Hasil untuk "Mechanics of engineering. Applied mechanics"

Jaroslav Pokorný, Radek Ševčík, Lucie Zárybnická et al.

Biomass residues from the agricultural industry, logging and wood processing activities have become a valuable fuel source. If processed under pyrolysis combustion, several products are generated. Bio-oil and gases are essential alternatives to fossil coal-based fuels for energy and electricity production, whose need is constantly growing. Biochar, the porous carbon-based lightweight product, often ends up as a soil fertilizer. However, it can be applied in other industrial sectors, e.g., in plastics production or in modifying cementitious materials intended for construction needs. This work dealt with the application of small amounts of softwood-based biochar up to 2.0 wt.% on hydration kinetics and a wide range of physical and mechanical properties, such as water transport characteristics and flexural and compressive strengths of modified cement pastes. In the comparison with reference specimens, the biochar incorporation into cement pastes brought benefits like the reduction of open porosity, improvement of strength properties, and decreased capillary water absorption of 7-day and 28-day-cured cement pastes. Moreover, biochar-dosed cement pastes showed an increase in heat evolution during the hydration process, accompanied by higher consumption of clinker minerals. Considering all examined characteristics, the optimal dosage of softwood-derived biochar of 1.0 wt.% of Portland cement can be recommended.

Filipe R. Cogo, Gustavo A. Oliva, Ahmed E. Hassan

The rapid advancement of AI-assisted software engineering has brought transformative potential to the field of software engineering, but existing tools and paradigms remain limited by cognitive overload, inefficient tool integration, and the narrow capabilities of AI copilots. In response, we propose Compiler.next, a novel search-based compiler designed to enable the seamless evolution of AI-native software systems as part of the emerging Software Engineering 3.0 era. Unlike traditional static compilers, Compiler.next takes human-written intents and automatically generates working software by searching for an optimal solution. This process involves dynamic optimization of cognitive architectures and their constituents (e.g., prompts, foundation model configurations, and system parameters) while finding the optimal trade-off between several objectives, such as accuracy, cost, and latency. This paper outlines the architecture of Compiler.next and positions it as a cornerstone in democratizing software development by lowering the technical barrier for non-experts, enabling scalable, adaptable, and reliable AI-powered software. We present a roadmap to address the core challenges in intent compilation, including developing quality programming constructs, effective search heuristics, reproducibility, and interoperability between compilers. Our vision lays the groundwork for fully automated, search-driven software development, fostering faster innovation and more efficient AI-driven systems.

Vidya Venkatesan, Aomawa L. Shields, Russell Deitrick et al.

Eccentric planets may spend a significant portion of their orbits at large distances from their host stars, where low temperatures can cause atmospheric CO2 to condense out onto the surface, similar to the polar ice caps on Mars. The radiative effects on the climates of these planets throughout their orbits would depend on the wavelength-dependent albedo of surface CO2 ice that may accumulate at or near apoastron and vary according to the spectral energy distribution of the host star. To explore these possible effects, we incorporated a CO2 ice-albedo parameterization into a one-dimensional energy balance climate model. With the inclusion of this parameterization, our simulations demonstrated that F-dwarf planets require 29% more orbit-averaged flux to thaw out of global water ice cover compared with simulations that solely use a traditional pure water ice-albedo parameterization. When no eccentricity is assumed, and host stars are varied, F-dwarf planets with higher bond albedos relative to their M-dwarf planet counterparts require 30% more orbit-averaged flux to exit a water snowball state. Additionally, the intense heat experienced at periastron aids eccentric planets in exiting a snowball state with a smaller increase in instellation compared with planets on circular orbits; this enables eccentric planets to exhibit warmer conditions along a broad range of instellation. This study emphasizes the significance of incorporating an albedo parameterization for the formation of CO2 ice into climate models to accurately assess the habitability of eccentric planets, as we show that, even at moderate eccentricities, planets with Earth-like atmospheres can reach surface temperatures cold enough for the condensation of CO2 onto their surfaces, as can planets receiving low amounts of instellation on circular orbits.

