Specific Engineering Research Articles

Verification of material characteristic of natural fibers for concrete reinforcement

The topic of the article is the verification of the tensile mechanical characteristics of selected natural fibres commonly available on the Czech market. Due to their high tensile strengths, some natural materials have a certain potential for use in specific engineering applications such as concrete reinforcement. Additionally, natural fibres are renewable materials, making them an environmentally friendly material. Potentially, its use as a reinforcement in the form of technical textiles for textilereinforced concrete could help create more sustainable reinforced concrete elements. This article deals with tensile tests of chosen available natural fibre materials, such as flax, hemp, jute, and sisal, both pure and impregnated (homogenised) using epoxy resin. In this article, the results and comparisons of tensile strengths and Young’s modulus are presented.

Mechanical strength investigation of chemically reinforced sandy soil using organic copolymers for geotechnical engineering applications

The chemical reinforcement of sandy soils is usually carried out to improve their properties and meet specific engineering requirements. Nevertheless, conventional reinforcement agents are often expensive; the process is energy-intensive and causes serious environmental issues. Therefore, developing a cost-effective, room-temperature-based method that uses recyclable chemicals is necessary. In the current study, poly (styrene-co-methyl methacrylate) (PS-PMMA) is used as a stabilizer to reinforce sandy soil. The copolymer-reinforced sand samples were prepared using the one-step bulk polymerization method at room temperature. The mechanical strength of the copolymer-reinforced sand samples depends on the ratio of the PS-PMMA copolymer to sand. The higher the copolymer-to-sand ratio, the higher the sample’s compressive strength. Sand (70 wt.%)-PS-PMMA (30 wt.%) sample exhibited the highest compressive strength of 1900 psi. The copolymer matrix enwraps the sand particles to form a stable structure with high compressive strengths.

Computation-guided transcription factor biosensor specificity engineering for adipic acid detection

Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.

Titanium Dioxide and Calcium Sulfate Whiskers Are Used for the Preparation of High Performance Polypropylene and Reduce White Pollution.

The anti-aging agent TiO2-polyacrylonitrile (PAN) and the mechanical strengthening agent CSW-PAN were prepared by radical polymerization using rutile nano-titanium dioxide (TiO2) and anhydrous calcium sulfate whisker (CSW) as raw materials. The structures of TiO2-PAN and CSW-PAN were characterized using Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). Simultaneously, the mechanical properties, aging properties, and thermal stability of TiO2-PAN/CSW-PAN/polypropylene (PP) composites were studied, and the results showed that the surfaces of nano-titanium dioxide and calcium sulfate whiskers were successfully grafted with acrylonitrile. Owing to the introduction of new elements, such as acrylonitrile, nano-titanium dioxide and calcium sulfate whiskers have anti-aging properties. In comparison of the impact strength and tensile strength of TiO2-PAN/PP and TiO2-PAN/CSW-PAN/PP before aging, it can be proven that adding CSW-PAN can significantly enhance the mechanical properties of TiO2-PAN/CSW-PAN/PP. After 1000 h of aging, the tensile strength of the ternary composite TiO2-PAN/CSW-PAN/PP was 19.88 MPa when the addition amount of TiO2-PAN and CSW-PAN was 3%. Moreover, the impact strength of the ternary composite material TiO2-PAN/CSW-PAN/PP after 1000 h of aging is even better than that of non-aging pure PP materials, proving that the service life of improved PP products is extended, unnecessary waste and environmental pollution can be relieved, and the needs of specific engineering fields can be met.

RETROFITTED HYBRID ELECTRIC BIKE

At the mention of global warming, the first thing that comes to mind is an increasing number of vehicles in traffic, as well as exhaust gasses these vehicles emit. To control the emissions caused by gasoline vehicles, we aim to offer a cost-effective and more environmentally friendly way to travel. So, this project describes a modified procedure for a conversion of a specific IC engine vehicle into an electric-powered vehicle. In this project, instead of making a normal electric vehicle, we are converting the existing traditional petrol vehicle into an electric vehicle by using the concept of retrofitting. We are using the chassis of the traditional vehicle and with the help of the BLDC Hub motor, battery set, and controller we are using the set of batteries as an energy source. KEYWORDS: Electrical Vehicles, IC Engine, Retrofitting, Chassis, BLDC Hub Motor, Controller And Batteries.

