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At least 451 records · Page 25

Lunar in-core thermionic nuclear reactor power system conceptual design

This paper presents a conceptual design of a lunar in-core thermionic reactor power system. The concept consists of a thermionic reactor located in a lunar excavation with surface mounted waste heat radiators. The system was integrated with a proposed lunar base concept representative of recent NASA Space Exploration Initiative studies. The reference mission is a permanently-inhabited lunar base requiring a 550 kWe, 7 year life central power station. Performance parameters and assumptions were based on the Thermionic Fuel Element (TFE) Verification Program. Five design cases were analyzed ranging from conservative to advanced. The cases were selected to provide sensitivity effects on the achievement of TFE program goals.

Mason, Lee S.↗

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^8 determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

J Wayne Mullinax↗

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗

Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond

In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying ns and allowing for w 0 w a CDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within 1σ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models.

79 ASTRONOMY AND ASTROPHYSICS↗

Space-Based Solar Power: An Enabler for Expanded Lunar Surface Exploration and Mobility Operations

The achievement of industrial and scientific goals set by the National Aeronautics and Space Administration (NASA) Artemis missions within the Moon to Mars (M2M) architecture greatly relies on the breadth and efficacy of lunar surface exploration. The lunar surface environment presents various challenges and complexities to sustainable mission operations and activities. Power generation and distribution capabilities are vital for exploration on the lunar surface, which can enable activities such as subsurface sample collection, permanently shadowed region (PSR) prospecting, and lunar terrain mapping. Innovative power technologies that demonstrate flexibility, reliability, and high capacity are desirable to achieve sustainable operations and infrastructure on the lunar surface. Studies have proposed solar-powered spacecraft in cislunar orbit capable of beaming power to lunar surface assets as a solution to this problem. This study analyzes the benefit that space-based solar power (SBSP) assets could deliver to the M2M architecture by measuring its potential to augment lunar surface exploration opportunity. Qualitative measures of SBSP’s potential impact will include, but not be limited to, power available across surface elements, surface mobility range, and delivered landed mass. These measures are assessed for a notional surface architecture measured against its baseline configuration (no external power augmentation). Additionally, this presentation will provide an overview of the SBSP system design configuration trade space, subsystem parameter trade space, and results from preliminary spacecraft concept of operations (ConOps) and sizing.

Space-based solar power↗

Basin & Range Investigation for Developing Geothermal Energy

Hidden geothermal systems represent a potentially prolific energy resource that could support critical U.S. public and government energy priorities. Basin and Range Investigations for Developing Geothermal Energy (BRIDGE) addressed some the challenges associated with hidden system exploration by prioritizing cost-effective exploration early on through strategic workflow and informed decision-making that mitigates early risk and shifts resources to later exploration stages (e.g., drilling). Sandia National Laboratories partnered with U.S. Navy Geothermal Office, Geologic Geothermal Group, and independent consultants, with additional collaboration with U.S. Geological Survey and private industry. The primary tool of the BRIDGE project was to deploy a regional-scale airborne electromagnetic method to investigate the shallow resistivity structure in areas with high prospectivity. This was followed up at several prospects by a multidisciplinary exploration approach, including additional geologic, geophysical and geochemical studies. A central tenet to the BRIDGE methodology is that zones of low resistivity frequently occur over geothermal systems in the Basin and Range, and when paired with other data constraints, imaging these zones can enable discovery of these systems. In addition to exploring greenfield areas (i.e., Grover Point), the BRIDGE project also flew HTEM resistivity surveys over known geothermal systems including those with established power plants (Don A. Campbell and Salt Wells) and prospects that are known to the literature but remain undeveloped, at least in part, due to a lack of understanding on the location of their producible reservoirs. BRIDGE produced a comprehensive set of data from prospects identified in the Nevada Play Fairway Analysis along with conceptual models for top ranking prospects, wherein all of the observations are used to inform an interpreted model of the system. These models present a range of possible system parameters such as temperature and size, and they are further informed by system analogues in the Basin and Range province and elsewhere. The results of this work leave space for further exploration that may now occur at prospects ‘down the list’ rather than distribution exploration resources evenly across all prospects.

