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The issue focuses on physics-informed machine learning and its applications for structural integrity and safety assessment of engineering systems/facilities. Data science and data mining are fields in fast development with a high potential in several engineering research communities; in particular, advances in machine learning (ML) are undoubtedly enabling significant breakthroughs. However, purely ML models do not necessarily carry physical meaning, nor do they generalize well to scenarios on which they have not been trained on. This is an emerging field of research that potentially will raise a huge impact in the future for designing new materials and structures, and then for their proper final assessment. This issue aims to update the current research state of the art, incorporating physics into ML models, and providing tools when dealing with material science, fatigue and fracture, including new and sophisticated algorithms based on ML techniques to treat data in real-time with high accuracy and productivity. This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
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The development of machine learning (ML) provides a promising solution to guarantee the structural integrity of critical components during service period. However, considering the lack of respect for the underlying physical laws, the data hungry nature and poor extrapolation performance, the further application of pure data-driven methods in structural integrity is challenged. An emerging ML paradigm, physics-informed machine learning (PIML), attempts to overcome these limitations by embedding physical information into ML models. This paper discusses different ways of embedding physical information into ML and reviews the developments of PIML in structural integrity including failure mechanism modelling and prognostic and health management (PHM). The exploration of the application of PIML to structural integrity demonstrates the potential of PIML for improving consistency with prior knowledge, extrapolation performance, prediction accuracy, interpretability and computational efficiency and reducing dependence on training data. The analysis and findings of this work outline the limitations at this stage and provide some potential research direction of PIML to develop advanced PIML for ensuring structural integrity of engineering systems/facilities. This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
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While advanced imaging strategies have improved the diagnosis of bone-related pathologies, early signs of bone alterations remain difficult to detect. The Covid-19 pandemic has brought attention to the need for a better understanding of bone micro-scale toughening and weakening phenomena. This study used an artificial intelligence-based tool to automatically investigate and validate four clinical hypotheses by examining osteocyte lacunae on a large scale with synchrotron image-guided failure assessment. The findings indicate that trabecular bone features exhibit intrinsic variability related to external loading, micro-scale bone characteristics affect fracture initiation and propagation, osteoporosis signs can be detected at the micro-scale through changes in osteocyte lacunar features, and Covid-19 worsens micro-scale porosities in a statistically significant manner similar to the osteoporotic condition. Incorporating these findings with existing clinical and diagnostic tools could prevent micro-scale damages from progressing into critical fractures.
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Polyurethane (PU) is a typical product of the reaction between isocyanate and polyol, whose ratio would greatly influence material properties. In this paper, to investigate the influence of isocyanate on PU thermal stability and flammability, three kinds of rigid polyurethanes (RPUs) with different isocyanate ratio (1.05, 1.1, and 2.0) were manufactured in a laboratory and employed to have a series of TG (thermogravimetry), DSC (differential scanning calorimetry), and cone calorimetry tests. Kissinger's method was used to calculate the activation energy and judge their stabilities. However, for such a complex degradation which consists of five reactions, it does not make sense by Kissinger method to obtain only two peak active energies. Considering complexity of PU degradation in air, genetic algorithm (GA) was employed to calculate kinetic triplets of five sub-reactions. The effects of isocyanate contents on each sub-reaction stability were obtained and then analyzed. By cone calorimeter testing, we found that great differences in heat release rate data. However, DSC analysis showed a complete opposite changed trend. Such difference is caused by DSC and calorimeter's sample morphology, the former using grinded polyurethane powders but the latter polyurethane foam block.
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Polyethylene (PE) is one the most used plastics worldwide for a wide range of applications due to its good mechanical and chemical resistance, low density, cost efficiency, ease of processability, non-reactivity, low toxicity, good electric insulation, and good functionality. However, its high flammability and rapid flame spread pose dangers for certain applications. Therefore, different flame-retardant (FR) additives are incorporated into PE to increase its flame retardancy. In this review article, research papers from the past 10 years on the flame retardancy of PE systems are comprehensively reviewed and classified based on the additive sources. The FR additives are classified in well-known FR families, including phosphorous, melamine, nitrogen, inorganic hydroxides, boron, and silicon. The mechanism of fire retardance in each family is pinpointed. In addition to the efficiency of each FR in increasing the flame retardancy, its impact on the mechanical properties of the PE system is also discussed. Most of the FRs can decrease the heat release rate (HRR) of the PE products and simultaneously maintains the mechanical properties in appropriate ratios. Based on the literature, inorganic hydroxide seems to be used more in PE systems compared to other families. Finally, the role of nanotechnology for more efficient FR-PE systems is discussed and recommendations are given on implementing strategies that could help incorporate flame retardancy in the circular economy model.
