Design Of High Strength Research Articles

Vibration analysis of functionally graded carbon nanotube‐reinforced composite open cylindrical shells with damping film embedded

AbstractIn the present study, a discrete layer model was established to explore the vibration performance of Functionally Graded Carbon Nanotube‐Reinforced Composite (FG‐CNTRC) open cylindrical shells with damping film embedded based on the first‐order shell theory. There are four configurations of stacking arrangements considered for FG‐CNTRC open cylindrical shells with damping film embedded. The equivalent structural parameters of the top and bottom FG‐CNTRC panels are generated by implementing the extended mixing rule. Governing equations are derived based on the Hamilton principle and solved with the Naiver solution. Subsequently, after verifying the validity of this paper's solution by comparing it with the published literature, a parametric elaborated investigation discloses the variation patterns of vibration performance of four FG‐CNTRC open cylindrical shells with damping film embedded. The conclusions of the study can be used as a useful guide about open cylindrical composite shell structures with the design of high strength and damping.Highlights Discrete layer vibration model was bulit based on first‐order shell theory. Vbration performance of FG‐CNTRC open sandwich shells was studied. Variation patterns of frequency and loss factor was disclosed.

Functionally graded multi-morphology lattice structures as an optimized sandwich core via digital light processing additive manufacturing

This investigation aims to present a high-strength sandwich core with functionally graded multi-morphology lattice inner structures through vat photo-polymerization additive manufacturing (AM). The five better strut-based designs based on [1], are considered here. All printed specimens have been fabricated from photopolymer resin to ensure manufacturability in a digital light processing (DLP) 3D printer. Firstly, the resin and structural characteristics have been examined. Simultaneously, the lattice core is divided into three regions based on the von Mises stress distribution and tensile and compression responses in finite element analysis (FEA). Based on the mechanical responses of the beam-based structures, these topologies have been applied in each region in an optimal fixed relative density distribution, considering different steps and types. This proposed technique is numerically investigated and experimentally validated using a three-point bending test. As a result, the optimized core demonstrated a 96% increase in maximum fracture force and a 174% increase in stiffness compared to the homogeneous body. Additionally, it exhibited a different deformation mode than the single morphology under similar conditions. These significant findings indicate that this approach provides a new perspective on a high-strength design involving more than three morphologies, and it is faster than computational topology optimization processes.

Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algorithm

Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algorithm

Calphad-assisted design of high strength – ductility martensitic stainless-steels with reverted austenite

Introducing reverted austenite at lath martensite boundaries has been shown to be an effective method to increase the ductility of martensitic steels. However, significant strength reductions can also be introduced during the reversion process in martensitic stainless steels. To overcome the strength-ductility trade-off, we explore the effects of alloying elements in delaying the overaging of the precipitates and accelerating the austenite formation. To this end, we carry multi-objective optimization considering (1) lattice misfit and diffusivity for kinetics of precipitation, and (2) austenite fraction and thermodynamic driving force of austenite reversion for austenite formation. With the insights from calculations, model alloy compositions are then proposed, and mechanical testing and microstructural analysis are applied. The model alloy confirms that a relatively higher volume fraction of austenite can form prior to overaging, which doubles the total elongation without significant strength loss.

Examining the endpoint impacts, challenges, and opportunities of fly ash utilization for sustainable concrete construction

Fly ash has been widely used as a cement substitute to improve the sustainability of concrete. Although the advantages of fly ash have been extensively documented, there is a gap in understanding why its use in mass concrete applications remains low in some countries, such as the Philippines. Thus, this work aims to understand the issues that impede waste utilization, particularly fly ash in the concrete construction industry, quantify the impact of the current practice, and identify opportunities for sustainable fly ash utilization. Endpoint impact analysis was conducted through the life cycle using SimaPro 9.3 to quantify the impacts on human health, ecosystem, and resources of 31 concrete mixtures of low, normal, and high strength design with 0 to 20% fly ash as cement replacement. In-depth, semi-structured interviews with key stakeholders were undertaken to determine the institutional, economic, social, and technological challenges related to the utilization of waste materials in large-scale concrete construction. More than 90% of the total impact of concrete contributes to damage to human health, primarily caused by global warming and fine particulate matter. The use of fly ash at 20% replacement by weight of cement benefits resources more significantly than human health and the ecosystem. The use of chemical admixture to improve strength has a significant impact on resources. High fly ash replacement for normal and high-strength concrete has a greater reduction in all endpoint categories than for low-strength design. Recommendations are proposed to maximize the beneficial impact of using fly ash in the concrete industry.

