Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “utility scale”

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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Airborne CO2 coherent lidar measurements of cloud backscatter and opacity over the ocean surface

The use of an airborne CO2 lidar to obtain cloud backscatter and extinction data at a thermal infrared wavelength is described. The extinction in this spectral region is proportional to the cloud liquid water content. The use of coherent detection results in high sensitivity and narrow field of view, the latter property greatly reducing multiple-scattering effects. Backscatter measurements in absolute units are obtained through a hard target calibration methodology. For clouds of low to moderate optical thickness at the lidar wavelength, both geometric thickness and optical thickness can be measured. The sea surface reflectance signal is used to obtain estimates of the cloud optical thickness. The utility of this technique results from studies that indicate that the spatial scale of variability of the sea surface reflectance is generally large compared with that of cloud optical thickness. Selected results are presented from data taken during flights over the Pacific Ocean.

Menzies, Robert T.↗
NASA NTRS1995

Image applications for coastal resource planning: Elkhorn Slough Pilot Project

The purpose of this project has been to evaluate the utility of digital spectral imagery at two levels of resolution for large scale, accurate, auto-classification of land cover along the Central California Coast. Although remote sensing technology offers obvious advantages over on-the-ground mapping, there are substantial trade-offs that must be made between resolving power and costs. Higher resolution images can theoretically be used to identify smaller habitat patches, but they usually require more scenes to cover a given area and processing these images is computationally intense requiring much more computer time and memory. Lower resolution images can cover much larger areas, are less costly to store, process, and manipulate, but due to their larger pixel size can lack the resolving power of the denser images. This lack of resolving power can be critical in regions such as the Central California Coast where important habitat change often occurs on a scale of 10 meters. Our approach has been to compare vegetation and habitat classification results from two aircraft-based spectral scenes covering the same study area but at different levels of resolution with a previously produced ground-truthed land cover base map of the area. Both of the spectral images used for this project were of significantly higher resolution than the satellite-based LandSat scenes used in the C-CAP program. The lower reaches of the Elkhorn Slough watershed was chosen as an ideal study site because it encompasses a suite of important vegetation types and habitat loss processes characteristic of the central coast region. Dramatic habitat alterations have and are occurring within the Elkhorn Slough drainage area, including erosion and sedimentation, land use conversion, wetland loss, and incremental loss due to development and encroachnnent by agriculture. Additonally, much attention has already been focused on the Elkhorn Slough due to its status as a National Marine Education and Research Reserve and as part of the Monterey Bay National Marine Sanctuary. These destinations have resulted in a rich collection of prior spatial and temporal habitat data.

Kvitek, Rikk G.↗
NASA NTRS2001

Compact Plasma Accelerator for Micropropulsion Applications

There is a need for a low power, light-weight (compact), high specific impulse electric propulsion device to satisfy mission requirements for microsatellite (1 to 20 kg) class missions. Satisfying these requirements entails addressing the general problem of generating a sufficiently dense plasma within a relatively small volume and then accelerating it. In the work presented here, the feasibility of utilizing a magnetic cusp to generate a dense plasma over small length scales of order 1 mm is investigated. This approach could potentially mitigate scaling issues associated with conventional ion thruster plasma containment schemes. Plume and discharge characteristics were documented using a Faraday probe and a retarding potential analyzer.

