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At least 829 records · Page 46

Closing the methane gap in US oil and natural gas production emissions inventories

Methane (CH 4 ) emissions from oil and natural gas (O&NG) systems are an important contributor to greenhouse gas emissions. In the United States, recent synthesis studies of field measurements of CH 4 emissions at different spatial scales are ~1.5–2× greater compared to official greenhouse gas inventory (GHGI) estimates, with the production-segment as the dominant contributor to this divergence. Based on an updated synthesis of measurements from component-level field studies, we develop a new inventory-based model for CH 4 emissions, for the production-segment only, that agrees within error with recent syntheses of site-level field studies and allows for isolation of equipment-level contributions. We find that unintentional emissions from liquid storage tanks and other equipment leaks are the largest contributors to divergence with the GHGI. If our proposed method were adopted in the United States and other jurisdictions, inventory estimates could better guide CH 4 mitigation policy priorities.

03 NATURAL GAS↗

The Impacts of Distinct Flexibility Enhancements on the Value and Dynamics of Natural Gas Power Plant Operations

The rapid increase of renewable generation and its anticipated continued growth requires greater operational flexibility in modern power systems. Previous studies explored the addition of more flexible resources to improve system flexibility, but this may also be achieved at lower cost by enhancing existing power plants via flexibility retrofits. Potential flexibility upgrades to existing thermal plants include modifications that enable faster ramp rates, increase maximum load levels, decrease minimum load levels, and provide faster and lower cost startup operations. In this paper, we focus on improvements to existing natural gas combined cycle generators, and apply a unit commitment model to analyze the impact that each specific upgrade has on their operational dynamics and profitability from both the system perspective and from the asset owner perspective. We show that the value of each type of flexibility improvement varies depending on the capacity factor and usage pattern of the generator before the upgrade, and that the relative benefit of each type of flexibility varies. We demonstrate diminishing returns to increased flexibility when upgrading multiple generators simultaneously. Sensitivity tests for several shares of renewable generation, different generation mixes and different net load realizations confirm the generality of the results shown.

03 NATURAL GAS↗

Front-End Engineering Design (FEED) Study for a Carbon Capture Plant Retrofit to a Natural Gas-Fired Gas Turbine Combined Cycle Power Plant (2x2x1 Duct-Fired 758-MWe Facility with F Class Turbines)

A comprehensive front-end engineering design (FEED) study has been undertaken by Bechtel National Inc. (Bechtel) for locating a post-combustion capture and compression (PCC) unit at Panda’s Sherman natural gas–combined cycle (NGCC) power plant in Sherman, Texas. This is described in the unredacted FEED Study report (Attachment 1) with all supporting documents, numbering over 150. The Study Report is publicly available. Sizing of the PCC plant is based on treating an amount of flue gas equivalent to that produced when generating 420 MW, which is approximately 68% of the total flue gas emitted by the NGCC power plant operating at guarantee condition with duct burners off. A reduced power plant capacity factor was used for sizing the PCC plant because the gas turbines at the site often operate at reduced load due to the high penetration of renewable power in the ERCOT region. The cost of carbon capture is primarily driven by capital cost (and therefore is highly sensitive to capacity factor). Sizing the capture unit so that when used it is nearly always operating at full capacity is critical to the economic viability of the proposed investment.

03 NATURAL GAS↗

Cyber Physical Protection for Natural Gas Compression

The secure transport of natural gas through North American pipelines is vital for both home and industrial purposes. GE in collaboration with Baker Hughes and Idaho National Laboratory, completed a US Department of Energy grant program to develop a new cyber-physical protection system that monitors the large compressor stations used to boost pressure and maintain proper gas flow. Algorithms were developed to detect the presence of a cyber-attack that impacts the compressor station physical processes, locate the critical functions being manipulated, and potentially neutralize the attack allowing continued operations. The technology was successfully demonstrated at an operating compressor facility located in New York state.

03 NATURAL GAS↗

Microwave Catalysis for Process Intensified Modular Production of Carbon Nanomaterials from Natural Gas

The objective of this project was to develop a novel, low-cost process intensified modular process to directly convert flare gas or stranded gas to carbon nanomaterials and co-product hydrogen (H 2 ) with high conversion, selectivity, and stability. The proposed project was based on our exciting exploratory research on a patent pending technology for one-step conversion of natural gas to carbon nanotubes (CNTs) and carbon fibers (CNFs) without emitting CO 2 : CH 4 → H 2 + C (CNT, Carbon Fibers).

