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1

The valuation of exit option in a lignite mine using Monte Carlo simulation

Pawlak Marcin, Wiśniewski Tomasz

Journal of Sustainable Mining

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2024

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Vol. 23, iss. 1

40--54

EN

This study aims to demonstrate the application of simulation techniques to the valuation of real options. The nature of the paper is methodological and empirical. The purpose of the valuation of the option to close a lignite mine in Poland is to demonstrate the methodology and advantages of employing Monte Carlo simulation in the valuation of real options. Close to actual numerical data reveals a complex optimization problem in the context of strategy selection by decisionmakers. Numerous factors (extraction costs, reclamation costs, the write-off for the reclamation fund, etc.), their interpenetration and multilevel influence on the decision to close the mine early enables simulation methods to demonstrate their valuation capabilities. The valuation techniques used in the paper, particularly the simulation comparative valuation method, are described in detail and are rooted in the literature and theory of finance.

2

Fault analysis and reliability evaluation for motorized spindle of cycloidal gear grinding machine based on multi-source bayes

Wang Huiliang, Zhang Zhijie, Li Jie, Xin Wen, Han Chunyang

Eksploatacja i Niezawodność

|

2024

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Vol. 26, no. 1

art. no. 175010

EN

A Monte Carlo simulation method based on multisource bayes is proposed to improve the reliability of motorized spindles in cycloid gear grinding machines and reduce their failure rate. Based on field investigations and motorized spindle maintenance records, a fault tree model of a motorized spindle was established, and the fuzzy importance of each bottom event was evaluated. The fault tree of a motorized spindle was used as a Monte Carlo reliability simulation model, and its importance was used as the input parameter for the simulation. The reliability evaluation index of the motorized spindle was obtained at different simulation times. The feasibility and accuracy of the reliability simulation were verified by comparing the importance and simulation importance. A vibration test was designed for bearing faults with high importance, and fault extraction was performed by combining the wavelet packet transform and empirical mode decomposition. This method can also be used to simulate and analyze the reliability of other equipment or machine tools.

3

Forecasting method of electric vehicle charging load based on virtual prediction parameter estimation strategy

Cai Yongxiang, Chen Qing, Wang Yang, Li Wei, Ren Jiakuan, Qu Yangquan

Archives of Electrical Engineering

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2024

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Vol. 73, nr 2

355--372

EN

In order to deal with the threat of the randomness of large-scale electric vehicle (EV) loads to the safe and economic operation of the distribution network effectively, a forecasting method of EV loads based upon virtual prediction parameter estimation strategy is proposed. Firstly, an in-depth analysis is conducted to thoroughly examine the applicability and target audience of various existing power user load forecasting methods. This initial phase provided a solid foundation for the introduction of the new methods. Secondly, utilizing the Monte Carlo simulation method, a charging load forecasting approach that considers both spatial and temporal distribution is developed. This method effectively captures the diversity of EV charging behaviors by leveraging virtual parameter estimation, integrating insights from historical data into future load predictions, thereby enhancing forecasting accuracy. Finally, to validate the effectiveness of this groundbreaking approach, comprehensive testing was conducted on the MATLAB R2017a simulation platform. This verification phase not only serves to demonstrate the method’s accuracy, but also underscores its practicality and reliability in real-world applications.

4

The Software with a Graphical User Interface for GAMOS: Basic Training and an Educational Tool for Medical Physicists

Kandemir Recep, Özsoykal İsmail, Akgüngör Kadir

Polish Journal of Medical Physics and Engineering

|

2023

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Vol. 29, Iss. 1

42--49

EN

Introduction: It is necessary to have special experience to perform the Monte Carlo calculation, commonly used in medical physics and accepted as the gold standard. In this study, we developed software to teach basic steps to medical physicists who were inexperienced in the medical linear accelerator Monte Carlo simulation. Material and methods: For the design interface, a software called GamosLinacGUI was developed using Gnome Builder, Python, and GTK. The user, who wants to learn the basics of GAMOS and simulate a linear accelerator, can enter the values in the software, select some options and quickly create geometry and physics files. Results: For proof that the software generates the correct inputs for GAMOS simulation in the same conditions for the measurements and calculations. Required files for GAMOS have been created and tested and run the simulation accordingly. This software was tested with Centos Linux. Conclusions: GamosLinacGUI has been successfully developed, which creates the geometry and physics files required for the simulation with GAMOS as a training and learning tool.

