Performance of Nano-Casson Fluid on Convective Flow Past a Permeable Stretching Sheet: Thermophoresis and Brownian Motion Effects

The paramount importance of the current study has to deliberate nanoparticles for the Casson fluid model supposing Thermophoresis and Brownian motion associates Runge-Kutta fifth-order technique is applied to reduce the elements of non-linear regular difference calculations. Nondimensional physical parameters have appeared after utilization of correspondence alterations among with the design of connected normal difference omputations, where govern the performance of Nano-Casson fluid. Joined calculations are then attempted mathematically, also then the physical behaviour of individually element is exposed explicitly. Numerical consequences for Nusselt and Sherwood numbers through various engineering linked parameters are presented in tabular forms. Finally, program code validation is discussed. Where identified the velocity profiles are decreasing function of Casson fluid and Magnetic field parameters. Temperature is found as an advanced function for the effects of Brownian motion and Thermophoresis limitations. Also, the consequences show that growing of stretching limitation mains to a growth in the velocity distribution and Skin-friction coefficient, while a decrease in the temperature distribution and Nusselt number coefficient. A growth of the Thermophoresis parameter leads to increased nanoparticle volume concentration distribution and the Sherwood number coefficient.

Assessment of Changes in Land Use/Land Cover and Land Surface Temperatures and Their Impact on Surface Urban Heat Island Phenomena in the Kathmandu Valley (1988–2018)

More than half of the world’s populations now live in rapidly expanding urban and its surrounding areas. The consequences for Land Use/Land Cover (LULC) dynamics and Surface Urban Heat Island (SUHI) phenomena are poorly understood for many new cities. We explore this issue and their inter-relationship in the Kathmandu Valley, an area of roughly 694 km2, at decadal intervals using April (summer) Landsat images of 1988, 1998, 2008, and 2018. LULC assessment was made using the Support Vector Machine algorithm. In the Kathmandu Valley, most land is either natural vegetation or agricultural land but in the study period there was a rapid expansion of impervious surfaces in urban areas. Impervious surfaces (IL) grew by 113.44 km2 (16.34% of total area), natural vegetation (VL) by 6.07 km2 (0.87% of total area), resulting in the loss of 118.29 km2 area from agricultural land (17.03% of total area) during 1988–2018. At the same time, the average land surface temperature (LST) increased by nearly 5–7 °C in the city and nearly 3–5 °C at the city boundary. For different LULC classes, the highest mean LST increase during 1988–2018 was 7.11 °C for IL with the lowest being 3.18 °C for VL although there were some fluctuations during this time period. While open land only occupies a small proportion of the landscape, it usually had higher mean LST than all other LULC classes. There was a negative relationship both between LST and Normal Difference Vegetation Index (NDVI) and LST and Normal Difference Moisture Index (NDMI), respectively, and a positive relationship between LST and Normal Difference Built-up Index (NDBI). The result of an urban–rural gradient analysis showed there was sharp decrease of mean LST from the city center outwards to about 15 kms because the NDVI also sharply increased, especially in 2008 and 2018, which clearly shows a surface urban heat island effect. Further from the city center, around 20–25 kms, mean LST increased due to increased agriculture activity. The population of Kathmandu Valley was 2.88 million in 2016 and if the growth trend continues then it is predicted to reach 3.85 million by 2035. Consequently, to avoid the critical effects of increasing SUHI in Kathmandu it is essential to improve urban planning including the implementation of green city technologies.

Implementation dbscan algorithm to clustering satellite surface temperature data in indonesia

Forest and land fires are national and international problems. The frequency of fires in one of Indonesia's provinces, Riau, is a significant problem. Knowing where to repair the burn is essential to prevent more massive fires. Fires occur because of a fire triangle, namely fuel, oxygen, and heat. The third factor can be seen through remote sensing. Using the Landsat-8 satellite, named the Enhanced Vegetation Index (EVI) variable, Normalized Burn Area (NBR), Normal Difference Humidity Index (NDMI), Normal Difference Difference Vegetation Index (NDVI), Soil Adapted Vegetation Index (SAVI), and Soil Surface Temperature (LST). DBSCAN, as a grouping algorithm that can group the data into several groups based on data density. This is used because of the density of existing fire data, according to the character of this algorithm. The selected cluster is the best cluster that uses Silhouette Coefficients, eps, and minutes value extracted from each variable, so there is no noise in the resulting cluster. The result is more than 0, and the highest is the best cluster result. There are 5 clusters formed by clustering, each of which has its members. This cluster is formed enough to represent the real conditions, cluster which has a high LST value or has an NBR value. A high LST value indicates an increase in the area's temperature; a high NBR value indicates a fire has occurred in the area. The combination of LST and NBR values indicates the area has experienced forest and land fires. This study shows that DBSCAN clustered fire and surface temperature data following data from the Central Statistics Agency of Riau Province. Proven DBSCAN can cluster satellite imagery data in Riau province into several clusters that have a high incidence of land fires.

