To study the temperature distribution and thermal-stress field in different service stages, a two-dimensional model of a turbine blade with thermal barrier coatings is developed, in which the conjugate heat transfer analysis and the decoupled thermal-stress calculation method are adopted. Based on the simulation results, it is found that a non-uniform distribution of temperature appears in different positions of the blade surface, which has directly impacted on stress field. The maximum temperature with a value of 1030 °C occurs at the leading edge. During the steady stage, the maximum stress of thermally grown oxide (TGO) appears in the middle of the suction side, reaching 3.75 GPa. At the end stage of cooling, the maximum compressive stress of TGO with a value of -3.5 GPa occurs at the leading edge. Thus, it can be predicted that during the steady stage the dangerous regions may locate at the suction side, while the leading edge may be more prone to failure on cooling.
Today's emergence of nano-micro hybrid structures with almost biological complexity is of fundamental interest. Our ability to adapt intelligently to the challenges has ramifications all the way from fundamentally changing research itself, over applications critical to future survival, to posing globally existential dangers. Touching on specific issues such as how complexity relates to the catalytic prowess of multi-metal compounds, we discuss the increasingly urgent issues in nanotechnology also very generally and guided by the motto ‘Bio Is Nature's Nanotech’. Technology belongs to macro-evolution.for example integration with artificial intelligence (AI) is inevitable. Darwinian adaptation manifests as integration of complexity, and awareness of this helps in developing adaptable research methods that can find use across a wide range of research. The second half of this work reviews a diverse range of projects which all benefited from ‘playful’ programming aimed at dealing with complexity. The main purpose of reviewing them is to show how such projects benefit from and fit in with the general, philosophical approach, proving the relevance of the ‘big picture’ where it is usually disregarded.
In this study, it is attempted to give an insight into the injection processability of three self-prepared polymers from A to Z. This work presents material analysis, injection molding simulation, design of experiments alongside considering all interaction effects of controlling parameters carefully for green biodegradable polymeric systems, including polylactic acid (PLA), polylactic acid-thermoplastic polyurethane (PLA-TPU) and polylactic acid-thermoplastic starch (PLA-TPS). The experiments were carried out using injection molding simulation software Autodesk Moldflow® in order to minimize warpage and volumetric shrinkage for each of the mentioned systems. The analysis was conducted by changing five significant processing parameters, including coolant temperature, packing time, packing pressure, mold temperature and melt temperature. Taguchi's L27 (35) orthogonal array was selected as an efficient method for design of simulations in order to consider the interaction effects of the parameters and reduce spurious simulations. Meanwhile, artificial neural network (ANN) was also used for pattern recognition and optimization through modifying the processing conditions. The Taguchi coupled analysis of variance (ANOVA) and ANN analysis resulted in definition of optimum levels for each factor by two completely different methods. According to the results, melting temperature, coolant temperature and packing time had significant influence on the shrinkage and warpage. The ANN optimal level selection for minimization of shrinkage and/or warpage is in good agreement with ANOVA optimal level selection results. This investigation indicates that PLA-TPU compound exhibits the highest resistance to warpage and shrinkage defects compared to the other studied compounds.
The last few decades have witnessed an increasing emphasis on the development of strain-based approach for predicting the creep life or damage of components operating at elevated temperatures. Creep ductility, as a key parameter in this approach, may vary with a number of factors including strain rate, state of stress, operating temperature, material microstructure, etc. The present paper, however, is focused on reviewing the state-of-the-art understanding of the effects of stress level and stress state on the creep ductility. Mechanisms involving the void growth and coalescence are presented to describe the role of stress level in the variation of uniaxial creep ductility. The prediction capacity of existing empirical ductility models is also assessed in light of uniaxial test data. On the other hand, a vast body of multiaxial creep test data, collected from open literature, is utilized to examine the influence of the state of stress on the creep ductility. Then, a variety of multiaxial ductility factor models are introduced and evaluated with the available experimental data. Finally, a brief discussion on the dependence of creep ductility on the stress triaxiality and Lode parameter, predicted by numerical methods, is provided.