15 GEOTHERMAL ENERGY↗

Exploring Cognition Using Software Defined Radios for NASA Missions

NASA missions typically operate using a communication infrastructure that requires significant schedule planning with limited flexibility when the needs of the mission change. Parameters such as modulation, coding scheme, frequency, and data rate are fixed for the life of the mission. This is due to antiquated hardware and software for both the space and ground assets and a very complex set of mission profiles. Automated techniques in place by commercial telecommunication companies are being explored by NASA to determine their usability by NASA to reduce cost and increase science return. Adding cognition the ability to learn from past decisions and adjust behavior is also being investigated. Software Defined Radios are an ideal way to implement cognitive concepts. Cognition can be considered in many different aspects of the communication system. Radio functions, such as frequency, modulation, data rate, coding and filters can be adjusted based on measurements of signal degradation. Data delivery mechanisms and route changes based on past successes and failures can be made to more efficiently deliver the data to the end user. Automated antenna pointing can be added to improve gain, coverage, or adjust the target. Scheduling improvements and automation to reduce the dependence on humans provide more flexible capabilities. The Cognitive Communications project, funded by the Space Communication and Navigation Program, is exploring these concepts and using the SCaN Testbed on board the International Space Station to implement them as they evolve. The SCaN Testbed contains three Software Defined Radios and a flight computer. These four computing platforms, along with a tracking antenna system and the supporting ground infrastructure, will be used to implement various concepts in a system similar to those used by missions. Multiple universities and SBIR companies are supporting this investigation. This paper will describe the cognitive system ideas under consideration and the plan for implementing them on platforms, including the SCaN Testbed. Discussions in the paper will include how these concepts might be used to reduce cost and improve the science return for NASA missions.

transmitters receivers↗

The SOUX AGN sample: SDSS– XMM-Newton optical, ultraviolet, and X-ray selected active galactic nuclei spanning a wide range of parameter space – sample definition

Abstract We assemble a sample of 696 type 1 active galactic nuclei (AGN) up to a redshift of z = 2.5, all of which have an SDSS spectrum containing at least one broad emission line (H α, H β, or Mg ii) and an XMM-Newton X-ray spectrum containing at least 250 counts in addition to simultaneous optical/ultraviolet photometry from the XMM Optical Monitor. Our sample includes quasars and narrow-line Seyfert 1s: thus our AGN span a wide range in luminosity, black hole mass, and accretion rate. We determine single-epoch black hole mass relations for the three emission lines and find that they provide broadly consistent mass estimates whether the continuum or emission line luminosity is used as the proxy for the broad emission line region radius. We explore variations of the UV/X-ray energy index αox with the UV continuum luminosity and with black hole mass and accretion rate, and make comparisons to the physical quasar spectral energy distribution model qsosed. The majority of the AGN in our sample lie in a region of parameter space with 0.02 < L/LEdd < 2 as defined by this model, with narrow-line type 1 AGN offset to lower masses and higher accretion rates than typical broad-line quasars. We find differences in the dependence of αox on UV luminosity between both narrow/broad-line and radio-loud/quiet subsets of AGN: αox has a slightly weaker dependence on UV luminosity for broad-line AGN and radio-loud AGN have systematically harder αox.

79 ASTRONOMY AND ASTROPHYSICS↗

Risk management for the Space Exploration Initiative

Probabilistic Risk Assessment (PRA) is a quantitative engineering process that provides the analytic structure and decision-making framework for total programmatic risk management. Ideally, it is initiated in the conceptual design phase and used throughout the program life cycle. Although PRA was developed for assessment of safety, reliability, and availability risk, it has far greater application. Throughout the design phase, PRA can guide trade-off studies among system performance, safety, reliability, cost, and schedule. These studies are based on the assessment of the risk of meeting each parameter goal, with full consideration of the uncertainties. Quantitative trade-off studies are essential, but without full identification, propagation, and display of uncertainties, poor decisions may result. PRA also can focus attention on risk drivers in situations where risk is too high. For example, if safety risk is unacceptable, the PRA prioritizes the risk contributors to guide the use of resources for risk mitigation. PRA is used in the Space Exploration Initiative (SEI) Program. To meet the stringent requirements of the SEI mission, within strict budgetary constraints, the PRA structure supports informed and traceable decision-making. This paper briefly describes the SEI PRA process.