5

A stochastic model to quantify and optimize the impact of operational risks on corporate sustainability using monte carlo simulation

Bravo-Sepúlveda Mariana, Wilke Daniel Nico, Isaza Cuervo Felipe, Polanco Jorge-Andrés

Polish Journal of Management Studies

|

2023

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Vol. 28, No. 2

59--75

EN

Operational risk has been widely studied, and international guidelines provide procedures for the correct management of operational risk; however, this has not been studied from a corporate sustainability point of view. Therefore, this work seeks to find a way to model and optimize the impact of operational risks on corporate sustainability. The methodology used is based on the assignment of two distribution functions for the creation of a probabilistic model that allows quantifying the probability of occurrence (frequency) and the expected monetary impact (severity) on the sustainability variables (environmental, social, and economic). The result is a statistical convolution through Monte Carlo simulation, which makes it possible to quantify aggregate losses to finally make an optimization process of the variables and estimate the financial impact. Therefore, this study extends the literature on risk quantification, proposing a stochastic model that quantifies and optimizes the operational risks that are related to corporate sustainability. The proposed model offers a practical way to quantify operational risks related to corporate sustainability while also being flexible, as it does not require historical information and can be used with data collected from the company based on the proposed probability distributions. Finally, the proposed model has three limitations: the distribution functions, use of Solver (Excel), and exclusion of some risk management strategies, which future research can consider.

PL

Ryzyko operacyjne zostało szeroko zbadane, a międzynarodowe wytyczne dostarczają procedur do prawidłowego zarządzania ryzykiem operacyjnym; jednakże nie badano tego z punktu widzenia zrównoważonego rozwoju przedsiębiorstwa. Dlatego też niniejsza praca ma na celu znalezienie sposobu modelowania i optymalizacji wpływu ryzyka operacyjnego na zrównoważony rozwój przedsiębiorstwa. Zastosowana metodologia opiera się na przypisaniu dwóch funkcji rozkładu w celu stworzenia modelu probabilistycznego, który pozwala kwantyfikować prawdopodobieństwo wystąpienia (częstotliwość) i oczekiwany monetarny wpływ (ciężkość) na zmienne zrównoważone (środowiskowe, społeczne i ekonomiczne). Rezultatem jest statystyczna konwolucja poprzez symulację Monte Carlo, który umożliwia ilościowe określenie zagregowanych strat, aby ostatecznie przeprowadzić proces optymalizacji zmiennych i oszacować wpływ finansowy. Dlatego też niniejsze badanie poszerza literaturę w obszarze kwantyfikacji ryzyka, proponując model stochastyczny, który kwantyfikuje i optymalizuje ryzyko operacyjne związane ze zrównoważonym rozwojem przedsiębiorstwa. Proponowany model oferuje praktyczny sposób ilościowego określenia ryzyk operacyjnych związanych ze zrównoważonym rozwojem przedsiębiorstwa, a jednocześnie jest elastyczny, ponieważ nie wymaga informacji historycznych i może być stosowany w połączeniu z danymi zebranymi z przedsiębiorstwa w oparciu o proponowane rozkłady prawdopodobieństwa. Wreszcie proponowany model ma trzy ograniczenia: funkcje rozkładu, użycie Solvera (Excel) i wykluczenie niektórych strategii zarządzania ryzykiem, które mogą zostać uwzględnione w przyszłych badaniach.

