CC BY
33
ws.n. = + dTLnTL + dIŒpnKLP + dVAnvA + where n-is an amount for Put production by principal technological
, , , , , equipment at in-plant procurement center, t.
+dxppn xpp + dBXnBX + d0BTn0BT + y^uvp^uvp + "osv^osv )
kw. h/design period
Table 2.
№ Name of mechanization facility Type Design indicators Experimental indicators
Efficiency, t/s Specified capacity, kw Specific consumption of energy, kw/t Actual efficiency, t/h Consumed capacity, kw Actualspecificenergy consumption, kw.h/t
1 Mobile belt cotton conveyor TXL-18 20 9,7 0,49 12 4 0,3
2 Belt conveyor TL 35 11,5 0,33 21 4,8 0,2
3 Belt mobile conveyor KLP-650 38 9,7 0,26 22,8 4 0,2
4 Receiving-feeding unit-feeder PLA 24 3 0,13 14,4 1,3 0,09
5 Receiving-feeding unit XPP 30 4,75 0,16 18 2 0,1
6 Batch packer BX 35 35 1 21 14,7 0,7
7 Tunnel digging machine OBT 3 13,2 4,4 1,8 5,5 3
8 Ventilator for air suction through tunnel at efficiency up to 0,7 UVP 2,5 m 3/s 22 8,8 kw. h/M3S 2,5 m3/s 14 5,6 kw. h/m 3s
So, it is recommended to use experimentally obtained data to of specific norms of energy consumption and absolute consumption analyze and predict energy indicators; they increase design accuracy of electric power.
References:
1. Guide on primary processing of cotton. - Book 1. - Tashkent, "Mehnat" - 1994-574 p.
2. Allaev P., Khoshimov F. A. Energy Savingin Industrial Enterprises. - Tashkent: FAN. - 2011. - 207 p.
DOI: http://dx.doi.org/10.20534/ESR-16-9.10-217-220
Usmanov Rishat Niyazbekovich, Kuchkorov Temurbek Ataxonovich, Oteniyazov Rashit Idrisovich, Tashkent University of Information Technologies, Tashkent, Uzbekistan E-mail: timanet4u@gmail.com
Environmental monitoring to get special data from observation points (based on ecological factors)
Abstract: For defining ecological factor's status, there is one of the useful methods that to get special data from observation points and analyses it without human factors. As well as, GIS modeling illustrates this collected data from observation points with environmental parameters.
Keywords: stations, observation points, ecological factors, digital data, big data, geoprocessing, environmental monitoring, EDMS.
Introduction: Our environment is constantly changing and there is no denying that. However, as our environment changes, so does the need to become increasingly aware of the problems that surround it. With a massive influx of natural disasters, warming and cooling periods, different types ofweather patterns and much more, people need to be aware of what types of environmental problems our planet is facing. Environmental problems contain pollution, global warming and climate; improve grand soiling, changing water, changing air quality and other problems in ecological stress area.
These areas need making environmental monitoring to define status of ecology.
Environmental monitoring describes the processes and activities that need to take place to characterize and monitor the quality of the environment. Environmental monitoring is used in the preparation of environmental impact assessments, as well as in many circumstances in which human activities carry a risk of harmful effects on the natural environment. All monitoring strategies and programs have reasons and justifications, which are often designed to establish
the status of an environment or to establish trends in environmental parameters. In all cases, the results of monitoring will be reviewed, analyzed statistically, intellectualized and published. In addition, collected data from observation points with environmental parameters are illustrated by GIS technology.
The purpose of the task: Actually, through ecological stress areas that a large number of distributed applications requires continuous and timely processing of information and data as it flows from the periphery to the center of the system.
Examples are that kind of systems, which analyze network traffic in real-time to identify possible attacks, environmental monitoring applications, which process raw data coming from sensor networks
to identify critical situations, or applications performing on-line analysis of stock prices to identify trends and forecast fUture values. To define ecological factor's value, we need sensor network to get special data from observation points in ecological stress areas.
A sensor network is a computer accessible network of many spatially distributed devices, which uses sensors to monitor conditions at different locations. In addition, it captures real-time information about environmental features. However, these networks of sensors are not connected to each other. This means that users cannot access the data from one convenient location; consequently, making an effective decision in a critical situation would be a challenging issue in the case of environmental monitoring (figure 1).
Figure 1. Sensor network
Actually, traditional DBMSs, which need to store and index data before processing it, can hardly fulfill the requirements of timeliness coming from such domains. Accordingly, during the last decade different research communities developed a number of tools, which we collectively special data from observation points in ecological stress areas. However, in this case Flow Processing (IFP) Systems, to support these scenarios. They differ in their system architecture, data model, rule model, and rule language. We survey these systems to help researchers, often coming from different backgrounds, in understanding how the various approaches they adopt may complement each other. In particular, we propose a general, unifying model to capture the different aspects of an IFP system and use it to provide a complete and precise classification of the systems and mechanisms proposed so far. In addition, commercial software Environmental Data Management Systems (EDMS) or E-MDMS are increasingly in common use by regulated industries. They provide a means of managing all monitoring data in a single central place. Quality validation, compliance checking, verifying all data has been received, and sending alerts are generally automated.
Function module: Why we use meaning of "ecological stress area"? Ecological stress area — combine that kind of areas have some problems with ecological factors. There is many ways to get data from ecological stress area:
— getting special data from observation points;
— processing aerospace pictures;
— getting expert's information (solutions and diagnoses);
— applying the knowledge of an expert and developing expert systems;
Given arguments of collecting data, help us to define state of ecological stress areas. Observation points can collect and send data about given area through sensor network. Actually, these points' data related to sensor type, for example sensors can get data from water, ground or from other objects (figure 2).
