U.S.-Japan Seminar: Structural Performance of High-Strength Concrete in Seismic Regions/November 1994/Honolulu, HI

美日研讨会：地震地区高强度混凝土的结构性能/1994 年 11 月/夏威夷州檀香山

• 批准号: 9315122
• 负责人: Catherine French
• 金额: $ 1.5万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-04-01 至 1995-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9315122&HistoricalAwards=false
• 关键词: U.S.; Japan; Seminar; Structural; Performance

9315122 French This award supports the participation of nine U.S. scientists and engineers in a U.S.-Japan Seminar on Structural Performance of High- Strength Concrete in Seismic Regions, scheduled for November 1994 in Honolulu, Hawaii. The seminar is co-organized by Professor Catherine French, Department of Civil and Mineral Engineering, University of Minnesota, and Professor Fumio Watanabe, Department of Architectural Engineering, Kyoto University. In addition to the U.S. and Japanese participants, scientists from Australia, Canada, and New Zealand, are expected to attend. A large quantity and variety of test data on high-strength reinforced concrete has become available through recent test programs conducted in the United States, Japan, Canada, New Zealand, and Norway. These data include information on material development, structural performance, and construction procedures. The seminar will focus on the design and performance of high-strength reinforced concrete structures located in seismic regions. Participants will exchange recently acquired data, evaluate the data, and develop rational design recommendations. In the process, deficiencies in the database and future research needs may be identified.

9315122法国 该奖项支持9名美国科学家和工程师参加美国-日本地震区高强度混凝土结构性能讨论会，定于1994年11月在夏威夷的檀香山举行。 研讨会由明尼苏达大学土木与矿物工程系Catherine French教授和京都大学建筑工程系Fumio Watanabe教授联合举办。 除了美国和日本的参与者，来自澳大利亚，加拿大和新西兰的科学家预计将参加。 通过最近在美国、日本、加拿大、新西兰和挪威进行的试验项目，已经可以获得大量和各种各样的关于高强钢筋混凝土的试验数据。 这些数据包括有关材料开发、结构性能和施工程序的信息。 该研讨会将重点放在位于地震区的高强度钢筋混凝土结构的设计和性能。 与会者将交流最近获得的数据，评估数据，并制定合理的设计建议。 在此过程中，可能会发现数据库中的缺陷和未来的研究需求。