Optimization of the water chemistry of the primary coolant at nuclear power plants with VVÉR

Results of the use of automatic hydrogen-content meter for controlling the parameter of hydrogen in the primary coolant circuit of the Kola nuclear power plant are presented. It is shown that the correlation between the hydrogen parameter in the coolant and the hydrazine parameter in the makeup water can be used for controlling the water chemistry of the primary coolant system, which should make it possible to optimize the water chemistry at different power levelsTranslated from Élektricheskie Stantsii, No. 12, December 2004, pp. 31 – 33.     

Spectral Reflectance,Growth and Chlorophyll Relationships for Rice Crop in a Semi-Arid Region of India

Relations among spectral reflectance, chlorophyll a, and growth of rice plants grown on irrigated light textured soil in a semi arid region are presented here. There was a linear relation between spectral reflectance and rice plant height (r = 0.97), for band 1 (0.45–0.52 m) reflectance values. On the other hand, in bands 2 (0.52–0.60 m) and 3 (0.63–0.69 m), reflectance values decreased until 70 days after planting (DAP) and then increased during the reproductive phase of the crop. The near infrared band 4 (0.76–0.90 m) showed a maximum reflectance at 59 DAP (panicle initiation stage) and a decline in reflectance thereafter through maturity. The peak value of IR/R ratio was 16.39 at 62 DAP during the early reproductive phase; thereafter, it declines gradually with the maturity of the crop. Chlorophyll a concentration was high during early growth (vegetative and early reproductive stages) and decreased during the flowering and maturity stages. The rice plant canopy show a high chlorophyll a concentration at 64 and 59 DAP for sites A and B, respectively. Chlorophyll a concentration is higher in site A plant canopies than it is in site B during the entire crop cycle. A good inverse correlation (r = 0.91) has been found between chlorophyll a and band 1, while the IR/R ratio and the normalised difference vegetation index (NDVI) showed a relationship (r = 0.78) with the chlorophyll a concentration during the crop cycle. Band 2, 3 and 4 radiance values show a biphasic linear relationship with chlorophyll a concentrations, negative for early growth and positive for flowering and maturity stages. Results indicate that the period between 66 to 70 DAP is most suitable for the assessment of rice crop yield, based on chlorophyll a concentration.     

Pre-posterior analysis as a tool for data evaluation: Application to aquifer contamination

This paper deals with the frequently encountered problem of pre-posterior data evaluation, i.e., assessment of the value of data before they become available. The role of data is to reduced the risk associated with decisions taken under conditions of uncertainty. However, while the inclusion of relevant data reduces risk, data acquisition involves cost, and there is thus an optimal level beyond which any addition of data has a negative net benefit. The Bayesian approach is applied to construct a method for updating decisions and evaluating the anticipated reduction in risk following consideration of additional data. The methodology is demonstrated on a problem of management of an aquifer under threat of contamination.Notation L matrix of losses for all combinations of states and decisions - l, m, h possible salinity levels from the proposed borehole - N, M, F possible decisions - P(·) vector of prior probabilities of states - P(.|l), P(.|m), P(.|h) conditional (updated) probability vectors of the different states given the salinity levels - P(.|), P(.|), P(.|) probability vectors of the different salinity levels given the true states (likelihood function) - P(l), P(m), P(h) probabilities of the salinity levels, irrespective of the true state - R(.|l), R(.|m), R(.|h) posterior risk vectors of the different decisions given the salinity levels - R(N), R(M), R(F) prior risk associated with different decisions - , , possible true states     

Determining Hydraulic Characteristics of Production Wells using Genetic Algorithm

