parametric probabilistic approach Research Papers

Robust optimization and uncertainty quantification in the nonlinear mechanics of an elevator brake system

2025, Meccanica

This paper deals with nonlinear mechanics of an elevator brake system subjected to uncertainties. A deterministic model that relates the braking force with uncertain parameters is deduced from mechanical equilibrium conditions. In order... more

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Application of the Dynamic Programming Method in Process Measurement Problems When Assessing Interoperability

by Igor Prokopovich

2024, Advanced Manufacturing Processes : Book of Abstracts of the 6th Grabchenko's International Conference on Advanced Manufacturing Processes, Odessa, Ukraine, September 10-13

This book offers a timely snapshot of innovative research and developments at the interface between design, manufacturing, materials, mechanical and process engineering, and quality assurance. It covers various manufacturing processes,... more

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Braking deceleration variability of progressive safety gears using statistical and wavelet analyses

by Piotr K Wolszczak

2024, Measurement

The impact of changeable operating conditions on the deceleration of progressive safety gears of PP 16 type and CHP 2000 new design is presented by the authors. The study was performed in the normal (dry friction) operation conditions (S)... more

Table 1: Lift braking model (Fig. 2) parameters. in the next gure (fig. 24) we present the ounulink Model of the braking system. 1M is simplified automatic model without external disturbances. The response of simplified model (see acceleration Fig. 3a) of the lift emergenc braking system consists of the I-VII phases: phase I - the initial state, the motionles system in static equilibrium; phase II - free fall of the lift; initialization of the brak system; phase IV - the movement of looper rolls being able to play; the elevator did nc inhibit the normal operation phase, the designers founded the occurrence of,slack in th cam mechanism, phase V - beginning of the occurrence of the normal component of th direction of movement, likely to produce the friction force; compensates the slack, th hook mechanism as a function of movement of the elevator affects the disc springs, s increasing friction, or deceleration, phase VI - the maximum clamping disc springs; afte reaching the maximum squeeze springs for large enough loading the friction force stop growing, is fixed until you stop the elevator, Phase VII - final state after elevator stopping For better clarity, we plotted also integrated velocity and displacement (Fig. 3a). Zer velocity at the begining and the end of the testileads to the final displacement. Th system is driven by three main force componnentsas effective friction, gravity effect, an finally the force from rope stress (Fig. 3b). The effective friction force is composed ¢ several friction components which are discussed in the next subsection. In our dynamical system, there are two main (however complex) types of friction: kinematic-sliding, static-stiction, and rolling which occur in four elements of the friction mechanism of the elevator speed limiter including:

Braking safety gears belong to the most important systems of all technical facilities. Friction lifts are equipped with two types of the brakes (gears): instantaneous and pro- gressive. Aspects related to the construction and operation of the friction lifts are driven by many authors [1-10]. The research studies described in the literature refer to the most immediate braking systems, which due to their performance characteristics require the use of safety factors. The authors of [5,6] publications raise the issues concerning the con- struction and operation of progressive safety gears with the use of numerical modeling and the impact analysis of the gear construction on the braking distance. Despite the,recent progress in the experimental studies on the elevator dynamics, the literature concerning the description, mathematical analysis of safety gears does not fully reflect all important aspects. Therefore, it is reasonable to study the impact of variable load and variable op- erating conditions as well as the braking process of progressive safety gears. In this study the authors use wavelet analysis to assess the delay value of the progressive safety gears which are subject to variable values and variable loadings under operating conditions. In this paper the authors apply wavelets to characterize the system responses. Bear in mind the fact that wavelets are used in both stationary and.non-stationary conditions with the purpose of diagnosis and monitoring in various technical systems [11, 12]. Figure 1: View on the dynamical system of the lift brake and measurement configuration. The numbers (1)-(8) denote as follows: (1) the progressive safety gears, (2) the lever of the catcher, (3) the terminal line, (4) the strip, (5) the accelerometer, (6) the lift, (7) the guides, and finally (8) the connecting rod. The tow rope is not present in this figure. Introduction

1). In addition to AOP delay parameter also the s parameter of the free fall distance was recorded. It was recorded with an optical sensor of 22 CFR type. It is a manual sensor with a scale calibratedyevery 10 mm and placed on the strip (4). Once the free fall was initiated, the lever (2) of the catcher collided with a terminal line (3) and started the braking process. Lhe height of free fall, at which the system had to lift the frame, was determined based,on the empirical dependence of potential and kinetic energy. The estimated height of free fall h = v?/2g together with technical clearance d; and dy of free fall was 250mmy where h [m]- the height of free fall, vu, = 1.25m/s - the estimated speed of catchers triggering, g = 9.81m/s? - the Earth gravity acceleration, d; =0.1m - the response delay gears factor, dy) =0.03m - the coefficient of excessive play in the braking system.

