The Central Strain Analytical Modeling and Analysis for the Plate Rolling Process

The strain after rolling plays an important role in the prediction of the microstructure and properties and plate deformation permeability. So it is necessary to establish a more accurate theoretical strain model for the rolling process. This paper studies the modeling method of the equivalent strain based on the upper bound principle and stream function method. The rolling deformation region is divided into three zones (inlet rigid zone, plastic zone, and outlet rigid zone) according to the kinematics. The boundary conditions of adjacent deformation zones are modified according to the characteristics of each deformation zone. A near-real kinematics admissible velocity field is established by the stream function method on this basis. The geometric boundary conditions of the deformation region are obtained. The deformation power, friction power and velocity discontinuous power are calculated according to the redefined geometric boundary conditions. On this basis, the generalized shear strain rate intensity is calculated according to the minimum energy principle. Finally, the equivalent strain model after rolling is obtained by integrating the generalized shear strain rate in time. The plate rolling experiments of AA1060 and the numerical simulations are carried out with different rolling reductions to verify the analytic model precision of the equivalent strain. The results show that the minimum and maximum relative equivalent strain deviation between the analytic model and the experiment is 0.52% and 9.96%, respectively. The numerical calculation and experimental results show that the model can accurately calculate the strain along the plate thickness. This model can provide an important reference for the rolling process setup and the microstructure and properties prediction.

Improving Coarse Grain Models of Protein Folding through Weighting of Polar-polar/hydrophobic-hydrophobic Interactions into Crowded Spaces

In this piece of work were tested 7 Hydrophobic-Polar sequences in two types of 2D-square space lattices, homogeneous and correlated, the latter simulating molecular crowding included as a geometric boundary restriction. The optimization of the 2D structures was carried out using a variant of Dill's model, inspired by the convex function, which takes into account both the hydrophobic (Dill’s model) and polar interactions, aimed to include more structural information to reach better folding solutions. While using correlated networks, the degrees of freedom in the folding of sequences were limited, and as a result in all cases more successful structural trials were found in comparison to the homogeneous lattice. In particular, the S5 sequence turned out to be the most difficult sequence of the seven folded, this perhaps due to the intrinsic i) degrees of freedom and ii) motifs of the expected 2D HP structure. Regarding S2 and S6 sequences, although optimal folding was not achieved for neither of the two approaches, folding with correlated network approach not only produced better results than homogeneous space, but for both sequences the best values found with crowding were very close to the expected optimal fitness. The sequences S1-S4 and S6 were better folded with medium lattice units for the correlated media, instead, S5 and S7 were better folded with a bit larger degree of lattice unit, revealing that depending on the degrees of freedom and particular folding motifs in each sequence would require particular crowding to achieve better folding. Finally, we claim that in all folded sequences in crowded spaces achieve better results than homogeneous ones.

Flexible bar compression test

The article considers experimental and theoretical research of longitudinal stability of a flexible steel bar design under axial compression. The bar is a flat thin-walled element, pivotally fixed at the ends. The experimental study was carried out on a Zwick/Roell Z100 installation using special equipment that simulates geometric boundary conditions. During the loading process, a diagram of the deformation of a real bar with initial shape imperfections was automatically constructed. The experimental critical force was determined from the deformation diagram. This force was compared with the critical forces obtained from calculations using two schemes: the Euler formula and the dynamic analysis methodology. In the second scheme, in contrast to the first one, the initial imperfection, established by the measurements of the tested structure, was taken into account. The design calculation errors for both schemes were determined.

A self-learning finite element extraction system based on reinforcement learning

Automatic generation of high-quality meshes is a base of CAD/CAE systems. The element extraction is a major mesh generation method for its capabilities to generate high-quality meshes around the domain boundary and to control local mesh densities. However, its widespread applications have been inhibited by the difficulties in generating satisfactory meshes in the interior of a domain or even in generating a complete mesh. The element extraction method's primary challenge is to define element extraction rules for achieving high-quality meshes in both the boundary and the interior of a geometric domain with complex shapes. This paper presents a self-learning element extraction system, FreeMesh-S, that can automatically acquire robust and high-quality element extraction rules. Two central components enable the FreeMesh-S: (1) three primitive structures of element extraction rules, which are constructed according to boundary patterns of any geometric boundary shapes; (2) a novel self-learning schema, which is used to automatically define and refine the relationships between the parameters included in the element extraction rules, by combining an Advantage Actor-Critic (A2C) reinforcement learning network and a Feedforward Neural Network (FNN). The A2C network learns the mesh generation process through random mesh element extraction actions using element quality as a reward signal and produces high-quality elements over time. The FNN takes the mesh generated from the A2C as samples to train itself for the fast generation of high-quality elements. FreeMesh-S is demonstrated by its application to two-dimensional quad mesh generation. The meshing performance of FreeMesh-S is compared with three existing popular approaches on ten pre-defined domain boundaries. The experimental results show that even with much less domain knowledge required to develop the algorithm, FreeMesh-S outperforms those three approaches in essential indices. FreeMesh-S significantly reduces the time and expertise needed to create high-quality mesh generation algorithms.

Contactless temperature measurement in wire-based electron beam additive manufacturing Ti-6Al-4V

The complex thermal cycles and temperature distributions observed in additive manufacturing (AM) are of particular interest as these define the microstructure and the associated properties of the part being built. Due to the intrinsic, layer-by-layer material stacking performed, contact methods to measure temperature are not suitable, and contactless methods need to be considered. Contactless infrared irradiation techniques were applied by carrying out thermal imaging and point measurement methods using pyrometers to determine the spatial and temporal temperature distribution in wire-based electron beam AM. Due to the vacuum, additional challenges such as element evaporation must be overcome and additional shielding measures were taken to avoid interference with the contactless techniques. The emissivities were calibrated by thermocouple readings and geometric boundary conditions. Thermal cycles and temperature profiles were recorded during deposition; the temperature gradients are described and the associated temperature transients are derived. In the temperature range of the α+β field, the cooling rates fall within the range of 180 to 350 °C/s, and the microstructural characterisation indicates an associated expected transformation of β→α'+α with corresponding cooling rates. Fine acicular α and α’ formed and local misorientation was observed within α as a result of the temperature gradient and the formation of the α’.

Identifying Complex Junctions in a Road Network

Automated generalization of road network data is of great concern to the map generalization community because of the importance of road data and the difficulty involved. Complex junctions are where roads meet and join in a complicated way and identifying them is a key issue in road network generalization. In addition to their structural complexity, complex junctions don’t have regular geometric boundary and their representation in spatial data is scale-dependent. All these together make them hard to identify. Existing methods use geometric and topological statistics to characterize and identify them, and are thus error-prone, scale-dependent and lack generality. More significantly, they cannot ensure the integrity of complex junctions. This study overcomes the obstacles by clarifying the topological boundary of a complex junction, which provides the basis for straightforward identification of them. Test results show the proposed method can find and isolate complex junctions in a road network with their integrity and is able to handle different road representations. The integral identification achieved can help to guarantee connectivity among roads when simplifying complex junctions, and greatly facilitate the geometric and semantic simplification of them.