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Retardadores de Chama , Nanocompostos/química , Polietileno/química , Boro/química , Temperatura Alta , Hidróxidos/química , Compostos Inorgânicos , Microscopia Eletrônica de Varredura , Nanotecnologia , Nitrogênio/química , Oxigênio/química , Fósforo/química , Polímeros/química , Silício/química , Triazinas/químicaRESUMO
The study focuses on testing a simplified way of estimating the resultant force due to ballistic impacts resulting in a full fragmentation of the impactor with no penetration of the target. The method is intended to be useful for the parsimonious structural assessment of military aircrafts with integrated ballistic protection systems by means of large scale explicit finite element simulations. The research investigates the effectiveness of the method in allowing the prediction of the fields of plastic deformation collected by hard steel plates impacted by a wide range of semi-jacketed, monolithic, and full metal jacket .308 Winchester rifle bullets. The outcomes show the effectiveness of the method being strictly related to the full compliance of the considered cases with the bullet-splash hypotheses. The study therefore suggests the application of the load history approach only after careful experimental investigations on the specific impactor-target interactions.
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This study attempts to synthesize MgZn/TiO2-MWCNTs composites with varying TiO2-MWCNT concentrations using mechanical alloying and a semi-powder metallurgy process coupled with spark plasma sintering. It also aims to investigate the mechanical, corrosion, and antibacterial properties of these composites. When compared to the MgZn composite, the microhardness and compressive strength of the MgZn/TiO2-MWCNTs composites were enhanced to 79 HV and 269 MPa, respectively. The results of cell culture and viability experiments revealed that incorporating TiO2-MWCNTs increased osteoblast proliferation and attachment and enhanced the biocompatibility of the TiO2-MWCNTs nanocomposite. It was observed that the corrosion resistance of the Mg-based composite was improved and the corrosion rate was reduced to about 2.1 mm/y with the addition of 10 wt% TiO2-1 wt% MWCNTs. In vitro testing for up to 14 days revealed a reduced degradation rate following the incorporation of TiO2-MWCNTs reinforcement into a MgZn matrix alloy. Antibacterial evaluations revealed that the composite had antibacterial activity, with an inhibition zone of 3.7 mm against Staphylococcus aureus. The MgZn/TiO2-MWCNTs composite structure has great potential for use in orthopedic fracture fixation devices.
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Developing accurate yet fast computational tools to simulate complex physical phenomena is a long-standing problem. Recent advances in machine learning have revolutionized the way simulations are approached, shifting from a purely physics- to AI-based paradigm. Although impressive achievements have been reached, efficiently predicting complex physical phenomena in materials and structures remains a challenge. Here, we present an AI-based general framework, implemented through graph neural networks, able to learn complex mechanical behavior of materials from a few hundreds data. Harnessing the natural mesh-to-graph mapping, our deep learning model predicts deformation, stress, and strain fields in various material systems, like fiber and stratified composites, and lattice metamaterials. The model can capture complex nonlinear phenomena, from plasticity to buckling instability, seemingly learning physical relationships between the predicted physical fields. Owing to its flexibility, this graph-based framework aims at connecting materials' microstructure, base materials' properties, and boundary conditions to a physical response, opening new avenues towards graph-AI-based surrogate modeling.
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Aprendizado de Máquina , Redes Neurais de Computação , Exame Físico , FísicaRESUMO
Fabrication based on additive manufacturing (AM) process from a three-dimensional (3D) model has received significant attention in the past few years. Although 3D printing was introduced for production of prototypes, it has been currently used for fabrication of end-use products. Therefore, the mechanical behavior and strength of additively manufactured parts has become of significant importance. 3D printing has been affected by different parameters during preparation, printing, and post-printing processes, which have influence on quality and behavior of the additively manufactured components. This paper discusses the effects of two printing parameters on the mechanical behavior of additively manufactured components. In detail, polylactic acid material was used to print test coupons based on fused deposition modeling process. The specimens with five different raster orientations were printed with different printing speeds. Later, a series of tensile tests was performed under static loading conditions. Based on the results, strength and stiffness of the examined specimens have been determined. Moreover, dependency of the strength and elastic modulus of 3D-printed parts on the raster orientation has been documented. In the current study, fractured specimens were visually investigated by a free-angle observation system. The experimental findings can be used for the development of computational models and next design of structural components.
