Areas Of Engineering Research Articles

Experimental Study on the Strength Deterioration and Mechanism of Stabilized River Silt Reinforced with Cement and Alginate Fibers.

River silt deposited by water in coastal areas is unsuitable for engineering construction. Thus, the in situ stabilization treatment of river silt as the bearing layer has been an important research area in geotechnical engineering. The strength degradation behavior and mechanism of stabilized river silt reinforced with cement and alginate fibers (AFCS) in different engineering environments are crucial for engineering applications. Therefore, freeze-thaw (F-T) cycle tests, wetting-drying (W-D) cycle tests, water immersion tests and seawater erosion tests were conducted to explore the strength attenuation of stabilized river silt reinforced with the same cement content (9% by wet weight) and different fiber contents (0%, 0.3%, 0.6% and 0.9% by weight of wet soil) and fiber lengths (3 mm, 6 mm and 9 mm). The reinforcement and damage mechanism of AFCS was analyzed by scanning electron microscopy (SEM) imaging. The results indicate that the strength of AFCS was improved from 84% to 180% at 15 F-T cycle tests, and the strength of AFCS was improved by 26% and 40% at 30 W-D cycles, which showed better stability and excellent characteristics owing to the hygroscopic characteristics of alginate fiber arousing the release of calcium and magnesium ions within the alginate. Also, the strength attenuation of AFCS was reduced with the increase in the length and content of alginate fibers. Further, the strength of specimens in the freshwater environment was higher than that in the seawater environment at the same fiber content, and the softening coefficient of AFCS in the freshwater environment was above 0.85, indicating that the AFCS had good water stability. The optimal fiber content was found to be 0.6% based on the unconfined compressive strength (UCS) reduction in specimens cured in seawater and a freshwater environment. And the strength of AFCS was improved by about 10% compared with that of cement-stabilized soil (CS) in a seawater environment. A stable spatial network structure inside the soil was formed, in which the reinforcing effect of fibers was affected by mechanical connection, friction and interfacial bonding. However, noticeable cracks developed in the immersed and F-T specimens. These microscopic characteristics contributed to decreased mechanical properties for AFCS. The results of this research provide a reference for the engineering application of AFCS.

Stability, modulation instability and traveling wave solutions of (3+1)dimensional Schrödinger model in physics

The nonlinear Schrödinger equation is one of the most important physical model in optical fiber theory for comprehension of the fluctuations of optical bullet development. In this study, the exact bullet solutions for the (3+1)-dimensional Schrödinger equation which demonstrate the bullet behaviours in optical fibers can be accumulated through the Sardar sub-equation method and the unified method. The applied strategies may retrieve several kinds of optical bullet solutions within one frameworks as well as is quite simple and reliable. Mathematica are utilised for describing the dynamics of different wave structures as 3D, 2D, and contour visualisations for a given set of parameters. As a result, we are able to develop a variety of travelling wave structures namely the periodic, singular and V shaped soliton wave solutions. The stability analysis for the derived results is analysed efficiently while the modulation instability for the governing model has also been studied to demonstrate the reliability of the research. The approaches implemented here works perfectly and can be extended to deal with many advanced models in contemporary areas of science and engineering. The solutions attain by using these techniques are robust, unique and straight forward and has applications in different fields of physics, engineering and mathematical science. Specially physical applications of these obtain results are in the transmission of data in optical fibers. We also add the graphics for the better understanding of the attain solutions behaviour.

Method for the consideration of statistically distributed geometrical deviations in the design of cylindrical roller bearing arrangements

Rolling bearings are of great importance in all areas of mechanical engineering due to their precise and low-friction guidance of rotating components at low cost. The design of rolling bearing arrangements is usually based on approximately ideal geometries of bearings and adjacent parts on which the bearing seats are located. However, real components inevitably show statistically distributed deviations from their nominal shapes, which are limited by tolerances. Tight tolerances result in high manufacturing costs while on the other hand their expansion leads to an increase of occurring geometrical deviations which cause changes in the bearing-internal contact and load conditions and can thus impair the operating behavior of the bearing, e.g. with regard to fatigue life, frictional torque or vibration behavior. By taking these effects into account in the design stage, potential problems in operation can be identified early during development and countermeasures can be taken, e.g. by adjusting bearing and seat tolerances. This enables an improvement of overall product quality and a reduction of costs. This paper presents a method for the integration of component deviations in the computation of the fatigue life (Lnmr) and dynamic behavior of cylindrical roller bearing arrangements—both of which are crucial design criteria—based on a combination of statistical tolerance analysis and multi-body simulations. The method is applied to an exemplary use case for illustration.

