scholarly journals Copula parameter estimation using Bayesian inference for pipe data analysis

2018 ◽  
Vol 45 (1) ◽  
pp. 61-70 ◽  
Author(s):  
Farzana Atique ◽  
Nii Attoh-Okine
Keyword(s):  
Data Analysis ◽  
Soil Condition ◽  
Condition Assessment ◽  
Pipe Material ◽  
Data Set ◽  
Copula Modeling ◽  
Structural Deterioration ◽  
Copula Parameter ◽  
Water Mains ◽  
Non Gaussian

Water main systems are aging and becoming a growing concern for maintenance. The structural deterioration of water mains is affected by different factors, such as pipe age, pipe material, soil condition, and pipe size, among others. Various methods of modeling have been used to predict the failure of water mains. Since pipe networks are underground and obtaining data on pipe conditions is very costly, statistical modeling has been widely used for pipe condition assessment. An emerging statistical method known as copula modeling is used here for pipe data analysis. The copula method is very useful in cases where marginals belong to different families of distributions. It is also useful for generating a large number of data points when it is difficult to obtain a data set, as is the case for pipe condition assessment, and where data sets have random variables belonging to non-Gaussian family distributions. Different copula families are applied here to model the dependency between the pipe age and repair age of pipes. The paper uses a Bayesian framework to estimate the parameter values in the copula model. This approach offers an additional option for estimating copula parameters for pipe data.

scholarly journals Planning renewal of water mains while considering deterioration, economies of scale and adjacent infrastructure

2010 ◽  
Vol 10 (6) ◽  
pp. 897-906 ◽  
Author(s):  
Yehuda Kleiner ◽  
Amir Nafi ◽  
Balvant Rajani
Keyword(s):  
Cathodic Protection ◽  
Economies Of Scale ◽  
Poisson Model ◽  
Pipe Material ◽  
Efficient Manner ◽  
Structural Deterioration ◽  
Dynamic Factors ◽  
Water Mains ◽  
Subsequent Failure

The structural deterioration of water mains and their subsequent failure are affected by many factors, both static (e.g., pipe material, pipe size, age (vintage), soil type) and dynamic (e.g., climate, cathodic protection, pressure zone changes). This paper describes a non-homogeneous Poisson model developed for the analysis and forecast of breakage patterns in individual water mains, while considering both static and dynamic factors. Subsequently, these forecasted breakage patterns are used to schedule the renewal of water mains in an economically efficient manner, while considering the various associated costs, including economies of scale and scheduled works on adjacent infrastructure. In this paper, he principles of the approach are described briefly and its application is demonstrated with the help of a case study.

scholarly journals I-WARP: Individual Water mAin Renewal Planner

2010 ◽  
Vol 3 (1) ◽  
pp. 71-77 ◽  
Author(s):  
Y. Kleiner ◽  
B. Rajani
Keyword(s):  
Research Council ◽  
National Research Council ◽  
Water Utilities ◽  
Pipe Material ◽  
Mathematical Approach ◽  
Structural Deterioration ◽  
Dynamic Factors ◽  
Water Mains ◽  
Subsequent Failure

Abstract. I-WARP is based upon a nonhomogeneous Poisson approach to model breakage rates in individual water mains. The structural deterioration of water mains and their subsequent failure are affected by many factors, both static (e.g., pipe material, pipe size, age (vintage), soil type) and dynamic (e.g., climate, cathodic protection, pressure zone changes). I-WARP allows for the consideration of both static and dynamic factors in the statistical analysis of historical breakage patterns. This paper describes the mathematical approach and demonstrates its application with the help of a case study. The research project within which I-WARP was developed, was jointly funded by the National Research Council of Canada (NRC), and the Water Research foundation (formerly known as the American Water Works Association Research Foundation – AwwaRF) and supported by water utilities from USA and Canada.

scholarly journals I-WARP: individual water main renewal planner

2010 ◽  
Vol 3 (1) ◽  
pp. 25-41 ◽  
Author(s):  
Y. Kleiner ◽  
B. Rajani
Keyword(s):  
Research Council ◽  
National Research Council ◽  
Water Utilities ◽  
Pipe Material ◽  
Mathematical Approach ◽  
Structural Deterioration ◽  
Dynamic Factors ◽  
Water Mains ◽  
Subsequent Failure

Abstract. I-WARP is based upon a nonhomogeneous Poisson approach to model breakage rates in individual water mains. The structural deterioration of water mains and their subsequent failure are affected by many factors, both static (e.g., pipe material, pipe size, age (vintage), soil type) and dynamic (e.g., climate, cathodic protection, pressure zone changes). I-WARP allows for the consideration of both static and dynamic factors in the statistical analysis of historical breakage patterns. This paper describes the mathematical approach and demonstrates its application with the help of a case study. The research project within which I-WARP was developed, was jointly funded by the National Research Council of Canada (NRC), and the Water Research foundation (formerly known as the American Water Works Association Research Foundation – AwwaRF) and supported by water utilities from USA and Canada.