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In this study, corrosion and wear behavior of three kinds of coatings by two processes, namely, plasma electrolytic oxidation (PEO) coatings (Ti/TiO2), gas nitriding coating (Ti/TiN), and the duplex coating (Ti/TiO2-N) by combination of PEO and gas nitriding methods were systematically investigated. X-ray diffraction tests, field-emission scanning electron microscopy, and adhesion tests are employed for the coating characterization, along with the wear and electrochemical test for evaluating the corrosion and tribological properties. The morphology and structure of the coating consist of micro-cavities known as the pancake structure on the surface. The electrolytic plasma oxidation process produces a typical annealing behavior with a low friction coefficient based on the wear test. The coating consists of nitride and nitrate/oxides titanium for nitrided samples. The surface morphology of nitrided oxide titanium coating shows a slight change in the size of the crystals and the diameter of the cavities due to the influence of nitrogen in the titanium oxide coating. The tribological behavior of the coatings showed that the wear resistance of the duplex coating (Ti/TiO2-N) and Ti/TiO2 coatings is significantly higher compared to Ti/TiN coatings and uncoated Ti samples. The polarization resistance of the Ti/TiO2-N and Ti/TiO2 coatings was 632.2 and 1451.9 kΩ cm2, respectively. These values are considerably greater than that of the uncoated Ti (135.9 kΩ cm2). Likewise, impedance showed that the Ti/TiO2-N and Ti/TiO2 coatings demonstrate higher charge transfer resistance than that of other samples due to better insulating behavior and denser structure.
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The dissimilar joining of martensitic and ferritic stainless steels have been developed that needs corrosion resistance and enhanced mechanical properties. In this study, the transient liquid-phase bonding of martensitic stainless steel 410 and super-ferritic stainless steel 446 was conducted with a nickel-based amorphous interlayer (BNi-2) at constant temperature (1050 °C) and increasing times of 1, 15, 30, 45, and 60 min. For characterization of the TLP-bonded samples, optical microscopy and scanning emission microscopy equipped with energy-dispersive X-ray spectroscopy were used. To investigate the mechanical properties of TLP-bonded samples, the shear strength test method was used. Finally, the X-ray diffraction method was used for microstructural investigation and phase identification. The microstructural study showed that the microstructure of base metals changed: the martensitic structure transited to tempered martensite, including ferrite + cementite colonies, and the delta phase in super-ferritic stainless steel dissolved in the matrix. During the transient liquid-phase bonding, the aggregation of boron due to its diffusion to base metals resulted in the precipitation of a secondary phase, including iron-chromium-rich borides with blocky and needle-like morphologies at the interface of the molten interlayer and base metals. On the other hand, the segregation of boron in the bonding zone resulted from a low solubility limit, and the distribution coefficient has induced some destructive and brittle phases, such as nickel-rich (Ni3B) and chromium-rich boride (CrB/Cr2B). By increasing the time, significant amounts of boron have been diffused to a base metal, and diffusion-induced isothermal solidification has happened, such that the isothermal solidification of the assembly has been completed under the 1050 °C/60 min condition. The distribution of the hardness profile is relatively uniform at the bonding zone after completing isothermal solidification, except the diffusion-affected zone, which has a higher hardness. The shear strength test showed that increasing the holding time was effective in achieving the strength near the base metals such that the maximum shear strength of about 472 MPa was achieved.
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The structure, mechanical and tribological properties of the PEI- and PI-based composites reinforced with Chopped Carbon Fibers (CCF) and loaded with commercially available micron-sized solid lubricant fillers of various nature (polymeric-PTFE, and crystalline-Gr and MoS2) were studied in the temperature range of 23-180 (240) °C. It was shown that tribological properties of these ternary composites were determined by the regularities of the transfer film (TF) adherence on their wear track surfaces. The patterns of TFs formation depended on the chemical structure of the polymer matrix (stiffness/flexibility) as well as the tribological test temperatures. Loading with PTFE solid lubricant particles, along with the strengthening effect of CCF, facilitated the formation and fixation of the TF on the sliding surfaces of the more compliant PEI-based composite at room temperature. In this case, a very low coefficient of friction (CoF) value of about 0.05 was observed. For the more rigid identically filled PI-based composite, the CoF value was twice as high under the same conditions. At elevated temperatures, rising both CoF levels and oscillation of their values made it difficult to retain the non-polar PTFE transfer film on the sliding surfaces of the PI-based composite. As a result, friction of the ceramic counterpart proceeded over the composite surface without any protecting TF at T ≥ 180 °C. For the sample with the more flexible PEI matrix, the PTFE-containing TF was retained on its sliding surface, providing a low WR level even under CoF rising and oscillating conditions. A similar analysis was carried out for the less efficient crystalline solid lubricant filler MoS2.