Roberto Verdecchia, Justus Bogner

While mastered by some, good scientific writing practices within Empirical Software Engineering (ESE) research appear to be seldom discussed and documented. Despite this, these practices are implicit or even explicit evaluation criteria of typical software engineering conferences and journals. In this pragmatic, educational-first document, we want to provide guidance to those who may feel overwhelmed or confused by writing ESE papers, but also those more experienced who still might find an opinionated collection of writing advice useful. The primary audience we had in mind for this paper were our own BSc, MSc, and PhD students, but also students of others. Our documented advice therefore reflects a subjective and personal vision of writing ESE papers. By no means do we claim to be fully objective, generalizable, or representative of the whole discipline. With that being said, writing papers in this way has worked pretty well for us so far. We hope that this guide can at least partially do the same for others.

Gajalakshmi G, Meenakshi S

This paper explores the intricate relationship between man and nature in Ernest Hemingway’s The Old Man and the Sea through the lens of deep ecology. It challenges the traditional anthropocentric interpretation of the novella, proposing that the protagonist Santiago’s struggle is not merely a tale of human triumph over nature but a journey towards understanding and coexisting with the natural world. By applying the principles of deep ecology, the study reveals how Santiago’s evolving relationship with the marlin and other sea elements reflects a broader ecological consciousness. The analysis also draws parallels between Santiago’s experience and the Biblical narrative of Jonah, suggesting that Santiago’s success is not solely due to his physical endurance but also the cosmic forces that aid him. This paper ultimately rethinks the themes of struggle and victory in the novella, emphasising the need for a harmonious relationship between humanity and the environment.

Luis Serrano-Gomez, Isabel C. Gil-García, M. Socorro García-Cascales et al.

In the context of isolated photovoltaic (PV) installations, selecting the optimal combination of modules and batteries is crucial for ensuring efficient and reliable energy supply. This paper presents a Decision Support System (DSS) designed to aid in the selection process of the development of new PV isolated installations. Two different multi-criteria decision-making (MCDM) approaches are employed and compared: AHP (Analytic Hierarchy Process) combined with TOPSIS (technique for order of preference by similarity to ideal solution) and Entropy combined with TOPSIS. AHP and Entropy are used to weight the technical and economic criteria considered, and TOPSIS ranks the alternatives. A comparative analysis of the AHP + TOPSIS and Entropy + TOPSIS methods was conducted to determine their effectiveness and applicability in real-world scenarios. The results show that AHP and Entropy produce contrasting criteria weights, yet TOPSIS converges on similar top-ranked alternatives using either set of weights, with the combination of lithium-ion batteries with the copper indium gallium selenide PV module as optimal. AHP allows for the incorporation of expert subjectivity, prioritising costs and an energy yield intuitive to PV projects. Entropy’s objectivity elevates criteria with limited data variability, potentially misrepresenting their true significance. Despite these discrepancies, this study highlights the practical implications of using structured decision support methodologies in optimising renewable energy systems. Even though the proposed methodology is applied to a PV isolated system, it can effectively support decision making for optimising other stand-alone or grid-connected installations, contributing to the advancement of sustainable energy solutions.

Dejene Tadesse Banjaw, Habtamu Gudisa Megersa

Garlic is a versatile vegetable commonly grown in subtropical and highland agroecosystems, which is utilized for its culinary, medicinal, and spice properties. The use of garlic as a medicinal aid can be traced back to ancient times. The health benefits of garlic production are attributed to its antiviral, antibacterial, and antifungal properties. The use of garlic is prevalent in both traditional and modern healthcare systems, where it is used to treat a wide range of conditions. Numerous studies have reported the therapeutic properties of garlic, and its effectiveness has been demonstrated in clinical trials. The growing global interest in health and wellness, the widespread use of garlic as a spice, and its potential economic, social, and health benefits have contributed to a surge in its demand worldwide. This review aims to provide a comprehensive overview of the scientific literature on the morphological descriptions of garlic and its nutritional and health significance.

