This report summarizes the results of international parallel test on the measurement of the elastic shear modulus at very small strains, Gmax, using bender elements which was carried out from 2003 to 2005 by technical committee, TC29 (Stress-strain and Strength Testing of Geomaterials) of the International Society of Soil Mechanics and Geotechnical Engineering. The purpose was to evaluate the consistency of the bender element test results obtained by applying the exactly similar test material as well as the test method besides identifying the various existing hardware and software being used in this test. It was decided that the domestic TC29 group of Japanese Geotechnical Society (TC29-JGS) was expected to lead this international co-operation. By 2005, reports of the test results were obtained from 23 institutions from 11 countries. This report has been prepared by TC29-JGS taking a leading role from the beginning. A standard test method is proposed here in order to obtain more accurate data from the bender element test by examining various test methods adopted at diŠerent institutions worldwide and the eŠects of various factors on the test results.

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The rapid development of wind energy in Japan and the associated high uncertainties and fluctuations in power generation present a big challenge for both wind power generators and electric grids. Accurate and reliable wind power predictions are necessary to optimize the integration of wind power into existing electrical systems. In this study, a hybrid forecasting system of wind power generation was developed by integrating the Kalman filter (KF) with the high resolution Weather Research and Forecasting (WRF) model as well as an empirical formula of wind power output (power curve). The system has been validated with observations including wind speed and power output over a six-month period for 15 turbine sites at a wind farm in Awaji-island, Japan. The results show that the tuned WRF model is able to provide hub-height wind speed prediction for the target area with reliability to some extent. The predicted wind field can be substantially improved by the Kalman filter as a post-processing procedure. The 15-turbine averaged improvements of mean error, root mean square error, and correlation coefficient are 97%, 22%, and 10%, respectively. Meanwhile, the Kalman filter also demonstrates a promising capability of reducing the uncertainties in the power curve model. Systematic validations regarding both wind speed and power output were carried out against the observations for the target wind farm, which show that the hybrid power forecasting system presented in this paper can be an effective and practical tool for short-term predictions of wind speed and power output in Japan area.

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