Technical Sciences

Concept and preliminary calculations of an optionally piloted research platform

Paulina Zenowicz, Kamil Zenowicz, Wojciech Skarka — Mon, 29 Jan 2024 00:00:00 +0000

Along with the technological progress, unmanned aerial vehicles have found application not only in a military, but also in civil applications. The article presents Concept and preliminary calculations of an optionally piloted research platform. A literature review revealed a small number of existing aircraft of similar design. The analysis began with basic analytical calculations for airplanes, and more specifically their wings. The initial concept of the external shape of the designed aircraft was determined, and then the initial optimization of the structure was carried out on the basis of mathematical and computer analysis. Another goal of the research will be the construction of a demonstrator and its analysis.

Comparison of pressure-loss evaluation fidelity in turbulent energy dissipation models of poppet check valves using computational fluid dynamics (CFD) software

Maciej Jerzy Kobielski, Wojciech Skarka, Michał Skarka — Mon, 12 Feb 2024 00:00:00 +0000

Check valves are critical components of fluid systems and have various applications, including house appliances. This article presents a methodology for mapping geometry-specific constriction pressure loss as a function of flow and turbulence in a check valve. This study aimed to gain insight on which Ansys Fluent available turbulent energy dissipation model should be used for further design optimization. This methodology consists of a statistical comparison of computational fluid dynamics (CFD) simulation results obtained using the turbulent energy dissipation models. The key components of the simulation process are discussed. The study’s main results are a comparison of empirical results among flow models’ estimated pressure loss, shown as a function of flow rate in specific geometry and identification of the most suitable model for the considered application. This study concludes that the K-Epsilon (Standard) model best represents the empirically measured behavior of naturally occurring flow energy losses in the considered geometry.

Application of Transition Finite Elements in hpq-Adaptive Modeling and Analysis of Machine Elements

Magdalena Zielińska, Grzegorz Zboiński — Fri, 12 Apr 2024 00:00:00 +0000

This paper concerns the modeling and analysis of machine elements using the adaptive finite element method. The adaptation used is of hpq type, which means that the finite element dimension h and element transverse q and longitudinal p approximation order may be different in each element. These parameters are determined automatically by the program to obtain modeling and approximation error levels not higher than the assumed admissible level of the errors. The presented paper focuses on the use of transition elements between basic elements corresponding to the three-dimensional theory of elasticity and the first-order shell model. Three applied transition elements differ in their assumptions regarding the continuity of the displacement, strain, and stress fields between the basic models. The effectiveness of the application of transition elements was assessed in terms of the removal of the internal boundary layer at the boundary between the models and the convergence of adaptive solutions taking into account these models.

Exploring Hu’s moment invariants and Zernike moments for effective identification of two-row and six-row barley varieties

Karolina Szturo — Tue, 14 May 2024 00:00:00 +0000

Barley variety identification is a complex and economically significant task. The identification of two-row and six-row grains is particularly important due to their different characteristics, such as protein and starch content, which have specific implications in different applications. This paper evaluates the effectiveness of discriminating between two-row and six-row barley grains using Hu moment invariants and Zernike moments in combination with various classifiers including linear and SVM classifiers with linear, RBF, polynomial, and sigmoid kernels. The application of Zernike moments and an SVM classifier using an RBF kernel achieved an accuracy level of 99.2%. In comparison, the application of Hu’s moment invariants resulted in an accuracy of 98.5%.

Effect of local airflow restriction in the intake system on the characteristics of a naturally aspirated spark-ignition engine

Michał Janulin, Szymon Piotr Kwiatkowski — Wed, 15 May 2024 00:00:00 +0000

One of the most important elements influencing the functioning of internal combustion engines is the intake system, whose task is to supplycold, fresh and filtered air to the combustion chambers of the engine. So far, the capacity tests of the intake system have focused on the appropriate selection of its geometry and diameter, which had a direct impact on the airflow rate, and thus on the performance of the vehicle. In this article, the focus is on conducting research consisting of placing the airflow restriction element in a specific locationin the intake system of a naturally aspirated spark-ignition engine. After the necessary preparations, authors made measurements of the engine performance (power and torque) and airflow rate in the intake systemvia original MAF sensor mounted in intake system and Chassis Dynamometer Interface via OBD protocol. After the engine parameters were measured, the test results were compared with the reference characteristics obtained during the measurements prior to the modification of the stock intake system. The article is crowned by conclusions based on the results of the measurements.