03 NATURAL GAS↗

Transformational Nano-confined Ionic Liquid Membrane for Greater than or Equal to 97 Percent Carbon Dioxide Capture from Natural Gas Combined Cycle Flue Gas

A transformational process based on nano-confined ionic liquid (NCIL) membranes was developed for capturing ≥97% CO 2 from natural gas combined cycle (NCCC) flue gas. The NCIL membranes were prepared by loading amino acid ionic liquid into a framework composed of single-walled carbon nanotube mesh filled with graphene oxide quantum dots. The membranes exhibited CO 2 permeance as high as 2,000 GPU with a CO 2 /N2 selectivity of 2,300 for a typical NGCC flue gas composition. When H 2 O vapor sweep was applied in the permeate side, 96.6% CO2 dry-basis purity and 97.6% CO 2 capture rate were achieved for a simulated NGCC flue gas with single stage. In the process design, a highly H 2 O-selective membrane would be needed to recover majority of the H 2 O vapor, and the recovered H 2 O vapor could be recycled to the permeate side of the NCIL membrane. Sulfonated poly(ether ether ketone) membranes were successfully developed for this purpose. These membranes exhibited H 2 O permeance great than 11,000 GPU and H 2 O/CO 2 selectivity greater than 1,000 at 70ºC for a feed mixture consisting of 14.5 vol% H2O and balanced CO 2 . A standalone membrane model using MATLAB platform was developed for process simulation. The model was validated with experimental data. Techno-economic analysis based on the testing data collected during the current program suggests this transformational membrane process can achieve 97% CO 2 capture efficiency with a cost of $47.8/tonne of CO 2 , which is a 21% reduction versus DOE’s reference case B31B.97.

03 NATURAL GAS↗

Direct solar self-catalyzing pyrolysis of natural gas to hydrogen and high-quality graphite (Final Technical Report)

This project, led by researchers at UCLA in partnership with Southwest Solar Technology (SST) and SolGrapH, successfully demonstrated a new method for producing clean hydrogen fuel and high-quality graphite using concentrated solar energy. The primary goal was to develop a technology that converts natural gas (primarily methane) into two valuable products—hydrogen gas and solid carbon—without releasing carbon dioxide (CO2) into the atmosphere. This process, known as solar thermal pyrolysis, uses heat from the sun to split the methane molecules directly.

03 NATURAL GAS↗

An Evaluation of Co-Simulation for Modeling Coupled Natural Gas and Electricity Networks

Reliance on natural gas for power generation has increased the coupling between gas and power networks. While this coupling can bring operational and economic benefits, it can also yield challenges, as the constraints in one system can impact the other. Co-simulation can capture the constraints and interactions between these systems, but so far, there has been limited comparison of co-simulation results to those of an integrated model. In this work, we develop a new co-simulation framework using the HELICS platform and the SAInt tool for modeling transient gas and AC optimal power flow. We evaluate this co-simulation framework against a fully integrated version of the SAInt power and gas simulators, thus providing a benchmarking of the co-simulation approach. We compare results across the two approaches for two test networks and a network representing the Belgian power and gas networks, testing both normal operating conditions and cases with compressor disruptions. In each of the cases tested, we find nearly identical results from the two approaches across various metrics of interest, such as nodal pressure, gas flow rates, and active power generation. This alignment suggests that co-simulation can yield comparable results to fully integrated models for modeling coupled gas and electricity networks.

03 NATURAL GAS↗

Heavy Duty Natural Gas Single Cylinder Research Engine Installation, Commissioning, and Baseline Testing

Natural Gas (NG) Internal Combustion Engines (ICE) are a promising alternative to diesel engines for on-road heavy-duty applications to reduce greenhouse gas and harmful pollutant emissions. NG engines have not been widely adopted due to the lower thermal efficiency compared with diesel engine counterparts. To develop the base knowledge required to reach the desired efficiency, a Single Cylinder Engine (SCE) is the most effective platform to acquire reliable and repeatable data. A SCE test cell was developed using a Cummins 15-liter six-cylinder heavy-duty engine block modified to fire one cylinder (2.5-liter displacement). A Woodward Large Engine Control Module (LECM) is integrated to permit implementation of real-time advanced combustion control. Intake and exhaust characteristics, fuel composition, and exhaust gas recirculated substitution rate (EGR) are fully adjustable. A high-speed data acquisition system acquires in-cylinder, intake, and exhaust pressure for combustion analysis. The baseline testing shows reliable and consistent results for engine thermal efficiency, indicated mean effective pressure (IMEP), and coefficient of variance of the IMEP over a wide range of operating conditions while achieving effective control of all engine control and operation variables. This test cell will be used to conduct a research program to develop new and innovative control algorithms and CFD optimized combustion chamber designs, allowing ultra-high efficiency and low emissions for NG ICE heavy-duty on-road applications.

