Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Deformation and annealing of (011)[011] oriented A1 single crystals

High purity Al single crystals of the (011)[011] orientation have been deformed in plane strain compression in a channel die. Deformation was carried out at a strain rate of 0.01 s−1 to true strains of 0.5 and 1.0, and at temperatures of 25, 200 and 300 °C. The as-deformed microstructure has been characterized using electron backscattered diffraction (EBSD) and X-ray diffraction (XRD). No recrystallization was detected after deformation, and the deformation texture analysis showed that the stability of the orientation decreased with increasing temperature, contrary to reports for other orientations.

Annealing was carried out for various times at 300 °C. Nucleation of recrystallization exhibited periodicity, with distinct bands of recrystallized grains forming parallel to the transverse direction. This recrystallized microstructure has been examined using EBSD. A model is proposed to account for the origin of the periodicity of nucleation and the retention of rods or cylinders of unrecrystallized material after significant annealing times.

Dynamic recrystallization of austenite in Ni-30 Pct Fe model alloy : microstructure and texture evolution

The microstructure and crystallographic texture development in an austenitic Ni-30 pct Fe model alloy was investigated within the dynamic recrystallization (DRX) regime using hot torsion testing. The prominent DRX nucleation mechanism was strain-induced grain boundary migration accompanied by the formation of large-angle sub-boundaries and annealing twins. The increase in DRX volume fraction occurred through the formation of multiple twinning chains. With increasing strain, the pre-existing Σ3 twin boundaries became gradually converted to general boundaries capable of acting as potent DRX nucleation sites. The texture characteristics of deformed grains resulted from the preferred consumption of high Taylor factor components by new recrystallized grains. Similarly, the texture of DRX grains was dominated by low Taylor factor components as a result of their lower consumption rate during the DRX process. The substructure of deformed grains was characterized by “organized,” banded subgrain arrangements, while that of the DRX grains displayed “random,” more equiaxed subgrain/cell configurations.

Integrating simulated annealing and delta technique for constructing optimal prediction intervals

This paper aims at developing a new criterion for quantitative assessment of prediction intervals. The proposed criterion is developed based on both key measures related to quality of prediction intervals: length and coverage probability. This criterion is applied as a cost function for optimizing prediction intervals constructed using delta technique for neural network model. Optimization seeks out to minimize length of prediction intervals without compromising their coverage probability. Simulated Annealing method is employed for readjusting neural network parameters for minimization of the new cost function. To further ameliorate search efficiency of the optimization method, parameters of the network trained using weight decay method are considered as the initial set in Simulated Annealing algorithm. Implementation of the proposed method for a real world case study shows length and coverage probability of constructed prediction intervals are better than those constructed using traditional techniques.

Microstructure evolution and softening processes occurring during annealing of hot deformed Ni-30Fe austenite

The current work investigates the microstructure evolution and softening processes that take place during annealing of an austenitic Ni-30Fe model alloy subjected to hot deformation in the dynamic recrystallization (DRX) regime. The substructure of the deformed matrix grains largely comprised organized microband arrays, though that of the DRX grains consisted of more random, complex subgrain/cell arrangements. This substructure disparity was also reflected by the distinct difference in the mechanism of post-deformation softening taking place during annealing of the deformed matrix and DRX grains. In the former, the recrystallization process took place through nucleation and growth of new grains fully replacing the deformed structure, as expected for the classical static recrystallization (SRX). The corresponding texture was essentially random, in contrast to that of the DRX grains dominated by low Taylor factor components. The microbands originally present within the deformed matrix grains displayed some tendency to disintegrate during annealing, nonetheless, they remained largely preserved even at prolonged holding times. During annealing of the fully DRX microstructure, a novel softening mechanism was revealed. The initial post-dynamic softening stage involved rapid growth of the dynamically formed nuclei and migration of the mobile boundaries in correspondence with the well-established metadynamic recrystallization (MDRX) mechanism. However, in contrast to the deformed matrix, SRX was not observed and the sub-boundaries within DRX grains rapidly disintegrated through dislocation climb and dislocation annihilation, which led to the formation of dislocation-free grains already at short holding times. Consequently, the DRX texture initially became slightly weakened and then remained largely preserved throughout the annealing process.

