Hasil untuk "Mechanics of engineering. Applied mechanics"

S. Pope

It was a pleasure to read this important book. To understand and predict the development of turbulent flows represents both a continuing scientific challenge and also a serious practical problem in many different fields. Professor Pope has based his book on graduate level lecture courses on turbulence that he has presented at MIT and at Cornell University. It is intended for students in engineering, applied mathematics, oceanography and atmospheric sciences, as well as researchers and practising engineers. The emphasis is on turbulent flows, rather than on the theory of homogeneous turbulence, and only constant-density, nonreacting flows are considered. The author states that his aim is to explain concepts and develop the necessary mathematical tools, rather than to provide a practical guide to turbulence modelling. The text is divided into two parts. Part I provides an introduction to turbulent flows and the fundamental physical processes involved. Topics discussed in separate chapters include: the equations of fluid motion, the statistical description of turbulent flows, the mean flow equations, free shear flows, scales of turbulent motion and wall flows. The chapter on statistical methods for turbulence is particularly good; together with the related appendices it represents a valuable and accessible introduction to the subject. Several approaches for modelling or simulating turbulent flows are then described in Part II, in which the various chapters describe direct numerical simulation (DNS), turbulent viscosity models such as the k-ε model, Reynolds stress and related second-moment models, probability density function (pdf) models and large-eddy simulation (LES) techniques. Finally, some necessary mathematical tools are summarized in ten Appendices dealing with a wide range of relevant topics including tensors, Dirac delta functions, Fourier transforms, random processes, derivation of pdf equations, characteristic functions and stochastic descriptions of diffusion processes. I particularly enjoyed the chapters on modelling and simulation of turbulent flows. A unified treatment of the different types of model has enabled the author to make valuable connections between them and to reach clear and logical conclusions about the strengths and weaknesses of each approach. Over many years Professor Pope has made very important contributions to the development and application of pdf methods for the prediction of nonreactive and also reactive turbulent flows. The chapter on this subject is an exceptionally clear description of these powerful and often under-utilized simulation methods. The final chapter, on LES, provides an excellent introduction, with valuable and novel insights into both the promise and the problems of this relatively new and rapidly developing approach. It should be compulsory reading for many LES practitioners. Each section of the book contains a number of exercises, which typically invite the reader either to derive an expression that is quoted in the text or to generalize an analysis set out in the text. These exercises are often divided into several stages, and contain appropriate instructions, so that a diligent student will find his or her way through them. An advantage of the extensive use of appendices and student exercises is that analytical clarity and physical understanding are not obscured by unnecessary algebraic detail or by the need to review basic mathematical tools. The result is an exceptionally clear presentation, together with an often penetrating critique of both classical methods and recent developments in the theory and modelling of turbulent flows. There is excellent cross-referencing between one section and another, and an extensive and up-to-date bibliography. I strongly recommend this book to advanced students of fluid mechanics, to their teachers and to all researchers, engineers and others with a professional interest in turbulent flows. K N C Bray

Dipjyoti Nath, Ankit, Debanga Raj Neog et al.

Hai Pham-Van

We present a symmetry-based framework for equilibrium statistical mechanics that formulates a single Lie group combining conventional spacetime symmetries with a recently identified phase-space gauge-shifting invariance [Muller et al., Phys. Rev. Lett. 133, 217101 (2024)]. Using Noether's theorem, we obtain a set of general Ward identities together with previously unexplored cross-relations arising from the noncommutation of different symmetry generators. The approach extends standard many-body symmetries, such as translations, rotations, Galilean boosts, dilations, and particle exchange, by incorporating an internal gauge-shift symmetry within a unified group structure. The resulting Lie algebra suggests a hierarchy of exact identities that encompass established sum rules and indicate possible cross-coupling relations between distinct response and correlation functions. We also identify a Wigner-Eckart-Ward reduction that simplifies tensor-hyperforce correlators to two scalar radial spectra in isotropic fluids, and we outline an equivariant gauge-constrained DFT formulation whose Euler-Lagrange equations are constructed to satisfy the corresponding Ward and cross-Ward constraints. This framework provides a consistent organizational basis for phenomena in liquids, mixtures, and interfaces, and may offer a symmetry-based perspective connecting structure, mechanics, and dynamics in many-body systems.

