Wyniki wyszukiwania - BazTech

1

Uncertainty analysis of operational conditions in selective artificial ground freezing applications

Zueter Ahmad, Akhtar Saad, Sasmito Agus

Journal of Sustainable Mining

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2022

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Vol. 21, iss. 3

169--179

EN

Artificial ground freezing (AGF) systems are susceptible to uncertain parameters highly affecting their performance. Particularly, selective artificial ground freezing (S-AGF) systems involve several uncertain operational conditions. In this study, uncertainty analysis is conducted to investigate four operational parameters: 1) coolant inlet temperature, 2) coolant flow rate, 3) pipes emissivity, and 4) pipes eccentricity. A reduced-order model developed and validated in our previous work for field-scale applications is exploited to simulate a total of 5,000 cases. The uncertain operational parameters are set according to Monte Carlo analysis based on field observations of a field-scale freeze-pipe in the mining industry extending to 460 m below the ground surface. The results indicate that the freezing time can range between 270 and 350 days with an average of 310 days, whereas the cooling load per one freeze-pipe ranges from 90 to 160 MWh, with an average of 129 MWh. Furthermore, it is observed that the freezing time and energy consumed are mostly dominated by the coolant inlet temperature, while energy dissipated in the passive zone (where ground freezing is not needed) is mostly affected by pipes emissivity. Overall, the conclusions of this study provide useful estimations for engineers and practitioners in the AGF industry.

2

Prediction of mineral product price based on mean reversion model

Huang Shuwei, Ma Zhaoyang, Jin Feng, Zhang Yuansheng

Gospodarka Surowcami Mineralnymi

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2022

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T. 38, z. 2

61--75

EN

The mean-reversion model is introduced into the study of mineral product price prediction. The gold price data from January 2018 to December 2021 are selected, and a mean-reverting stochastic process simulation of the gold price was carried out using Monte Carlo simulation (MCS) method. By comparing the statistical results and trend curves of the mean-reversion (MR) model, geometric Brownian motion (GBM) model, time series model and actual price, it is proved that the mean-reversion process is valid in describing the price fluctuation of mineral product. At the same time, by comparing with the traditional prediction methods, the mean-reversion model can quantitatively assess the uncertainty of the predicted price through a set of equal probability stochastic simulation results, so as to provide data support and decision-making basis for the risk analysis of future economy.

PL

W badaniach predykcji cen produktów mineralnych wprowadzono model średniej rewersji. Wybrano dane dotyczące cen złota od stycznia 2018 do grudnia 2021 r., a symulację ceny złota w procesie odwracania średniej przeprowadzono metodą symulacji Monte Carlo (MCS). Porównując wyniki statystyczne i krzywe trendu modelu średniej rewersji (MR), modelu geometrycznego ruchu Browna (GBM), modelu szeregów czasowych i rzeczywistej ceny, udowodniono, że proces średniej rewersji jest prawidłowy w opisie fluktuacji cen na produkt mineralny. Jednocześnie, porównując z tradycyjnymi metodami predykcji, model średniej rewersji może ilościowo oszacować niepewność przewidywanej ceny za pomocą zestawu wyników symulacji stochastycznej równego prawdopodobieństwa, w celu zapewnienia wsparcia danych i podstawy decyzyjnej do analizy ryzyka przyszłej gospodarki.

3

Intelligent velocity picking and uncertainty analysis based on the Gaussian mixture model

Wang Xiaowei, Gao Yang, Chen Chang, Yuan Huan, Yuan Sanyi

Acta Geophysica

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2022

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Vol. 70, no 6

2659--2673

EN

The stacking velocity is often obtained manually. However, manually picking is inefficient and is easily affected by subjective factors such as the priori information and the experience of different processors. To enhance its objectivity, efficiency and consistency, we investigated an unsupervised clustering intelligent velocity picking method based on the Gaussian mixture model (GMM). This method can automatically pick the stacking velocity fast, and provide uncertainty analysis as a quality control. Combined with the geometry feature of energy clusters in velocity spectra, taking advantages of the geometric diversity of energy clusters, GMM can ft the energy clusters with different distributions more appropriately. Then, mean values of the final several submodels are located as the optimal velocity, and the multiples are avoided under the expert knowledge and geological rules. In addition, according to the covariance of submodels, we can derive the uncertainty analysis of the final time-velocity pairs, so as to indicate the reliability of picking velocity at different depths. Moreover, the automated interpreted velocity field is used for both normal moveout (NMO) correction and stacking. The comparison with the manual references is adopted to evaluate the quality of the unsupervised clustering intelligent velocity picking method. Both synthetic data and 3D field data have shown that the proposed unsupervised intelligent velocity picking method can not only achieve similar accuracy with manual results, but also get rid of multiples. Furthermore, compared with manual picking, it can significantly improve the efficiency and accuracy in identifying pore and cave structures, as well as indicating the uncertainty of time-velocity pairs by variance.