Foster, John E.↗
NASA NTRS2006

Aerocapture Technology Development for Planetary Science - Update

Within NASA's Science Mission Directorate is a technological program dedicated to improving the cost, mass, and trip time of future scientific missions throughout the Solar System. The In-Space Propulsion Technology (ISPT) Program, established in 2001, is charged with advancing propulsion systems used in space from Technology Readiness Level (TRL) 3 to TRL6, and with planning activities leading to flight readiness. The program's content has changed considerably since inception, as the program has refocused its priorities. One of the technologies that has remained in the ISPT portfolio through these changes is Aerocapture. Aerocapture is the use of a planetary body's atmosphere to slow a vehicle from hyperbolic velocity to a low-energy orbit suitable for science. Prospective use of this technology has repeatedly shown huge mass savings for missions of interest in planetary exploration, at Titan, Neptune, Venus, and Mars. With launch vehicle costs rising, these savings could be the key to mission viability. This paper provides an update on the current state of the Aerocapture technology development effort, summarizes some recent key findings, and highlights hardware developments that are ready for application to Aerocapture vehicles and entry probes alike. Description of Investments: The Aerocapture technology area within the ISPT program has utilized the expertise around NASA to perform Phase A-level studies of future missions, to identify technology gaps that need to be filled to achieve flight readiness. A 2002 study of the Titan Explorer mission concept showed that the combination of Aerocapture and a Solar Electric Propulsion system could deliver a lander and orbiter to Titan in half the time and on a smaller, less expensive launch vehicle, compared to a mission using chemical propulsion for the interplanetary injection and orbit insertion. The study also identified no component technology breakthroughs necessary to implement Aerocapture on such a mission. Similar studies of Aerocapture applications at Neptune, Venus, and Mars were studied in 2003 through 2005. All showed significant performance improvements for the missions studied. Findings from these studies were used to guide the technology development tasks originally solicited in a 2002 NASA ROSS Research Announcement. The tasks are now in their final year and have provided numerous improvements in modeling and hardware, for use in proposals or new mission starts. Major Accomplishments: Since validation of the Aerocapture maneuver requires a space flight, ground developments have focused on modeling and environment prediction, materials, and sensors. Lockheed Martin has designed and built a 2-meter Carbon-Carbon aeroshell "hot structure." The article utilizes co-cured stiffening ribs and advanced insulation to achieve large scale, and up to a 40% reduction in areal density over the Genesis probe construction. This concept would be an efficient solution for probes that experience heat rates near 800-1000 W/cm(exp 2), such as at Venus and Earth. Applied Research Associates has extensively tested a family of efficient ablative TPS materials that provide solutions for a range of heating conditions. These materials are being applied to high-temperature structures built by ATK Space Systems, led by Langley Research Center. One-meter aeroshells will be thermally tested to validate construction and demonstrate higher bondline temperatures, which can lead to mass savings of up to 30% over traditional heatshields. Ames Research Center has developed aeroshell instrumentation that could measure environmental conditions and material performance during atmospheric entry. Instruments to measure TPS recession, heat flux, and catalycity could be combined with traditional sensors to provide a "plug-and-play" system for minimal mass and power, that would acquire flight data for model improvement and risk reduction on future missions. Improved atmospheric and aerothermodynamic models ha also been a major focus of the program. Next Steps: Aerocapture is one of five technologies in competition for a flight validation opportunity through the New Millennium Program. If selected, a fully autonomous vehicle will perform an Aerocapture at Earth in 2010, and flight data will be used to validate the guidance system and the TPS material for science mission infusion.

Munk, Michelle M.↗
NASA NTRS1977

Industrial Productivity

NASTRAN is an offshoot of the computer-design technique used in construction of airplanes and spacecraft. [n this technique engineers create a mathematical model of the aeronautical or space vehicle and "fly" it on the ground by means of computer simulation. The technique enables them to study performance and structural behavior of a number of different designs before settling on the final configuration and proceeding with construction. From this base of aerospace experience, NASA-Goddard developed the NASTRAN general purpose computer program, which offers an exceptionally wide range of analytic capability with regard to structures. NASTRAN has been applied to autos, trucks, railroad cars, ships, nuclear power reactors, steam turbines, bridges, and office buildings. NASA-Langley provides program maintenance services regarded as vital by many NASTRAN users. NASTRAN is essentially a predictive tool. It takes an electronic look at a computerire$.dedgn and reports how the structure will react under a great many different conditions. It can, for example, note areas where high stress levels will occur-potential failure points that need strengthening. Conversely, it can identify over-designed areas where weight and material might be saved safely. NASTRAN can tell how pipes stand up under strong fluid flow, how metals are affected by high temperatures, how a building will fare in an earthquake or how powerful winds will cause a bridge to oscillate. NASTRAN analysis is quick and inexpensive. It minimizes trial-and-error in the design process and makes possible better, safe, lighter structures affording large-scale savings in development time and materials. Some examples of the broad utility NASTRAN is finding among industrial firms are shown on these pages.

