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Сообщения, помеченные ‘Sharapov R.V.’

3
Mar

Sharapov R.V. Estimating the cost of storing geo-environmental monitoring information at different levels of a multi-tiered storage

Estimating the cost of storing geo-environmental monitoring information at different levels of a multi-tiered storage

Sharapov R.V.

The paper estimates the cost of storing information at the different levels of a multi-tiered storage. Solid state drives (SSDs) provide the highest access speed, but they have the highest storing information cost. For this reason, SSDs can be used at the top level of storage to provide the superfast access to the operational data if a problem arises. Hard disk drives can be used as major storage media for the operational data storage. They provide high-speed access to the data and have an acceptable storage cost. Tape libraries can be used as a lower level for storing large and very large data amount. Despite the low speed of data access, they have the lowest storage cost.
Keywords: storage, multi-tiered storage, data, cost, speed.

References

  1. Sharapov R.V. Apparatnye sredstva hranenija bol’shih ob#jomov dannyh [Hardware parst of large amounts of data storage] // Inzhenernyj vestnik Dona [Engineering Vestnik of Don], 2012, №4, part 3. – P.20-23.
  2. Sharapov R.V. Apparatnye sredstva organizacii verhnego urovnja operativnogo hranenija chasto ispol’zuemyh jekologicheskih dannyh v mnogourovnevyh sistemah hranenija [Hardware organization of top-level operational storage of frequently used environmental data in multilevel storage systems] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2011, № 3. – P.28-33.
  3. Sharapov R.V. Voprosy primenenija lentochnyh bibliotek v mnogourovnevyh sistemah hranenija jekologicheskih dannyh [The application of tape libraries in a multi-level storage of environmental data] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2011, № 2. – P.33-36.
  4. Sharapov R.V. Nekotorye voprosy ispol’zovanija mnogourovnevyh sistem hranenija izobrazhenij v zadachah monitoringa okruzhajushhej sredy [Some questions of using multi-tiered storage of images in the problems of environmental monitoring] // Sovremennye naukoemkie tehnologii [Modern high technologies], 2011, № 2. – P.50-52.

«Engineering industry and life safety» №3 (21), 2014. Pages: 48-51

Download full text:Sharapov R.V. The use of cloud technology for storing data on geo-environmental monitoring

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

3
Mar

Sharapov R.V. The use of cloud technology for storing data on geo-environmental monitoring

The use of cloud technology for storing data on geo-environmental monitoring

Sharapov R.V.

The paper considers the issue of cloud technologies for storing data on geo-environmental monitoring. Cloud data storage is a set of servers distributed throughout the networks and connected into a single cloud. From the user’s perspective the storage is a high-capacity drive. The internal cloud structure and physical storage media are not visible to the user. An effective solution to providing storage of geo-environmental monitoring data can be a multi-tiered storage within its own cloud integrating all the necessary data. In addition, the cloud storage makes it possible to perform undetected data distribution at different levels of the multi-tiered storage. For consumers, the information is still stored in the cloud and transferred between different devices within the cloud without being noticed by the user.
Keywords: monitoring, data, cloud storage, cloud tehnology, storage.