The application of high performance in our lives

This paper provides an overview of high-performance concrete (HPC), including its definition, behavior, development,design criteria, innovative structural application examples, prospects, challenges, and limitations. HPC is a special typeof concrete with higher strength, durability, and other properties than conventional concrete. Several factors, such asshrinkage properties, thermal properties, flexibility, and durability, influence HPC behavior. Design criteria for HPCinclude High strength design, water-cement ratio, temperature resistance, and other design properties. Over the years,HPC has evolved to meet the growing demand for high-performance structures, such as using recycled aggregates inHPC, developing self-compacting concrete (SCC), and developing ultra-high performance concrete (UHPC). Innovativestructural applications of HPC include the application of HPC in precast components, high-rise building structures, etc.The future of HPC is promising as it is continuously developed and optimized for various applications. However, thereare still some challenges and limitations to overcome, such as high production costs, maintenance work requirements,difficulty mixing, and so on. This paper provides valuable insights for engineers, architects, and researchers interested indesigning and constructing HPC structures.

Solute clustering governed elastic properties in aluminum

Here, we report an extensive screening of homoatomic solute-solute binding energies and calculate the resulting elastic moduli in aluminum using density functional theory. Following a full-configuration strategy, a robust solute clustering map made up of 65 elements is established. Deriving from elemental and DFT-calculated properties, a total of 20 atomistic descriptors are used to evaluate the contributions of cluster bindings. A volume-effect dominated solute atomic binding mechanism is proposed. It suggests that not only the central zone but also the outer Al shell responds to solute bindings. The impact of stable solute clusters on the elastic properties of Al alloys is calculated. An unconventional enhancement mechanism of Young's modulus in these Al-based alloys is proposed. Based on the interatomic interaction forces derived elastic response theory, modified ‘atomic distance-electron density-Young's modulus' models applying to different element groups are proposed. Our work is expected to provide insight into the design of high strength, and high stiffness Al alloys.

Bending Study of Six Biological Models for Design of High Strength and Tough Structures.

High strength and tough structures are beneficial to increasing engineering components service span. Nonetheless, improving structure strength and, simultaneously, toughness is difficult, since these two properties are generally mutually exclusive. Biological organisms exhibit both excellent strength and toughness. Using bionic structures from these biological organisms can be solutions for improving these properties of engineering components. To effectively apply biological models to design biomimetic structures, this paper analyses strengthening and toughening mechanisms of six fundamentally biological models obtained from biological organisms. Numerical models of three-point bending test are established to predict crack propagation behaviors of the six biological models. Furthermore, the strength and toughness of six biomimetic composites are experimentally evaluated. It is identified that the helical model possesses the highest toughness and satisfying strength. This work provides more detailed evidence for engineers to designate bionic models to the design of biomimetic composites with high strength and toughness.

Study on the microstructure and age hardening capability in Al–Cu–Li alloys with different Cu/Li ratio

Abstract The microstructural evolution during natural ageing and artificial ageing treatment has been quantified in Al–Cu–Li alloys with Cu/Li ratios of 2.3 and 3.9. Methods including various ageing, hardness testing, transmission electron microscopy and differential scanning calorimetry were employed. The precipitation of T1 (Al2CuLi) phase was confirmed for the first time in the high Li content alloy under natural ageing treatment for 5 months, while the Li-lean alloy exhibits barely any precipitation at room temperature. Under artificial ageing, the Li-rich alloy exhibits a significant increase in hardness due to the formation of high density spherical δ′ phase. On the other hand, the increasing Cu/Li ratio promotes the precipitation of the Cu containing precipitates T1 and θ (Al2Cu), the high Cu/Li ratio (3.9) alloy shows a recovery of ductility, with a uniform elongation of ∼20 %, which is caused by the strong interactions between the dislocations and the nano-scale T1 and θ precipitates. Meanwhile, as the main strengthening precipitate changes from θ and T1 to T1 alone with prolonged ageing time, the alloy displays a double-peak age hardening behavior. This work sheds light on the design of high strength and ductile Al–Li alloys through the well-controlled T1 phase precipitation.

Simultaneously enhanced strength and ductility of Cu-15Ni-8Sn alloy with periodic heterogeneous microstructures fabricated by laser powder bed fusion

