scholarly journals Meteorite hazard model for a space mission to Mars

2021 ◽  
Vol 2103 (1) ◽  
pp. 012031
Author(s):  
N Y Demina ◽  
A O Andreev ◽  
Y A Nefedyev
Keyword(s):  
Spatial Distribution ◽  
State Standard ◽  
Complex Problem ◽  
Space Mission ◽  
The State ◽  
Distribution Model ◽  
Orbital Parameters ◽  
Space Flights ◽  
Near Earth Space ◽  
The Earth

Abstract Currently, for the world’s space agencies, the robotic exploration of Mars is one of the most important tasks. One of the necessary stages for the implementation of this mission is the development and addition of new information to the State standard “Meteoric substance, spatial distribution model”. Until now, the State Standard has been more detailed in comparison with the American analogue (developed by NASA) and the European one. The standard is a mandatory document in the design of spacecraft. It should be noted that modeling of meteor hazard at a distance from Earth to Mars is a complex problem, since the analysis of the meteor population in near-Earth space does not give a complete picture of the propagation of meteoroids along the Earth-Mars route. Moreover, the further the trajectory of the spacecraft from the Earth’s orbit is, the less the number of near-Earth meteorites becomes. That is, objects that have the same orbital parameters with small bodies crossing the Earth’s orbit. The only way to solve this problem is to build an interpolation regression model, which is based on measurements from the Earth’s surface and observations of space missions. For this purpose, the density of sporadic meteoroids was transformed from the space mission coordinate system to the ground one. This was done in order to analyze meteorite observations by the Mariner 4 and Pioneer 10 spacecrafts. The results of the work made it possible to obtain new data for the spatial distribution of meteoroids on the Earth-Mars path. According to a comparison of our data with the data on the density of space debris in the previous works the most safe for space flights are normalization conditions of distributions of the elements of the orbits of meteoric bodies P(Z, e, i) < 60.

The analysis is geometrically stable orbits of spacecraft remote sensing of the Еarth

2018 ◽  
Vol 15 (1) ◽  
pp. 12-22
Author(s):  
V. M. Artyushenko ◽  
D. Y. Vinogradov
Keyword(s):  
Remote Sensing ◽  
Gravitational Field ◽  
State Vector ◽  
Semimajor Axis ◽  
The State ◽  
Zonal Harmonics ◽  
The Earth ◽  
Conditions Of Stability

The article reviewed and analyzed the class of geometrically stable orbits (GUO). The conditions of stability in the model of the geopotential, taking into account the zonal harmonics. The sequence of calculation of the state vector of GUO in the osculating value of the argument of the latitude with the famous Ascoli-royski longitude of the ascending node, inclination and semimajor axis. The simulation is obtained the altitude profiles of SEE regarding the all-earth ellipsoid model of the gravitational field of the Earth given 7 and 32 zonal harmonics.

scholarly journals Spatio-temporal distribution patterns of Plutella xylostella (Lepidoptera: Plutellidae) in a fine-scale agricultural landscape based on geostatistical analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jian-Yu Li ◽  
Yan-Ting Chen ◽  
Meng-Zhu Shi ◽  
Jian-Wei Li ◽  
Rui-Bin Xu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Plutella Xylostella ◽  
Agricultural Landscape ◽  
Seasonal Pattern ◽  
Distribution Patterns ◽  
Geostatistical Analysis ◽  
Distribution Model ◽  
Detailed Knowledge ◽  
Fine Scale ◽  
Spatio Temporal

AbstractA detailed knowledge on the spatial distribution of pests is crucial for predicting population outbreaks or developing control strategies and sustainable management plans. The diamondback moth, Plutella xylostella, is one of the most destructive pests of cruciferous crops worldwide. Despite the abundant research on the species’s ecology, little is known about the spatio-temporal pattern of P. xylostella in an agricultural landscape. Therefore, in this study, the spatial distribution of P. xylostella was characterized to assess the effect of landscape elements in a fine-scale agricultural landscape by geostatistical analysis. The P. xylostella adults captured by pheromone-baited traps showed a seasonal pattern of population fluctuation from October 2015 to September 2017, with a marked peak in spring, suggesting that mild temperatures, 15–25 °C, are favorable for P. xylostella. Geostatistics (GS) correlograms fitted with spherical and Gaussian models showed an aggregated distribution in 21 of the 47 cases interpolation contour maps. This result highlighted that spatial distribution of P. xylostella was not limited to the Brassica vegetable field, but presence was the highest there. Nevertheless, population aggregations also showed a seasonal variation associated with the growing stage of host plants. GS model analysis showed higher abundances in cruciferous fields than in any other patches of the landscape, indicating a strong host plant dependency. We demonstrate that Brassica vegetables distribution and growth stage, have dominant impacts on the spatial distribution of P. xylostella in a fine-scale landscape. This work clarified the spatio-temporal dynamic and distribution patterns of P. xylostella in an agricultural landscape, and the distribution model developed by geostatistical analysis can provide a scientific basis for precise targeting and localized control of P. xylostella.