References

  1. Buyya R., Broberg J., Goscinski A. Cloud Computing: Principles and Paradigms. New York, USA: Wiley Press, 2011. – pp. 1–44.
  2. Cloud-integrated Storage – What & Why: Storsimple white paper: Cloud-integrated storage // http://www.storsimple.com/Portals/65157/ docs/storsimple%20-%20cloud-integrated%20storage.pdf
  3. Dropbox // https://www.dropbox.com/
  4. Google Drive // https://drive.google.com/
  5. Jones T. Anatomy of a cloud storage infrastructure // IBM  developer Works, 30 November 2010
  6. Kolodner E.K., Tal S., Kyriazis D., Naor D.,Allalouf M. A Cloud Environment for Data-intensive Storage Services // In proceeding of: IEEE 3rd Interna-tional Conference on Cloud Computing Technology and Science, CloudCom 2011, Athens, Greece, November 29 – December 1, 2011.
  7. Sangani K. Consumer cloud storage // Engineering and Technology Magazine, 2013, Vol. 8, Issue 2.
  8. SkyDrive // https://skydrive.live.com/‎
  9. Walker G. Cloud computing fundamentals // IBM  developer Works, 17 December 2010.
  10. Yandex.Disk // http://disk.yandex.ru/
  11. Sharapov R.V. Apparatnye sredstva hranenija bol’shih ob#jomov dannyh [Hardware parst of large amounts of data storage] // Inzhenernyj vestnik Dona [Engineering Vestnik of Don], 2012, №4, part 3. – P.20-23.
  12. Sharapov R.V. Apparatnye sredstva organizacii verhnego urovnja operativnogo hranenija chasto ispol’zuemyh jekologicheskih dannyh v mnogourovnevyh sistemah hranenija [Hardware organization of top-level operational storage of frequently used environmental data in multilevel storage systems] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2011, № 3. – P.28-33.
  13. Sharapov R.V. Voprosy primenenija lentochnyh bibliotek v mnogourovnevyh sistemah hranenija jekologicheskih dannyh [The application of tape libraries in a multi-level storage of environmental data] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2011, № 2. – P.33-36.
  14. Sharapov R.V. Nekotorye voprosy ispol’zovanija mnogourovnevyh sistem hranenija izobrazhenij v zadachah monitoringa okruzhajushhej sredy [Some questions of using multi-tiered storage of images in the problems of environmental monitoring] // Sovremennye naukoemkie tehnologii [Modern high technologies], 2011, № 2. – P.50-52.

«Engineering industry and life safety» №3 (21), 2014. Pages: 44-47

Download full text:Sharapov R.V. The use of cloud technology for storing data on geo-environmental monitoring

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

20
Jul

Sharapov R.V. Organization of automatic surface waters observation

Organization of automatic surface waters observation

Sharapov R.V.

The paper deals with the organization of surface waters observation systems. The analysis of equipment intended for automatic data collecting without human interference is performed. Standalone recorders (loggers) for logging temperature, surface water level and salinity are tested. Performance characteristics of Solinst Model 3001 Levelogger Edge, Solinst Model 3001 Levelogger Junior, Solinst Model 3001 LTC Levelogger Junior are given. The data collector for receiving data from loggers is presented. The plan to implement a wireless system sending data from the standalone recording device to a processing centre is considered. Using this approach, it is possible to deploy a surface water observation network over a large area and collect data online. The high sensor reaction rate may help monitor the status change at the frequency ranging from a second fraction to 99 hours. This gives new opportunities for hydrosphere surface research.

Keywords: monitoring, rivers, surface water, pollution, water, equipment, sensors.

References

  1. Sharapov R.V. Perehod ot tehnicheskih k prirodno-tehnicheskim sistemam [The transition from the technical to the natural-technical systems]// Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2012, № 2. – P.43-46.
  2. Solovjev L.P., Bulkin V.V., Sharapov R.V. Sushhestvovanie cheloveka v ramkah tehnosfery [The existence of man in the technosphere] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2012, № 1 (11). – P.31-39
  3. Solinst Canada Ltd http://www.solinst.com/
  4. Solinst Levelogger Series. Model 3001 Data Sheet http://www.solinst.com/products/data/3001.pdf
  5. Solinst Levelogger Junior Edge. Model 3001 Data Sheet http://www.solinst.com/products/data/3001junior.pdf
  6. Solinst LTC Levelogger Junior Model 3001 Data Sheethttp://www.solinst.com/products/data/3001ltc-junior.pdf
  7. Solinst Leveloader Gold. For Use with Model 3001 http://www.solinst.com/products/data/3001leveloadergold.pdf
  8. Solinst Telemetry Systems. Model 9100 and 9200 Gold Data Sheet http://www.solinst.com/products/data/9100.pdf
  9. Neptune’s R900® GPRS Gateway http://www.neptuneequipment.com/pdf/fixedbase/gateway.pdf
  10. Sharapov R.V. Lesnye pozhary 2010 goda i ih prichiny [Forest fires in 2010 and their causes]// Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2010, № 7. – P.68-71

«Engineering industry and life safety» №2 (20), 2014. Pages: 32-38

Download full text:Sharapov R.V. Organization of automatic surface waters observation

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

5
Jul

Sharapov R.V. Methods of processing incomplete data for geo-environmental monitoring

Methods of processing incomplete data for geo-environmental monitoring

Sharapov R.V.

