scholarly journals Data Mining of the Thermal Performance of Cool-Pipes in Massive Concrete via In Situ Monitoring

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Zheng Zuo ◽  
Yu Hu ◽  
Qingbin Li ◽  
Liyuan Zhang
Keyword(s):  
Data Mining ◽  
Flow Rate ◽  
Thermal Performance ◽  
Monitoring Program ◽  
Heat Removal ◽  
Arch Dam ◽  
In Situ Monitoring ◽  
High Arch Dam ◽  
Massive Concrete

Embedded cool-pipes are very important for massive concrete because their cooling effect can effectively avoid thermal cracks. In this study, a data mining approach to analyzing the thermal performance of cool-pipes via in situ monitoring is proposed. Delicate monitoring program is applied in a high arch dam project that provides a good and mass data source. The factors and relations related to the thermal performance of cool-pipes are obtained in a built theory thermal model. The supporting vector machine (SVM) technology is applied to mine the data. The thermal performances of iron pipes and high-density polyethylene (HDPE) pipes are compared. The data mining result shows that iron pipe has a better heat removal performance when flow rate is lower than 50 L/min. It has revealed that a turning flow rate exists for iron pipe which is 80 L/min. The prediction and classification results obtained from the data mining model agree well with the monitored data, which illustrates the validness of the approach.

A monitoring-mining-modeling system and its application to the temperature status of the Xiluodu arch dam

2016 ◽  
Vol 20 (2) ◽  
pp. 235-244 ◽  
Author(s):  
Yu Hu ◽  
Guohe Liang ◽  
Qingbin Li ◽  
Zheng Zuo
Keyword(s):  
Data Mining ◽  
Numerical Modeling ◽  
Thermal State ◽  
Arch Dam ◽  
In Situ Monitoring ◽  
External Boundary ◽  
High Arch Dam ◽  
Element Analysis ◽  
First Case ◽  
Cooling Pipes

Knowledge of the concrete temperature of a dam is necessary for the implementation of improved construction methodologies. A monitoring-mining-modeling system is proposed in this article to study the thermal state of a super high arch dam in China. The monitoring-mining-modeling system includes an in situ monitoring network setup, data mining methods, and numerical finite element analysis. Two engineering cases are surveyed in detail using monitoring-mining-modeling system. The first case is the long-term temperature rise phenomenon, whose cause is determined from the data mining result, and the numerical modeling of the external boundary condition is improved using the result. The modeling result then shows that the effect of the TRP is also a dangerous factor for the deformation and stress state of the dam. The second case is the performance of cooling pipes. The energy absorption capability of the cooling pipes is revealed by the data mining result, as well as the performance difference between high-density polyethylene and iron pipes. The numerical modeling result shows good agreement with the monitored result, which demonstrates the closed-loop validity of the monitoring-mining-modeling system.

Remote sensing of cyanobacterial blooms in Lake Champlain, USA

2013 ◽  
Vol 13 (5) ◽  
pp. 1402-1409
Author(s):  
Adam Trescott ◽  
Elizabeth Isenstein ◽  
Mi-Hyun Park
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Monitoring Program ◽  
In Situ Monitoring ◽  
Cyanobacterial Blooms ◽  
Lake Champlain ◽  
Initiation And Propagation ◽  
Landsat 7

The objective of this study was to develop cyanobacteria remote sensing models using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) as an alternative to shipboard monitoring efforts in Lake Champlain. The approach allowed for estimation of cyanobacteria directly from satellite images, calibrated and validated with 4 years of in situ monitoring data from Lake Champlain's Long-Term Water Quality and Biological Monitoring Program (LTMP). The resulting stepwise regression model was applied to entire satellite images to provide distribution of cyanobacteria throughout the surface waters of Lake Champlain. The results demonstrate the utility of remote sensing for estimating the distribution of cyanobacteria in inland waters, which can be further used for presenting the initiation and propagation of cyanobacterial blooms in Lake Champlain.

In Situ Functional Monitoring of Aerosol Jet-Printed Electronic Devices Using a Combined Sparse Representation-Based Classification (SRC) Approach

2018 ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
Darshana L. Weerawarne ◽  
M. Samie Tootooni ◽  
Prahalada K. Rao ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Functional Properties ◽  
Process Parameters ◽  
Flow Rate ◽  
Gas Flow ◽  
Electronic Devices ◽  
In Situ Monitoring ◽  
Gas Flow Rate ◽  
Aerosol Jet Printing

The goal of this work is in situ monitoring of the functional properties of aerosol jet-printed electronic devices. In pursuit of this goal, the objective is to develop a multiple-input, single-output (MISO) machine learning model to estimate the device functional properties in a near real-time fashion as a function of process parameters as well as 2D/3D features of line morphology. The aim is to use the MISO model for in situ estimation and thus, monitoring of line/device resistance in aerosol jet printing (AJP) process. To realize this objective, silver nanoparticle structures are printed by varying three process parameters: (i) sheath gas flow rate (ShGFR), (ii) exhaust gas flow rate (EGFR), and (iii) print speed (PS). Subsequently, line morphology is captured in situ using a high-resolution charge-coupled device (CCD) camera, mounted coaxial to the nozzle. Besides, utilizing 2D/3D quantifiers (introduced in the authors’ previous publications), the line morphology is further quantified, and the extracted features (e.g., line width, overspray, cross-sectional area, etc.) are fed as inputs to a novel sparse representation-based classification (SRC) model. The four-point probe method is used for measurement of resistance, and definition of a priori classification labels. The outcome of this research paves the way for future control of device functional properties in AJP process.

scholarly journals Stability of a Rock Tunnel Passing through Talus-Like Formations: A Case Study in Southwestern China

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Shaoqiang Zhang ◽  
Wenqiang Li ◽  
Jiashan Tan ◽  
Bokuan Li ◽  
Xiaochang Li ◽  
...  
Keyword(s):  
Rock Mass ◽  
Rock Pressure ◽  
Monitoring Program ◽  
Surrounding Rock ◽  
In Situ Monitoring ◽  
Monitoring Data ◽  
Surrounding Rock Pressure ◽  
Set Up ◽  
Highway Project

Tayi tunnel is one of the component tunnels in the Jian-Ge-Yuan Highway Project located in Yunnan Province, southeast of China. It mainly passes through talus-like formations comprised of rock blocks of diverse sizes and weak interlayers with clayey soils with different fractions. Such a special composition leads to the loose and fractured structure of talus-like formations, which is highly sensitive to the excavation perturbation. Therefore, Tayi tunnel has become the controlled pot of the whole highway project as the construction speed has to be slowed down to reduce the deformation of surrounding talus-like rock mass. To better understand the tunnel-induced ground response and the interaction between the surrounding rock mass and tunnel lining, a comprehensive in situ monitoring program was set up. The in situ monitoring contents included the surrounding rock pressure on the primary lining, the primary lining deformation, and the stress of steel arches. Based on the monitoring data, the temporal and the long-term spatial characteristics of mechanical behavior of surrounding rock mass and lining structure due to the excavation process were analyzed and discussed. It is found that the excavation of lower benches released the surrounding rock pressure around upper benches, resulting in the decrease of the surrounding rock pressure on the primary lining and the stress of steel arches. In addition, the monitoring data revealed that the primary lining sustained bias pressure from the surrounding rock mass, which thereby caused unsymmetrical deformation of the primary lining, in accordance with the monitored displacement data. A dynamically adaptive support system was implemented to strengthen the bearing capacity of the lining system especially in the region of an extremely weak rock mass. After such treatment, the deformation of the primary lining has been well controlled and the construction speed has been considerably enhanced.

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