Preparation of Interior Latex Coatings by Recycling Banknote Printing Wastewater

2010 ◽  
Vol 168-170 ◽  
pp. 1509-1512
Author(s):  
Zu Min Qiu ◽  
Yan Yan Zeng ◽  
Zhong Wei Liu
Keyword(s):  
State Standard ◽  
Raw Materials ◽  
Low Cost ◽  
The State ◽  
Acrylic Emulsion ◽  
Latex Coatings ◽  
Silicon Sol

This paper related to the recycling of banknote printing wastewater, using which as raw materials, a low cost interior latex coatings has been developed. This coatings is formulated based on styrene-acrylic emulsion and silicon sol as main film former. It has been shown that the performance of of this product meets the state standard of GB/T 9756-2009.

Playing with Death

2021 ◽  
pp. 647-660
Author(s):  
Steed Vernyl Davidson
Keyword(s):  
The State ◽  
State Of Exception ◽  
Systematic Analysis ◽  
The Earth ◽  
Book Of Jeremiah ◽  
Central Claim ◽  
Rhetorical Violence

The task of identifying a single rationale for the violence on display in the book of Jeremiah may end with a coherent answer, but perhaps not a satisfactory one. That violence serves a reforming purpose seems satisfactory to theological readers in search of theodicy, as well trauma analyses that find the violence problematic but understandable. Other interpreters of Jeremiah, such as feminists and postcolonialists, struggle with the gratuitous and seemingly arbitrary nature of the violence. While not an attempt to rationalize the violence, this chapter engages the arbitrariness of the violence through a systematic analysis of four targets of violence in the book of Jeremiah: the prophet, the feminized Israel/Judah as adulterous wife, foreign nations, and the earth. By distinguishing these separate targets, the chapter examines how gender, sexuality, nationality, and speciesism intersect in the enactment of the rhetorical violence in the book. These delineations also set the stage for a central claim of the chapter, that of exceptional violence. Building upon Carl Schmidt’s notion that exceptional violence stems from exceptional vulnerability that requires the state of exception to use unrestrained violence, the chapter considers how the violence as narrated in Jeremiah not only performs this exceptionalism but also has exceptions. By examining who/what dies from the violence in the book, the chapter points out how the politics of death is played out upon different targets.

Exploring the use of gpr and satellite-based snow data for snowmelt runoff predictions

2021 ◽  
Author(s):  
Ilaria Clemenzi ◽  
David Gustafsson ◽  
Jie Zhang ◽  
Björn Norell ◽  
Wolf Marchand ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Data Assimilation ◽  
Snow Water Equivalent ◽  
Distribution Model ◽  
Accurate Estimation ◽  
Snowmelt Runoff ◽  
Snow Water ◽  
Snow Distribution ◽  
The Impact

&lt;p&gt;Snow in the mountains is the result of the interplay between meteorological conditions, e.g., precipitation, wind and solar radiation, and landscape features, e.g., vegetation and topography. For this reason, it is highly variable in time and space. It represents an important water storage for several sectors of the society including tourism, ecology and hydropower. The estimation of the amount of snow stored in winter and available in the form of snowmelt runoff can be strategic for their sustainability. In the hydropower sector, for example, the occurrence of higher snow and snowmelt runoff volumes at the end of the spring and in the early summer compared to the estimated one can substantially impact reservoir regulation with energy and economical losses. An accurate estimation of the snow volumes and their spatial and temporal distribution is thus essential for spring flood runoff prediction. Despite the increasing effort in the development of new acquisition techniques, the availability of extensive and representative snow and density measurements for snow water equivalent estimations is still limited. Hydrological models in combination with data assimilation of ground or remote sensing observations is a way to overcome these limitations. However, the impact of using different types of snow observations on snowmelt runoff predictions is, little understood. In this study we investigated the potential of assimilating in situ and remote sensing snow observations to improve snow water equivalent estimates and snowmelt runoff predictions. We modelled the seasonal snow water equivalent distribution in the Lake &amp;#214;veruman catchment, Northern Sweden, which is used for hydropower production. Simulations were performed using the semi-distributed hydrological model HYPE for the snow seasons 2017-2020. For this purpose, a snowfall distribution model based on wind-shelter factors was included to represent snow spatial distribution within model units. The units consist of 2.5x2.5 km&lt;sup&gt;2&lt;/sup&gt; grid cells, which were further divided into hydrological response units based on elevation, vegetation and aspect. The impact on the estimation of the total catchment mean snow water equivalent and snowmelt runoff volume were evaluated using for data assimilation, gpr-based snow water equivalent data acquired along survey lines in the catchment in the early spring of the four years, snow water equivalent data obtained by a machine learning algorithm and satellite-based fractional snow cover data. Results show that the wind-shelter based snow distribution model was able to represent a similar spatial distribution as the gpr survey lines, when assessed on the catchment level. Deviations in the model performance within and between specific gpr survey lines indicate issues with the spatial distribution of input precipitation, and/or need to include explicit representation of snow drift between model units. The explicit snow distribution model also improved runoff simulations, and the ability of the model to improve forecast through data assimilation.&lt;/p&gt;

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