Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “operating costs”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine Learning Classification of Molten Salt Heat Exchanger Channel Plugging using Synthetic Data

This report addresses the requirements of Milestone M3.4 AI capability to identify and predict maintenance events. Development of digital twins (DT) for molten salt reactor (MSR) components is crucial for reducing operating and maintenance costs (O&M) and ensuring commercial viability of these reactors. Our focus is on development of DT for MSR primary system heat exchanger (HX), a critical component, the fault in which can reduce operating efficiency and force reactor shutdown. We are investigating the feasibility of a conceptual DT of HX consisting of internal distributed temperature sensing with fiber optics and machine learning (ML) algorithms to detect and localize faults. To determine the optimal approach to detection and localization of channel plugging, we benchmark seven different ML models: Logistic Regression, K-Nearest Neighbors (KNN), Gaussian Naïve Bayes, Support Vector Machines (SVM), Decision Tree Classifier, Random Forest Tree Classifier, and Feed-Forward Neural Network. ML algorithms are benchmarked using synthetic HX plugging data generated with computational fluid dynamics COMSOL software, with added brown noise to represent experimental noise. We show that the best performance is obtained with the Decision Tree classifier.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

A new approach for measuring the carbon and oxygen content of atmospherically relevant compounds and mixtures

Abstract. Due to its complexity, gas- and particle-phase organic carbon in the atmosphere is often classified by its bulk physicochemical properties. However, there is a dearth of robust, moderate-cost approaches to measure the bulk chemical composition of organic carbon in the atmosphere. This is particularly true for the degree of oxygenation, which critically affects the properties and impacts of organic carbon but for which routine measurement approaches are lacking. This gap has limited the understanding of a wide range of atmospheric components, including particulate matter, the mass of which is monitored worldwide due to its health and environmental effects but the chemical characterization of which requires relatively high capital costs and complex operation by highly trained technical personnel. In this work, we demonstrate a new approach to estimate the mass of carbon and oxygen in analytes and mixtures that relies only on robust, moderate-cost detectors designed for use with gas chromatography. Organic compounds entering a flame ionization detector were found to be converted with approximately complete efficiency to CO2, which was analyzed downstream using an infrared detector to measure the mass of carbon analyzed. The ratio of the flame ionization detector (FID) signal generated to CO2 formed (FID∕CO2) was shown to be strongly correlated (R2=0.89) to the oxygen-to-carbon ratio (O∕C) of the analyte. Furthermore, simple mixtures of analytes behaved as the weighted average of their components, indicating that this correlation extends to mixtures. These properties were also observed to correlate well with the sensitivity of the FID estimated by structure activity relationships (quantified as the relative effective carbon number). The relationships between measured FID∕CO2, analyte O∕C, and FID sensitivity allow the estimation of one property from another with <15 % error for mixtures and <20 % error for most individual analytes. The approach opens the possibility of field-deployable, autonomous measurement of the carbon and oxygen content of particulate matter using time-tested, low-maintenance detectors, though such an application would require some additional testing on complex mixtures. With some instrumental modifications, similar measurements on gas-phase species may be feasible. Moreover, the potential expansion to additional gas chromatography detectors may provide concurrent measurement of other elements (e.g., sulfur, nitrogen).

42 ENGINEERING↗
DOE OSTI2022

High Yield, Economical and Environmentally Benign Production of Rare Earth Elements from Coal Ash [Abstract]

