Latest Contributions by TomDeWitte

Part 1 of 5 By Tom DeWitte and Tom Coolidge Utilities collect a lot of data. This means utility field staff are spending a lot of time filling out forms.  Many companies today are undertaking efforts to convert paper forms to digital forms.  The basic justification for this effort is to eliminate the duplicate data entry of having an office person read, interpret, and recreate in the corporate enterprise systems what is captured in the field. But what about the field staff themselves, where is their benefit of digital transformation?  This blog series is about how to improve the productivity of field staff - how to automate data entry, leverage mobile device sensors, utilize intelligent software, and truly reduce the amount of time field staff spend filling out forms. Making life easier for field staff Have you ever met a utility field worker who walks into the office in the morning and says “Boy, I can’t wait to fill out forms today?” No, well me either. What is common to hear field workers complain about is spending too much time completing paperwork. The data utility field staff collect is vital to the successful operation and engineering of the utility system. Asking the field staff to stop collecting data is not an option.  But what about creating forms that auto-populate themselves to the maximum extent possible?  Stop typing The first step in making life easier for the utility field worker is to deploy solutions which minimize the amount of manual data entry they must perform. Today’s mobile devices and applications provide a wide range of capabilities to capture a large amount of information with minimal effort by the utility field worker. An example of this is barcodes.  The natural gas industry uses the ASTM F2897 barcode standard for its plastic pipe, fittings, and devices. A field worker equipped with a mobile application on a smart phone or tablet can use the device’s   camera to capture the barcode. This automatically inserts the barcode into the form. Then the mobile application can decode the information embedded in the barcode and auto-populate the appropriate form fields. If you are keeping score that is 8 form fields auto-populated and zero manual data entered for the utility field worker.  Barcodes can also be used on a worker's badge. Use the mobile device camera to read the badge and auto-populate the worker’s information into the form.  Take this idea a step further and have the mobile application compare the scanned worker ID against a table of operator qualifications to instantly verify that the worker has the current valid qualifications for performing the work, such as a weld or a plastic fusion. All of these intense data documentation and validation steps can be performed with no manual data entry.   Auto-populate what is already known The second step in making life easier for the utility field worker is to stop asking them to enter information the organization already knows. An example of this is project data.  Before a utility field worker drives up to a construction site, the project information is already well known within the utility planning, engineering, and permitting departments. A common utility practice is to create a project polygon to define the extent of the construction area. When using a geography-based mobile application this project polygon can be referenced to automatically insert project information into the form by having the field utility worker simply be within the extent of the project area. Another example is asset condition inspections, such as a valve inspection.  It is very common for a valve inspection form to ask for information about the valve. What size is it? Who was the manufacturer? What type of valve? The organization should already know the answer to these questions. The utility field worker simply needs to verify that the organization information is correct.  In this example the geography-based mobile application enables the utility field worker to simply click on the valve on the map to initiate the valve inspection. By selecting the valve from the map, the form automatically retrieves the information from the valve record and auto-populates the valve information portion of the form. All the field worker must do is review the information to verify it is correct. Asset Catalogs Another method for auto-populating what the organization already knows are lookup tables. When documenting new construction, these lookup tables are called Asset Catalogs.  An Asset Catalog record contains the manufacturer specifications for an asset. For example, when installing a steel pipe, the organization already knows the nominal diameter, wall thickness, outside diameter, material, manufacturer, manufacture type, specified minimum yield strength (SMYS), and pipe coating type to name a few of the known characteristics.   When a mobile application can leverage a lookup table, the utility field worker experience is very straightforward.  Select the installed type of steel pipe from a picklist. The mobile application then uses the selected item to query the asset catalog table. The selected asset catalog table is read, and the information is used to auto-populate the new steel pipe record. Review the now populated asset information to verify it is correct. The mobile user has populated multiple data fields by only manually selecting a single value from a picklist. Once again, no typing is required. The mobile sensor array The third step for making life easier for the mobile field worker is to leverage the many sensors of your mobile device. Most phones and tablets available today come with a built-in GPS chip. When you have a geography-based mobile application which can leverage that GPS, it can do much more than simply place a dot on the map to show you your location.  