Tanja E. J. Vos, Tijs van der Storm, Alexander Serebrenik et al.

Software engineering is the invisible infrastructure of the digital age. Every breakthrough in artificial intelligence, quantum computing, photonics, and cybersecurity relies on advances in software engineering, yet the field is too often treated as a supportive digital component rather than as a strategic, enabling discipline. In policy frameworks, including major European programmes, software appears primarily as a building block within other technologies, while the scientific discipline of software engineering remains largely absent. This position paper argues that the long-term sustainability, dependability, and sovereignty of digital technologies depend on investment in software engineering research. It is a call to reclaim the identity of software engineering.

Lili Chen, Winn Wing-Yiu Chow, Stella Peng et al.

PURPOSE OR GOAL: This study investigates how GenAI can be integrated with a criterion-referenced grading framework to improve the efficiency and quality of grading for mathematical assessments in engineering. It specifically explores the challenges demonstrators face with manual, model solution-based grading and how a GenAI-supported system can be designed to reliably identify student errors, provide high-quality feedback, and support human graders. The research also examines human graders' perceptions of the effectiveness of this GenAI-assisted approach. ACTUAL OR ANTICIPATED OUTCOMES: The study found that GenAI achieved an overall grading accuracy of 92.5%, comparable to two experienced human graders. The two researchers, who also served as subject demonstrators, perceived the GenAI as a helpful second reviewer that improved accuracy by catching small errors and provided more complete feedback than they could manually. A central outcome was the significant enhancement of formative feedback. However, they noted the GenAI tool is not yet reliable enough for autonomous use, especially with unconventional solutions. CONCLUSIONS/RECOMMENDATIONS/SUMMARY: This study demonstrates that GenAI, when paired with a structured, criterion-referenced framework using binary questions, can grade engineering mathematical assessments with an accuracy comparable to human experts. Its primary contribution is a novel methodological approach that embeds the generation of high-quality, scalable formative feedback directly into the assessment workflow. Future work should investigate student perceptions of GenAI grading and feedback.

Kha Tuan Tran Huynh, Khoa Anh Vo, Vay Siu Lo et al.

This paper investigates the enhancement of Wells turbine blades by modifying the chord length design parameter. The Wells turbine, a promising device in wave energy conversion systems, faces a limited operating range due to flow separation, which restricts its efficiency at higher flow rates. Enhancing the performance of the Wells turbine is crucial for effective wave energy exploitation. The computational simulations in this study are conducted using ANSYS Fluent. Turbine performance is evaluated based on non-dimensional torque, pressure torque, and efficiency, derived from solving the steady 3D incompressible Reynolds Averaged Navier–Stokes equations. The results are validated against reliable references, showing good agreement. The numerical findings reveal that altering the turbine chord length significantly impacts efficiency. Optimizing the chord length enhances the Wells turbine's performance in wave energy conversion, making it a more viable option for renewable energy power generation.

Paloma Guenes, Rafael Tomaz, Bianca Trinkenreich et al.

Research shows that more than half of software professionals experience the Impostor Phenomenon (IP), with a notably higher prevalence among women compared to men. IP can lead to mental health consequences, such as depression and burnout, which can significantly impact personal well-being and software professionals' productivity. This study investigates how IP manifests among software professionals across intersections of gender with race/ethnicity, marital status, number of children, age, and professional experience. Additionally, it examines the well-being of software professionals experiencing IP, providing insights into the interplay between these factors. We analyzed data collected through a theory-driven survey (n = 624) that used validated psychometric instruments to measure IP and well-being in software engineering professionals. We explored the prevalence of IP in the intersections of interest. Additionally, we applied bootstrapping to characterize well-being within our field and statistically tested whether professionals of different genders suffering from IP have lower well-being. The results show that IP occurs more frequently in women and that the prevalence is particularly high among black women as well as among single and childless women. Furthermore, regardless of gender, software engineering professionals suffering from IP have significantly lower well-being. Our findings indicate that effective IP mitigation strategies are needed to improve the well-being of software professionals. Mitigating IP would have particularly positive effects on the well-being of women, who are more frequently affected by IP.