Buchbinder, Ben↗

Effect of Engine Thrust and Isp Tradeoffs and Alternate Propellants on ΔV Budget and Architecture Mass for 1st Generation Nuclear Thermal Propulsion Flight Test Systems

Following the first Nuclear Thermal Propulsion (NTP) system test, also known as DRACO, the next NTP system to be developed would be the 1st Generation NTP system. An analysis was conducted to determine the performance of different vehicle configurations utilizing hydrogen (H-NTP), ammonia (A-NTP), and methane (M-NTP) as propellants launched onboard commercial launch vehicles. This was enabled by a quasi-steady-state power balance engine model and vehicle component physics that sized the vehicle system using Master Equipment List (MEL) parameters. The analysis considered configuration cases outlined by a matrix of different mission classes and vehicle configurations that covered the design space of the 1st Generation NTP system to explore various propellant options, engine architectures, and mission scopes. Four mission classes were evaluated which included single burn missions performing maneuvers having a ΔV of 1 km/s and 2.5 km/s followed by 2-burn and 4-burn missions that aimed to exhaust the launch vehicles volume or mass limitations. In all cases, the NTP systems with the lowest thrust class had the longest burn time of which A-NTP and M-NTP systems provided the longest and shortest burn times depending on the launch vehicle used while H-NTP systems tended to cluster together in the middle. Longer burn times could be useful as a testing platform to increase the time for data accumulation. Across the multi-burn cases, H-NTP systems were found to be volume limited while A-NTP and M-NTP systems were mass limited. Both single burn missions showed that A-NTP configurations provided the lowest dry mass given that ammonia had the highest density with comparable performance to M-NTP systems and no requirement for cryocoolers. The results showed that beyond the propellant selection type, the launch vehicle selection, which included Starship, New Glenn, Vulcan, Falcon 9 (recoverable), and Falcon Heavy (recoverable), was a primary driving factor in the test vehicle’s capabilities. Trends were determined based on a set of dimensionless parameters that included the mass ratio of inert mass to initial wetted mass, ratio of specific impulse to burn time, and a dimensionless engine parameter (ratio of impulse to engine momentum). These relationships found the “knees-in-the-curves” that could be a significant point of reference for the designer as they indicate a change in the trend which is located at a specific impulse to burn time ratio of 1, a mass ratio of 0.6, and an engine performance parameter of 4. This study did not attempt to make a recommendation rather provide the tools for the reader to select their own configuration based on their needs.

Propellant↗

Effect of Engine Thrust and Isp Tradeoffs and Alternate Propellants on ΔV Budget and Architecture Mass for 1st Generation Nuclear Thermal Propulsion Flight Test Systems

Following the first Nuclear Thermal Propulsion (NTP) system test, also known as DRACO, the next NTP system to be developed would be the 1st Generation NTP system. An analysis was conducted to determine the performance of different vehicle configurations utilizing hydrogen (H-NTP), ammonia (A-NTP), and methane (M-NTP) as propellants launched onboard commercial launch vehicles. This was enabled by a quasi-steady-state power balance engine model and vehicle component physics that sized the vehicle system using Master Equipment List (MEL) parameters. The analysis considered configuration cases outlined by a matrix of different mission classes and vehicle configurations that covered the design space of the 1st Generation NTP system to explore various propellant options, engine architectures, and mission scopes. Four mission classes were evaluated which included single burn missions performing maneuvers having a ΔV of 1 km/s and 2.5 km/s followed by 2-burn and 4-burn missions that aimed to exhaust the launch vehicles volume or mass limitations. In all cases, the NTP systems with the lowest thrust class had the longest burn time of which A-NTP and M-NTP systems provided the longest and shortest burn times depending on the launch vehicle used while H-NTP systems tended to cluster together in the middle. Longer burn times could be useful as a testing platform to increase the time for data accumulation. Across the multi-burn cases, H-NTP systems were found to be volume limited while A-NTP and M-NTP systems were mass limited. Both single burn missions showed that A-NTP configurations provided the lowest dry mass given that ammonia had the highest density with comparable performance to M-NTP systems and no requirement for cryocoolers. The results showed that beyond the propellant selection type, the launch vehicle selection, which included Starship, New Glenn, Vulcan, Falcon 9 (recoverable), and Falcon Heavy (recoverable), was a primary driving factor in the test vehicle’s capabilities. Trends were determined based on a set of dimensionless parameters that included the mass ratio of inert mass to initial wetted mass, ratio of specific impulse to burn time, and a dimensionless engine parameter (ratio of impulse to engine momentum). These relationships found the “knees-in-the-curves” that could be a significant point of reference for the designer as they indicate a change in the trend which is located at a specific impulse to burn time ratio of 1, a mass ratio of 0.6, and an engine performance parameter of 4. This study did not attempt to make a recommendation rather provide the tools for the reader to select their own configuration based on their needs.

