning system that can alert the potential impact of a significant increase in DTRs. With regard to climate change, if global DTR decreases as the climate warms, then our results suggest that hospitalization rates will decrease as well, though in regions where DTR increases, hospitalization rates might increase. Further research on the relationship between temperature variability and respiratory infections that utilizes more granular data and that considers other important meteorological factors, influenza strain type, and vaccination history is needed