LAND SURFACE TEMPERATURE PROFILING AND ITS RELATIONSHIPS WITH LAND INDICES: A CASE STUDY ON LUCKNOW CITY

Globally, 54.5% of the total population was living in urban settings in 2016 and a projection indicates that if the same trend goes, then this population will be 60% in 2030. Natural land has been converted to impervious space rapidly which is altering the climate change. The main focus of the present paper is the study of Land Surface Temperature (LST) dynamics and its relationship with Land Indices, viz., Normal Difference Vegetation Index (NDVI) which is found negative, Normal Difference Built-up Index (NDBI) which is found positive, Enhanced Built-up and Bareness Index (EBBI) which is found positive in Lucknow city on both time points of 1993 and 2019. This study also includes the effects of land indices on LST profiling in nine different parts and eight different directions to explore the spatial dynamics of city landscape. The NDVI is found higher in the southern side than any other parts of the city in 2019 because of high vegetation growth which resulted in reduction of LST by 4.42 °C to 5.76 °C as compared to parts of the city. The results of NDBI and EBBI exhibit high built-up growth in the landscape of the Lucknow city especially from city center to 13 kms (least growth in south-eastern side) from 1993 to 2019. The results indicate intensification of LST in the range of 0.26 °C to 2.24 °C between city centre and city periphery from 1993 to 2019. The findings of the present study will help urban planners and policy makers to adopt suitable measures for sustainable planning for Lucknow city landscape to reduce the adverse effects of LST.

A Hovercraft-Borne LiDAR and a Comprehensive Filtering Method for the Topographic Survey of Mudflats

To obtain the mudflat topography when existing measuring systems and data processing methods are impracticable under special conditions, this paper presents a hovercraft-borne LiDAR (light detection and ranging) system and a novel comprehensive filtering method. The system is based on a hovercraft and equipped with a laser scanner and a POS (position and orientation system). The filtering method firstly segments the point cloud into different segments by combining the geometric and intensity information, then fitting the ground surface by cloth simulation method, and finally synthetically extracts the ground points with three constraints. These constraints are the distance of the point to the fitting surface, the normal difference between the point and the fitting surface, and the proportion of the possible ground points in the total points of each segment. The effectiveness of the measurement system and the development of the post-processing results were verified on the basis of field measurements, in which a total filtering error of 0.3% and the elevation accuracy of 6.4 cm were obtained. The proposed system and methods provide a new way for efficient and accurate topographic survey on mudflats.

Spatiotemporal Analysis of Land Use/Land Cover and Its Effects on Surface Urban Heat Island Using Landsat Data: A Case Study of Metropolitan City Tehran (1988–2018)

This article summarized the spatiotemporal pattern of land use/land cover (LU/LC) and urban heat island (UHI) dynamics in the Metropolitan city of Tehran between 1988 and 2018. The study showed dynamics of each LU/LC class and their role in influencing the UHI. The impervious surface area expanded by 286.04 (48.27% of total land) and vegetated land was depleted by 42.06 km2 (7.10% of total land) during the period of 1988–2018. The mean land surface temperature (LST) has enlarged by approximately 2–3 °C at the city center and 5–7 °C at the periphery between 1988 and 2018 based on the urban–rural gradient analysis. The lower mean LST was experienced by vegetation land (VL) and water body (WB) by approximately 4–5 °C and 5–7 °C, respectively, and the higher mean LST by open land (OL) by 7–11 °C than other LU/LC classes at all time-points during the time period, 1988–2018. The magnitude of mean LST was calculated based on the main LU/LC categories, where impervious land (IL) recorded the higher temperature difference compared to vegetation land (VL) and water bodies (WB). However, open land (OL) recorded the highest mean LST differences with all the other LU/LC categories. In addition to that, there was an overall negative correlation between LST and the normal difference vegetation index (NDVI). By contrast, there was an overall positive correlation between LST and the normal difference built-up index (NDBI). This article, executed through three decadal change analyses from 1988 to 2018 at 10-year intervals, has made a significant contribution to delineating the long records of change dynamics and could have a great influence on policy making to foster environmental sustainability.

The influence of inertia on the rheology of a periodic suspension of neutrally buoyant rigid ellipsoids

We investigate the rheological properties of a suspension of neutrally buoyant rigid ellipsoids by fluid–structure interaction simulations of a particle in a periodic domain under simple shear using the curvilinear immersed-boundary (CURVIB) method along with a quaternion–angular velocity technique to calculate the dynamics of the particle’s motion. We calculate all the different terms of particle stress for the first time for non-spherical particles, i.e. in addition to the stresslet, we calculate the acceleration and Reynolds stress, which are typically ignored in previous similar works. Furthermore, we derive analytical expressions for all these terms to verify the numerical results and deduce the effect of inertia by comparing our numerical results with the analytical solution. The effect of particle Reynolds number ($\mathit{Re}$), volume fraction (${\it\phi}$), and the shape of particles has been studied on all mechanisms of stress generation, the intrinsic viscosity, and normal stress differences of the suspension for the range$0.008\leqslant {\it\phi}\leqslant 0.112$and$0.01\leqslant \mathit{Re}\leqslant 10.0$. We found that inertia increases the shear and the second normal difference of the stresslet (dominant term of the particle stress), and decreases the first normal difference that is generated due to the strain field. The contribution of acceleration stress to the total stress is found to be important in the second normal stress difference, with a cycle-average comparable to the stresslet component. We also discovered that the contribution of Reynolds stress in the first normal stress difference becomes important even when inertia is as low as$\mathit{Re}\sim O(0.1)$, and its value can be even greater than the stresslet when inertia increases, i.e. Reynolds stresses cannot be ignored for non-spherical particles. For concentrations in the range from dilute to semi-dilute, the effect of inertia on the intrinsic viscosity of a suspension is found to be comparable to the volume fraction. Furthermore, our calculations show that for a dilute concentration and the low-inertia regime ($\mathit{Re}<1.0$), the intrinsic viscosity of a suspension consisting of ellipsoids with an aspect ratio of five can be 20 % higher than its Stokesian analytical value.