The paper analyzes the methods of incomplete data processing received in the course of geo-environmental monitoring. In the surveying process the part of data can be missed as a result of hardware failures, errors in research conducting, or when observations fail to be made in some periods, etc. Furthermore, the maximum likelihood method, the regression method, the principal component analysis, the stepwise regression, multivariate linear extrapolation method, the method of predictive variables can be used for error detecting and filling in the gaps of data sets. These methods work fine for large data sets and known distribution functions of the values in question. Empirical methods can be used for processing small amounts of information. The method of modeling low-dimensional manifolds is applied for filling in the incomplete data and correcting its errors.

Keywords: exogenous processes, monitoring, data, data processing, incomplete data.

References

  1. Sharapov R.V. O soglasovanii dannyh monitoringa jekzogennyh processov, poluchennyh iz raznorodnyh istochnikov [On the conformity of monitoring data obtained from various sources]// Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2013, № 4. – P.43-46.
  2. Sharapov R.V.Nekotorye voprosy monitoringa jekzogennyh processov [Some problems of exogenous processes monitoring] // Fundamental’nye issledovanija [Fundamental research], 2013, № 1-2. – P. 444-447
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  6. Walsh J.E. Computer-feasible method for handling incomplete data in regression analysis // Journal of ACM, 1961, vol. 18. – P. 201-211.
  7. Gleason T.C., Staelin R. A proposal for handling missing data // Psychometrika, 1975, vol. 40. – P. 229-252.
  8. Frane G.M. Some simple procedures for handling missing values in multivariate analysis // Psychometrika, 1976, vol. 41. – P. 409-415.
  9. Rastrigin L.A., Ponamarev Yu.P. Jekstrapoljacionnye metody proektirovanija i upravlenija [Extrapolation methods, design and management]. – Moscow: Mashinostroenie, 1986. – 120 p.
  10. Zhanatausov S.U.Metody prognosticheskih peremennyh. Mashinnye metody obnaruzhenija zakonomernostej [Methods prognostic variables. Machine methods of detection patterns] – Novosibirsk, 1981, vol. 88, Computer systems. – P. 151-155.
  11. Engelman L. An efficient algorithm for computing covariance matrices from data with missing values // Communications in Statistics PartB., 1982, vol. 11. – P. 113-121.
  12. Huseby J.R., Schwertman N.C., Allen D.M. Computation of the mean vector and dispersion matrix for incomplete multivariate data // Communications in Statistics Part B., 1980, vol. 9. – P. 301-309.
  13. Dempster A.P., Laird N.M., Rubin D.B. Maximum likelihood from incomplete data via the EM-algorithm // Journal of the Royal Statistical Society Series B, 1977, vol. 39. – P. 1-38.
  14. Little R.J., Smith P.J. Editing and imputation for quantitative survey data // Journal of the AmericanStatisticalAssociation, 1987, vol. 82. – P. 58-68.
  15. Little R.J., Rubin D. B. Statistical Analysis with Missing Data. – Chichester, John Wiley & Sons, 1987. – 278 р.
  16. Zagorujko N.G., Elkina V.N., Timerkaev V.S. Algoritm zapolnenija propuskov v jempiricheskih tablicah (algoritm ZET) [Algorithm fill the gaps in empirical tables (algorithm ZET)] // Vychislitel’nye sistemy [Computer systems]. Novosibirsk, 1975. vol. 61. Jempiricheskoe predskazanie i raspoznavanie obrazov [Empirical prediction and pattern recognition]. – P. 3-27.
  17. Gorban A.N., Novohodko Yu.A., Tsaregorodtsev V.G. Nejrosetevaja realizacija transponirovannoj zadachi linejnoj regressii [Neural implementation of the transposed linear regression problem] // Nejroinformatika i ee prilozhenija. Tes. docl. IV Vseross. seminara [Proceedings of Neuroinformatics and its applications], Krasnoyarsk, 5-7 October 1996. – P. 37–39.
  18. Gorban A.N., Rossiev A.A. Neural network iterative method of principal curves for data with gaps // Journal of Computer and Systems Sciences International. 1999. Т. 38. № 5. С. 825-830.