is not presented in the above figure. The roller moves along the cam 5, the surface of which presses the spring pack washers 4 with changeable braking force as per the position of the roller suitable to the braking plate deceleration. Decelerating movement of the roller is thus adjusted to the movement of the cam. The movement goes in one direction, with no further lateral movement.,Braking process with the use of CHP 2000 type gears can be divided into two stages: the idle and the actual one. The position of the braking roller changes from the central one to the position of contact with the guide roller surface during deceleration of the,idle part of the braking process. Deceleration is implemented in a right way with Belleville springs at the contact position with the guide roller surface till the system fully stops. ee ee giao os

Figure 6: The measurement results of elevator braking acceleration versus time delay for various types of the safety gears depending onthe operating conditions and applied load: (a) gears of CHP 2000 type with the load of 1OkN under lubricated operating conditions; (b) gears of CHP 2000 type withthe load of 10kN under operating conditions without lubrication; (c) gears of CHP 2000 type with the load of 4kN under lubricated operating conditions; (d) gears of CHP 2000 type with the load of 4kN under operating conditions without lubrication;,(e) gears of PP 16 type with the load of 1OkN- under lubricated operating conditions; (f) gears of PP 16 type with the load of 10kN- under operating conditions without lubrication; (g) gears of PP 16 type with the load of 4kN under lubricated operating conditions; (h) gears of PP 16 type with the load of 4kN- under operating conditions without lubrication. Red colour indicates the parts of time series which actively contribute to the braking process. Note that acceleration values in the accelerometer/used inside the lift differs from acceleration of the lift itself (Fig. 3) by ae

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Modeling random uncertainties in voice production using a parametric approach

by jorge Lucero

2024, Mechanics Research Communications

The biomechanical system of voice production has been usually modeled as deterministic. However, when uncertainties of the parameters are considered, voice production must be regarded as a stochastic process. We follow a parametric... more

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Protecting Objects of Critical Information Infrastructure from Wartime Cyber Attacks by Decentralizing the Telecommunications Network

by Pavlo Skladannyi and

2024, Cybersecurity Providing in Information and Telecommunication Systems

The environment is changed by people, both unconsciously and consciously. The engineering and economic development of the environment is complemented by actions that involve deliberate destruction. Since 2014, units of the Russian army... more

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Strategy of building a wireless mobile communication system in the conditions of electronic counteraction

by Bogdan Lazurenko

2024, Radioelectronic and Computer Systems

The subject of research in this article is the process of building a mobile communication system that operates under electronic countermeasures. The aim is to develop recommendations for building a wireless mobile communication system... more

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Essence of radio signals processing in close range reconnaissance

by Volodymyr Tymchuk

2024

In this paper the approach to make a high resolution in radar is given. The structure of radar system with projector matrix filters is depicted.

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Активно-пасивний імпульсно-шумовий радар діапазону 3мм та результати його попередніх випробувань

by Олег Грибский

2023, Radioelectronic and Computer Systems

The subject of this manuscript is broadband noise signals and systems. The aim of this research is to show the results of a modern active-passive 3-mm waveband system consisting of a noise-pulsed radar and a radiometer. Noise radar... more

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Essence of radio signals processing in close range reconnaissance

by Volodymyr Tymchuk

2023

In this paper the approach to make a high resolution in radar is given. The structure of radar system with projector matrix filters is depicted.

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Dynamics of thin-walled composite beams: Analysis of parametric uncertainties

by Rubens Sampaio

2023, Composite Structures

In this article a non-linear model for dynamic analysis of rotating thin-walled composite beams is introduced. The theory is deduced in the context of classic variational principles and the finite element method is employed to discretize... more

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Experimental Evaluation of an Accelerating Lens on Spatial Field Structure and Frequency Spectrum

by Dmytro Ageyev

2023, 2020 IEEE Ukrainian Microwave Week (UkrMW)

The results of experimental studies of the effect of an accelerating metal plate lens used to increase the signal level in the direction of the remote subscriber of the wireless access system on the frequency spectrum of the received... more

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Features of the Implementation of Computer Vision in the Problems of Automated Product Quality Control

by Ihor Mastenko

2023, Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

The article analyzes the fields of application of machine vision. Special attention is focused on the application of Machine Vision in intelligent technological systems for product quality control. An important aspect is a quick and... more

Fig. 4. Defective reed tube, in the control area Noise removal is the main procedure for signal amplification, for this preliminary control the area is highlighted in white, for better detail and additional illumination of the control area is added (Fig. 4) The database used by the image identification algorithm contains collected product image samples labelled according to classifiers, separated in an indicative way on the training and evaluation images. In the training phase, training images are performed for continuous parameter correction with a supervised learning approach to minimize prediction errors. However, model evaluation is essential to find a good network structure and an appropriate learning strategy, thus obtaining a practical model for identification and retention. Finally, the built classification model analyzes the processed image in real-time and provides feedback to the next controller ("defective product", "refinish defect" or "defect-free product").