Source record↗
NASA NTRS2008

Observation of Solar Wind Charge Exchange Emission from Exospheric Material in and Outside Earth's Magnetosheath

A long XMM-Newton exposure is used to observe solar wind charge exchange (SWCX) emission from exospheric material in and outside Earth s magnetosheath. The light curve of the O VII (0.5-0.62 keV) band is compared with a model for the expected emission, and while the emission is faint and the light curve has considerable scatter, the correlation is significant to better than 99.9%. This result demonstrates the validity of the geocoronal SWCX emission model for predicting a contribution to astrophysical observations to a scale factor of order unity (1.36). The results also demonstrate the potential utility of using X-ray observations to study global phenomena of the magnetosheath which currently are only investigated using in situ measurements.

Snowden, S. L.↗
NASA NTRS2009

Satellite Proving Ground for the GOES-R Geostationary Lightning Mapper (GLM)

The key mission of the Satellite Proving Ground is to demonstrate new satellite observing data, products and capabilities in the operational environment to be ready on Day 1 to use the GOES-R suite of measurements. Algorithms, tools, and techniques must be tested, validated, and assessed by end users for their utility before they are finalized and incorporated into forecast operations. The GOES-R Proving Ground for the Geostationary Lightning Mapper (GLM) focuses on evaluating how the infusion of the new technology, algorithms, decision aids, or tailored products integrate with other available tools (weather radar and ground strike networks; nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing forecasts and warning products. Additionally, the testing concept fosters operation and development staff interactions which will improve training materials and support documentation development. Real-time proxy total lightning data from regional VHF lightning mapping arrays (LMA) in Northern Alabama, Central Oklahoma, Cape Canaveral Florida, and the Washington, DC Greater Metropolitan Area are the cornerstone for the GLM Proving Ground. The proxy data will simulate the 8 km Event, Group and Flash data that will be generated by GLM. Tailored products such as total flash density at 1-2 minute intervals will be provided for display in AWIPS-2 to select NWS forecast offices and national centers such as the Storm Prediction Center. Additional temporal / spatial combinations are being investigated in coordination with operational needs and case-study proxy data and prototype visualizations may also be generated from the NASA heritage Lightning Imaging Sensor and Optical Transient Detector data. End users will provide feedback on the utility of products in their operational environment, identify use cases and spatial/temporal scales of interest, and provide feedback to the developers for adjusted or new products.

Goodman, Steven J.↗
NASA NTRS1994

Influence of Incidence Angle on Sound Generation by Airfoils Interacting with High-Frequency Gusts

A theoretical model is developed for the sound generated when a convected vortical or entropic gust encounters an airfoil at nonzero angle of attack. The theory is based on a linearization of the Euler equations about the steady, subsonic flow past the airfoil. High-frequency gusts, whose wavelengths are short compared to the airfoil chord, but long compared to the displacement of the mean-flow stagnation point from the leading edge, are considered. The analysis utilizes singular perturbation techniques and involves four asymptotic regions. Local regions, which scale on the gust wavelength, are present at the airfoil leading and trailing edges. Behind the airfoil a "transition" region, which is similar to the transition zone between illuminated and shadow zones in optical problems, is present. In the outer region, far away from the airfoil edges and wake, the solution has a geometric-acoustics form. The primary sound generation is found to be concentrated in the local leading-edge region. The trailing edge plays a secondary role as a scatterer of the sound generated in the leading-edge region. Parametric calculations are presented which illustrate that moderate levels of airfoil steady loading can significantly affect the sound field produced by airfoil-gust interactions.

