Context Of Engineering Research Articles

Adaptive caching for operation-based versioning of models

Abstract In a collaborative multi-user model-driven engineering context, it becomes important to track who changed what model part how and why. Operation-based versioning addresses this need by persisting a meaningful edit history which enables a single user to navigate through a model’s evolution over time, to analyze arbitrary previous model versions, or to trace the impact of an operation. However, to load a distinct prior version, it must be restored by reapplying all previous operations, which is time-consuming and, thus, interrupts a user’s workflow. Caching with a fixed distance between caches helps to overcome this problem to the cost of increasing memory requirements. Further, there is no caching approach supporting branches, merges, and possibly resolved conflicts. We propose two advanced caching strategies for operation-based versioning capable of the previously mentioned features: zonal and adaptive caching. Both strategies reduce the memory in use by not applying the same static distance between two caches across the whole edit history. Instead, the distance increases depending on a version’s age and its distance to a branch’s head. Both strategies aim to reduce the restoration time of arbitrary prior versions below a threshold to not interrupt a user’s flow of thought. Zonal caching employs predefined distances compatible with a broad range of model sizes. In contrast, adaptive caching derives the distances individually depending on the initial time to load the model on a user’s computer and the model’s size.We conducted controlled experiments with models of varying sizes and compared the time to restore model versions and the memory in use for no caching, caching with static distances, zonal, and adaptive strategies on different computers. The developed strategies decrease the time to restore a version remarkably while using less memory than static caching. Our results show that for all considered systems and models individual adaptive caching reduces memory usage even further compared to zone-based caching while still satisfying application responsiveness requirements.

Conceptually engineering the post-truth crisis

ABSTRACT This article uses the current post-truth crisis to level a charge against deflationism. It argues that a post-truth society rejects the normativity of truth, thereby deflating truth, by treating disagreements about, say, scientific facts, as mere disagreements of taste. To have substantive disagreements, the notion of truth at stake must be substantive as well. To ward off the perils of post-truth politics, truth must be taken to be more than what deflationists can account for. If we want our disagreements to amount to more than mere differences of opinion, we should have an inflated notion of truth. The article concludes with putting this claim within the context of conceptual engineering.

Joint response of surface subsidence and strong mine earthquake under high-positioned and thick-hard strata in deep coal mine

Multiple active mining faces and extensive excavations under thick-hard strata in deep coal mines result in frequent strong mine earthquakes, often accompanied by significant surface subsidence deformation. Understanding the specific law of surface movement and the spatiotemporal distribution response to intense mine earthquakes is crucial for effectively preventing and mitigating dynamic disasters in deep mines. Utilizing the key layer theory, the intricate strata of the Yingpanhao Coal Mine are systematically delineated, drawing upon the engineering context of working faces 2201 and 2202 within the Ordos Chemical Co., Ltd., a subsidiary of the Shandong Energy Group. Field investigations are conducted to analyze the law of surface subsidence associated with multi-working face extraction within deep thick-hard strata, as well as to elucidate the spatiotemporal distribution characteristics of strong mine earthquakes. Furthermore, the interplay between law of surface subsidence and the spatial distribution of strong mine earthquakes is investigated, revealing a cohesive relationship between these phenomena. The research findings of this study provide certain references for the pre-control of surface subsidence and strong mine earthquakes during multiple working face and large space mining under thick-hard strata in deep coal mine with similar engineering geological conditions.

MHD nanofluid flow over a thin needle: Impact of second‐order slip and variable thermal properties

AbstractThe complexity of second‐order slip flow phenomena demonstrated by magnetohydrodynamics (MHD) nanofluids passing through a thin needle with dynamically changing thermal characteristics is explored in this article. It delves deeply into the mutual effects of thermophoretic and Brownian motion and analyzes the implications of MHD. Specifically, temperature‐dependent variations in the viscosity and thermal conductivity of the nanofluid are observed, and the boundary contact is subject to a strict zero mass flow constraint. Employing transformative methodologies, the governing equations are transmuted into a set of intricate ordinary differential equations (ODEs), systematically tackled using the sophisticated MATLAB bvp4c algorithm to furnish precise numerical solutions. This research provides important new understandings of the complex dynamics of nanofluids surrounding thin needles, clarifying their relevance in many engineering contexts. The study reveals that the rate of heat transfer is enhanced for the higher surface needle thickness, and the fluid with higher viscosity yields a decrease in the temperature of the fluid.