4

Automatic defect detection and characterization by thermographic images based on damage classifiers evaluation

Dinardo Giuseppe, Fabbiano Laura, Tamborrino Rosanna, Vacca Gaetano

Metrology and Measurement Systems

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2020

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Vol. 27, nr 2

219--242

EN

In the framework of non-destructive evaluation (NDE), an accurate and precise characterization of defects is fundamental. This paper proposes a novel method for characterization of partial detachment of thermal barrier coatings from metallic surfaces, using the long pulsed thermography (LPT). There exist many applications, in which the LPT technique provides clear and intelligible thermograms. The introduced method comprises a series of post-processing operations of the thermal images. The purpose is to improve the linear fit of the cooling stage of the surface under investigation in the logarithmic scale. To this end, additional fit parameters are introduced. Such parameters, defined as damage classifiers, are represented as image maps, allowing for a straightforward localization of the defects. The defect size information provided by each classifier is, then, obtained by means of an automatic segmentation of the images. The main advantages of the proposed technique are the automaticity (due to the image segmentation procedures) and relatively limited uncertainties in the estimation of the defect size.

5

Parameter sensitivity and uncertainty of radiation interception models for intercropping system

Zeng Wenzhi, Lu Yuchao, Srivastava Amit Kumar, Gaiser Thomas, Huang Jiesheng

Ecological Chemistry and Engineering. S

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2020

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Vol. 27, nr 3

437--456

EN

Estimating the interception of radiation is the first and crucial step for the prediction of production for intercropping systems. Determining the relative importance of radiation interception models to the specific outputs could assist in developing suitable model structures, which fit to the theory of light interception and promote model improvements. Assuming an intercropping system with a taller and a shorter crop, a variance-based global sensitivity analysis (EFAST) was applied to three radiation interception models (M1, M2 and M3). The sensitivity indices including main (Si) and total effects (STi) of the fraction of intercepted radiation by the taller (ftaller), the shorter (fshorter) and both intercrops together (fall) were quantified with different perturbations of the geometric arrangement of the crops (10-60 %). We found both ftaller and fshorter in M1 are most sensitive to the leaf area index of the taller crop (LAItaller). In M2, based on the main effects, the leaf area index of the shorter crop (LAIshorter) replaces LAItaller and becomes the most sensitive parameter for fshorter when the perturbations of widths of taller and shorter crops (Wtaller and Wshorter) become 40 % and larger. Furthermore, in M3, ftaller is most sensitive to LAItaller while fshorter is most sensitive to LAIshorter before the perturbations of geometry parameters becoming larger than 50 %. Meanwhile, LAItaller, LAIshorter, and Ktaller are the three most sensitive parameters for fall in all three models. From the results we conclude that M3 is the most plausible radiation interception model among the three models.

6

Measurement of basic observation parameters of optoelectronic devices in an accredited laboratory. Measurement methodology, uncertainty analysis

Bareła Jarosław, Kastek Mariusz, Firmanty Krzysztof

Measurement Automation Monitoring

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2019

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Vol. 65, No. 1

2--6

EN

The article describes the methodologies for measuring the basic parameters of optoelectronic observation devices in accordance with applicable standards and international procedures. Noise equivalent temperature difference NETD, minimum resolvable temperature difference MRTD, detection, recognition and identification ranges according to STANAG 4347, angular field of view FOV and modulation transfer function MTF are described. The description and requirements for laboratory measuring stations are presented. The article contains an analysis of measurement uncertainty of measured quantities in accordance with ISO 17025: 2018 and JCGM 100: 2008 guide based on the TOP 6-3-040 procedure.