Analysis of Diaphragm Force on Reinforced Concrete Building Structures with Horizontal Irregularities of Diaphragm Discontinuity

The diaphragm plays a crucial role in distributing seismic forces within buildings during earthquakes, affecting both regular and irregular structures differently. This study investigates the seismic behavior of diaphragms in various building geometries resembling the letters I, T, L, and O, focusing on their influence on structural performance and reinforcement requirements. Using analytical methods, diaphragm seismic forces, slab shear stresses, and internal forces were calculated for a sample of buildings with different geometrical irregularities. The study reveals significant differences in diaphragm earthquake forces between regular and irregular buildings, with irregular geometries exhibiting distinct patterns of shear stress distribution. Particularly, the building with an L-shaped plan and concentrated stress points showed the highest maximum shear stresses in both orthogonal directions. Analysis of internal forces—axial, shear, and moment—highlighted varying reinforcement needs among the studied buildings. While axial and shear forces necessitated minimal additional reinforcement across all structures, moment forces indicated substantial reinforcement requirements, particularly in the L-shaped building. These findings underscore the importance of tailored diaphragm design strategies for buildings with irregular geometries to mitigate potential structural vulnerabilities during seismic events. The study contributes insights into optimizing diaphragm design practices and emphasizes the need for further research in this critical area of structural engineering.

Design and comparison of particle swarm optimization tuned Kalman filter based linear quadratic Gaussian controller and linear quadratic regulator for surface to air missile guidance system

AbstractThe study of missile guidance systems is a well‐known nonlinear control engineering area of research. To enhance the control performance of a missle guidance system, several technologies have been proposed in existing works. To resolve the weighting matrix selection issue of a linear quadratic Gaussian (LQG) controller for the surface‐to‐air missile guidance control system, this study utilizes the particle swarm optimization (PSO) technique. Selecting the best state (Q) and input (R) weighting matrices is a significant difficulty in the design of the LQG controller for real‐time applications since it affects the controller's performance and optimality. The weighting matrices are often chosen by a trial‐and‐error method that not only complicates the design but also does not yield optimal outcomes. Therefore, in this paper, a PSO method is developed and used in the design of the linear quadratic regulator (LQR) and LQG controllers for the surface‐to‐air missile control system to choose the elements of the Q and R matrices in the best possible way. Finally, a comparative analysis between the designed controllers was presented. The results shows that a good performance was achieved by using the proposed PSO‐tuned design process. The LQG and LQR are designed by manually adjusting the weighting matrices and utilizing an intelligent procedure, PSO algorithm which achieved optimal results. Further results indicate that the designed controllers, the PSO tuned LQR and LQG achieved a better performance over the manually adjusted LQR and LQG controllers.

Multi-technique characterization and thermal degradation study of epoxy modified resins designed for multifunctional applications

Tetraglycidyl methylene dianiline (TGMDA) was mixed with 1,4-Butanediol diglycidyl ether (BDE) (in a 4:1 mass ratio) and with a stoichiometric amount of the curing agent diaminodiphenyl sulfone which was solubilized at 120 °C for 20 min in the liquid mixture TGMDA + BDE. The so obtained unfilled epoxy resin matrix, denoted as ER, was blended with glycidyl polyhedral oligomeric silsesquioxane and carbon nanotubes in suitable proportions to obtain binary and ternary mixtures. Characterization of the formulated materials was performed using different experimental techniques, such as Dynamic mechanical analysis, Thermogravimetry (TG), Field emission scanning electron microscopy. Furthermore, the investigation of the flame behavior was carried out by the limiting oxygen index and mass loss calorimeter measurements. Direct current measurements and investigation by Tunneling atomic force microscopy of the conductive nanodomain map allowed the evaluation of the electrical properties of the developed nanofilled systems. The TG data related to thermal decomposition of ER and its binary and ternary mixtures were processed according to isoconversional kinetic analysis by assuming a non-Arrhenian behavior of the temperature function, and lifetime prediction was estimated at suitable relatively low temperatures and possible relation between the thermal stability and the presence of each component was discussed. This method of kinetic analysis paves the way for the possibility of evaluating in a more realistic way, on the basis of thermal stability, the potential application of structural resins with primary load functions in contact with hot areas of aeronautical aircraft engines.

