Fracture surface, impact energy and hardness of Ni-free high-Mn steels

Two manganese steels were investigated: Fe-19.7%Mn (VM339A) and Fe-19.7%Mn stabilized with 0.056%C, 0.19%Ti and 0.083%Al (VM339B). The toughness of VM339A was higher than VM339B, but VM339B had higher hardness. Tempering does not affect the toughness of the alloys. SEM images of the fracture surface for both the alloys revealed ductile fractures. A further alloy with a lower manganese content, Fe-8.46%Mn-0.24%Nb-0.038%C, and thus even lower cost than the conventional 3.5Ni cryogenic steel, was tested for its impact toughness after heat treatment at 600°C, giving promising results.

NP-hardness of MAP in Ternary Tree Bayesian Networks

This paper strengthens the NP-hardness result for the (partial) maximum a posteriori (MAP) problem in Bayesian networks with topology of trees (every variable has at most one parent) and variable cardinality at most three. MAP is the problem of querying the most probable state configuration of some (not necessarily all) of the network variables given evidence. It is demonstrated that the problem remains hard even in such simplistic networks.

Effect of Single and Double Austenitization heat treatments on the Microstructure and Hardness of AISI D2 Tool Steel

This investigation is concerned with the study of effect of Double Austenitization (DA) and Single Austenitization (SA) heat treatment processes on microstructure and mechanical property of AISI D2type cold worked tool steel. To maximize hardness, tool steels are used in a quenched and tempered condition. This involves heating the material to the austenitizing temperature (∼850−1100 °C), quenching at an appropriate rate to form martensite, and tempering to reduce the retained austenite content and induce toughness. The merits of DA treatment isto promote dissolution of carbides at the same time proscribe grain coarsening significantly was attempted in D2 tool steel. The study has found that DA treatment has induced high hardness with insignificant growth in grains. The increase in hardness is attributed to increase in carbon content in matrix due to dissolution of carbides; whereas finer grains due to role of inclusions.

Effect of Single and Double Austenitization heat treatments on the Microstructure and Hardness of AISI D2 Tool Steel

This investigation is concerned with the study of effect of Double Austenitization (DA) and Single Austenitization (SA) heat treatment processes on microstructure and mechanical property of AISI D2type cold worked tool steel. To maximize hardness, tool steels are used in a quenched and tempered condition. This involves heating the material to the austenitizing temperature (∼850−1100 °C), quenching at an appropriate rate to form martensite, and tempering to reduce the retained austenite content and induce toughness. The merits of DA treatment isto promote dissolution of carbides at the same time proscribe grain coarsening significantly was attempted in D2 tool steel. The study has found that DA treatment has induced high hardness with insignificant growth in grains. The increase in hardness is attributed to increase in carbon content in matrix due to dissolution of carbides; whereas finer grains due to role of inclusions.

Examination of the flow rheological and textural properties of polymer gels composed of poly(methylvinylether-co-maleic anhydride) and poly(vinylpyrrolidone): rheological and mathematical interpretation of textural parameters.

The purpose of this study was to mathematically characterize the effects of defined experimental parameters (probe speed and the ratio of the probe diameter to the diameter of sample container) on the textural/mechanical properties of model gel systems. In addition, this study examined the applicability of dimensional analysis for the rheological interpretation of textural data in terms of shear stress and rate of shear. Aqueous gels (pH 7) were prepared containing 15% w/w poly(methylvinylether-co-maleic anhydride) and poly(vinylpyrrolidone) (PVP) (0, 3, 6, or 9% w/w). Texture profile analysis (TPA) was performed using a Stable Micro Systems texture analyzer (model TA-XT 2; Surrey, UK) in which an analytical probe was twice compressed into each formulation to a defined depth (15 mm) and at defined rates (1, 3, 5, 8, and 10 mm s-1), allowing a delay period (15 s) between the end of the first and beginning of the second compressions. Flow rheograms were performed using a Carri-Med CSL2-100 rheometer (TA Instruments, Surrey, UK) with parallel plate geometry under controlled shearing stresses at 20.0°?±?0.1°C. All formulations exhibited pseudoplastic flow with no thixotropy. Increasing concentrations of PVP significantly increased formulation hardness, compressibility, adhesiveness, and consistency. Increased hardness, compressibility, and consistency were ascribed to enhanced polymeric entanglements, thereby increasing the resistance to deformation. Increasing probe speed increased formulation hardness in a linear manner, because of the effects of probe speed on probe displacement and surface area. The relationship between formulation hardness and probe displacement was linear and was dependent on probe speed. Furthermore, the proportionality constant (gel strength) increased as a function of PVP concentration. The relationship between formulation hardness and diameter ratio was biphasic and was statistically defined by two linear relationships relating to diameter ratios from 0 to 0.4 and from 0.4 to 0.563. The dramatically increased hardness, associated with diameter ratios in excess of 0.4, was accredited to boundary effects, that is, the effect of the container wall on product flow. Using dimensional analysis, the hardness and probe displacement in TPA were mathematically transformed into corresponding rheological parameters, namely shearing stress and rate of shear, thereby allowing the application of the power law (??=?k?n) to textural data. Importantly, the consistencies (k) of the formulations, calculated using transformed textural data, were statistically similar to those obtained using flow rheometry. In conclusion, this study has, firstly, characterized the relationships between textural data and two key instrumental parameters in TPA and, secondly, described a method by which rheological information may be derived using this technique. This will enable a greater application of TPA for the rheological characterization of pharmaceutical gels and, in addition, will enable efficient interpretation of textural data under different experimental parameters.

Software Products for Modelling and Simulation in Materials Science

Models and software products have been developed for modelling, simulation and prediction of different correlations in materials science, including 1. the correlation between processing parameters and properties in titanium alloys and ?-titanium aluminides; 2. time–temperature–transformation (TTT) diagrams for titanium alloys; 3. corrosion resistance of titanium alloys; 4. surface hardness and microhardness profile of nitrocarburised layers; 5. fatigue stress life (S–N) diagrams for Ti–6Al–4V alloys. The programs are based on trained artificial neural networks. For each particular case appropriate combination of inputs and outputs is chosen. Very good performances of the models are achieved. Graphical user interfaces (GUI) are created for easy use of the models. In addition interactive text versions are developed. The models designed are combined and integrated in software package that is built up on a modular fashion. The software products are available in versions for different platforms including Windows 95/98/2000/NT, UNIX and Apple Macintosh. Description of the software products is given, to demonstrate that they are convenient and powerful tools for practical applications in solving various problems in materials science. Examples for optimisation of the alloy compositions, processing parameters and working conditions are illustrated. An option for use of the software in materials selection procedure is described.