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Bulletin of the Polish Academy of Sciences Technical Sciences

Bulletin of the Polish Academy of Sciences Technical Sciences

Description

The Bulletin of the Polish Academy of Sciences Technical Sciences is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred:

  • Artificial and Computational Intelligence,
  • Biomedical Engineering and Biotechnology,
  • Civil Engineering,
  • Control, Informatics and Robotics,
  • Electronics, Telecommunication and Optoelectronics,
  • Mechanical and Aeronautical Engineering, Thermodynamics,
  • Material Science and Nanotechnology,
  • Power Systems and Power Electronics.

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Journal Metrics:
JCR Impact Factor 2023: 1.2
5 Year Impact Factor 2022: 1.1
CiteScore 2023: 2.8
SCImago Journal Rank (SJR) 2023: 0.282
Source Normalized Impact per Paper (SNIP) 2023: 0.573
Ministry of Education and Science: 100 points

Abbreviated title: Bull. Pol. Acad. Sci. Tech. Sci.
ISSN
ISSN 2300-1917

Editorial Board 2023-2025

Editor-in-Chief:

A. Rogalski, Military University of Technology

Honorary (Past) Editor-in Chief:

T. Kaczorek, Warsaw University of Technology

M.P. Kaźmierkowski, Warsaw University of Technology

Deputy Editor-in-Chief:

B. Błachowski, Institute of Fundamental Technological Research PAN

M. Mrozowski, Gdansk University of Technology

Board of Topical Co-editors:

Artificial and Computational Intelligence

S. Osowski, B. Sawicki and T. Leś, Warsaw University of Technology

Biomedical Engineering and Biotechnology

D. Pijanowska, Institute of Biocybernetics and Biomedical Engineering PAN

Civil Engineering

L. Czarnecki, Building Research Institute, ITB, Warsaw

Ł. Sadowski, Wroclaw University of Science and Technology

Control, Robotics and Informatics

J. Klamka and A. Babiarz, Silesian Technical University

J. Stefanowski, Poznan University of Technology

Electronics, Telecommunication and Optoelectronics

M. Mrozowski and A. Lamęcki, Gdansk University of Technology

Mechanical and Aeronautical Engineering, Thermodynamics

B. Błachowski, Institute of Fundamental Technological Research PAN

G. Zboiński, Institute of Fluid-Flow Machinery PAN and University of Warmia and Mazury in Olsztyn

Materials Science and Nanotechnology

B. Major and P. Czaja, Institute of Metallurgy and Materials Science PAN

Power Systems and Power Electronics

J. Rąbkowski and M. Jasiński, Warsaw University of Technology

International Editorial Advisory Board

R. Asthana, University of Wisconsin-Stout, Menomonie, USA

Xu Binshi, China Association of Plant Engineering, Beijing, P.R. China

F. Blaabjerg, Aalborg University, Denmark

C. Cecati, University of L’Aquila, Italy

A. Cichocki, RIKEN Institute, Tokyo, Japan

M. David, National Polytechnique de Toulouse, France

R. Ebner, Materials Centre Leoben, Leoben, Austria

E. Fornasini, University of Padova, Padova, Italy

L.G. Franquelo, University of Sevilla, Spain

M. Gad-el-Hak, Virginia Commonwealth University, Richmond, USA

M. Giersig, Free University of Berlin, Germany

D. van Gemert, Catholic University Leuven, KU Leuven, Belgium

L. Keviczky, Hungarian Academy of Sciences, Budapest, Hungary

V. Kučera, Czech Technical University in Prague, Prague, Czech Republic

R. Kennel, Technical University Munich, Germany

T.A. Kowalewski, Institute of Fundamental Technological Research PAN

E. Levi, Liverpool John Moore University, UK

G. Maier, Technical University of Milan, Milan, Italy

K.F. Man, City University of Hong Kong,

R. Maniewski, Institute of Biocybernetics and Biomedical Engineering PAN

H.A. Mang, Austrian Academy of Sciences, Vienna, Austria

H. Mihashi, Tohoku University, Aoba-ku, Sendai, Japan

S. Mindess, University of British Columbia, Vancouver, Canada

D.A. Mlynski, University of Karlsruhe, Karlsruhe, Germany

A.S. Nowak, University of Michigan, Ann Arbor, USA

K. Ohnishi, Keio University, Yokohama, Japan

A. Öberg, Linköping University, Linköping, Sweden

W. Pedrycz, University of Alberta, Canada

M. Razeghi, Northwestern University, Evanston, USA

J. Rodriguez, University of Andres Bello, Santiago, Chile

J.V. Sloten, Catholic University Leuven, Leuven, Belgium

B.M. Wilamowski, University of Auburn, Alabama, USA

A.L. Yarin, University of Illinois at Chicago, USA

Du Xiangwan, Chinese Academy of Engineering, China

J. Żurada, Department of Computer Engineering, University of Louisville, USA

Editorial Office:

Pałac Kultury i Nauki

Wydział IV Nauk Technicznych PAN

Pl. Defilad 1

PL 00-901 Warszawa

Managing Editor:

Renata Podraza, e-mail: Renata.Podraza@pan.pl

Finance:

Katarzyna Łasak, e-mail: Katarzyna.Lasak@pan.pl

The Bulletin of the Polish Academy of Sciences Technical Sciences is an open access journal with all content available with no charge in full text version.


The journal content is available under the licencse CC BY 4.0 https://creativecommons.org/licenses/by/4.0/.

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Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access

1 Identification and Classification of Turn ShortCircuit and Demagnetization Failures in PMSM Using LSTM and GRU Methods
Timur Lale , Gökhan Yüksek
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e15158
Keywords: gated recurrent unit (GRU) long short term memory fault diagnosis PMSM
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Abstract

In a very broad range of industrial applications, especially in electric vehicles, permanent magnet synchronous motors (PMSMs) play an important role. Any failure in PMSMs may cause possible safety hazards, a drop in productivity, and expensive downtime. Therefore, their reliable operation is essential. Accurate failure identification and classification allow for addressing problems before they escalate, which helps ensure the seamless operation of PMSMs and reduces the likelihood of equipment failure. Therefore, in this paper, novel failure identification methods based on gated recurrent unit (GRU) and long short-term memory (LSTM) from recurrent neural network (RNN) methods are proposed for early identification of stator interturn short circuit failure (ISCF) and demagnetization failure (DF) occurring in PMSMs under multiple operating conditions. The proposed methods use three phase current signals recorded from the experimental study under multiple operating conditions of the motor as input data. In the proposed methods, both feature extraction and classification are executed within a unified framework. The experimental outcomes obtained demonstrate that the proposed methods are able to identify a total of six unique motor conditions, including three ISCF variations and two DF variations, with high accuracy. The LSTM and GRU approaches predicted the identification of failures with 98.23% and 98.72% accuracy, respectively. Compared to existing methods, the success of the proposed approaches is satisfactory. In addition, LSTM and GRU-based failure identification methods are also compared in detail for accuracy, precision, sensitivity, specificity and training time in this study.
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Authors and Affiliations

Timur Lale
ORCID: ORCID
Gökhan Yüksek
ORCID: ORCID
2 An Algorithm for Automatically Arranging Flight Training Plans
Pengfei Sun , Jia Liu , Hao Nian
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e151672 | DOI: 10.24425/bpasts.2024.151672
Keywords: flight day plan goal programming algorithm military aviation
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Abstract

With a continued strong pace of artificial intelligence, the way of formulating the flight day plan has a significant impact on the efficiency of flight training. However, through extensive research we find that the scheduling of flight days still relies on manual work in most military aviation academies. This method suffers from several issues, including protracted processing times, elevated error rates, and insufficient degree of optimization. This article provides a comprehensive analysis of automated flight scheduling using Goal Programming algorithm and details the implementation of the corresponding algorithm on the LINGO platform. The study enhances the flexibility and robustness of the model by setting bias variables, wherein the flight courses for students and instructors can be automatically and reasonably scheduled.
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Authors and Affiliations

Pengfei Sun
Jia Liu
ORCID: ORCID
Hao Nian
3 Assessing the equivalent spring modelling method of CFS elements encased in ultra-lightweight concrete
Ahmed Alabedi , Péter Hegyi
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e151384 | DOI: 10.24425/bpasts.2024.151384
Keywords: plate buckling; numerical analysis; equivalent spring model; sustainability
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Abstract

An efficient finite element approach was recently developed to analyse encased cold-formed steel (CFS) structures. This new technique replaced encasing material with unidirectional springs, analogous to the Winkler foundation concept, to shorten the analysis time while ensuring accuracy and reliability in predicting the structural behaviour of encased CFS components. In this paper, the validity, and limitations of the simplified spring model to represent outstanding plates were assessed. The investigation demonstrated that the simplified spring model could effectively predict the ultimate load for a wide range of ultra-lightweight concrete moduli (50-250 MPa) with an acceptable error. The analysis indicated that plate elements initially in cross-section class 4 without encasing material become at least class 3, or better as a consequence of encasing. Previously reported experiments were used to evaluate the performance of the ESM. The analysis demonstrated that the ESM can accurately predict the local failure ultimate load of encased CFS sections with an acceptable error percent and significantly less computational effort than a 3D solid model.
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Authors and Affiliations