Cu-15Ni-8Sn alloy with layer-by-layer periodic heterogeneous microstructures composed of ultrafine equiaxed (~2.6 µm) and coarse columnar (~12.8 µm) grains was successfully fabricated by laser powder bed fusion (LPBF) additive manufacturing. The microstructures were composed of Sn-depleted α-Cu (Ni, Sn) matrix and Sn-enriched γ-(CuxNi1-x)3Sn nano-precipitates. The γ nano-precipitates were found to be mainly uniformly distributed at the melt pool boundaries due to Sn reverse segregation, as though the densely distributed seeds on the surface of a strawberry. The interesting periodic bi-modal microstructure exhibited a simultaneous positive effect on the enhancement of strength and ductility. The yield strength, ultimate tensile strength and elongation at break were (474.04 ± 2.88) MPa, (584.36 ± 4.74) MPa and (14.29 ± 1.78)%, respectively. Remarkable improvements of 12% and 286% in the yield strength and elongation at break were achieved compared with those cast counterparts reported in the published literature. The high dislocations density (~6.78 ×1014 m−2) were the dominant source of high strength and contributed ~49% to the yield strength according to the theoretical calculation. Massive dislocation cells were generated around the γ nano-precipitates during tensile deformation, improving the dislocation storage capacity and the work hardening ability. These findings validated the LPBF printability and the property enhancement of Cu-15Ni-8Sn and provided a promising strategy for the design of high strength and ductility copper alloys through layered precipitation microstructures.

Design of high strength and wear-resistance β-Ti alloy via oxygen-charging

Titanium (Ti) is a promising biomedical material due to its superior corrosion resistance, low elastic modulus and favorable biocompatibility. Nevertheless, Ti faces a dilemma because of its inferior abrasion performance and strength-ductility trade-off, which poses a limitation in application as biomedical implants. Here, we developed an oxygen-charging method to fabricate a β-Ti alloy with combination of ultrahigh surface hardness, strength, toughness and remarkable wear resistance. The superior mechanical performance of β-Ti alloy originates from a 200 μm-thick α+β phase hard shell, a 600 μm oxygen gradient region and an oxygen-free β-Ti core. The gradient phase and composition structures display different deformation mechanisms, transforming from simple but unusual basal slip in α phase to multiple-slip activities in β phase. The unique oxygen gradient distribution makes β-Ti alloy much stronger and tougher that can resist surface crack propagation and sample catastrophic failure. Oxygen charging is a novel technique to design high-performance Ti implants for biomedical applications.

Design of high strength and electrically conductive aluminium alloys by machine learning

Traditionally, thermodynamic modeling considers only the equilibrium conditions and one-dimensional evolution of phases. Therefore, it has difficulty in predicting the final properties of materials, especially when the functional and mechanical properties are correlated and heavily dependent on the combination of different phases which distribute in three dimensions. Recently, machine learning enabled us to establish the complex relationship between alloy compositions, processing conditions, various phases, and final properties. In this work, machine learning is coupled with thermodynamic calculations to optimise the alloy compositions, processing conditions, and the combinations of phases for improved electrical conductivity and mechanical property. Compared with previous chemistry design by machine learning for multiple inputs and single object outputs, the introduction of intermediate phases from thermodynamic calculations can improve the prediction accuracy. Combining machine learning with thermodynamic calculation is expected to optimise new alloys.

Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algorithm

Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algorithm

Design and Optimization of Lightweight and HSD Excavator Bucket with Uncertain Load

Excavators are used primarily to excavate below the natural surface of the ground on which the machine rests and load it into trucks or tractor. Due to severe working conditions, excavator parts are subjected to high loads. The excavator mechanism must work reliably under unpredictable working conditions. Thus, it is very much necessary for the designers to provide not only a equipment of maximum reliability but also of minimum weight and cost, keeping design. safe under all loading conditions weight and cost, keeping design safe under all loading conditions. It can be concluded that, force analysis and strength analysis is an important step in the design of excavator parts. This paper presents a methodology for lightweight and high-strength design of an excavator bucket under uncertain loading. Uncertain loads are obtained by using the Monte Carlo simulation based on the existing soil-bucket interaction model in which the soil parameters are variable. And the well-known 3-sigma methodology is used for the quantification of the uncertain loads. Excavator bucket modelling is finished by using ANSYS Parameter Design Language (APDL). A multi-objective optimization model aiming to decrease the maximum von Mises stress and to reduce the weight of the bucket is established on the foundations of the uncertain load and the parametric geometry model. The structural shape and topology of the bucket are then designed by using the mixed variable genetic algorithm to solve the established optimization problem. The results show that the presented method can be effectively and efficiently applied for the optimization design of the excavator bucket and that the optimized bucket signifies obvious decreases in the weight and the stress compared with the initial reference model. The proposed methodology for structure optimization design considering uncertain loads not only provides the technical means for the design and development of high-performance bucket but also lays a preliminary theoretical foundation for the optimization design integrated machine-environment interaction.

