Hasil untuk "Materials of engineering and construction. Mechanics of materials"

Mi Zhou, Wei Lu, Jianwei Song et al.

LIU Xinyuan, JI Yue, QU Ying et al.

Purposes Data-driven transient stability assessment of power systems has become the mainstream research direction at this stage. However, in the practical applications, there are still problems such as too few unstable samples and lack of consideration of the impact of power system spatial topology information on transient stability assessment. In view of these issues, a new transient stability assessment model based on conditional generative adversarial network (CGAN) and graph convolution network (GCN) is proposed. Methods First, CGAN was used to perform targeted enhancement on sparsely distributed unstable samples as a link between the original unbalanced data set and the data-driven transient stability discrimination method, so as to achieve accurate optimization of the extremely unbalanced original data set. Then, the spatial topology information of the power grid was introduced as input, and the GCN was used to mine the spatial feature relationship of the power grid. After that, the transient stability assessment model was constructed by combining the feature vector of the node itself and its transient stability label, which enhances the model’s generalization ability for changes in power grid operation mode and topological structure. Finally, simulation verifications were carried out on the IEEE-39 node system and the IEEE-118 node system. Conclusions The results show that the proposed CGAN-GCN transient stability assessment model has improved accuracy and demonstrates strong generalization ability during model topology changes.

Krzysztof Grzyb, Łukasz Drobiec, Jakub Zając et al.

The castle in Malbork is one of the most representative brick buildings in the world and an excellent example of medieval defensive and residential architecture in Central Europe. This facility is a top-class monument, as evidenced by its inclusion on the UNESCO World Heritage List. Although it might seem that the subsoil is consolidated within the castle and no new cracks should be visible in the masonry structure - recent years have shown that the facility still requires both systematic monitoring of displacements and comprehensive structural diagnostics. Damage was observed in the Palace of the Grand Masters, particularly on the eastern wall and the barrel and palm vaults. The paper presents a preliminary analysis of palace damage and observed cracks. The assessment of the technical condition of the walls and the causes of the structural irregularities was carried out based on local inspections and tests of the structure, including geodetic measurements, ultrasonic tomograph tests and geophysical tests performed using the GPR method using the short-offset reflective profiling (GPR) technique. Additionally, destructive tests were also performed by drilling holes in the basement floor with the introduction of an inspection camera. It was found that the cause of the damage was uneven settlement of the subsoil. Additionally, it was found that there is probably a previously undiscovered brick vault below the basement floor, where visual inspection holes have been made.

Klaudia Trembecka-Wójciga, Sylwia Terlicka, Karol Janus et al.

The design of multifunctional ceramic–metal composites is essential for advancing high-performance materials in both structural and biomedical fields. Here, we report for the first time the infiltration, magnesiothermic reduction of zirconia, and interfacial bond formation within 3D-printed porous scaffolds exposed to molten magnesium. This redox-driven transformation converts stoichiometric ZrO2 into oxygen-deficient black zirconia (ZrO2−x), creating oxygen vacancies. Although sessile drop tests revealed macroscopically poor wetting, permanent Mg–ZrO2−x bonds were established through interfacial oxygen transfer, underscoring the decisive role of oxygen management in joining otherwise non-wetting systems. Infiltration of molten Mg into porous scaffolds occurred only under force-assisted injection, demonstrating that external pressure is required to achieve effective penetration in such architectures. Metallographic analysis further revealed a discontinuous distribution of Mg, dictated by pore geometry and interfacial reactions. These findings identify oxygen vacancy formation and pressure-assisted infiltration as key parameters for Mg/ZrO2 integration and provide a framework for designing bioinspired interpenetrating composites where chemical reactivity complements mechanical infiltration.

Izim Turker Kader, Yurdanur Ucar, Pinar Kursoglu

ABSTRACT The degree of conversion (DC) is a critical determinant of the biocompatibility and long‐term performance of occlusal splints. However, limited evidence exists on how emerging three‐dimensional printing technologies, particularly masked stereolithography (MSLA), affect polymerization efficiency compared to established methods. This study investigated the DC of a photopolymer‐based occlusal splint resin fabricated using stereolithography (SLA) and MSLA technologies, compared to a conventional heat‐polymerized acrylic resin. DC was assessed by Fourier Transform Infrared Spectroscopy (FTIR) at three stages for printed specimens: the unpolymerized resin, after printing and washing (DC Print), and after post‐curing (final DC). The difference between DC Print and final DC (ΔDC) represented the contribution of the post‐curing step. Conventional specimens were evaluated after mixing and after polymerization. The final DC of the conventional group was significantly higher than both SLA and MSLA groups (p < 0.001), although SLA and MSLA did not differ significantly (p > 0.05). Post‐curing significantly enhanced polymerization in both printed groups. MSLA printing achieved comparable DC to SLA while reducing production time. These findings support MSLA as a promising and time‐efficient method for splint fabrication, though further improvements in resin formulation and post‐curing protocols are warranted to match the polymerization efficiency of conventional heat‐polymerized acrylics.