Optimization of micro‐rotation effect on magnetohydrodynamic nanofluid flow with artificial neural network

AbstractIt is a major research area in mathematics, physics, engineering, and computer science to study the heat and mass transfer properties of flow. Suspensions containing multiple nanoparticles or nanocomposites have recently gained a wide range of applications in biological research and clinical trials under certain conditions. Nanofluids are important suspensions that allow nanoparticles to disseminate and behave in a homogeneous and stable environment. Therefore, here magnetohydrodynamic micropolar nanofluid flow towards the stretching surface with artificial neural network has been considered. In this study, radiation and heat source phenomena have been presented in heat convection. Brownian and thermophoresis effects and micro‐rotational particles are also taking into account. The non‐linear simplified equations have been calculated numerically via Runge‐Kutta fourth‐order shooting process. The calculation of the Sherwood number, Nusselt number, couple stress coefficient, and skin friction coefficient has been conducted utilizing diverse parameters. Furthermore, the outcomes have been employed to create four distinct artificial neural networks. Our observation indicates that an increase in the heat source quantity leads to a rise in heat generation, resulting in a greater total heat output and an increase in the temperature field. Coefficient of determination “R” values higher than 0.99 have been obtained for the artificial neural network models. The obtained findings have shown that artificial neural networks can predict thermal parameters with high accuracy.

Advancing auxetic materials: Emerging development and innovative applications

Abstract The development of auxetic materials, known for their unique negative Poisson’s ratio, is transforming various industries by introducing new mechanical properties and functionalities. These materials offer groundbreaking applications and improved performance in engineering and other areas. Initially found in natural materials, auxetic behaviors have been developed in synthetic materials. Auxetic materials boast improved mechanical properties, including synclastic behavior, variable permeability, indentation resistance, enhanced fracture toughness, superior energy absorption, and fatigue properties. This article provides a thorough review of auxetic materials, including classification and applications. It emphasizes the importance of cellular structure topology in enhancing mechanical performance and explores various auxetic configurations, including re-entrant honeycombs, chiral models, and rotating polygonal units in both two-dimensional and three-dimensional forms. The unique deformation mechanisms of these materials enable innovative applications in energy absorption, medicine, protective gear, textiles, sensors, actuating devices, and more. It also addresses challenges in research, such as practical implementation and durability assessment of auxetic structures, while showcasing their considerable promise for significant advancements in different engineering disciplines.

Assemblies of Coaxial Pick-Up Coils as Generic Inductive Sensors of Magnetic Flux: Mathematical Modeling of Zero, First and Second Derivative Configurations.

Coils are one of the basic elements employed in devices. They are versatile, in terms of both design and manufacturing, according to the desired inductive specifications. An important characteristic of coils is their bidirectional action; they can both produce and sense magnetic fields. Referring to sensing, coils have the unique property to inductively translate the temporal variation of magnetic flux into an AC voltage signal. Due to this property, they are massively used in many areas of science and engineering; among other disciplines, coils are employed in physics/materials science, geophysics, industry, aerospace and healthcare. Here, we present detailed and exact mathematical modeling of the sensing ability of the three most basic scalar assemblies of coaxial pick-up coils (PUCs): in the so-called zero derivative configuration (ZDC), having a single PUC; the first derivative configuration (FDC), having two PUCs; and second derivative configuration (SDC), having four PUCs. These three basic assemblies are mathematically modeled for a reference case of physics; we tackle the AC voltage signal, VAC (t), induced at the output of the PUCs by the temporal variation of the magnetic flux, Φ(t), originating from the time-varying moment, m(t), of an ideal magnetic dipole. Detailed and exact mathematical modeling, with only minor assumptions/approximations, enabled us to obtain the so-called sensing function, FSF, for all three cases: ZDC, FDC and SDC. By definition, the sensing function, FSF, quantifies the ability of an assembly of PUCs to translate the time-varying moment, m(t), into an AC signal, VAC (t). Importantly, the FSF is obtained in a closed-form expression for all three cases, ZDC, FDC and SDC, that depends on the realistic, macroscopic characteristics of each PUC (i.e., number of turns, length, inner and outer radius) and of the entire assembly in general (i.e., relative position of PUCs). The mathematical methodology presented here is complete and flexible so that it can be easily utilized in many disciplines of science and engineering.