The geography-based mobile application can auto-populate your form location descriptors such as address, city, state, zip code, and utility division. Area based descriptors of location such as utility division, city, state, and zip code can be determined by having the software automatically perform a point on polygon overlay using the GPS location as the point location. Some geography-based applications can also use the GPS location to perform a reverse geocode operation to determine the address. In both examples, the software automatically populates this information when the field worker taps on the screen to capture the GPS location. No other user input is required. Use geography to automate The fourth and final step for making life easier for the mobile field worker is to leverage geography. There are many examples in utility field data collection where multiple assets or locationally unique items need to be grouped together. A pressurized pipe system example is pressure test documentation. After construction of the pipe system, that new or modified section of pipe must be pressure tested to verify it will not leak. This documentation step requires that all assets which were part of the pressure test be grouped together and assigned a common Pressure Test ID. This can be a very time-consuming documentation step as a single pressure test can include dozens of individual assets. With a geography based mobile application the utility mobile worker can draw a polygon to encompass the assets which were pressure tested. The geography-aware mobile application automatically uses the utility field worker defined polygon to select all pipe segments, fittings, and devices within the polygon. Each selected asset is assigned the pressure test ID. Improve data quality and completeness These examples of how to make life easier for utility mobile workers also have a benefit for the office staff. This auto-population provides a more complete record of the asset. Pipe asset values such as wall thickness and SMYS are often not considered values which are required to be entered by the field worker. Human nature is that anything not required likely will not be populated. Yet, these values are critical to engineers determining the range of safe operation of the pipe network. Conclusion Digitally transforming utility field data collection needs to be more than creating a digital form to improve the productivity of the field staff.  It needs to automate data entry. These forms need to leverage mobile device sensors, utilize geography-aware mobile applications, and truly reduce the amount of time field staff spend filling out forms. About This Blog Series This blog article is the first in a series of five blog articles. Upcoming blogs will explain in greater detail how to configure the Esri ArcGIS Field Maps mobile application to deploy these examples. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions.   ... View more

ArcGIS for District Energy: Tracing Thermal Energy By Tom DeWitte and Tom Coolidge The purpose of a district energy system is to transport thermal energy to customers (district heating) or to transport thermal energy away from customers (district cooling). It sounds simple, yet the looped nature of district energy pipe networks makes them some of the most complicated utility pipe networks. Modeling flow through this complicated network of energy plants, pipes, pumps, valves, and eventually buildings is not easy. Yet, it is vital to planners, engineers, and operators of the pipe network to understand how their product moves to and from their customers. This gets even more complicated if the district energy organization utilizes circulation zones with heat exchangers. In that system configuration, the water flow is not the same as the thermal energy flow. This requires an application and data model smart enough to differentiate between water flow and thermal energy flow. This is where ArcGIS with its ArcGIS Utility Network capability and District Energy Data Model can help.  Thermal Energy and District Heating When modeling a district heating pipe network, it is vital to understand where the energy starts and where it goes. For district heating, the start is typically the energy plant. From the energy plant the heated water or steam transports the thermal energy through pipes, pumps, heat exchangers, valves, more pipes and eventually it to a building. The customer in that building consumes the thermal energy to heat their home. In a full loop system, the now cooled water returns to the energy plant to be reheated. Thermal Energy and District Cooling When modeling a district cooling pipe network, the thermal energy starts with the customer and is delivered to the cooling plant where it is typically released into the air. In a full loop system, after the thermal energy is released to the air, it is sent to chiller units to further remove thermal energy. This results in an additional decrease to the water temperature. Once cooled it is transported through pipes, pumps, heat exchangers, valves, and more pipes