O Kachouri, J Bardon, D Ruch et al.

The emergence of debonding technologies has enabled adhesive systems to better align with the principles of sustainability and the circular economy by addressing the gap between the end-of-life stage of adhesively bonded products and the potential for component reuse. In this context, the present study explores the application of thermally responsive additives to induce controlled debonding in adhesive joints. In our previous investigations, it was shown that integrating various types of flame retardants (intumescent and non-intumescent) significantly reduced the debonding temperature, by altering the thermomechanical properties of the joint at temperatures substantially lower than the degradation onset of the unmodified adhesive system. Expandable graphite (EG), a thermally responsive material, has previously been employed with success for similar purposes. Its incorporation into the adhesive layer, even in trace amounts, results in a very significant expansion upon the application of heat, thereby providing an effective mechanism for disassembling adhesively bonded structural assemblies. The present study builds on this prior research and probes deeper into the manufacturing processes underlying EG. The primary hypothesis explored is whether tailoring these processes can result in modulating the thermal response of adhesives modified by EG, thereby achieving debonding at distinct temperature ranges suitable for a wide spectrum of applications. This study investigates EG-modified adhesives, assessing their mechanical properties, thermomechanical degradation, and microstructural changes using characterization techniques such as pull-off tests, microtomography, TGA, and DMA. Finally, the recycling potential is demonstrated through the successful reuse of debonded substrates after a simple cleaning process.

Tomi Suomi, Petri Ihantola, Tommi Mikkonen et al.

Agile software development relies on self-organized teams, underlining the importance of individual responsibility. How developers take responsibility and build ownership are influenced by external factors such as architecture and development methods. This paper examines the existing literature on ownership in software engineering and in psychology, and argues that a more comprehensive view of ownership in software engineering has a great potential in improving software team's work. Initial positions on the issue are offered for discussion and to lay foundations for further research.

Wei Xun, Xin Liu, Youdong Zhang et al.

Altermagnetism, as a newly identified form of unconventional antiferromagnetism, enables the removal of spin degeneracy in the absence of net magnetization that provides a platform for the low power consumption and ultra-fast device applications. However, the rare attention has been paid to the relationship between stacking, strain and altermagnet, multipiezo effect and topological state. Here, we propose a mechanism to realize the altermagnet, multipiezo effect, and topological state in two-dimensional materials by the stacking and strain engineering. Based on the analysis of symmetry, we find that the spin splitting feature related to the Ut, PTt, MzUt, or MzPTt symmetries in altermagnet multilayers. In addition, we find that the stacking engineering can effectively realize the transform from antiferromagnetism to altermagnetism and semiconductor to metal for the Jauns bilayer V2SeTeO. More interestingly, the strain not only induces an intriguing multipiezo effect, encompassing the piezovalley, piezomagnetism and piezoelectric, but also achieves the abundant topological phase. Our findings offer a generalized direction for manipulating the spin splitting, valley polarization, and topological states, promoting practical application of valleytronic and spintronic devices based on two-dimensional altermagnets.

Matheus I. N. Rosa, Konstantinos Karapiperis, Kaoutar Radi et al.

Architected materials achieve unique mechanical properties through precisely engineered microstructures that minimize material usage. However, a key challenge of low-density materials is balancing high stiffness with stable deformability up to large strains. Current microstructures, which employ slender elements such as thin beams and plates arranged in periodic patterns to optimize stiffness, are largely prone to instabilities, including buckling and brittle collapse at low strains. This challenge is here addressed by introducing a new class of aperiodic architected materials inspired by quasicrystalline lattices. Beam networks derived from canonical quasicrystalline patterns, such as the Penrose tiling in 2D and icosahedral quasicrystals in 3D, are shown to create stiff, stretching-dominated topologies with non-uniform force chain distributions, effectively mitigating the global instabilities observed in periodic designs. Numerical and experimental results confirm the effectiveness of these designs in combining stiffness and stable deformability at large strains, representing a significant advancement in the development of low-density metamaterials for applications requiring high impact resistance and energy absorption. Our results demonstrate the potential of deterministic quasi-periodic topologies to bridge the gap between periodic and random structures, while branching towards uncharted territory in the property space of architected materials.

