Hasil untuk "Mechanics of engineering. Applied mechanics"

Jorge Melegati

The adoption of Generative AI (GenAI) suggests major changes for software engineering, including technical aspects but also human aspects of the professionals involved. One of these aspects is how individuals perceive themselves regarding their work, i.e., their work identity, and the processes they perform to form, adapt and reject these identities, i.e., identity work. Existent studies provide evidence of such identity work of software professionals triggered by the adoption of GenAI, however they do not consider differences among diverse roles, such as developers and testers. In this paper, we argue the need for considering the role as a factor defining the identity work of software professionals. To support our claim, we review some studies regarding different roles and also recent studies on how to adopt GenAI in software engineering. Then, we propose a research agenda to better understand how the role influences identity work of software professionals triggered by the adoption of GenAI, and, based on that, to propose new artifacts to support this adoption. We also discuss the potential implications for practice of the results to be obtained.

Jinhai Zhao, Gang Zong, Shimin Zhang et al.

Steel structure specimens exhibit high strength and ductility and are often subjected to complex loading conditions and pre-existing cracks in critical engineering applications. In this study, peridynamics (PD) theory—known for its unique advantages in modeling structural damage and failure—is employed to establish specimens with bilateral cracks and double central cracks at varying longitudinal spacings. To address the complexity of elastic–plastic behavior, the D-M model is applied to transform the nonlinear problem into an equivalent linear elastic one. This approach is integrated with PD theory and the crack tip opening displacement (COD) concept of fracture mechanics to derive a novel linear fracture criterion, termed the PD-COD. Furthermore, numerical models based on PD and the PD-COD criterion are developed for central cross double-crack specimens, enabling analysis of crack propagation under loading. The results validate the effectiveness of the PD-COD damage criterion and elucidate the underlying mechanisms of crack propagation in centrally intersecting double-crack configurations. This work contributes to a deeper understanding of the damage evolution in defective steel structures under load and provides theoretical guidance for engineering design.

Randi Purnama Putra, Dori Yuvenda, Remon Lapisa et al.

The development of lightweight electric cars for urban mobility requires efficient aerodynamic design without sacrificing space efficiency. This study presents a novel method by investigating the combination of a two-seater city car's compact dimensions and square back shape, which has not been extensively researched for low- to medium-velocity vehicles. This study's objective is to assess the design's aerodynamic performance using numerical simulations using the Computational Fluid Dynamics (CFD) approach. The vehicle model is designed with a compact body and square back, which is commonly used in small vehicles with high maneuverability requirements. The simulations are conducted at three different air velocity levels: 10, 20, and 30 m/s. The results of the study showed an increase in the value of the drag coefficient (Cd) along with an increase in flow velocity. At a velocity of 10 m/s, the Cd value was recorded at 0.4536. When the velocity increased to 20 m/s, the drag coefficient increased slightly to 0.4563. Further increases in velocity to 30 m/s resulted in a Cd value of 0.4581. This Cd value shows the consistency of aerodynamic performance with increasing velocity, with fluctuations that remain within the efficiency limits of lightweight vehicles. The pressure distribution contour shows high-pressure accumulation at the front and low pressure at the rear of the vehicle, which generates large turbulent wakes in the rear area and contributes to increased drag. These findings indicate that the square rear body design faces significant aerodynamic challenges. Therefore, design strategies such as adding a rear spoiler, using a rear diffuser, and optimizing the rear body angle are suggested as potential solutions to improve flow efficiency.

Raja Vavekanand, Aybek Kalandarov Ruzimbaevich, Muhabbat Jumaniyozova

Large language models (LLMs) excel at various natural language tasks, even those beyond their explicit training. Fine-tuning these models on smaller datasets enhances their performance for specific tasks but it can also lead to risk of training data memorization, raising privacy concerns. This study explores the extraction of private training data from fine-tuned LLMs through a series of experiments. The focus is on assessing the ease of data extraction using various techniques and examining how factors such as the size of training data, number of epochs, training sample length and content, and fine-tuning parameters influence this process. Our results indicate that data extraction is relatively straightforward with direct model access, especially when training loss is computed over entire prompts. Models with higher precision (8-bit and 16-bit) demonstrate increased memorization capabilities compared to 4-bit quantized models. Even without direct access, insights into training data can be obtained by comparing output probability scores across multiple queries. Furthermore, the study also reveals that the proportion of extractable data increases with training dataset size, given a fixed number of epochs. These findings highlight the privacy risks faced by individuals whose data is used in fine-tuning, as well as for organizations deploying fine-tuned models in public applications.