Evaluation of factors affecting the number of traffic accidents

Piotr Gorzelanczyk, Piotr Piątkowski — Mon, 27 May 2024 00:00:00 +0000

Year after year, the number of traffic accidents is decreasing. This value in recent years has been influenced mainly by the pandemic. However, the value is still very high. For this reason, every effort should be made to reduce the number of traffic accidents. The purpose of this article is to evaluate the factors affecting the number of traffic accidents according to weather conditions. For this purpose, a random selection was made of 10 measurement points in Poland, for which the following parameters were analyzed: traffic volume on the road and the number of accidents at the analyzed points. Based on the study, it can be concluded that the number of road accidents is most influenced by factors such as good weather conditions, as well as cloudy and rainy days. In addition, based on the study, the weights of factors affecting the number of traffic accidents are as follows: good weather 0.5406; rain 0.1529; cloudy 0, 3065.

The Stand characteristics of the GTM 400 MOD turbojet engine

Lukasz Brodzik — Mon, 03 Jun 2024 00:00:00 +0000

Miniaturization of turbine jet engines not only enables testing of fuel mixtures but also opens up new possibilities for their use in smaller aircraft. In this work, measurements were carried out in the GTM 400 MOD engine in order to create the stand characteristics of unit thrust and specific fuel consumption. For both parameters, polynomials were determined describing their changes in the range of rotational speeds used. These calculations constitute the first stage of research on a hybrid turbojet engine powered by aviation kerosene and hydrogen. The reason for the research is to check the possibility of using hydrogen in turbomachinery engines. Hydrogen is one of the fuel additives approved for use by the European Union, which forces the aviation industry to reduce exhaust emissions into the atmosphere. Hydrogen can not only enrich aviation kerosene but also become an alternative fuel.

Neural network architectures in data sequence analysis: diagnosis of Reinke's oedema and Laryngeal polyps

Jarosław Szkoła — Mon, 10 Jun 2024 00:00:00 +0000

In this review paper, we focus our attention on presenting selected neural network architectures dedicated to the analysis of sequential data, in particular to support the diagnosis of Reinke’s oedema and laryngeal polyps. The research discussed here is located in the area of clinical computer decision support systems (CDS) based on the use of artificial recurrent neural networks (RNNs) for speech signal analysis. RNNs are able to predict time series due to their memory and local recurrent connections. In the experimental part, Elman-Jordan artificial neural networks are used, whose characteristics are speed and accuracy in pattern learning allowing real-time decision-making. In the review presented here, one important theme is the use of Bezier curves for preprocessing the speech signal, leading to data reduction and noise elimination. Elman-Jordan networks significantly speed up the learning process and show high classification accuracy in laryngopathy diagnosis.

Evaluation of the influence of the laser alloying with Cr, B and Ni of grey iron parts on their wear resistance

Marta Paczkowska — Thu, 13 Jun 2024 00:00:00 +0000

The aim of this research was to evaluate the influence of the laser alloying with Cr, Cr+B+Ni and B+Ni on the wear resistance of grey iron. Agricultural component (coulter flap) exposed on friction wear (as well as corrosion) in the soil has been take into account as a tested machine part. Even 85% decrease of mass loss of the coulter flap with laser alloyed layer (with nickel and boron) after wear test in comparison to mass loss of flap without laser treatment was achieved. In case of alloying with chromium it was 44% and in case of nickel, boron and chromium this decrease was 58%. Laser alloying in each performed variant caused formation of the modified surface layer consisting of fine grains of mainly martensite enriched with alloy elements, increase of hardness of the surface layer and reduction of roughness parameters of the treated surface in comparison to the base surface.