Matthew R. Myers↗
DOE OSTI2020

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids: Preprint

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. Different types of DERs such as Photovoltaics (PV), energy storage, electric vehicles (EVs), etc. have varying effects on the grid based on how and where they are deployed. Again, the DER deployment and its impact are network-dependent, while the traditional electric grids were not designed to host DERs. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper investigates the impacts of integrating a mix of DERs in the utility distribution network in Colorado, U.S. Firstly, BTM DERs at the residential scale including distributed PV; battery energy storage systems (BESS); heating, ventilation, and air-conditioning (HVAC) load; electric water heater (EWH) load; and EVs are modeled. The impacts of integrating these resources on the distribution network are evaluated by conducting time-series simulations for different scenarios considering different days to capture the worst-case conditions. Monte Carlo simulations are conducted to generate the realistic EV charging profile. The voltage issues, substation transformer loadings, and critical nodes in the network are identified with the incorporation of uncoordinated EV charging loads and other DER in the network. This analysis helps visualize the DER impact on the grid, identify the challenges, and provides an insight into the new distribution management and control needs to enable reliable and resilient distribution grid operations. Additionally, further analysis is performed to estimate the daily residential electricity cost with the inclusion of DERs under time-of-use tariffs. The result shows the daily residential electricity cost reduced by 20:7% on average with DERs compared to the case without DERs.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Physics-Based Feature Extraction from Bulk Time-Series PMU Datasets for Event Detection

In this work, two physics-based feature extraction techniques are developed for bulk time-series phasor measurement unit (PMU) datasets collected from the field to train the machine learning model for anomaly detection. Two approaches have been developed to extract useful features for different types of events. An admittance-based feature extraction technique is developed to detect events that involve line outages and system topology variations. The developed algorithm extracts the system equivalent admittance variation. Additionally, Fielder’s Theory is utilized to further reduce the potential computation burden by sectionalizing large-scale grids and datasets into smaller areas. Second, an oscillation-based feature extraction technique is developed to detect low-frequency oscillations in power grids. The dominant oscillation modes in the grids are extracted using energy-sorted Prony analysis. The extracted dominant oscillation modes by the developed work exhibit a high fitting resolution. Finally, the developed techniques have been validated using large-scale and real-world datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗
DOE OSTI2025

Across the Scales of the Nucleus: Understanding Short Range Correlations from Medium Modification to Probe Independence

The atomic nucleus presents an intricate system due to the non-linear forces described by Quantum Chromodynamics (QCD) that govern its structure. The range of scales involved is remarkable; the most massive nuclei weigh approximately five orders of magnitude more than the quarks that compose them. The nucleus can be analyzed at various levels, from quarks to hadrons to the nucleus as a whole. Short-Range Correlations (SRCs) within the nucleus play a significant role that spans these diverse scales. At the most fundamental level, SRCs influence the interaction between nucleons. The nucleon-nucleon (NN) interaction, arising from QCD, is crucial in determining nuclear properties. SRCs serve as valuable probes for measuring this NN interaction, as the nucleons within SRCs become effectively decoupled from the rest of the nucleus. Multiple experimental techniques, including electron scattering, have been employed to investigate the NN interaction through SRCs. However, our first project demonstrates that inclusive measurements alone are inadequate to constrain this interaction fully. Moving to the scale of the nucleus, SRCs contribute to the high-momentum tail of the nuclear spectral function. While the low-momentum region is characterized by nucleons exhibiting bulk properties, nucleons begin to pair into SRCs at higher momenta. Our research aims to bridge the understanding between the mean-field portion of the nucleus and its high-momentum SRC components. Additionally, SRCs affect the quark structure of protons, as evidenced by the EMC effect, which indicates that quarks behave differently when protons are embedded within a nucleus—an effect referred to as medium modification. This thesis explores the correlation between SRCs and medium modification across various experimental setups. Finally, we seek to establish an interpretation of the nuclear ground state. Accomplishing this requires demonstrating that our SRC observables are independent of the probe’s scale and scheme. The concluding project of this thesis illustrates how we utilize triple coincidence quasi-elastic scattering across a range of (Q2) values to develop a model-dependent framework for understanding SRC distributions within the nucleus’s ground-state wavefunction.