Minglun Li, Marina Ruths, Bilin Zhuang et al.

Surface polyelectrolyte brush materials responsive to solvent quality and added ions have widespread applications in interfacial materials. The interplay between solvent quality and ion valency plays a pivotal role in determining the conformation of polyelectrolyte brushes, yet its mechanisms remain underexplored. In this study, we systematically investigate these coupling effects on sodium poly(styrene sulfonate) (PSS) brushes through a combination of theoretical modeling, all-atom molecular dynamics (MD) simulations, and atomic force microscopy (AFM) experiments. By tuning the water-to-isopropyl alcohol (IPA) ratio in binary solvents, we reveal that solvent quality drives a gradual decrease in brush height, culminating in a rapid collapse at higher IPA volume fractions (ϕIPA≈0.8). Theoretically, we extend our unified framework for ion-valency effects to incorporate Flory–Huggins interaction parameters derived from solvent solubility parameters, yielding predictions consistent with experimental and simulation results. Our findings highlight that the solvent-polymer interactions govern brush height more significantly than dielectric constants in mixed solvents. Solvent-induced brush collapse occurs uniformly, whereas multivalent ions induce localized adsorption, leading to chain aggregation and non-homogeneous collapse. The constructed brush height landscape further demonstrates that solvent quality predominates for short chains, while both solvent quality and ion valency exhibit synergistic and nonlinear effects on longer chains, with pronounced collapse transitions observed under specific conditions. This study provides a comprehensive understanding of the coupled effects of solvent quality and ion valency on polyelectrolyte brushes, offering valuable insights for designing stimuli-responsive surfaces. These findings are particularly relevant for applications in vapor sensing, gas separation, and advanced surface engineering technologies, where precise control over brush height and morphology is crucial.

Alexandre Epalle, Isabelle Ramière, Guillaume Latu et al.

Parallel implementation of numerical adaptive mesh refinement (AMR)strategies for solving 3D elastostatic contact mechanics problems is an essential step toward complex simulations that exceed current performance levels. This paper introduces a scalable, robust, and efficient algorithm to deal with 2D and 3D elastostatics contact problems between deformable bodies in a finite element framework. The proposed solution combines a treatment of the contact problem by a node-to-node pairing algorithm with a penalization technique and a non-conforming h-adaptive refinement of quadrilateral/hexahedral meshes based on an estimate-mark-refine approach in a parallel framework. One of the special features of our parallel strategy is that contact paired nodes are hosted by the same MPI tasks, which reduces the number of exchanges between processes for building the contact operator. The mesh partitioning introduced in this paper respects this rule and is based on an equidistribution of elements over processes, without any other constraints. In order to preserve the domain curvature while hierarchical mesh refinement, super-parametric elements are used. This functionality enables the contact zone to be well detected during the AMR process, even for an initial coarse mesh and low-order discretization schemes. The efficiency of our contact-AMR-HPC strategy is assessed on 2D and 3D Hertzian contact problems. Different AMR detection criteria are considered. Various convergence analyses are conducted. Parallel performances up to 1024 cores are illustrated. Furthermore, memory footprint and preconditionners performance are analyzed.

