MRI: Development of a Wirelessly-Connected Network of Seismometers and GPS Instruments for Polar and Geophysical Research

MRI：开发用于极地和地球物理研究的地震仪和 GPS 仪器无线连接网络

• 批准号: 1039982
• 负责人: Sridhar Anandakrishnan
• 金额: $ 97.49万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1039982&HistoricalAwards=false
• 关键词: MRI; Development; Wirelessly; Connected; Network

Intellectual Merit: Knowledge of englacial and subglacial conditions are critical for ice sheet models and predictions of sea-level change. Some of the critical variables that are poorly known but essential for improving flow models and predictions of sea-level change are: basal roughness, subglacial sedimentary and hydrologic conditions, and the temporal and spatial variability of the ice sheet flow field. Seismic reflection and refraction imaging and dense arrays of continuously operating GPS receivers can determine these parameters. The PIs propose to develop a network of wirelessly interconnected geophysical sensors (geoPebble) that will allow glaciologists to carry out these experiments simultaneously. This sensor web will provide a new way of imaging the ice sheet that is not possible with current instruments. With this sensor web, the PIs will extend the range of existing instruments from 2D to 3D, from low resolution to high resolution, but more importantly, all the geophysical measurements will be conducted synchronously. By the end of the proposal period the PIs will produce a network of 150-200 geoPebbles that will be available for NSF-sponsored glaciology research projects. Broader impacts: Improved knowledge of the flow law of ice, the sliding of glaciers and ice streams, and paleoclimate history will contribute to assessments of the potential for abrupt ice-sheet mass change, with consequent sea-level effects and significant societal impacts. This improved modeling ability will be a direct consequence of better knowledge of the physical properties of ice sheets, which this project will facilitate. The development effort will be integrated with the undergraduate education program via the capstone design classes in EE and the senior thesis requirement in Geoscience. The PIs will also form a cohort of first-year and sophomore students who will work in their labs from the beginning of the project to develop specifications through the commissioning of the network.

智力优势：冰内和冰下条件的知识对于冰盖模型和海平面变化的预测至关重要。有些关键变量鲜为人知，但对改进水流模型和海平面变化预测至关重要，它们是：基底粗糙度、冰下沉积和水文条件以及冰盖流场的时空变异性。地震反射和折射成像以及连续工作的全球定位系统接收器的密集阵列可以确定这些参数。PI建议开发一个无线互联的地球物理传感器网络（geoPebble），使冰川学家能够同时进行这些实验。这种传感器网络将提供一种新的方式来成像冰盖，这是目前的仪器无法实现的。有了这个传感器网络，PI将把现有仪器的范围从2D扩展到3D，从低分辨率扩展到高分辨率，但更重要的是，所有的地球物理测量将同步进行。到提案期结束时，PI将产生一个由150-200个geoPebble组成的网络，可用于NSF赞助的冰川学研究项目。更广泛的影响：对冰的流动规律、冰川和冰流的滑动以及古气候历史的进一步了解，将有助于评估冰盖质量突然变化的可能性，以及随之产生的海平面影响和重大社会影响。这种改进的建模能力将是更好地了解冰盖物理特性的直接结果，该项目将促进这一点。开发工作将通过EE的顶点设计课程和地球科学的高级论文要求与本科教育计划相结合。PI还将组成一个由一年级和二年级学生组成的队列，他们将从项目开始就在实验室工作，通过网络的调试来制定规范。