Материал: Russian Journal of Building Construction and Architecture

2.Mel'kumov V. N., Kuznetsov S. N., Pavlyukov S. P., Cheremisin A. V. Nestatsionarnoe pole kontsentratsiy prirodnogo gaza v skvazhine pri ego utechke iz podzemnogo gazoprovoda [Nonstationary field of concentration of natural gas in the well in a leakage of underground pipeline]. Privolzhskiy nauchnyy zhurnal, 2008, no. 4, pp. 98––103.

3.Mel'kumov V. N., Kuznetsov I. S., Guseva L. Yu., Cheremisin A. V. Otsenka akkumuliruyushchey sposobnosti ventiliruemykh ob"emov dlya snizheniya trebuemogo vozdukhoobmena v pomeshcheniyakh [Evaluation of the accumulating capacity of the vented volume to reduce the required air exchange in premises].

Vestnik Voronezh. gos. tekhn. un-ta, 2007, vol. 3, no. 1, pp. 205––207.

4.Mel'kumov V. N., Kuznetsov S. N., Pavlyukov S. P., Kuznetsov R. N. Formirovanie kon-vektivnykh vozdushnykh potokov pri deystvii v pomeshchenii istochnika tepla [Formation of convective air flow under the action of indoor heat source]. Vestnik Volgograd. gos. arkh.-stroit. un-ta. Stroitel'stvo i arkhitektura, 2008, no. 12, pp. 76––80.

5.El'terman V. M. Ventilyatsiya khimicheskikh proizvodstv [Ventilation of chemical plants]. Moscow, Khimiya Publ., 1980. 284 p.

6.Mel'kumov V. N., Kuznetsov S. N. Dinamika formirovaniya vozdushnykh potokov i poley temperatur v pomeshchenii [Dynamics of formation of air streams and temperatures fields in premise]. Nauchnyy vestnik Voronezhskogo GASU. Stroitel'stvo i arkhitektura, 2008, no. 4, pp. 172––178.

7.Mel'kumov V. N., Kuznetsov S. N. Vzaimodeystvie ventilyatsionnykh vozdushnykh potokov s konvektivnymi potokami ot istochnikov teploty [The interaction of ventilation air flows with convection flows from heat sources]. Izvestiya vuzov. Stroitel'stvo, 2009, no. 1, pp. 63––70.

8.Kuznetsov S. N., Sklyarov K. A., Cheremisin A. V. Modelirovanie rasprostraneniya vrednykh veshchestv v smezhnykh pomeshcheniyakh [Modelling of distribution of harmful substances in the adjacent rooms].

Nauchnyy vestnik Voronezhskogo GASU. Stroitel'stvo i arkhitektura, 2008, no. 1, pp. 108––112.

9.Mel'kumov V. N., Kuznetsov S. N., Pavlyukov S. P., Cheremisin A. V. Prognozirovanie fil'tratsii gaza v grunte pri ego utechke iz podzemnogo gazoprovoda [Prediction of gas filtration in the soil when it leaks from an underground pipeline]. Izvestiya OrelGTU. Stroitel'stvo. Transport, 2008, no. 3/19(549), pp. 61––65.

10.Mel'kumov V. N., Kuznetsov S. N., Gulak V. V. Modelirovanie zadymlennosti pomeshcheniy slozhnoy konfiguratsii v nachal'noy stadii pozhara [Modeling of smoke content of premises of complex configuration at initial stage of fire]. Nauchnyy vestnik Voronezhskogo GASU. Stroitel'stvo i arkhitektura, 2010, no. 3(19), pp. 131––138.

11.Loboda A. V., Kuznetsov S. N. Ispol'zovanie metoda konformnykh otobrazheniy dlya opredeleniya poley skorostey vozdushnykh potokov v zadachakh ventilyatsii [Using the method of conformal mappings to determine velocity fields of air flows in ventilation tasks]. Nauchnyy vestnik Voronezhskogo GASU. Stroitel'stvo i arkhitektura, 2011, no. 1(21), pp. 15––22.