7

Application of uncertainty analysis based on Monte Carlo (MC) simulation for life cycle inventory (LCI)

Sala Dariusz, Bieda Bogusław

Inżynieria Mineralna

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2019

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R. 21, nr 2/2

264--269

EN

The use of Monte Carlo (MC) simulation was presented in order to assess uncertainty in life cycle inventory (LCI) studies. The MC method is finded as an important tool in environmental science and can be considered the most effective quantification approach for uncertainties. Uncertainty of data can be expressed through a definition of probability distribution of that data (e.g. through standard deviation or variance). The presented case in this study is based on the example of the emission of SO2, generated during energy production in Integrated Steel Power Plant (ISPP) in Kraków, Poland. MC simulation using software Crystal Ball® (CB), software, associated with Microsoft® Excel, was used for the uncertainties analysis. The MC approach for assessing parameter uncertainty is described. Analysed parameter (SO2,) performed in MC simulation were assigned with log-normal distribution. Finally, the results obtained using MC simulation, after 10,000 runs, more reliable than the deterministic approach, is presented in form of the frequency charts and summary statistics. Thanks to uncertainty analysis, a final result is obtained in the form of value range. The results of this study will encourage other researchers to consider this approach in their projects, and the results of this study will encourage other LCA researchers to consider the uncertainty in their projects and bring closer to industrial application.

8

Analiza wrażliwości i niepewności modelu hydrodynamicznego (SWMM) do prognozowania odpływu wód opadowych ze zlewni zurbanizowanej – studium przypadku

Szeląg B., Kiczko A., Dąbek L.

Ochrona Środowiska

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2016

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Vol. 38, nr 3

15--22

PL

Modelowanie ilości ścieków oraz napełnień przewodów sieci kanalizacyjnej stanowi istotny element umożliwiający ocenę funkcjonowania systemów odprowadzania wód opadowych z terenu zlewni. Złożoność procesów fizycznych, które są symulowane oraz ograniczona liczba danych dostępnych do kalibracji powoduje dużą niepewność uzyskanych wyników. W artykule przedstawiono przykład zastosowania techniki GSA-GLUE do analizy wrażliwości i probabilistycznej identyfikacji parametrów (szerokość drogi spływu, wysokość retencji terenowej powierzchni uszczelnionych i nieuszczelnionych, udział powierzchni uszczelnionej, współczynnik szorstkości kanałów, spadek podłużny zlewni) w przypadku modelu zlewni zurbanizowanej wykonanego w programie SWMM (storm water management model). Do kalibracji i walidacji modelu zlewni wykorzystano wyniki pomiarów wysokości opadów oraz przepływów ścieków deszczowych wykonanych w latach 2009–2011. Przeprowadzone obliczenia wykazały, że największy wpływ na kształt hydrogramu odpływu wód opadowych ze zlewni zurbanizowanej w opracowanym modelu hydrodynamicznym miały współczynnik szorstkości ścian kanałów oraz wysokość retencji terenów uszczelnionych. Uzyskane wyniki przeprowadzonej symulacji potwierdziły, że zastosowane w pracy metody oceny wrażliwości i identyfikacji parametrów mogą być pomocne przy kalibracji modeli hydrodynamicznych zlewni zurbanizowanych.

EN

Modeling of sewage volume and sewer system filling-ups is an important element that allows performance assessment of a rainfall drainage system from a basin area. The complex nature of physical processes being simulated and limited amount of observation data available for calibration make the model outcomes highly uncertain. The presented case study demonstrates an application of the GSA-GLUE technique (global sensitivity – generalized uncertainty estimation) to the sensitivity analysis and probabilistic identification of parameters (surface runoff width, water capacity of impervious and pervious surfaces, impervious surface fraction, the Manning roughness coefficient of channels and longitudinal basin slope) for the urban catchment model designed with the SWMM software. Measurement data of rainfall intensity and rain water flow from the period of 2009 to 2011 was used for calibration and validation of the basin model. The numerical experiments revealed that the channel roughness coefficient and water capacity measures of impervious surfaces had the highest impact on shape of the calculated hydrograph for storm water runoff in an urban basin. The simulation results confirmed that the sensitivity analysis and parameter identification methods applied might be useful in calibration of urbanized basin hydrodynamic models.

