Using field data to evaluate the complex bridge piers scour methods

2016 ◽  
Vol 43 (3) ◽  
pp. 218-225 ◽  
Author(s):  
M.H. Jannaty ◽  
A. Eghbalzadeh ◽  
S.A. Hosseini
Keyword(s):  
Field Data ◽  
Complex Geometry ◽  
Bridge Piers ◽  
Scour Depth ◽  
Laboratory Studies ◽  
Sediment Characteristics ◽  
Pier Scour ◽  
Recorded Data

Scour is a phenomenon that causes riverbed erosion. Many laboratory studies have been conducted to identify the complex geometry of the scour mechanism and to predict its depth, and various methods have been proposed. In this study, the performance of these methods in estimating scour depth was evaluated using field data. For this purpose, scour data on the Adinan Bridge, which was destroyed as a result of the scour phenomenon and consequently rebuilt, was collected. The bridge was built with complex piers. The flow and sediment characteristics for the bridge site were determined using field measurement. Then, the pier scour was calculated using the empirical formula and the calculated values were compared with the recorded data. The results showed the inefficiency of these methods in accurately estimating the scour depth. However, the role of the components of a composite pier has not been reflected properly in the determination of scour in these methods.

Evaluation of Selected Pier-Scour Equations Using Field Data

1996 ◽  
Vol 1523 (1) ◽  
pp. 186-195 ◽  
Author(s):  
Mark N. Landers ◽  
David S. Mueller
Keyword(s):  
Field Measurements ◽  
Bridge Piers ◽  
Critical Ratio ◽  
Scour Depth ◽  
Flow Depth ◽  
Clear Water ◽  
Pier Scour ◽  
Logarithmic Space ◽  
State Highway ◽  
Federal Highway

Field measurements of channel scour at bridges are needed to improve the understanding of scour processes and the ability to accurately predict scour depths. An extensive data base of pier-scour measurements has been developed over the last several years in cooperative studies between state highway departments, the Federal Highway Administration, and the U.S. Geological Survey. Selected scour processes and scour design equations are evaluated using 139 measurements of local scour in live-bed and clear-water conditions. Pier-scour measurements were made at 44 bridges around 90 bridge piers in 12 states. The influence of pier width on scour depth is linear in logarithmic space. The maximum observed ratio of pier width to scour depth is 2.1 for piers aligned to the flow. Flow depth and scour depth were found to have a relation that is linear in logarithmic space and that is not bounded by some critical ratio of flow depth to pier width. Comparisons of computed and observed scour depths indicate that none of the selected equations accurately estimate the depth of scour for all of the measured conditions. Some of the equations performed well as conservative design equations; however, they overpredict many observed scour depths by large amounts. Some equations fit the data well for observed scour depths less than about 3 m (9.8 ft), but significantly underpredict larger observed scour depths.

scholarly journals ANFIS-based approach for scour depth prediction at piers in non-uniform sediments

2009 ◽  
Vol 12 (3) ◽  
pp. 303-317 ◽  
Author(s):  
M. Muzzammil ◽  
M. Ayyub
Keyword(s):  
Fuzzy Inference ◽  
Bridge Piers ◽  
Scour Depth ◽  
Fuzzy Inference Systems ◽  
Foundation Design ◽  
Pier Scour ◽  
Depth Prediction ◽  
Alternative Approach ◽  
Inference Systems ◽  
Bridge Pier Scour

An estimation of scour depth is a prerequisite for the efficient foundation design of important hydraulic structures such as bridge piers and abutments. Most of the scour depth prediction formulae available in the literature have been developed based on the analysis of the laboratory/field data using statistical methods such as the regression method (RM). Conventional statistical analysis is generally replaced in many fields of engineering by the alternative approach of artificial neural networks (ANN) and adaptive network-based fuzzy inference systems (ANFIS). These recent techniques have been reported to provide better solutions in cases where the available data is incomplete or ambiguous by nature. An attempt has been made to compare the performance of ANFIS over RM and ANN in modeling the depth of bridge pier scour in non-uniform sediments. It has been found that the ANFIS performed best amongst all these methods.

scholarly journals THE ROLE OF MELATONIN DEFICIENCY IN THE GENESIS OF ARTERIAL HYPERTENSION IN PATIENTS WITH CHRONIC KIDNEY DISEASE

2020 ◽  
Vol 115 (1) ◽  
pp. 18-26
Author(s):  
Anna Petrova ◽  
Olena Karpenko
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Hemodialysis Patients ◽  
Laboratory Studies ◽  
Healthy Individuals ◽  
Age Dependent ◽  
Salivary Melatonin ◽  
The Relationship

The study analyzed the prevalence of hypertension and impaired melatonin-forming function of the epiphysis in patients with stage 5 chronic kidney disease treated with hemodialysis. The relationship between epiphysis dysfunction and hypertension has been identified. 130 persons (50% of men) undergoing permanent hemodialysis treatment were examined. Controls were 20 healthy individuals. The determination of daytime and nighttime levels of melatonin in saliva and clinical and laboratory studies. As a result of the study it was found that for patients with stage 5 chronic kidney disease undergoing treatment, there is a frequent violation of melatonin-forming function of the pineal gland (84.6%) and hypertension (78%). In hemodialysis patients, blood pressure increases are age-dependent and are determined with salivary melatonin levels.

