Characteristics of numerical errors using the overset grid method are investigated. The overset grid method has some problems with the interpolation of data between each mesh. In the case of the computing advective equation, a traveling wave passing through an interface of overlapping meshes causes numerical oscillations. The oscillations near the interface destroy the solution, and cause overflow. In order to investigate the causes of the numerical errors on the overset grid, we apply wave analysis on each component mesh. We show that phase differences between component meshes cause the numerical errors and that the accuracy of the phase velocity is quite important to compute the advective equation with less numerical errors on the overset grid. We suggest that calculations using accurate phase velocity will reduce numerical errors. We show that CIP scheme is one of the most useful schemes to represent wave propagation with high accuracy and without oscillation on the overset grid.

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Multi-Channel Seismic reflection (MCS) system is a seismic system exploring underground structure, which enables to image of underground structure analyzing seismic signals reflecting at layer-boundaries and faults. Japan Agency for Marine-Earth Science and Technology has been conducted seismic surveys for understating seismogenesis using seismic systems. Nowadays objectives for seismic surveys have become broader than ever so high resolution imaging is needed. Moreover, seismic system loading on various vessels seems to be required for the survey in the special waters such as shallow areas or arctic sea. To fulfill the new demand, a Portable MCS system was implemented in 2011. Acquired data is in good quality to confirm the realization of the intended high-resolution structural images. Moreover, detailed structural images using the Portable MCS system were acquired around the toe of landward slope of the Japan Trench, contributing to the proposal of ocean drilling stations (or points). Since more seismic surveys using the Portable MCS system are scheduled in the future, the system will be used more frequently and widely.

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Because the frictional properties of fault gouge are important for understanding earthquake slip behavior, laboratory studies of high velocity rock friction have been conducted. A sleeve of polytetrafluoroethylene (PTFE) is used around the specimen to maintain pressure and prevent leaks during the experiment, and sometimes appeared to be worn and material from it was mixed into the specimen. However, the effect of PTFE contamination in the specimen is uncertain, although PTFE is known for its extremely low frictional coefficient. Here we reported new quantitative measurements of the amount of contamination by worn PTFE sleeve material in the specimen after experiments by a calorimetric technique using simultaneous thermogravimetry and differential scanning calorimetry. We also performed the friction experiments using mixtures of illite-rich shale and PTFE powder, and demonstrated that high PTFE contamination can affect the friction values of specimens.

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Previous studies have not demonstrated the estimate errors in growth parameters (skeletal density, extension rate and calcification rate) for massive coral skeletons. In order to discuss the variability of coral skeletal growth, it is crucial for quantitative evaluation of the parameters with errors. We report the protocol of calculating errors as combined standard uncertainty for coral skeletal density (u_ρSA) based on ISO/IEC Guide 98–3 (2008). We applied the non-destructive transparent X-ray 2-D imaging scanner, TATSCAN-X1, which enabled to quick and quantitative analysis of the u_ρSA parameters with digital procedures. We analyzed the annual skeletal density for massive Porites coral collected from Ishigaki Island. The skeletal densities changed from 1.45 to 1.70 g/cm³ and u_ρSA were ca. 0.02 g/cm³. Our results indicated that the u_ρSA was derived from the combined effects of 78.5% from the standard uncertainty of deducing of analytical curve (u _{ln OD (Y)→ρ*t (X)}) and 6.3% from that of the sample thickness error (u_tSA).

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