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With the advent of "intelligent" materials, the design of smart bioadhesives responding to chemical, physical, or biological stimuli has been widely developed in biomedical applications to minimize the risk of wounds reopening, chronic pain, and inflammation. Intelligent bioadhesives are free-flowing liquid solutions passing through a phase shift in the physiological environment due to stimuli such as light, temperature, pH, and electric field. They possess great merits, such as ease to access and the ability to sustained release as well as the spatial transfer of a biomolecule with reduced side effects. Tissue engineering, wound healing, drug delivery, regenerative biomedicine, cancer therapy, and other fields have benefited from smart bioadhesives. Recently, many disciplinary attempts have been performed to promote the functionality of smart bioadhesives and discover innovative compositions. However, according to our knowledge, the development of multifunctional bioadhesives for various biomedical applications has not been adequately explored. This review aims to summarize the most recent cutting-edge strategies (years 2015-2021) developed for stimuli-sensitive bioadhesives responding to external stimuli. We first focus on five primary categories of stimuli-responsive bioadhesive systems (pH, thermal, light, electric field, and biomolecules), their properties, and limitations. Following the introduction of principal criteria for smart bioadhesives, their performances are discussed, and certain smart polymeric materials employed in their creation in 2015 are studied. Finally, advantages, disadvantages, and future directions regarding smart bioadhesives for biomedical applications are surveyed.
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Bioinspired architectures are effective in enhancing the mechanical properties of materials, yet are difficult to construct in metallic systems. The structure-property relationships of bioinspired metallic composites also remain unclear. Here, Mg-Ti composites were fabricated by pressureless infiltrating pure Mg melt into three-dimensional (3-D) printed Ti-6Al-4V scaffolds. The result was composite materials where the constituents are continuous, mutually interpenetrated in 3-D space and exhibit specific spatial arrangements with bioinspired brick-and-mortar, Bouligand, and crossed-lamellar architectures. These architectures promote effective stress transfer, delocalize damage and arrest cracking, thereby bestowing improved strength and ductility than composites with discrete reinforcements. Additionally, they activate a series of extrinsic toughening mechanisms, including crack deflection/twist and uncracked-ligament bridging, which enable crack-tip shielding from the applied stress and lead to "Γ"-shaped rising fracture resistance R-curves. Quantitative relationships were established for the stiffness and strengths of the composites by adapting classical laminate theory to incorporate their architectural characteristics.
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Impressão Tridimensional , TitânioRESUMO
In tissue engineering, three-dimensional (3D) printing is an emerging approach to producing functioning tissue constructs to repair wounds and repair or replace sick tissue/organs. It allows for precise control of materials and other components in the tissue constructs in an automated way, potentially permitting great throughput production. An ink made using one or multiple biomaterials can be 3D printed into tissue constructs by the printing process; though promising in tissue engineering, the printed constructs have also been reported to have the ability to lead to the emergence of unforeseen illnesses and failure due to biomaterial-related infections. Numerous approaches and/or strategies have been developed to combat biomaterial-related infections, and among them, natural biomaterials, surface treatment of biomaterials, and incorporating inorganic agents have been widely employed for the construct fabrication by 3D printing. Despite various attempts to synthesize and/or optimize the inks for 3D printing, the incidence of infection in the implanted tissue constructs remains one of the most significant issues. For the first time, here we present an overview of inks with antibacterial properties for 3D printing, focusing on the principles and strategies to accomplish biomaterials with anti-infective properties, and the synthesis of metallic ion-containing ink, chitosan-containing inks, and other antibacterial inks. Related discussions regarding the mechanics of biofilm formation and antibacterial performance are also presented, along with future perspectives of the importance of developing printable inks.