«Engineering industry and life safety» №1 (19), 2014. Pages: 68-72

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

5
Jul

Bulkin V.V., Solovjev L.P., Sharapov R.V., Pervushin R.V., Kirillov I.N. The problems of creating monitoring systems for acoustic noise pollution in residential areas

The problems of creating monitoring systems for acoustic noise pollution in residential areas

Bulkin V.V., Solovjev L.P., Sharapov R.V., Pervushin R.V., Kirillov I.N.

Noise pollution of residential areas is becoming an increasingly serious problem. Continuous growth in automotive transport intensity, construction and industrial sites in the urban environment lead to the fact that the acoustic discomfort zone in modern cities covers up to 50 % of their territory. It is urgent to monitor acoustic noise pollution in residential areas as well as predict possible noise propagation deep into residential areas. Besides acoustic noise of the audible range, infrasound and ultrasonic waves aggravate noise pollution. When predicting acoustic noise propagation, it is necessary to consider the local meteorological parameters for specific areas of urban environment. Thus, the task of creating automatic combined monitoring systems is becoming extremely important. Noise propagation prediction can be provided by means of geographic information systems. The paper analyzes the known and possible approaches and tools for solving the problem of efficient noise pollution monitoring of residential areas.

Keywords: acoustic noise, meteorological parameters, infrasound, visualization, measuring system.

References

  1. Mukhamedova G.R. Harakteristiki otoakusticheskoj jemissii ulic, podvergajushhihsja vozdejstviju intensivnogo proizvodstvennogo shuma [Otoacoustic emission characteristics in individuals exposed to intense industrial noise]: PhD work. –Moscow: 2006. –16 p.
  2.  Kalinichenko M.V. Nekotorye aspekty problemy zagrjaznenija urbanizirovannyh territorij avtotransportom (na primere goroda Muroma)[Some aspects of the problem of pollution in urban areas motor vehicles (for example, the city of Murom)] // Jekologija i promyshlennost’ Rossii [Ecology and Industry of Russia], 2012, №12. – P.2-5.
  3. Solovjev L.P., Bulkin V.V., Sharapov R.V. Sushhestvovanie cheloveka v ramkah tehnosfery [The existence of man in the technosphere] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2012, № 1 (11). – P.31-39.
  4. Bulkin V.V., Bulkin A.V. Raspredelenie vetrovyh potokov v urbanizirovannom prostranstve kak jelement sistemy kon-trolja jekologicheskoj obstanovki [Distribution of wind flows in an urban space as an element of control environmental conditions] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2008, № 5. –P.14-20.
  5. Belyaev V.E., Bulkin V.V., Kirillov I.N. Operativnyj akustolokacionnyj monitoring prizemnogo sloja atmosfery [Operational monitoring acoustic location atmospheric boundary layer] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2010, № 7. –P.18-21.
  6. Report of the United Nations Conference on Environment and Development. Rio de Janeiro, 3-14 June 1992. Volume 1. http://www.un.org/ru/documents/ ods.asp?m=A/CONF.151/26/REV.1 (VOL.I)
  7. Impact of infrasound on the human body // Construction equipment. Weekly electronic publication. Issue 23. Article 4. http://www.mrmz.ru/article/v23/article4.htm
  8. Smit K. Principles of Applied Climatology.– McGraw-Hill Book Company (UK) Limited, London, 1975.
  9. Panova M.S., Bulkin V.V. O dostovernosti kontrolja sinopticheskih parametrov pri nalichii i otsutstvii vozmushhajushhih faktorov tehnogennogo haraktera [The reliability of the synoptic control parameters in the presence and absence of disturbing factors manmade] // Metody i ustrojstva peredachi i ob-rabotki informacii [Methods and the transmission and processing of information], 2010, № 1 (12). – P.38-40.
  10. Bulkin V.V., Grigorjuk E.N., Bulkin A.V. Analiz vozmozhnogo vlijanija raspredelenija vetrovyh potokov na harakter rasprostranenija zagrjaznjajushhih veshhestv v okrestnostjah Muroma [An analysis of the possible impact of the distribution of wind flows on the distribution of contaminants in the vicinity of Murom] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2012, № 2. –P.16-19.
  11. Bulkin V.V., Belyaev V.E., Kirillov I.N. Model’ passivno-aktivnoj akustolokacionnoj jekologo-meteo37.
  12. Ryazapov A.Z., Vasyuchkova E.I., Voronich S.S., Bagryantsev V.A., Slepchenko V.N., Lomakin G.V. Vozmozhnosti razvitija apparaturno-metodicheskogo obespechenija regional’noj sistemy jekologicheskogo monitoringa [Opportunities for the development of hardware and methodological support of the regional environmental monitoring system] // Jekologicheskie sistemy i pribory [Environmental Systems and Devices], № 7, 2012. –P.13-17.
  13. Pervushin R.V. Model’ izmeritel’noj radiometeorologicheskoj sistemy [Model radiometeorological measuring system] // Metody i ustrojstva peredachi i obrabotki informacii [Methods and the transmission and processing of information], 2009, № 11. –P.406-410.
  14. Bulkin V.V. Sovmeshhjonnye radiolokacionnye sistemy meteorologicheskogo naznachenija [Combined radar systems for meteorological purposes] // Radiotehnicheskie i telekommunikacionnye sistemy [Ra86.
  15. Demidenko A.G. Opyt primenenija GIS-tehnologij KB “Panorama” pri postroenii avtomatizirovannyh sistem monitoringa[Experience in the application of GIS technology KB “Panorama” in the construction of automated monitoring systems] // Inzhenernye izyskanija [Engineering surveys], 2009, № 10. – P.62-66.
  16. Sharapov R.V., Sharapova E.V., Tsvetnikov A.V. Geoinformacionnaja sistema edinogo jekologicheskogo monitoringa regiona [Geoinformation system of unified environmental monitoring region] // Valihanovskie chtenija-10: Sbornik materialov mezhdunarodnoj nauchno-prakticheskoj konferencii [Proceeding of Valihanov reeds 10]. Vol. 9. Kazakhstan, Kokshetau, 2005. – P.263-266.
  17. Solovjev L.P. Sovershenstvovanie sistemy monitoringa selitebnyh territorij naselennyh punktov jekologo-jekonomicheskih sistem [Improvement of monitoring residential areas of ecological and economic systems] // Mashinostroenie i bezopasnost’ zhiznedejatel’nosti [Engineering industry and life safety], 2013, № 2. –P.15-19.