Determining Safe Levels of Mycotoxins

1984 ◽  
Vol 47 (7) ◽  
pp. 570-575 ◽  
Author(s):  
PAT B. HAMILTON
Keyword(s):  
Data Base ◽  
Field Data ◽  
Laboratory Data ◽  
Epidemiological Studies ◽  
Animal Experimentation ◽  
Laboratory Studies ◽  
Safe Level ◽  
Subjective Evaluations ◽  
Increasing Risk

The establishing of safe levels of mycotoxins to date has been a legal rather than scientific exercise. This has resulted in levels which have varied in response to economic and political pressures. The data base for rationally determining safe levels is very small. This has resulted in subjective evaluations of the worth of different studies in attempts to deduce safe levels from experiments designed to demonstrate effects, and in assumed safe levels which vary from field experiences. Using physiological parameters other than growth as criteria of safety, known deleterious interactions of mycotoxins with other factors, and statistical corrections for inadequate numbers of animals tested, permit better agreement between safe levels determined from laboratory data and from field data. However, the number of animals required makes impractical the laboratory determination of truly safe levels. Well-conceived and executed epidemiological studies coupled with laboratory studies designed to elaborate underlying principles appear to be the best approach to determining safe levels of mycotoxins. Until safe levels are based on sound animal experimentation, the prudent person would assume there is no truly safe level and that increasing levels of mycotoxins carry increasing risk.

scholarly journals Prediction of scour depth around bridge piers using self-adaptive extreme learning machine

2016 ◽  
Vol 19 (2) ◽  
pp. 207-224 ◽  
Author(s):  
Isa Ebtehaj ◽  
Ahmed M. A. Sattar ◽  
Hossein Bonakdari ◽  
Amir Hossein Zaji
Keyword(s):  
Extreme Learning Machine ◽  
Prediction Models ◽  
Differential Evolution Algorithm ◽  
Bridge Piers ◽  
Support Vector ◽  
Scour Depth ◽  
Pier Scour ◽  
New Model ◽  
Learning Machine ◽  
Self Adaptive

Accurate prediction of pier scour can lead to economic design of bridge piers and prevent catastrophic incidents. This paper presents the application of self-adaptive evolutionary extreme learning machine (SAELM) to develop a new model for the prediction of local scour around bridge piers using 476 field pier scour measurements with four shapes of piers: sharp, round, cylindrical, and square. The model network parameters are optimized using the differential evolution algorithm. The best SAELM model calculates the scour depth as a function of pier dimensions and the sediment mean diameter. The developed SAELM model had the lowest error indicators when compared to regression-based prediction models for root mean square error (RMSE) (0.15, 0.65, respectively) and mean absolute relative error (MARE) (0.50, 2.0, respectively). The SAELM model was found to perform better than artificial neural networks or support vector machines on the same dataset. Parametric analysis showed that the new model predictions are influenced by pier dimensions and bed-sediment size and produce similar trends of variations of scour-hole depth as reported in literature and previous experimental measurements. The prediction uncertainty of the developed SAELM model is quantified and compared with existing regression-based models and found to be the least, ±0.03 compared with ±0.10 for other models.

scholarly journals Prediction of maximum scour depth around piers with debris accumulation using EPR, MT, and GEP models

2016 ◽  
Vol 18 (5) ◽  
pp. 867-884 ◽  
Author(s):  
Mohammad Najafzadeh ◽  
Mohammad Rezaie Balf ◽  
Esmat Rashedi
Keyword(s):  
Polynomial Regression ◽  
Gene Expression Programming ◽  
Laboratory Data ◽  
Experimental Studies ◽  
Local Scour ◽  
Bridge Piers ◽  
Scour Depth ◽  
Effective Parameters ◽  
Pier Scour ◽  
Debris Accumulation

Pier scour phenomena in the presence of debris accumulation have attracted the attention of engineers to present a precise prediction of the local scour depth. Most experimental studies of pier scour depth with debris accumulation have been performed to find an accurate formula to predict the local scour depth. However, an empirical equation with appropriate capacity of validation is not available to evaluate the local scour depth. In this way, gene-expression programming (GEP), evolutionary polynomial regression (EPR), and model tree (MT) based formulations are used to develop to predict the scour depth around bridge piers with debris effects. Laboratory data sets utilized to perform models are collected from different literature. Effective parameters on the local scour depth include geometric characterizations of bridge piers and debris, physical properties of bed sediment, and approaching flow characteristics. The efficiency of the training stages for the GEP, MT, and EPR models are investigated. Performances of the testing results for these models are compared with the traditional approaches based on regression methods. The uncertainty prediction of the MT was quantified and compared with those of existing models. Also, sensitivity analysis was performed to assign effective parameters on the scour depth prediction.