Integrated Data Processing Architecture Applied to Learning Objects Repository for Educational Robotics: Proposing Approach

Educational Robotics has emerged as a multidisciplinary field integrating Information and Communication Technologies, Engineering, and Artificial Intelligence areas in education. Furthermore, Educational Robotics offers an innovative approach to teaching and learning by incorporating the construction and programming of robots. However, the small number of platforms for sharing Educational Robotics Learning Objects with a large amount of well-described metadata poses a challenge for efficient search and retrieval of relevant educational content. This study presents an architecture for data processing and ingestion in the RepositORE system, a Learning Objects Repository for Educational Robotics that stores educational content and associated metadata based on the Dublin Core standard. Based on microservices architecture, the proposed system aims to facilitate the location and reuse of learning objects by adapting the RepositORE system to work as a client service. The theoretical framework explores the concepts of learning objects, repositories, and the significance of Educational Robotics in education, and reviews related works. The proposed architecture and system can potentially enhance the accessibility and discoverability of Educational Robotics Learning Objects, fostering effective teaching and learning experiences.

How framing bias impacts preferences for innovation in bone tissue engineering.

It is currently unknown if surgeons and biomaterial scientists &or tissue engineers (BS&orTE) process and evaluate information in similar or different (un)biased ways. For the gold standard of surgery to move "from bench to bedside", there must naturally be synergies between these key stakeholders' perspectives. Because only a small number of biomaterials & tissue engineering innovations have been translated into the clinic today, we hypothesised this lack of translation is rooted in the psychology of surgeons and BS&orTE. Presently, both clinicians and researchers doubt the compatibility of surgery and research in their daily routines. This has led to the use of a metaphorical expression "squaring of the circle," which implies an unsolvable challenge. As bone tissue engineering belongs to the top 5 research areas in tissue engineering we choose the field of bone defect treatment options for our bias study. Our study uses an online survey instrument for data capture: incorporating a behavioural economics cognitive framing experiment methodology. Our study sample consisted of surgeons (n=208) and BS&orTE (n=59). And we employed a convenience sampling method, with participants (conference attendants) being approached both in person and via email - 22 October 2022-13 March 2023. We find no distinct positive-negative cognitive framing differences by occupation. That is, any framing bias present in this surgical decision-making setting does not appear to differ significantly between surgeon and BS&orTE specialisation. When we explored within group differences by frames, we see statistically significant (p<0.05) results for surgeons in the positive frame ranking autologous bone graft transplantation lower compared to surgeons in the negative frame. Further, surgeons in the positive frame rank Ilizarov bone transport method higher compared to surgeons in the negative frame (p<0.05).

An instructional framework for teaching STEM to students with moderate to severe disabilities

AbstractAnswering questions and solving problems are critical skills that affect the quality of life for all people. The content areas of science and engineering traditionally and most directly address the processes of inquiry and problem‐solving. While there is an increasing body of research surrounding teaching academic content (i.e., mathematics and science) as well as skills that are critical to support student success in these areas (i.e., communication and self‐determination), the research supporting instruction of math, science, and engineering practices and processes are only emerging. The purpose of this article is to provide a research‐based framework for instructional design that provides ideas for cognitive accessibility and supports for students with MSD in STEM. The framework aims to guide teachers in considering why to teach STEM, what to teach, and how to teach it. The framework guides teachers to use evidence‐based practices in special education to teach students to know about STEM (i.e., academic content), do STEM practices and processes (i.e., critical thinking skills combined into routines for asking questions or solving problems), and think in ways that support this learning (i.e., metacognitive behaviors).

Localized thermal emission from topological interfaces.

