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Number of results: 8
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Abstract

The paper formulates some objections to the methods of evaluation of uncertainty in noise measurement which are presented in two standards: ISO 9612 (2009) and DIN 45641 (1990). In particular, it focuses on approximation of an equivalent sound level by a function which depends on the arithmetic average of sound levels. Depending on the nature of a random sample the exact value of the equivalent sound level may be significantly different from an approximate one, which might lead to erroneous estimation of the uncertainty of noise indicators. The article presents an analysis of this problem and the adequacy of the solution depending on the type of a random sample.
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Authors and Affiliations

Bartosz Przysucha
Wojciech Batko
Agata Szeląg
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Abstract

This paper presents the statistical modelling of the monitoring data on oxygen indicators in the Rega River, collected in years of 1992-97. In the first part, the six probability distributions are examined to fit the experimental data. The results indicate that the lognormal and Gamma distributions give an adequate description for all considered data series, as measured by P-P probability plots, and a Kolmogorov-Srnirnov goodness of fit test. In the second part, the detailed statistical analysis was performed based on lognormal distribution. This study showed that the approximation of monitoring data with the appropriate probability distribution could be very useful for evaluating of water quality.
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Authors and Affiliations

Janina Możejko
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Abstract

The paper presents the method of determination of two-dimensional probability distribution Pf of crack initiation versus fatigue life N and the fatigue damage parameter : Pf − N − ϭ. The proposed distribution Pf uses parameters of the standard fatigue characteristics and allows calculating fatigue life of elements with heterogeneous stress fields at any probability level. The model was successfully verified on experimental test results.

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Authors and Affiliations

Aleksander Karolczuk
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Abstract

The paper discusses service load measurements (weight of construction materials, small equipment and workers) conducted on 120 frame scaffoldings all over Poland in 2016‒2018. Despite the fact that the scaffolding should ensure the safety of its users, most accidents on construction sites are caused by fall from height. Service loads are one of the elements affecting the safety of scaffolding use. On the basis of the studies, maximum load on one platform and maximum load on a vertical scaffolding module for one day were obtained. They were treated as the random variables of the maximum values. Histograms and probability density functions were determined for these variables. The selection of a probability distribution consisted in the selection of a probability density function by means of fitting curves to the study result histograms using the method of least squares. The analysis was performed for distribution Weibull and Gumbel probability density functions which are applied for maximum values of random variables. Parameters of these functions can be used for the purposes of the reliability analysis to calibrate partial safety factors in simulation of service load during the scaffolding failure risk assessment. Besides, the probability of not exceeding the standard loads provided for frame scaffoldings for 120 weeks was established on the aforementioned basis. The results of the presented research show that in Poland there is a high probability of exceeding the permissible service loads in one year and thus there is a high risk of scaffolding damage.
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Bibliography

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Authors and Affiliations

Ewa Błazik-Borowa
1
ORCID: ORCID
Michał Pieńko
1
ORCID: ORCID
Iwona Szer
2
ORCID: ORCID
Bożena Hoła
3
ORCID: ORCID
Krzysztof Czarnocki
4
ORCID: ORCID

  1. Faculty of Civil Engineering and Architecture, Lublin University of Technology, Nadbystrzycka 40, 20-618 Lublin, Poland
  2. Faculty of Civil Engineering, Architecture and Environmental Engineering, Lodz University of Technology, Politechniki 6, 90-924 Łódz, Poland
  3. Faculty of Civil Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
  4. Faculty of Management, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland
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Abstract

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 ( BOD 5), chemical oxygen demand ( COD Cr), total suspended solids ( TSS), total nitrogen (N tot), total phosphorus (P tot). 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 BOD 5, COD Cr and TSS, and a high variability of composition for N tot and P tot. The best fitted distribution was log-normal for BOD 5, TSS, N tot and P tot and general extreme values for COD Cr. The simulation carried out using the Monte-Carlo method confirmed that there may be problems associated with the reduction of nutrients (N tot and P tot) 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.
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Authors and Affiliations

Karolina Migdał
1
ORCID: ORCID
Agnieszka Operacz
1
ORCID: ORCID
Iryna Vaskina
2
ORCID: ORCID
Paulina Śliz
3
ORCID: ORCID
Jorge Tavares
4 5
ORCID: ORCID
Adelaide Almeida
4 5 6
ORCID: ORCID
Michał Migdał
7

  1. University of Agriculture in Krakow, Faculty of Environmental Engineering and Land Surveying, Department of Sanitary Engineering and Water Management, al. Mickiewicza 24/28, 30-059 Kraków, Poland
  2. Sumy State University, Faculty of Technical System and Energy Efficient Technologies, Department of Applied Ecology, Sumy, Ukraine
  3. Cracow University of Economics, Institute of Spatial Management and Urban Studies, Department of Spatial Management, Kraków, Poland
  4. Polytechnic Institute of Beja, Department of Technology and Applied Sciences, Beja, Portugal
  5. University of Beira Interior, Faculty of Engineering, Research Unit Fiber Materials and Environmental Technologies (FibEnTech-UBI), Covilhã, Portugal
  6. University Nova of Lisbon, Faculty of Science and Technology, Center for Environmental and Sustainability Research (CENSE), Lisbon, Portugal
  7. Stalprodukt S.A., Bochnia, Poland
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Abstract

An embedded time interval data acquisition system (DAS) is developed for zero power reactor (ZPR) noise experiments. The system is capable of measuring the correlation or probability distribution of a random process. The design is totally implemented on a single Field Programmable Gate Array (FPGA). The architecture is tested on different FPGA platforms with different speed grades and hardware resources. Generic experimental values for time resolution and inter-event dead time of the system are 2.22 ns and 6.67 ns respectively. The DAS can record around 48-bit x 790 kS/s utilizing its built-in fast memory. The system can measure very long time intervals due to its 48-bit timing structure design. As the architecture can work on a typical FPGA, this is a low cost experimental tool and needs little time to be established. In addition, revisions are easily possible through its reprogramming capability. The performance of the system is checked and verified experimentally.

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Authors and Affiliations

Mohammad Arkani
Hossein Khalafi
Naser Vosoughi
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Abstract

Together with the dynamic development of modern computer systems, the possibilities of applying refined methods of nonparametric estimation to control engineering tasks have grown just as fast. This broad and complex theme is presented in this paper for the case of estimation of density of a random variable distribution. Nonparametric methods allow here the useful characterization of probability distributions without arbitrary assumptions regarding their membership to a fixed class. Following an illustratory description of the fundamental procedures used to this end, results will be generalized and synthetically presented of research on the application of kernel estimators, dominant here, in problems of Bayes parameter estimation with asymmetrical polynomial loss function, as well as for fault detection in dynamical systems as objects of automatic control, in the scope of detection, diagnosis and prognosis of malfunctions. To this aim the basics of data analysis and exploration tasks - recognition of outliers, clustering and classification - solved using uniform mathematical apparatus based on the kernel estimators methodology were also investigated

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Authors and Affiliations

P. Kulczycki

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