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.
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 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.
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 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.
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 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.
The consideration of uncertainties in numerical simulation is generally reasonable and is often indicated in order to provide reliable results, and thus is gaining attraction in various fields of simulation technology. However, in multibody system analysis uncertainties have only been accounted for quite sporadically compared to other areas.
The term uncertainties is frequently associated with those of random nature, i.e. aleatory uncertainties, which are successfully handled by the use of probability theory. Actually, a considerable proportion of uncertainties incorporated into dynamical systems, in general, or multibody systems, in particular, is attributed to so-called epistemic uncertainties, which include, amongst others, uncertainties due to a lack of knowledge, due to subjectivity in numerical implementation, and due to simplification or idealization. Hence, for the modeling of epistemic uncertainties in multibody systems an appropriate theory is required, which still remains a challenging topic. Against this background, a methodology will be presented which allows for the inclusion of epistemic uncertainties in modeling and analysis of multibody systems. This approach is based on fuzzy arithmetic, a special field of fuzzy set theory, where the uncertain values of the model parameters are represented by socalled fuzzy numbers, reflecting in a rather intuitive and plausible way the blurred range of possible parameter values. As a result of this advanced modeling technique, more comprehensive system models can be derived which outperform the conventional, crisp-parameterized models by providing simulation results that reflect both the system dynamics and the effect of the uncertainties.
The methodology is illustrated by an exemplary application of multibody dynamics which reveals that advanced modeling and simulation techniques using some well-thought-out inclusion of the presumably limiting uncertainties can provide significant additional benefit.