What Tools Are Available to Help Maintain a Code Compliant MAOP for a Highly Complex and Changing Gas Pipeline System?

2008 ◽  
Author(s):  
Larry C. Decker
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Continuous System ◽  
Geographic Information ◽  
Gas Pipeline ◽  
Data Driven ◽  
Pipeline System ◽  
Operating Pressure ◽  
Gis Data ◽  
Diverse Groups

Companies that operate large and complex gas pipeline systems face the difficult task of maintaining those assets while complying with code and continuing to operate. Continuous system additions and changes, implemented by diverse groups across the company, result in tedious data driven studies to ensure that operating pressure strictly complies with code. This document presents a model and an approach that utilizes Geographic Information Systems (GIS) data to accurately and efficiently calculate a code-compliant Maximum Allowable Operating Pressure (MAOP), for systems that have thousands of miles of wide-ranging pipe segments and components.

Geographic Information Systems (GIS) in International Relations

2016 ◽  
Vol 70 (4) ◽  
pp. 845-869 ◽  
Author(s):  
Jordan Branch
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
International Relations ◽  
Selection Bias ◽  
Geographic Information ◽  
Data Sets ◽  
Gis Data ◽  
Technical Details ◽  
Default Data ◽  
Do So

AbstractGeographic Information Systems (GIS) are being applied with increasing frequency, and with increasing sophistication, in international relations and in political science more generally. Their benefits have been impressive: analyses that simply would not have been possible without GIS are now being completed, and the spatial component of international politics—long considered central but rarely incorporated analytically—has been given new emphasis. However, new methods face new challenges, and to apply GIS successfully, two specific issues need to be addressed: measurement validity and selection bias. Both relate to the challenge of conceptualizing nonspatial phenomena with the spatial tools of GIS. Significant measurement error can occur when the concepts that are coded as spatial variables are not, in fact, validly measured by the default data structure of GIS, and selection bias can arise when GIS systematically excludes certain types of units. Because these potential problems are hidden by the technical details of the method, GIS data sets and analyses can sometimes appear to overcome these challenges when, in fact, they fail to do so. Once these issues come to light, however, potential solutions become apparent—including some in existing applications in international relations and in other fields.

Nonpoint Source (NPS) Pollution Modeling Using Models Integrated with Geographic Information Systems (GIS)

1993 ◽  
Vol 28 (3-5) ◽  
pp. 685-690 ◽  
Author(s):  
B. A. Engel ◽  
R. Srinivasan ◽  
J. Arnold ◽  
C. Rewerts ◽  
S. J. Brown
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Geographic Information ◽  
Nonpoint Source ◽  
Rainfall Events ◽  
Watershed Response ◽  
Nps Pollution ◽  
Gis Data ◽  
Pollution Modeling ◽  
Sediment Data

Models play an important role in the estimation of nonpoint source (NPS) pollution severity and in the identification of NPS problem areas. The use of these models has been severely limited because of the data and expertise required to operate these models. The integration of NPS pollution models with geographic information systems (GIS) can likely overcome these problems. Three NPS pollution models that were integrated with a GIS were used to simulate a watershed response to a series of rainfall events. The simulated responses were compared with observed runoff and sediment data. The simulated results matched the observed results reasonably well considering model inputs were estimated from base GIS data.

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