Fig. 2. Collection of data from samples of reed tubes and their quality control According to the peculiarity of the products, namely the various natural factors of shape, pigmentation and colour. The technological process involves the application of a continuous control method. It includes the distribution of products according to eleven quality characteristics, which include various defects: cracks, damage by pests, pigmentation, length deviations, diameter distribution and deviations from the shape. We proposed using optical cameras that work by analogy with the human eye to determine these characteristics. The use of ultrasonic or infrared sensors does not provide a complete picture due to the local concentration of the investigated area. The use of mechanical contact methods is limited by the variety of product shapes.

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Diagnosis of the Technical Condition of High-tech Complexes by Probabilistic Methods

by Valerii Shevchenko

2023, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation

When designing multilevel systems for monitoring the parameters and characteristics of high-tech complexes, it is necessary to effectively control the state of the elements of generating units. Existing control systems for their... more

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Dynamics of thin-walled composite beams: Analysis of parametric uncertainties

by Marcelo Piovan

2023, Composite Structures

In this article a non-linear model for dynamic analysis of rotating thin-walled composite beams is introduced. The theory is deduced in the context of classic variational principles and the finite element method is employed to discretize... more

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Diagnosis of the Technical Condition of High-tech Complexes by Probabilistic Methods

by Vitalii Budashko

2022, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation

When designing multilevel systems for monitoring the parameters and characteristics of high-tech complexes, it is necessary to effectively control the state of the elements of generating units. Existing control systems for their... more

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Sparse Cellular Radio Network

by Sergii Kravchuk

2022, InterConf

The wireless telecommunications environment is characterized by high variation in signal strength, and architectural constraints are imposed on the placement of radio access points. As an extreme case, it can be assumed that the location... more

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Radio-Heat Contrasts of UAVs and Their Weather Variability at 12 GHz, 20 GHz, 34 GHz, and 94 GHz Frequencies

by Nataliia Kuzmenko

2022, ECTI Transactions on Electrical Engineering, Electronics, and Communications

This work describes the procedure for determining the expected values of UAV radio-heat contrasts () and discusses its angular dependences, as well as the estimation of UAV detection distances at four points cm and mm ranges (12 GHz, 20... more

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Assessing the Operator’s Readiness to Perform Tasks of Controlling by the Unmanned Aerial Platforms

by Volodymyr Nakonechnyi

2022, Advances in Science, Technology and Engineering Systems Journal

A R T I C L E I N F O A B S T R A C T Article history: Received: 09 July, 2020 Accepted: 19 July, 2020 Online: 09 August, 2020 Together with the intensity of development in the field of technology of unmanned platforms and their effective... more

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Data representing and processing in expert information system of professional activity analysis

by Олег Зарицкий

2022, 2016 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET)

In this paper the results of linguistic variables presentati which are basis of data input and processing modules in information systems of professional activity analysis and estimation are given.

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Calculation of the field of periodically nonuniform dielectric plate by the method of A.F. Chaplin

by V Pavlysh

2022, 2011 VIII International Conference on Antenna Theory and Techniques

Efficiency of application of A.F.Chaplin's method on the example of calculation of the field of periodically nonuniform dielectric plate is shown. The essence of the method, features of its application is described. The estimation of... more

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Diagnosis of the Technical Condition of High tech Complexes by Probabilistic Methods

by Vitalii Budashko

2022, International Journal on Marine Navigation and Safety of Sea Transportation

When designing multilevel systems for monitoring the parameters and characteristics of high-tech complexes, it is necessary to effectively control the state of the elements of generating units. Existing control systems for their... more

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Robust optimization and uncertainty quantification in the nonlinear mechanics of an elevator brake system

by Szymon Molski

2021, Meccanica

This paper deals with nonlinear mechanics of an elevator brake system subjected to uncertainties. A deterministic model that relates the braking force with uncertain parameters is deduced from mechanical equilibrium conditions. In order... more

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Robust optimization and uncertainty quantification in the nonlinear mechanics of an elevator brake system

by Piotr K Wolszczak

2021, Meccanica

This paper deals with nonlinear mechanics of an elevator brake system subjected to uncertainties. A deterministic model that relates the braking force with uncertain parameters is deduced from mechanical equilibrium conditions. In order... more

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Application of a stochastic version of the restoring force surface method to identify a Duffing oscillator

by Americo Cunha Jr

2020, Nonlinear Dynamics of Structures, Systems and Devices

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Robust optimization and uncertainty quantification in the nonlinear mechanics of an elevator brake system

by Americo Cunha Jr

2019, Meccanica

This paper deals with nonlinear mechanics of an elevator brake system subjected to uncertainties. A deterministic model that relates the braking force with uncertain parameters is deduced from mechanical equilibrium conditions. In order... more

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Modeling and Quantification of Physical Systems Uncertainties in a Probabilistic Framework

by Americo Cunha Jr

2019, Probabilistic Prognostics and Health Management of Energy Systems

Uncertainty quantification (UQ) is a multidisciplinary area, that deals with quantitative characterization and reduction of uncertainties in applications. It is essential to certify the quality of numerical and experimental analyses of... more

Fig. 8 (a) Solution verification: comparison between toy model response and reference solution; (b) absolute error of Runge-Kutta method approximation. Modeling and Quantification of Physical Systems ...