before it reaches the customer's building. At the building the chilled water absorbs the customer’s waste heat and transports it back to the cooling plant. Leveraging Utility Network Modeling this real-world transportation of thermal energy through a pipe network, requires more than an understanding of how the pipes, pumps, heat exchangers, valves and other components are connected. It requires the ability to understand which pumps are operating, and which valves are closed. It also needs to differentiate between cathodic protection wires and leak detection wires. These wires are connected to the pipes but do not transmit thermal energy. To accurately represent these additional real-world complexities, we need a more advanced connectivity model. We need to leverage the Utility Network. The Utility Network is an extension to ArcGIS. ArcGIS is the geographic information system (GIS) provided by Esri. What Stops Thermal Energy Flow With a Utility Network comes the Trace geoprocessing tool. A configuration of this tool is what will be used to perform the thermal energy flow trace. To correctly configure the thermal energy flow trace requires a real-world understanding of what can stop the thermal energy flow. In the real-world devices which are closed, such as a valve, or are not operating, such as a pump, will impede the flow of the thermal energy. Add to this list any pipe segment or device which is not in service, such as retired pipe segments or pipe segments which are proposed but have not yet been built. Lastly, there is the need to exclude the cathodic protection wires and leak detection wires which are part of the pipe network but do not conduct thermal energy flow. When using the District Energy Utility Network Foundation data model, those constraints look like this: Pipe segment or asset is not in service: Lifecycle Status Does not equal In Service Valve is closed: Device Status is equal to closed Pump is not operating: Device Status is equal to closed Cathodic Protection wires: Category is equal to CP Only Leak detection wires: Category is equal to Leak Detection Only Configuring the Trace Tool The Trace geoprocessing tool in ArcGIS Pro has many parameters. Here is how to transpose the constraints into the specific settings in the Trace tool. The type of trace will be a downstream trace, leveraging the DHC domain network, and the DHC Energy Tier. Setting the Tier to “DHC Energy Tier” is important as it sets the flow source as the energy plant/chiller plant, versus the “DHC Pressure” tier which would set the source as in-system pumps. The constraints will be added as Traversability Barriers. If any one constraint is true, the trace will not traverse beyond the asset. When this trace is run, it will return all pipe segments, devices, fittings, and customer service points which are receiving thermal energy from the designated start location. This includes both the supply and return portions of the pipe network. If you are a district heating organization and only interested in the thermal energy flow supplying energy to the customer, you can add a filter barrier: Pipe segments are only supply lines: Line Asset Type does not equal supply This will return a selection set of the pipe network which shows how the thermal energy traverses the pipe network from the designated location to the customer. The same configuration will work on the district cooling pipe network. Sharing the Trace Now that you know how to configure the trace tool to perform a thermal energy flow trace, how do you share this with others in your organization. And, how do you share it in a way that does not require everyone to manually perform this configuration of the Trace Tool. This is where the new functionality introduced at ArcGIS 10.9, called Trace Configurations is useful. Trace Configurations is the ability to store a configuration of the Trace Tool within the Geodatabase. When the Thermal Energy Flow trace is stored in the Geodatabase, other desktop, web, and mobile users do not need to know how to configure the tool. A simple check of the “Use Trace Configuration” option removes all the configuration options and replaces it with a simple pulldown menu for the end user to select from. Having the trace configuration centrally stored and accessible to end users ensures that everyone is running a properly configured thermal energy flow trace. Summary Planners, engineers, and operators require this type of advanced flow modeling to help them perform their daily activities. Thermal energy flow modeling is just one of the many types of water, thermal, cathodic protection, leak detection flow analysis which can be configured with the ArcGIS Utility Network.  These trace capabilities help to remove some of the complexity of maintaining and operating a district energy pipe system. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

Thru 2021 the Esri Gas team worked with multiple natural gas organizations to help them deploy ArcGIS Field Maps to construction crews. This effort builds on the Tracking and Traceability capabilities such as GPS, Laser Range Finder, and barcode scanner integration accomplished prior to 2021. The 2021 effort resulted in many enhancements to automating the construction documentation process. A few of these enhancements include: Realtime decoding of the barcode Compatible unit table lookup for non-barcoded plastic and steel assets Automatic assignment of Construction Project ID to collected assets Automatic assignment of PressureTestID to all tested assets This video demonstrates how a configuration of ArcGIS Field Maps can be used to address the mobile as-builting needs of gas organizations. ... View more