9

Metrological Analysis of Precision of the System of Delivering a Water Capsule for Explosive Production of Water Aerosol

Śmigielski G., Toczek W., Dygdała R., Stefański K.

Metrology and Measurement Systems

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2016

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Vol. 23, nr 1

47--58

EN

In this paper precision of the system controlling delivery by a helicopter of a water capsule designed for extinguishing large scale fires is analysed. The analysis was performed using a numerical method of distribution propagation (the Monte Carlo method) supplemented with results of application of the uncertainty propagation method. In addition, the optimum conditions for the airdrop are determined to ensure achieving the maximum area covered by the water capsule with simultaneous preserving the precision level necessary for efficient fire extinguishing.

10

Measurement Uncertainty In Algorithms Using PCA Method

Augustyn J.

Measurement Automation Monitoring

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2015

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Vol. 61, No. 11

494--497

EN

Propagation analysis of selected uncertainty sources in algorithms using the PCA method has been presented. The paper shows uncertainty analysis in algorithms, which use minimization of squared distances technique and maximizing the variance technique. On the basis of simulation tests the influence of the used signal sampling technique on the eigenvalues vector for the sinusoidal signal containing additive white noise, has been compared. Three applied sampling techniques have been analyzed: synchronization of the beginning of the data acquisition, for the successive sequences xi, immediately after a positive zero-level crossing of the analyzed waveform; separation of the NM-element sequence x to M of N-element sequences xi collected sequentially in subsequent rows of the matrix X; and application of sampling with the fractional delay of d=Ts/2, and X matrix construction from alternating strings: x2i-1 - sampled with a delay of d, and x2i - sampled with a zero delay from the moment of the zero crossing by analyzed waveform.

11

Determination of transient fluid temperature using the inverse method

Jaremkiewicz M.

Archives of Thermodynamics

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2014

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Vol. 35, no. 1

61--76

EN

This paper proposes an inverse method to obtain accurate measurements of the transient temperature of fluid. A method for unit step and linear rise of temperature is presented. For this purpose, the thermometer housing is modelled as a full cylindrical element (with no inner hole), divided into four control volumes. Using the control volume method, the heat balance equations can be written for each of the nodes for each of the control volumes. Thus, for a known temperature in the middle of the cylindrical element, the distribution of temperature in three nodes and heat flux at the outer surface were obtained. For a known value of the heat transfer coefficient the temperature of the fluid can be calculated using the boundary condition. Additionally, results of experimental research are presented. The research was carried out during the start-up of an experimental installation, which comprises: a steam generator unit, an installation for boiler feed water treatment, a tray-type deaerator, a blow down flashvessel for heat recovery, a steam pressure reduction station, a boiler control system and a steam header made of martensitic high alloy P91 steel. Based on temperature measurements made in the steam header using the inverse method, accurate measurements of the transient temperature of the steam were obtained. The results of the calculations are compared with the real temperature of the steam, which can be determined for a known pressure and enthalpy.

12

Analiza wpływu niepewności danych wejściowych na dokładność systemów detekcji nieszczelności

Turkowski M., Bratek A., Ostapkowicz P.

Pomiary Automatyka Robotyka

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2013

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R. 17, nr 4

89-94

PL

Przedstawiono metodę oceny dokładności systemów detekcji i lokalizacji nieszczelności. Metoda bazuje na znanych z metrologii metodach analizy niepewności. Przedstawiono wyniki obliczeń oraz badań eksperymentalnych przeprowadzonych na instalacji modelowej.

EN

The method of the assessment of the leak detection and localization systems accuracy is presented. The method is based on the uncertainty analysis known from metrology. The calculations and experimental results carried on modeling installation were presented.

13

Air quality modeling in Warsaw Metropolitan Area

Holnicki P., Nahorski Z.