Bruce D. Popp

This paper reviews a paper from 1906 by J. Henri Poincaré on statistical mechanics with a background in his earlier work and notable connections to J. Willard Gibbs. Poincaré's paper presents important ideas that are still relevant for understanding the need for probability in statistical mechanics. Poincaré understands the foundations of statistical mechanics as a many-body problem in analytical mechanics (reflecting his 1890 monograph on The Three-Body Problem and the Equations of Dynamics) and possibly influenced by Gibbs independent development published in chapters in his 1902 book, Elementary Principles in Statistical Mechanics. This dynamical systems approach of Poincaré and Gibbs provides great flexibility including applications to many systems besides gasses. This foundation benefits from close connections to Poincaré's earlier work. Notably, Poincaré had shown (e.g. in his study of non-linear oscillators) that Hamiltonian dynamical systems display sensitivity to initial conditions separating stable and unstable trajectories. In the first context it precludes proving the stability of orbits in the solar system, here it compels the use of ensembles of systems for which the probability is ontic and frequentist and does not have an a priori value. Poincaré's key concepts relating to uncertain initial conditions, and fine- and coarse-grained entropy are presented for the readers' consideration. Poincaré and Gibbs clearly both wanted to say something about irreversibility, but came up short.

Ruchi Kansal, Mahtab Ahmed

The paper discusses the role of social marketing in preventing health-related harmful habits such as tobacco consumption and smoking. These habits are the causes of deadly diseases such as lung cancer, tuberculosis, and other chronic infections which are detrimental to life of the people. Children fall prey to the wrong habits in the wrong company and become tobacco addicts. So many cases of teen drug addicts are reported in a large number. They have a lack of conscience at a tender age and negligence of their counselling and awareness increases the number of smokers, drunkards, and drug addicts. Once they are afflicted with the diseases they must run for medicines and treatment. Therefore, it should be prevented before suffering as the saying goes, “Prevention is better than cure “. They are unaware that they are prevented not only by clinical treatment and medicines but also by social awareness and education. Social mobilization of the people through awareness programs, education, camps, campaigns, etc. is known as social marketing. The significance of social marketing is its effects on the prevention of physically detrimental habits in the youth which contributed a lot to the reduction of cases of diseases. The role of government programs, educational and medical institutions, social workers, and NGOs is worth applauding in India which undertake and complete projects, organize awareness camps, and educate parents and youths to save themselves from the consumption of harmful substances. It has also produced good output in India that the cases of smoking and drug addiction have reduced to support the country’s development as India is advancing towards becoming the third largest economy and a developed country by 2030 and 2047 respectively.

Chenlu Kang, Pengcheng Chen, Xin Yi et al.

Cell migration towards stiff substrates has been coined as durotaxis and implicated in development, wound healing, and cancer, where complex interplays between immune and non-immune cells are present. Compared to the emerging mechanisms underlying the strongly adhesive mesenchymal durotaxis, little is known about whether immune cells - migrating in amoeboid mode - could follow mechanical cues. Here, we develop an imaging-based confined migration device with a stiffness gradient. By tracking live cell trajectory and analyzing the directionality of T cells and neutrophils, we observe that amoeboid cells can durotax. We further delineate the underlying mechanism to involve non-muscle myosin IIA (NMIIA) polarization towards the soft-matrix-side but may not require differential actin flow up- or down-stiffness gradient. Using the protista Dictyostelium, we demonstrate the evolutionary conservation of amoeboid durotaxis. Finally, these experimental phenomena are theoretically captured by an active gel model capable of mechanosensing. Collectively, these results may shed new lights on immune surveillance and recently identified confined migration of cancer cells, within the mechanically inhomogeneous tumor microenvironment or the inflamed fibrotic tissues.

Cuiyun Gao, Xing Hu, Shan Gao et al.

With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the field of software engineering (SE) has also witnessed a paradigm shift. These models, by leveraging the power of deep learning and massive amounts of data, have demonstrated an unprecedented capacity to understand, generate, and operate programming languages. They can assist developers in completing a broad spectrum of software development activities, encompassing software design, automated programming, and maintenance, which potentially reduces huge human efforts. Integrating LLMs within the SE landscape (LLM4SE) has become a burgeoning trend, necessitating exploring this emergent landscape's challenges and opportunities. The paper aims at revisiting the software development life cycle (SDLC) under LLMs, and highlighting challenges and opportunities of the new paradigm. The paper first summarizes the overall process of LLM4SE, and then elaborates on the current challenges based on a through discussion. The discussion was held among more than 20 participants from academia and industry, specializing in fields such as software engineering and artificial intelligence. Specifically, we achieve 26 key challenges from seven aspects, including software requirement & design, coding assistance, testing code generation, code review, code maintenance, software vulnerability management, and data, training, and evaluation. We hope the achieved challenges would benefit future research in the LLM4SE field.

