thermophysical modeling
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2021 ◽  
Vol 11 (23) ◽  
pp. 11089
Author(s):  
Nataliya Yurkevich ◽  
Irina Fadeeva ◽  
Elizaveta Shevko ◽  
Alexey Yannikov ◽  
Svetlana Bortnikova

The storage of wastes from mining and mineral processing plants in the tailing dumps in regions with cold climates has a number of environmental consequences. Interactions of water with tailings in cold climates often lead to the thawing of permafrost soils, formation of technogenic thawing zones, and leakage of drainage waters. In the case of fault zones development in these areas, technogenic solutions are often filtered outside the tailing dump, promoting further development of filtration channels. In order to prevent leakage of solution from tailing dumps over time, it is necessary to determine the thawing zones and prevent the formation of filtration channels. In the case of the formation of a filtration channel, it is necessary to know what rate of rock thawing occurred near the formed filtration channel. In this study, for the tailing dump of a diamond mining factory, we calculated two exothermic effects: (1) due to physical heating of dump rock by filtering industrial water with temperatures from 2 to 15 °C through the rock; and (2) due to the chemical interaction of industrial water with the dam base rock. The amount of energy transferred by the water to the frozen and thawed rock over 10 years was calculated using thermophysical modeling and was 207.8 GJ and 8.39 GJ respectively. The amount of energy that the rock received during the ten-year period due to dissolution of the limestones and equilibration of solutions was calculated using thermodynamic modeling and was 0.37 GJ, which is 4.4% of the average amount of energy, expended on heating the thawed rock (8.39 GJ).


2021 ◽  
Author(s):  
Edoardo Rognini ◽  
Maria Teresa Capria ◽  
Angelo Zinzi ◽  
Ernesto Palomba ◽  
Stavro Ivanovski

2021 ◽  
pp. 92-99
Author(s):  
V.I. Postnov ◽  
◽  
S.M. Kachura ◽  
E.A. Veshkin ◽  
◽  
...  

Curing parameters have the greatest impact on the physical and mechanical properties of FRP, therefore their optimum value is of particular importance for obtaining quality products. During curing temperature of the inner layers of the FRP can increase unevenly, which can lead to the formation of a gradient in the degree of conversion and heterogeneity of physical and mechanical properties. The article is devoted to the development of a mathematical model of the curing process of the EDT-69N resin, taking into account the kinetic parameters of curing and implementation thermophysical modeling using the finite element method. The correspondence of the family of curves for the degree of conversion along the sample cross-section and the family of microhardness curves is also shown.


Author(s):  
V.V. Golik ◽  
◽  
M.Yu. Zemenkova ◽  
Yu.D. Zemenkov ◽  
T.G. Ponomareva ◽  
...  

2020 ◽  
Vol 32 (4) ◽  
pp. 042008
Author(s):  
Sebastian Enderle ◽  
Marius Bolsinger ◽  
Simon Ruck ◽  
Volker Knoblauch ◽  
Harald Riegel

2020 ◽  
Author(s):  
Edoardo Rognini ◽  
Angelo Zinzi ◽  
Davide Grassi ◽  
Alberto Adriani ◽  
Alessandro Mura ◽  
...  

<p>MATISSE (Multi-purpose Advanced Tool for the Solar System Exploration) [1] is a tool that allows the visualization of observations from space missions and datasets derived from these observations on  a  three-dimensional  model  of  the  selected  target  body.  The  second  version  of  the  tool  (named MATISSE  2.0 –https://tools.ssdc.asi.it/Matisse)  will,  among  other  things,  include  algorithms developed  by  partner  research  teams;  in  this  work  we  focalize  our  attention  on  the  MATISSE inclusion of two codes developed for atmospheric retrieval and thermophysical modeling. The retrieval code is used for the analysis of the spectra provided by the JIRAM instrument (Jovian Infrared Auroral Mapper [2]) onboard the NASA’s Juno mission, whose main purpose is the study of the upper regions of Jupiter’s atmosphere in the 2-5 μm wavelength range and pressure up to 5-7 bar. The spectra provided by the instrument are processed with the retrieval code that calculates, for each pixel of a hyperspectral image, the chemical and physical parameters in the corresponding points of the  atmosphere  [3].  The  code  processes  all  pixels  of  a  hyperspectral  image,  so  parallelization  is convenient  in  order  to  reduce  the  computation  time;  this  is  possible  by  using  the  Python  language tools, which allow the execution of a code written in its own language (FORTRAN in this case) by providing  the  required  parallelization. As a further optimization step,  the  code has been converted into a Docker image to make it portable and easy to run on heterogeneous architectures. The second  code  included  in  MATISSE  is  a  thermophysical  model  that  calculates  the  surface temperature of airless bodies as function of thermal conductivity [4,5] and other physical properties; the calculated temperature can be compared with the measured ones, if any, in order to retrieve the thermal properties of the soil, or can be used to compute other temperature-dependent quantities. At the present time this code is going to be used for Mercury and Ceres and is almost ready to be included in MATISSE 2.0.</p> <p>[1] Zinzi, A., et al. (2016), Astronomy & Computing, 15, 16-28<br />[2] Adriani, A., et al. (2017), Space Science Reviews, 213, 393-446<br />[3] Grassi et al. (2010), Planetary and Space Science, 58, 1265-1278<br />[4] Capria, M. T. et al (2014), Geophysical Research Letters, 41, 1438-1443<br />[5] Rognini et al. (2019), Journal of Geophysical Research, https://doi.org/10.1029/2018JE005733</p>


2020 ◽  
Vol 638 ◽  
pp. A11
Author(s):  
E. Podlewska-Gaca ◽  
A. Marciniak ◽  
V. Alí-Lagoa ◽  
P. Bartczak ◽  
T. G. Müller ◽  
...  

Context. Thanks to the Gaia mission, it will be possible to determine the masses of approximately hundreds of large main belt asteroids with very good precision. We currently have diameter estimates for all of them that can be used to compute their volume and hence their density. However, some of those diameters are still based on simple thermal models, which can occasionally lead to volume uncertainties as high as 20–30%. Aims. The aim of this paper is to determine the 3D shape models and compute the volumes for 13 main belt asteroids that were selected from those targets for which Gaia will provide the mass with an accuracy of better than 10%. Methods. We used the genetic Shaping Asteroids with Genetic Evolution (SAGE) algorithm to fit disk-integrated, dense photometric lightcurves and obtain detailed asteroid shape models. These models were scaled by fitting them to available stellar occultation and/or thermal infrared observations. Results. We determine the spin and shape models for 13 main belt asteroids using the SAGE algorithm. Occultation fitting enables us to confirm main shape features and the spin state, while thermophysical modeling leads to more precise diameters as well as estimates of thermal inertia values. Conclusions. We calculated the volume of our sample of main-belt asteroids for which the Gaia satellite will provide precise mass determinations. From our volumes, it will then be possible to more accurately compute the bulk density, which is a fundamental physical property needed to understand the formation and evolution processes of small Solar System bodies.


2019 ◽  
Vol 158 (3) ◽  
pp. 97 ◽  
Author(s):  
Joseph R. Masiero ◽  
E. L. Wright ◽  
A. K. Mainzer

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