12.Pavlyukov S. P., Kuznetsova G. A., Kobelev A. N. Analiz sostava i prodolzhitel'nosti ekspluatatsii gazovogo oborudovaniya [Analysis of the composition and duration of operation of gas equipment]. Inzhenernye sistemy i sooruzheniya, 2012, no. 3(8), pp. 16––23.

13.Kuznetsov S. N., Kuznetsova G. A., Mkrtchyan A. G. Sostavlenie kart vliyayushchikh faktorov pri opredelenii optimal'noy trassy avtomobil'noy dorogi [Mapping the influencing factors when determining the optimal route of the road]. Inzhenernye sistemy i sooruzheniya, 2014, no. 4(17), pp. 202––206.

21

Russian journal of building construction and architecture

14.Kuznetsov I. S., Kuznetsova G. A., Mkrtchyan A. G. Integrirovannye karty vliyayushchikh faktorov dlya vybora optimal'noy trassy avtomobil'noy dorogi [Integrated maps of influencing factors to select the optimal route of the road]. Inzhenernye sistemy i sooruzheniya, 2014, no. 2(15), pp. 67––72.

15.Kuznetsov I. S., Kuznetsova G. A., Mkrtchyan A. G. Algoritmy poiska optimal'noy trassy prokladki avtomobil'noy dorogi [Algorithms for finding the optimal way of laying of roads]. Inzhenernye sistemy i sooruzheniya, 2014, no. 2(15), pp. 73––79.

16.Chow W. K., C. L. Chow, S. S. Li Simulating smoke filling in big halls by computational fluid dynamics. Modelling and Simulation in Engineering, 2011, Article ID 781252, 16 p.

17.Shu K., Huang Y., Zhang S. Reasonable layout and numerical simulation of compound ventilation mode in power transformer room, Building Energy Efficiency, 2010, vol. 38, no. 1, pp. 34––38.

18.Juan C. R., Beiza M., Jon G., Rivas A., Raúl A., Larraona G. S., Miguel I. de. Numerical modeling of the natural ventilation of underground transformer substations, Applied Thermal Engineering, 2013, vol. 51, no. 1–– 2, pp. 852––863.

19.Cox G., Kumar S. Modelling enclosure fires using CFD, in SFPE Handbook of Fire Protection Engineering, pp. 3-194–3-218, Natl Fire Protection Assn, Quincy, Mass, USA, 4th edition, 2008.

20.J. Ratnieks, A. Jakovičs, Gendelis S. Mathematical modelling of airflow velocity and temperature fields for experimental test houses. Proceedings of the 10th Nordic Symposium on Building Physics, 15––19 June 2014. Lund, Sweden, pp. 871––878.

21.Seredin P. V., Glotov A. V., Ternovaya V. E., etc. Spinodal decomposition of Ga (x) In1-x As (y) P1-y quaternary alloys. SEMICONDUCTORS, 2011, vol. 45, iss. 11, pp. 1433––1440.

22

UDC(519.9 + 518.5) : 532.54

M. Ya. Panov1, G. N. Martynenko2, A. I. Kolosov3

PROMPT MANAGEMENT ON THE BASIS OF THE DISTURBED STATE

OF THE URBAN GAS SUPPLY SYSTEM

Voronezh State Technical University

Russia, Voronezh, tel.: +7-900-304-62-51, e-mail: glen2009@mail.ru

1D. Sc. in Engineering, Prof. of the Dept. of Heat and Gas Supply and Oil and Gas Business 2PhD in Engineering, Assoc. Prof. of the Dept. of Heat and Gas Supply and Oil and Gas Business 3PhD in Engineering, Assoc. Prof. of the Dept. of Heat and Gas Supply and Oil and Gas Business

Statement of the problem. The problem of the regulation of gas flows in urban gas distribution systems by managing them promptly is addressed.

Results. A complete mathematical model is developed of the disturbed state of a distribution gas supply system in the field of a reverse analysis which formalizes the synthesis of the throttle characteristics of the system and includes a model of the disturbed system state and the system of normal equations. Based on the synthesized throttle characteristics the algorithm was proposed of a preliminary and accurate forecast of consumption in the system.