Experimental and numerical failure analysis of a rotary vacuum disc lime filter - Part 1: Fluid flow study of filtration process

Fri, 19 Jul 2024 00:00:00 +0000

The mechanical separation of solids from liquids (filtration) is a critical process in many chemical process industries. The rotary drum filter can be considered a work-horse device which is one of the oldest filtration devices that has been used for centuries. Its reliability is affected by several process parameters resulting in reduced life and poor separation effectiveness. Common problems include breakage of the filtration medium, wear of filtration holes and breakage of the backing plates. In this work a study is conducted to understand the causes of significant wear exhibited in a single rotary disc vacuum filter to understand the process parameters that led to this failure. The process parameters were recorded and used to validate a CFD model, which in turn was utilised to conduct a parametric study of the systems. The whole study comprises two parts. The first one presents the numerical and experimental analysis of the fluid (water and slurry) flow in the filter, the second one focuses on the numerical and experimental mechanical evaluation of drum filter membrane material.

Analysis of the effect of selected additives of aviation lubricants on their performance properties

Karol Bogucki — Tue, 17 Sep 2024 00:00:00 +0000

The article presents typical lubricants used in aviation and examples of operational problems resulting from, among other things, the introduction of lubricant replacements for old aviation technology or new additives to improve the lubricity of common aviation fuel. A selected aviation fuel additive (DCI-4A) was then analyzed and its effect on a selected engine was studied. FTIR spectrum analysis was also carried on the presence of water using the TN-699 oil as an example. In conclusion, conclusions and recommendation are presented – the implementation of new lubricants and additives requires, in each case, a series of laboratory and bench tests and monitoring of tribological processes in the operation of machinery and equipment.

Forecasting the number of road accidents in Poland using trend models depending on the days of the week

Piotr Gorzelanczyk — Wed, 02 Oct 2024 00:00:00 +0000

Every year a very large number of people die on the roads. Although the number decreases year by year, it remains high. The pandemic has reduced the number of road accidents, but the value is still very high. For this reason, it is necessary to know on which days the highest number of traffic accidents occur, and to know the forecast of accidents by day of the week for the coming years, so that we can do everything possible to minimize the number of traffic accidents. The purpose of the article is to make a forecast of the number of road accidents in Poland according to the day of the week. The research was divided into two parts. The first was the analysis of annual data from the Police statistics on the number of road accidents in Poland in 2000-2021, and on this basis the forecast of the number of road accidents for 2022-2031 was determined. The second part of the research, dealt with monthly data from 2000-2021. Again, the analyzed forecast for the period January 2022 – December 2023 was determined. The results of the study indicate that we can still expect a decline in the number of accidents in the coming years, which is particularly evident when analyzing annual data. It is worth noting that the prevailing pandemic distorts the results obtained. The research was conducted in MS Excel, using selected trend models.

Sustainable acoustics: The impact of AI on acoustics design and noise management

Adam Starowicz, Marcin Zieliński — Fri, 18 Oct 2024 00:00:00 +0000

The collaboration between artificial intelligence (AI) and acoustics marks a groundbreaking advancement in creating optimal soundscapes across various environments. This article explores the profound impact of AI on reshaping acoustics, transitioning from an art form to a precise science. Through AI-driven techniques, architects and designers can now analyze architectural parameters and materials to achieve ideal sound properties in room acoustics design. Additionally, AI plays a pivotal role in noise reduction and control, mitigating unwanted sounds and enhancing auditory clarity. Its application extends to improving speech intelligibility in noisy environments, particularly in modern workplaces, and facilitating environmental noise monitoring for urban planning and noise pollution mitigation. With numerous case studies highlighting AI’s transformative influence, this article provides valuable insights into future innovations and the potential for AI to revolutionize our sonic surroundings. In essence, AI harnesses computer systems to simulate human intelligence processes, optimizing sound environments and revolutionizing the field of acoustics.

From the Cosserats mechanics backgrounds to modern field theory

Waldemar Dudda, Janusz Badur — Wed, 02 Oct 2024 00:00:00 +0000

In the paper, yet weekly known, Cosserats’ original four concepts as follow: the four-time unification of rigid body dynamics, statics of flexible rods, statics of elastic surfaces and 3D deformable body dynamics; the intrinsic formulation based on the local, von Helmholtz symmetry group of monodromy; the invariance under the Euclidean group. The concept of a set of low-dimensional branes immersed into Euclidean space are revalorized and explained in terms of the modern gauge field theory and the extended strings theory. Additionally, some useful mathematical tools that connect the continuum mechanics and the classical field theory (for instance, the convective coordinates, von Mises’ “Motorrechnung”, the Grassmann extensions, Euclidean invariance, etc.) are involved in the historical explanation that how the ideas were developing themself.