Zhimin Zhao

Foundation models (FMs), particularly large language models (LLMs), have shown significant promise in various software engineering (SE) tasks, including code generation, debugging, and requirement refinement. Despite these advances, existing evaluation frameworks are insufficient for assessing model performance in iterative, context-rich workflows characteristic of SE activities. To address this limitation, we introduce \emph{SWE-Arena}, an interactive platform designed to evaluate FMs in SE tasks. SWE-Arena provides a transparent, open-source leaderboard, supports multi-round conversational workflows, and enables end-to-end model comparisons. The platform introduces novel metrics, including \emph{model consistency score} that measures the consistency of model outputs through self-play matches, and \emph{conversation efficiency index} that evaluates model performance while accounting for the number of interaction rounds required to reach conclusions. Moreover, SWE-Arena incorporates a new feature called \emph{RepoChat}, which automatically injects repository-related context (e.g., issues, commits, pull requests) into the conversation, further aligning evaluations with real-world development processes. This paper outlines the design and capabilities of SWE-Arena, emphasizing its potential to advance the evaluation and practical application of FMs in software engineering.

M. Kotek, V. Kopecký

Teppei J. Yasunari, Daiju Narita, Toshihiko Takemura et al.

Abstract Wildfires emit atmospheric aerosols, affecting climate and air quality. Siberia is a known source region of wildfires. However, comprehensive knowledge regarding the impact associated with particulate matter pollution due to Siberian wildfires on climate and air quality and their effects on mortality and the economy under present and near‐future warmer atmospheric conditions remains poor. Thus, we performed model sensitivity experiments (atmospheric model and coupled atmosphere‐ocean model settings) simulating the effects of changing Siberian wildfire emissions under the present and near‐future climate conditions, using the Model for Interdisciplinary Research on Climate version 5 (MIROC5). Increased Siberian wildfire smoke likely caused a cooling effect in broad areas of the Northern Hemisphere and worsened the air quality near the source and in the downwind region (i.e., East Asia). The more Siberian wildfires occur, the more air pollution is present in those regions, which likely increases mortality and welfare losses there. However, the total impact of changing temperature on the gross domestic product under present and near‐future climate conditions is ambiguous. Our comprehensive results on the air quality changes due to Siberian wildfires under present and near‐future climate conditions suggest that increased efforts to limit the aerosol impact of Siberian wildfires are crucial to prevent possible excess mortality and economic losses.

Ihsan Ur Rahman, Hamin Jaafar Mohammed, Misbah Ullah et al.

Global warming is a serious concern worldwide, while there are many contributors to rise the temperature of earth. One major source to it, is air pollution. It is of utmost importance to apply the necessary remedial actions to address the contaminants in outdoor and indoor environment. In this research a step is taken to treat flue gases, for which membrane technology is introduced. A porous ceramic membrane is synthesized from calcined porous alumina (Al2O3) and activated washed fly ash. Some other additives like starch (C6H10O5) n, binder solution along with ethyl silicate (C8H2O4Si) and a deflocculating agent carbonic acid (H2CO3), are employed. Alongside it, some of the issues are discussed which are faced during fabrication of porous ceramic membrane i.e., crakes in membrane sample, non-active reactants issue, un-even rise or fall during de-moisturization or sintering steps. Further, the membrane sample is characterized through different test including:  Further, the membrane sample is characterized through different test including thermogravimetric analysis (TGA) and DTG, which shown a satisfactory results, as there is negligible percentage weight loss after 750°C. X-ray fluorescence (XRF) for fly ash portrayal and X-ray diffraction (XRD) analysis for structure assessing are conducted, which described that the fabricated membrane has a crystalline structure as like ceramic. Archimedes Principal technique is used to determine bulk density, and porosity of the membrane sample, the values are 4.484 g/cm3, and 62.5% respectively. Average pore size of 7.6 µm is find out through optical microscopy test, similarly mechanical strength is found to be 2.7 MPa. Furthermore, a pilot scale visual permeability test is performed for flue gases treatment of combusting fuel containing tyre and coal powder. The results show the compatibility of the fabricated porous ceramic membrane to be utilized for treatment of flue gases.