Proper well management requires the determination of characteristic hydraulic parameters of production wells such as well loss coefficient (C) and aquifer loss coefficient (B), which are conventionally determined by the graphical analysis ofstep-drawdowntest data. However, in the present study, the efficacy of a non-conventional optimization technique called Genetic Algorithm (GA), which ensures near-optimal or optimal solutions, is assessedin determining well parameters from step-drawdown test data. Computer programs were developed to optimize the well parametersby GA technique for two cases: (i) optimization of B and C only, and (ii) optimization of B, C and p (exponent) as well as to evaluate the well condition. The reliability and robustness of the developed computer programs were tested usingnine sets of published and unpublished step-drawdown data from varying hydrogeologic conditions. The well parameters obtained by the GA technique were compared with those obtained by the conventional graphical method in terms of root mean square error(RMSE) and visual inspection. It was revealed that the GA technique yielded more reliable well parameters with significantlylow values of RMSE for almost all the datasets, especially in caseof three-variable optimization. The optimal values of the parametersB, C and p for the nine datasets were found to range from 0.382 to 2.292 min m^-2, 0.091 to 3.262, and 1.8 to 3.6, respectively. Because of a wide variation of p, the GA techniqueresulted in considerably different but dependable and robust well parameters as well as well specific capacity and well efficiency compared to the graphical method. The condition of three wells was found to be good, one well bad and that of the remaining five wells satisfactory. The performance evaluation of the developed GA code indicated that a proper selection of generation number and population size is essential to ensure efficient optimization. Furthermore,a sensitivity analysis of the obtained optimal parameters demonstrated that the GA technique resulted in a unique set ofthe parameters for all the nine datasets. It is concluded thatthe GA technique is an effective and reliable numerical tool for determining the characteristic hydraulic parameters of production wells.     

An Aquifer Management Case Study – The Chalk of the English South Downs

The Chalk aquifer of the English South Downs is very heavily utilised. The groundwater resources have enjoyed a formal programme of management which started in the 1950s, although a number of actions had been taken earlier in order to deal with saline intrusion and potential risk to groundwater quality from urbanisation. In the late 1950s the policy of leakage/storage boreholes was first adopted, whereby the leakage boreholes along the coast were pumped in winter to intercept fresh water discharge to the sea and to maximise the recharge potential inland, and inland storage boreholes were used, as much as possible, in the summer months only. A comprehensive monitoring programme supported by aquifer modelling has enabled a gradual increase in overall abstraction to take place without increasing groundwater degradation due to saline intrusion. There have been various pollution prevention strategies over the years, and these have been effective in protecting the groundwater despite the high population density and widespread agricultural activity within the South Downs. The management of the aquifer has clearly been successful; there are many lessons from this experience that can be applied to other regions and other aquifers.     

Use of parameter estimation in determining soil hydraulic properties from unsaturated transient flow

This paper proposes a model for determining the parameters given by the closed-form equations of van Genuchten. An objective function is made by the observed data from vertical drainage, and the solutions of optimization show that less computation and more accurate estimates are made as head profiles are taken into account rather than cumulative drainage. Sensitivity analysis of the error vector to parameters interprets this reason. The convergence and stability of solutions are evaluated with different magnitudes of measured errors in the head, and the results show good estimates will be obtained if a sufficient pressure head at the soil bottom is applied. A variable _k is introduced to avoid the estimations of and n being affected by the uncertainties of Ks and _s .     

Water Drainage in Layered Soils. Laboratory Experiments and Numerical Simulation

Experimental results during first and second drainage in a vertical column of saturated layered soil were compared to those predicted from simulation. The sample was composed of a sandyloam soil overlying a fine sand. The soil water content was measured by using -ray absorption method (²⁴¹Am) and the water pressure through tensiometers, arranged vertically along the column and connected to pressure transducers. From the evaluation of moisture and pressure versus time, the characteristic curves () of the layers were obtained and approximated by van Genuchten's analytical equation. The relationship K() between hydraulic conductivity and moisture was estimated by van Genuchten's prediction model. () and K() equations were used as inputs in the numerical model. The drainage of water was simulated by Richard's partial differential equation, which was solved with the finite differences computational scheme type Laasonen. The upper and lower boundary conditions were zero flux and a periodically changing head respectively. Numerical results show a good agreement with experimental data, with small deviations for certain hours.     