USE OF INTELLIGENT FUZZY IMAGE SEGMENTATION SYSTEMS IN THE PROFESSIONAL TRAINING OF FUTURE SPECIALISTS IN ENGINEERING AND PEDAGOGICAL FIELDS

Relevance: The article addresses the critical issue of integrating intelligent image segmentation systems that utilize fuzzy logic into the training processes for future specialists in engineering and pedagogical fields. This integration is a significant aspect of the digitization of higher education. Aim: The goal is to implement intelligent vehicle image segmentation systems using fuzzy logic to train specialists in engineering and pedagogical fields. Methods: The preliminary processing of the images of the studied objects (vehicles) involved digital filtering methods, contour detection, profile analysis, and contrast enhancement. Image segmentation was performed using watershed methods, contour lines, and region growing. After segmentation, the obtained segments were selected based on size. Fuzzy membership functions were then applied to determine the degree of affiliation of the segments to the meaningful parts of the studied objects, ensuring reliable recognition of these parts and stable operation of the intelligent system despite external influences on the acquired images. Results: A computer system has been developed for the segmentation of vehicle images using fuzzy logic, which has been integrated into the training of specialists in engineering and pedagogical fields. The segmentation methods isolate objects within the images, which are then recognized using fuzzy logic. Thanks to the fuzzy membership functions, elements of vehicle images are reliably recognized even when there is some ambiguity in the shapes of the segments. The practical significance of the developed system is demonstrated through the processing of car images. Conclusions: The integration of the developed system into the educational process provides students with both theoretical knowledge and practical skills related to intelligent image processing systems.

The axially-loaded behaviours of Schwarz Primitive (SP)-based structures: An experimental and DEM study

This study delves into the axial responses of Schwarz Primitive (SP) structures. Emphasising on bearing capacity, force distribution, cracking phenomena, load-displacement curve and energy absorption. Discrete element method (DEM) is adopted to analyse the axial load-bearing behaviour and fracture mechanics of Main SP and Secondary SP structures under various unit cell configurations after validated by experimental tests. The results indicates that despite sharing the same 1/8th cell structure, the axially-loaded behaviours of the Main SP and Secondary SP structures are not identical, particularly in scenarios involving a large unit cell size and a small number of unit cells. The Main SP structures display an axial load-bearing behaviour that is largely unaffected by variations in the number of unit cells along the x and y axes, while Secondary SP structures show a more pronounced improvement in average strength and energy absorption capacity when the number of unit cells increases. Main SP structures offer superior axial load-bearing capabilities and energy absorption efficiency, which is a significant consideration for their application in scenarios demanding high structural integrity. This distinction underlines the importance of tailored design and selection of SP configurations based on specific engineering requirements.

Upgrading of Precast Roof Beam–Column Connections with Seismic Safety Key Devices

To meet the increasing demands for innovations in precast systems with high seismic resistance, in this study, we introduced a novel seismic upgrading technique for roof beam-column (RBC) connections, termed the targeted seismic upgrading (TSU) method, incorporating the innovative seismic safety key (SSK) devices we developed. These devices significantly enhance seismic resilience, offering a substantial improvement over traditional pin-based RBC connections in precast structures, which are known to have limited effectiveness. Our experimental tests on half-scale models of conventional RBC connections, coupled with comprehensive refined finite element method-based nonlinear analytical studies, conclusively demonstrated the enhanced seismic retrofitting capabilities of RBC connections augmented with SSK devices. The paper delineates a technical procedure for applying the SSK, our proprietary innovation, for the targeted seismic upgrading of RBC connections within modern precast systems. Notably, the SSK-upgraded RBC connections exhibited a marked increase in safety, as evidenced by results from experimentally validated nonlinear three-dimensional micro-analytical models. The incorporated flexible design elements in the TSU method ensure its high effectiveness and general applicability for seismic upgrading of both existing and new precast industrial hall structures, offering a significant advancement in this specific seismic engineering topic. Doi: 10.28991/CEJ-2024-010-05-06 Full Text: PDF

Improving environmental indicators of the wheeled tractor diesel engine by using biofuels