Muhammad Khafidh, Finny Pratama Putera, Rahmadi Yotenka et al.

The use of composite materials in brake pads is becoming increasingly popular due to their high-performance characteristics, including good thermal stability, high wear resistance, and low noise generation. However, the development of new composite materials that offer even better performance is still an ongoing research area. In this study, the composite was made by hand layup method using epoxy resin as matrix material, with rice husk, Al2O3, and Fe2O3 as reinforcing materials. The composition of the composites was varied by changing the percentage of the reinforcement materials. The composites were then subjected to several characterization tests, including density, hardness, flexural strength, thermal analysis, Scanning Electron Microscopy (SEM), TGA/DSC, and wear testing. The test results showed that additional reinforcement materials to the epoxy resin matrix improved the mechanical properties of the composites. Overall, the study demonstrates that a hand layup method is a viable approach for preparing brake pad composite materials and that the addition of rice husk, Al2O3, and Fe2O3 can improve the mechanical properties of the composites. The best properties produced in this research were found in one of the specimens which used epoxy, rice husk, Al2O3, and Fe2O3 with a composition of 50 wt.%, 20 wt.%, 15 wt.%, and 15 wt.%. However, the addition of rice husk also provides wear resistance and thermal stability. This study contributes to the Sustainable Development Goals (SDGs) by advancing innovation, promoting sustainability, and reducing emissions in automotive industry applications.

B. Talatahari, M. Azizi, S. Talatahari et al.

PurposeIn this paper, the authors aim to examine and comparatively evaluate a recently-developed metaheuristic called crystal structure algorithm (CryStAl) – which is inspired by the symmetries in the internal structure of crystalline solids – in solving engineering mechanics and design problems.Design/methodology/approachA total number of 20 benchmark mathematical functions are employed as test functions to evaluate the overall performance of the proposed method in handling various functions. Moreover, different classical and modern metaheuristic algorithms are selected from the optimization literature for a comparative evaluation of the performance of the proposed approach. Furthermore, five well-known mechanical design examples are utilized to examine the capability of the proposed method in dealing with challenging optimization problems.FindingsThe results of this study indicated that, in most cases, CryStAl produced more accurate outputs when compared to the other metaheuristics examined as competitors.Research limitations/implicationsThis paper can provide motivation and justification for the application of CryStAl to solve more complex problems in engineering design and mechanics, as well as in other branches of engineering.Originality/valueCryStAl is one of the newest metaheuristic algorithms, the mathematical details of which were recently introduced and published. This is the first time that this algorithm is applied to solving engineering mechanics and design problems.

Yu Li, S. Qiang, Wenqiang Xu et al.