Forecast model of water consumption for Naples

The data refer to the monthly water consumption in the Neapolitan area over more than a 30 year period. The model proposed makes it possible to separate the trend in the water consumption time series from the seasonal fluctuation characterized by monthly peak coefficients with residual component. An ARMA (1,1) model has been used to fit the residual component process. Furthermore, the availability of daily water consumption data for a three-year period allows the calculation of the daily peak coefficients for each month, and makes it possible to determine future water demand on the day of peak water consumption.Notation j numerical order of the month in the year - i numerical order of the year in the time series - t numerical order of the month in the time series - h numerical order of the month in the sequence of measured and predicted consumption values after the final stage t of the observation period - Z _ji effective monthly water consumption in the month j in the year i (expressed as m³/day) - T _ji predicted monthly water consumption in the month j in the year i minus the seasonal and stochastic component (expressed as m³/day) - C _ji monthly peak coefficient - E _ji stochastic component of the monthly water consumption in the month of j in the year i - Z _i water consumption in the year i (expressed as m³/year) - Z _j (t) water consumption in the month j during the observation period (expressed as m³/day) - evaluation of the correlation coefficient - Z _j (t) water consumption in the month j during the observation period minus the trend - Y _t transformed stochastic component from E _t : Y _t =ln Et - Y _t+h measured value of stochastic component for t+h period after the final stage t of the observation period - Y _t (h) predicted value of stochastic component for t+h period after the final stage t of the observation period - _j transformation coefficients from the ARMA process (m, n) to the MA () process     

Errors of kinematic-wave and diffusion-wave approximations for time-independent flows

Time-independent (or steady-state) cases of planar (overland) flow were treated. Errors of the kinematic-wave and diffusion-wave approximations were derived for three types of boundary conditions: zero flow at the upstream end, and critical flow depth and zero depth-gradient at the downstream end. The diffusion wave approximation was found to be in excellent agreement with the dynamic wave approximation, with error in the range of 1–2% for values ofKF ₀ ² (7.5). Even for small values ofKF ₂ ⁰ (e.g.,KF ₂ ⁰ =0.75), the errors were typically in the range of 11–15%. The accuracy of the diffusion wave approximation was greatly influenced by the downstream boundary condition. The error of the kinematic wave approximation was found to vary from 7 to 13% in the regions 0.05x0.95 forKF ₀ ² =0.75 and was greater than 30% forKF ₀ ² =0.75.     

A real-time flood forecasting model based on maximum-entropy spectral analysis: I. Development

This paper, the first of two, develops a real-time flood forecasting model using Burg's maximum-entropy spectral analysis (MESA). Fundamental to MESA is the extension of autocovariance and cross-covariance matrices describing the correlations within and between rainfall and runoff series. These matrices are used to derive the model forecasting equations (with and without feedback). The model may be potentially applicable to any pair of correlated hydrologic processes.Notation a _k extension coefficient of the model atkth step - B _k backward extension matrix forkth step - B _ijk element of the matrixB _k (i,j=1, 2) - c _k coefficient of the entropy model atkth step in the LB algorithm - e _k (e _x ,e _y )k = forecast error vector atkth step - E _k error matrix atkth step - E _ijk element of theE _k (i,j=1, 2) - f frequency - F _k forward extension matrix atkth step - F _ijk element of theF _k matrix (i,j=1, 2) - H(f) entropy expressed in terms of frequency - H _X entropy of the rainfall process (X) - H _Y entropy of the runoff process (Y) - H _XY entropy of the rainfall-runoff process - I identity matrix - forecast lead time - m model order, number of autocorrelations - R correlation matrix - S _x standard deviation of the rainfall data - S _y standard deviation of the runoff data - t time - T ₁ rainfall record - T ₂ runoff record - T rainfall-runoff record (T=T ₁ T ₂) - x _t rainfall data (depth) - X X() = rainfall process - mean of the rainfall data - y _t direct runoff data (discharge) - Y Y() = runoff process - mean of the runoff data - (x, y) _t rainfall-runoff data (att T) - (x, y, z) _t rainfall-runoff-sediment yield data (att T) - z complex number (in spectral analysis) - _k coefficient of the LB algorithm atkth step - _nj Lagrange multiplier atjth location in the _n matrix - _{n n} = matrix of the Lagrange multiplier atkth step - _X (k), _Y (k) autocorrelation function of rainfall and runoff processes atkth lag - _XY (k) cross-correlation function of rainfall and runoff processes atkth lag - W ₁(f) power spectrum of rainfall or runoff - W ₂(f) cross-spectrum of rainfall or runoff Abbreviations acf autocorrelation function - ARMA autoregressive moving average (model) - ARMAX ARMA with exogenous input - ccf cross-correlation function - det() determinant of the (...) matrix - E[...] expectation of [...] - FLT forecast lead time - KF Kalman filter - LB Levinson-Burg (algorithm) - MESA maximum entropy spectral analysis - MSE mean square error - SS state-space (model) - STI sampling time interval - forecast ofx - forecast ofx -step ahead - x _F feedback ofx-value (real value) - |x| module (absolute value) ofx - X ^–1 inverse of the matrixX - X* transpose of the matrixX     