Denniston, A. W. Denniston [University of Tel Aviv↗
DOE OSTI2023

Domain Adaptation for Measurements of Strong Gravitational Lenses

Upcoming surveys are predicted to discover galaxy-scale strong lenses on the order of $10^5$, making deep learning methods necessary in lensing data analysis. Currently, there is insufficient real lensing data to train deep learning algorithms, but the alternative of training only on simulated data results in poor performance on real data. Domain Adaptation may be able to bridge the gap between simulated and real datasets. We utilize domain adaptation for the estimation of Einstein radius ($\Theta_E$) in simulated galaxy-scale gravitational lensing images with different levels of observational realism. We evaluate two domain adaptation techniques - Domain Adversarial Neural Networks (DANN) and Maximum Mean Discrepancy (MMD). We train on a source domain of simulated lenses and apply it to a target domain of lenses simulated to emulate noise conditions in the Dark Energy Survey (DES). We show that both domain adaptation techniques can significantly improve the model performance on the more complex target domain dataset. This work is the first application of domain adaptation for a regression task in strong lensing imaging analysis. Our results show the potential of using domain adaptation to perform analysis of future survey data with a deep neural network trained on simulated data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2015

Comparison of Instantaneous Frequency Scaling from Rain Attenuation and Optical Disdrometer Measurements at K/Q bands

Rain attenuation is strongly dependent on the rain rate, but also on the rain drop size distribution (DSD). Typically, models utilize an average drop size distribution, such as those developed by Laws and Parsons, or Marshall and Palmer. However, individual rain events may possess drop size distributions which could be significantly different from the average and will impact, for example, fade mitigation techniques which utilize channel performance estimates from a signal at a different frequency. Therefore, a good understanding of the characteristics and variability of the raindrop size distribution is extremely important in predicting rain attenuation and instantaneous frequency scaling parameters on an event-toevent basis. Since June 2014, NASA Glenn Research Center (GRC) and the Politecnico di Milano (POLIMI) have measured the attenuation due to rain in Milan, Italy, on the 20/40 GHz beacon signal broadcast from the Alphasat TDP#5 Aldo Paraboni Q/V-band Payload. Concomitant with these measurements are the measurements of drop size distribution and rain rate utilizing a Thies Clima laser precipitation monitor (disdrometer). In this paper, we discuss the comparison of the predicted rain attenuation at 20 and 40 GHz derived from the drop size distribution data with the measured rain attenuation. The results are compared on statistical and real-time bases. We will investigate the performance of the rain attenuation model, instantaneous frequency scaling, and the distribution of the scaling factor. Further, seasonal rain characteristics will be analysed.

millimeter wave↗
DOE OSTI2023

Domain Adaptation for Measurements of Strong Gravitational Lenses

Upcoming surveys are predicted to discover galaxy-scale strong lenses on the order of 10\textsuperscript{5}, making deep learning methods necessary in lensing data analysis. Currently, there is insufficient real lensing data to train deep learning algorithms, but the alternative of training only on simulated data results in poor performance on real data. Domain Adaptation may be able to bridge the gap between simulated and real datasets. We utilize domain adaptation for the estimation of Einstein radius ($\Theta_E$) in simulated galaxy-scale gravitational lensing images with different levels of observational realism. We evaluate two domain adaptation techniques - Domain Adversarial Neural Networks (DANN) and Maximum Mean Discrepancy (MMD). We train on a source domain of simulated lenses and apply it to a target domain of lenses simulated to emulate noise conditions in the Dark Energy Survey (DES). We show that both domain adaptation techniques can significantly improve the model performance on the more complex target domain dataset. This work is the first application of domain adaptation for a regression task in strong lensing imaging analysis. Our results show the potential of using domain adaptation to perform analysis of future survey data with a deep neural network trained on simulated data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1993