S. Cheng, S. Cheng, X. Cheng et al.

<p>The tropospheric concentrations of nitrogen dioxide (NO<span class="inline-formula">₂</span>) and formaldehyde (HCHO) have high spatio-temporal variability, and in situ observations of these trace gases are still scarce, especially in remote background areas. We made four similar circling journeys of mobile multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in the Three Rivers' Source region over the Tibetan Plateau in summer (18–30 July) 2021 for the first time. The differential slant column densities (DSCDs) of NO<span class="inline-formula">₂</span> and HCHO were retrieved from the measured spectra, with very weak absorptions along the driving routes. The tropospheric NO<span class="inline-formula">₂</span> and HCHO vertical column densities (VCDs) were calculated from their DSCDs by the geometric approximation method, and they were further filtered to form reliable data sets by eliminating the influences of sunlight shelters and the vehicle's vibration and bumpiness. The observational data show that the tropospheric NO<span class="inline-formula">₂</span> and HCHO VCDs decreased with the increasing altitude of the driving route, whose background levels <span class="inline-formula">±</span> standard deviations were 0.40 <span class="inline-formula">±</span> <span class="inline-formula">1.13×10¹⁵</span> molec. cm<span class="inline-formula">⁻²</span> for NO<span class="inline-formula">₂</span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M12" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">2.27</mn><mo>±</mo><mn mathvariant="normal">1.66</mn><mo>×</mo><msup><mn mathvariant="normal">10</mn><mn mathvariant="normal">15</mn></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="88pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="8269baa0786241d04505b2cd3bb4a517"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-3655-2023-ie00001.svg" width="88pt" height="14pt" src="acp-23-3655-2023-ie00001.png"/></svg:svg></span></span> molec. cm<span class="inline-formula">⁻²</span> for HCHO in July 2021 over the Three Rivers' Source region. The NO<span class="inline-formula">₂</span> VCDs show similar geographical distribution patterns between the different circling journeys, but the levels of the HCHO VCDs are different between the different circling journeys. The elevated NO<span class="inline-formula">₂</span> VCDs along the driving routes usually corresponded to enhanced transport emissions from the towns crossed. However, the spatial distributions of the HCHO VCDs depended significantly on natural and meteorological conditions, such as surface temperature. By comparing TROPOMI satellite products and mobile MAX-DOAS results, we found that TROPOMI NO<span class="inline-formula">₂</span> and HCHO VCDs have large positive offsets in the background atmosphere over the main area of the Three Rivers' Source. Our study provides valuable data sets and information of NO<span class="inline-formula">₂</span> and HCHO over the Tibetan Plateau, benefitting the scientific community in investigating the spatio-temporal evolution of atmospheric composition in the background atmosphere at high altitudes, validating and improving the satellite products over mountain terrains, and evaluating the model's ability to simulate atmospheric chemistry over the Tibetan Plateau.</p>

Luis Espinoza, Jose Antonio Bea, Sourojeet Chakraborty et al.

While several theoretical and experimental studies for cracks in piping exist, most pertain to pipelines, equipment, or fittings under pressure conditions or under stress corrosion conditions at welding. Element finite Method models have occasionally supplemented experimental methods, to investigate such operational fails. In this approach we explore technical options to comprehensively understand crack propagations, by first, evaluating the Stress Intensity Factor (KI) using ANSYS Parametric design language then, comparing with the Displacement Correlation Technique, for an elliptical base gas piping (20″APL Gr. B) suffering a longitudinal welding-induced crack, under a compression of 1.86 MPa. The KIvalue for an Electric Resistance Welding crack was calculated for the two-dimensional plane, for a quarter-length of propagated crack along the elliptical front. The KI value estimates are 0.94x(10)−3 MPam from ANSYS Parametric design language vs. 0.70x(10)−2 MPamfrom DCT the two methods are close less than 1. These results were compared with the theorical stress intensity factor for elliptical cracks by Broek11 Broek, D. (1984). Elementary engineering fracture mehcanics . The Hague: Martinus Nijhoff Publishers. David called elementary engineering fracture mechanics where the values were 0.5x(10)−1 MPam. We found that the proposed FEM method for estimating (KI)is the approach that is closest to the theoretical value.