Balance of the rotors of hydroelectric generators

Conclusions The described method of finding the heavy point of a turbine rotor permits balancing without the use of complex apparatus and cumbersome graphic plots; the plane of imbalance is determined with sufficient accuracy during one start.Translated from Gidrotekhnicheskoe Stroitel'stvo, No. 9, pp. 54–55, September, 1981.     

Intangible Flood Damage Quantification

Flooding is a natural disaster that may cause tremendous tangibleand intangible damage to the national economy. The tangible damage assessment, i.e. the monetary value of all direct and indirect physical damages, has already been studied, whileintangible damages have not yet been taken into account. Thisarticle, therefore, is the first systematic attempt to assess bothtangible and intangible damages. The new proposed Anxiety-Productivity and Income Interrelationgship Approach (API) has been developed to quantify the intangible damage in monetary terms. The Bangkok area has been selected as the research area because several severe flood events have occurredthere over the last two decades. The 1983 Bangkok flood caused 6600 million baht in damage, according to estimates by the National Statistical Office (NSO). This article examines the totalflood damage (including the intangible damage) at different flood magnitudes. Case studies with and without flood mitigation projects are studied and compared. Furthermore, thisarticle also discusses the improvements over the conventional approach offered by the new API methodology.     

Determination of optimal unit hydrographs by linear programming

A unit hydrograph (UH) obtained from past storms can be used to predict a direct runoff hydrograph (DRH) based on the effective rainfall hyetograph (ERH) of a new storm. The objective functions in commonly used linear programming (LP) formulations for obtaining an optimal UH are (1) minimizing the sum of absolute deviations (MSAD) and (2) minimizing the largest absolute deviation (MLAD). This paper proposes two alternative LP formulations for obtaining an optimal UH, namely, (1) minimizing the weighted sum of absolute deviations (MWSAD) and (2) minimizing the range of deviations (MRNG). In this paper the predicted DRHs as well as the regenerated DRHs by using the UHs obtained from different LP formulations were compared using a statistical cross-validation technique. The golden section search method was used to determine the optimal weights for the model of MWSAD. The numerical results show that the UH by MRNG is better than that by MLAD in regenerating and predicting DRHs. It is also found that the model MWSAD with a properly selected weighing function would produce a UH that is better in predicting the DRHs than the commonly used MSAD.Notations M number of effective rainfall increments - N number of direct runoff hydrograph ordinates - R number of storms - MSAD minimize sum of absolute deviation - MWSAD minimize weighted sum of absolute deviation - MLAD minimize the largest absolute deviation - MRNG minimize the range of deviation - RMSE root mean square error - P _m effective rainfall in time interval [(m–1)t,mt] - Q _n direct runoff at discrete timent - U _k unit hydrograph ordinate at discrete timekt - W _n weight assigned to error associated with estimatingQ _n - _n ⁺ error associated with over-estimation ofQ _n - _n ^– error associated with under-estimation ofQ _n - _max ⁺ maximum positive error in fitting direct runoff hydrograph - _max ^– maximum negative error in fitting direct runoff hydrograph - _max largest absolute error in fitting obtained direct runoff - E _r,1 thelth error criterion measuring the fit between the observed DRHs and the predicted (or reproduced) DRHs for therth storm - E ₁ averaged value of error criterion overR storms     

Experience of the “Élektrosila” Joint-Stock Company in Reconstruction and Updating of Hydroelectric Generators

The experience and potential of the Élektrosila plant in updating hydrogenerators is described. The volume of the reconstruction, its goals and approaches are presented.     