Shunyuan Mao, Ruobing Dong, Kwang Moo Yi et al.

We introduce Disk2Planet, a machine-learning-based tool to infer key parameters in disk–planet systems from observed protoplanetary disk structures. Disk2Planet takes as input the disk structures in the form of 2D density and velocity maps, and outputs disk and planet properties, that is, the Shakura–Sunyaev viscosity, the disk aspect ratio, the planet–star mass ratio, and the planet’s radius and azimuth. We integrate the Covariance Matrix Adaptation Evolution Strategy, an evolutionary algorithm tailored for complex optimization problems, and the Protoplanetary Disk Operator Network, a neural network designed to predict solutions of disk–planet interactions. Our tool is fully automated and can retrieve parameters in one system in 3 minutes on an Nvidia A100 graphics processing unit. We empirically demonstrate that our tool achieves percent-level or higher accuracy, and is able to handle missing data and unknown levels of noise.

Jieke Shi, Zhou Yang, David Lo

Large Language Models (LLMs) have recently shown remarkable capabilities in various software engineering tasks, spurring the rapid growth of the Large Language Models for Software Engineering (LLM4SE) area. However, limited attention has been paid to developing efficient LLM4SE techniques that demand minimal computational cost, time, and memory resources, as well as green LLM4SE solutions that reduce energy consumption, water usage, and carbon emissions. This paper aims to redirect the focus of the research community towards the efficiency and greenness of LLM4SE, while also sharing potential research directions to achieve this goal. It commences with a brief overview of the significance of LLM4SE and highlights the need for efficient and green LLM4SE solutions. Subsequently, the paper presents a vision for a future where efficient and green LLM4SE revolutionizes the LLM-based software engineering tool landscape, benefiting various stakeholders, including industry, individual practitioners, and society. The paper then delineates a roadmap for future research, outlining specific research paths and potential solutions for the research community to pursue. While not intended to be a definitive guide, the paper aims to inspire further progress, with the ultimate goal of establishing efficient and green LLM4SE as a central element in the future of software engineering.

Yvonne Dittrich, Helen Sharp, Cleidson de Souza

Ethnography has become one of the established methods for empirical research on software engineering. Although there is a wide variety of introductory books available, there has been no material targeting software engineering students particularly, until now. In this chapter we provide an introduction to teaching and learning ethnography for faculty teaching ethnography to software engineering graduate students and for the students themselves of such courses. The contents of the chapter focuses on what we think is the core basic knowledge for newbies to ethnography as a research method. We complement the text with proposals for exercises, tips for teaching, and pitfalls that we and our students have experienced. The chapter is designed to support part of a course on empirical software engineering and provides pointers and literature for further reading.

Eisuke Kita, Norio Kamiya, Youichi Ikeda

This paper presents the boundary-type schemes of the first- and the second-order sensitivity analyses by Trefftz method. In the Trefftz method, physical quantities are approximated by the superposition of the T-complete functions satisfying the governing equations. Since the T-complete functions are regular, the approximate expressions of the quantities are also regular. Therefore, direct differentiation of them leads to the expressions of the sensitivities. Firstly, the Trefftz method for the two-dimensional potential problem is formulated by means of the collocation method. Then, the first- and the second-order sensitivity analysis schemes are explained with the simple numerical examples for their verification.

Jinwu Ye

In the realm of statistical mechanics, it has been established that there is no distinction between the micro-canonical and canonical ensembles in the thermodynamic limit. However, this paradigm may alter when addressing statistical mechanics in the context of a moving sample with a velocity $ v $. Our investigation reveals significant disparities between the two ensembles when considering relativistic effects up to the order of $ (v/c)^2 $. While the temperature remains the same in the former, it experiences an increase in the latter. If the system undergoes a finite-temperature phase transition, the critical temperature decreases in the co-moving frame of the latter ensemble. The implications of these findings on the thermodynamic zeroth to the third laws and the eigenstate thermalization hypothesis are analysed. The potential for the experimental detection of these novel effects in condensed matter systems are discussed.