Application of a Senior Student's Rhetorical Skillset in a Novel Situation to Assess Learning Transfer

Previous research suggests that our communication program has had success in developing students’ rhetorical judgment, allowing them to successfully navigate the transition to professional engineering environments. However, we are situated in the College of Engineering; it is possible that the weight of the environment is having an unrecognized positive influence on students’ ability to adapt to the context of professional engineering. This paper seeks to understand whether the identity of rhetorician, embraced by a graduate of our program, extends beyond the particular professional context of engineering. Calling upon Dillon’s discussion of the dimensions of footing from Rhetoric as Social Imagination: Explorations in the Interpersonal Functions of Language (2008), a student’s success in adapting to a novel communication environment is assessed to reflect on whether her communication judgment transfers to an environment other than professional engineering.

Research Through Design – A research paradigm that integrates engineering designers and engineering education researchers

Engineering education as currently practiced is effectively undertaking traditional educational research in an engineering context. While valuable for understanding and promoting change in engineering education, this approach calls into question why engineering education should be redefined as a unique research discipline. This research paper explores an emerging research paradigm – "Research Through Design" (RTD) – and suggests how it can be integrated into engineering education research. The aim of this paper is to provide a practical understanding of the history, objectives, and methods of RTD, and to assess its potential applicability both to advance engineering education research and to integrate the engineering education research community

The Innovation Problem Finder Dartboard: Embedding Critical Design in the Engineering Workflow

This paper introduces the “Innovation Problem Finder Dartboard" (IPFD), a generative critical design-inspired pedagogical tool for ideating on the potential uses, misuses, and alternative contexts of a given technology. In a first year Engineering Communication course, students used the IPFD, accompanied by a brief worksheet they completed in groups, during the problem definition stage of their term project. The aim of employing the IPFD activity in this context is twofold: students will 1) generate ideas about how equity, diversity, and inclusion (EDI) and social and environmental justice factor into an engineering design problem and 2) think critically about existing and potential engineering contexts, cultures, and practices.

Does self-paced learning in mobile flood protection unit construction in virtual reality have advantages over traditional measures?

IntroductionThe study explores the application of virtual reality (VR) in university education, specifically within the context of civil engineering. It aims to investigate the potential of an immersive virtual lab employing self-paced learning for teaching complex tasks. The focus is on the construction of a Mobile Flood Protection Unit (MFPU), traditionally taught through written instructions or video tutorials.MethodsAn experiment was conducted involving 48 students who were divided into two groups. One group learned to build an MFPU using a VR tutorial, while the other group used a traditional instructional video. The effectiveness of these teaching tools was assessed based on factual and procedural knowledge transfer. Additionally, students' personal perceptions regarding the use of VR software were evaluated.ResultsThe findings indicated a positive effect on factual knowledge transfer when using VR. Moreover, students expressed favorable perceptions towards utilizing VR as a learning tool.DiscussionThe study suggests that VR can enhance factual knowledge acquisition and is well-received by students in educational settings. However, it also highlights the need for further research to better understand its impact on procedural knowledge gain. Future studies could explore long-term effects and different applications within various fields of education.

Commutative Chain Rings with Index of Nilpotency 5 and Residue Field Fpm

This paper gives a thorough characterization of chain rings with index of nilpotency 5 and residue field Fpm, where p represents a prime number, contributing valuable insights to the field of algebraic structures. It carefully identifies and categorizes the family of chain rings with these specifications, thereby enhancing the understanding of their properties and applications. In addition, the work offers a detailed enumeration of all chain rings containing p5m elements. The significance of finite chain rings is emphasized, particularly in their suitability for coding theory, which confirms their relevance in contemporary mathematical and engineering contexts.