The control of thermal radiation by shaping its spatial and spectral emission characteristics plays a key role in many areas of science and engineering. Conventional approaches to tailoring thermal emission using metamaterials are hampered both by the limited spatial resolution of the required subwavelength material structures and by the materials' strong absorption in the infrared. In this work, we demonstrate an approach based on the concept of topology. By changing a single parameter of a multilayer coating, we were able to control the reflection topology of a surface, with the critical point of zero reflection being topologically protected. The boundaries between subcritical and supercritical spatial domains host topological interface states with near-unity thermal emissivity. These topological concepts enable unconventional manipulation of thermal light for applications in thermal management and thermal camouflage.

Fractional dynamics study: analytical solutions of modified Kordeweg-de Vries equation and coupled Burger’s equations using Aboodh transform

The study examines the using of Aboodh residual power series method and the Aboodh transform iteration method (ATIM) to analyze modified Korteweg-de Vries equation (mKdV) beside coupled Burger’s equations in the framework of the Caputo operator. These sets of equations represent the non-linear wave description for various physical systems. Through APM and ATIM, the solution for the coupled Burger’s equations and the mKdV equation get accurate dynamics information that will reveal the nature of their interactions. Using mathematically proven techniques and computational simulations, the developed methods’ efficiency and reliability are illustrated in the complex behaviors of these nonlinear wave equations, so that we can gain deeper insights into their complex dynamics. The research is aimed at an increase of the knowledge about the fractional calculus utilization for nonlinear wave motion and it also provides analytical tools for an analysis of wave acting in different scientific and engineering areas.

DESIGN A SINGLE SCREW EXTRUDER FOR POLYMER-BASED TISSUE ENGINEERING

In the area of tissue engineering, single screw extrusion (SSE) has gained attention due to its versatility and efficiency in fabricating polymer-based scaffolds. Furthermore, advancements such as the implementation of extrusion techniques and the integration of bioactive agents have significantly expanded the capabilities of SSE. This study aims to investigate the configuration of a custom-designed plastic extrusion for tissue engineering, highlighting its potential in fabricating suture technology for various regenerative biomedical applications. Furthermore, the challenges and future perspectives in SSE technology are discussed, with a focus on the need for additional research to optimize processing parameters, enhance structure bioactivity, and facilitate clinical usage. SSE provides precise regulation of structure morphology, mechanical properties, and porosity, which are critical factors that influence cell behavior and tissue regeneration. Overall, SSE holds great promise as a scalable and cost-effective manufacturing technique for producing polymer-based structures with tailored properties, advancing the field of tissue engineering towards effective clinical solutions. The paper provides a comprehensive overview of a filament extruder production machine that is capable of manufacturing high-quality filament sutures (FS) using thermoplastic materials, specifically bio-protein derived from human serum albumin. The main focus of the paper is to explain the design and operation principles of the filament extruder. The extruder is equipped with a die that can measure a range starting from 2.5 mm and going down to smaller scales. This allows for the extrusion of filaments with a diameter as small as 1.75 mm. Although the design of the extrusion apparatus closely resembles that of commercially available machines, the focus here is on its adaptability and cost-effectiveness for laboratory-scale production. Overall, the research contributes to advancing the understanding of extrusion processing technologies in the context of biomedical applications, with a specific focus on utilizing human serum albumin-derived thermoplastics for manufacturing FS.

81‐1: Invited Paper: What Makes a Good Automotive Display and How MicroLEDs Will Improve Them Even Further

Vehicle‐mounted displays are subject to some unique use‐cases and integration constraints that must be thoroughly considered during development to make the project successful, and the customer and end‐user pleased. This paper will touch upon some of the areas of automotive display engineering that deserves special attention. The automotive industry follows the development of MicroLED with excitement, as it holds promise of increased robustness and brightness, as well as new display types. This paper will examine some of the features that make MicroLED unique, the current state of research and its possible impact on the automotive industry.

