scholarly journals Assumptions in the evaluation of lava effusion rates from heat radiation

2009 ◽  
Vol 36 (8) ◽  
Author(s):  
Michele Dragoni ◽  
Andrea Tallarico
Keyword(s):  
Heat Radiation ◽  
Lava Effusion ◽  
Effusion Rates

Calculation of lava effusion rates from Landsat TM data

1998 ◽  
Vol 60 (1) ◽  
pp. 52-71 ◽  
Author(s):  
Andrew J. L. Harris ◽  
Luke P. Flynn ◽  
Laszlo Keszthelyi ◽  
Peter J. Mouginis-Mark ◽  
Scott K. Rowland ◽  
...  
Keyword(s):  
Landsat Tm ◽  
Lava Effusion ◽  
Effusion Rates

Lava effusion rates from hand-held thermal infrared imagery: an example from the June 2003 effusive activity at Stromboli

2005 ◽  
Vol 68 (2) ◽  
pp. 107-117 ◽  
Author(s):  
Andrew Harris ◽  
Jon Dehn ◽  
Matt Patrick ◽  
Sonia Calvari ◽  
Maurizio Ripepe ◽  
...  
Keyword(s):  
Thermal Infrared ◽  
Infrared Imagery ◽  
Effusive Activity ◽  
Lava Effusion ◽  
Effusion Rates ◽  
Thermal Infrared Imagery

Simulation of Heat Radiation Asymmetry with Maple

2013 ◽  
Vol 23 (3-4) ◽  
Author(s):  
Ildiko Perjesi-Hamori
Keyword(s):  
Heat Radiation

scholarly journals Design of Thermal Insulation Materials with Different Geometries of Channels

Polymers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 2217
Author(s):  
Daniela Șova ◽  
Mariana Domnica Stanciu ◽  
Sergiu Valeriu Georgescu
Keyword(s):  
Thermal Conductivity ◽  
Porous Structure ◽  
Base Material ◽  
Cost Effective ◽  
Heat Radiation ◽  
Average Temperature ◽  
Temperature Regimes ◽  
The Face ◽  
Inclined Channels ◽  
Air Channels

Investigating the large number of various materials now available, some materials scientists promoted a method of combining existing materials with geometric features. By studying natural materials, the performance of simple constituent materials is improved by manipulating their internal geometry; as such, any base material can be used by performing millimeter-scale air channels. The porous structure obtained utilizes the low thermal conductivity of the gas in the pores. At the same time, heat radiation and gas convection is hindered by the solid structure. The solution that was proposed in this research for obtaining a material with porous structure consisted in perforating extruded polystyrene (XPS) panels, as base material. Perforation was performed horizontally and at an angle of 45 degrees related to the face panel. The method is simple and cost-effective. Perforated and simple XPS panels were subjected to three different temperature regimes in order to measure the thermal conductivity. There was an increase in thermal conductivity with the increase in average temperature in all studied cases. The presence of air channels reduced the thermal conductivity of the perforated panels. The reduction was more significant at the panels with inclined channels. The differences between the thermal conductivity of simple XPS and perforated XPS panels are small, but the latter can be improved by increasing the number of channels and the air channels’ diameter. Additionally, the higher the thermal conductivity of the base material, the more significant is the presence of the channels, reducing the effective thermal conductivity. A base material with low emissivity may also reduce the thermal conductivity.

Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption

2021 ◽  
Vol 83 (4) ◽  
Author(s):  
Hannah R. Dietterich ◽  
Angela K. Diefenbach ◽  
S. Adam Soule ◽  
Michael H. Zoeller ◽  
Matthew P. Patrick ◽  
...  
Keyword(s):  
Rift Zone ◽  
Effusion Rate ◽  
Lava Effusion

scholarly journals Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 988
Author(s):  
Kshirasagar Naik ◽  
Tejas Pandit ◽  
Nitin Naik ◽  
Parth Shah
Keyword(s):  
Internet Of Things ◽  
Activity Recognition ◽  
Thermal Model ◽  
Thermal Image ◽  
Heat Radiation ◽  
Household Activity ◽  
Thermal Images ◽  
Gas Leakage ◽  
3D Space ◽  
Image Pairs

In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces.