Ahmed Alabedi
ORCID: ORCID
Péter Hegyi
4 Trusses of the smallest total potential energy
Sławomir Czarnecki , Tomasz Lewiński
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e151673 | DOI: 10.24425/bpasts.2024.151673
Keywords: topology optimization trusses prescribed displacements
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Abstract

The paper concerns the problem of minimization of the total potential energy of trusses subjected to static loads in the presence of prescribed displacements of selected supporting nodes. The positions of the internal (free) nodes are fixed and the supporting nodes are imposed, the member stiffnesses being design variables, while the truss volume represents the cost of the design. Due to the assumption of the stiffnesses being non-negative, the problem is reduced to a problem of optimization of structural topology. Upon eliminating all the design variables analytically the optimum design problem is eventually reduced to the two mutually dual problems expressed either in terms of member forces or in terms of displacements of free nodes. The problem setting concerning the case when the prescribed displacements of supports are the only loads applied (i.e. kinematic loads) assumes a particularly simple form. A specific numerical method of solving the stress-based auxiliary problem has been developed for the selected 2D and 3D optimal designs. The study is the first step towards topology optimization of trusses with distortions
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Authors and Affiliations

Sławomir Czarnecki
ORCID: ORCID
Tomasz Lewiński
ORCID: ORCID
5 A random field-based simulational identification of possible levels of material imperfections of adhesive-bonded joints
Karol Winkelmann , Jan Faizullah , Łukasz Smakosz , Violetta Konopińska-Zmysłowska , Victor Eremeyev , Marcin Kujawa
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e151678 | DOI: 10.24425/bpasts.2024.151678
Keywords: adhesive-bonded joints adhesive imperfections random fields probabilistic analysis reliability
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Abstract

Recently, structural adhesives have become significant in the shaping of structural elements, especially in thin-walled structures, where they replace or supplement traditional connection methods. However, adhesive-bonded joints are highly susceptible to internal structural imperfections due to their application technique and the nature of the adhesive. These material inconsistencies impact the strength parameters and the mechanical behavior of the entire connection. This study proposes a simplified method for the probabilistic numerical modeling of structural imperfections in an adhesive layer. The adhesive is modeled as an uncorrelated random field with weakened elements representing structural imperfections randomly scattered throughout its entire volume. The percentage of these imperfections (in relation to the total volume) is adopted a random variable. By conducting experimental tests on dogbone specimens of a selected adhesive and comparing them to adequate numerical tests with varying volumes of weakened elements, the determination of the representative imperfection volume of the investigated adhesive was possible. Based on these tests, the calibration of the probability density function to describe the volume of the imperfections may be performed. Furthermore, the application of the random model for an adhesive-bonded single lap-joint is shown to be viable. Finally, the calculation of a probability-based mechanical response (in this case, the normal force at critical elongation) of the single lap-joint with structural imperfections is performed, and its resultant reliability is assessed and evaluated.
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Authors and Affiliations

Karol Winkelmann
Jan Faizullah
Łukasz Smakosz
ORCID: ORCID
Violetta Konopińska-Zmysłowska
Victor Eremeyev
Marcin Kujawa
6 The influence of brace to chord rotational connection stiffness on stability of the truss
Marcin Krajewski
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e151952 | DOI: 10.24425/bpasts.2024.151952
Keywords: truss stability connection rotational stiffness
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Abstract

The paper is devoted to the numerical analysis of the roof truss subjected to upward wind loading and braced at the tensioned top chord. The linear buckling analysis were performed for the beam and shell model of the structure. As the result the influence of rotational connection stiffness between the brace and the top chord on the truss stability was appointed. The biaxial strength testing machine was used to conduct the experimental tests of the rotational connection stiffness between selected steel profiles. The results in the form of measured structural displacements and rotations were presented. The static nonlinear analysis results performed for the shell model of the structural connection were compared to the results obtained on the experimental set-up.
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Authors and Affiliations

Marcin Krajewski
7 Microstructural characteristics of a highchromium cast iron hard-facing alloy
Teresa Faras , Benjamin Koenig , Paul P. Meyer , Ibra Diop
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e151957 | DOI: 10.24425/bpasts.2024.151957
Keywords: arc welding FCAW hard-facing alloys HC-O high-chromium cast iron EBSD micro-hardness
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Abstract

t. Hard-facing alloys increase the service life of components exposed to abrasive, erosive, or metal-to-metal wear conditions. Hard-facing is a metalworking process in which layers of a harder material are arc-welded onto a base metal. In particular, high-chromium hard-face weld deposit layers form a strong metallurgical bond with the substrate steel plate, enhancing the resistance to abrasive loadings. Metallurgical and microstructural analysis is conducted to improve the performance of such bi-layered metal structures. The discussion of an HC-O hard-face alloy deposited on S235 steel substrate plates is hereby presented, focusing on the characterization of the coating’s microstructure. The study establishes the relationship among the chemical composition, ‘as-cladded’ microstructure, and hardness properties of the investigated high chromium Fe–27 wt.% Cr–5 wt.% C hard-facing alloy.
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Authors and Affiliations