Fly ash stored in landfills and ponds across the United States is an attractive, abundant domestic resource for the cost-effective recovery of rare earth elements (REE) and other critical minerals (CM). Physical Sciences Inc. (PSI) and its team members, Winner Water Services (WWS) and University of Kentucky/Center for Applied Energy Research (UK/CAER) successfully executed a multiphase program that developed and demonstrated pilot plant operations for cost-effective and environmentally-friendly production of rare earth element oxide (REO) concentrates, and the critical minerals scandium and aluminum (in the forms of salts or oxide products). We constructed and operated a sub-scale (0.5 kg/day) micropilot facility to demonstrate the key physical and chemical processing operations, predict yields, and troubleshoot process bottlenecks. The project team then designed, constructed and operated two decoupled pilot plant operations: (1) an operational pilot plant for physical separation processes with a capacity of 0.4 metric tons per day (tpd) where we optimized processes to produce selected ash fractions as the feedstock for chemical processing as well as valuable byproducts such as cement substitute, cenospheres, magnetic ash and secondary fuel carbon, and (2) an operational pilot plant for chemical processing with a capacity of 0.5 tpd that developed optimized processes for the production of: (a) REO concentrates, (b) critical minerals recovery (Sc, Al), and (c) beneficiated ash as valuable byproduct suitable for cement applications.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Multimodal CO2 Transportation Cost Model

This model provides a cost estimate for transporting CO2 via truck or rail in the United States using commercially available equipment and technologies. The model includes an analysis of direct and indirect CO2 emissions to determine costs per net tonne of CO2 transported. Publicly available data and methods published in the peer-reviewed literature are used to the extent possible; references are available at the bottom of the "Calculations" sheet. Upstream (i.e., liquefaction, buffer storage) and downstream (i.e., buffer storage, reconditioning) activities are included in the model of emissions and costs. All capital and operating expenditures are estimated in the "Calculations" sheet. The cost of financing the project is determined in the "FINEX" sheet. All user inputs are done via drop down menus in on the "User Interface" sheet. Summary results are also provided on the "User Interface" sheet.

Myers, CoreyA↗
DOE OSTI2024

An innovative SR-WEC for a market-disruptive LCOE

The objective of DE-EE0008630: An innovative SR-WEC for a market-disruptive LCOE was to develop and test a scaled prototype of the Surface-Riding Wave Energy Converter that can result in a market-disruptive Levelized Cost of Energy by a combination of an extended operating window, substantially lowered cost and amplified average power output by simple optimum control. Initially conceptualized as a floating linear electrical generator (LEG), the SR-WEC evolved into an intermediate-scale version where multiple LEGs were mounted on a floating cylindrical body, driven by the need to enhance scalability and improve power performance.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Solid Sorbent Cost Sensitivity Analysis: A Framework for UNF Reprocessing Sorbent Cost Comparison

Solid sorbents have been the subject of research and development across the U.S. Department of Energy national laboratory complex for many years. They are generally accepted as a safer alternative to cryogenic distillation for noble gas capture, and they present an easier pathway in development of long-term waste forms after iodine capture. As more types of sorbents have been proposed for capture of volatile radionuclides, it has become necessary to compare them based on performance and cost criteria. This report details cost and performance information for three promising sorbents and provides a cost sensitivity analysis. The goal of this analysis is to establish a framework which can be utilized to directly compare future sorbents, with differing properties, to the sorbents discussed in this report. Direct comparison is instrumental to making informed decisions to efficiently guide research and minimize laborious detours. In all cases, sorbent capacity is a major cost driver as it influences the mass of sorbent, operational footprint, and disposal cost requirements., However, sorbent price can greatly increase the cost of a capture technology. For sorbents used in krypton capture, the purity of krypton released to storage is the highest cost driver.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Evaluating the Impact of Tritium Permeation Membrane Performance and Direct Internal Recycling on Fusion Fuel Cycle Efficiency Using TMAP8