By Tom DeWitte and Tom Coolidge Last month, Esri released an updated version of the District Energy Data Model. This release continues Esri’s practice of maintaining a template data model ready “out-of-the-box” to manage district cooling, district heating, and steam data within an Esri geodatabase. Why District Energy Data Model The goal of the Esri District Energy Data Model is to make it easier, quicker, and more cost-effective for district heating, district cooling, and steam utilities to implement the ArcGIS platform. Esri accomplishes this by freely providing a data model that takes full advantage of the capabilities of the geodatabase. The data model is created and tested with ArcGIS products to ensure that it works. This significantly reduces the complexity, time, and cost to implement a spatially enabled district energy data repository. District Energy Enterprise Data Management For many district energy utility enterprises, deploying the ArcGIS platform that leverages the concepts of a service-oriented web gis is more than loading the district energy data model into an enterprise geodatabase. It requires additional steps such as creating an ArcGIS Pro map configured for publishing the data model and publishing of the Pro map to create the required map and feature services. To help simplify these additional steps performed with the industry data model, Esri has embedded the data model into a new ArcGIS for district energy solution.  The new solution is called District Energy Utility Network Foundation. This solution provides the data model, sample data, and an ArcGIS Pro project configured with tasks and performance optimized maps. You can access this solution from the Esri ArcGIS for District Energy solution site. A data dictionary for this data model is available online. Best Practice Use of ArcGIS This updated version of the District Energy data model is configured to take advantage of the latest capabilities provided by the ArcGIS technology. This includes recent enhancements such as contingent values, attribute rules, and the utility network. In this data model you will find contingent value configurations to restrict the valid types of pipe insulation and pipe material based on whether the pipe transits steam, condensate, heated water, or chilled water. Included are many attribute rules to automate attribute population as well as provide data quality checks. This data model includes utility network subnetwork configurations for defining pressure zones, circulation areas, leak detection zones, cathodic protection zones, and energy zones. And let’s not forget the thousands of connectivity, containment, and association rules of the utility network. Embeds Industry Business Rules Business rules are a great way to share industry knowledge. Sometimes it is simple, such as ensuring that the maximum operating temperature is greater than the standard operating temperature, or that the in-service date occurred after the date of installation. Others are more complicated, such as knowing when to create a containment association between two assets.  Thanks to the combined knowledge of many persons across the industry, these business rule examples and many more are included with this data model. Modeling Flow thru your Pipe Network District energy systems often have a dual set of pipes in a single trench. One flows from the energy facility to the customer, the other flows from the customer back to the energy facility. This makes modeling flow through a district energy pipe system unique among the pipe utilities. This data model supports the dynamic tracing of water flow, heat flow, cathodic electric flow, and leak detection circuits across the dual pipe network. A Foundation to Build Upon The official name of this first district energy solution is District Energy Utility Network Foundation. The name was intentional as this spatially-enabled data management solution is the foundation from which many more district energy solutions can be added. With this foundation, district energy organizations can provide analytics, visualization, and data collection solution to their users. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

Utility and Pipeline Data Model 2021 is Released By Tom DeWitte and Tom Coolidge Esri’s Utility and Pipeline Data Model (UPDM) 2021 is available now. This release continues Esri’s practice of maintaining a template data model ready “out-of-the-box” to manage natural gas and hazardous liquid pipe system data within an Esri geodatabase. This release includes enhancements to keep up with changes in industry practice, regulatory requirements, and previous implementation feedback. Gas and Pipeline Enterprise Data Management For many gas utility and pipeline enterprises, deploying the ArcGIS platform is more than simply loading the UPDM 2021 data model into an enterprise geodatabase. That’s because ArcGIS leverages the concepts of a service-oriented web GIS. It requires additional steps, such as creating an ArcGIS Pro map configured for publishing the data model, publishing of the Pro map to create the required map and feature services and, perhaps, configuring a location referencing system. To help simplify these additional steps