Ethicists have thus far not paid much attention to uncertainty, very often concentrating on highly idealized hypothetical situations where both empirical (e.g. the state of the world, the spectrum of possible decisions and their consequences, the causal connections between events) and normative (the content of norms, value scales) matters were clearly defined and well-known to the decision-maker. In this article, which stems from a project on different types of decisions under uncertainty related to the rapid progress in biomedical research, I analyze some situations of normative uncertainty, cases when an agent must make a decision, but does not know which choice is correct, for example, because he/she has contrary intuitions about the permissibility of available decisions. The view termed comparativism claims that in such cases the appropriate decision depends not only on the credences that one assigns to different norms, but also on how much possible decisions are worth taking in the light of these norms. I analyze a few cases of normative uncertainty, and a specific counter-argument against the current versions of comparativism, showing that under normative uncertainty this view imposes risk neutrality, although it permits us to have different risk attitudes under empirical uncertainty. I also argue that a precautionary approach to situations of normative uncertainty is overly simplistic.

The well-known Manning formula is usually used for the calculation of the calculative volumetric flow rate in a river or open canal. The discharge depends on the geometry of the channel, i.e. the water area, the wetted perimeter and the slope, as well as on the roughness coefficients. All these quantities are determined with some uncertainty. The article proposes a methodology for calculating the uncertainty of the roughness coefficients of the riverbed and the floodplain as well as the uncertainty of the geometric dimensions of the riverbed. Then, the method of calculating the uncertainty of the calculative discharge is then given. If these uncertainties are taken into consideration in the process of discharge calculation, then, as has been demonstrated for a hypothetical river channel, the ratio of the uncertainty to the calculated value of the discharge will change from several dozen percent in case of small flows to about ten percent in case of big, flood flows. It has also been shown that the uncertainty of the roughness coefficients has the biggest influence on the uncertainty of the flow rate. The presented calculations show that in order to take into account the influence of uncertainty of linear dimensions and roughness coefficients, the engineer designing the riverbed should assume for the calculations the flow rate increased by 10% then design flow. The obtained results can be used for homogeneous flows only, which is usually assumed in practical engineering calculations.

Knowledge of the uncertainty of measurement of testing results is important when results have to be compared with limits and specifications. In the measurement of sound insulation following standards ISO 140-4 and 140-5 the uncertainty of the final magnitude is mainly associated to the average sound pressure levels L1 and L2 measured. However, the study of sound fields in enclosed spaces is very difficult: there are a wide variety of rooms with different sound fields depending on factors as volume, geometry and materials. A parameter what allows us to quantify the spatial variation of the sound pressure level is the standard deviation of the pressure levels measured at the different positions of the room. Based on the analysis of this parameter some results have been pointed out: we show examples on the influence of the microphone positions and the wall characteristics on the uncertainty of the final magnitudes mainly at the low frequencies regime. In this line, we propose a theoretical calculus of the standard deviation as a combined uncertainty of the standard deviation already proposed in the literature focused in the room geometry and the standard deviation associated to the wall vibrational field.

The object of the present study is to investigate the influence of damping uncertainty and statistical correlation on the dynamic response of structures with random damping parameters in the neighbourhood of a resonant frequency. A Non-Linear Statistical model (NLSM) is successfully demonstrated to predict the probabilistic response of an industrial building structure with correlated random damping. A practical computational technique to generate first and second-order sensitivity derivatives is presented and the validity of the predicted statistical moments is checked by traditional Monte Carlo simulation. Simulation results show the effectiveness of the NLSM to estimate uncertainty propagation in structural dynamics. In addition, it is demonstrated that the uncertainty in damping indeed influences the system response with the effects being more pronounced for lightly damped structures, higher variability and higher statistical correlation of damping parameters.

The fundamental problem from the point of view of pipeline exploitation in KGHM Polska Miedz S.A. is the very high overwearing of the pipes used for the transport of tailings, as well as determining the time of trouble-free operation of pipe system components. Failures involve significant financial outlays, severe restrictions on operation and in some cases even stopping operation. For this reason, it is vital to monitor the condition of the transport systems, as well as to determine the permissible service life of the pipe sections, after which segments at risk should be replaced or turned over in order to extend their further operation. This paper focuses on the application of interval numbers to assess the durability of piping systems. The calculations were made using classical interval numbers by using code written in INTLAB libraries. The correctness of the solutions obtained was verified using the Monte Carlo method, assuming a uniform distribution of random variables.