«Engineering industry and life safety» №1 (19), 2014. Pages: 48-54

Download full text:Bulkin V.V., Solovjev L.P., Sharapov R.V., Pervushin R.V., Kirillov I.N. The problems of creating monitoring systems for acoustic noise pollution in residential areas

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Bulkin Vladislav Venediktovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: vvbulkin@mail.ru
Solovjev Lev Petrovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: solovjev47@mail.ru
Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru
Pervushin Radislav Valentinovich – Ph.D., Murom Institute of Vladimir State University. E-mail: prv@pochta.ru
Kirillov Ivan Nikolaevich – Graduate student, Murom Institute of Vladimir State University, Murom, Russia. E-mail: lwb@mivlgu.ru

5
Jul

Sharapov R.V. Conformity algorithm for exogenous processes monitoring data

Conformity algorithm for exogenous processes monitoring data

Sharapov R.V.

The paper deals with conformity of exogenous processes monitoring data obtained from different sources. To provide sharing data with different accuracy and measurement error, an algorithm for its conformity is present-ed. The algorithm involves bringing data to a single measurement unit. Data with varying accuracy is brought to single accuracy and order. Accuracy is determined by taking into account the measurement interval. For con-formal processing data, having different error, a three-item combination of «value, accuracy, measuring inter-val» is applied. Error value can significantly change the measurement data. For this reason, when calculating the trend lines (process dynamics) from various sources data, it is necessary to perform the estimation based on the three values rather than on a specific value.

Keywords: exogenous processes, monitoring, data, data processing, error, matching.

References

  1. Sharapov R.V.The transition from the technical to the natural-technical systems // Engineering industry and life safety, 2012, № 2. – P.43-46.
  2. Sharapov R.V. Monitoring exogenous processes // Engineering industry and life safety, 2012, № 2. – P.39-42.
  3. Sharapov R.V.Indicators for monitoring and assessment of karst processes // Engineering industry and life safety, 2013, № 1. – P.28-34.
  4. Sharapov R.V.On the conformity of monitoring data obtained from various sources// Engineering industry and life safety, 2013, № 4. – P.43-46.
  5. Sharapov R.V.Some problems of exogenous processes monitoring // Fundamental research, 2013, № 1-2. –P. 444-447.
  6. SharapovR.V., Sharapova E.V.The problem of integration of digital collections of the state of ecosystems // Engineering industry and life safety,2009, № 6. – P.75-78.
  7. Sharapov R.V. Determination of karst collapse intensity from incomplete data // Engineering industry and life safety, 2013, № 2. – P.36-40.