As you see, figure 2 shows that, we have a special ecological stress area with water soiling factors. Observation points can define value of water soiling with intermediate value 0 to 5. For example, table gives that, X2 and X3 observation points are normal area. Because, the indicator shows that water soiling less than other observation points. This environmental monitoring is used to define value of water soling in special ecological stress area.
Solution of environmental monitoring need developing mathematical models of getting data from observation points. The mathematical model considers environmental monitoring tasks are non-linear partial differential equations that describe the processes occurring in the subsurface hydrosphere variations in temperature (ten-day, monthly, seasonal) of air.
As you know, GIS technology is one the best thing to illustrate data that collected from observation points. Actually, GIS technology has different kind of functions. GIS is a broad term that can refer to a number of different technologies, processes, and methods. It is attached to many operations and has many applications related to engineering, planning, management, transport/logistics, insur-
ance, telecommunications, and business. For that reason, GIS and location-enabled services that rely on analysis and visualization location intelligence applications can be the foundation for many (figure 3).
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St4
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ObtcrvatKTj poinli to get 5jre:tal data from ecûlogjjcal stress area
Inttrnil or Errtarpr» IPtohnrfc
Seivrri
XI X2 X3 X4 xs
IßS 0,45 0,32 3,22 I,SB
1,74 0,57 0,24 | 3,45 2,15
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1,15 0,32 0,3] 3,7£ 1,92
0,67 0,41 0,20 3,67 I,9S
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Figure 2. System architecture of observation points
Computers or mobile devices Mobile devices Computers
Figure 3. Sensor network to get special data from observation points in ecological stress areas
Typical interrogation functionality enables comparison of data sets both temporarily and spatially. Actually, defining ecological stress areas following ecological factors and monitoring environments are necessary:
• Air quality monitoring
• Soil monitoring
• Water quality monitoring
Air quality monitoring is performed using specialized equipment and analytical methods used to establish air pollutant concentrations. Actually, air monitors are operated by citizens, regulatory agencies and researchers that is investigated air quality and the effects of air pollution. Air dispersion models that combine topographic, emissions and meteorological data to predict air pollutant concentrations are often helpful in interpreting air-monitoring data.
Soil monitoring is the process of collection of soil and testing in laboratory by analytical methods. Soil samplings are of two types:
— Grab sampling: in this method, sample is collected randomly from field.
— Composite sampling: In this method, mixing of multiple sub samples for larger and non-uniform fields.
Water quality monitoring is of little use without a clear and unambiguous definition of the reasons for the monitoring and the objectives that it will satisfy. Almost all monitoring (except perhaps remote sensing) is in some part invasive of the environment under study and extensive and poorly planned monitoring carries a risk of damage to the environment. This may be a critical consideration in wilderness areas or when monitoring very rare organisms or those that are averse to human presence. Some monitoring techniques, such gill netting fish to estimate populations, can be very damaging, at least to the local population and can also degrade public trust in scientists carrying out the monitoring.
References:
1. Usmanov R. N. and others «Моделирования сложных процессов и управление ими в условиях нечёткой информации». T.: «Fan va texnologiya», - 2016, - 296 p.
2. Mandana Mokhtary, "Sensor Observation Service for Environmental Monitoring Data" School ofArchitecture and the Built Environment Royal Institute of Technology, - April - 2012, - 114 p.
3. Lingjun Zhao, Lajiao Chen, "Cluster Computing" - March - 2016, - Volume 19, Issue 1, - P. 139-152. Geographical information system parallelization for spatial big data processing.
4. Michael Kennedy, «Introducing Geographic Information Systems with ArcGIS: A Workbook Approach to Learning GIS», John Wiley & Sons, - Apr 13, - 2009 - Science - 571 p.
DOI: http://dx.doi.org/10.20534/ESR-16-9.10-220-223
Fatkhullaev Alisher Mirzatilloevich PhD in Technical Sciences, Associate Professor, Senior Researcher. Tashkent Institute of Irrigation and Melioration (TIIM) E-mail: timi-hydro@inbox.ru Arifjanov Aybek Muhamedjanovich, Doctor of technical sciences, professor, Head of the Department of Hydraulics Tashkent Institute of Irrigation and Melioration (TIIM)
E-mail: obi-life@mail.ru
Optimization of hydraulic parameters of irrigation canals in earthen channel
Abstract: A review and analysis of the stock and the published materials devoted to the methods of calculating the parameters of irrigation canals. We consider the analysis of the hydraulic characteristics of the channels in earthen channel. It is shown
Solution of environmental monitoring is developing mathematical models of getting data from observation points. The mathematical model considers environmental monitoring tasks are non-linear partial differential equations that describe the processes occurring in the subsurface hydrosphere variations in temperature (ten-day, monthly, seasonal) of air.
Complex mathematical model of filtration of groundwater and migration of salts in the groundwater flow is represented as: dh „2 d dh
^ = 1,=!(kh) + f - w (1) dt dx. dx.
d(hc) dq, f
~ dc
q,=vc - d t dx (3)
where, h(xvx2,t)j = vc(xpx2,t) — groundwater salinity, k(X 1> X 2)> DD (X 1> X 2) — filter coefficients and diffusion salts, q. — salts coefficients.
The system (1) and (2) are implemented with the objectives of the relevant initial and boundary conditions, certain natural conditions [1]. Territorial distributed objects characterize the parameters of these models, so the implementation of such models is carried out based on modern GIS technology.
Summary: This paper details that clarifying the useful method that to get special data from observation points in ecological stress areas without human factors. In this case environmental monitoring can play more important role to get special data that water quality, water or grand soiling, air quality and others from observation points. We should create sensor network and share special data through servers to different kind of devices that computers or mobile devices.