scholarly journals CT Scans of Asbestos Cement Pipes as a Reference for Condition Assessment of Water Mains

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2391
Author(s):  
Karel van Laarhoven ◽  
Jip van Steen ◽  
Frank van der Hulst ◽  
Hector Hernandez Delgadillo
Keyword(s):  
Water Distribution ◽  
Poor Performance ◽  
Water Distribution Network ◽  
Condition Assessment ◽  
Water Utilities ◽  
Detailed Knowledge ◽  
Pipe Material ◽  
Detailed Measurement ◽  
Asbestos Cement ◽  
Water Mains

The water distribution network of The Netherlands contains around 30,000 km of asbestos cement (AC) pipes, which constitutes around 25% of the total network. As a pipe material, AC has a relatively poor performance, and therefore is a high priority for renewal. To help decide an effective order of replacement, the water utilities need condition assessment techniques that help them determine which pipes have the highest risk of failure. In the presented work, X-ray computed tomography (CT) was used to measure the degradation of AC pipes taken out of the field. These scans provide a description of the pipe degradation with unmatched detail. The results are compared with strength tests performed on the same pipes, revealing that detailed knowledge of the complete pipe degradation is more important than previously assumed. Moreover, comparison of the CT results to those of a commercial, non-destructive inspection technique was used as a new avenue for validation of this technique, demonstrating its future usefulness for attaining the detailed measurement of pipe degradation required by water utilities.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

SEMIPARAMETRIC CLUSTERING METHOD FOR MICROARRAY DATA ANALYSIS

2008 ◽  
Vol 06 (02) ◽  
pp. 261-282 ◽  
Author(s):  
AO YUAN ◽  
WENQING HE
Keyword(s):  
Data Analysis ◽  
Microarray Data ◽  
Mixture Distribution ◽  
Information Criterion ◽  
Optimal Number ◽  
Microarray Data Analysis ◽  
Parametric Methods ◽  
Clustering Methods ◽  
Microarray Gene Expression ◽  
Data Set

Clustering is a major tool for microarray gene expression data analysis. The existing clustering methods fall mainly into two categories: parametric and nonparametric. The parametric methods generally assume a mixture of parametric subdistributions. When the mixture distribution approximately fits the true data generating mechanism, the parametric methods perform well, but not so when there is nonnegligible deviation between them. On the other hand, the nonparametric methods, which usually do not make distributional assumptions, are robust but pay the price for efficiency loss. In an attempt to utilize the known mixture form to increase efficiency, and to free assumptions about the unknown subdistributions to enhance robustness, we propose a semiparametric method for clustering. The proposed approach possesses the form of parametric mixture, with no assumptions to the subdistributions. The subdistributions are estimated nonparametrically, with constraints just being imposed on the modes. An expectation-maximization (EM) algorithm along with a classification step is invoked to cluster the data, and a modified Bayesian information criterion (BIC) is employed to guide the determination of the optimal number of clusters. Simulation studies are conducted to assess the performance and the robustness of the proposed method. The results show that the proposed method yields reasonable partition of the data. As an illustration, the proposed method is applied to a real microarray data set to cluster genes.

Twitter users exhibited coping behaviours during the COVID-19 lockdown: an analysis of tweets using mixed methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruchi Mittal ◽  
Wasim Ahmed ◽  
Amit Mittal ◽  
Ishan Aggarwal
Keyword(s):  
Data Analysis ◽  
The Body ◽  
Data Set ◽  
Content Type ◽  
Twitter Data ◽  
Long Run ◽  
The World ◽  
Twitter Users ◽  
The Government ◽  
Using Data