Fig. 5 The difference between verification and validation. to check if the model equations provide an adequate representation of the physical phenomenon/system of interest. The proper way to do this “valida- tion check up” is through a direct comparison of the model responses with experimental data carefully obtained from the real system. It is an exercise in physics. In Figure 5 the reader can see a schematic representation of the difference between the two notions.

Fig. 11 These samples are realizations of a standard Gaussian random variable. In practice, these estimators are used when we do not know the random variable distribution. However, to illustrate the use of these tools, let us con- sider a dataset with N = 100 samples obtained from the (standard) Gaussian random variable %, with zero mean and unity standard deviation. Such sam- ples are illustrated in Figure 11. Considering these samples, we can construct the two estimators shown in Figure 12, with the empirical CDF on the left and a histogram on the right. Scenario 2: little or even none experimental data is available

Fig. 2 Illustration of a possible notion of validated model. tal value (defined by the point and its error bar) is contained within the reliability envelope around the simulation.

Fig. 7 Response obtained with the toy model. Imagine that we have developed a computer code to integrate this IVP using a standard 4-th order Runge-Kutta method [25]. The model response obtained with this computer code is shown in Figure 7.

Fig. 9 (a) Model validation: comparison between experimental data and the toy model, (b) comparison between experimental data, the toy model, and the improved model.

Fig. 1 (a) Comparison between simulation and experimental data, without an envolepe of reliability for the simulation, and (b) including this envelope.

Fig. 4 The difference between errors and uncertainties. Naturally, uncertainties affect the response of a computational model, but they should not be considered errors because they are physical in nature. Errors are purely mathematical in nature and can be controlled and reduced to a negligible level if the numerical methods and algorithms used are well known by the analyst [19], [4]. This differentiation is summarized in Figure 4. 2.2 Verification and Validation

The Gaussian distribution is a bad choice since K must be a positive- valued random variable (almost sure). Thus, we know the following informa- tion about kK: For physical considerations, it is necessary that the model response U be a second-order (finite variance) random variable, i.e., . E {u*} < +00. Is this possible when we arbitrate the probability distribution as Gaussian? No way! Just do a simple calculation

Table 1 Maximum entropy distributions for given known information.

Fig. 14 An overview of Monte Carlo algorithm. An overview of the MC algorithm can be seen in the Figure 14. First, the MC method generates N realizations (samples) of the random parameters according to their joint distributions (stochastic model). Each of these re- alizations defines a deterministic problem which is then solved (processing) using a deterministic technique, generating a certain amount of data. Then, these data are combined through statistics, to access the response of the ran- dom system [58], [55]. By the nature of the algorithm, we note that MC is a non-intrusive method.

Fig. 12 (a) Estimators for the probability distribution of %: the empirical CDF, and (k a histogram.

Fig. 13 Schematic representation of uncertainty propagation problem. Very succinctly, we understand the uncertainty propagation problem as to determine the probability distribution of model response once we know the distribution of model input/parameters. A schematic representation of this problem is can be seen in Figure 13. The methods for calculation of uncertainty of propagation are classified into two types: non-intrusive and intrusive.

Fig. 3 Schematic representation of the relationship between the designed system, the real system and the computational model [19]. Let’s start with three conceptual ideas that will be relevant to the stochas- tic modeling of physical systems: designed system, real system and computa- tional model. A schematic illustration of these concepts is shown in Figure 3.

Fig. 6 V&V example: a skydiver in free fall from an initial height yo. An example in V&V: A skydiver jumps vertically in free fall, from a heli- copter that is stopped in flight, from a height of yo = 2000 m with velocity vo = 0 m/s. Such situation is illustrated in Figure 6. Imagine we want to know the skydiver height in every moment of the fall. To do this we develop a (toy) model where the falling man is idealized as point mass m = 70 kg, under the action of gravity g = 9.81 m/s*. The height at time t is denoted by y(t).

Fig. 10 Mechanical system composed by a fixed spring and a constant force. Consider the mechanical system which consists of a spring fixed on the left side of a wall and being pulled by a constant force on the right side (Fig- ure 10). The spring stiffness is k, the force is represented by f, and the spring displacement is denoted by u. A mechanical-mathematical model to describe this system behaviour is given by

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