The multicriteria decision process consists of five main steps: definition of the optimisation problem, determination of the weight structure of the decision criteria, design of the evaluation matrix, selection of the optimal evaluation method and ranking of solutions. It is often difficult to obtain the optimal solution to a multicriterion problem. The main reason is the subjective element of the model – the weight functions of the decision criteria. Expert opinions are usually taken into account in their determination. The aim of this article is to present a novel method of minimizing the uncertainty of the weights of the decision criteria using Monte Carlo simulation and method of data reconciliation. The proposed method is illustrated by the example of multicriterion social effectiveness evaluation for electric power supply to a building using renewable energy sources.

The acoustic climate assessment needed for the selection of solutions (technical, legal and organisational), which will help to minimise the acoustic hazards in the analysed areas, is realised on the basis of acoustic maps. The reference computational algorithms, assigned to them, require very thorough preparation of input data for the considered noise source model representing - in the best possible way - the acoustic climate. These input data are burdened with certain uncertainties in this class of computational tasks. The uncertainties are related to the problem of selecting proper argument values (from the interval of their possible variability) for the modelled processes. This situation has a direct influence on the uncertainty of acoustic maps.

The idea of applying the interval arithmetic for the assessment of acoustic models uncertainty is formulated in this paper. The computational formalism assigned to the interval arithmetic was discussed. The rules of interval estimations for the model solutions determining the sound level distribution around the analysed noise source - caused by possible errors in the input data - were presented. The application of this formalism was illustrated in uncertainty assessments of modelling acoustic influences of the railway noise linear source on the environment.

The objective of the submitted paper is to analyze the influence of the load on the calibration of micro-hardness and hardness testers. The results were validated by Measurement Systems Analysis (MSA), Analysis of Variance (ANOVA) and Z-score. The relationship between the load and micro-hardness in calibration of micro-hardness testers cannot be explained by Kick's Law (Meyer's index "n" is different from 2). The conditions of Kick's Law are satisfied at macro-hardness calibration, the values of "n" are close to 2, regardless of the applied load. The apparent micro-hardness increases with the increase of the load up to 30 g; the reverse indentation size effect (ISE) behavior is typical for this interval of the loads. The influence of the load on the measured micro-hardness is statistically significant for majority of calibrations.

House prices are of special importance for monetary policy since their sudden falls are usually associated with credit crunch followed by long-lasting and painful recessions. Despite several spectacular episodes of such events, each time house prices exhibit long-lasting growth trend with little volatility around it, it is argued that this pattern is a “new normal”. This paper shows that a central bank following this view would increase the volatility of inflation and output as compared to a policy that assumes high volatility of house prices. In the former case the monetary authority would conduct too accommodative monetary policy during abrupt house price expansions significantly increasing output and inflation fluctuations. In the latter situation, in turn, the policy would work well irrespective of the realized house price volatility.

The suitability of several low-labor geostatistical procedures in the interpolation of highly positively skewed seismic data distributions was tested in the Baltic Basin. These procedures were a combination of various estimators of the model of spatial variation (theoretical variogram) and kriging techniques, together with the initial data transformation to normal distribution or lack thereof. This transformation consisted of logarithmization or normalization using the anamorphosis technique. Two variations of the theoretical variogram estimator were used: the commonly used classical Matheron estimator and the inverse covariance estimator (InvCov), which is robust with regard to non-ergodic data. It was expected that the latter would also be resistant to strongly skewed data distributions. The kriging techniques used included the commonly used ordinary kriging, simple kriging useful for standardized data and the non-linear median indicator kriging technique. It was confirmed that normalization (anamorphosis) is the most useful and less laborious geostatistical procedure of those suitable for such data, which results in a standardized normal distribution. The second, not obvious statement for highly skewed data distributions suggests that the non-ergodic inverted covariance (InvCov) estimator of variogram has an advantage over the Matheron’s estimator. It gives a better assessment of the C ₀ (nugget effect) and C (sill) parameters of the spatial variability model. Such a conclusion can be drawn from the fact that the higher the estimation of the relative nugget effect L = C ₀/(C ₀ + C) using the InvCov estimator, the weaker the correlation between the kriging estimates and the observed values. The values of the coefficient L estimates obtained by using the Matheron’s estimator do not meet this expectation.