Journal of Theoretical and Applied Computer Science

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2013

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Vol. 7, nr 1

56--69

EN

Decision support of air quality management needs to connect several categories of the input data with the analytical process of air pollution dispersion. The aim of the respective model of air pollution is to provide a quantitative assessment of environmental impact of emission sources in a form of spatial/temporal maps of pollutants’ concentration or deposition in the domain. These results are in turn used in assessment of environmental risk and supporting respective planning actions. However, due to the complexity of the forecasting system and the required input data, such environmental prognosis and related decisions contain many potential sources of imprecision and uncertainty. The main sources of uncertainty are commonly considered meteorological and emission input data. This paper addresses the problem of emission uncertainty, and impact of this uncertainty on the forecasted air pollution concentrations and adverse health effects. The computational experiment implemented for Warsaw Metropolitan Area, Poland, encompasses one-year forecast with the year 2005 meteorological dataset. The annual mean concentrations of the main urban pollutants are computed. The impact of uncertainty in emission field inventory is also considered. Uncertainty assessment is based on the Monte Carlo technique where the regional scale CALPUFF model is the main forecasting tool used in air quality analysis.

14

Modelling of solute transport in rivers under different fflow rates: A case study without transient storage

Romanowicz R.J., Osuch M., Wallis S.

Acta Geophysica

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2013

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Vol. 61, no. 1

98--125

EN

A methodology to derive solute transport models at any flow rate is presented. The novelty of the proposed approach lies in the assessment of uncertainty of predictions that incorporate parameterisation based on flow rate. A simple treatment of un certainty takes in to account hetero- scedastic modelling errors related to tracer experiments performed over a range of flow rates, as well as the uncertainty of the observed flow rates themselves. The proposed approach is illustrated using two models for the transport of a conservative solute: a physically based, deterministic, advection-dispersion model (ADE), and a stochastic, transfer function based, active mixing volume model (AMV). For both models the uncertainty of any parameter increases with increasing flow rate (reflecting the heteroscedastic treatment of modelling errors at different observed flow rates), but in contrast the uncertainty of travel time, computed from the predicted model parameters, was found to decrease with increasing flow rate.

15

Uncertainty analysis of the kinetic model of natural gas combustion in IC Engine

Mansha M., Naqvi J. H.

Polish Journal of Chemical Technology

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2012

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Vol. 14, nr 1

1-4

EN

The purpose of this analysis is to determine the uncertainties originating due to the kinetic parameters of the rate of a reaction proposed kinetic model. A kinetic model consisting of 208 reaction steps and 73 species was adopted for analysis. In the required uncertainty analysis, the accuracy of approximate models, generated by the Chemkin 4.1.1 for pollutant species, is determined. The reactions which contribute the uncertainty in the output concentrations of the pollutnats species formed in the combustion chamber were identifi ed. The percentage contribution to the uncertainty in the output concentrations of pollutants were also determined.

16

Ocena niepewności rozwiązania w modelowaniu zmienności przestrzennej parametrów ośrodka za pomocą metody kosymulacji

Pirowska K.

Nafta-Gaz

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2012

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R. 68, nr 12

1050--1054

PL

W publikacji poruszono problem analizy niepewności w przypadku stosowania metod symulacji czy kosymulacji. Posiadając zbiór alternatywnych realizacji otrzymanych w wyniku działania tych metod, nie jest możliwe wskazanie najlepszej realizacji, na której można by oprzeć dalsze interpretacje, obliczenia, a finalnie – wydać odpowiednie, strategiczne dla przemysłu nafty i gazu decyzje. Zachodzi potrzeba zastosowania narzędzi, które – uwzględniając wszystkie realizacje – są pomocne w ocenie wyników. Niezbędne jest obliczenie wartości średniej, wariancji warunkowej, przydatne może być też obliczenie rozkładów prawdopodobieństwa czy rozkładów kwantyli. Przy użyciu wymienionych rozkładów, na przykładzie modelowania porowatości metodą kosymulacji sekwencyjnej Gaussa, przedstawiono ocenę niepewności rozwiązania.

EN

In this paper the problem of uncertainty assessment was brought up. In the case of the application of simulation or co-simulation a set of realizations were received as the result. It is not possible to choose the best realization on which to base further interpertations, calculations and, what is most important, make strategic decisions for the oil and gas industry. It is necessary to use tools, which take into account all realizations and are helpful in results assessment. It is essential to calculate the mean values and conditional variance. It can be useful to calculate probability distribution or quantile distribution. In this paper application of these distributions was presented as the example of the uncertainty assessment in porosity modeling using Gaussian sequential co-simulation.

17

Zastosowanie koncepcji analizy wrażliwości w zarządzaniu procesami logistycznymi

Nowakowski T., Tubis A.