Teresa Faras
Benjamin Koenig
Paul P. Meyer
Ibra Diop
8 STAFGCN:A spatial-temporal attention-based fusion graph convolution network for pedestrian trajectory prediction
Guihong Lui , Chenying Pan , Xiaoyan Zhang , Qiangkui Leng
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e151960 | DOI: 10.24425/bpasts.2024.151960
Keywords: pedestrian trajectory prediction micro-level spatial-temporal relationship spatial-temporal attention fusion graph convolution Time-Stacked Convolutional Neural Network
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Abstract

Pedestrian trajectory prediction provides crucial data support for the development of smart cities. Existing pedestrian trajectory prediction methods often overlook the different types of pedestrian interactions and the micro-level spatial-temporal relationships when handling the interaction information in spatial dimension and temporal dimension. The model employs a spatial-temporal attention-based fusion graph convolutional framework to predict future pedestrian trajectories. For the different types of local and global relationships between pedestrians, it first employs spatial-temporal attention mechanisms to capture dependencies in pedestrian sequence data, obtaining the social interactions of pedestrians in spatial contexts and the movement trends of pedestrians over time. Subsequently, a fusion graph convolutional module merges the temporal weight matrix and the spatial weight matrix into a spatial-temporal fusion feature map. Finally, a decoder section utilizes TimeStacked Convolutional Neural Networks to predict future trajectories. The final validation on the ETH and UCY datasets yielded experimental results with an Average Displacement Error(ADE) of 0.34 and an Final Displacement Error(FDE) of 0.55. The visualization results further demonstrated the rationality of the model.
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Authors and Affiliations

Guihong Lui
Chenying Pan
Xiaoyan Zhang
Qiangkui Leng
9 Fixed Switching Frequency Model Predictive Control and Passivity Based Control for DC-DC Converter
Yajing Zhang , Yuqing Shen , BaoYing Huang , Jiangchao Zhang , Haojing Chang
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152209 | DOI: 10.24425/bpasts.2024.152209
Keywords: DC-DC converter FCS-MPC passivity-based control
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Abstract

The DC-DC converter represents a crucial component in the renewable energy sources. The stability and dynamic capability enhancement of the DC/DC converter have emerged as a significant research topic in the current era. Model predictive control (MPC) is particularly prevalent due to its high dynamic response speed, simplicity of the controller design, and capacity for multi-objective optimization. However, the traditional finite control set model predictive control (FCS-MPC) method is suffer to variable switching frequency and vast computing. To improve the dynamic performance of the converter, a novel nonlinear control strategy named fixed switching frequency MPC and passivity-based control (PBC), named FSFPBMPC, is proposed, which could achieve fixed switching frequency and enhance the system's dynamic response speed. Firstly, the Euler-Lagrange (EL) model of the boost converter is established. Secondly, the relationship between duty cycle and MPC is established. Ultimately, the output voltage of PBC is incorporated into the cost function of the FCS-MPC. The characteristics of PBC power shaping and damping injection can enhance the system's immunity to interference, improve the system's dynamic response speed, and thus reinforce the system's stability. Then, depending on MATLAB, the simulation results proved that the proposed strategy has the same effect as we expected.
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Authors and Affiliations

Yajing Zhang
Yuqing Shen
BaoYing Huang
Jiangchao Zhang
Haojing Chang
10 Mechanical energy absorption capacity of the porous Ti-6Al-4V alloy under quasi-static and dynamic compression
Pavlo E. Markovsky , Jacek Janiszewski , Oleksandr O. Stasiuk , Dymitro G. Savvakin , Denys V. Oryshych , Piotr Dziewit
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e151959 | DOI: 10.24425/bpasts.2024.151959
Keywords: porous titanium and alloys mechanical properties high strain rate testing direct impact Hopkinson pressure bar technique microstructure influence deformation mechanism energy absorption
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Abstract