An efficient fuel cycle is vital to sustainable and cost-effective energy generation in fusion systems. Since tritium is not widely available, fusion systems must breed their own tritium for sustainable fusion deuterium-tritium reactions. An inefficient fuel cycle increases the tritium inventory needed for operations, which increases costs, constraints on tritium management systems, and safety concerns. A fuel cycle model is a powerful tool for understanding tritium inventories and flow rates across all systems in the fuel cycle. By simplifying the technical details into time-dependent tritium flow rates and inventories, the model can simulate the entire fuel cycle with high computational efficiency, even for technologies that are still under development. It can therefore quantify the impact of new tritium management technologies on fuel cycle efficiency. To evaluate the impact of key components on reducing tritium inventory, we are using and expanding an existing fuel cycle models based on latest advancements in fuel cycle research. The new model integrates Tritium Permeation Membrane (TPM) and Direct Internal Recycling (DIR) to enhance tritium transport from blanket breeders and plasma exhaust. These fuel cycle models are implemented in TMAP8 (Tritium Migration Analysis Program, version 8), a MOOSE-based open-source application designed to provide cutting-edge capabilities for tritium transport and fuel cycle modeling. The study aims to demonstrate the extensibility of existing fuel cycle modeling capability in TMAP8 and to offer a proof-of-principle design for future fusion plant systems. The presentation will cover the performance of fuel cycle modeling capabilities available in TMAP8, highlight advancements in fuel cycle research, and present a sensitivity analysis of these models. The results underline potential approaches and technology solutions to lower tritium inventory requirements, highlighting their role in shaping the future of fusion energy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Application of a Heat Integrated Post-combustion CO 2 Capture System with Hitachi Advanced Solvent into Existing Coal-Fired Power Plant (Final Technical Report)

The goal of this final project report is to comprehensively summarize the work conducted on project DE-FE0007395. In accordance with the Project Management Plan (PMP), Revision F dated 5/10/2019, and Statement of Project Objectives (SOPO) within, the University of Kentucky (UK) Center for Applied Energy Research (CAER) (Recipient) has successfully demonstrated a unique, versatile CO 2 capture system (CCS) using a heat integrated process combined with two-stage stripping for process intensification, heat recovery and demineralized (DM) water generation. This project involved the design, fabrication, installation, testing of and data analysis from the UK CAER 0.7 MWe small pilot scale CO2 capture process installed at Kentucky Utilities (KU) E.W. Brown Generating Station in Harrodsburg, KY. During each of the four project Budget Periods (BPs), UK CAER met all project deliverables, all project milestones, with National Energy Technology Laboratory (NETL) approved adjustments made to the campaign long-term hours during BP4. The CCS was constructed in modular skids. Two solvent campaigns were initially conducted; the first with a 30 wt% monoethanolamine (MEA) as a baseline, and the second with the Hitachi H3-1 advanced solvent. Additional tests were performed with two advanced solvents including CAER and Proprietary Solvent C. Short-period testing with a higher concentration of 40 wt% MEA was conducted to evaluate the potential saving with high alkalinity. From the various solvent campaigns, unique aspects of the UK CAER CCS technology, as well as its flexibility and versatility were experimentally validated and demonstrated. With respect to solvent evaluation efforts in identifying candidates with significant operational and capital cost savings potential, performance of solvents were evaluated to determine the energy requirements for regeneration; environmental impacts from secondary emissions and degradation products; degradation rates, solvent make-up rates and stability. The assessments were done from parametric tests that determined optimum operating conditions for the individual solvents to maximize process efficiency and minimize the parasitic load of the power plant, and from long term campaigns (1000 hours for 30 wt% MEA and 1000 hours for H3-1) which collectively informed the techno-economic analyses (TEA) of the process. The long term campaigns included corrosion studies which used three types of metal coupons in different sections of the process: (absorber, primary stripper, lean carbon-loaded and rich carbon loaded flow streams in process) to mimic heat and flow dynamics process equipment were exposed to. The estimated corrosion rates were used to elucidate corrosion mechanisms and to further guide process material selection for potential capital cost savings.

gas separation↗
DOE OSTI2025

Siting and sizing of public–private charging stations impacts on household and electric vehicle fleets