performed with UPDM 2021, Esri has embedded UPDM 2021 into a newly renamed ArcGIS for Gas solution. The new solution is called Gas and Pipeline Referencing Utility Network Foundation. This solution provides UPDM 2021, sample data, and an ArcGIS Pro project configured with tasks and performance optimized maps. You can access this solution from the Esri ArcGIS for Gas solution site. A full data dictionary of UPDM 2021 is available online. A change log documenting the full list of changes incorporated into UPDM 2021 is also available online. Enhancements for Managing Cathodic Protection Interest in leveraging ArcGIS to manage Cathodic Protection (CP) data has grown significantly over the last few years. Recent implementations have shown an interest in modeling a more detailed representation of CP systems. With UPDM 2021, our industry data model now includes models for managing the following CP assets: Linear Anode AC Mitigation Wire Decoupler Grounding Point Cathodic Assembly Grounding Mat Feedback from Pipeline Implementations Pipeline implementations of UPDM have been many and varied. These previous implementations have resulted in feedback that has resulted in dozens of adjustments to improve how we model pipeline assets. Two specific enhancements based on previous implementations to highlight are the defining of the attributes “odorized” and “piggable” as Utility Network Network Attributes. Having “odorized” and “piggable” as Network Attributes provides additional capabilities for leveraging tracing. Tracing is the ability to understand how the components of a pipe system are connected, and how the gas and hazardous liquids flow through the pipe system. With this new template configuration, pipeline operators can trace across their pipe system and see where the “piggable” portion stops when it reaches an asset which is tagged as not piggable. Similarly, planners and engineers can trace to see what portion of their pipe system is “odorized.”                    Feedback from Gas Utility Implementations Previous implementations of UPDM in Gas Utilities have also resulted in feedback to help fine-tune the gas and pipeline industry data model. Some of these adjustments include improved modeling of relief valves, flanges, and taps to name a few. Other enhancements include adjustments to the Utility Network rulebase. What is UPDM UPDM is a geodatabase data model template for operators of pipe networks in the gas and hazardous liquids industries. UPDM is a moderately normalized data model that explicitly represents each physical component of a gas pipe network from the wellhead to the customer meter, or a hazardous liquids pipe network from the wellhead to the terminal or delivery point, in a single database table object.     UPDM is the only industry model which can manage a single representation of the entire pipe system.  For many companies around the world this single data repository aligns well with enterprise practices to vertically integrate business processes and operations.  Why UPDM The goal of the Esri UPDM is to make it easier, quicker, and more cost-effective for pipeline operators and gas utilities to implement the ArcGIS platform. The Esri UPDM accomplishes this by freely providing a data model that takes full advantage of the capabilities of the geodatabase. The data model is created and tested with ArcGIS products to ensure that it works. This significantly reduces the complexity, time, and cost to implement a spatially enabled hazardous liquid or gas pipe system data repository. Looking Forward to UPDM 2022 A wise man once said “change is the only constant.” This is a great quote when thinking about UPDM going forward. The Esri development team will continue to enhance the capabilities of ArcGIS. Industry will continue to evolve its practices. To continue adjusting to industry practices and incorporating new ArcGIS capabilities, UPDM will continue to evolve.  This evolution will help assure gas utilities and pipeline operators that their GIS industry-specific data model is current with their needs. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions.       ... View more

  By Tom DeWitte and Tom Coolidge The natural gas industry’s drive to a lower or net zero carbon footprint is focused on actions that generally can be organized in three groups: (1) reducing methane emissions from operations, (2) reducing methane emissions from customer consumption, and (3) embracing new sources and uses of alternative lower carbon fuels. This blog focuses on a key activity central to reducing methane emissions from operations – finding and fixing leaks. Managing methane emissions is without a doubt as critical a set of tasks as any every natural gas pipe organization performs.  For the owners and operators of the pipe networks which transport this critical energy source, managing methane emissions starts with surveillance programs to identify leaks. Class 1 leaks are immediately fixed. But low-level leaks are studied via engineering analysis to rank the risk and consequence of those leaks. Once analyzed, construction activities can be scheduled to repair the identified and qualified leaks. This very straightforward set of tasks to “find the leak” and to “fix the leak” have been going on for decades. So, what’s new in the world of methane emission reduction? What’s new for methane emission reduction is the availability of new sensor platforms to “find the leak”. Many Platforms for Detecting Methane Finding the leak has long been a human-intensive process of walking the pipe network. While walking, field technicians will carry methane emission detectors. Once a leak is found, a gas leak report is created to document the location, quantity, and likely source of the leak. Then came the ability to mount methane sensors on cars and trucks. These vehicles could cover more miles of pipe than the walkers. Advancements by manufacturers of these devices have further enhanced these vehicle- mounted sensors to better estimate the location of the source of the leak. These potential leaks are then investigated by field technicians to verify and complete the gas leak report.   