Porous materials are very efficient in absorbing mechanical energy in different applications. In the present study, porous materials based on the Ti-6(wt.%)Al-4V alloy were manufactured with the use of two different powder metallurgy methods: i) blended elemental powder approach using titanium hydride (TiH2) as well as V-Al master alloy powders and ii) using hydrogenated Ti-6-4 pre-alloyed powder. The powder compacts were sintered with additions of ammonium bicarbonate as a pore-holding removable agent. The emission of hydrogen from hydrogenated powders on vacuum sintering and the resulting shrinkage of powder particles permitted the control of the sintering process and creation of anticipated porous structures. Mechanical characteristics were evaluated under quasi-static and dynamic compressive loading conditions. Dynamic compression tests were performed using the direct impact Hopkinson pressure bar technique. All investigations aimed at characterizing the mechanical energy-absorbing ability of the obtained porous structures. The anticipated strength, plasticity, and energy-absorbing characteristics of porous Ti-6-4 material were evaluated, and the possibilities of their application were also discussed. Based on the obtained results, it was found that porous Ti-6-4 material produced with a blended elemental powder approach showed more promising energy absorption properties in comparison with pre-alloyed powder.
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Authors and Affiliations

Pavlo E. Markovsky
Jacek Janiszewski
Oleksandr O. Stasiuk
Dymitro G. Savvakin
Denys V. Oryshych
Piotr Dziewit
11 The influence of the metal phase of novel Al2O3/TiO2/TiAl2O5 composites obtained via a slip casting method
Marcin Wachowski , Justyna Zygmuntowicz , Robert Kosturek , L. Śnieżek , P. Piotrkiewicz , Radosław Żurowski , Karolina Korycka
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152213 | DOI: 10.24425/bpasts.2024.152213
Keywords: ceramic matrix composites TiAl2O5 slip casting composites
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Abstract

This study aims to analyze the ceramic-metal composite Al2O3/TiO2/TiAl2O5 obtained using the slip-casting method. Samples containing 50% vol. of the solid phase and 2% vol. and 4% vol. fractions of the metallic phase were examined. Rheological investigations were performed. Measurements of shrinkage and density of the composites produced were determined. The phase composition of the obtained composite was investigated using SEM/EDS and XRD techniques. Stereological analysis was performed as well. The slip-casting method enables the production of the proposed composite, reinforced by the presence of TiO2 and TiAl2O5. With the increase in the content of the metallic phase in the composite, the thialite phase content increases, but the relative density and volumetric shrinkage of the obtained composites decrease. Thialite grains are characterized by a size in the range of 4 µm to 15 µm, which leads to a low density of the samples. The results revealed that no significant effect of changing the metal phase content of the slurries used for fabricated composites was observed on the limiting grain growth of alumina during the sintering process of slip-casting composites. This finding is important as it suggests that the increase in metallic phase content does not lead to undesirable grain coarsening, which could degrade mechanical properties.
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Authors and Affiliations

Marcin Wachowski
Justyna Zygmuntowicz
Robert Kosturek
ORCID: ORCID
L. Śnieżek
ORCID: ORCID
P. Piotrkiewicz
Radosław Żurowski
Karolina Korycka
12 The influence of multiple processing on selected properties of a new polymer material based on thermoplastic starch
Krzysztof Moraczewski , Cezary Gozdecki , Marek Kociszewski , Bartłomiej Jagodziński , Krzysztof Szabliński , Magdalena Stepczyńska
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152212 | DOI: 10.24425/bpasts.2024.152212
Keywords: thermoplastic starch multiple processing recycling
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Abstract

The study discusses the results of research on the multiple processing of thermoplastic starch-based polymer compositions. The research subject was two compositions from the envifill® M product line (Grupa Azoty, Poland): M30 and MB173, intended for injection applications. The materials underwent four processing cycles, each consisting of extrusion and injection operations. The research included determining the mass flow rate, mechanical parameters (tensile strength, bending strength, Young's modulus, impact strength), thermomechanical parameters (storage modulus as a function of temperature), and thermal parameters (thermal resistance, phase transition temperature). The change in these parameters as a function of the processing rate was examined. It has been shown that if one wants to reuse waste from the tested compositions, MB173 turns out to be a better material. Even though in the case of the M30 material, the changes obtained do not disqualify this material for re-use, a greater control of the degree of prior processing and the amount of waste used is recommended.
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Authors and Affiliations

Krzysztof Moraczewski
Cezary Gozdecki
Marek Kociszewski
Bartłomiej Jagodziński
Krzysztof Szabliński
Magdalena Stepczyńska
13 Mitigating Sensor Quality Issues in UAV System Identification Through Wavelet Decomposition
Pedro Jimenez-Soler , Piotr Lichota
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152216 | DOI: 10.24425/bpasts.2024.152216
Keywords: unmanned aerial vehicle (UAV) wavelet transform time synchronization system identification noise reduction aerodynamics flight mechanics
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Abstract