Design of High Strength and Lightweight Construction Composites Using Advanced Porous and Tough Cementitious Materials

High-strength and lightweight are two of the most important parameters for composites in the construction field. Here, we developed a novel foam concrete structure with sandwich porous structure by using in-situ polymerized polyacrylamide and ultra-stable foam, which can obtain higher mechanical strength in comparison to the normal porous concrete with the same density. The ratio of stiffness to weight was maximized to achieve the optimal sandwich porous structure size. The SEM images showed that the interface bond between the foam concrete and the polymer modified cement paste was tight and robust. The flexural strength of the novel structure was 65.6% higher than that of the foamed concrete at the same density. The series model was established to calculate the composite thermal conductivity of the novel foam concrete structure, indicating that the heat insulation was slightly improved compared with the normal foam concrete. Moreover, water resistance displayed a slight increase by constructing this sandwich porous structure. Hopefully, the novel composite with sandwich porous structure can put a new way for designing the lightweight and high strength insulation thermal structure.

MATLAB code for the design of high strength concrete mix

Concrete is a composite mixture containing various ingredients, whose properties may vary widely. The properties of these materials can influence the quality of concrete. Concrete mix design is a process of selecting proper ingredients and deciding on their proportions to achieve the desired workability, strength and durability. Determination of right quantities of these materials makes the construction economical. As the properties of materials varies widely, it is a tedious job to arrive at the right proportions of the concrete mix and time consuming, if worked out manually. Hence, an attempt has been made to develop a MATLAB code for the mix design of high strength concrete as per IS 10262:2019. The computer program thus developed eliminates the tedious hand calculations and helps us in mix proportioning of the input variables for a required set of output parameters. The developed program is thoroughly tested and compared the results with many manually designed problems for correctness. The MATLAB code developed for the high strength concrete mix design is computationally efficient, accurate and saves lot of time.

Enhanced Strength in a Novel CoCrNi-Base MEA via Double Nano-Precipitations by Two Step Heat Treatment

A double nano-precipitations structure was produced by aging treatment based on full-recrystallized structure of fine grains. The high-coherent L12 nano-precipitates and non-shearable incoherent μ phase formed during aging, which results in a satisfactory strength-ductility combination (the yield strength of 900 MPa, the tensile strength of 1215MPa and 40% tensile ductility) by hindering dislocation movement. The high-coherent L12 ordered structure created by spinodal decomposition can be sheared to eliminates the stress concentrations. Meanwhile, the non-shearable incoherent μ phase with a nano-size can be bypassed by dislocation and can also eliminate the stress concentrations. Our concept of annealing process is useful for the design of high strength and ductility materials.

분자동역학 모사를 이용한 고강도, 저발열 고분자 복합재료 설계 및 연구

분자동역학 모사를 이용한 고강도, 저발열 고분자 복합재료 설계 및 연구

Ultra-high strength and plasticity mediated by partial dislocations and defect networks: Part II: Layer thickness effect

Layer thickness dependent mechanical behaviors of metallic nanolaminates have been extensively investigated. In a recent study [1], we show that a particular defect network, consisting of layer interface, stacking faults and twin boundaries, plays an important role in achieving high strength in Cu/Co multilayers. Here, we report a follow-up study on the effect of layer thickness on this unique interplay of defect networks. To this end, we investigate the mechanical behavior of highly textured Cu (111)/Co (0002) multilayers with individual layer thickness of 5, 25 and 100 nm. In situ micropillar compression tests show that the Cu/Co 25 nm multilayers have a much higher strength than 100 nm and 5 nm multilayers. Post-deformation TEM analyses and MD simulations reveal the layer thickness dependent variations of defect density dominating the strengthening effect in multilayers. This study provides new perspectives on optimal defect networks for the design of high strength, deformable metallic materials.

Plastic Deformation and Hardening Mechanisms of a Nano-twinned Cubic Boron Nitride Ceramic.

A very interesting experimental finding shows that a nano-twinned cubic boron nitride (NT-cBN) ceramic has size-dependent hardness. In order to reveal the hardening mechanism of NT-cBN, the plastic deformation mechanism of single-crystalline cubic boron nitride (SC-cBN) under nano-indentation is first studied, and then that of NT-cBN is further investigated using atomistic simulations with a parameter-modified Tersoff potential. It is found that the plastic deformation of SC-cBN under nano-indentation is mainly attributed to serial dislocation behaviors, such as the formation of dislocation embryos, shear loops, and prismatic loops. In comparison, for NT-cBN, the plastic behavior is much more complex, which is influenced by a dislocation blockage, absorption, dissociation, and re-nucleation due to the interaction between dislocations and twin boundaries (TBs). From the plastic deformation mechanism of NT-cBN, it is found that the size-dependent hardening behavior of NT-cBN is a competitive result between the hardening sources, including slip transfer, dislocation accumulation, and suppression of dislocation nucleation, and the softening sources, including TBs being destroyed, parallel slips of dislocations, and the formation of new sites for dislocation nucleation. The smaller the distance between the adjacent TBs, the more dominant the role of hardening sources is, resulting in the high size-dependent hardness of NT-cBN. The results in this paper should be helpful for the optimized design of high strength and toughness of nano-structured cBN ceramics.