scholarly journals Dynamic Changes of Local Climate Zones in the Guangdong–Hong Kong–Macao Greater Bay Area and Their Spatio-Temporal Impacts on the Surface Urban Heat Island Effect between 2005 and 2015

2021 ◽  
Vol 13 (11) ◽  
pp. 6374
Author(s):  
Yang Lu ◽  
Jiansi Yang ◽  
Song Ma
Keyword(s):  
Hong Kong ◽  
Land Surface ◽  
Morphological Changes ◽  
Mapping Method ◽  
Heat Radiation ◽  
Climate Zones ◽  
Local Climate ◽  
Bay Area ◽  
Local Climate Zones ◽  
Urban Heat

Local climate zones (LCZs) emphasize the influence of representative geometric properties and surface cover characteristics on the local climate. In this paper, we propose a multi-temporal LCZ mapping method, which was used to obtain LCZ maps for 2005 and 2015 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), and we analyze the effects of LCZ changes in the GBA on land surface temperature (LST) changes. The results reveal that: (1) The accuracy of the LCZ mapping of the GBA for 2005 and 2015 is 85.03% and 85.28%, respectively. (2) The built type category showing the largest increase in area from 2005 to 2015 is LCZ8 (large low-rise), with a 1.01% increase. The changes of the LCZs also vary among the cities due to the different factors, such as the economic development level and local policies. (3) The area showing a warming trend is larger than the area showing a cooling trend in all the cities in the GBA study area. The main reasons for the warming are the increase of built types, the enhancement of human activities, and the heat radiation from surrounding high-temperature areas. (4) The spatial morphology changes of the built type categories are positively correlated with the LST changes, and the morphological changes of the LCZ4 (open high-rise) and LCZ5 (open midrise) built types exert the most significant influence. These findings will provide important insights for urban heat mitigation via rational landscape design in urban planning management.

scholarly journals Simple empirical method for estimating lava-effusion rate using nighttime Himawari-8 1.6-µm infrared images

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Takayuki Kaneko ◽  
Atsushi Yasuda ◽  
Toshitsugu Fujii
Keyword(s):  
Lava Flow ◽  
Estimation Method ◽  
Simulation Software ◽  
Spectral Radiance ◽  
Effusion Rate ◽  
Actual Distribution ◽  
High Positive Correlation ◽  
Low Viscosity ◽  
Lava Effusion ◽  
The Relationship

AbstractThe effusion rate of lava is one of the most important eruption parameters, as it is closely related to the migration process of magma underground and on the surface, such as changes in lava flow direction or formation of new effusing vents. Establishment of a continuous and rapid estimation method has been an issue in volcano research as well as disaster prevention planning. For effusive eruptions of low-viscosity lava, we examined the relationship between the nighttime spectral radiance in the 1.6-µm band of the Himawari-8 satellite (R1.6Mx: the pixel value showing the maximum radiance in the heat source area) and the effusion rate using data from the 2017 Nishinoshima activity. Our analysis confirmed that there was a high positive correlation between these two parameters. Based on the linear-regression equation obtained here (Y = 0.47X, where Y is an effusion rate of 106 m3 day−1 and X is an R1.6Mx of 106 W m−2 sr−1 m−1), we can estimate the lava-effusion rate from the observation data of Himawari-8 via a simple calculation. Data from the 2015 Raung activity—an effusive eruption of low-viscosity lava—were arranged along the extension of this regression line, which suggests that the relationship is applicable up to a level of ~ 2 × 106 m3 day−1. We applied this method to the December 2019 Nishinoshima activity and obtained an effusion rate of 0.50 × 106 m3 day−1 for the initial stage. We also calculated the effusion rate for the same period based on a topographic method, and verified that the obtained value, 0.48 × 106 m3 day−1, agreed with the estimation using the Himawari-8 data. Further, for Nishinoshima, we simulated the extent of hazard areas from the initial lava flow and compared cases using the effusion rate obtained here and the value corresponding to the average effusion rate for the 2013–2015 eruptions. The former distribution was close to the actual distribution, while the latter was much smaller. By combining this effusion-rate estimation method with real-time observations by Himawari-8 and lava-flow simulation software, we can build a rapid and precise prediction system for volcano hazard areas.

Sign in / Sign up

Export Citation Format

Share Document