Unmanned aerial vehicles (UAVs) require precise system identification for optimal performance and safety, yet sensor noise and signal distortion frequently compromise data quality. Recent studies have explored various approaches to mitigate these issues; however, this study introduces a novel method that utilizes wavelet transform techniques, distinctively enhancing UAV sensor signal processing. Unlike conventional methods that primarily focus on noise reduction, this approach employs multi-resolution wavelet decomposition to denoise and align signals effectively, crucial for accurate system identification. This systematic exploration of various wavelet bases and the application of the Output Error Method for correlating signals provide a unique combination not extensively covered in current literature. The technique was validated using simulated sensor data at 50 Hz from a small UAV platform, the Multiplex® Fun Cub, specifically targeting longitudinal dynamics response. Results demonstrated substantial improvements in signal quality, with significantly enhanced correlation coefficients, showcasing the potential of our wavelet techniques to refine UAV system analysis. This paper presents a comprehensive framework for applying wavelet-based techniques in UAV system identification, significantly advancing the robustness and reliability of identification processes and distinguishing our work from existing methods by its integration of wavelet decomposition and advanced system identification techniques
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Authors and Affiliations

Pedro Jimenez-Soler
Piotr Lichota
ORCID: ORCID
14 Evaluation of the Factors Determining Thermal Comfort and Occupational Health Conditions of Employees in Multi-Storey Business Buildings in the Light of Expert Experiences
Murat Cal , Fatih Yilmaz
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152215 | DOI: 10.24425/bpasts.2024.152215
Keywords: thermal comfort occupational health and safety multi-storey buildings AHP data envelopment analysis
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Abstract

Previous studies have generally focused on indoor temperature of buildings and air supplies to their environment. The effect of outdoor pollutants on thermal conditions has also received some attention in recent years. However, the number of studies on other factors that may potentially affect thermal comfort and health in high-rise buildings are limited. A structured Analytical Hierarchy Process and an improved Data Envelopment Analysis method are used in this study to determine the indoor and outdoor spatial features and climatic effects that influence thermal comfort in multi-storey business buildings. The impact levels of these factors on thermal conditions are determined with heuristic algorithms. Further, two climate zones in two countries are compared in terms of the factors that affect thermal comfort and their individual impact levels. The most critical main criterion for Kuwait is external insulation features, whereas for Turkey it is indoor air conditioning. The most critical subcriterion is temperature for Kuwait, whereas for Turkey it is insufficient heat and light insulation of windows. The Data Envelopment Analysis yields that respiratory health diseases are the most critical effect in Kuwait, and work accidents are the most important effect for Turkey. Temperature and humidity play a significant role in thermal comfort in Kuwait. Insulation and air conditioning are crucial factors in thermal comfort conditions in Turkey.
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Authors and Affiliations

Murat Cal
Fatih Yilmaz
15 Introduction to the Investigation of reproduction of the real geometry of UBM panels
Ryszard Walentyński , R Cybulski , Henryk Myrcik
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152214 | DOI: 10.24425/bpasts.2024.152214
Keywords: UBM K-span thin-walled panels 3D scanning arch structures double corrugated steel sheets
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Abstract

The article concisely describes UBM technology (Ultimate Building Machine), that can be used as a solution for buildings and roof structures. The structure of this technology is made of double corrugated thin-walled steel profiles manufactured on the construction site by a self-contained UBM manufacturing factory on wheels. These panels serve as both the building envelope and the structural system. The specificity of the construction poses many design problems, especially the determination of the strength parameters and stiffness of the double-corrugated panels from which the structure is made. The article presents the results of spatial scanning tests of double-corrugated steel sheets, which were carried out using commonly available 3D scanning devices: Leica 3D Disto and MagiScan app. Additionally, results of numerical analyses performed on scanned samples and a comparison of these results with preliminary laboratory tests have been presented in the article. The purpose of scanning was to obtain an accurate and real geometry of the UBM panels, to implement it into a numerical software, and then to perform numerical analyses. Commonly available 3D scanning devices were used because using advanced 3D scanners is not popular nowadays for economic reasons, and hand-built geometric models pose a lot of problems and are not accurate enough. Promising results were obtained, which form the basis for further research.
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Authors and Affiliations

Ryszard Walentyński
R Cybulski
Henryk Myrcik
16 Human-like Decision Making for autonomous lane change driving: a hybrid inverse reinforcement learning with game-theoretical vehicle interaction model
Yalan Jiang , Xuncheng Wu , Weiwei Zhang , Wenfeng Guo , Wangpengfei Yu , Jun Li
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152602 | DOI: 10.24425/bpasts.2024.152602
Keywords: expressway lane-changing scenarios inverse reinforcement learning Stackelberg game theory human-like decision-making interaction model
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Abstract