6

Simulation of the influence of cutting speed and feed rate on tool life in hard turning of AISI 4140 steel

Paengchit Phacharadit, Saikaew Charnnarong

Materials Science Poland

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2023

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Vol. 41, No. 2

311--324

EN

Tool life performances of Al2O3+TiC and TiN+AlCrN tool inserts were investigated experimentally under different cutting conditions in turning AISI 4140 steel. The tool life model is defined in accordance with a maximum surface roughness of 0.8 μm for the tool life criterion. The relationships between machining factors (i.e., cutting speed and feed rate) and tool life were obtained by Taylor’s formular. The sensitivity of cutting speed and feed rate to tool life was evaluated by Monte Carlo simulation. The results showed that turning with high cutting speeds and feed rates decreased the tool life of both inserts. At different cutting speeds and feed rates, Al2O3+TiC exhibited better tool life performance than TiN+AlCrN. In addition, the simulation results indicated the average tool life of Al2O3+TiC was approximately 40% greater than that of TiN+AlCrN by varying cutting speeds below and above the cutting speed of 220 m/min while keeping the feed rate constant at 0.06 mm/rev. Similarly, when keeping the cutting speed constant at 220 m/min, the average tool life of Al2O3+TiC was approximately 45% greater than that of TiN+AlCrN by varying feed rates below and above the feed rate of 0.06 mm/rev. Variations of tool life values by varying cutting speeds were more sensitive than those by varying feed rates for both tool inserts.

7

Productivity Improvement Based on the Theory of Constraint and Eliminate, Combine, Rearrange, Simplify for Chilled Beef Production in Indonesia

Neisyafitri Rendayu Jonda, Ongkunaruk Pornthipa, Ongcunaruk Wisute

Management and Production Engineering Review

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2023

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Vol. 14, No. 2

111--123

EN

This paper aims to enhance the productivity of a chilled beef production line by comparing two techniques; standard time calculation and simulation. The best improvement method was obtained using the work-study principle, a network diagram, and bottleneck identification. Two methods for improvement are proposed based on the ECRS, the Theory of Constraint (TOC), and line balancing concepts. A simulation model is developed to mimic the actual production line. The simulation results are verified, validated, and compared. Some workstations were combined, and the allocation of the workers was arranged. The present production line efficiency was 46.21%, which increased to 67.09% and 79.71% from the suggested methods. It showed that using the standard time calculation gives a different result from the simulation. In summary, the simulation model along with the application of TOC and ECRS, provides accurate information and improves overall productivity.

8

Improvement of Value Stream Mapping by Integrating a Monte Carlo Simulation: A Conceptual Model

Araibi Alaa Salahuddin, Shaiful Ashrul Ishak Mohamad, Shadhar Muhanad Hatem

Management and Production Engineering Review

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2023

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Vol. 14, No. 1

72--86

EN

Value stream mapping (VSM) is a well-known lean analytical tool in identifying wastes, value, value stream, and flow of materials and information. However, process variability is a waste that traditional VSM cannot define or measure since it is considered as a static tool. For that, a new model named Variable Value Stream Mapping (V-VSM) was developed in this study to integrate VSM with risk management (RM) using Monte Carlo simulation. This model is capable of generating performance statistics to define, analyze, and show the impact of variability within VSM. The platform of this integration is under Deming’s Plan-Do-Check-Act (PDCA) cycle to systematically implement and conduct V-VSM model. The model has been developed and designed through literature investigation and reports that lead in defining the main four concepts named as; Continuous Improvement, Data Variability, Decision-Making, and Data Estimation. These concepts can be considered as connecting points between VSM, RM and PDCA.

9

A Goal Programming-Monte Carlo Simulation Methodology for Modeling Process Quality Control

Morán-Zabala Jean P., Cogollo-Flórez Juan M.