Texture evolution and softening processes in an austenitic Ni-30Fe alloy subjected to hot deformation and subsequent annealing

The current work has investigated the texture development in an austenitic Ni-30Fe model alloy during deformation within the dynamic recrystallization (DRX) regime and after post-deformation annealing. Both the deformed matrix and DRX texture displayed the expected FCC shear components, the latter being dominated by the low Taylor factor grains, which was presumably caused by their lower consumption rate during DRX. The deformed matrix grains were largely characterized by organized, microband structures, while the DRX grains showed more random, complex subgrains/cell arrangements. The latter substructure type proved to be significantly less stable during post-deformation annealing. The recrystallization of the deformed matrix occurred through nucleation and growth of new grains fully replacing the deformed structure, as expected for the classical static recrystallization (SRX). Unlike the DRX grains, the SRX texture was essentially random. By contrast, a novel softening mechanism was revealed during annealing of the fully DRX microstructure. The initial post-dynamic softening stage involved rapid growth of the dynamically formed nuclei and migration of the mobile boundaries in line with the well-established metadynamic recrystallization (MDRX) mechanism, which weakened the starting DRX texture. However, in parallel, the sub-boundaries within the deformed DRX grains progressively disintegrated through dislocation climb and dislocation annihilation, which ultimately led to the formation of dislocation-free grains. Consequently, the weakened DRX texture largely remained preserved throughout the annealing process.

Effect of substructure characteristics on the dislocation annihilation process during post-deformation annealing

Two distinct substructures were produced in a Ni-30Fe austenitic model alloy by different thermomechanical processing routes. The first substructure largely displayed organized, banded subgrain arrangements with alternating misorientations, resulting from the deformation at a strain just before the initiation of dynamic recrystallization (DRX). By contrast, the second substructure was more random in character and exhibited complex subgrain/cell arrangements characterized by local accumulation of misorientations, formed through DRX. During the post-deformation annealing, the latter substructure revealed a rapid disintegration of dislocation boundaries leading to the formation of dislocation-free grains within a short holding time, though the former largely preserved its characteristics till becoming replaced by growing statically recrystallized grains.

Asymmetric rolling of interstitial-free steel using differential roll diameters. Part II : microstructure and annealing effects

The effects of annealing on the microstructure, texture, tensile properties, and R value evolution of an IF steel sheet after room-temperature symmetric and asymmetric rolling were examined. Simulations were carried out to obtain R values from the experimental textures using the viscoplastic self-consistent polycrystal plasticity model. The investigation revealed the variations in the textures due to annealing and symmetric/asymmetric rolling and showed that the R values correlate strongly with the evolution of the texture. An optimum heat treatment for the balance of strength, ductility, and deep drawability was found to be at 873 K (600 _C) for 30 minutes.

Evolution of strain-induced precipitates in a model austenitic Fe-30Ni-Nb steel and their effect on the flow behaviour

The present work investigated the evolution of strain-induced NbC precipitates in a model austenitic Fe-30Ni-Nb steel deformed at 925 °C to a strain of 0.2 during post-deformation holding between 3 and 1000 s and their effect on the reloading flow stress. The precipitate particles preferentially nucleated on the nodes of the periodic dislocation networks constituting microband walls. Holding for 10 s resulted in the formation of fine, largely coherent NbC particles with a mean diameter of ∼5 nm, which displayed a cube-on-cube orientation relationship with austenite and caused the maximum increase in the reloading steady-state flow stress. A further increase in the holding time from 30 to 1000 s led to the formation of semi-coherent, gradually coarser and more widely spaced particles with a mean diameter of 8 nm and above, which led to a gradual decrease in the reloading steady-state flow stress. The holding time increase resulted in progressive disintegration of the dislocation substructure and dislocation annihilation through static recovery processes, which was also reflected by the measured softening fractions. The precipitate particle shape changed during post-deformation annealing from elliptical to faceted octahedral and subsequently to tetra-kai-decahedral. © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Projected length annealing of etched Sm-152 ion tracks in apatite

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effects of thermal annealing on the semi-insulating properties of radio frequency magnetron sputtering-produced germanate thin films

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Simulated annealing for building roof contours identification from lidar data

This paper proposes a method by simulated annealing for building roof contours identification from LiDAR-derived digital elevation model. Our method is based on the concept of first extracting aboveground objects and then identifying those objects that are building roof contours. First, to detect aboveground objects (buildings, trees, etc.), the digital elevation model is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing algorithm. Experiments carried out with laser scanning digital elevation model showed that the methodology works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives.

Estudo do annealing de traços de fissão em epídoto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

Atomically resolved study of the morphology change of InAs/GaAs quantum dot layers induced by rapid thermal annealing

The optoelectronic properties of InAs/GaAs quantum dots can be tuned by rapid thermal annealing. In this study, the morphology change of InAs/GaAs quantum dots layers induced by rapid thermal annealing was investigated at the atomic-scale by cross-sectional scanning tunneling microscopy. Finite elements calculations that model the outward relaxation of the cleaved surface were used to determine the indium composition profile of the wetting layer and the quantum dots prior and post rapid thermal annealing. The results show that the wetting layer is broadened upon annealing. This broadening could be modeled by assuming a random walk of indium atoms. Furthermore, we show that the stronger strain gradient at the location of the quantum dots enhances the intermixing. Photoluminescence measurements show a blueshift and narrowing of the photoluminescence peak. Temperature dependent photoluminescence measurements show a lower activation energy for the annealed sample. These results are in agreement with the observed change in morphology. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4770371]