«Engineering industry and life safety» №4 (18), 2013. Pages: 47-49

Download full text:Sharapov R.V. Conformity algorithm for exogenous processes monitoring data

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

5
Jul

Sharapov R.V. On the conformity of monitoring data obtained from various sources

On the conformity of monitoring data obtained from various sources

Sharapov R.V.

The paper deals with the issues of processing data obtained from different sources. This data formats are different and can be received by means of different devices using various techniques. Furthermore, data may have different accuracy and measurement error. This complicates their sharing and can lead to significant errors. That is why, it is advisable to apply three-item combinations of «value, error, measurement interval», converting and bringing the combinations to common measurement units, if necessary, instead of using direct indicator readings taken from one source or another. This solution enables us to provide sufficient adequacy of data, collected from various sources, to the practical situation. In addition, the measurement error record enables us to assess the processes dynamics more accurately. So, you can filter value instability in the error zone and identify really significant changes.

Keywords: exogenous processes, monitoring, data, data processing, error, information source.

References

  1. Sharapov R.V. Monitoring exogenous processes // Engineering industry and life safety, 2012, № 2. – P.39-42.
  2. Sharapov R.V.The transition from the technical to the natural-technical systems // Engineering industry and life safety, 2012, № 2. – P.43-46.
  3. Dimakova N.A., Sharapov R.V. The problem of groundwater pollution // Modern high technologies, 2013, № 2. – P. 79-82.
  4. Sharapov R.V.Principles of groundwater monitoring // Engineering industry and life safety, 2012, № 3. – P.27-30.
  5. Sharapov R.V.The structure of the groundwater monitoring system// Engineering industry and life safety, 2012, № 4. – P.20-23.
  6. Sharapov R.V. The generalized structure of the groundwater monitoring system // 13 international multidisciplinary scientific geoconference SGEM2013. Water resources. Forest, marine and ocean ecosystems. Conference proceedings. 16-22 June 2013, Albena, Bulgaria, 2013. P. 389-392.
  7. Novitskiy P.V., Zograph I.A. Estimation of errors of measurement results. – Moskow: Energoatomizdat, 1990.
  8. Granovskiy V.A., Siraya T.N. Methods of experimental data processing. – Leningrad: Energoatomizdat, 1990.

«Engineering industry and life safety» №4 (18), 2013. Pages: 43-46

Download full text:Sharapov R.V. On the conformity of monitoring data obtained from various sources

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

19
Jan

Sharapov R.V. Indicators for monitoring and assessment of karst processes

Indicators for monitoring and assessment of karst processes

Sharapov R.V.

The paper presents a system of indicators used for monitoring and evaluation of karst processes. It details the quantitative indicators of the surface displays of karst processes, undersurface karst processes and underground hydrology displays. The indicators characterizing the undersurface forms of karst processes include the following: karst area infestation rate, karst form intensity rate, average frequency of karst formation, areal rate of karst area infestation , the average annual rate of karst area infestation, the volumetric rate of karst infestation, karst formation volume factor, an average annual expansion of karst area, the depth and the diameter of specific karst forms, indicator of the sinkholes depth, the rate of karst expansion size. The indicators characterizing the underground forms of karst processes are: the linear coefficient of internal karst formation, the linear coefficient of external karst formation, the linear coefficient of the total karst formation, the linear coefficient of surface karst formation, the abnormality coefficient, the linear density of karst cavities, the areal density of karst cavities, the volume density of karst cavities, karst processes activity rate, the total deposition of study area, the dissolution layer rate. The indicators characterizing the hydrological regime of the area involve the groundwater level, the rate of groundwater flow, the groundwater temperature, the chemical composition of groundwater, filtration rate of groundwater, fluctuations rate of karst springs flow rate, underground karst denudation, water saturation deficit of calcium sulfate, fluctuation rate of karst water mineralization, activity production of calcium and sulfate, calcium and carbonate, the leaching gradient.

