Search results

Introduction Positron annihilation lifetime spectroscopy (PALS) is very sensitive and able to identify different kinds of defects and their agglomerates such as vacancies, dislocations, vacancy loops, grain boundaries, vacancy-impurity complexes, and voids [1-4].
A consequence of the absorption by MR is the considerable decrease in positron intensity and hence the number of annihilation incidences is lower in the composite.
The positronium lifetime tPs also showed a decrease at higher irradiation doses since the number of smaller pores increase as the aggregated vacancy clusters initially form small pores.
In this scenario, one expects a decrease in Ie+ with a corresponding increase in IPs as the aggregated vacancy clusters form small pores resulting in an increase in number of pores as the irradiation dose increases.

For many low cycle fatigue formulations, the cyclic degradation phenomenon is effectively modelled by either Paris law [6] or Peerling law [7], generally as functions of the stress cycle amplitude, mean value and the number of loading cycles.
In Ref. [12] Oller et al. developed a continuum mechanics approach to fatigue analysis, in the framework of damage modelling, for which the threshold damage is function of the cycle number.
The modelled mechanical behavior is governed by the evolution of the state variables during any loading path, instead of the number of cycles.
Benedetti, “An enhanced grain-boundary framework for computational homogenization and micro-cracking simulations of polycrystalline materials,” Computational Mechanics, vol. 56, no. 4, pp. 631-651, 2015

One of the ways of the fractality determination is a count of the number of cells falling within the concentric circles of different diameters.
The dimension of cell packing on the plane is approximately equal to ~2, at that, the whole-number value of dimension suggests the uniform filling-in of the plane.
The sample in Fig. 1d, on the contrary, was “sewn” of sufficiently large “grains”, parts numbering several dozens of cells each and having the characteristic «diameter» of about 4-7 cells.

Fire-retardant coatings Sample number and composition Presence (+) or absence (–) of a basic components Presence (+) or absence (–) of a additional component Composition of the flame retardant, pH-value Fire-retardant coating: technical lignosulphanate powder, sodium carbonate, sapropel, potassium iodide 1H3PO3: 1NH4OH, pH ≤ 5.5 2H3PO3: 2NH4OH: 1CH4NO2, pH ≤ 5.5 1H3PO3: 8NH4OH, pH = 8.5 1 wood + + + – steel – – – – 2 wood + + + – steel – – – – 3 wood + + + – steel – – – – 4.1 wood + + + – steel – – – + 4.2 wood + + + – steel – – – + 4.3 wood + + + – steel – – – + 5 wood – – – – steel – – – – Results The results of the experiments have shown that more than 19% weight loss was recorded in samples untreated by fire retardant agents and exposed to an open flame for 10 min., and a 30% decrease of weight for samples treated in an open flame for 25 min (in control sample).
Wood fracture caused by flame impact Sample number and composition Wood fracture, % (mass.)
Bending strength of Steel after flame impact Sample number and composition Bending strength of Steel, kN Composition of the flame retardant, pH-value 1H3PO3: 1NH4OH, pH ≤ 5.5 2H3PO3: 2NH4OH: 1CH4NO2, pH ≤ 5.5 1H3PO3: 8NH4OH, pH = 8.5 by flame impact for 10 min by flame impact for 25 min by flame impact for 10 min by flame impact for 25 min by flame impact for 10 min by flame impact for 25 min 1 wood-steel 1.12 1.3 1.11 1.3 1.10 1.30 2 wood-steel 1.2 1.33 1.18 1.35 1.2 1.33 3 wood-steel 1.00 1.15 1.05 1.2 1.10 1.2 4.1 wood-steel 1.15 1.30 1.14 1.32 1.15 1.34 4.2 wood-steel 1.20 1.35 1.22 1.36 1.20 1.35 4.3 wood-steel 1.05 1.2 1.00 1.21 1.05 1.2 5 wood-steel 1.00 1.15 1.02 1.17 1.01 1.13 Conclusions In a wood-steel composite, wood is the component most susceptible to destruction by flame.
[14] Petrycki, A. and Salem, O. (2019), "Structural fire performance of wood-steel-wood bolted connections with and without perpendicular-to-wood grain reinforcement", Journal of Structural Fire Engineering, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JSFE-02-2019-0016 [15] Muhaned A.

Deformation introduces a large density of dislocations into the material, which can alter the precipitation behaviour and sequence in a number of ways [1-5]: (i) Dislocations act as vacancy sinks and annihilate quenched-in vacancies resulting in the suppression of clustering during natural aging [1, 6]; (ii) Dislocations provides heterogeneous nucleation sites for precipitates [5]; (iii) Precipitation on dislocations promotes the stable rather than metastable phases [1]; (iv).In many alloys the presence of dislocations prior to aging may increase mechanical properties after the heat treatment, which results from the superposition of the modification of the precipitation characteristics and of the intrinsic strain hardening due to dislocations.
New dislocations are then generated or multiplied as proposed by the Frank-Read mechanism [17], and they further frequently pile up on slip planes at grain and subgrain boundaries.
The governing factor for such a case is the dislocation density, when with increasing amount of introduced dislocations, the number of nucleation sites for precipitates is increased and faster dislocation-assisted diffusion replaces slower bulk diffusion.
These observations are in a good agreement with the findings of a number of research groups [2, 4, 7, 19, 20].

It was reported that for an operation of 400,000 km/year the number of stress cycles of axles and wheels is about 2x108 cycles [1] falling in the fatigue life known as gigacycle fatigue [2].
A number of 100 measurements of splats diameter and thickness were performed for each sample in order to evaluate the splats average size and distribution.
These findings are consistent with other author’s works that have studied the influence of the support material temperature on the splashing tendency and grain morphology [11].
A number of 100 splats randomly selected on the top surface were measured and the distribution and average equivalent splat diameter, D, was calculated.

This seems to be appropriate as the steel fiber lengths are usually larger than the grain size of concrete (Hassan Ahmad et al., 1991[4]).
The mechanical properties of SFRC are determined by a number of factors including the elastic modulus and strengths of constituents; the aspect ratio, volume fraction, orientation and distribution of steel fibers; and the nature of the interface of steel fiber/matrix bond.

A large number of studies have investigated the thermoelectric characteristics of Mg2Si, and the output characteristics of Mg2Si and modules have been reported by Iida and others[3,4].
The Co3O4 phase disappeared at x=1.5, and a single phase of NaCo2O4 was obtained because a small amount of Na became localized at the grain boundary or evaporated during the heat treatment in the electrical furnace.

The microstructure of alloy A consists of lamellar martensite, retained austenite, VC particles with exploded shape and (Fe,Cr,V)7C3 complex carbides, the (Fe,Cr,V)7C3 complex carbides are distributed on the grain boundaries with a interrupted netted structure, as illustrated in.
In Fig.3c, when the Cr content is 25% , it was found that there are a number of (Fe,Cr,V)7C3 complex carbides with hexagonal shape distributed dispersely and uniformly in the matrix.

After liming, symmetrically cutting the whole limed pelt along the ridge line, then cutting to a number of small leather pieces, weighing, and then adding different deliming materials to implement deliming experiment according to the following processes.
Measuring the content of calcium ion in the grain layer, middle layer and meat layer of the leather sample; specifically splitting the leather sample with an operating knife blade according to the method specified in 1.2.1, and respectively calculating the content of calcium ion of each layer.