More recently, methane emission sensors have been mounted on aerial platforms ranging from drones to helicopters to planes. In addition to aerial mounted sensors, there are now satellites circling our planet in low earth orbit with methane sensors. These satellite-based sensors sell their data and analytics, providing gas pipe operators with yet another capability to survey the pipe network and “find the leak”. Still Need Those Humans These newer tools to surveil the pipe network do not replace the regulatory requirements of Leak Survey. But they do provide a new affordable capability for higher frequency monitoring. Then when a methane emission is detected, a field technician can be sent out to the emission area to validate the sensor reading and fill out the gas leak report with the details needed for the organization to “fix the Leak”. As powerful as these additional methane detections are, humans are still required to verify and document every leak. Need a Common Repository Adding additional platforms of methane detection opens new opportunities to reduce methane emissions.  It also creates a new, but manageable, data management issue. With these new sensor platforms to identify potential methane emissions, a common data management system is needed to capture, track, and document the status of these potential leaks. With location being critical to each potential leak, A geographical information system (GIS) is the best data management system for aggregating and managing this information.   Critical Information for Gas Pipe System Management Combining the information from these many methane detection platforms into a single data management system is not the finish line.  It is at best mid span. This data still needs to flow into analytical programs such as DIMP and TIMP. This data still needs to be monitored with dashboards, summarized with reports, and communicated to gas executives, regulators, and the public. This data needs to flow to construction and mobile viewing devices enabling the gas organization to “fix the Leak”. That is the finish line. The natural gas industry is enjoying a technological revolution. New technologies are continuously being applied to better solve gas industry problems.  And the gas industry is embracing and implementing these new capabilities at a faster pace than ever before.  Placing your GIS at the center of your methane emission management ensures the data collected by all these new sensor platform technologies is fully leveraged throughout your gas organization. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

By Tom DeWitte and Tom Coolidge What keeps pipe network utility executives up at night? One common cause is the worry about the consequences of a failure that results in negative impacts to people, property, or the environment. One-way utilities pro-actively seek to pre-empt pipe network failures is investment in repairing or replacing those parts of their network thought most likely to possibly fail. Every year utilities determine which sections of their pipe system will be replaced as part of their capital construction budget. How do utilities know which sections of the pipe system need to be replaced? What are the criteria that should be used to identify and prioritize the sections of pipe for replacement? To many pipe engineers, the answer is to perform a pipe risk analysis. Pipe risk analysis is a method of identifying criteria which will be used to rank which sections of pipe should be replaced. These criteria are quantified and weighted against each other using an equation to tally the total risk score for each section of pipe. What criteria do you use to measure risk? When dealing with pressurized pipe systems, such as natural gas, hazardous liquids, district energy, and water the initial criteria list typically starts with these items:                 -pipe material                 -pipe age                 -pipe installation method                 -pipe insulation/coating materials                 -leak history These items are valid criteria that contribute to the likelihood a pipe system may fail. These types of data are easy to put into a spreadsheet and tabulate. But none of these measures the consequence of those failures and the risk to the organization. Understanding the risk to the organization can only be accomplished by including a measurement of the consequences. Understanding Risk to the Organization Risk to the organization is typically summarized as a cost, with the unit of measure being monetary ($). This cost is much more than simply the expense to the utility to have the construction group replace the identified deficient section of pipe.  