A TRIAL OF RECYLING ORIENTED STEEL DESIGN

我们在1994年jpn . ints . metals的年度秋季会议上提出了未来钢铁设计的主要理念，以改善回收利用：从自然资源的角度来看，一种具有简单化学成分的多用途钢铁是可取的。基于这种思维方式，我们选择了Fe-Mn-Si-C体系作为“生态钢”的典型例子。对一种Fe-Mn-Si-C钢的拉伸性能范围进行了实验研究。为了进行调查，对两种钢进行了熔化、铸造和热遗忘，其中一些进行了冷轧。制作了板材拉伸试样，并对试样进行了各种热处理。通过光电子显微镜和扫描电镜对复合组织（铁素体-珠光体、铁素体-贝氏体、铁素体-马氏体和铁素体-贝氏体-马氏体）和单一组织（贝氏体-马氏体）进行了表征。分别用ISIJ数据库（Swift方程）和割线法（细观力学）预测了单组织钢的拉伸流动曲线变化。讨论了拉伸性能与微观组织关系的上下限，并首次用迭代计算技术计算了三微观组织钢的流动曲线。预测结果与实验结果吻合较好。最后，将上述性能预测方法与材料生命周期分析（MLCA）相结合，讨论了生态钢的设计。

We propsed a principal idea for future steel design to improve the recycling at the 1994 annual fall meeting of Jpn.Inst.Metals : a steel for multi-purpose use with simple chemical compositions consisting of optimistic elements from the viewpoint of natural resources is desirable. Based on this way of thinking, we have chosen an Fe-Mn-Si-C system as a typical example of "eco-steel".The rage of tensile properties which can be covered by controlling the micro-structure of one kind of Fe-Mn-Si-C steel was experimentally examined. For investigation, two steels were melted, cast and hot forget and some of them were cold rolled. Plate tension specimes were made and various kinds of heat treatment were subjected to the specimens. The resultant microstructures of single-microstructure (bainite and martensite) and multi-microstructure (ferrite-pearlite, ferrite-bainite, ferrite-martensite and ferrite-bainite-martensite) were characterized by light and scanning electron microsopes.The variations of tensile flow curves were predicted : by using data base of ISIJ (Swift equation) for single-microstructure steels and by the secant method (micromechanics) for muli-microstructure steels, respectively. The upper and lower limits in microstructure depedence of tensile properties have been discussed and the flow curve of a tri-microstructure steel were first caluclated using iterative computing technique. The predictions have been found to show good agreements with experimental results.Finally, the eco-steel design was discussed by coupling the above properties prediction method and materials life cycle analysis (MLCA).