Logistyka

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2012

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nr 2

PL

Analiza wrażliwości jest narzędziem szeroko wykorzystywanym w różnych dziedzinach nauki związanych nie tylko z przedsiębiorstwem. Jest to koncepcja, która z powodzeniem może być wykorzystywana również w procesach logistycznych. Autorzy na podstawie przeprowadzonych badań literatury przedstawili różne definiowanie i zastosowanie analizy wrażliwości w trzech wybranych przez siebie obszarach - rachunkowości zarządczej, teorii decyzji oraz naukach technicznych. Następnie w oparciu o przeprowadzoną analizę pojęciową autorzy podjęli próbę scharakteryzowania zakresu tej analizy i jej zastosowania w zarządzaniu procesami logistycznymi.

EN

Sensitivity analysis is tool that is broadly applied in different branches of science, not only related to the enterprise. It is a concept that can be successfully used with logistic processes as well. On the basis of literature review authors present different definitions and application of sensitivity analysis in three chosen areas – management accounting, decision theory and engineering. Afterward on the basis of conceptual analysis authors attempt to characterize the range of aforementioned analysis and its application to logistic processes.

18

Metoda analizy niepewności oparta na połączeniu zasady maksymalnej entropii i metody oceny punktowej

Zhang X. L., Huang H. Z., Wang Z. L., Xiao N. C., Li Y. F.

Eksploatacja i Niezawodność

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2012

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Vol. 14, No. 2

114-119

PL

Niepewność jest nieodłącznym elementem procesów projektowania produktu. Dlatego też podejmowanie niezawodnych decyzji wymaga analizy niepewności, która uwzględniałaby wszystkie rodzaje niepewności. W praktyce inżynierskiej, z powodu niepełnej wiedzy, wyznaczenie rozkładu niektórych zmiennych projektowych nie jest możliwe. Co więcej, funkcja stanu granicznego jest wysoce nieliniowa, co sprawia, że do poprawnego obliczenia prawdopodobieństwa uszkodzenia potrzebna jest znajomość momentów wyższych rzędów tej funkcji. W niniejszej pracy zaproponowano metodę analizy niepewności łączącą zasadę maksymalnej entropii z metodą bootstrapową. W pierwszej części pracy wykorzystano metodę bootstrapową do obliczenia przedziałów ufności czterech pierwszych momentów dla zmiennych losowych typu mieszanego oraz zmiennych z próby. Następnie, wyznaczono momenty wyższych rzędów funkcji stanu granicznego przy użyciu metody redukcji wymiarów. Po trzecie, w celu obliczenia funkcji gęstości prawdopodobieństwa (PDF) oraz dystrybuanty (CDF) funkcji stanu granicznego, sformułowano model optymalizacji oparty na zasadzie maksymalnej entropii. Proponowana metoda nie wymaga założenia znajomości rozkładów zmiennych losowych ani obliczania wrażliwości dla funkcji stanu granicznego w odniesieniu do najbardziej prawdopodobnego punktu awarii. W końcowej części artykułu porównano na podstawie przykładów numerycznych wyniki otrzymane za pomocą proponowanej metody oraz symulacji Monte Carlo (MCS).

EN

Uncertainty is inevitable in product design processes. Therefore, to make reliable decisions, uncertainty analysis incorporating all kinds of uncertainty is needed. In engineering practice, due to the incomplete knowledge, the distribution of some design variables can not be determined. Furthermore, the performance function is highly nonlinear, therefore, the high order moments of the performance function are needed to calculate the probability of failure accurately. In this paper, an uncertainty analysis method combining the maximum entropy principle and the bootstrapping method is proposed. Firstly, the bootstrapping method is used to calculate the confidence intervals of the first four moments for mixed random variables and sample variables. Secondly, the high order moments of limit state functions are estimated using the reduced dimension method. Thirdly, to calculate the probability density function (PDF) and cumulative distribution function (CDF) of the limit state functions, an optimization model based on the maximum entropy principle is formulated. In the proposed method, the assumptions that the distribution of the random variables are known and the calculation of the sensitivity for limit state function with respect to the Most Probable Point (MPP) are avoided. Finally, comparisons of results from the proposed methods and the MCS method are presented and discussed with numerical examples.

19

Analiza elementów ryzyka geologicznego rejonu Suliszewo–Radęcin w kontekście składowania CO2

Michna M., Papiernik B.