03 NATURAL GAS↗

Contextualizing Air Traffic Management Conversations using Natural Language Understanding

Efficient management of air traffic and mitigation of delays depend on extracting actionable information from unstructured data, such as dialogues from the Federal Aviation Administration’s (FAA’s) Air Traffic Control System Command Center (ATCSCC) telecons. This study presents a pipeline utilizing Natural Language Processing (NLP) methods for Intent Classification (IC) and Slot Filling (SF) to identify and extract Traffic Management Initiatives (TMIs) from aviation-specific dialogues. We leveraged DeBERTa, a pre-trained transformer model, and fine-tuned it to the nuances of the aviation domain. Despite challenges posed by annotation complexities, the IC model achieved promising results with a weighted average F1-score of 0.81. Our results are close to those of human annotators, which demonstrates the model’s strong alignment with human-level performance. The SF model also showed strong performance, achieving a weighted F1-score of 0.97, which demonstrates its effectiveness in accurately predicting key slots. Our analysis revealed limitations in handling less frequent intents and slot labels due to data sparsity, motivating future efforts to adopt joint IC-SF modeling and data augmentation strategies. This research highlights the potential of domain-specific NLP to streamline decision-making in the aviation industry and improve the management of TMIs.

Air Traffic Control Management↗

Influence of NOx Chemistry on the Prediction of Natural Gas End-Gas Autoignition

Research on the influence of NOx (NO/NO2) chemistry on HC oxidation has shown that NOx plays an important role in the promotion/inhibition of HC autoignition [1-6]. Current data for n-heptane, iso-octane, ethanol, and toluene [3, 4] have shown that NO chemistry inhibits autoignition at low temperatures and concentrations. However, at medium and high temperatures and low concentrations, autoignition is promoted, decreasing the Negative Temperature Coefficient (NTC) effect. This autoignition promotion, however, becomes weaker as NO concentrations are increased. Additionally, fundamental kinetics studies have suggested that NOx chemistry also promotes the autoignition of smaller HC, such as CH4 [7-10], C2H6 [11-14], and C3H8 [15]. Additionally to the chemical kinetics studies, a growing body of evidence supports the importance of NOx chemistry on SI engine simulations [16, 17]. Foong et al. [18] suggested that the addition of NO in their models significantly improved the agreement between simulations and experiments where the onset of knock was advanced due to the presence of NO, and Morganti et al. [19] showed that NO addition in the residual-gas was necessary for their models to obtain good agreement with experimental data. Lastly, Mohr et al. [20, 21] investigated the effect of Natural Gas (NG) reactivity and EGR substitution rate and composition on homogeneous ignition delay, flame speeds, and EGAI for stoichiometric NG/oxidizer/EGR blends. They observed that the addition of EGR composed of only inert species (CO2 and Ar) suppressed homogeneous autoignition in all NG fuels tested under all conditions. However, for all NG fuels tested, increasing EGR rates with reactive species (Ar, CO2, CO, and NO) promoted homogeneous autoignition under all conditions, thus reproducing the same trends for various NG fuel compositions that were observed in other studies and fuels. For this reason, a study is being conducted to analyze the effects of NOx chemistry on the prediction of NG/air/EGR homogeneous autoignition. This study has been divided into two tasks. First, the addition of NOx chemistry to the ARIES82 mechanism [20] is being validated using homogeneous ignition delay data collected by Mohr [20, 21]. Second, once the new modified mechanism with NOx reactions has been validated, it will be employed on engine multi-dimensional modeling presented in [22, 23] to analyze the influence of NOx chemistry on NG EGAI. Results thus far have shown that homogeneous ignition delay calculations are sensitive to NOx chemistry, where the modified mechanisms captured well all trends and closely matched the homogeneous ignition delays observed by Mohr et al. Also, the results in this work suggest that NOx chemistry is necessary to correctly capture the trends in NG homogeneous autoignition when EGR with reactive species is used since the opposite behavior is observed when only inert species are considered for the EGR composition.