A new analytical model to predict the hydraulic conductivity of unsaturated soils

A new analytical model is presented for the prediction of hydraulic conductivity. The new model is based on the Brutsaert characteristic curve () and the Mualem integral relation. It is presented by a series expansion of the effective saturation () power and given in a simple algebraic relation. For checking the new model, twelve soils were selected from the available literature and a comparison was made between the new model, the experimental curve and the van Genuchten model as well. The suggested model is very close to the van Genuchten model in all cases except one and it exhibits hysteresis, due to the different values of the parameter b of Brutsaert equation for the wetting and drainage curves. Also a second model is presented, based on the Burdine integral relation.     

Time-dependent soil-water distribution under a circular trickle source

Soil-water distribution in homogeneous soil profiles of Yolo clay loam and Yolo sand (Typic xerorthents) irrigated from a circular source of water, was measured several times after the initiation of irrigation. The effect of trickle discharge rates and soil type on the locations of the wetting front and soil-water distribution was considered. Soil-water tension and hydraulic conductivity, as functions of soil-water content, were also measured. The theories of time-dependent, linearized infiltration from a circular source and a finite-element solution of the two-dimensional transient soil-water equation were compared with the experimental results. In general, for both soils the computer horizontal and vertical advances of the wetting front were closely related to those observed. With both theories, a better prediction of the wetting front position for the clay loam soil than for the sandy soil is shown. The calculated and measured horizontal vertical advances did not agree over long periods of time. With the linearized solution, overestimated and underestimated vertical advances for the clay and sandy soils, respectively, were shown. The finite-element model approximate in a better way the vertical advances than the linearized solution, while an opposite tendency for the horizontal advances indicated, especially in sandy soil.Notation k constant (dK/d) - K hydraulic conductivity - K ₀ saturated hydraulic conductivity - J ₀,J ₁ Bessel functions of the first kind - h soil water tension - q Q/r ₀ ² - Q discharge rate - r cylindrical coordinate; also horizontal distance in soil surface - R dimensionless quantity forr - r ₀ constant pond radius - R ₀ dimensionless quantity forr ₀ - t time - T dimensionless quantity fort - x, y Cartesian coordinates - z vertical coordinate; also vertical distance along thez axis chosen positively downward - Z dimensionless quantity forz - empirical soil characteristic constant - dummy variable of integration - volumetric soil water content - matrix flux potential - dimensionless quantity for      

Efficient steam turbines produced by the “Ural Turbine Plant” company

Design features and efficiency of some steam turbines produced at present by a plant formed as a result of division of the Turbine Motor Plant Company into several enterprises are presented.Translated from Élektricheskie Stantsii, No. 11, November 2004, pp. 27 – 32.     

Specifics of reconstruction and expansion of Niva HPP-2 hydroelectric plant

The practice of reconstructing and expanding a functioning hydrosystem in the Far North is discussed.Translated from Gidrotekhnicheskoe Stroitelstvo, No. 8, August 2004, pp. 3–7.     

Estimation of the Technical Condition of Overhead Transmission Lines After 30 Years of Operation

Results of an inspection of 220-kV overhead transmission lines (OTL) in the Cherepovets network of the Vologdaénergo Company performed with the use of specially developed Methodological recommendations for estimation of the technical condition of 35 – 750-kV OTL after long-term operation are discussed. The reliability margin of poles and footings is determined by calculation of actual loads on unified structures. Conductor sizes are evaluated in all spans and the distribution of out-of-size places over the OTL route is determined without resorting to expensive geodetic surveys. Two ways for solving the problem of further safe operation of the studied OTL are suggested, namely, traditional (restoration of appropriate clearances to earth by heaving the conductor or erecting new poles) and alternative (determination of the latent margin contained in the Rules for design of electric installations, allowance for the actual current load on the line and the true size of farm equipment used over the route, etc.) ones. It is recommended to find individual solutions to problems arising in OTL after long-term service.