United Nations Framework Convention on Climate Change obliges member countries to make an inventory of greenhouse gases emission and, among others, an inventory of fugitive emission from coal mining system. To comply with this obligation, basing on 1992 data. Poland has evaluated so-called "emission factors" for identified sources of methane emission. According to IPCC/OECD guidelines, the emission factors multiplied by coal output allow simple evaluation of methane emission. Since the time when the emission factors were evaluated in 1994, coal industry in Poland has undergone major organisational and technical changes. At the same time significant development of basic knowledge on geology of methane in coal-bearing strata have occurred. Both these facts make the emission factors evaluated earlier inaccurate. A wide range of research indispensable for accurate evaluation of new emission factors is described in the paper. It is also recommended in the paper that by the time the research results are known, the improved emission factors. which take into account organisational changes of mining industry should be used. Methane emission from coal mining system in 1999 evaluated using those emission factors equals 527,889 Gg.

An adsorber in which sorption processes occur is one of the key components of an adsorption chiller. Precise real-time monitoring of and supervision over these processes are particularly important to ensure their proper execution. The article describes the experimental stand used for the measurement of the adsorber’s operating parameters and analyses pressure measurement uncertainties, taking into account the impact of the temperature on the test system filled with the adsorbent in the form of silica gel, while concurrently considering the influence of other factors (e.g. the environment, the A/A, and A/D conversion, or data processing) on measurement uncertainties. A complex analysis of uncertainties was carried out, including the results of the statistical analysis of the measurement data obtained from long-term experimental tests of the object and the uncertainties of the pressure measuring chain by the type B method, involving the consideration of interactions between the system components and the temperature impact on the propagation of uncertainties. As part of the analysis, the characteristic stages of the data collection and processing operations related to the sampling rate and measurement intervals were separated. The article presents the prototype test stand and original pressure measurement system for the verification of a single-bed adsorber working below10 hPa.The novel construction of a single-bed adsorberwas used as a test object. Furthermore, in this paper, the developed algorithm of the research method implemented in the system was discussed and positively verified.

The paper presents an evaluation with the Type A and B methods for standard uncertainties of coefficients of a polynomial function of order k determined by n points obtained by measurement of input and output quantities. A method for deriving a posteriori distributions of function coefficients based on the transformation of estimator distributions without assuming any a priori distributions is presented. It was emphasized that since the correct values of the standard uncertainty of type A depend on the √ n-k-3 and not on the p √ n-k-1, therefore, with a small number of measurement points, the use of the classical approach leads to a significant underestimation of uncertainty. The relationships for direct evaluation with the type B method of uncertainties caused by uncorrected systematic additive (offset error) and multiplicative (gain error) effects in the measurements of both input and output quantities are derived. These standard uncertainties are determined on the basis of the manufacturers’ declared values of the maximum permissible errors of the measuring instruments used. A Monte Carlo experiment was carried out to verify the uncertainties of the coefficients and quadratic function, the results of which fully confirmed the results obtained analytically.

Civil engineering is one of the many fields of occurrences of uncertain parameters. The present paper in an attempt to present and describe the most common methods used for inclusions of uncertain parameters . These methods can be applied in the area of civil engineering as well as for a larger domain. Definitions and short explanations of methods based on probability, interval analysis, fuzzy sets, and convex sets are presented. Selected advantages, disadvantages, and the most common fields of implementation are indicated.

An example of a cantilever beam presented in this paper shows the main differences between the methods. Results of the performed analysis indicate that the use of convex sets allows us to obtain an accuracy of results similar to stochastic models. At the same time, the computational speed characteristic for interval methods is maintained.

The uncertainty, threats and risks are unavoidable aspects of human existence. The response to them is trust, the expectation of beneficial, future actions of others (individuals, institutions, organizations). Risk and trust take unique forms during pandemic. Risk is global, universal, hard to assess and attached to common, everyday actions. Trust, the bridge over the abyss of uncertainty, is directed toward three addressees: the government, medicine (medical science, services and products), and the other members of society. For each category the expectations are different. These theoretical considerations are applied and illustrated by the brief history of the pandemic in Poland.

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.

The paper presents analysis of optimisation results of power system stabilizer (PSS) parameters when taking into account the uncertainty of mathematical model parameters of the power system (PS) elements. The Pareto optimisation was used for optimisation of the system stabilizer parameters. Parameters of five stabilizers of PSS3B type were determined in optimisation process with use of a genetic algorithm with tournament selection. The results obtained were assessed from the point of view of selecting the criterion function. The analysis of influence of the parameter uncertainty on the quality of the results obtained was performed.