Management and Production Engineering Review

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2023

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Vol. 14, No. 2

70--78

EN

Quality profiling seeks to know the quality characteristics of products and processes to improve customer satisfaction and business competitiveness. It is required to develop new techniques and tools that upgrade and complement the traditional analysis of process variables. This article proposes a new methodology to model quality control of the process and product quality characteristics by applying optimization and simulation tools. The application in the production process of carbonated beverages allowed us to identify the most influential variables on the gas content and the degrees Brix of beverage.

10

A contribution to structural reliability analysis of composite high-pressure hydrogen storage tanks

Sid Amer Youcef, Benammar Samir, Fah Tee Kong, Wadi Mohammed, Jouda Mohammed S.

Journal of KONBiN

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2023

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Vol. 53, iss. 2

33--44

EN

Although composite high-pressure tanks are a subject of growing interest, especially for hydrogen storage applications, a detailed structural reliability analysis still needs to be improved. This work aims to provide a probabilistic investigation of the mechanical response of composite high-pressure hydrogen storage tanks using the Monte Carlo Simulation method. A performance function based on the circumferential model of composite pressure cylinders is employed with five random design variables. According to the results, the internal pressure and the helical layer thickness are the foremost parameters significantly impacting the structural reliability of the tank, whereas, the helical layer thickness and winding angles have a minor influence. In addition, high coefficients of variation values cause the contraction of the safety margin potentially leading to the failure of the composite hydrogen high-pressure tank. The obtained results were validated with experimental tests available in the literature.

PL

Chociaż kompozytowe zbiorniki wysokociśnieniowe są przedmiotem rosnącego zainteresowania, zwłaszcza w zastosowaniach związanych z magazynowaniem wodoru, szczegółowa analiza niezawodności konstrukcji wciąż wymaga poprawy. Niniejsza praca ma na celu zapewnienie probabilistycznego badania odpowiedzi mechanicznej kompozytowych wysokociśnieniowych zbiorników do przechowywania wodoru przy użyciu metody symulacji Monte Carlo. Zastosowano funkcję wydajności opartą na modelu obwodowym kompozytowych cylindrów ciśnieniowych z pięcioma losowymi zmiennymi projektowymi. Zgodnie z wynikami, ciśnienie wewnętrzne i grubość warstwy obwodowej są głównymi parametrami istotnie wpływającymi na niezawodność konstrukcyjną zbiornika, podczas gdy grubość warstwy spiralnej i kąty uzwojenia mają niewielki wpływ. Ponadto duże wartości współczynników zmienności powodują kurczenie się marginesu bezpieczeństwa potencjalnie prowadząc do awarii kompozytowego zbiornika wysokociśnieniowego na wodór. Uzyskane wyniki zostały zweryfikowane z badaniami eksperymentalnymi dostępnymi w literaturze.

11

Impact of human energy expenditure on order picking productivity: a Monte Carlo simulation study in a zone picking system

Al Theeb Nader A., Al-Araidah Omar, Al-Ali Malik M., Khudair Adnan I.

Engineering Management in Production and Services

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2023

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Vol. 15, no. 4

12--24

EN

This article aims to investigate the impact of allowable human energy expenditure (HEE) of order pickers on the throughput of workers in manual order zone picking systems MOP. The method used in this research is the Monte Carlo simulation, used while considering many human and job factors. The results showed that a worker’s gender and an item’s weight have little effect on the HEE. On the other hand, body weight, walking speed, distance travelled, and the targeted zone significantly impacted the HEE, rest allowance, and throughput. For example, male pickers at a weight of 75 kg can move up to speed to 1 m/s and pick up items weighing up to 5 kg without reaching the allowable HEE rate, equal to 4.3 kcal/min, and, thus, no rest is needed. Female pickers at a weight of 75 kg reach the allowable HEE rate, equal to 2.6 kcal/min, at a very low speed of approximately 0.1 m/s when picking up items up to 5 kg, and, thus, frequent rest is needed, which leads to low throughput. To increase the throughput of female pickers, they can be assigned to pick up lighter items. Utilising Monte Carlo simulation to evaluate the HEE in MOP while considering many factors.