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Application of Additive Manufacturing (AM) has significantly increased in the past few years. AM also known as three-dimensional (3D) printing has been currently used in fabrication of prototypes and end-use products. Considering the new applications of additively manufactured components, it is necessary to study structural details of these parts. In the current study, influence of a post-processing on the mechanical properties of 3D-printed parts has been investigated. To this aim, Acrylonitrile Butadiene Styrene (ABS) material was used to produce test coupons based on the Fused Deposition Modeling (FDM) process. More in deep, a device was designed and fabricated to fix imperfection and provide smooth surfaces on the 3D-printed ABS specimens. Later, original and treated specimens were subjected to a series of tensile loads, three-point bending tests, and water absorption tests. The experimental tests indicated fracture load in untreated dog-bone shaped specimen was 2026.1 N which was decreased to 1951.7 N after surface treatment. Moreover, the performed surface treatment was lead and decrease in tensile strength from 29.37 MPa to 26.25 MPa. Comparison of the results confirmed effects of the surface modification on the fracture toughness of the examined semi-circular bending components. Moreover, a 3D laser microscope was used for visual investigation of the specimens. The documented results are beneficial for next designs and optimization of finishing processes.
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An analytical model is proposed to rapidly capture the thermal and residual stresses values induced by the hybrid metal extrusion and bonding (HYB) process on dissimilar-metal butt-welded joints. The power input for two welding velocities is first assessed using a thermal-mechanical model solved by a heat generation routine written in MATLAB code. Subsequently, the obtained temperature history is used as input to solve the equilibrium and compatibility equations formulated to calculate the thermal and residual stresses. To verify the soundness of the analytical approach, a Finite Element numerical model of the entire process is carried out and results are compared with those coming from the proposed rapid method. It is found that the degree of accuracy reached by the analytical model is excellent, especially considering the tremendous time reduction when compared to that characterizing the standard numerical approach.
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In the work presented herein, the structural integrity of polymeric functional components made of Nylon-645 and Polylactic acid (PLA) produced by additive manufacturing (Fused Deposition Modelling, FDM) is studied. The PLA component under study was selected from the production line of a brewing company, and it was redesigned and analyzed using the Finite Element Method, 3D printed, and installed under real service. The results obtained indicated that, even though the durability of the 3D printed part was lower than the original, savings of about EUR 7000 a year could be achieved for the component studied. Moreover, it was shown that widespread use of AM with other specific PLA components could result in even more significant savings. Additionally, a metallic hanger (2700 kg/m3) from the cockpit of an airplane ATR 70 series 500 was successfully redesigned and additively manufactured in Nylon 645, resulting in a mass reduction of approximately 60% while maintaining its fit-for-purpose. Therefore, the components produced by FDM were used as fully functional components rather than prototype models, which is frequently stated as a major constraint of the FDM process.
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Additive manufacturing (AM) is the process through which components/structures are produced layer-by-layer. In this context, 4D printing combines 3D printing with time so that this combination results in additively manufactured components that respond to external stimuli and, consequently, change their shape/volume or modify their mechanical properties. Therefore, 4D printing uses shape-memory materials that react to external stimuli such as pH, humidity, and temperature. Among the possible materials with shape memory effect (SME), the most suitable for additive manufacturing are shape memory polymers (SMPs). However, due to their weaknesses, shape memory polymer compounds (SMPCs) prove to be an effective alternative. On the other hand, out of all the additive manufacturing techniques, the most widely used is fused filament fabrication (FFF). In this context, the present paper aims to critically review all studies related to the mechanical properties of 4D-FFF materials. The paper provides an update state of the art showing the potential of 4D-FFF printing for different engineering applications, maintaining the focus on the structural integrity of the final structure/component.
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In this research article, a mini-review study is performed on the additive manufacturing (AM) of the polymeric matrix composites (PMCs) and nanocomposites. In this regard, some methods for manufacturing and important and applied results are briefly introduced and presented. AM of polymeric matrix composites and nanocomposites has attracted great attention and is emerging as it can make extensively customized parts with appreciably modified and improved mechanical properties compared to the unreinforced polymer materials. However, some matters must be addressed containing reduced bonding of reinforcement and matrix, the slip between reinforcement and matrix, lower creep strength, void configurations, high-speed crack propagation, obstruction because of filler inclusion, enhanced curing time, simulation and modeling, and the cost of manufacturing. In this review, some selected and significant results regarding AM or three-dimensional (3D) printing of polymeric matrix composites and nanocomposites are summarized and discuss. In addition, this article discusses the difficulties in preparing composite feedstock filaments and printing issues with nanocomposites and short and continuous fiber composites. It is discussed how to print various thermoplastic composites ranging from amorphous to crystalline polymers. In addition, the analytical and numerical models used for simulating AM, including the Fused deposition modeling (FDM) printing process and estimating the mechanical properties of printed parts, are explained in detail. Particle, fiber, and nanomaterial-reinforced polymer composites are highlighted for their performance. Finally, key limitations are identified in order to stimulate further 3D printing research in the future.