Influence of Ni and Process Parameters in Medium Mn Steels Heat Treated by High Partitioning Temperature Q&P Cycles

In this work, two medium Mn steels (5.8 and 5.7 wt pct Mn) were subjected to a quenching and partitioning (Q&P) treatment employing a partitioning temperature which corresponded to the start of austenite reverse transformation (ART). The influence of a 1.6 wt pct Ni addition in one of the steels and cycle parameters on austenite stability and mechanical properties was also studied. High contents of retained austenite were obtained in the lower quenching temperature (QT) condition, which at the same time resulted in a finer microstructure. The addition of Ni was effective in stabilizing higher contents of austenite. The partitioning of Mn and Ni from martensite into austenite was observed by TEM–EDS. The partitioning behaviour of Mn depended on the QT condition. The lower QT condition facilitated Mn enrichment of austenite laths during partitioning and stabilization of a higher content of austenite. The medium Mn steel containing Ni showed outstanding values of the product of tensile strength (TS) and total elongation (TEL) in the lower QT condition and a higher mechanical stability of the austenite.

     

Crop mapping in countries with small-scale farming: a case study for West Shewa,Ethiopia

Remote sensing is nowadays considered to be a valuable input for the annual collection of crop statistics. Derived crop maps can serve as a baseline for yield or area estimation or to target next year's census. For subsistence farming, where small parcels are mixed with other land use, crop mapping remains very challenging. This article evaluates the potential of discriminating crops in West Shewa, an area with small-scale farming in central Ethiopia. A hard classification of high-resolution (30 m) images, yielding good results for commercial farming, could not deal with mixed pixels due to the small parcels. Very high resolution (4 m) images have a more appropriate pixel size, although they only cover subsets of the region. The very high resolution classification was used to calibrate a neural network for sub-pixel classification of the high resolution images. The accuracies were not satisfactory, but did at least demonstrate the potential of this approach.