Conclusions. The throttle characteristics of the system obtained by means of modelling are the basis of forecasts of gas consumption of domestic, municipal and industrial consumers on the basis of the principles of energy reduction.

Keywords: gas supply, operational management, analysis of flow distribution.

Introduction

The state of a gas supply system can be determined using a vector of state parameters Z that includes the dependent Y and independent X variables.

Y contains the following:

––a vector of the expenses of the environment in the areas Q with the components Qi(i {I} is a total number of areas in the system);

––a vector of node pressures Р with the components Pj(j {J} is a total number of nodes);

–– a vector Pj (j {Jн} is a total number of energy nodes (EN) with a fixed node pressure);

© Panov М. Ya., Маrtynenko G. N., Kolosov А. I., 2017

23

Russian journal of building construction and architecture

–– a vector of a node supply (inflow) q with the components qj (j {Jq} is a total number of EN with a fixed node supply (inflow) including a zero supply, {Jн Jq} {Jz} where {Jz} is a total number of EN);

–– a vector S with the components Si (i {ID} is a total number of areas with throttle elements, Si is a coefficient of hydraulic resistance).

A variable X contains the following:

–– a vector S with components Si(i {IS}is a total number of areas including those with throttles, {JS JD} {J});

–– vectors D, L with components Di, Li (diameters and lengths of main pipes) i {I}, etc. The components of the vector X is included in what is called a single-valuedness condition [2—6, 11, 13]. In order to identify the initial vector Y a model of flow distribution is essential

U(Z) U(Y,X) 0.

1. Designing a flow distribution model based on the excited state of a gas supply system.

A flow distribution model [1, 2] is depicted using a ninary structural graph in its excited state containing the specified area and users’ subsystems. Modelling management in the system is suggested to be conducted using predictions of gas supply levels. The reverse analysis is a synthesis of throttle characteristics. It is designed using a square matrix МВС with unknown values Si, (i {ID}). In order to determine Si, (i {ID}), it is necessary to specify how a target product is consumed, in particular gas [14—21]. This makes it imperative to identify linearly independent connections that are excessive in relation to those form the structure of a model of the excited state of a system. The model of the excited state is obtained as a result of variation which uses the principle of least action for a gas supply network [2, 5, 8, 10, 12], i.e. there is always a clear-cut connection between the vectors Y and X. An extra connection is found in early regression analysis [5, 6, 7] which is determined using the method of least squares (MLS).

A gas distribution system has different complex interior connections [3]. The configuration of MLS for a gas supply system is adjusted to the energy and mass exchange with the environment using a set Jz of energy nodes. There is no question of the original information as it does not have to do with measuring devices and their errors, i.e. such independent variables as previously specified values of the expenses of fictional lines (Qjfa , j {Jн}) are values changing in time and influenced by subjective factors.

It is known that MLS is designed using minimization of the residual function F, here for a set Jн of the components of the vectors Р and Q that are connected with a dependence by means

24

of the Bernoulli’s equation. Considering that, let us present an objective function for a hydraulic system based on the method of least squares:

where Qjfa ,Qjf are previouslyspecified and actual values of the gas expenses through a fictional area j; is the Lagrange multiplier; J , J is a set of sources and outflows of a gas distri-

bution system respectively. The second group of summands (1) confirms the hydraulics theory which runs that F should be identified as part of the continuity conditions of the environment. Asystemof normalpressuresisdesigned usingthe minimum conditionsof an objective function:

The actual expenses Qjf are not independent within previous prediction as they are connected with a flow distribution model.

The exclusion results in a system of normal equations that meet the condition

According to (2), (3), the specific number of extra independent connections per unit is less than of energy node flows, i.e. Jн – 1.

2. Synthesis of throttle characteristics of a gas distribution system. A complete mathematical model of the excited state of a gas distribution system in the range of reverse analysis that formalizes the synthesis of the throttle characteristics of the system and includes МВС [2, 4] and the system of normal equations are in the matrix form below:

25