scholarly journals CONSERVATION AND MAINTENANCE CONCEPTS OF SOONG CHING LING’S DOLOMITE MARBLE STATUE IN SHANGHAI AND SUPPORTING SURVEY METHODS

2021 ◽  
Vol XLVI-M-1-2021 ◽  
pp. 579-584
Author(s):  
T. Qin ◽  
Y. Wang ◽  
J. Li ◽  
Z. Tang ◽  
S. Dai
Keyword(s):  
Survey Methods ◽  
Monitoring Program ◽  
Climatic Data ◽  
Republic Of China ◽  
National Monument ◽  
Dolomite Marble ◽  
Marble Statue ◽  
Maintenance Work ◽  
Ultrasonic Ct

Abstract. The dolomite marble statue of Madam Soong Ching Ling, Honorary Chairlady of the People’s Republic of China, is situated in the memorial square of Soong Ching Ling’s Mausoleum in Shanghai, China. The statue is composed of 4 pieces of white marble (Hanbaiyu) from Fangshan, Beijing. The statue, along with the mausoleum, has been listed as a national monument since 1982, yet severe deterioration occurred in recent years. In May 2018, a diagnostic investigation of the statue was carried out. Aided by advanced photogrammetry methods such as 3D modelling, macro photography and infrared thermography, all micro cracks were identified and labelled. Other advanced in-situ and laboratory surveys such as in-situ microscope, ultrasonic CT inspection, chalking evaluation test and mineralogical investigation were applied to further evaluate the condition. Based on analysis of all test results, conservation and maintenance concepts including a monitoring program specifically to control cracking has been developed. This concept was approved by the authorities and implemented in May 2019. After two years’ exposure, an evaluation of previous conservation and a new maintenance work were recently completed in April 2021. A long-term monitoring strategy as well as maintenance methods will be worked out based on the evaluation of all implemented efforts and climatic data.

In-situ load testing of a WWII era timber Warren truss in the development of a structural health monitoring program

2021 ◽  
Vol 239 ◽  
pp. 112274
Author(s):  
Henry Helmer-Smith ◽  
Nicholas Vlachopoulos ◽  
Marc-André Dagenais ◽  
Bradley Forbes
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Monitoring Program ◽  
Load Testing ◽  
Structural Health

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.

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.

Use of Long Term Pavement Performance-Seasonal Monitoring Program Data to Develop and Validate a Generalized Regression Model to Predict the In-Situ Resilient Modulus of Subgrade Soils for Pavement Design and Evaluation

2020 ◽  
Vol 2674 (5) ◽  
pp. 673-684
Author(s):  
Mohamed Elshaer ◽  
Christopher DeCarlo ◽  
Wade Lein ◽  
Harshdutta Pandya ◽  
Ayman Ali ◽  
...  
Keyword(s):  
Prediction Model ◽  
Resilient Modulus ◽  
Monitoring Program ◽  
Pavement Design ◽  
Pavement Performance ◽  
Regression Approach ◽  
Seasonal Monitoring ◽  
Generalized Regression

Resilient modulus (Mr) is a critical input for pavement design as it is the main property used to evaluate the contribution of subgrade to the overall pavement structure. Considering this, practitioners need simple and accurate ways to determine the Mr of in-situ subgrade without the need for expensive and time-consuming testing. The objective of this study is to develop a generalized regression prediction model for in-situ Mr of subgrades, compare it with established prediction models, and assess the model’s predictions on pavement performance using the Mechanistic-Empirical Pavement Design Guide (Pavement ME). The prediction model was built using field data from 30 pavement sections studied in the Long Term Pavement Performance (LTPP) Seasonal Monitoring Program where backcalculated modulus from falling weight deflectometer testing, in-situ moisture contents, and subgrade material properties were considered in the model. Based on the results, it was found that liquid limit, plasticity index, WPI (the product of percent passing #200 and plasticity index), percent coarse sand, percent fine sand, percent silt, percent clay, moisture content, and their respective interactions were significant predictors of in-situ Mr values. The findings showed that the generalized regression approach was able to predict Mr more accurately than predictions from the Witczak model. To assess the application of the predictive model on pavement performance, three LTPP sections located in New York, South Dakota, and Texas were analyzed to predict the rutting performance based on Mr values obtained from the developed generalized prediction model and those obtained from the current Pavement ME model and then compared with rut depths measured in the field. The findings showed that, for coarse-grained subgrades that have a low degree of plasticity, the generalized regression model predicted rutting performance similar to the embedded Pavement ME model. For fine-grained subgrades, the developed model tends to predict lower rut depths which were closer to the field measured rut depths. Overall, the generalized regression approach was successfully applied to create a simple, practical, cost-effective and accurate Mr prediction model that can be used to estimate the stiffness of subgrades when designing and evaluating pavements.

