654 research outputs found

    Prediction of qualitative parameters of slab steel ingot using numerical modelling

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    The paper describes the verification of casting and solidification of heavy slab ingot weighing 40 t from tool steel by means of numerical modelling with use of a finite element method. The pre-processing, processing and post-processing phases of numerical modelling are outlined. Also, the problems with determination of the thermodynamic properties of materials and with determination of the heat transfer between the individual parts of the casting system are discussed. The final porosity, macrosegregation and the risk of cracks were predicted. The results allowed us to use the slab ingot instead of the conventional heavy steel ingot and to improve the ratio, the chamfer and the external shape of the wall of the new design of the slab ingot

    GENETIC AND PHENOTYPIC PARAMETERS ESTIMATED FROM NEBRASKA SPECI FIC-PATHOGEN-FREE SWINE FIELD RECORDS

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    Records collected during 1971 through 1979 from 101,606 hogs raised in 18 Nebraska Specific Pathogen Free herds were analyzed. Traits considered were backfat at 100 kg (BF), weight at 140 d of age (WT) and, in some analyses, number of live pigs/litter at birth (NBA). The phenotypic correlation of BF and WT, averaged across herds, was -.07. The correlations between BF and NBA and between WT and NBA were .04 and -.05, respectively. Average phenotypic standard deviations for BF, WT and NBA were 2.6 mm, 8.8 kg and 2.0 pigs. Estimates of the heritability of BF and WT were lower than most estimates reported from university research herds. Within breed, herd and sex estimates of heritability ranged from -.22.and .51 (unweighted Χ̅ = .16 ± .025) for BF and ranged from -.28 to .49 (Χ̅ = .16 ± .016) for WT. Estimates of the genetic correlation between BF and WT were extremely variable (Χ̅ = -.62 ± 14.3, range = -9.42 to 1.30) among breed-herd-sex subclasses

    Determination of solidus and liquidus temperatures for S34MnV steel grade by thermal analysis and calculations

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    The paper is devoted to the comparison of the results in the frame of solidus and liquidus temperatures obtained by thermo analytical methods with the generally used empirically based formulas and thermo dynamical Computherm software. The series of thermal analysis measurements of high temperature phase transformations of real steel grade (S34MnV) under conditions of two analytical devices (Netzsch STA 449 F3 Jupiter; Setaram Multi High Temperature Calorimeter (MHTC)) were carried out. Two thermo analytical methods were used (DSC and Direct Thermal Analysis). The different weight of samples was used (2,6 g; 23 g). The liquidus and solidus temperatures for close to equilibrium conditions during heating (DSC: 1 °C/min; 2 °C/min) and during cooling (Direct Thermal Analysis: 1 °C/min) were determined and compared. Then, the discussion on the different values obtained by experiments and empirically based calculation is realised

    The use of remotely sensed data and polish NFI plots for prediction of growing stock volume using different predictive methods

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    Forest growing stock volume (GSV) is an important parameter in the context of forest resource management. National Forest Inventories (NFIs) are routinely used to estimate forest parameters, including GSV, for national or international reporting. Remotely sensed data are increasingly used as a source of auxiliary information for NFI data to improve the spatial precision of forest parameter estimates. In this study, we combine data from the NFI in Poland with satellite images of Landsat 7 and 3D point clouds collected with airborne laser scanning (ALS) technology to develop predictive models of GSV. We applied an area-based approach using 13,323 sample plots measured within the second cycle of the NFI in Poland (2010–2014) with poor positional accuracy from several to 15 m. Four different predictive approaches were evaluated: multiple linear regression, k-Nearest Neighbours, Random Forest and Deep Learning fully connected neural network. For each of these predictive methods, three sets of predictors were tested: ALS-derived, Landsat-derived and a combination of both. The developed models were validated at the stand level using field measurements from 360 reference forest stands. The best accuracy (RMSE% = 24.2%) and lowest systematic error (bias% = −2.2%) were obtained with a deep learning approach when both ALS- and Landsat-derived predictors were used. However, the differences between the evaluated predictive approaches were marginal when using the same set of predictor variables. Only a slight increase in model performance was observed when adding the Landsat-derived predictors to the ALS-derived ones. The obtained results showed that GSV can be predicted at the stand level with relatively low bias and reasonable accuracy for coniferous species, even using field sample plots with poor positional accuracy for model development. Our findings are especially important in the context of GSV prediction in areas where NFI data are available but the collection of accurate positions of field plots is not possible or justified because of economic reasons