Investigation of heat and mass transfer on unsteady MHD flow through a porous medium past an exponentially accelerated plate with stratification effects

AbstractThis research analyzes the effects of heat and mass transfer on unsteady magnetohydrodynamics fluid flow through a porous material along a vertical plate that accelerates exponentially and has both thermal and mass stratification. We find the solutions to the system's governing equations by employing the Laplace transformation approach and graphs are produced by implementing MATLAB software. The unique aspect of this problem is that we find the precise solution by applying the extremely effective Laplace transform approach, which yields an error‐free exact answer. The effect of flow variables on velocity, temperature, and concentration profiles are illustrated using graphs. The results show that when the magnetic field parameters are raised, there is a corresponding increase in temperature and decrease in velocity. As the permeability parameter increases velocity profile increases, temperature and concentration profiles decreases. The need to better understand fluid flow in a variety of engineering and environmental contexts—such as geothermal energy extraction, thermal management, chemical processing industries, and environmental control technologies—could be the driving force behind this study. Understanding flow mechanisms in both natural and artificially created porous environments is improved by this innovative method.

Estimating stress-strength reliability based on two-parameter exponential records in the presence of inter-record times

ABSTRACT This study addresses the problem of point and interval estimation for the reliability parameter in a stress-strength model when the data available consist of record values along with inter-record times, under two-parameter exponential distributions. The motivation for this paper arises from the need to improve reliability assessments in engineering and manufacturing contexts where products are subjected to stress conditions. Understanding the relationship between stress (the actual load on a system) and strength (the maximum load a system can withstand) is crucial for ensuring safety and performance. Record data, which encompass extreme observations, provide a valuable means to estimate the reliability parameter. We also explore the point and interval estimation of the reliability parameter when the scale parameters of the two exponential distributions are assumed to be equal. Monte Carlo simulations are conducted to assess the performance of the proposed estimates. Finally, we apply the results obtained in this paper to analyze two real data sets.

Teaching Reading Skills in the Indian Engineering Context: Challenges and Experiences

ABSTRACT This study focuses on teaching Engineering students reading skills in the English classroom. The methodology comprised conducting surveys—with the aid of three questionnaires—to gather the views of Engineering students, English faculty, and Engineering faculty on how reading skills could be taught and learned effectively. In addition, the researchers conducted semi-structured interviews to clarify some doubts that arose after the survey. The survey questions gathered the survey participants’ background, their reading purposes, their preferences regarding reading and reading activities, reading expectations and challenges, suggestions for interesting reading materials, and ways to improve reading skills. The data interpretation of the three surveys and the subsequent interviews highlights the steps to be taken to enhance the Engineering learners’ English reading skills.

Magnetohydrodynamic Effects on Double Diffusion of Non‐Newtonian Hybrid Nanofluid in Circular Eccentric Annuli

ABSTRACTThe numerical investigation conducted in this study focuses on the heat and mass transfer in magnetohydrodynamic non‐Newtonian power‐law fluid flow of temperature‐dependent Al2O3–Fe3O4–water hybrid nanofluid within cylindrical annuli across four different eccentricities. This type of problem finds widespread application in various engineering contexts, where hybrid non‐Newtonian fluids offer enhanced efficiency for cooling and insulation purposes. In this configuration, the inner circle of the geometry is hot while the outer circle is cold, with the nanofluid filling the space between the cylinders. The governing equations are simulated using the Galerkin weighted residual finite element method. Various parameters are controlled in the study, including the Rayleigh number ranging from to , power‐law index ranging from to , nanoparticle volume fraction ranging from to , Hartmann number ranging from to , Buoyancy ratio ranging from to , and Lewis number ranging from to , in addition to the fixed Prandtl number (6.8377). The study presents visualizations such as streamlines, isotherms, and iso‐concentration contours, along with the assessment of heat and mass transfer rates expressed in terms of Nusselt and Sherwood numbers. The findings reveal that the heat transfer rate increases with higher nanoparticle volume fraction, Rayleigh number, and Buoyancy ratio. Similarly, the mass transfer rate is enhanced with increased Rayleigh number, Lewis number, and power‐law index. Notably, elevating the power‐law index leads to a decrease of 50.1% in the local Nusselt number and 52.4% in the local Sherwood number, respectively. With and , increasing from to raises and .