Keywords: karst, karst processes, monitoring, karst surface forms, undersurface karst forms, groundwater.

References

  1. Bondarik G.K., Pendin V.V., Jarg L.A. Engineering Geodynamics – Moskow: KDU 2009. – 440 p.
  2. GOST R 22.1.06-99. «Safety in emergencies. Monitoring and forecasting of hazardous geological phenomena and processes. General requirements» – Moskow: 1999.
  3. Dubrovkin V.L. Karst study of new processes in seeking to track rail lines // Soviet Geology, 1948, № 35
  4. Kostarev V.P. The quantitative indicators of karst and their use in engineering-geological assessment of karst territories // Engineering and construction surveying, 1979, № 1.
  5. Makeev Z.A. The principles of engineering geological zoning of karst regions // Moscow Conference on Karst, vol. 4. – Molotov: Publication Molotov State University, 1948
  6. Maksimovic G.A. Karst basics. Volume 1. – Perm: Perm Book Publishing House, 1963.
  7. Guidelines on the organization and production of observation mode level, pressure and flow of groundwater. – M: VSEGINGEO, 1983.
  8.  Guidance on the production of observation mode, the temperature of groundwater. – M: VSEGINGEO, 1983.
  9. Problems of studying caverns mountain regions of the USSR. – Tashkent: Fan Uzbek SSR, 1983. – 150 p.
  10. Design, construction and operation of the roadbed in karst areas. – Moscow: Transport, 1968.
  11. Rodionov N.V. Engineering-geological studies in karst areas. – Moscow: Gosgeoltechizdat, 1958.
  12. Guidelines for geotechnical investigations in areas of karst. – Moscow: PNIIIS, 1995. – 167p.
  13. Sevarensky I.A. Engineering-geological assessment of karst phenomena in the area of Dzerzhinsk // Proceedings of the laboratory Giedre Geological Problems F.P. Savarensky, 1962, vol. 47.
  14. Tolmachev V.V. Engineering and building development of karst territories / V.V. Tolmachev, G.M. Troitsky, V.P. Homenko; Ed. E.A. Sorochana. – M. ​​Stroyizdat, 1986. – 176 p.
  15. Sharapov R.V. Monitoring exogenous processes // Engineering industry and life safety. 2012, № 2. – P.39-42.
  16. Sharapov R.V. Principles of groundwater monitoring // Engineering industry and life safety. 2012, № 3. – P.27-30.

«Engineering industry and life safety» №1 (15), 2013. Pages: 28-34

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

18
Jan

Sharapov R.V. Determination of karst collapse intensity from incomplete data

Determination of karst collapse intensity from incomplete data

Sharapov R.V.

The paper deals with the definition of karst collapse intensity. The technique for determining the intensity of karst formation and collapse on the basis of calculation and probabilistic method is given. In reality, karst col-lapse formation is affected by a great variety of natural and anthropogenic factors. Each factor can vary quite widely. Certain combinations of factors can cause karst process activation, while other combinations are not able to bring the natural system out of balance. The paper describes a technique for determining karst collapse intensity from incomplete data. It uses karst processes monitoring data in the area and monitoring data of areas with similar values of the most significant factors leading to the karst collapses.

Keywords: karst collapse intensity, karst, karst collapse.

References

  1. Makeev Z.A. The principles of engineering geological zoning of karst regions // Moscow Conference on Karst, vol. 4. – Molotov: Publication Molotov State University, 1948.
  2. Maksimovic G.A. Karst basics. Volume 1. – Perm: Perm Book Publishing House, 1963.
  3. Tolmachev V.V. Engineering and building development of karst territories / V.V. Tolmachev, G.M. Troitsky, V.P. Homenko; Ed. E.A. Sorochana. – Moscow: Stroyizdat, 1986. – 176 p.
  4. Tolmachev V.V. On the method of quantitative assessment of environmental factors affecting the formation of karst failures. Processing of MIIT, 1968, vol. 273.
  5. Sharapov R.V. Monitoring exogenous processes // Engineering industry and life safety, 2012, № 2. – P.39-42.
  6. Sharapov R.V.  Some of the application of new information technologies in the simulation of emergency situations // Engineering industry and life safety, 2008, № 5. – P.62-66.
  7. Sharapov R.V.  Some problems of exogenous processes monitoring // Fundamental research, 2013, № 1-2. – P. 444-447.
  8. Sharapov R.V. Review of approaches to modeling emergency situations // Engineering industry and life safety, 2012, № 1. – P.39-41.
  9. Sharapov R.V. Indicators for monitoring and assessment of karst processes // Engineering industry and life safety, 2013, № 1. – P.28-34.
  10. Sharapov R.V.Reflections on ecological and geological systems // Bulletin of the Tambov University. Series: Natural and Technical Sciences, 2013, Vol 18, № 3. – P. 918-922.
  11. Scheffe H. The analysis of variance – Moscow: Science, 1980. – 512 p.