When a pipe section fails, it impacts the people and facilities near the location of failure. This consequence cost to the organization often greatly exceeds the cost to replace.  The recent situation of Pacific Gas & Electric declaring bankruptcy after the involvement of its electric transmission lines in forest fires is the exclamation point example.  Every pipe utility industry has multiple examples they can point to which validate that the consequence cost of a failure greatly exceeds the cost to replace. Property damage, loss of life, loss of business revenue, civil lawsuits, and government regulatory fines are just of few of the consequences of failure and its resultant cost to the organization. To measure the risk to the organization, we need spatial tools     Quantifying the consequence of failure begins with understanding “where.”                 -Where are the properties and facilities nearby pipe segments?                 -Where are the persons who reside or congregate near the pipe segments?                 -Who are the customers downstream of the pipe segment who will be impacted by the failure? Understanding the relationship between your pipe sections in relation to critical facilities, persons, and customers, requires spatially aware-analysis tools. Spatially aware tools, such as those provided with Esri’s ArcGIS products, enable pipe utilities to identify, aggregate, calculate, and quantify these consequences. Understanding Who is Nearby Every person who resides or congregates near a pipe section is at risk of being impacted by the failure of that pipe section. As stated previously, this is key to quantifying the overall risk to the organization. Spatial analysis methods, such as buffer, can define the area near the pipe segment to look for persons and places of gathering. More advanced spatial analysis methods, such as least cost path analysis, enable pipe utilities to identify the direction in which spilled liquids will flow. Once these spatial areas near the pipe segment are identified, it is a simple intersect analysis against data sets which identify the number and type of persons who reside or congregate within the now identified areas of impact.  With this analysis capability, pipe utility organizations can quantify the consequence of the failure of a pipe segment to persons. Understanding What is Nearby The cost to the pipe organization of the failure of a pipe section includes not only the impacted persons, but also the impacted facilities. Having your own facilities damaged is bad enough, but also having to pay to repair the facilities of other utilities can be much more expensive. Understanding the consequence of failure to facilities goes beyond electric, telecommunications, and other pipe utilities, it includes transportation network systems such as road and railroad. No pipe utility wants to be the one that caused a major road route to be closed due to the damage caused by the pipe section failure. The same ArcGIS analysis tools used to identify persons impacted by a pipe section failure (Buffer, Least Cost Path, Intersect, Identity) are the tools used to identify and quantify what facilities are impacted.   This understanding of the consequence of failure to nearby facilities further clarifies the true risk to the organization. But there is still one more critical consequence to be understood and quantified.  That is the consequence to the pipe utilities customers who are downstream of the pipe section which has failed. Understanding Customers Downstream When a pipe section fails, customers downstream of that point of failure will be without the transported commodity until repairs are completed.  This means that natural gas and district heating customers could be without heating in the middle of a winter deep freeze. District cooling customers could be without air conditioning during a summer heat wave. Both consequences of failure can literally result in death to customers. Programmatically understanding and quantifying the impact to a pipe utility’s customers requires a different set of spatial analysis tools. These different spatially aware analysis tools need to understand how the pipe network of pipes, valves, and fittings connect to create a pipe network. Only when a software application understands how a commodity flows through the pipe network can the analysis quantify the consequence of failure to the customers. This pipe network aware tool which is critical to measuring the consequence of failure to customers is the downstream trace.  The downstream trace is a configuration of the Trace tool provided with ArcGIS Utility Network. With this type of spatially aware analysis, it is now possible to quantify how many critical facilities such as hospitals, senior living complexes, refineries, power generation plants, and major manufacturing facilities are impacted by the failure of a pipe section. It’s a Spatial Thing Understanding the total risk to a pipe organization requires spatial awareness.  This spatial awareness empowers pipe organizations to improve their capital improvement plans. Engineers leveraging spatially aware tools such as those provided with ArcGIS can quantify the multiplier impact consequences have on threats of failure. Knowing how your customers will be impacted by a pipe section failure is another type of spatial analysis that is also key to measuring risk to the organization. As you can see, pipe risk analysis is spatial. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions.     ... View more