03 NATURAL GAS↗

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach

Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects’ neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants’ demographic characteristics. Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.

neuropsychological↗

Processing Compressed Expanded Natural Graphite for Phase Change Material Composites

Phase change materials (PCMs) are used in various thermal energy storage applications but are limited by their low thermal conductivity. One method to increase conductivity involves impregnating organic PCMs into highly porous conductive matrix materials. Of these materials, compressed expanded natural graphite (CENG) matrices have received the most attention. Despite this attention, the effect that CENG processing has on PCM saturation and overall matrix thermal conductivity has not been fully investigated. Therefore, the effect of the heat treatment process used to expand intercalated graphite flakes is evaluated here. Higher heat treatment temperatures yielded higher saturation rates and overall saturation at similar matrix porosities. For example, increasing temperature from 300 °C to 700 °C resulted in approximately 60%-70% increase in pore saturation after 100 minutes of soaking. The exposure time to heat treatment had less of an effect on PCM saturation. The exposure time had negligible effect above 30 min and above 500 °C heating temperatures. However, because the expanded graphite was found to oxidize around 700 °C, the use of longer exposure time in manufacturing applications can be beneficial if a shortened impregnation time is needed. Heat treatment conditions did not impact thermal conductivity. The composite latent heat of fusion was also reduced approximately proportionally to the PCM mass fraction. A local maximum in axial thermal conductivity was observed at around 83% porosity, which is similar to previous studies. The observed conductivity at this maximum was a factor of 81 times greater than the conductivity of the PCM.

36 MATERIALS SCIENCE↗

Effectiveness of nature-based solutions to reduce flooding in Quad Cities Metro Area (QCMA) using SWMM-HEC based flood model

Nature-based solutions (NbS) have gained significant attention as strategies for addressing urban environmental challenges, particularly since the establishment of the UN Sustainable Development Goals (SDGs) for 2030. However, the current research on NbS for urban flood management lacks comprehensive methodological approaches for identifying suitable areas and evaluating their effectiveness across different urban settings. Here, this study attempts to fill this gap by proposing a methodological framework integrating multi-criteria analysis with a SWMM-HEC-based hydrologic and hydraulic (HH) model to assess the suitability of NbS for the Quad Cities Metro Area (QCMA), consisting of Davenport, Bettendorf, Moline, and Rock Island. Eight NbS options-green roofs, rain gardens, infiltration trenches, permeable pavements, vegetative swales, dry detention basins, retention ponds, and rain barrels/cisterns - were considered based on volumetric efficiency and runoff reduction efficiency. The study reveals that implementing the proposed NbS could have substantially reduced flood depths in key historical flood events by 21% in 1993, 15% in 2008, 16% in 2011, 23% in 2014, 40% in 2019, and 10% in 2023. The findings highlight a critical trade-off between peak runoff and NbS implementation: while NbS effectively reduce flood impacts, they also enhance volumetric efficiency by approximately 43%. In high-density areas of the QCMA, flood depth reductions of around 20% suggest that NbS are a viable solution for dense urban environments with limited space. This shows the potential for integrating NbS into existing infrastructure, offering a promising approach for cities facing increasing flooding risks. The proposed methodology provides a practical framework for incorporating NbS into urban stormwater management, addressing gaps in optimizing NbS performance, and offering a pathway to scale their application in other urban areas with various environmental and social contexts.

CMIP6↗

Natural transformation as a tool in Acinetobacter baylyi : Evolution by amplification of gene copy number

For many years, the natural competency of Acinetobacter baylyi ADP1 facilitated studies of bacterial metabolism, biochemistry, and physiology. With the advent of synthetic biology, new opportunities arise to exploit the remarkable transformability and chromosomal plasticity of this model organism. In this chapter, we describe a recently developed method, “Evolution by Amplification and Synthetic Biology” (EASy). EASy allows the targeted amplification of chromosomal segments that give rise to new phenotypes. Increased gene dosage regulates protein expression in a rudimentary fashion by establishing a chromosomal array in which copy number adjusts via recombination between repeated DNA sequences. Selective conditions enrich for cells within the population that confer a growth advantage. Under continuous selective pressure, beneficial mutations may accumulate in any genomic region. Such mutations favor decreases in the average copy number of the target region. Thus, the genetic flexibility afforded by transient copy number variation helps accelerate the selection of engineered strains with desired traits during laboratory evolution. As a result, thanks to the extremely simple genetic manipulation of Acinetobacter baylyi ADP1, the EASy method can be readily implemented by researchers without the need for advanced instrumentation or complex cloning techniques.