Abstract In order to study the nonlinear creep mechanism of concrete materials, predict and evaluate the safety of the structure, uniaxial nonlinear creep tests of concrete specimens under different ages and stress-strength ratios ( σ / f c ) were carried out. Based on the discrete element theory (DEM), a concrete three-phase numerical simulation model is established, which considers the real aggregate shape and the strength difference of each phase material. The study found that the nonlinear creep duration of the early-age concrete specimens increases exponentially with age, and decreases exponentially with the increase of stress-strength ratio. Age has the greatest influence on total deformation of concrete nonlinear creep. The quantitative relationship between creep characteristics (duration, total deformation) and control variables (age, stress-strength ratio) is established. The numerical simulation model simulates the uniaxial nonlinear creep process of the concrete specimen. Compared with the measured data, it is found that the creep curve is in good agreement. At the same time, the overall trend of the measured damage value defined by the wave velocity and the damage simulation value defined by the number of cracks is in good agreement, which objectively reflects the general law of damage and crack development in the nonlinear creep process. Through the analysis of the failure mode and fabric diagram of the concrete specimen, the microcracks first occurred on the interface. At the same time, the cement gel in the cement mortar undergoes viscous flow, the stress is redistributed, and the microcracks continue to produce, expand, and connect, which ultimately leads to the complete failure of the specimen. The quantitative relationship and numerical simulation model proposed in this paper can be applied to the creep prediction and safety calculation of components or buildings under the condition of high stress-strength ratio, and has a good engineering application prospect.

Johan Bergelin, Per Erik Strandberg

There is an increasing interest in research on the combination of AI techniques and methods with MDE. However, there is a gap between AI and MDE practices, as well as between researchers and practitioners. This paper tackles this gap by reporting on industrial requirements in this field. In the AIDOaRt research project, practitioners and researchers collaborate on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in cyber-physical systems. The project specifically lies at the intersection of industry and academia collaboration with several industrial use cases. Through a process of elicitation and refinement, 78 high-level requirements were defined, and generalized into 30 generic requirements by the AIDOaRt partners. The main contribution of this paper is the set of generic requirements from the project for enhancing the development of cyber-physical systems with artificial intelligence, DevOps, and model-driven engineering, identifying the hot spots of industry needs in the interactions of MDE and AI. Future work will refine, implement and evaluate solutions toward these requirements in industry contexts.

Jan Steinkühler, Piermarco Fonda, Tripta Bhatia et al.

Abstract Biological cells are contained by a fluid lipid bilayer (plasma membrane, PM) that allows for large deformations, often exceeding 50% of the apparent initial PM area. Isolated lipids self‐organize into membranes, but are prone to rupture at small (<2–4%) area strains, which limits progress for synthetic reconstitution of cellular features. Here, it is shown that by preserving PM structure and composition during isolation from cells, vesicles with cell‐like elasticity can be obtained. It is found that these plasma membrane vesicles store significant area in the form of nanotubes in their lumen. These act as lipid reservoirs and are recruited by mechanical tension applied to the outer vesicle membrane. Both in experiment and theory, it is shown that a “superelastic” response emerges from the interplay of lipid domains and membrane curvature. This finding allows for bottom‐up engineering of synthetic biomaterials that appear one magnitude softer and with threefold larger deformability than conventional lipid vesicles. These results open a path toward designing superelastic synthetic cells possessing the inherent mechanics of biological cells.

Noor Abdulkareem AL-Ali, Makarim H. Abdulkareem, Iman Adnan Anoon

In this study, two systems of bio-ceramic coating (45S5 bioactive glass and hydroxyapatite) were used in order to compare between them for biomedical applications. Each system consists from two layers of coating done by electrophoretic deposition (EPD) technique on 316L stainless steel material as substrate. Two types of biopolymer were used (Chitosan with Gelatin) as first layer of coating. Taguchi approach with L9 array was used in order to choose the best conditions (concentrations, voltage and time) for coating layers. Each system consists of two layer (biopolymer (first layer) and bioceramic (second layer)) materials. The optimum parameters for first layer of biopolymer was (3g/L concentration, 20 voltage and 3 minute) while optimum parameters for second layer of bioceramic group (6g/L concentration, 30 voltage and 1 minute) for 45S5 BG system and (6g/L concentration, 40 voltage and 1 minute) for HA system. Zeta potential test were employed to measure suspensions stability. The tape test method was used to evaluate the adhesion between substrate and coating layers, the results show that the percentage of removal area for optimum coating layer (biopolymer, 45S5 BG and HA   8.06%, 10.668%, 6.01% subsequently). XRD inspection was used for identify the phases of coating layers. The Cyclic polarization test was used for evaluation of pitting corrosion resistance, the results show all layers gives good corrosion resistance but 45S5BG system gives the best corrosion resistance when compared with HA system.