The development of automated driving vehicles aims to provide safer, comfortable, and more efficient mobility options. However, the decision-making control of autonomous vehicles still embraces limitations on human performance mimicry. These limitations become particularly evident in complex and unfamiliar driving scenarios, where weak decisionmaking abilities and poor adaptation of vehicle behaviour are prominent issues. This paper proposes a game-theoretic decisionmaking algorithm for human-like driving in the vehicle lane change scenario. Firstly, an inverse reinforcement learning (IRL) model is used to quantitatively analyse the lane change trajectories of the natural driving dataset, establishing the human-like human cost function. Subsequently, joint safety, comfort to build the comprehensive decision cost function. Use the combined decision cost function to conduct a non-cooperative game of vehicle lane changing decision to solve the optimal decision of host vehicle lane changing. The host vehicle lane-changing decision problem is formulated as a Stackelberg game optimization problem. To verify the feasibility and effectiveness of the algorithm proposed in this study, a lane change test scenario has been established. Firstly, we analyse the human-like decision-making model derived by the maximum entropy inverse reinforcement learning algorithm to verify the effectiveness and robustness of the IRL algorithm. Secondly, the human-like game decisionmaking algorithm in this paper is validated by conducting an interactive lane-changing experiment with obstacle vehicles of different driving styles. The experimental results prove that the human-like driving decision-making model proposed in this study can make lane-changing behaviours in line with human driving patterns in lane-changing scenarios of expressway.
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Authors and Affiliations

Yalan Jiang
Xuncheng Wu
Weiwei Zhang
Wenfeng Guo
Wangpengfei Yu
Jun Li
17 Impact of Data Particle Divide Depth Level on Effectiveness of Hypergeometrical Divide Classifier
Łukasz Rybak , Janusz Dudczyk
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152603 | DOI: 10.24425/bpasts.2024.152603
Keywords: data information artificial intelligence machine learning information processing hypergeometrical divide data particle data gravitation
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Abstract

Gravitational classifiers belong to the supervised machine learning area, and the basic element that they process is a data particle. So far, many algorithms have been presented in the world literature. They focus on creating a data particle and determining its two important parameters - a centroid and a mass. Hypergeometrical Divide is one of the latest algorithms in this group, which focuses on reducing the amount of processing data and keeping relevant information. A proportion of data to information depends on the data particle divide depth level. Its properties and application potential have been researched, and this article is the next step of the work. The aim of the research described in this article was to determine relation of the depth level value of data particle divide to the effectiveness of the Hypergeometrical Divide algorithm. The research was conducted on 7 real data sets with different characteristics, applying methods and measures of evaluating artificial intelligence algorithms described in the literature. 63 measurements were performed. As a result, the effectiveness of the Hypergeometrical Divide method was defined at each of available data particle divide depth levels for each of used databases.
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Authors and Affiliations

Łukasz Rybak
Janusz Dudczyk
18 Application of thermodynamic equilibrium modelling to predict slagging and fouling tendencies of bituminous coal and wheat straw blends
Karol Król , Dorota Nowak-Woźny , Tomasz Janiczek
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152604 | DOI: 10.24425/bpasts.2024.152604
Keywords: sintering biomass coal FactSage mechanical testing pressure drop test co–combustion
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Abstract

The combustion or co-combustion of biomass or alternative fuels is important in the energy sector because of the need to reduce the share of fossil fuels. This article is a continuation of previous studies on the behaviour of the mineral matter of selected fuels during the sintering processes. The blends of wheat straw biomass from Polish crops (WS) with bituminous coal from the Makoszowa mine (BC) were studied. The study included proximate and ultimate analysis and oxide analysis of ash blends with the following composition: 10wt% WS/90wt%BC, 25wt% WS/75wt%BC and 50wt% WS/50wt%BC. Based on the oxide content, a prediction (using FactSage 8.0 software) of the sintering process of the mixtures tested. The following parameters were determined: slag phase content, specific heat at constant pressure, and ash density. The fracture stresses tests were carried out using the mechanical test. Pressure tests were also performed using the pressure drop test method. The test results of all test methods used were compared with each other. On the basis of this comparison, a clear correlation was found between the sintering temperatures determined by the mechanical method and the pressure drop method and the physical properties of the ashes, such as density and heat capacity, as well as the chemical properties, i.e. the content of the slag phase. The results of the presented research are a valuable addition to the previous work of the authors. The goal of this work is to develop a precise and measurably simple method to determine the sintering temperature of ashes. This is an extremely important issue, especially in the case of the need to use a wide range of fuels in the energy industry.
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Authors and Affiliations