Nadezhda A. Andreeva, Vitaly V. Chaban

In the contemporary era of rapid advancements in materials science, the development of new compounds and materials is proceeding at an accelerated pace. The concept of the potential energy landscape (PEL) plays a pivotal role in supporting the meticulous engineering of novel structures. This review article examines the historical evolution of the PEL concept and its diverse applications in materials design. A comprehensive overview of the major methods employed to sample the PEL is presented, accompanied by a critical discussion highlighting relevant modern endeavors. Specific applications of the PEL in rationalizing the design of molecules and materials for energy storage, electrolytic solutions, and greenhouse gas capture are exemplified. This review serves as an up-to-date guide for exploring and analyzing the PEL, facilitating a deeper understanding of its significance in materials science.

Hossam Hassan, S.M.A. El-Gamal, M.S.H. Shehab et al.

Dazhi Wang, Tianyi Li, Yongliang Ni et al.

A gas turbine cooling system is a typical multivariable, strongly coupled, nonlinear system; however, the randomness and large disturbances make it difficult to control the variables precisely. In order to solve the problem of precise process control for multi-input and multi-output coupled systems with flow, pressure, and temperature, this article conducts the following research: (1) Designing a secondary circuit for waste hot water and establishing a water-circulating gas turbine cooling system to improve the efficiency of waste heat utilization. (2) Identifying the coupled system model and establishing a mathematical model of the coupling relationship based on the characteristic data of input and output signals in the gas turbine cooling system. (3) Designing a coupled-system decoupling compensator to weaken the relationships between variables, realizing the decoupling between coupled variables. (4) An Opposition-based Learning Jumping Spider Optimization Algorithm is proposed to be combined with the PID control algorithm, and the parameters of the PID controller are adjusted to solve the intelligent control problems of heat exchanger water inlet flow rate, pressure, and temperature in the gas turbine cooling system. After simulation verification, the gas turbine cooling system based on an Opposition-based Learning Jumping Spider Optimization Algorithm can realize the constant inlet flow rate, with an error of no more than 1 m³/h, constant inlet water temperature, with an error of no more than 0.2 °C, and constant main-pipe pressure, with an error of no more than 0.01 MPa. Experimental results show that a gas turbine cooling system based on the Opposition-based Learning Jumping Spider Optimization Algorithm can accurately realize the internal variable controls. At the same time, it can provide a reference for decoupling problems in strongly coupled systems, the controller parameter optimization problems, and process control problems in complex systems.

Vladimir L. Mondrus, Dmitry K. Sizov, Timofei M. Kvasnikov

The article presents a calculation of rubber-metal vibration isolators with five holes of different diameters using a software package that implements the finite element method. A comparative analysis of the Eigen frequencies of rubber-metal vibration isolators with five holes (one in the center, 4 symmetrically at the corners) and without holes is presented. Finite element models of a rubber-metal vibration isolator with and without holes are modeled, and their characteristics are analyzed. The results show that vibration isolators with several symmetrically located holes have several advantages in a number of parameters to vibration isolators without holes, and, therefore, can be used for vibration isolation of buildings, especially in the case of delayed installation of vibration protection.

Willi Grossmann, Sebastian Eilermann, Tim Rensmeyer et al.

Traditional design cycles for new materials and assemblies have two fundamental drawbacks. The underlying physical relationships are often too complex to be precisely calculated and described. Aside from that, many unknown uncertainties, such as exact manufacturing parameters or materials composition, dominate the real assembly behavior. Machine learning (ML) methods overcome these fundamental limitations through data-driven learning. In addition, modern approaches can specifically increase system knowledge. Representation Learning allows the physical, and if necessary, even symbolic interpretation of the learned solution. In this way, the most complex physical relationships can be considered and quickly described. Furthermore, generative ML approaches can synthesize possible morphologies of the materials based on defined conditions to visualize the effects of uncertainties. This modern approach accelerates the design process for new materials and enables the prediction and interpretation of realistic materials behavior.

P. Raag Harshavardhan, Anandakumar Subbaiyan, U. Vasavi et al.

Batteries that have been used and thrown away are potential threats to the environment. The aim of the present study is to explore the bacterial bioremediation of the battery-contaminated soil. The battery contaminated soil sample was collected from the municipal compost yard, Vellalore, Coimbatore, Tamil Nadu, India. The Bacillus sp was isolated by the serial dilution method. The Bacillus strain was identified based on the colony morphology as well as the 16s ribosomal ribonucleic acid partial gene sequence and was designated the name HVRCBNR. It was deposited in the GenBank under the accession number Bacillus sp MZ959824. The bacterial growth was evaluated by measuring the optical density of the media (OD600), while the degradation was determined by FTIR analysis. The phytotoxic analysis was performed using Trigonella foenum-graecum to assess the toxicity of the battery waste before and after bacterial treatment. The spectroscopic study showed that the strain HVRCBNR achieved 83.6% degradation. The growth indexes of Trigonella foenum-graecum showed that the biodegraded soil was nonphytotoxic in comparison with the control. This study supports the degradability of the strain HVRCBNR, and this could pave a way for sustainable solution to battery contaminated soil treatment.

