Effects of ferrite content and concentrations of carbon and silicon on weld solidification cracking susceptibility of stainless steels

In the welding of austenitic stainless steels, the formation of approximately 5% δ-ferrite phase is often used to decrease the susceptibility to solidification cracking. The partition coefficients of impurity elements such as phosphorous and sulfur of the ferrite phase are high, which expand the temperature range of solidification. At the same time, it is well known that the solidification cracking susceptibility increases with increasing δ-ferrite content above 20%. Thus, high δ-ferrite content increases the solidification cracking susceptibility, even though the δ-ferrite phase has high solubility of the impurity elements. The aim of this work was to investigate the effects of the δ-ferrite content and the concentration of carbon and silicon on the solidification crack susceptibility of Fe–18%Cr stainless steel with various nickel concentrations. The ferrite content was controlled by adding various amounts of nickel. The brittle temperature range (BTR) hardly changed with increasing δ-ferrite content, regardless of the type and concentrations of carbon and silicon. Therefore, the effect of the ferrite content on solidification cracking susceptibility must be small. In addition, the BTR increased with the concentrations of carbon and silicon. The specimens containing higher concentrations of carbon exhibited higher BTRs than those containing silicon. It is considered that the solidification segregation corresponding to the partition coefficient of carbon to the δ-ferrite phase induces an increase in cracking susceptibility. In addition, the formation of austenite during solidification reduces cracking susceptibility owing to the higher solubility of carbon

Effects of toe and ankle training in older people: a cross-over study.

Maintenance of physical function in the elderly is important. Previous studies have focused mainly on training-center-based interventions, accompanied by training staff or equipped with training machinery. The purpose of this study was to investigate the effects of toe and ankle training for the elderly

Adaptive Multi-Level Compilation in a Trace-based Java JIT Compiler

This paper describes our multi-level compilation techniques implemented in a trace-based Java JIT compiler (trace-JIT). Like existing multi-level compilation for method-based compilers, we start JIT compilation with a small compilation scope and a low optimization level so the program can start running quickly. Then we identify hot paths with a timer-based sampling profiler, generate long traces that capture the hot paths, and recompile them with a high optimization level to improve the peak performance. A key to high performance is selecting long traces that effectively capture the entire hot paths for upgrade recompilations. To do this, we introduce a new technique to generate a directed graph representing the control flow, a TTgraph, and use the TTgraph in the trace selection engine to efficiently select long traces. We show that our multilevel compilation improves the peak performance of programs by up to 58.5 % and 22.2 % on average compared to compiling all of the traces only at a low optimization level. Comparing the performance with our multi-level compilation to the performance when compiling all of the traces at a high optimization level, our technique can reduce the startup times of programs by up to 61.1 % and 31.3 % on average without significant reduction in the peak performance. Our results show that our adaptive multilevel compilation can balance the peak performance and startup time by taking advantage of different optimization levels