Karol Król
Dorota Nowak-Woźny
Tomasz Janiczek
19 Machine Learning-based Filtering system for fNIRS Signals’ Analysis Purpose
Mariusz Pelc , Dariusz Mikolajewski , Adrian Luckiewicz , Adam Sudol , Patryk Mendon , Edward Jacek Gorzelańczyk , Aleksandra Kawala-Sterniuk
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152605 | DOI: 10.24425/bpasts.2024.152605
Keywords: functional near-infrared spectroscopy biomedical signal processing machine learning; filtering brain signals smoothing filtering cascade filtering
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Abstract

This paper presents a preliminary study delving into the application of machine learning-based methods for optimising parameter selection in filtering techniques. The authors focus on exploring the efficacy of two prominent filtering methods: smoothing and cascade filters, known for their profound impact on enhancing the quality of brain signals. The study specifically examines signals acquired through functional near-infrared spectroscopy (fNIRS), a non-invasive neuroimaging modality offering valuable insights into brain activity. Through meticulous analysis, the research underscores the potential of machine learning approaches in discerning optimal parameters for filtering, thereby leading to a significant enhancement in the quality and reliability of fNIRS-derived signals. The results demonstrate the effectiveness of machine learning-based methods in optimizing parameter selection for filtering techniques, particularly in the context of fNIRS signals. By leveraging these approaches, the study achieves notable improvements in the quality and reliability of brain signal data. This work sheds light on promising avenues for refining neuroimaging methodologies and advancing the field of signal processing in neuroscience. The successful application of machine learning-based techniques highlights their potential for optimizing neuroimaging data processing, ultimately contributing to a deeper understanding of brain function.
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Authors and Affiliations

Mariusz Pelc
ORCID: ORCID
Dariusz Mikolajewski
Adrian Luckiewicz
Adam Sudol
Patryk Mendon
Edward Jacek Gorzelańczyk
Aleksandra Kawala-Sterniuk
ORCID: ORCID
20 Efficacy of modal curvature damage detection in various pre-damage data assumptions and modal identification techniques
Milena Drozdowska , Marek Szafrański , Anna Szafrańska , Agnieszka Tomaszewska
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152217 | DOI: 10.24425/bpasts.2024.152217
Keywords: modal curvature based damage detection stochastic subspace identification eigensystem realization algorithm natural excitation technique masonry tower
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Abstract

The efficacy of modal curvature approach for damage localization is discussed in the paper in the context of input data. Three modal identification methods, i.e., Eigensystem Realization Algorithm (ERA), Natural Excitation Technique with ERA (NExT-ERA) and Covariance Driven Stochastic Subspace Identification (SSI-Cov), and four methods of determining baseline data, i.e., real measurement of the undamaged state, analytical function, Finite Element (FE) model and approximation of current experimental mode shape, are considered. Practical conclusions are formulated based on analysis of two cases. The first is a laboratory beam with a notch and the second is a stonemasonry historic lighthouse with modern restoration in its upper part. The analysis shows that NExT-ERA and SSI-Cov in combination with approximation of current mode shape provide high efficacy in damage localization alongside relatively straightforward determination of baseline data. It proves that the construction of advanced FE models of a structure can be replaced with a much simpler method of baseline data acquisition. Furthermore, the research shows the structural mode shapes identified with ERA may not always indicate the presence of damage.
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Authors and Affiliations

Milena Drozdowska
Marek Szafrański
Anna Szafrańska
Agnieszka Tomaszewska
21 Design of fuzzy dynamic decoupler for a class of Two-Inputs Two-Outputs nonlinear systems
Szymon Król , Paweł Dworak
Bulletin of the Polish Academy of Sciences Technical Sciences | Early Access | e152218 | DOI: 10.24425/bpasts.2024.152218
Keywords: dynamic decoupling TITO plant nonlinear plant experimental modeling fuzzy logic
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Abstract

This paper deals with the problem of designing a dynamic decoupler for a class of Two-Inputs Two-Outputs nonlinear MIMO systems with experimentally modeled dynamics. The work describes the well-known linear theory of dynamic decoupling of TITO plants and discusses problems related to its application to nonlinear systems. The solution of constructing a fuzzy dynamic decoupler with two possible approaches is proposed. The paper gives a practical example of the synthesis of such a system for the air heater, which is an example of nonlinear thermal plant.
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Authors and Affiliations

Szymon Król
Paweł Dworak

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