scholarly journals Prediction of local scour depth at bridge piers under clear-water and live-bed conditions: comparison of literature formulae and artificial neural networks

2011 ◽  
Vol 13 (4) ◽  
pp. 812-824 ◽  
Author(s):  
E. Toth ◽  
L. Brandimarte
Keyword(s):  
Neural Networks ◽  
Sediment Transport ◽  
Field Data ◽  
Local Scour ◽  
Bridge Piers ◽  
Validation Dataset ◽  
Scour Depth ◽  
Clear Water ◽  
Transport Mode ◽  
Artificial Neural

The scouring effect of the flowing water around bridge piers may undermine the stability of the structure, leading to extremely high direct and indirect costs and, in extreme cases, the loss of human lives. The use of Artificial Neural Network (ANN) models has been recently proposed in the literature for estimating the maximum scour depth around bridge piers: this study aims at further investigating the potentiality of the ANN approach and, in particular, at analysing the influence of the experimental setting (laboratory or field data) and of the sediment transport mode (clear water or live bed) on the prediction performances. A large database of both field and laboratory observations has been collected from the literature for predicting the maximum local scour depth as a function of a parsimonious set of variables characterizing the flow, the sediments and the pier. Neural networks with an increasing degree of specialization have been implemented – using different subsets of the calibration data in the training phase – and validated over an external validation dataset. The results confirm that the ANN scour depths' predictions outperform the estimates obtained by empirical formulae conventionally used in the literature and in the current engineering practice, and demonstrate the importance of taking into account the differences in the type of available data – laboratory or field data – and the sediment transport mode – clear water or live bed conditions.

scholarly journals Prediction of Bridge Pier Scour Depth and Field Scour Depth Monitoring

2018 ◽  
Vol 40 ◽  
pp. 03007
Author(s):  
Fong-Zuo Lee ◽  
Jihn-Sung Lai ◽  
Yuan-Bin Lin ◽  
Kuo-Chun Chang ◽  
Xiaoqin Liu ◽  
...  
Keyword(s):  
Numerical Model ◽  
Real Time ◽  
Earthquake Engineering ◽  
Model Simulation ◽  
Bridge Pier ◽  
Bridge Piers ◽  
Scour Depth ◽  
Pier Scour ◽  
River Bed ◽  
Bridge Pier Scour

In practice, it is a major challenge in real-time simulation and prediction of bridge pier scour depth, especially using 3-D numerical model. The simulation time spend too much to use 3-D numerical model simulation and inefficiently to predict bridge pier scour depth in real-time. With heavy rainfall during flood season in Taiwan, abundant sediment with flash flood from upstream watershed is transported to downstream river reaches and transportation time is limited within one day. The flood flow tends to damage bridge structures and affect channel stabilization in fluvial rivers. In addition, the main factors affecting the erosional depth around bridge piers and river bed stabilization are hydrological and hydrographic characteristics in river basin, the scouring and silting of river bed section near the bridge piers, the bridge geometry and protection works of bridge piers. Therefore, based on the observed rainfall data provided by the Central Weather Bureau and the hydrological conditions provided by the Water Resources Agency during flood event as the boundary condition, we develop an effective simulation system for scour depth of bridge piers. The scour depth at the bridge pier is observed by the National Center for Research on Earthquake Engineering for model calibration. In this study, an innovative scour monitoring system using vibration-based Micro-Electro Mechanical Systems (MEMS) sensors was applied. This vibration-based MEMS sensor was packaged inside a stainless sphere with the proper protection of the full-filled resin, which can measure free vibration signals to detect scouring/deposition processes at the bridge pier. It has demonstrated that the measurement system for monitoring bridge scour depth evolution is quite successful in the field.

Role of laboratory studies in diagnostics of rare diseases. «Hair cellular leukemia»

2021 ◽  
pp. 66-69
Author(s):  
Tatyana Vladimirovna Krugova
Keyword(s):  
Laboratory Data ◽  
Laboratory Research ◽  
Laboratory Studies ◽  
Medical Decisions ◽  
High Quality ◽  
High Quality Medical Care ◽  
Choice Of Therapy ◽  
Quality Medical Care

Automation of laboratory production, formalization of processes and a phased quality control system ensure sufficient reliability of laboratory data, which is of great importance for the provision of high-quality medical care. For many people, laboratory research remains the invisible side of medicine. Nevertheless, 60–70 % of all medical decisions are made based on the results of clinical and laboratory studies, from the diagnosis to the choice of therapy and the determination of the prognosis.

Sign in / Sign up

Export Citation Format

Share Document