The Terra-correlator: A computing facility for massive real-time data assimilation in environmental science
The Terra-correlator: A computing facility for massive real-time data assimilation in environmental science
批准号:
NE/L012979/1
负责人:
Ian Main
金额:
$37.93万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2013
资助国家:
英国
项目状态:
已结题
起止时间:
2013 至 --
中文摘要
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英文摘要
1. Seismic interferometry: Seismologists have traditionally explored the Earth by measuring, analysing and modelling signals generated naturally by earthquakes, or deliberately by man-made sources. Since 2003, several authors derived new methods based on cross-correlation of seismograms that allowed similar information to be obtained in the absence of impulsive events - from the Earth's ambient fluctuations, previously regarded as noise. Current global data sets can be used to produce Earth impulse responses of ~20kB size every two hours, or up to 2TB of output data per day, the bulk of this providing completely new information. This will be done on node 1. The output will then be data-mined continuously and in parallel to extract near-real time information about subsurface changes for forecasting purposes. This requires additional near-real time correlations in time-lapse mode, pattern matching, and other methods of analysis and modelling to be applied on a separate node (node 2), tied to a portal that will ensure such analysis and any forecasts of future behaviour or events (say a volcanic eruption following a seismic velocity change) is verifiably done in advance of the real event time, removing at a stroke perennial problems with retrospective selection bias when analysing forecast quality based on past data.2. Earth system science: (a) A recurring challenge is to analyse direct Earth observation, satellite and model data with data- and compute-intensive processing for uncertainty analyses and parameter-space exploration. The new facility will be used to produce estimates of carbon stocks and fluxes with confidence intervals over the period 2000-2013. Ultimately our UK runs at 1 km2 may be used to generate near-real time analyses of GHG emissions that are likely to be useful for policy makers. The information content of planned EO missions, such as ESA's BIOMASS mission, will also be explored in observing system simulation experiments. ( b) Many of our typical current analyses of the performance of climate models in comparison with the outcome are constrained by reading in data multiple times, due to lack of memory. We will analyse NOAA data to find extreme events at much higher resolution than before of 25km globally, to research the mechanisms and characteristic signatures of extreme precipitation events. 3. High-resolution real time monitoring of deformation and fluid flow in porous rocks: X-ray C-T (computer-tomography) imaging is computationally intensive in a range of applications, but a very large amount of post-processing is required by the operator to tune the resulting image, notably to separate pore space from the solid phase. Time-lapse measurements open up the possibility of tracking fluid flow in fractures or pores, or observing deformation at unprecedented resolution by tracking (cross-correlating) particle movements. Accordingly the infrastructure overhead used in the first two applications will be used to make such analysis possible in a 'live' experiment, in support of on-going experimental and modelling work in rock physics, initially focussed on carbonates.
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dispel4py: An Agile Framework for Data-Intensive eScience
dispel4py:数据密集型电子科学的敏捷框架
DOI:
10.1109/escience.2015.40
发表时间:
2015
期刊:
影响因子:
--
作者:
[Filgueira R]
通讯作者:
Filgueira R
Using Statistical Models and Machine Learning Techniques to Process Big Data from the Forth Road Bridge
使用统计模型和机器学习技术处理第四路大桥的大数据
DOI:
10.1680/icsic.64669.411
发表时间:
2019
期刊:
影响因子:
--
作者:
[Xu D]
通讯作者:
Xu D
dispel4py : A Python framework for data-intensive scientific computing
dispel4py:用于数据密集型科学计算的 Python 框架
DOI:
10.1177/1094342016649766
发表时间:
2016
期刊:
The International Journal of High Performance Computing Applications
影响因子:
--
作者:
[Filguiera R]
通讯作者:
Filguiera R
dispel4py
驱散4py
DOI:
10.1145/2835857.2835863
发表时间:
2015
期刊:
影响因子:
--
作者:
[Krause A]
通讯作者:
Krause A
On the edge?
-
批准号:NE/X014541/1
-
项目类别:Research Grant
-
资助金额:$107.07万
-
财政年份:2023
-
负责人:Ian Main
-
依托单位:
Catastrophic Failure: what controls precursory damage localisation in rocks?
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批准号:NE/R001693/1
-
项目类别:Research Grant
-
资助金额:$80.91万
-
财政年份:2017
-
负责人:Ian Main
-
依托单位:
Probability and Uncertainty in Risk Estimation and Communication
-
批准号:NE/N012356/1
-
项目类别:Research Grant
-
资助金额:$25.95万
-
财政年份:2016
-
负责人:Ian Main
-
依托单位:
Hydrocarbon reservoir analytics using high-frequency pressure data
-
批准号:NE/L008386/1
-
项目类别:Research Grant
-
资助金额:$7.22万
-
财政年份:2014
-
负责人:Ian Main
-
依托单位:
Active reservoir management for improved hydrocarbon recovery
-
批准号:NE/J006483/1
-
项目类别:Research Grant
-
资助金额:$14.95万
-
财政年份:2012
-
负责人:Ian Main
-
依托单位:
Probability, Uncertainty and Risk in the Natural Environment
-
批准号:NE/J016438/1
-
项目类别:Research Grant
-
资助金额:$39.31万
-
财政年份:2012
-
负责人:Ian Main
-
依托单位:
Localizing signatures of catastrophic failure (LOCAT)
-
批准号:EP/I018492/1
-
项目类别:Research Grant
-
资助金额:$25.05万
-
财政年份:2011
-
负责人:Ian Main
-
依托单位:
Active reservoir management for improved hydrocarbon recovery
-
批准号:NE/I029846/1
-
项目类别:Research Grant
-
资助金额:$1.64万
-
财政年份:2011
-
负责人:Ian Main
-
依托单位:
Hazard forecasting in real time: from controlled laboratory tests to volcanoes and earthquakes
-
批准号:NE/H02297X/1
-
项目类别:Research Grant
-
资助金额:$67.15万
-
财政年份:2011
-
负责人:Ian Main
-
依托单位:
Time-dependent deformation: bridging the strain rate gap in brittle rocks.
-
批准号:NE/G019061/1
-
项目类别:Research Grant
-
资助金额:$5.44万
-
财政年份:2009
-
负责人:Ian Main
-
依托单位:
海外基金