Vimal Sam Singh R., Ramachandran Achyuth, Selvam Anirudh et al.

As composites are materials whose properties can essentially be customized to suit the necessities of the engineering application on hand, they are being widely used in many applications for radically different purposes. In order to ensure quality in production process of composite products, a solid understanding of the process involved during its manufacturing is essential to ensure the product is free from both internal and external defects. To that aim, a study was conducted to model Thrust force and Torque on drilling of Glass-Hemp-Flax reinforced polymer composite by fabricating and maching the composite as per Taguchi's L 27 Orthogonal Array. The process parameters considered for modeling are drill diameter, spindle speed and feed rate. Using the process control parameters as inputs and thrust force and torque to be predicted as outputs, artificial neural networks (ANNs) were created to model the effects of the inputs and their interactions. The predictions obtained from the neural networks were compared with the values obtained from experimentation. Excellent agreement was found between the two sets of values, establishing grounds for more extensive use of neural networks in modelling of machining parameters.

Jihyeok Park, Seungmin An, Dongjun Youn et al.

Modern programming follows the continuous integration (CI) and continuous deployment (CD) approach rather than the traditional waterfall model. Even the development of modern programming languages uses the CI/CD approach to swiftly provide new language features and to adapt to new development environments. Unlike in the conventional approach, in the modern CI/CD approach, a language specification is no more the oracle of the language semantics because both the specification and its implementations can co-evolve. In this setting, both the specification and implementations may have bugs, and guaranteeing their correctness is non-trivial. In this paper, we propose a novel N+1-version differential testing to resolve the problem. Unlike the traditional differential testing, our approach consists of three steps: 1) to automatically synthesize programs guided by the syntax and semantics from a given language specification, 2) to generate conformance tests by injecting assertions to the synthesized programs to check their final program states, 3) to detect bugs in the specification and implementations via executing the conformance tests on multiple implementations, and 4) to localize bugs on the specification using statistical information. We actualize our approach for the JavaScript programming language via JEST, which performs N+1-version differential testing for modern JavaScript engines and ECMAScript, the language specification describing the syntax and semantics of JavaScript in a natural language. We evaluated JEST with four JavaScript engines that support all modern JavaScript language features and the latest version of ECMAScript (ES11, 2020). JEST automatically synthesized 1,700 programs that covered 97.78% of syntax and 87.70% of semantics from ES11. Using the assertion-injection, it detected 44 engine bugs in four engines and 27 specification bugs in ES11.

J. Morgenroth, U. Khan, M. Perras

Machine learning methods for data processing are gaining momentum in many geoscience industries. This includes the mining industry, where machine learning is primarily being applied to autonomously driven vehicles such as haul trucks, and ore body and resource delineation. However, the development of machine learning applications in rock engineering literature is relatively recent, despite being widely used and generally accepted for decades in other risk assessment-type design areas, such as flood forecasting. Operating mines and underground infrastructure projects collect more instrumentation data than ever before, however, only a small fraction of the useful information is typically extracted for rock engineering design, and there is often insufficient time to investigate complex rock mass phenomena in detail. This paper presents a summary of current practice in rock engineering design, as well as a review of literature and methods at the intersection of machine learning and rock engineering. It identifies gaps, such as standards for architecture, input selection and performance metrics, and areas for future work. These gaps present an opportunity to define a framework for integrating machine learning into conventional rock engineering design methodologies to make them more rigorous and reliable in predicting probable underlying physical mechanics and phenomenon.