Purpose Using data from Twitter, the purpose of this paper is to assess the coping behaviour and reactions of social media users in response to the initial days of the COVID-19-related lockdown in different parts of the world. Design/methodology/approach This study follows the quasi-inductive approach which allows the development of pre-categories from other theories before the sampling and coding processes begin, for use in those processes. Data was extracted using relevant keywords from Twitter, and a sample was drawn from the Twitter data set to ensure the data is more manageable from a qualitative research standpoint and that meaningful interpretations can be drawn from the data analysis results. The data analysis is discussed in two parts: extraction and classification of data from Twitter using automated sentiment analysis; and qualitative data analysis of a smaller Twitter data sample. Findings This study found that during the lockdown the majority of users on Twitter shared positive opinions towards the lockdown. The results also found that people are keeping themselves engaged and entertained. Governments around the world have also gained support from Twitter users. This is despite the hardships being faced by citizens. The authors also found a number of users expressing negative sentiments. The results also found that several users on Twitter were fence-sitters and their opinions and emotions could swing either way depending on how the pandemic progresses and what action is taken by governments around the world. Research limitations/implications The authors add to the body of literature that has examined Twitter discussions around H1N1 using in-depth qualitative methods and conspiracy theories around COVID-19. In the long run, the government can help citizens develop routines that help the community adapt to a new dangerous environment – this has very effectively been shown in the context of wildfires in the context of disaster management. In the context of this research, the dominance of the positive themes within tweets is promising for policymakers and governments around the world. However, sentiments may wish to be monitored going forward as large-spikes in negative sentiment may highlight lockdown-fatigue. Social implications The psychology of humans during a pandemic can have a profound impact on how COVID-19 shapes up, and this shall also include how people behave with other people and with the larger environment. Lockdowns are the opposite of what societies strive to achieve, i.e. socializing. Originality/value This study is based on original Twitter data collected during the initial days of the COVID-19-induced lockdown. The topic of “lockdowns” and the “COVID-19” pandemic have not been studied together thus far. This study is highly topical.

Integrated Production Data Analysis and Water Injection Optimization in A Giant Carbonate Field

2021 ◽  
Author(s):  
Adel Mehrabadi ◽  
Gabriele Urbani ◽  
Simona Renna ◽  
Lucia Rossi ◽  
Italo Luciani ◽  
...  
Keyword(s):  
Data Analysis ◽  
Water Injection ◽  
Water Flooding ◽  
Integrated Analysis ◽  
Production Data ◽  
Data Set ◽  
Proper Actions ◽  
Injection Scheme ◽  
Vertical Heterogeneity ◽  
Current Water

Abstract In case of giant brown fields, a proper water injection management can result in a very complex process, due to the quality and quantity of data to be analysed. Main issue is the understanding of the injected water preferential paths, especially in carbonate environment characterized by strong vertical and areal heterogeneities (karst). A structured workflow is presented to analyze and integrate a massive data set, in order to understand and optimize the water injection scheme. An extensive Production Data Analysis (PDA) has been performed, based on the integration of available geological data (including NMR and Cased Hole Logs), production (allocated rates, Well Tests, PLT), pressure (SBHP, RFT, MDT, ESP) and salinity data. The applied workflow led to build a Fluid Path Conceptual Model (FPCM), an easy but powerful tool to visualize the complex dynamic connections between injectors-producers and aquifer influence areas. Several diagnostic plots were performed to support and validate the main outcomes. On this basis, proper actions were implemented to optimize the current water injection scheme. The workflow was applied on a carbonate giant brown field characterized by three different reservoir members, hydraulically communicating at original conditions, characterized by high vertical heterogeneity and permeability contrast. Moreover, dissolution phenomena, localized in the uppermost reservoir section, led to important permeability enhancement through a wide network of connected vugs, acting as water preferential communication pathways. The geological analysis played a key role to investigate the reservoir water flooding mechanism in dynamic conditions. The water rising mechanism was identified to be driven by the high permeability contrast, hence characterized by lateral independent movements in the different reservoir members. The integrated analysis identified room for optimization of the current water injection strategy. In particular, key factor was the analysis and optimization at block scale, intended as areal and vertical sub-units, as identified by the PDA and visualized through the FPCM. Actions were suggested, including injection rates optimization and the definition of new injections points. A detailed surveillance plan was finally implemented to monitor the effects of the proposed actions on the field performances, proving the robustness of the methodology. Eni workflow for water injection analysis and optimization was previously successfully tested only in sandstone reservoirs. This paper shows the robustness of the methodology also in carbonate environment, where water encroachment is strongly driven by karst network. The result is a clear understanding of the main dynamics in the reservoir, which allows to better tune any action aimed to optimize water injection and increase the value of mature assets.

scholarly journals Inference for copula modeling of discrete data: a cautionary tale and some facts

2017 ◽  
Vol 5 (1) ◽  
pp. 121-132 ◽  
Author(s):  
Olivier P. Faugeras
Keyword(s):  
Model Misspecification ◽  
Discrete Data ◽  
Cautionary Tale ◽  
Copula Models ◽  
Problematic Use ◽  
Copula Modeling ◽  
Copula Parameter ◽  
Parametric Copula

AbstractIn this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula models. For the latter, we stress, among other issues, the possibility of obtaining impossible models, arising from model misspecification or unidentifiability of the copula parameter.

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