Ting Zhang, Ivana Clairine Irsan, Ferdian Thung et al.

Software development involves collaborative interactions where stakeholders express opinions across various platforms. Recognizing the sentiments conveyed in these interactions is crucial for the effective development and ongoing maintenance of software systems. For software products, analyzing the sentiment of user feedback, e.g., reviews, comments, and forum posts can provide valuable insights into user satisfaction and areas for improvement. This can guide the development of future updates and features. However, accurately identifying sentiments in software engineering datasets remains challenging. This study investigates bigger large language models (bLLMs) in addressing the labeled data shortage that hampers fine-tuned smaller large language models (sLLMs) in software engineering tasks. We conduct a comprehensive empirical study using five established datasets to assess three open-source bLLMs in zero-shot and few-shot scenarios. Additionally, we compare them with fine-tuned sLLMs, using sLLMs to learn contextual embeddings of text from software platforms. Our experimental findings demonstrate that bLLMs exhibit state-of-the-art performance on datasets marked by limited training data and imbalanced distributions. bLLMs can also achieve excellent performance under a zero-shot setting. However, when ample training data is available or the dataset exhibits a more balanced distribution, fine-tuned sLLMs can still achieve superior results.

Alessandra Aimi, Giulia Di Credico, Heiko Gimperlein

This article proposes a boundary element method for the dynamic contact between a linearly elastic body and a rigid obstacle. The Signorini contact problem is formulated as a variational inequality for the Poincaré-Steklov operator for the elastodynamic equations on the boundary, which is solved in a mixed formulation using boundary elements in the time domain. We obtain an a priori estimate for the resulting Galerkin approximations. Numerical experiments confirm the stability and convergence of the proposed method for the contact problem in flat and curved two-dimensional geometries, as well as for moving obstacles.

Maël Jeulin, Olivier Cahuc, Philippe Darnis et al.

Most of the cutting models developed in the literature attest only to the presence of cutting forces in the balance of mechanical energy resulting from cutting. However, several studies [1–4] have highlighted the presence of cutting moments during machining, and particularly for milling. From a theoretical point of view, a complete energy balance must integrate all the components of the mechanical actions (forces and moments). The predictive model of this study proposes to characterize the evolution of the moments in the cutting zone for milling. The objective is to determine a model similar to the cutting forces which expresses a relationship with the chip section define by the Kc coefficient but by integrating the specific behavior of the moments. This work gives perspectives from an energetic point of view for which the part of moments in the energy balance could be substantial for specific configurations as small-radius tools or high-speed milling.

Josh E. Baker

With potential relevance to biomechanics, an interesting problem in statistical mechanics not previously solved is a binary mechanical model system. Discrete chemical states of proteins are often associated with discrete metastable structural states, such that with a change in state a protein acts as a molecular switch. An ensemble of molecular switches that displace compliant elements equilibrated with an external force, F, constitutes a binary mechanical model system. As one in a series of publications developing this model, here I consider the mechanical performance of this system. Four processes naturally emerge from a transient analysis which are consistent with the four phases observed in a muscle force transient.

Daniel Regulin, Thomas Aicher, Birgit Vogel-Heuser

For improving flexibility and robustness of the engineering of automated production systems (aPS) in case of extending, reducing or modifying parts, several approaches propose an encapsulation and clustering of related functions, e.g. from the electrical, mechanical or software engineering, based on a modular architecture. Considering the development of these modules, there are different stages, e.g. module planning or functional engineering, which have to be completed. A reference model that addresses the different stages for the engineering of aPS is proposed by AutomationML. Due to these different stages and the integration of several engineering disciplines, e.g. mechanical, electrical/electronic or software engineering, information not limited to one discipline are stored redundantly increasing the effort to transfer information and the risk of inconsistency. Although, data formats for the storage and exchange of plant engineering information exist, e.g. AutomationML, fixed domain specific structures and relations of the information, e.g. for automated material flow systems (aMFS), are missing. This paper presents the integration of a meta model into the development of modules for aMFS to improve the transferability and consistency of information between the different engineering stages and the increasing level of detail from the coarse-grained plant planning to the fine-grained functional engineering.