The object of this study is the process of operation of a diesel engine in a wheeled tractor on methyl ether of spent frying sunflower oil. The task being solved is to improve the environmental performance of a diesel engine in a wheeled tractor during the operation of its diesel on such biodiesel fuel and its mixtures with mineral diesel fuel. The characteristics of the diesel D-243 were determined by the experimental method with the measurement of the toxicity of the waste gases during its operation on the methyl ether of the spent sunflower oil, mineral fuel, and their mixtures. A decrease in the content of soot in diesel exhaust gases and a slight increase in the types of nitrogen oxides was registered. The theoretical method using a mathematical model determined the indicators of a wheeled tractor during its movement with a trailer for the accepted driving cycle and the operation of its diesel on different fuels. To that end, the characteristics of a specific diesel engine were described by polynomial models. The adequacy of the mathematical model of the movement of a tractor with a trailer over a driving cycle was tested. By means of a mathematical model, the total road emissions of harmful substances of a diesel engine were calculated when the tractor is running with a trailer over the accepted driving cycle. Calculations were performed for two types of fuel: mineral diesel fuel and biodiesel fuel. Biofuel consumption increases by almost 10 % compared to diesel fuel. The total emissions of harmful substances are 1.1 times lower in a diesel engine running on biofuel than when using mineral fuel. The results could be used in the operation of technological transport in the industry and agriculture provided there is a sufficient volume of raw materials for the production of biofuel

Varying Levels of Proficiency in the Delivery of Value Engineering Objectives among Built Environment and Allied Professionals in Kogi State, Nigeria

Value Engineering (VE) practices analyze designed building features, systems, equipment, and material selections to achieve essential functions and enhance results while reducing the life-cycle cost. Hence, the objective of this paper was to evaluate the varying levels of proficiency in the delivery of VE objectives among the Built Environment and allied professionals in Kogi State, Nigeria. Data were harnessed from 94 study questionnaires administered across strata of these professionals in the study area. It was found that Architects, Builders, Engineers, Estate Surveyors and Valuers, and Town Planners in the study area exhibited varied levels of proficiencies across specific value engineering objectives (VEOs), whereas project managers and quantity surveyors exhibited very high-, and high levels of proficiency in the delivery of all the ten VEOs respectively. The variation which is an indication of their diversified skills in project cost management and control was significantly determined by the ten VE objectives commencing with enhancing of project functionality and terminating with minimizing project operating cost. The study recommended project managers and quantity surveyors as first- and second choice professionals in value workshop facilitation, given their high levels of proficiency in the delivery of these VEOs.

History of Education Meets Digital Humanities: A Field-Specific Finding Aid to Review Past and Present Research

ABSTRACT Research in the field of History of Education has experienced a remarkable increase in recent decades. Resulting publications are referenced in generalist databases that do not catalogue academic works according to the specific characteristics of History of Education. Seeking to give response to this bibliographic gap, we are developing a database catered for historians of education that aims to map out present, past, and future research. Conceived within the framework of Digital Humanities/Digital History, Hecumen is being designed, with the aid of Artificial Intelligence, as an open access finding aid that permits (1) conducting specific and multilevel complex engine searches, (2) having a panoramic view of publications; (3) mapping out relevant/missing areas of research, and, ultimately, (4) keeping up to date with the research produced by historians of education. This paper presents, contextualises, and problematises Hecumen – a digital tool that will facilitate and boost History of Education research.

Presentation on the methodology used to calculate the self-rescuing index for communities downstream mining dams

This paper presents the methodology developed to calculate the Self-Rescuing Index for communities downstream of mining tailings dams. An initial calculation formula was developed based on consultations with specialists in engineering, safety, geotechnology, geotechnics, geography, social work, and social sciences. This formula consisted of twenty-two indicators and five indices that make up the final index. The initial results were revised after a new round of consultation using the Delphi method, as well as considering the data available from official sources, Dam Break studies, and primary data collection from communities located in risk areas. The results were georeferenced, enabling a detailed analysis of people's location, their vulnerabilities, as well as of the territory, making a consistent geostatistical tool available for decision-making in managing disaster risks related to mining dams.

Innovation of Course System for Metallurgical Technology Specialty Combining Engineering With Study

With the continuous development of social economy and science and technology, my country's education has also undergone various changes. In order to meet the requirements of the current society, metallurgical technology education in higher vocational colleges must improve the teaching quality from the innovative curriculum system. Vocational colleges themselves are places for cultivating talents for social enterprises, so only by perfecting the curriculum system can the comprehensive ability of students be improved from diversified education. the effective innovation of the curriculum system requires the construction of the higher vocational curriculum system in the mode of combination of work and study. This article mainly focuses on the analysis and research on the innovation of the combined engineering and course system for metallurgical technology majors.