Biuletyn Państwowego Instytutu Geologicznego

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2012

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nr 448 (1)

81--86

PL

Artykuł skupia się na analizie elementów ryzyka dolnojurajskiej formacji zawodnionej w rejonie Radęcin–Suliszewo. Skałami zbiornikowymi są tutaj piaskowce synemuru oraz pliensbachu a uszczelniają je mułowce i iłowce toarku. Autorzy stworzyli model strukturalny a następnie bazowe modele parametryczne rejonu Radęcin–Suliszewo. Na podstawie modeli bazowych oszacowano wyjściową wartość możliwego do zatłoczenia CO2. W kolejnym etapie, używając procedury Uncertainty Analysis w programie Petrel dokonano analizy czterech elementów niepewności (nasycenia gazem, położenia kontaktu woda/gaz, porowatości, proporcji skał zbiornikowych do uszczelniających) wpływających na wartości wolumetryczne. Określono rozkład oraz zakres poszczególnych elementów niepewności. Dzięki symulacji metodą Monte Carlo wykonano losowanie prób dla wymienionych parametrów niepewności. Dla każdej realizacji wyliczono objętość gazu w warunkach złożowych.Wyniki przedstawiono w postaci histogramów oraz wykresu tornado. W ten sposób określono, w jakim stopniu poszczególne elementy niepewności wpływają na ilość CO2 możliwego do zmagazynowania. Największy wpływ na ilość możliwego do zmagazynowania gazu ma odpowiednio założony model nasycenia gazem (93–116% względem modelu bazowego) następnie określony kontakt między mediami złożowymi (93,5–106,5% względem modelu bazowego). Porowatość wpływa w tym przypadku w granicy 97–103,5% na wyniki analizy, natomiast różnica w progowej wartości skały zbiornikowe/skały uszczelniające jest nieznaczna i można ją zaniedbać.

EN

The paper presents the analysis of risk elements in the Lower Jurassic water-saturated formation in the Radęcin–Suliszewo area. The reservoir rocks in this area are represented by Sinemurian and Pliensbachian sandstones sealed by Toarcian mudstones and claystones. The authors constructed a structural model and then base parametric models for the Radęcin–Suliszewo area. Based on the base models, an output value of the CO2 amount possible to be injected was estimated. In the next stage, following the Uncertainty Analysis procedure in Petrel, analysis of four elements affecting volumetric values was carried out (i.e. gas saturation, location of gas/water contact, porosity, and the ratio of reservoir rocks versus sealing rocks). With ap.lication of the Monte Carlo method, sampling for the above uncertainty elements was performed. For each realization, gas volume in reservoir conditions was computed. The results were presented in the form of histograms and a tornado chart. In this way, the authors determined to what degree the individual uncertainty elements affect the CO2 amount possible to be injected. The strongest effects on the amount are associated with the properly assumed model of gas saturation (93–116% in relation to the base model) and then the determined contact between reservoir media (93.5–106.5% in relation to the base model). Porosity affects from 97–103.5% of the analysis results and the difference in the threshold value of the reservoir rocks/sealing rocks ratio is insignificant and can be neglected.

20

Filtered thermal contrast based technique for testing of material by infrared thermography

Gryś S.

Opto-Electronics Review

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2011

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Vol. 19, No. 2

234-241

EN

A new kind of thermal contrast, called ''filtered contrast'' is presented, which allows detecting and characterizing material defects using active thermography under some assumptions on physical and thermal parameters of materials. In opposition to known definitions of the thermal contrast, knowledge about defect-free area is not necessary and this contrast is less sensitive to nonuniformity of heat disposal to the material surface. The measurements were performed on an experimental setup equipped with a ThermaCAM PM 595 infrared camera and frame grabber. The step heating was chosen as heat excitation. The results demonstrate usefulness of the 1D model of heat transfer used for determination of depth of subsurface defects. The influence of the parameter of the smoothing filter, required for filtered contrast implementation, thermal parameters of the tested material and defect on expanded uncertainty of determination of defect depth is also presented. Due to significant complexity of the model of heat transfer, the conditions for the "law of propagation of uncertainty" were not fulfilled and a numerical method, i.e., Monte Carlo simulation is applied for the propagation of distributions.