To facilitate the provision of electric vehicle charging stations (EVCS) in urban areas, this study investigates the benefits of co-locating fleet-owned chargers with public charging stations to enable construction incentives and cord-sharing cost savings. Shared EVCS can serve charging demand from both user types: private (household) EV owners and those managing fleet vehicles – like shared and fully automated EV (SAEV) fleets. Using POLARIS to simulate all person-travel across the 6-county Austin, Texas region, new EVCS were sited and sized with DC fast-charging (DCFC) plugs to lower operating and construction costs while providing public + private (PP) service across an 81-square-mile core geofence (where 200 SAEVs were active) over 24-hour days. When co-location is permitted, 115 DCFC cords were added to the 23 existing (publicly available) stations to enable SAEVs and household EVs (HHEVs) charging access, within the geofence. Each 250-mile-range SAEV was simulated to travel an average of 330 miles per day, serve over 92 person-trips, and recharge 2.7 times a day (for 2.4 h per session). The new DCFC plugs were primarily added to public EVCS at shopping centers and schools, and in residential settings along freeways. The average plug served 4.8 EVs per day. Most co-located PP EVCS permitted immediate (no-wait) charging, except for 2 stations along freeways that averaged 8 min of wait time to begin charging. In conclusion, the co-location strategy lowered fleet owners’ initial EVCS construction costs by 12 % (thanks to cord-sharing to avoid cord duplication), while reducing SAEV wait times to just 3.1 min (versus 10.7 min if SAEV managers had to build and operate their own EVCS).

EV charging modeling↗
DOE OSTI2024

Microchannel reactive distillation for the conversion of aqueous ethanol to ethylene

Here we demonstrate the proof-of-concept for microchannel reactive distillation for alcohol-to-jet application: combining ethanol/water separation and ethanol dehydration in one unit operation. Ethanol is first distilled into the vapor phase, converted to ethylene and water, and then the water co-product is condensed to shift the reaction equilibrium. Process intensification is achieved through rapid mass transfer—ethanol stripping from thin wicks using novel microchannel architectures—leading to lower residence time and improved separation efficiency. Energy savings are realized with integration of unit operations. For example, heat of condensing water can offset vaporizing ethanol. Furthermore, the dehydration reaction equilibrium shifts towards completion by immediate removal of the water byproduct upon formation while maintaining aqueous feedstock in the condensed phase. For aqueous ethanol feedstock (40% w ), 71% ethanol conversion with 91% selectivity to ethylene was demonstrated at 220 °C, 600 psig, and 0.28 h -1 wt hour space velocity. 2.7 stages of separation were also demonstrated, under these conditions, using a device length of 8.3 cm. This provides a height equivalent of a theoretical plate (HETP), a measure of separation efficiency, of ~3.3 cm. By comparison, conventional distillation packing provides an HETP of ~30 cm. Thus, 9.1× reduction in HETP was demonstrated over conventional technology, providing a means for significant energy savings and an example of process intensification. Finally, preliminary process economic analysis indicates that by using microchannel reactive distillation technology, the operating and capital costs for the ethanol separation and dehydration portion of an envisioned alcohol-to-jet process could be reduced by at least 35% and 55%, respectively, relative to the incumbent technology, provided future improvements to microchannel reactive distillation design and operability are made.

10 SYNTHETIC FUELS↗
DOE OSTI2020

Reducing Cost of Chlorinated Volatile Organic Compound Remediation by Transitioning from Active to Passive Soil Vapor Extraction - 20157