Transition aerodynamics for 20-percent-scale VTOL unmanned aerial vehicle

An investigation was conducted in the Langley 14- by 22-Foot Subsonic Tunnel to establish a transition data base for an unmanned aerial vehicle utilizing a powered-lift ejector system and to evaluate alterations to the ejector system for improved vehicle performance. The model used in this investigation was a 20-percent-scale, blended-body, arrow-wing configuration with integrated twin rectangular ejectors. The test was conducted from hover through transition conditions with variations in angle of attack, angle of sideslip, free-stream dynamic pressure, nozzle pressure ratio, and model ground height. Force and moment data along with extensive surface pressure data were obtained. A laser velocimeter technique for measuring inlet flow velocities was demonstrated at a single flow condition, and also a low order panel method was successfully used to numerically simulate the ejector inlet flow.

Kjerstad, Kevin J.↗
DOE OSTI2020

Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data

Nationwide population-based cohort provides a new opportunity to build an automated risk prediction model based on individuals’ history of health and healthcare beyond existing risk prediction models. We tested the possibility of machine learning models to predict future incidence of Alzheimer’s disease (AD) using large-scale administrative health data. From the Korean National Health Insurance Service database between 2002 and 2010, we obtained de-identified health data in elders above 65 years (N = 40,736) containing 4,894 unique clinical features including ICD-10 codes, medication codes, laboratory values, history of personal and family illness and socio-demographics. To define incident AD we considered two operational definitions: “definite AD” with diagnostic codes and dementia medication (n = 614) and “probable AD” with only diagnosis (n = 2026). We trained and validated random forest, support vector machine and logistic regression to predict incident AD in 1, 2, 3, and 4 subsequent years. For predicting future incidence of AD in balanced samples (bootstrapping), the machine learning models showed reasonable performance in 1-year prediction with AUC of 0.775 and 0.759, based on “definite AD” and “probable AD” outcomes, respectively; in 2-year, 0.730 and 0.693; in 3-year, 0.677 and 0.644; in 4-year, 0.725 and 0.683. The results were similar when the entire (unbalanced) samples were used. Important clinical features selected in logistic regression included hemoglobin level, age and urine protein level. This study may shed a light on the utility of the data-driven machine learning model based on large-scale administrative health data in AD risk prediction, which may enable better selection of individuals at risk for AD in clinical trials or early detection in clinical settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Carbon Dioxide Refinery: The Core of a Sustainable Carbon-based Circular Economy

The atmospheric carbon dioxide (CO 2 ) accumulation (2–2.5 ppmv/year) is the result of the enormous gap between its emissions (37 Gton/year) and its capture, storage, and utilization (<500 Mton/year). Climate has been dramatically affected due to the failure of natural sinks, in working effectively. To address this Gton-scale gap, numerous uses and applications are needed particularly, those consuming vast volumes of this compound and/or rendering longevous products or long lifecycle services. Thus, carbon utilization (CU) can be seen as the step to close the carbon cycle. Among CU, R&D on CO 2 chemical conversion has proposed a variety of processes, with different degrees of developmental maturity. These chemical process technologies could be efficiently and effectively integrated into refineries to upgrade emitted CO 2 . A technology pipeline consisting of a database of these processes and the technology market status should be defined based on published scientific results and patents. Then, an innovative top-down methodology is proposed to eco-design configurations of that refinery, to warrant a sustainable carbon cycle (in terms of energy, environment, and economy) and to change the ways of producing fuels, chemicals, and materials. Additionally, the proposed methodology could be used to identify research and development gaps and needs, for orienting science and technology investments and measures. Hopefully, sustainable CO 2 refineries will be implemented to close the carbon cycle of a circular C-based economy and underpin a decarbonized chemical industry.

54 ENVIRONMENTAL SCIENCES↗