12

Reliability analysis of multi-site damage with failure dependency of the turbine based on flow-thermal-solid coupling analysis and the Monte Carlo validated simulations

Qian Wenxue, Zeng Xianhai, Huang Shuanghui, Yin Xiaowei

Eksploatacja i Niezawodność

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2023

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Vol. 25, no. 3

art. no. 168771

EN

The harsh environmental loads may lead to strength failure in the turbine in an aero-engine. To accurately assess the strength reliability of the turbine under multiple loads, the stress distributions of 41 danger sites of a turbine under thermal, centrifugal, and pneumatic loads were determined by the flow-thermal-solid coupling analysis using ANSYS. Second, based on the flow-thermal-solid coupling analysis and response surface method, the probabilistic analysis model of stress at the danger site was established. And the probabilistic distribution of stress was determined by sampling and hypothesis testing. Finally, the reliability model of the turbine with multi-site damage and failure dependency was established, by which a reliability of 0.99802 was calculated. And the actual reliability of the turbine was 0.99626 determined by the Monte Carlo simulations, which verified the model in precision. The results indicated that the reliability model has a high efficiency and higher precision than the traditional reliability model with failure independence.

13

A Monte Carlo strategy to simulate positrons and positronium in biological materials

Franz Małgorzata, Franz Jan

Bio-Algorithms and Med-Systems

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2023

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Vol. 19, no. 1

40--42

EN

We present an algorithm for Monte Carlo simulations of positron tracks in biological materials. The algorithm takes into account the cross-section data for elastic and inelastic collisions between positrons and molecules and processes like direct annihilation, ionization and positronium formation. In the case of positronium formation, the algorithm considers the interactions of positronium with molecules. The algorithm can be used to identify the processes that are responsible to determine the lifetime of the positrons and their annihilation mechanism (direct or through positronium formation).

14

Influence of Component Proportions in Casting Process on Hardness and the Quality of Cast Iron

Saikaew Charnnarong, Harnsopa S.

Archives of Foundry Engineering

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2023

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Vol. 23, iss. 2

35--42

EN

The purposes of this study were to investigate the impact of proportions of cast iron scrap, steel scrap, carbon and ferro silicon on hardness and the quality of cast iron and to obtain an appropriate proportion of the four components in iron casting process using a mixture experimental design, analysis of variance and response surface methodology coupled with desirability function. Monte Carlo simulation was used to demonstrate the impacts of different proportions of the four components by varying the proportions of components within ±5% of the four components. Microstructures of the cast iron sample obtained from a company and the cast iron samples casted with the appropriate proportions of the four components were examined to see the differences of size and spacing of pearlite particle. The results showed that linear mixture components were statistically significant implying a high proportion of total variability for hardness of the cast iron samples explained by the casting mixtures of raw materials. The graphite of the sample casted from the appropriate proportion has shorter length and more uniform distribution than that from the company. When varying percentages of the four components within ±5% of the appropriate proportion, simulated hardness values were in the range of 237 to 256 HB.

15

Reliability assessment of water treatment plant with application of the Monte Carlo simulation

Mirosław-Świątek Dorota, Morawski Dariusz, Pieniak Łukasz, Świątek Bartłomiej, Czapski Przemysław, Siwiec Tadeusz

Zeszyty Naukowe SGSP / Szkoła Główna Służby Pożarniczej

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2022

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Nr 83

61--81

EN

The paper presents a comprehensive Reliability, Availability and Maintainability (RAM) assessment of the Water Supply Plant WULS-SGGW (WSP). The Monte Carlo method was used to simulate failure events of components in the technological process of the water treatment system. BlockSim application was used to perform an analysis. The reliability block diagram was used as a system modeling method. Reliability metrics were estimated based on 1000 simulations of 15 years of operation of the station. Simulations allowed the estimation of reliability metrics for the WSP, its subsystems, sections as well as basic elements included in the model. They also made it possible to determine which components are most critical to reliability.