P. Sankudevan, R. V. Sakthivel, Ramalingam Gopal et al.

In the present work, the effect of Mn doping in Zinc Chromite (ZnCr2O4) and particle size reduction on catalytic and photocatalytic degradation performance have been evaluated. The pristine Zn1−xMnxCr2O4 (x = 0 to 0.03) nanoscale samples are synthesized through a hydrothermal approach. The synthesized catalysts are characterized by XRD, HR-SEM, HR-TEM, catalytic, and photocatalytic degradation analyses. X-ray diffraction analysis results confirmed the formation of the ZnCr2O4 structure and its phase purity, crystallite size, and Mn dopant effect. The surface morphology and particle size of Zn1−xMnxCr2O4 samples are evaluated by SEM and TEM measurements. The textural properties of ZnCr2O4 samples are identified by the surface area analysis. The catalytic performance of Mn-doped ZnCr2O4 samples reveals superior catalytic performance compared to pristine ZnCr2O4 in benzaldehyde and carbonyl compound productions. Under UV irradiation, an excellent photocatalytic degradation efficiency of 89.66% for Zn0.97Mn0.03Cr2O4 catalyst with methylene blue has been obtained.

Bilal Zaarour

Enhancing the electrical outputs of energy harvesters is a great demand for researchers in recent years. In this work, the effect of the plasticizer treatment (Tetrahydrofuran [THF]) on the β phase content (F[ β ]) of electrospun polyvinylidene fluoride (PVDF) fiber webs which are used as active layers to directly make a piezoelectric nanogenerator (PENG) is demonstrated. The results showed that during the plasticizer treatment, the F( β ) of the web increases when the initial length of the web (L _0 ) equals the distance between the two ends of the solid support (L) which the web fixed on it, whereas the F( β ) decreases when L < L _0 resulting in the formation of crimped fibers. Furthermore, the electrical outputs of the PENG based on the pristine web, and treated webs at different lengths are investigated. We believe this work can be used as a good reference for enhancing the electrical outputs of the PENG by enhancing the F ( β ) of PVDF nanofiber webs using a plasticizer treatment.

Li-gang Zhang, Jing-ya Zhou, Zhen-yu Wang et al.

This study presents the design of a high strength titanium alloy based on the idea that the β titanium alloy with critically stable composition could precipitate ultra-fine α phase. An efficient method was used to find the composition of TC21-xV alloy in which ultra-fine α phase could be obtained. It is found that TC21-5V alloy containing ultra-fine α phase and possessing highest hardness could be obtained after solution treatment in the β single-phase region and subsequent aging. The morphology of primary and secondary α phases can be controlled by changing the solution treatment and aging temperatures. Calculation results of driving force and growth rate of secondary α phase show that the growth rate may be a decisive factor for the final size of secondary α phase after solution and aging treatments in the two-phase region. Finally, when the alloy was solution treated at 820 °C and aged at 500 °C, the highest strength of 1540 MPa was obtained. The alloy was solution treated at 820 °C and aged at 600 °C exhibited high strength of 1210 MPa with 11.4% elongation.

N. S. Johnson, P. S. Vulimiri, A. C. To et al.

In metals additive manufacturing (AM), materials and components are concurrently made in a single process as layers of metal are fabricated on top of each other in the near-final topology required for the end-use product. Consequently, tens to hundreds of materials and part design degrees of freedom must be simultaneously controlled and understood; hence, metals AM is a highly interdisciplinary technology that requires synchronized consideration of physics, chemistry, materials science, physical metallurgy, computer science, electrical engineering, and mechanical engineering. The use of modern machine learning approaches to model these degrees of freedom can reduce the time and cost to elucidate the science of metals AM and to optimize the engineering of these complex, multidisciplinary processes. New machine learning techniques are not needed for most metals AM development; those used in other sects of materials science will also work for AM. Most prolifically, the density functional theory (DFT) community has used many of them since the early 2000s for evaluating numerous combinations of elements and crystal structures to discover new materials. This materials technologies-focused review introduces the basic mathematics and terminology of machine learning through the lens of metals AM, and then examines potential uses of machine learning to advance metals AM, highlighting the many parallels to previous efforts in materials science and manufacturing while also discussing new challenges and adaptations specific to metals AM.