High throughput automated characterization of enamel microstructure using synchrotron tomography and optical flow imaging

The remarkable damage-tolerance of enamel has been attributed to its hierarchical microstructure and the organized bands of decussated rods. A thorough characterization of the microscale rod evolution within the enamel is needed to elucidate this complex structure. While prior efforts in this area have made use of single particle tracking to track a single rod evolution to various degrees of success, such a process can be both computationally and labor intensive, limited to the evolution path of a single rod, and is therefore prone to error from potentially tracking outliers. Particle image velocimetry (PIV) is a well-established algorithm to derive field information from image sequences for processes that are time-dependent, such as fluid flows and structural deformation. In this work, we demonstrate the use of PIV in extracting the full-field microstructural distribution of rods within the enamel. Enamel samples from a wild African lion were analyzed using high-energy synchrotron X-ray micro-tomography. Results from the PIV analysis provide sufficient full-field information to reconstruct the growth of individual rods that can potentially enable rapid analysis of complex microstructures from high resolution synchrotron datasets. Such information can serve as a template for designing damage-tolerant bioinspired structures for advanced manufacturing. Statement of significanceThorough characterization and analysis of biological microstructures (viz. dental enamel) allows us to understand the basis of their excellent mechanical properties. Prior efforts have successfully replicated these microstructures via single particle tracking, but the process is computationally and labor intensive. In this work, optical flow imaging algorithms were used to extract full-field microstructural distribution of enamel rods from synchrotron X-ray computed tomography datasets, and a field method was used to reconstruct the growth of individual rods. Such high throughput information allows for the rapid production/prototyping and advanced manufacturing of damage-tolerant bioinspired structures for specific engineering applications. Furthermore, the algorithms used herein are freely available and open source to broaden the availability of the proposed workflow to the general scientific community.

Financial big data management and intelligence based on computer intelligent algorithm

With the acceleration of China’s economic integration process, enterprises have gained greater advantages in the fierce market competition, and gradually formed the trend of grouping and large-scale. However, as the scale of the company increases, the establishment of a branch also causes many problems. For example, in order to obtain more benefits, the business performance of the company can generate false growth, resulting in financial and operational risks. This paper analyzed the current situation and needs of enterprise financial control from two aspects of theory and practice, combined with specific engineering projects, taking ZH Group as an example, according to the actual situation of the enterprise. The article first introduces the basic situation of the enterprise; Then, the financial control strategy was designed, and different modules were designed to achieve financial control; Afterwards, use a reverse neural network to evaluate the effectiveness of financial management and risk warning; Relying on particle swarm optimization algorithm to seek the optimal solution and applying it to financial management and risk warning, in order to improve the level of introspection and risk management in decision-making. Finally, the value of computer intelligence algorithms in financial big data management is evaluated by constructing a financial risk indicator system. Through the analysis of enterprise financial management, the total asset turnover rate of ZH Group decreased by 0.39 times in 5 years. After 5 years of adjustment of the company’s business, the company’s overall operational capabilities still needed to be improved, and the company’s comprehensive business capabilities also still needed to be improved. Therefore, the application of intelligent algorithms for financial control is very necessary.

Practical Exploration of Simulation Technology Based on Artificial Intelligence in Engineering Design

This paper discusses the application and practice of the simulation technology based on artificial intelligence (AI) in the field of engineering design. By integrating AI into the traditional engineering design process, we can achieve more efficient and accurate design solutions. Taking a specific engineering design project as an example, this article shows how AI simulation technology contributes to design optimization, risk assessment and cost control. The results show that AI simulation technology can not only improve the design quality, but also shorten the design cycle, bringing revolutionary changes to the field of engineering design.

The Soccer-Playing Unicorn – Mitigating Gender Bias in AI-Created STEM Teaching Materials

Artificial Intelligence (AI) tools are increasingly being used in education for various purposes. In particular, AI chatbots such as ChatGPT, with their user-friendly interfaces are being explored in education to co-create teaching materials, provide advice and guidance to educators, simulate classroom scenarios, and offer personalized recommendations to students on how to study and approach subjects. With all the enthusiasm for these new opportunities, one should be aware of the risks due to potential biases in the generated content or the responses. These biases can be associated with factors such as gender, race, religion, or political orientation. As a consequence, educators who are using AI chatbots to (co-)create teaching materials need to have the knowledge and the strategies to mitigate such biases. This paper focuses on one particular type of bias, namely gender bias, and on specific disciplines, namely Science, Technology, Engineering and Mathematics (STEM). Gender bias in STEM education is particularly problematic because it may reinforce existing stereotypes about girls and women in STEM and contribute to their underrepresentation in STEM fields. To raise awareness of these risks of gender bias in AI-co-created STEM teaching materials, this paper identifies risks of gender bias by analysing potential usage patterns of AI chatbots by educators when creating teaching materials. An example of such a risk is if the AI chatbot generates educational materials that primarily portray men as STEM professionals and underrepresent women. This would exacerbate the lack of female role models in STEM. Therefore, strategies are developed that educators can apply to mitigate these risks. These strategies will be demonstrated using practical examples. This will allow them to break the vicious cycle of perpetuating stereotypes in STEM education. In addition, these examples demonstrate how AI chatbots can be used to make STEM education more inclusive, which may include co-creating educational materials tailored to individual interests and learning styles.