Waseem Siddique, Aneeq Raheem, Muhammad Aqeel et al.

Heat transfer augmentation has become the utmost industrial desire. Turbulence promoters seems to be a better option for better heat transfer but at the expense of enormous pressure drop. In the current study, experimental optimization of heat transfer and pressure drop in various configurations of ribbed and corrugated surfaces on the bottom wall of the Solar Air Heater channel, having aspect ratio of 26:5 was performed. The results were evaluated in terms of enhancement in heat transfer (Nu/Nu s), friction factor ratio (f/f s) and thermal performance factor ( η). Three different cases and nine configurations with a pitch to rib/corrugation height ratio of 4.0 were studied. Case A consists of a smooth, continuous square rib, inline and staggered broken ribs. Case B comprises 30°, 45°, 60° and 90° trapezoidal corrugated geometries while Case C is the comparison of smooth, wavy corrugated and the best configurations of cases A and B. The results show that rectangular duct with staggered broken ribs and trapezoidal corrugation at 45° are the best configurations for case A and B, respectively. The 45° corrugated configuration is the best one amongst all, with values of 1.53, 1.5 and 1.33% for Nu/Nu s, f/f s and η respectively.

Bob Eisenberg

Statistical mechanics has grown without bounds in space. Statistical mechanics of point particles in an unbounded perfect gas is commonly accepted as a foundation for understanding many systems, including liquids like the concentrated salt solutions of life and electrochemical technology, from batteries to nanodevices. Liquids, however, are not gases. Liquids are filled with interacting molecules and so the model of a perfect gas is imperfect. Here we show that statistical mechanics without bounds (in space) is impossible as well as imperfect, if the molecules interact as charged particles, as nearly all atoms do. The behavior of charged particles is not defined until boundary structures and values are defined because charges are governed by the Maxwell partial differential equations. Partial differential equations require boundary conditions to be computable or well defined. The Maxwell equations require boundary conditions on finite sized spatial boundaries (i.e., structures). Boundary conditions cannot be defined 'at infinity' in a general (i.e., unique) way because the limiting process that defines infinity includes such a wide variety of behavior, from light waves that never decay, to fields from dipole and multipolar charges that decay steeply, to Coulomb fields that decay but not so steeply. Statistical mechanics involving charges thus involves spatial boundaries and boundary conditions of finite size. Nearly all matter involves charges, thus nearly all statistical mechanics requires structures and boundary conditions on those structures. Boundaries and boundary conditions are not prominent in classical statistical mechanics. Including boundaries is a challenge to mathematicians. Statistical mechanics must describe bounded systems if it is to provide a proper foundation for studying matter.

Antti Knutas, Timo Hynninen, Maija Hujala

Student evaluations of teaching (SET) are commonly used in universities for assessing teaching quality. However, previous literature shows that in software engineering students tend to rate certain topics higher than others: In particular students tend to value programming and software construction over software design, software engineering models and methods, or soft skills. We hypothesize that these biases also play a role in SET responses collected from students. The objective of this study is to investigate how the topic of a software engineering course affects the SET metrics. We accomplish this by performing multilevel regression analysis on SET data collected in a software engineering programme. We analyzed a total of 1295 student evaluations from 46 university courses in a Finnish university. The results of the analysis verifies that the student course evaluations exhibit similar biases as distinguished by previous software engineering education research. The type of the course can predict a higher SET rating. In our dataset, software construction and programming courses received higher SET ratings compared to courses on software engineering processes, models, and methods.