Application of artificial intelligence for processing digital ultrasonic images in the shipbuilding industry

Halina Tańska, Jolanta Sala, Bartosz Janiszewski — Thu, 14 Nov 2024 00:00:00 +0000

The article describes the completed research and development work conducted for the shipbuilding industry by a scientific consortium from 2020 to 2023 and addresses selected aspects of the commercialization of the developed prototype solutions. The goal of the R&D project was to develop and implement a modern solution for quality control of welded joints and monitoring of the production process. This article focuses on the application of artificial intelligence (AI) to improve the efficiency and rationality of operational processes, such as welding production processes verified by the advanced PAUT ultrasonic method. The prototype UT/PA system is presented synthetically from the perspective of measurement and analytical components, focusing on the processing of ultrasonic images after measurements and their decision-making potential for improving the quality of welded joints. Synthetic conclusions of a methodological, operational, and strategic nature are highlighted. The planned direction for the continuation of the completed research and development work and the finalized commercialization is also presented.

Operation and challenges of biogas technology: A fundamental overview

Agnieszka Pilarska, Krzysztof Pilarski — Mon, 25 Nov 2024 00:00:00 +0000

The modern world is facing a huge energy crisis related to the depletion of conventional energy sources. Therefore, obtaining energy from alternative sources is sparking increasing interest, expressed by both scientists and entrepreneurs. One such source is biogas, which has great potential to become, along with wind and solar energy, an important renewable energy source (RES). The development of biogas production should proceed in a sustainable manner, meaning it should be economically stable and minimize negative environmental impacts. Its goal is to create efficient and eco-friendly energy solutions – largely based on the use of organic waste – that support a circular economy and help reduce greenhouse gas emissions. Achieving these conditions, however, requires addressing technical challenges, which often include the need to optimize biomass processing and invest in new technologies, issues with substrate heterogeneity, gas management and purification, digestate management, as well as infrastructure and scalability concerns. Sustainable biogas development thus requires solutions to these technical and infrastructure challenges, as well as support from policy and local communities.

Drivers' confidence in advanced drivers assistance systems (ADAS)

Przemysław Drożyner, Paweł Mikołajczak — Mon, 25 Nov 2024 00:00:00 +0000

Road accidents are a serious social problem, both in terms of public health and the costs associated with it, and as individual tragedies. Efforts to reduce the role of human factors in road accidents include partial or full automation of tasks performed by drivers through various types of advanced driver assistance systems. The question arises as to what characteristics of a technology user determine the degree of their trust in it in the context of the functionality and reliability of this technology. Two research questions related to the assessment of technology users (ADAS) of its reliability and effectiveness of operation and the differentiation of these assessments in individual groups of respondents were adopted. Data were obtained through survey research using the CATI (Computer Aided Interaction) technique Assisted Web Interview. 155 respondents participated in the study. As a result of the conducted research, it was found that the oldest systems, used for many years – ABS, airbags, inspire the greatest trust among drivers, while the least popular, used relatively recently – line assistance system. The respondent’s metrics (gender, age, experience) do not affect the perception of the effectiveness and reliability of ADAS; this may be surprising, because it is commonly believed that young people are more willing to use various types of technological innovations. Many respondents have no opinion on the effectiveness and efficiency of ADAS systems – most often these are people who do not have such systems installed in their cars or have not had contact with them. The most “educated” group in terms of knowledge of ADAS are – which is not surprising – professional drivers, although the number of such respondents whose knowledge is negligible (17%) may be surprising.