Soot aerosols from commercial aviation engines are poor ice-nucleating particles at cirrus cloud temperatures

Abstract. Ice-nucleating particles catalyze ice formation in clouds, affecting climate through radiative forcing from aerosol–cloud interactions. Aviation directly emits particles into the upper troposphere where ice formation conditions are favorable. Previous studies have used proxies of aviation soot to estimate their ice nucleation activity; however, investigations with commercial aircraft soot from modern in-use aircraft engines have not been quantified. In this work, we sample aviation soot particles at ground level from different commercial aircraft engines to test their ice nucleation ability at temperatures ≤228 K as a function of engine thrust and soot particle size. Additionally, soot particles were catalytically stripped to reveal the impact of mixing state on their ice nucleation ability. Particle physical and chemical properties were further characterized and related to the ice nucleation properties. The results show that aviation soot nucleates ice at or above relative humidity conditions required for homogeneous freezing of solution droplets (RHhom). We attribute this to a mesopore paucity inhibiting pore condensation and the sulfur content which suppresses freezing. Only large soot aggregates (400 nm) emitted under 30 %–100 % thrust conditions for a subset of engines (2 out of 10) nucleate ice via pore condensation and freezing. For those specific engines, the presence of hydrophilic chemical groups facilitates the nucleation. Aviation soot emitted at thrust ≥ 100 % (sea level thrust) nucleates ice at or above RHhom. Overall, our results suggest that aviation soot will not contribute to natural cirrus formation and can be used in models to update impacts of soot–cirrus clouds.

Shear modulus and damping ratio of granulated rubber-sand mixtures: Influence of relative particle size

Rubber-sand mixtures (RSM) have gained recognition as a valuable, lightweight, and cost-efficient energy-absorbing material with extensive potential application in engineering construction. However, the small-strain dynamic properties and prevailing mechanisms of RSM have not been thoroughly understood. This study conducted a series of resonant column tests on the small-strain dynamic modulus and damping ratio of RSM, considering the effects of particle size ratio (PSR), rubber content (RC), and confining pressure. The results reveal that the dynamic shear modulus of RSM generally decreases with increasing RC and increases with rising confining pressure. For all RC and confining pressure levels, the maximum dynamic shear modulus of RSM reaches the minimum value as the PSR approaches 1.0. In this case, the dynamic shear modulus of RSM decreases most gently with the strain. The addition of rubber consistently augments the damping ratio, whereas the PSR initially diminishes the damping ratio before eventually enhancing it. Simultaneously, as the PSR is nearing 1.0, the damping ratio achieves its lowest point. Furthermore, new empirical equations were developed to quantitatively analyze the dynamic properties of RSM, in which the predicted values of the dynamic shear modulus and the modulus attenuation coefficient show good agreement with the observed values. This work will facilitate the preparation of artificial RSM-cored geotechnical seismic isolation layers tailored to specific engineering requirements.

A Computationally Efficient Algorithm for Constructing Effective Vector-Valued Seismic Intensity Measures for Engineering Structures

ABSTRACT Seismic intensity measures (IMs) quantify the severity of ground motions and their impacts on structures. They play a vital role in many aspects of earthquake engineering. This paper proposes a novel method, namely the express iteration method (EIM), for constructing effective vector-valued IMs based on dozens of existing scalar ones given a specific engineering structure or a class of them. Taking advantage of the sophisticated while efficient mapping between scalar IMs and engineering demand parameters (EDPs) via a machine learning model, EIM iteratively eliminates less important scalar IMs from a pool of candidates to find the most effective combinations for a vector-valued IM and achieves superior computational efficiency by avoiding updating the nonlinear mapping during the process. Taking a base-isolated structure and its non-isolated counterpart for a demonstrating case study, the performance of the vector-valued IMs determined by EIM is compared with those by other existing methods in the literature for the task of selecting the most unfavorable ground motions. The results show that EIM prioritizes records with the largest peak inter-story drift PIDs and thus leads to the smallest subset that imposes most severe structural damage, while its computational cost was two orders of magnitude smaller as compared to the existing methods of similar effectiveness. Such superior performance can also be expected in all tasks that involve vector-valued IMs, including but not limited to multi-dimensional fragility analysis, incremental dynamic analysis, and real-time seismic damage prediction.