Areas of high chlorinated volatile organic compound (cVOC) contamination at the Savannah River Site (SRS) have been undergoing remediation via soil vapor extraction, sometimes coupled with thermal treatments to enhance extraction rates. These active systems are effective in removing large amounts of contaminant mass from the subsurface and mitigating the impacts to groundwater. However, as extraction rates decline, costs must be evaluated with respect to the benefit of continued active operation. A decision framework for identifying conditions when a transition to a more passive remediation is appropriate has been developed with state and federal regulatory agencies. Two remediation areas have recently been transitioned from active soil vapor extraction (ASVE) to passive soil vapor extraction (PSVE) at the SRS. Performance evaluation goals including plume stabilization, overall mass removal trends, environmental sustainability and costs were considered in transitioning from active remediation to passive technologies at both sites. At the Dynamic Underground Stripping (DUS) project at the M-Area Settling Basin, ASVE was combined with steam injection to extract cVOCs during active operations. Steam injection occurred from September 2005 to September 2009. DUS utilized 63 steam injection wells, 34 active vapor extraction wells, and 3 active soil vapor extraction units (SVEUs). Two active SVEUs had 60 horsepower blowers; the third had a 25-horsepower blower. Mass removal was closely tracked during DUS operations; over 181,437 kilograms (400,000 pounds) of cVOCs were removed while active steam injection occurred. After steaming was stopped, ASVE continued. The 34 active wells were evaluated in 2012. The ASVE wells were grouped into categories of high, medium, and low extraction rates. High producing wells remained connected to a single active SVEU. Low producing wells were abandoned, and the medium producing wells were transitioned to PSVE (Microblowers{sup TM}). Microblowers{sup TM} utilize a dedicated blower per well and are solar powered. This passive technology provides energy, maintenance, and operation costs savings while still providing an efficient reduction in cVOC migration to groundwater. In 2018, the remaining ASVE wells were evaluated again. The purpose of this testing was to identify which wells removed the most mass. An optimal well configuration was determined. The criteria to discontinue ASVE was removal of less than 18 kilograms (40 pounds) per week of cVOCs. After 3 months of shutdown (rebound conditions), 2.7 kilograms (5.9 pounds) of cVOCs per week were being removed. Data from the rebound test justified ending ASVE and transitioning wells with higher extraction rates to PSVE. Wells that had depleted the cVOC mass within their zone of influence were abandoned. Performance data from existing PSVE wells justified ending PSVE at wells with depleted extraction rates. Currently the system has 16 PSVE wells operating. Another ASVE system was being used to treat cVOC contaminated soil at the A-Area Miscellaneous Rubble Pile (AMRP) at SRS. System operation began in 2004, with 7 ASVE wells connected to a 60- horsepower blower. Mass removal rates and contaminant concentrations remained consistently low over the ASVE lifespan at AMRP. This indicated that mass removal was diffusion limited. With this data, the 7 ASVE wells were transitioned to PSVE in 2017. Twelve pressure monitoring points were also transitioned to PSVE wells. AMRP currently has 19 PSVE wells operating. Both transitions from active to passive remediation had concurrence from the United States Environmental Protection Agency and the South Carolina Department of Health and Environmental Control. These transitions ensure that only the necessary amount of energy is being exerted to remediate the environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

A Tool for Performing Link Analysis, Operational Sequence Analysis, and Workload Analysis to Support Nuclear Power Plant Control Room Modernization

Nuclear power continues to have an imperative role for the U.S.’s electricity generation. However, for these nuclear power plants (NPPs) to remain economically viable, new strategies for reducing operations and maintenance costs must be explored. The U.S. Department of Energy Light Water Reactor Sustainability Program is researching how to digitally transform existing analog and hybrid main control rooms into a fully integrated control room that addresses this challenge. The transformation will fundamentally change the conduct of operations for these U.S. NPPs. Human factors engineering has a vital role in this effort, where traditional task analysis methods are important in informing the design of advanced human-system interface displays. This work describes a preliminary tool to support task analysis for the development of these advanced displays. Details on the use of this tool, including the specific task analysis methods offered, are presented in this paper.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Techno-Economic Viability of Flexible Dispatch of Unconventional Geothermal Systems

Flexible geothermal operations could boost project returns through the allocation of improved power purchase agreements and/or exploitation of power price arbitrage opportunities. In this study, we investigated the techno-economic feasibility of variable flow rate control and time-of-day pricing in closed-loop geothermal systems. We considered U-shaped multilateral system configurations and modeled a variety of technical system parameters. These designs were simulated using a slender-body theory (SBT) model for transient heat transfer and fluid flow. This subsurface model was integrated into the flexible geothermal economic model (FGEM) tool to evaluate the overall flexible geothermal system techno-economics. Future hourly ambient temperature conditions were based on the Sup3rCC dataset. Published datasets were used for future hourly wholesale electricity prices. We analyzed four operating strategies: 1) baseload operation, 2) seasonal dispatch (high flow rate during summer and nominal flow rate during the rest of the year), 3) net generation maximization by varying flow rate to maximize net power output, and 4) revenue maximization by varying flow rate to maximize revenue. We ran all four scenarios for a multiloop configuration with 12 lateral passes, 7-km vertical depth and 87-km total drilling length. Furthermore, we assumed a 60 degrees C/km geothermal gradient and ambient temperature and wholesale electricity prices for New Mexico as a typical state location. The nominal flow rate was set to 80 kg/s. When considering drilling costs of $1,000/m and a discount rate of 7%, the generation maximization scenario resulted in the lowest levelized cost of electricity (LCOE) of ~$150/MWh. When considering project return on investment (ROI), defined as lifetime net income divided by upfront capital costs, all flexible operation scenarios performed better than the base case scenario. The highest ROI of 80% was obtained with the revenue maximization scenario. With drilling costs of $200/m and a discount rate of 5%, the generation maximization scenario resulted in LCOE of $49/MWh.

