Alarm Forecasting in Natural Gas Pipelines

This thesis examines alarm forecasting methods for a natural gas production pipeline to assure the efficient transportation of high-quality natural gas. Natural gas production companies use pipelines to transport natural gas from the extraction well to a distribution point. Forecasting natural gas pipeline pressure alarms helps control room operators maintain a functioning pipeline and avoid costly down time. As gas enters the pipeline and travels to the distribution point, it is expected that the gas meets certain specifications set in place by either state law or the customer receiving the gas. If the gas meets these standards and is accepted at the distribution point, the pipeline is referred to as being in a steady-state. If the gas does not meet these standards, the production company runs the risk of being shut-in, or being unable to flow any more gas through the distribution point until the poor-quality gas is removed.Sensors are used to collect real-time gas quality information from within the pipe, and alarms are used to alert the control operators when a threshold is exceeded. If operators fail to keep the pipeline’s gas quality within an acceptable range, the company risks being shut¬¬-in or rupturing the pipeline. Predicting gas quality alarms enables operators to act earlier to avoid being shut-in and is a form of predictive maintenance. We forecast alarms by using a 10th-order autoregressive model, autoregressive model with exogenous variable, simple exponential smoothing with drift (Theta Method) and an artificial neural network with alarm thresholds. The alarm thresholds are defined by the production company and are occasionally adjusted to meet current environment conditions. The results of the alarm forecasting method show that we accurately forecast natural gas pipeline alarms up to a 30-minute time horizon. This translates into sensitivity rates that drop from around 100% at one minute to 82.7% at a 30-minute forecast horizon. This means that at 30 minutes, we correctly forecast 82.7% of the alarms. All alarm forecasting models outperform the state-or-the-art forecaster used by the production company, with the artificial neural network performing the best

Anticipating and Adapting to Increases in Water Distribution Infrastructure Failure Caused by Interdependencies and Heat Exposure from Climate Change

abstract: This dissertation advances the capability of water infrastructure utilities to anticipate and adapt to vulnerabilities in their systems from temperature increase and interdependencies with other infrastructure systems. Impact assessment models of increased heat and interdependencies were developed which incorporate probability, spatial, temporal, and operational information. Key findings from the models are that with increased heat the increased likelihood of water quality non-compliances is particularly concerning, the anticipated increases in different hardware components generate different levels of concern starting with iron pipes, then pumps, and then PVC pipes, the effects of temperature increase on hardware components and on service losses are non-linear due to spatial criticality of components, and that modeling spatial and operational complexity helps to identify potential pathways of failure propagation between infrastructure systems. Exploring different parameters of the models allowed for comparison of institutional strategies. Key findings are that either preventative maintenance or repair strategies can completely offset additional outages from increased temperatures though-- improved repair times reduce overall duration of outages more than preventative maintenance, and that coordinated strategies across utilities could be effective for mitigating vulnerability.Dissertation/ThesisDoctoral Dissertation Civil, Environmental and Sustainable Engineering 201

Integrating Green Infrastructure Into Stormwater Policy: Reliability, Watershed Management, and Environmental Psychology as Holistic Tools for Success

As cities continue to expand, the issues of flood control and urban water quality have become major modern sustainability challenges. Green infrastructure—the use of nature-based solutions to target, treat, and store stormwater at its source—has emerged as a possible solution. While green infrastructure does offer multiple benefits for urban users, its performance is also highly variable. This Article addresses a key gap in existing literature by explicitly addressing how uncertainty in environmental and anthropogenic factors affects green infrastructure performance and integration within the Clean Water Act’s municipal separate storm sewer (MS4) regulatory program

Optimal sensor placement for sewer capacity risk management

2019 Spring.Includes bibliographical references.Complex linear assets, such as those found in transportation and utilities, are vital to economies, and in some cases, to public health. Wastewater collection systems in the United States are vital to both. Yet effective approaches to remediating failures in these systems remains an unresolved shortfall for system operators. This shortfall is evident in the estimated 850 billion gallons of untreated sewage that escapes combined sewer pipes each year (US EPA 2004a) and the estimated 40,000 sanitary sewer overflows and 400,000 backups of untreated sewage into basements (US EPA 2001). Failures in wastewater collection systems can be prevented if they can be detected in time to apply intervention strategies such as pipe maintenance, repair, or rehabilitation. This is the essence of a risk management process. The International Council on Systems Engineering recommends that risks be prioritized as a function of severity and occurrence and that criteria be established for acceptable and unacceptable risks (INCOSE 2007). A significant impediment to applying generally accepted risk models to wastewater collection systems is the difficulty of quantifying risk likelihoods. These difficulties stem from the size and complexity of the systems, the lack of data and statistics characterizing the distribution of risk, the high cost of evaluating even a small number of components, and the lack of methods to quantify risk. This research investigates new methods to assess risk likelihood of failure through a novel approach to placement of sensors in wastewater collection systems. The hypothesis is that iterative movement of water level sensors, directed by a specialized metaheuristic search technique, can improve the efficiency of discovering locations of unacceptable risk. An agent-based simulation is constructed to validate the performance of this technique along with testing its sensitivity to varying environments. The results demonstrated that a multi-phase search strategy, with a varying number of sensors deployed in each phase, could efficiently discover locations of unacceptable risk that could be managed via a perpetual monitoring, analysis, and remediation process. A number of promising well-defined future research opportunities also emerged from the performance of this research