PL

W artykule przedstawiono kompleksową ocenę niezawodności, dostępności i utrzymywalności (RAM) Zakładu Wodociągowego WULS-SGGW (WSP). Do symulacji zdarzeń awaryjnych obiektów w procesie technologicznym systemu uzdatniania wody wykorzystano metodę Monte Carlo. Do przeprowadzenia analizy wykorzystano aplikację BlockSim. Jako metodę modelowania systemu zastosowano niezawodnościowy schemat blokowy. Metryki niezawodnościowe oszacowano na podstawie 1000 symulacji 15-letniej eksploatacji stacji. Symulacje pozwoliły na oszacowanie metryk niezawodnościowych dla WSP, jej podsystemów, sekcji, a także podstawowych elementów wchodzących w skład modelu. Pozwoliły również na określenie, które elementy są najbardziej krytyczne dla niezawodności.

16

Analiza niepewności wskaźnika emisji metanu z wydobycia węgla kamiennego w Polsce

Zasina Damian, Zawadzki Jarosław

Rynek Energii

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2022

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Nr 3

77--81

PL

W artykule przedstawiono analizę niepewności zrealizowaną dla wskaźnika emisji metanu z górnictwa węgla kamiennego w Polsce. Posłużono się wytycznymi międzynarodowej metodyki inwentaryzacji emisji gazów cieplarnianych oraz dostępnymi danymi pochodzącymi z pomiarów CH4 zrealizowanych w kopalniach w Polsce zarządzanych przez jedną z krajowych spółek wydobywczych. Zauważono, że wartość wskaźnika emisji CH4 oszacowane z wykorzystaniem fragmentarycznych danych może znacznie różnić się od średniej wartości wykorzystanej na potrzeby prowadzenia krajowej inwentaryzacji emisji gazów cieplarnianych, niemniej jednak oszacowanie przedziału ufności dla wskaźnika emisji oraz jego podstawowych właściwości statystycznych może znaleźć zastosowanie w oszacowaniu wielkości emisji krajowej CH4 do powietrza.

EN

The paper presents the uncertainty analysis performed for the methane (CH4) emission factor from coal mining in Poland. The analysis is carried out in line with the international guidelines on the air emission inventory. Results are obtained using the measurement data acquired from selected Polish coal mines managed by the one of coal mining companies. It is noted that the CH4 emission factor may be significantly different from the mean value applied for purposes of fulfilling of international obligations. Nevertheless, the estimation of the confidence interval along with the basic statistical properties of the emission factor can be applied for purposes of the national CH4 emission inventory elaborated under the Climate Convention.

17

Physical aspects of Bragg curve of therapeutic oxygen-ion beam: Monte Carlo simulation

Ounoughi Nabil, Dribi Yamina, Boukhellout Abdelmalek, Kharfi Faycal

Polish Journal of Medical Physics and Engineering

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2022

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Vol. 28, Iss. 3

160--168

EN

Introduction: Oxygen (16O) ion beams have been recommended for cancer treatment due to its physical Bragg curve feature and biological property. The goal of this research is to use Monte Carlo simulation to analyze the physical features of the 16O Bragg curve in water and tissue. Material and methods: In order to determine the benefits and drawbacks of ion beam therapy, Monte Carlo simulation (PHITS code) was used to investigate the interaction and dose deposition properties of oxygen ions beam in water and human tissue medium. A benchmark study for the depth–dose distribution of a 16O ion beam in a water phantom was established using the PHITS code. Bragg's peak location of 16O ions in water was simulated using the effect of water's mean ionization potential. The contribution of secondary particles produced by nuclear fragmentation to the total dose has been calculated. The depth and radial dose profiles of 16O, 12C, 4He, and 1H beams were compared. Results: It was shown that PHITS accurately reproduces the measured Bragg curves. The mean ionization potential of water was estimated. It has been found that secondary particles contribute 10% behind the Bragg peak for 16O energy of 300 MeV/u. The comparison of the depth and radial dose profiles of 16O, 12C, 4He, and 1H beams, shows clearly, that the oxygen beam has the greater deposited dose at Bragg peak and the minor lateral deflection. Conclusions: The combination of these physical characteristics with radio-biological ones in the case of resistant organs located behind the tumor volume, leads to the conclusion that the 16O ion beams can be used to treat deep-seated hypoxic tumors.