Scaling the predictions of multiphase flow through porous media using operator learning

Operator learning promises generalized and accelerated predictions for fluid flow problems. Using non-body fitted Cartesian mesh based CFD simulation data, we explore if multiphase flow in large spatial extents can be predicted through Fourier Neural Operator (FNO) using pore-scale direct numerical simulations in smaller, representative domains. While operator learning is known to be resolution independent, its relevance for scaling up a domain for spatially emergent phenomena has not been sufficiently explored in an engineering context. Firstly, we verify the predictions from FNO using single-phase flow over complex shaped obstacles and two phase flows through an arbitrary arrangement of circular cylinders, mimicking pore microstructure in a packed bed. Further, we perform multiphase flow predictions in domains larger than those used in training sets to assess the potential of FNO for ‘domain-scaling.’ We also test if transfer learning improves the prediction on the larger domain.

Building Bridges: Teaching Programming through Problem-Based Learning in Mechanical Engineering

Abstract—Teaching programming to mechanical engineering students, often seen as a computer science endeavor, requires a thoughtful approach to highlight its relevance in their field. The mechanical engineering teacher can bridge this gap by demonstrating how programming solves complex engineering problems. Using real-world examples such as simulating mechanical systems or automating data analysis, illustrates the practical benefits of programming skills. To engage students, the teacher implemented Problem-Based Learning (PBL) activities tailored to mechanical engineering contexts. Activities like “Trace it Out,” where students identify code errors, and “Jumble the Code,” which involves ordering or debugging code pieces, help students connect programming concepts to engineering projects. Solutions to real-world problems are presented as poster presentations, making learning interactive and hands-on. Community problems and solutions were documented and assessed using designed rubrics, reinforcing programming knowledge and developing problem-solving skills. Regular feedback and project-based assessments, rather than traditional exams, better measure students’ understanding and ability to apply programming skills to engineering problems. This comprehensive approach—linking programming with mechanical engineering applications, mentoring, active learning, and continuous feedback—transforms students’ perspectives, helping them realize the invaluable role of programming in their professional development as mechanical engineers. Providing access to online resources and encouraging participation in coding communities further enhances their learning experience.

Intelligent optimization of thermal performance in nanoparticle-enhanced enclosures with sinusoidal heating and magnetic field interaction using Multi Expression Programming

This study advances a comprehensive numerical analysis aimed at enhancing thermal transfer within square enclosures filled with water-based oxide nanoparticle suspensions subjected to central sinusoidal heating. Central to this research is the integration of Multi Expression Programming (MEP) for the predictive optimization of thermal efficiency, taking into account the intricate effects of sinusoidal heating geometry, nanoparticles concentration, and an inclined magnetic field. The analysis maintains the initial setup boundary conditions: no-slip at the enclosure walls, isothermal conditions at the left and right walls, and adiabatic conditions at the top and bottom walls, except where sinusoidal heating is applied. Using MEP, these conditions are explored to identify configurations that significantly enhance thermal performance. This method allows for a detailed examination of the impacts of heating element undulation, magnetic field orientation, and nanoparticle dispersion on flow dynamics and thermal transmission. The results emphasize the significant impact of heating element undulation on the heat transfer rate, with MEP predicting optimal undulations that boost thermal efficiency. Furthermore, the strategic application of magnetic fields, as optimized through MEP, facilitates controlled flow distribution and buoyancy effects, with an increased Rayleigh number leading to enhanced convection patterns. The study also delineates the specific boundary conditions under which the Nusselt number, indicative of thermal performance, increases. These MEP-driven insights are invaluable for designing optimized heat transfer systems and energy-efficient applications, establishing a new benchmark for thermal management strategies in practical engineering contexts, firmly rooted in the precision afforded by computational optimization and predictive modeling.

Numerical computation of tangent hyperbolic magnetohydrodynamic Darcy–Forchheimer Williamson hybrid nanofluid flow configuring variable thermal conductivity