Reza Aghayari, Ammar Al-Mwanes

Nowadays fire has become one of the large prominent threats to buildings and concrete structures in the world. In this research, an experimental study was performed to examine the spalling phenomenon and residual mechanical properties of fiber toughened Ultra-High-Performance Concrete (polypropylene (PPF) and steel fibers (SF)). Moreover, the effect of high temperatures, namely, 250 ºC and 500 ºC for 2.5 hours and 5 hours has been studied for each mix of samples. This research discussed the results of compressive strength, flexural tensile strength, and splitting strength. Weight loss of the specimens and the effect of hybrid fibers incorporation (PPF and SF) behavior Ultra-High-Performance Concrete at high temperature were studied. The study concludes that the residual resistance of UHPC decreases as the temperature increases. Also, increasing the heating time resulted in lowering the residual concrete strength. The addition of the optimum percentage of PPF (0.8%) results in a remarkable effect on decreasing the risk of spalling in the UHPFRC. Polypropylene fibers provide channels in the concrete for this reduced pore pressures and the risk of spalling. Incorporating hybrid fiber seems to enhance the resistance of UHPFRC to explosive spalling due to the significant increase of permeability in UHPFRC. In addition to that, the steel fibers will increase the ductility of the UHPFRC and render it more able to withstand the high internal pressures which were experimentally confirmed by this work.

Saeed Asiri

Functionally Graded Materials (FGM) are extensively employed for hip plant component material due to their certain properties in a specific design to achieve the requirements of the hip-joint system. Nevertheless, if there are similar properties, it doesn’t necessarily indicate that the knee plant is efficiently and effectively working. Therefore, it is important to develop an ideal design of functionally graded material femoral components that can be used for a long period. A new ideal design of femoral prosthesis can be introduced using functionally graded fiber polymer (FGFP) which will reduce the stress shielding and the corresponding stresses present over the interface. Herein, modal analysis of the complete hip plant part is carried out, which is the main factor and to date, very few research studies have been found on it. Moreover, this enhances the life of hip replacement, and the modal, harmonic, and fatigue analysis determines the pre-loading failure phenomena due to the vibrational response of the hip. This study deals with the cementless hip plant applying the finite element analysis (FEA) model in which geometry is studied, and the femoral bone model is based in a 3D scan.

Sadjad Arzash, Abhinav Sharma, Fred C. MacKintosh

Biopolymer networks are common in biological systems from the cytoskeleton of individual cells to collagen in the extracellular matrix. The mechanics of these systems under applied strain can be explained in some cases by a phase transition from soft to rigid states. For collagen networks, it has been shown that this transition is critical in nature and it is predicted to exhibit diverging fluctuations near a critical strain that depends on the network's connectivity and structure. Whereas prior work focused mostly on shear deformation that is more accessible experimentally, here we study the mechanics of such networks under an applied bulk or isotropic extension. We confirm that the bulk modulus of subisostatic fiber networks exhibits similar critical behavior as a function of bulk strain. We find different non-mean-field exponents for bulk as opposed to shear. We also confirm a similar hyperscaling relation to what previously found for shear.

Ana Pavlovic, Cristiano Fragassa, Marco Bertoldi et al.

This research outlines the numerical predictions of the heat distribution in solar cells, accompanied by their empirical validation. Finite element thermal models of five laminated silicon solar photovoltaic cells were firstly established using a simulation software (ANSYS®). The flexible laminated solar cells under study are made of a highly transparent frontsheet, a silicon cell between two encapsulants, and a backsheet. Different combinations of layers (i.e., materials and thicknesses) were taken into account in order to analyze their effect on thermal behavior. Thermal properties of materials were derived in accordance with the literature. Similarly, boundary conditions, loads, and heat losses by reflection and convection were also specified. The solar cells were tested using solar lamps under standard conditions (irradiance: 1000W/m2; room-temperature: 25°C) with real-time temperatures measured by a thermal imager. This analysis offers an interpretation of how temperature evolves through the solar cell and, consequently, how the design choice can influence the cells’ efficiency.