Unattended network operations technology assessment study. Technical support for defining advanced satellite systems concepts

The results are summarized of an unattended network operations technology assessment study for the Space Exploration Initiative (SEI). The scope of the work included: (1) identified possible enhancements due to the proposed Mars communications network; (2) identified network operations on Mars; (3) performed a technology assessment of possible supporting technologies based on current and future approaches to network operations; and (4) developed a plan for the testing and development of these technologies. The most important results obtained are as follows: (1) addition of a third Mars Relay Satellite (MRS) and MRS cross link capabilities will enhance the network's fault tolerance capabilities through improved connectivity; (2) network functions can be divided into the six basic ISO network functional groups; (3) distributed artificial intelligence technologies will augment more traditional network management technologies to form the technological infrastructure of a virtually unattended network; and (4) a great effort is required to bring the current network technology levels for manned space communications up to the level needed for an automated fault tolerance Mars communications network

Min Metall Explor

Powered haulage continues to be a large safety concern for the mining industry, accounting for approximately 50% of the mining fatal accidents every year. Among these fatal accidents, haul-truck-related accidents are the most common, with 6 of 28 and 6 of 27 fatal accidents occurring in 2017 and 2018, respectively. To better understand why these accidents continue to occur and what can be done to prevent them, researchers reviewed the 91 haul-truck-related fatal accidents that occurred in the USA from 2005 to 2018 and performed bow-tie analyses using the final reports published by the Mine Safety and Health Administration. The analyses explore the context of the accidents with a focus on the initiating event, event outcome, hazards present, and possible preventative and mitigative controls. Overall, the vast majority of the accidents resulted in a haul truck colliding with the environment, and the majority of these events were initiated by loss of situational awareness or loss of control. The majority of the hazards were related to design and organizational controls. The results of this study suggest a need to investigate operator decision-making and organizational controls and to focus on improving design and operation controls such as mine design and operational procedures.CC999999/ImCDC/Intramural CDC HHSUnited States/2022-04-01T00:00:00Z34423255PMC837174811163vault:3814

A Strategic Digital Transformation for the Water Industry

This book is a compilation of the knowledge shared and generated so far in the IWA Digital Water Programme. It is an insightful collection of white papers covering best practices, linking academic and industrial studies/insights with applications to give real-world examples of digital transformation. These White Papers are designed to help utilities, water professionals and all those interested in water management and stewardship issues to better understand the opportunities of digital technologies. This book covers a plethora of topics including: Instrumentation and data generation Artificial intelligence and digital twins The digital transformation and public health Mapping the digital transformation journey into the future With these topics, the aim is to present an all-encompassing reference for practitioners to use in their day-to-day activities. Through the Digital Water Programme, the IWA leverages its worldwide member expertise to guide a new generation of water and wastewater utilities on their digital journey towards the uptake of digital technologies and their integration into water services

The importance of preventative maintenance on flow measurement instrumentation

Abstract: Process plants need to produce more and more to keep up with growing demand. However,  these plants are also becoming eroded and dysfunctional due to the lack of maintenance, in  this case preventative maintenance (PM). PM is the schedule or periodic checking, to detect  the  degradation  of  equipment  on  a  plant.  Achieving  such  maintenance  efficiently  and  effectively is a vital activity to ensure good, safe, and high product quality on a plant. This  research considers the technical personnel’s perception towards conducting preventative  maintenance on flow measuring instruments on their respective plants.   This research looks at the preventative maintenance activities that are required on flow meter  instrumentation. It also considers the impact of not conducting such maintenance and the  importance of this maintenance as perceived by technical personnel responsible for the plant.    Through literature review, primary preventative maintenance activities are presented. All  these activities need to take place in order to keep instruments from failing abruptly in order  to avoid degradation, profit losses and to minimize downtime on the process plant. A survey  in the form of a questionnaire was distributed using snowball methodology. 101 technical  personal in three different industries across the SADC region responded to the questions.  Each participant indicated where they were from and they type of plant they worked on. The  participant’s responses also included if they conducted preventive maintenance proactively  or not, as well as the impact of not conducting such maintenance...M.Phil. (Engineering Management