«Engineering industry and life safety» №2 (16), 2013. Pages: 36-40

Download full text:Sharapov R.V. Determination of karst collapse intensity from incomplete data

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

16
Jan

Sharapov R.V. Microzoning Nizhny Novgorod NPP construction site Monakovo in terms of karst hazard based on insufficient data

Microzoning Nizhny Novgorod NPP construction site Monakovo in terms of karst hazard based on insufficient data

Sharapov R.V.

The paper deals with zoning in terms of karst hazard. An approach to zoning on incomplete data is based on computational-probabilistic technique. Indicator of karst failures intensity is used as the basis for assessing karst hazard. The above-mentioned approach is used for zoning the territory intended for the nuclear power plant construction at the site of Monakovo in Nizhny Novgorod region. Due to the fact that no proper observations have been done at the site lately, the indicators of karst failures intensity have been calculated with incomplete data (obtained mainly in the last few years). The index distribution of karst failures intensity in the area under study has been mapped. The map helps to visualize the karst danger area. The analysis shows that the area intended for the nuclear power plant construction at the site of Monakovo in Nizhny Novgorod region features an extremely high rate of karst danger.

Keywords: karst, karst failure, karst failures intensity, map, zoning.

References

  1. Makeev Z.A. The principles of engineering geological zoning of karst regions // Moscow Conference on Karst, vol. 4. – Molotov: Publication Molotov State University, 1948.
  2. Recommendations for conducting the engineering studies, design, construction and operation of buildings and structures on karst areas of the Nizhny Novgorod region. – Nizhny Novgorod, 2012. – 139 p.
  3. Manual of geotechnical investigations in karst areas. – Moscow: PNIIIS Russian Ministry of Construction, 1995.
  4. SP 11-105-97 «Engineering geological site investigations for construction». Part II «Work in the areas of hazardous geological and geotechnical processes».
  5. Tolmachev V.V. Engineering and building development of karst territories / V.V. Tolmachev, G.M. Troitsky, V.P. Homenko; Ed. E.A. Sorochan. – Moscow: Stroyizdat, 1986. – 176 p.
  6. Tolmachev V.V. On the method of quantitative assessment of environmental factors affecting the formation of karst failures. Processing of MIIT, 1968, vol. 273.
  7. Chervjakov V.A. The concept in the field of cartography. – Novosibirsk: Nauka, 1978. – 149 p.
  8. Sharapov R.V. Monitoring exogenous processes // Engineering industry and life safety, 2012, № 2. – P.39-42.
  9. Sharapov R.V. Some problems of exogenous processes monitoring // Fundamental research, 2013, № 1-2. – P. 444-447.
  10. Sharapov R.V. Indicators for monitoring and assessment of karst processes // Engineering industry and life safety, 2013, № 1. – P.28-34.
  11. Sharapov R.V. Determination of karst collapse intensity from incomplete data // Engineering industry and life safety, 2013, № 2. – P.36-40.
  12. Sharapov R.V., Kuzichkin O.R. Monitoring of Karst-Suffusion Formation in  Area of Nuclear Power Plant // Proceedings of the 7th 2013 IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 12-14 September 2013, Berlin, Germany. Vol. 2, 2013. – P. 810-813.

«Engineering industry and life safety» №3 (17), 2013. Pages: 37-41

Download full text:Sharapov R.V. Microzoning Nizhny Novgorod NPP construction site Monakovo in terms of karst hazard based on insufficient data

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Sharapov Ruslan Vladimirovich – Ph.D., Murom Institute of Vladimir State University, Murom, Russia. E-mail: info@vanta.ru

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