    Orthogonal methods based ant colony search for solving continuous optimization problems

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    Research into ant colony algorithms for solving continuous optimization problems forms one of the most significant and promising areas in swarm computation. Although traditional ant algorithms are designed for combinatorial optimization, they have shown great potential in solving a wide range of optimization problems, including continuous optimization. Aimed at solving continuous problems effectively, this paper develops a novel ant algorithm termed "continuous orthogonal ant colony" (COAC), whose pheromone deposit mechanisms would enable ants to search for solutions collaboratively and effectively. By using the orthogonal design method, ants in the feasible domain can explore their chosen regions rapidly and e±ciently. By implementing an "adaptive regional radius" method, the proposed algorithm can reduce the probability of being trapped in local optima and therefore enhance the global search capability and accuracy. An elitist strategy is also employed to reserve the most valuable points. The performance of the COAC is compared with two other ant algorithms for continuous optimization of API and CACO by testing seventeen functions in the continuous domain. The results demonstrate that the proposed COAC algorithm outperforms the others

    A novel approach for construction of radiocarbon-based chronologies for speleothems

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    Robust chronologies are crucial for the correct interpretation of climate proxy records and for detailed reconstructions of palaeoclimate. Stalagmites have garnered strong interest as recorders of past climate in part due to their amenability to U-series dating. However, many stalagmites are not dateable using this technique due to low 238U and/or high detrital Th concentrations (e.g., many tropical cave systems (Adkins et al., 2013)), and occasionally these issues affect stalagmites across wide geographical regions (e.g., large parts of Australia (Green et al. 2013)) complicating the use of stalagmites in these areas. Radiocarbon (14C) offers an alternative method of dating stalagmites, but issues associated with the ‘dead carbon fraction’ (DCF) have historically hindered this approach. Here, a novel 14C-based method for dating stalagmites is presented and discussed. The technique calculates a best-fit growth rate between a time-series of stalagmite 14C data and known atmospheric 14C variability. The new method produces excellent results for stalagmites that satisfy four requirements: i) the absence of long-term secular variability in DCF (i.e., stalagmite DCF varies around a mean value with no long-term trend), ii) stalagmite growth rate does not vary significantly (the technique identifies stalagmites with substantial growth rate variability), iii) the stalagmite record is long enough that measurable 14C decay has occurred, and iv) one ‘anchor’ point exists where the calendar age is known. The model produces good results for a previously U–Th dated stalagmite from Heshang Cave, China, and is then applied to an undated stalagmite from southern Poland. The new method will not replace high-precision U–Th measurements, because the precision of the technique is difficult to quantify. However, it provides a means for dating certain stalagmites undateable by conventional U–Th methods and for refining coarse U–Th chronologies

    Physicochemical and Biological Characterisation of Diclofenac Oligomeric Poly(3-hydroxyoctanoate) Hybrids as β-TCP Ceramics Modifiers for Bone Tissue Regeneration

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    Nowadays, regenerative medicine faces a major challenge in providing new, functional materials that will meet the characteristics desired to replenish and grow new tissue. Therefore, this study presents new ceramic-polymer composites in which the matrix consists of tricalcium phosphates covered with blends containing a chemically bounded diclofenac with the biocompatible polymer-poly(3-hydroxyoctanoate), P(3HO). Modification of P(3HO) oligomers was confirmed by NMR, IR and XPS. Moreover, obtained oligomers and their blends were subjected to an in-depth characterisation using GPC, TGA, DSC and AFM. Furthermore, we demonstrate that the hydrophobicity and surface free energy values of blends decreased with the amount of diclofenac modified oligomers. Subsequently, the designed composites were used as a substrate for growth of the pre-osteoblast cell line (MC3T3-E1). An in vitro biocompatibility study showed that the composite with the lowest concentration of the proposed drug is within the range assumed to be non-toxic (viability above 70%). Cell proliferation was visualised using the SEM method, whereas the observation of cell penetration into the scaffold was carried out by confocal microscopy. Thus, it can be an ideal new functional bone tissue substitute, allowing not only the regeneration and restoration of the defect but also inhibiting the development of chronic inflammation
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