Wilhelm Hasselbring

In empirical software engineering, benchmarks can be used for comparing different methods, techniques and tools. However, the recent ACM SIGSOFT Empirical Standards for Software Engineering Research do not include an explicit checklist for benchmarking. In this paper, we discuss benchmarks for software performance and scalability evaluation as example research areas in software engineering, relate benchmarks to some other empirical research methods, and discuss the requirements on benchmarks that may constitute the basis for a checklist of a benchmarking standard for empirical software engineering research.

Alex Serban, Koen van der Blom, Holger Hoos et al.

The increasing reliance on applications with machine learning (ML) components calls for mature engineering techniques that ensure these are built in a robust and future-proof manner. We aim to empirically determine the state of the art in how teams develop, deploy and maintain software with ML components. We mined both academic and grey literature and identified 29 engineering best practices for ML applications. We conducted a survey among 313 practitioners to determine the degree of adoption for these practices and to validate their perceived effects. Using the survey responses, we quantified practice adoption, differentiated along demographic characteristics, such as geography or team size. We also tested correlations and investigated linear and non-linear relationships between practices and their perceived effect using various statistical models. Our findings indicate, for example, that larger teams tend to adopt more practices, and that traditional software engineering practices tend to have lower adoption than ML specific practices. Also, the statistical models can accurately predict perceived effects such as agility, software quality and traceability, from the degree of adoption for specific sets of practices. Combining practice adoption rates with practice importance, as revealed by statistical models, we identify practices that are important but have low adoption, as well as practices that are widely adopted but are less important for the effects we studied. Overall, our survey and the analysis of responses received provide a quantitative basis for assessment and step-wise improvement of practice adoption by ML teams.

Neil A. Ernst, Jeffrey C. Carver, Daniel Mendez et al.

Peer review is a key activity intended to preserve the quality and integrity of scientific publications. However, in practice it is far from perfect. We aim at understanding how reviewers, including those who have won awards for reviewing, perform their reviews of software engineering papers to identify both what makes a good reviewing approach and what makes a good paper. We first conducted a series of in-person interviews with well-respected reviewers in the software engineering field. Then, we used the results of those interviews to develop a questionnaire used in an online survey and sent out to reviewers from well-respected venues covering a number of software engineering disciplines, some of whom had won awards for their reviewing efforts. We analyzed the responses from the interviews and from 175 reviewers who completed the online survey (including both reviewers who had won awards and those who had not). We report on several descriptive results, including: 45% of award-winners are reviewing 20+ conference papers a year, while 28% of non-award winners conduct that many. 88% of reviewers are taking more than two hours on journal reviews. We also report on qualitative results. To write a good review, the important criteria were it should be factual and helpful, ranked above others such as being detailed or kind. The most important features of papers that result in positive reviews are clear and supported validation, an interesting problem, and novelty. Conversely, negative reviews tend to result from papers that have a mismatch between the method and the claims and from those with overly grandiose claims. The main recommendation for authors is to make the contribution of the work very clear in their paper. In addition, reviewers viewed data availability and its consistency as being important.

K. Tůma, M. Rezaee-Hajidehi, J. Hron et al.

Large-scale 3D martensitic microstructure evolution problems are studied using a finite-element discretization of a finite-strain phase-field model. The model admits an arbitrary crystallography of transformation and arbitrary elastic anisotropy of the phases, and incorporates Hencky-type elasticity, a penalty-regularized double-obstacle potential, and viscous dissipation. The finite-element discretization of the model is performed in Firedrake and relies on the PETSc solver library. The large systems of linear equations arising are efficiently solved using GMRES and a geometric multigrid preconditioner with a carefully chosen relaxation. The modeling capabilities are illustrated through a 3D simulation of the microstructure evolution in a pseudoelastic CuAlNi single crystal during nano-indentation, with all six orthorhombic martensite variants taken into account. Robustness and a good parallel scaling performance have been demonstrated, with the problem size reaching 150 million degrees of freedom.