scholarly journals Application of FBG Sensing Technology to Internal Deformation Monitoring of Landslide

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Haiyou Peng ◽  
Bolin Chen ◽  
Ping Dong ◽  
Si chen ◽  
Yunping Liao ◽  
...  
Keyword(s):  
Slip Surface ◽  
Survey Methods ◽  
Surface Displacement ◽  
Deformation Monitoring ◽  
In Situ Monitoring ◽  
Fiber Grating ◽  
Monitoring Point ◽  
Sensing Technology ◽  
Internal Deformation

Limited by geological survey methods, processes, and cost, it has long been a difficult thing to accurately detect the position of landslide slip surface and monitor the landslide internal deformation. Fiber Bragg grating (FBG) sensing technology has been widely used in geological engineering and geotechnical engineering due to its high-precision property. In this research, FBG sensing technology was applied to the monitoring of landslide internal deformation in Toudu, Chongqing, China. The in situ monitoring by FBG accurately determined the position of the landslide slip surface. Based on the relationship between fiber grating strain and deflection, the formula between landslide internal deformation and fiber grating strain was obtained, and the rationality of the formula was verified by the monitoring data of surface displacement. Finally, the internal deformation at the monitoring point of the Toudu landslide was calculated and the mechanism of the landslide was analyzed.

Smart: Scientific Monitoring of Advanced Response Technologies

1999 ◽  
Vol 1999 (1) ◽  
pp. 1265-1267 ◽  
Author(s):  
Nir Barnea ◽  
Roger Laferriere
Keyword(s):  
Real Time ◽  
Monitoring Program ◽  
Visual Observation ◽  
Data Logging ◽  
Tier Ii ◽  
Oil Spill Response ◽  
Aerial Platforms ◽  
Unified Command ◽  
Trained Observers

ABSTRACT SMART (Scientific Monitoring of Advanced Response Technologies) is a new monitoring program designed to provide the Unified Command with real-time field data when in situ burning and dispersants are used during oil spill response. For dispersant monitoring, SMART recommends a three-tiered approach. Tier I has visual observation by trained observers from vessels or from aerial platforms. Tier II combines visual observations with water-column sampling using a fluorometer at a single depth. Tier III expands the fluorometry monitoring to several water depths, and uses a water-quality lab. Water samples for later analysis and correlation of fluorometry readings are taken both in Tier II and Tier III. For in situ burning, SMART recommends deploying three or more monitoring teams, each equipped with a real-time particulate monitor with data-logging capability. The teams deploy downwind of the burn at sensitive locations, and report particulate concentration trends to the Unified Command.

The Design of a Monitoring Program for Iron Alloys on Underwater Historic Shipwrecks in Fathom Five National Marine Park, Ontario, Canada

1996 ◽  
Vol 462 ◽  
Author(s):  
John Stewart ◽  
Lome D. Murdock ◽  
Nancy Binnie
Keyword(s):  
Monitoring Program ◽  
Iron Alloys ◽  
Visual Observation ◽  
Photographic Recording ◽  
Ph Measurements ◽  
Surface Ph ◽  
X Ray ◽  
Marine Park ◽  
Predominant Form

ABSTRACTIn order to design a scheme to monitor the state of preservation of iron alloys that are found on historic shipwrecks sunk in fresh water, it was first necessary to identify the predominant form of corrosion found on the wrecks. This was done by visual observation, in situ surface pH measurements, and X-ray powder diffraction of the corrosion layers. Once the form of corrosion was identified as pitting corrosion, a monitoring scheme based on photographic recording of the rust-red tubercles was designed. This scheme is simple and nondestructive, both necessary characteristics for the monitoring of submerged historic resources.

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