Referring to the Guide to the Expression of Uncertainty in Measurement (GUM), the paper proposes a theoretical contribution to assess the uncertainty interval, with relative confidence level, in the case of n successive observations. The approach is based on the Chi-square and Fisher distributions and the validity is proved by a numerical example. For a more detailed study of the uncertainty evaluation, a model for the process variability has been also developed.

The main aim of the study was to determine the goodness of fit between the relaxation function described with a rheological model and the real (experimental) relaxation curves obtained for digital materials fabricated with a Connex 350 printer using the PolyJet additive manufacturing technology. The study involved estimating the uncertainty of approximation of the parameters of the theoretical relaxation curve. The knowledge of digital materials is not yet sufficient; their properties are not so well-known as those of metallic alloys or plastics used as structural materials. Intensive research is thus required to find out more about their behavior in various conditions. From the calculation results, i.e. the uncertainty of approximation of the relaxation function parameters, it is evident that the experimental curves coincide with the curves obtained by means of the solid model when the approximation uncertainty is taken into account. This suggests that the assumed solid model is well-suited to describe a real material.

The paper presents a new method for simultaneous tracking of varying grid impedance and its uncertainty bounds. Impedance tracking consists of two stages. In the first stage, the actual noise estimate is obtained from least squares (LS) residua. In the second stage, the noise covariance matrix is approximated with the use of residual information. Then weighted least squares (WLS) method is applied in order to estimate impedance and background voltage. Finally uncertainty bounds for impedance estimation are computed. The robustness of the method has been verified using simulated signals. The proposed method has been compared to sliding LS. The results have shown, that the method performs much better than the LS for all considered cases, even in the presence of significant background voltage variations.

The paper concerns the problem of treatment of the systematic effect as a part of the coverage interval associated with the measurement result. In this case the known systematic effect is not corrected for but instead is treated as an uncertainty component. This effect is characterized by two components: systematic and random. The systematic component is estimated by the bias and the random component is estimated by the uncertainty associated with the bias. Taking into consideration these two components, a random variable can be created with zero expectation and standard deviation calculated by randomizing the systematic effect. The method of randomization of the systematic effect is based on a flatten-Gaussian distribution. The standard uncertainty, being the basic parameter of the systematic effect, may be calculated with a simple mathematical formula. The presented evaluation of uncertainty is more rational than those with the use of other methods. It is useful in practical metrological applications.

The issues connected with the complex design of various facilities, including up-to-date boiler equipment as well as the ways of organizing the space around them, are the reasons why there is often a lack of room for mounting a flowmeter in accordance with the recommendations of manufacturers. In most cases the problem is associated with ensuring sufficient lengths of straight pipe leading into and out of a flowmeter. When this condition cannot be fulfilled, the uncertainty of measurement increases above the value guaranteed by the manufacturer of the flowmeter. This sort of operation problem has encouraged the authors of this paper to undertake research aimed at the analysis of applicability of averaging Pitot tubes in the areas of flow disturbance.

The paper deals with the problem of bias randomization in evaluation of the measuring instrument capability. The bias plays a significant role in assessment of the measuring instrument quality. Because the measurement uncertainty is a comfortable parameter for evaluation in metrology, the bias may be treated as a component of the uncertainty associated with the measuring instrument. The basic method for calculation of the uncertainty in modern metrology is propagation of distributions. Any component of the uncertainty budget should be expressed as a distribution. Usually, in the case of a systematic effect being a bias, the rectangular distribution is assumed. In the paper an alternative randomization method using the Flatten-Gaussian distribution is proposed.

The aim of this study was to estimate the measurement uncertainty for a material produced by additive manufacturing. The material investigated was FullCure 720 photocured resin, which was applied to fabricate tensile specimens with a Connex 350 3D printer based on PolyJet technology. The tensile strength of the specimens established through static tensile testing was used to determine the measurement uncertainty. There is a need for extensive research into the performance of model materials obtained via 3D printing as they have not been studied sufficiently like metal alloys or plastics, the most common structural materials. In this analysis, the measurement uncertainty was estimated using a larger number of samples than usual, i.e., thirty instead of typical ten. The results can be very useful to engineers who design models and finished products using this material. The investigations also show how wide the scatter of results is.