flexible geothermal↗
DOE OSTI2021

Development of Energy Storage: Cost models

Energy storage technologies offer a promising solution to electric grid stability issues associated with the integration of variable renewable generators. The capability to match the electrical power output to instantaneous fluctuations in grid demand is crucial to ensure continuity of service. Including energy storage capability in an integrated energy system (IES) can provide the flexibility needed to meet variable electric demand and reduce the load following demands place on the reactor. In this report, economic data collected for energy storage (ES) technologies are described to support the objective of assessing the profitability of ES integration within the IES framework. In particular, there is a growing interest in thermal energy storage (TES) given its unique capability for long-duration storage for improving electricity reliability at a low levelized cost. It is common practice to evaluate the total lifetime cost and profitability before commercializing new technologies. In this report we identify and examine the models needed to better understand the economics of thermal energy storage. We extend the TES cost model in RAVEN in the context of a balance of plant (BOP) that incorporates thermal storage. To focus the discussion, following a general overview of the most promising TES technologies, we consider a use case that involves a sensible heat, two-tank, molten-salt system. Structural and operational details are reported to identify the source of construction capital expenditure and operation and maintenance cost. A detailed description of the different cost items is provided as well as the cost scaling with different storage capacity and power ratings for capacity optimization purpose. In addition, the capital expenditure and the recurring cost of representative two-tank, molten salt coupled with concentrated solar plants are provided for readers’ reference. The ES use case is noteworthy as it is in the pilot stage of commercialization. We identify those areas that would benefit from an increased economic focus to obtain a more complete compilation of cost data. We also describe the thermal coupling issues that arise from integration of the two-tank molten salt thermal energy storage system with a BOP, which is the subject of our current research. Some components of costs will need to be evaluated through dedicated technoeconomic analysis in future modeling activities using modeling procedures proposed in this report. With the data presented and the procedures described in this report, sufficiently accurate models can be implemented for the solution of both the power dispatch and the capacity expansion problems within the RAVEN-based HYBRID framework.

25 ENERGY STORAGE↗
DOE OSTI2025

Stress evolution and creep deformation in solid-oxide electrolysis cell systems – Dynamic modeling and multi-objective optimization to maximize stack life and efficiency

Here, this study develops a thermal stress model of solid-oxide electrolysis cells (SOECs) including a model for creep strain and failure probability that is integrated with a dynamic plant-wide model of a hydrogen production process. Uncertainties in key material properties of the cell are quantified to assess their impact on stress profile variability. The oxygen electrode is found to have about 10 times higher failure probability compared to the fuel electrode. The study shows that if the stack operation is not optimized, cycling operation would lead to stress build-up eventually leading to catastrophic failure. A dynamic optimization problem is set up for obtaining the optimal operational profile considering a variable hydrogen production rate. Due to the tradeoff between the efficiency and stress build-up, the dynamic optimization problem is multi-objective. It is observed that the optimizer can considerably reduce the stress build-up (i.e., can increase the stack life) albeit at the cost of a lower efficiency thus exhibiting strong tradeoffs between capital and operating costs. For example, if the stack would be replaced in 0.5 yr, specific energy requirement would be 48.5 kWh/kg H 2 while for a stack replacement time of about 6 yr, the specific energy requirement rises by about 4.2 %.

SOEC↗
DOE OSTI2021

Smart Methane Emission Detection System Development Final Report

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators.

03 NATURAL GAS↗
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