59 BASIC BIOLOGICAL SCIENCES↗

Natural attenuation of uranium in a fluvial Wetland: Importance of hydrology and speciation

A nuclear fuel fabrication facility released 43,500 kg of uranium into a riparian wetland located on the Savannah River Site between 1955 and 1988. Studies were undertaken to evaluate hydrological and geochemical processes influencing uranium accumulation in the wetland. Gamma-radiation-mapping surveys were conducted by systematically walking over the contaminated wetland with backpacks equipped with global positioning systems and NaI gamma detectors. Based on maps compiled from >700,000 gamma spectra and eight sediment uranium depth profiles, it was determined that 94% of the released uranium remained in the wetland. The uranium in the wetland is concentrated in five multi-hectare areas along the stream, accounting for ~11% of the land area adjacent to the stream. While land type (upland or wetland) and topography provided a reasonable first approximation of where much of the uranium was deposited, hydrological watershed modeling revealed that the stream velocity was especially slow through many of the hot spots. Here, using autoradiography combined with SEM/EDX measurements of contaminated sediments, surprisingly few hot particles were detected. Instead, uranium was evenly distributed throughout the sampled sediment, suggesting that dissolved uranium had bound to sediment particles that became suspended and later deposited in low energy (low flow velocity) portions of the stream. EXAFS suggested that U atoms were present as individual ions in disordered complexes within the sediment. Furthermore, linear combination analyses suggested that the predominant component of the U(VI) was adsorbed to sediment minerals (~70%) and a minor component (~30%) was associated with organic matter phases. Furthermore, these studies show that wetlands can be extraordinarily effective at binding and retaining uranium, thereby providing a natural barrier to the transport of uranium out of a watershed. However, significant anthropogenic or climatic changes to wetlands, such as those associated with flooding, forest fires, or land use, may disrupt the complex hydrological and biogeochemical balance necessary to maintain long-term immobilization of uranium.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

CFD modeling of natural circulation in LiCl-KCl molten salt closed loop

Characterizing flow within a molten salt closed-loop system is crucial for assessing system requirements, evaluating performance, and identifying potential flaws. Direct flow measurement using instrumentation is challenging due to extreme environmental conditions and the limitations associated with measuring molten salt flow under natural convection. Here, this study aims to provide comprehensive insights into the thermal-hydraulic behavior of a closed loop, with a particular focus on temperature distribution and velocity prediction. The Computational Fluid Dynamics (CFD) model demonstrated the capability to effectively simulate and predict both temperature distributions and flow velocities within the molten salt loop. The CFD model's predictive capability was validated by its ability to replicate temperature measurements under varying boundary conditions. The analysis revealed that the CFD model tends to underpredict temperatures in the cold leg and overpredict them in the hot leg, highlighting the need for continuous model refinement and acknowledging the limitations of using a steady-state approach. Furthermore, the potential of using external temperature measurements to estimate internal molten salt temperatures and predict flow velocity was explored, revealing that this approach could introduce up to a 5.5% error in flow velocity calculations. Line probes mapping temperature distributions across the tube's cross-section and molten salt provided valuable insights into temperature gradients, emphasizing the need for a thermal conductivity equation for molten salt with lower uncertainty to achieve more accurate temperature predictions of the system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Structural changes of lignins in natural Populus variants during different pretreatments

In the present study, three leading pretreatment technologies including dilute acid (DA), liquid hot water (LHW), and organosolv pretreatments (OS) were applied on two Populus natural variants with different recalcitrance. The structural features of the isolated lignins were analyzed accordingly. All the studied pretreatments reduced the molecular weights of the lignins. Aliphatic OH was reduced while phenolic OH was increased in all pretreated lignins. HSQC analysis revealed that pretreatment influenced the lignin composition and relative distribution of inter-unit linkages. The lignin S/G ratio was found to increase during DA pretreatment, while it was decreased after LHW and OS pretreatment. LHW pretreatment also resulted in much less cleavage of β-O-4 linkage than the other two pretreatments. These results could offer guidelines on appropriate selection of biomass and pretreatment technology in the future biorefinery process.

59 BASIC BIOLOGICAL SCIENCES↗