The current investigation delves into the tangent hyperbolic Williamson hybrid nanofluid flow featuring varying thermal conductivity through the Darcy–Forchheimer medium across an exponentially stretching cylinder. Incorporating the activation energy and chemical reaction effects into consideration also strengthens the mathematical model's vitality. The considered hybrid nanofluid comprises silver and molybdenum disulfide nanoparticles submerged in the water. The highly non-linear system of equations is solved utilizing the MATLAB bvp4c approach. The influences of the leading variables versus involved fields are demonstrated through graphical delineations and tables. The core findings demonstrated that a strong Weissenberg number and Darcy-Forchheimer factor decay the velocity curve and strengthen the thermal curve. Also, the fluid concentration is enhanced for escalating activation energy and tangent hyperbolic factor. Additionally, the hybrid nanofluid betokens substantially enhance the thermal transportation rate of up to 8.8 % in contrast to nanofluid. Also, in contrast to the nanofluid and Williamson hybrid nanofluid, the hybrid nanofluid exhibits notably higher mass and thermal transport rate. This study is a noteworthy advancement in the disciplines of fluid dynamics and nanofluid research, as it provides promising potential for optimizing the transfer of mass and heat in a wide range of engineering and industrial contexts. The findings exhibit good agreement when contrasted with previously published work.

Finite element structural analysis of simply supported solid and stiffened plates: A comparative study

A structure’s form and shape influence how it behaves when loaded. This was achieved by contrasting the stiffened plate’s performance with that of a solid plate made of the same material and volume. The results have demonstrated that bending stress in stiffened plates is decreased when a solid plate of the same material and volume is transformed into a stiffened plate. Because stiffened plates have a higher strength to weight ratio than solid plates, this supports the recommendation of stiffened plates for a variety of technical applications. In order to determine the impact of stiffener orientation on bending stress reduction in stiffened plates, additional investigations were carried out on a number of plates. An investigation was carried out to determine the ideal stiffener angle in a stiffened plate that could offer the least amount of stress. The current work offers insightful information about particular stiffened plate design characteristics that can be used in a variety of engineering contexts.

Application of the Atangana–Baleanu operator in Caputo sense for numerical solutions of the time-fractional Burgers–Fisher equation using finite difference approaches

This research investigates the numerical solution of the time-fractional Burgers–Fisher equation, utilizing the Atangana–Baleanu differential operator in the Caputo sense. This study addresses the need to comprehend the dynamics of nonlinear phenomena encountered in various scientific and engineering contexts, specifically within the Burgers–Fisher equation, which intertwines diffusion and reaction processes. Our findings reveal that the application of the Atangana–Baleanu operator significantly alters the behavior of the system, exhibiting distinct characteristics compared to traditional methods. Notably, we identify unique patterns of propagation, such as enhanced wave speed and altered front dynamics, that emerge due to the fractional dynamics. The simulations demonstrate improved stability and convergence properties when utilizing the Atangana–Baleanu operator, allowing for more accurate representations of physical processes. Additionally, we observe the emergence of non-local effects and the potential for multiple equilibrium states, enriching our understanding of the complex interactions within the system. Through the finite difference method, we efficiently discretize the continuous problem, facilitating simulations that illustrate the intricate temporal behavior of the time-fractional system. This methodology not only enhances the understanding of the physical processes involved but also contributes a novel framework for studying time-fractional equations, emphasizing the rich dynamics introduced by the Atangana–Baleanu operator in conjunction with the Caputo fractional derivative.

Probabilistic Topology Optimization Framework for Geometrically Nonlinear Structures Considering Load Position Uncertainty and Imperfections

In this manuscript, a novel approach to topology optimization is proposed which integrates considerations of uncertain load positions, thereby enhancing the reliability-based design within the context of structural engineering. Extending the conventional framework to encompass imperfect geometrically nonlinear analyses, this research discovers the intricate interplay between nonlinearity and uncertainty, shedding light on their combined effects on probabilistic analysis. A key innovation lies in treating load position as a stochastic variable, augmenting the existing parameters, such as volume fraction, material properties, and geometric imperfections, to capture the full spectrum of variability inherent in real-world conditions. To address these uncertainties, normal distributions are adopted for all relevant parameters, leveraging their computational efficacy, simplicity, and ease of implementation, which are particularly crucial in the context of complex optimization algorithms and extensive analyses. The proposed methodology undergoes rigorous validation against benchmark problems, ensuring its efficacy and reliability. Through a series of structural examples, including U-shaped plates, 3D L-shaped beams, and steel I-beams, the implications of considering imperfect geometrically nonlinear analyses within the framework of reliability-based topology optimization are explored, with a specific focus on the probabilistic aspect of load position uncertainty. The findings highlight the significant influence of probabilistic design methodologies on topology optimization, with the defined constraints serving as crucial conditions that govern the optimal topologies and their corresponding stress distributions.