GraphPyRec: A novel graph-based approach for fine-grained Python code recommendation

Artificial intelligence has been widely applied in software engineering areas such as code recommendation. Significant progress has been made in code recommendation for static languages in recent years, but it remains challenging for dynamic languages like Python as accurately determining data flows before runtime is difficult. This limitation hinders data flow analysis, affecting the performance of code recommendation methods that rely on code analysis. In this study, a graph-based Python recommendation approach (GraphPyRec) is proposed by converting source code into a graph representation that captures both semantic and dynamic information. Nodes represent semantic information, with unique rules defined for various code statements. Edges depict control flow and data flow, utilizing a child-sibling-like process and a dedicated algorithm for data transfer extraction. Alongside the graph, a bag of words is created to include essential names, and a pre-trained BERT model transforms it into vectors. These vectors are integrated into a Gated Graph Neural Network (GGNN) process of the code recommendation model, enhancing its effectiveness and accuracy. To validate the proposed method, we crawled over a million lines of code from GitHub. Experimental results show that GraphPyRec outperforms existing mainstream Python code recommendation methods, achieving Top-1, 5, and 10 accuracy rates of 68.52%, 88.92%, and 94.05%, respectively, along with a Mean Reciprocal Rank (MRR) of 0.772.

Application of PID and self-tuning fuzzy PID control methods in the control of non-linear magnetic levitation system

Because of the Magnetic Levitation System's (MLS) low energy consumption and little friction two factors that are deemed crucial for unstable and nonlinear systems MLS research is now being conducted in the engineering area. This article discusses the comparison of the performance of control theories used by applying advanced control theories to cope with the complexity of the structure and controllability difficulties of MLS. The control methods compared are Proportional–Integral–Derivative (PID) and Self-Tuning Fuzzy PID (STFPID) methods. These methods were developed in the MATLAB environment. The MLS model created in the MATLAB environment was subjected to the suggested control methods, and the outcomes were compared. The outcomes unequivocally demonstrate that MLS location control may make use of PID and STFPID techniques. Four criteria were used to compare the developed control approaches performances. These are the criteria; rise time, settling time, percent maximum overshoot and overshoot value. It is clearly seen in the results that the STFPID control method provides control of the MLS with greater stability than the PID control method.

Green and facile fabrication of robust calcium alginate sponges via thermally bonded nonwoven induced freeze-drying for dressing applications

Alginate sponges have been widely studied in areas of wound healing, drug release, tissue engineering, and wastewater treatment due to their potential biological activity, biocompatibility, high porosity, and large surface area. However, their poor mechanical properties greatly limit the practical applications of alginate sponge. In this study, a structurally controllable and high-performance sponge material preparation strategy was proposed by optimizing the structure of the freeze-dried calcium alginate (CA) sponge using fluffy and porous thermally bonded nonwovens (NWs). The performance of composite sponges (CA@NWs) prepared at different pre-freezing temperatures and concentrations were tested. The results showed that the NWs skeleton could improve the formation structure and size stability of the freeze-dried CA sponge, making it have good fluid absorption, moisture permeability, moisture retention, and wet state mechanical properties. The RF-1.0-CA@NWs sponge had the highest fluid absorption rate of 1415 %. The wet state RF-1.5-CA@NWs sponge had tensile strengths of 1.913 MPa and 0.465 MPa in the MD and CD directions, respectively, which was about 95 times higher than that of the wet state pure CA sponge.

Design and Additive Manufacturing of Nerve Guide Conduits Using Triple Periodic Minimal Surface Structures

Scaffold design is a key study area in tissue engineering. A scaffold is a three-dimensional framework that provides temporary support for the formation of new tissue before being implanted with isolated cells. The aim of tissue engineering scaffolds is to be colonized by cells. To ensure sufficient tissue growth, scaffolds need to transmit the necessary chemical and physical signals. The design of the scaffold determines its functionality. The design and manufacturing of tissue engineering scaffolds is a highly complex procedure. Scaffolds must have the necessary qualities to create an optimal architecture for cell growth, proliferation, and differentiation in order to form tissue. However, constrained structural designs and outdated manufacturing procedures impede the enhancement of scaffold qualities. To address these restrictions, researchers are merging computer-aided scaffold design with 3D printing processes during production. This method permits the design and manufacture of scaffolds with extremely intricate microstructures. The literature shows that computer-aided design combined with 3D printing technology is often utilized to design and manufacture nerve guide conduits for nerve regeneration. In this study, three different nerve guide conduit structures were designed and produced. Two of them are based on triple periodic minimal surfaces derived from Gyroid, schwarz. Although triple periodic minimal surfaces used as the basis for scaffold designs offer promising advantages for tissue engineering applications, limited information is available regarding their manufacturability. The designs created in this study, as well as their fabrication, will add to the literature on the manufacturability of triple periodic minimum surfaces.