The use of sewage sludge in anaerobic digestion: formation, properties, and implementation

Agnieszka Pilarska, Tomasz Kałuża, Maciej Pawlak, Tomasz Kalupa — Mon, 25 Nov 2024 00:00:00 +0000

The effect of municipal wastewater treatment, in addition to improving its quality, is sludge formation. Disposal of sewage sludge (SS) is a critical environmental problem that requires careful management. Under current legislation, SS represents waste requiring stabilisation to eliminate pathogenic microorganisms and substances potentially harmful to the environment. Anaerobic digestion (AD) is an efficient method of treating SS, and it produces biogas as a renewable energy source (RES). The efficiency of the process can be increased by combining SS with other organic wastes as cosubstrates. Therefore, AD allows for a twofold benefit crucial for sustainable waste and energy management, i.e. sludge stabilisation and biogas production. Another equally important consideration in the construction of biogas plants at wastewater treatment plants is reducing the plant's operating costs by using the electricity and heat generated in the cogeneration units for the plant's needs. This paper discusses the formation technology and properties of sewage sludge, the legal aspects of using and disposing of SS, the conditions for employing their anaerobic biodegradation, and the co-digestion systems used.

Modeling the phenomenon of ultrasonic wave propagation in selected fluids using Comsol – a case study

Konrad W. Nowak, Agata Wielkopolan — Mon, 02 Dec 2024 00:00:00 +0000

The aim of this study was to model the propagation of acoustic waves with frequencies in the ultrasound range in three selected fluids. Ultrasonic wave propagation in the studied fluids was tested in a laboratory to validate the model. The laboratory tests involved simple measurements of the time of flight of an ultrasonic wave with a frequency of 5 MHz in fluids with different parameters: demineralized water, rapeseed oil, and gelatinized potato starch colloid. In the second part of the study, the COMSOL Multiphysics program was used to develop a model of ultrasonic wave propagation in the same fluids. The model was developed using the Transient analysis type in the Pressure Acoustics application mode of the Acoustics Module. The modeling results were somewhat different from those obtained in laboratory tests; therefore, they did not meet the research assumptions in this stage of research. The limitations of the presented model were discussed. The study demonstrated that medium density was a parameter that exerted the greatest influence on the modeling process.

Development of a method for assessing the quality of barley for brewing using hyperspectral imaging

Piotr Zapotoczny — Mon, 02 Dec 2024 00:00:00 +0000

The paper discusses the utilization of hyperspectral imaging in the process of assessing the quality of barley grain intended for brewing purposes. A specialized research setup comprising a spectrophotometer coupled with a CCD camera was employed. During measurements, the spectral distribution of each pixel in the image was recorded within the range of 400 to 1000 nm, enabling the extraction of homogeneous areas on the grain surfaces. Subsequently, surface texture parameters were computed on the designated areas. Prior to engaging in classification analyses, variable reduction was performed utilizing: (a) Fisher's coefficient, (b) classification error coefficient along with the averaged correlation coefficient POE+ACC, and (c) mutual information coefficient MI. The research material consisted of grain categorized into rain-soaked (B), mold -infested (M), and healthy (H). The best classification results were obtained for a wavelength of 800 nm from the extracted homogeneous areas. The classification accuracy reached 100% across all quality groups.

Application of condition-based monitoring in enhancing mechanical system reliability and proactive structural damage detection

Marjan Djidrov — Tue, 03 Dec 2024 00:00:00 +0000

Technologies, processes, and systems are not immune to failure, which is why robust monitoring systems are crucial to ensure their continued functionality and safety. An interdisciplinary approach that combines engineering, data science, and material science allows for more comprehensive measurement and analysis, enabling better decision-making and more accurate predictions of performance. The integration of these technologies leads to increased safety, reduced human error, and significant cost savings by preventing costly repairs and downtime. Continuous monitoring helps in avoiding catastrophic failures, allowing for early detection of issues before they escalate. Additionally, it opens opportunities for improving the design of mechanical systems and structures, optimizing the organization of maintenance. By reducing human impact and enhancing safety, these monitoring systems offer a more secure and efficient operation. Furthermore, through advanced predictive analytics, the remaining service life can be estimated, facilitating more effective planning. The development of such smart, intelligent mechanical systems and structures promises a future where maintenance is proactive rather than reactive, creating a safer, more sustainable environment for both operators and systems by leveraging advanced sensors, data analytics, and adaptive technologies for real-time monitoring and damage detection.