18

Identification of the structure break point for data with changing variance

Witulska Justyna, Wyłomańska Agnieszka

Mathematica Applicanda

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2022

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Vol. 50, no. 1

65--106

EN

In this paper, we discuss the problem of the structure break point detection for data with changing variance. Considering the limitations and advantages of five well-known techniques, we propose a hybrid algorithm dedicated to the considered problem. The new method enables us to detect break point, even if the data exhibit non-Gaussian characteristics and the small differences between variances in separate segments occur. The efficiency is verified for simulated data from three general classes of distributions, namely platykurtic, leptokurtic and mesokurtic classes represented here by Gaussian, Laplace, Student's t, and generalized Gaussian distributions. The simulation study is supported by real data analysis.

PL

W artykule omówiono problem detekcji punktu zmiany reżimu dla danych o zmiennej wariancji. Uwzględniając ograniczenia i zalety pięciu znanych technik, zaproponowano hybrydowe podejscie dla omawianego problemu. Nowa metoda umożliwia wykrycie punktu zmiany, nawet jeśli dane wykazują charakterystykę niegaussowską i występują niewielkie różnice pomiędzy wariancjami w poszczególnych segmentach. Skuteczność metody jest weryfikowana dla danych symulowanych pochodzących z trzech ogólnych klas rozkładów, mianowicie platykurtycznych, leptokurtycznych oraz mezokurtycznych reprezentowanych tutaj przez rozkład normalny, Laplace'a, t-Studenta oraz uogólniony rozkład normalny. Badania symulacyjne poparte są analizą danych rzeczywistych.

19

Assessment of the reliability of the operation of a sewage treatment plant using Monte Carlo simulation

Migdał Karolina, Operacz Agnieszka, Vaskina Iryna, Śliz Paulina, Tavares Jorge, Almeida Adelaide, Migdał Michał

Journal of Water and Land Development

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2022

|

Special Issue

80--90

EN

The aim of the study was to model the operation of a wastewater treatment plant using the Monte Carlo method and selected probability distributions of random variables. Pollutant indices in treated wastewater were analysed, such as: biological oxygen demand (BOD5), chemical oxygen demand (CODCr), total suspended solids (TSS), total nitrogen (Ntot), total phosphorus (Ptot). The preliminary analysis of pollution indicators series included the: calculation of descriptive statistics and assessment of biological degradability of wastewater. The consistency of the theoretical distributions with the empirical ones was assessed using Anderson-Darling statistics. The best-fitting statistical distributions were selected using the percent bias criterion. Based on the calculations performed, it was found that the analysed indicators of pollution in treated wastewater were characterised by an average variability of composition for BOD5, CODCr and TSS, and a high variability of composition for Ntot and Ptot. The best fitted distribution was log-normal for BOD5, TSS, Ntot and Ptot and general extreme values for CODCr. The simulation carried out using the Monte-Carlo method confirmed that there may be problems associated with the reduction of nutrients (Ntot and Ptot) the analysed wastewater treatment plant. Results of values obtained of the risk values of negative control of wastewater treatment plant operation for biogenic compounds, different from 1, indicate that the number of exceedances at the outflow may be higher than the acceptable one.

20

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.