Molecular dynamics simulation of uniaxial tension along  has been performed to study the influence of various surface defects on the initiation of plastic deformation and fracture of γ-TiAl single crystals. The results indicate that brittle fracture occurs in perfect bulk; surfaces and edges will be detrimental to the strength of materials and provide dislocation nucleation site. The defects on surfaces and edges cause further weakening with various effects depending on defect type, size, position and orientation, while the edge dimples are the most influential. For γ-TiAl rods with surface dimples, dislocations nucleate from an edge of the rod when dimples are small, dimple dislocation nucleation occurs only when the dimples are larger than a strain rate dependent critical size. The dislocations nucleated upon  tension are super dislocations with Burger vectors <011] or 1/2 < 112] containing four 1/6 < 112 > partials. The effects of surface scratches are orientation and shape sensitive. Scratches parallel to the loading direction have little influence, while sharp ones perpendicular to the loading direction may cause crack and thus should be avoided. This simulation also shows that, any type of surface defect would lower strength, and cause crack in some cases. But some may facilitate dislocation nucleation and improve ductility of TiAl if well controlled.
In a fusion reactor, due to high heat flux (HHF) loads, the plasma facing components (PFCs) will suffer severe thermal shock. In this paper, the temperature distribution and thermal-stress field of tungsten armor under HHF loads were investigated by the method of finite element modeling and simulating. The orthogonal experiment and range analysis were employed to compare the influence degree of four representative factors: steady-state heat flux; thickness of tungsten armor; inner diameter of cooling tube and the coefficient of convection heat transfer (CCHF) of cooling water, on thermal shock behavior tungsten mock-ups, and then get an optimization model to conduct the transient heat flux experiment. The final simulation results indicated that the steady-state heat flux and the thickness of W armor are the main influential factors for the maximum temperature of mock-ups. Furthermore, the influence of transient thermal shock all mainly concentrates on the shallow surface layer of tungsten (about 500 μm) under different transient heat flux (duration 0.5 ms). The results are useful for the structural design and the optimization of tungsten based plasma facing materials for the demonstration reactor (DEMO) or other future reactors.
We investigate the dependency of strain rate, temperature and size on yield strength of hexagonal close packed (HCP) nanowires based on large-scale molecular dynamics (MD) simulation. A variance-based analysis has been proposed to quantify relative sensitivity of the three controlling factors on the yield strength of the material. One of the major drawbacks of conventional MD simulation based studies is that the simulations are computationally very intensive and economically expensive. Large scale molecular dynamics simulation needs supercomputing access and the larger the number of atoms, the longer it takes time and computational resources. For this reason it becomes practically impossible to perform a robust and comprehensive analysis that requires multiple simulations such as sensitivity analysis, uncertainty quantification and optimization. We propose a novel surrogate based molecular dynamics (SBMD) simulation approach that enables us to carry out thousands of virtual simulations for different combinations of the controlling factors in a computationally efficient way by performing only few MD simulations. Following the SBMD simulation approach an efficient optimum design scheme has been developed to predict optimized size of the nanowire to maximize the yield strength. Subsequently the effect of inevitable uncertainty associated with the controlling factors has been quantified using Monte Carlo simulation. Though we have confined our analyses in this article for Magnesium nanowires only, the proposed approach can be extended to other materials for computationally intensive nano-scale investigation involving multiple factors of influence.
First-principles computation methods play an important role in developing and designing new magnesium alloys. In this article, we present an overview of the first-principles modeling techniques used in recent years to simulate ideal models of the structure of strengthening compounds in Mg alloys. For typical Mg compounds, structural stability, mechanical properties, electronic structure and thermodynamic properties have been discussed. Specifically, the elastic anisotropies of these compounds are examined, which is highly correlated with the possibility of inducing micro-cracks. Furthermore, some heterogeneous nucleation interfaces investigated by first-principles method are reviewed. Some of the theoretical results are compared with available experimental observations. We hope to illustrate that the first-principles computation can help to accelerate the design of new Mg-based materials and the development of materials genome initiative. Remaining problems and future directions in this research field are considered.