Propellant↗

Effect of Engine Thrust and Isp Tradeoffs and Alternate Propellants on ΔV Budget and Architecture Mass for 1st Generation Nuclear Thermal Propulsion Flight Test Systems

Following the first Nuclear Thermal Propulsion (NTP) system test, also known as DRACO, the next NTP system to be developed would be the 1st Generation NTP system. An analysis was conducted to determine the performance of different vehicle configurations utilizing hydrogen (H-NTP), ammonia (A-NTP), and methane (M-NTP) as propellants launched onboard commercial launch vehicles. This was enabled by a quasi-steady-state power balance engine model and vehicle component physics that sized the vehicle system using Master Equipment List (MEL) parameters. The analysis considered configuration cases outlined by a matrix of different mission classes and vehicle configurations that covered the design space of the 1st Generation NTP system to explore various propellant options, engine architectures, and mission scopes. Four mission classes were evaluated which included single burn missions performing maneuvers having a ΔV of 1 km/s and 2.5 km/s followed by 2-burn and 4-burn missions that aimed to exhaust the launch vehicles volume or mass limitations. In all cases, the NTP systems with the lowest thrust class had the longest burn time of which A-NTP and M-NTP systems provided the longest and shortest burn times depending on the launch vehicle used while H-NTP systems tended to cluster together in the middle. Longer burn times could be useful as a testing platform to increase the time for data accumulation. Across the multi-burn cases, H-NTP systems were found to be volume limited while A-NTP and M-NTP systems were mass limited. Both single burn missions showed that A-NTP configurations provided the lowest dry mass given that ammonia had the highest density with comparable performance to M-NTP systems and no requirement for cryocoolers. The results showed that beyond the propellant selection type, the launch vehicle selection, which included Starship, New Glenn, Vulcan, Falcon 9 (recoverable), and Falcon Heavy (recoverable), was a primary driving factor in the test vehicle’s capabilities. Trends were determined based on a set of dimensionless parameters that included the mass ratio of inert mass to initial wetted mass, ratio of specific impulse to burn time, and a dimensionless engine parameter (ratio of impulse to engine momentum). These relationships found the “knees-in-the-curves” that could be a significant point of reference for the designer as they indicate a change in the trend which is located at a specific impulse to burn time ratio of 1, a mass ratio of 0.6, and an engine performance parameter of 4. This study did not attempt to make a recommendation rather provide the tools for the reader to select their own configuration based on their needs.

Propellant↗

NASCAP simulation of PIX 2 experiments

The latest version of the NASCAP/LEO digital computer code used to simulate the PIX 2 experiment is discussed. NASCAP is a finite-element code and previous versions were restricted to a single fixed mesh size. As a consequence the resolution was dictated by the largest physical dimension to be modeled. The latest version of NASCAP/LEO can subdivide selected regions. This permitted the modeling of the overall Delta launch vehicle in the primary computational grid at a coarse resolution, with subdivided regions at finer resolution being used to pick up the details of the experiment module configuration. Langmuir probe data from the flight were used to estimate the space plasma density and temperature and the Delta ground potential relative to the space plasma. This information is needed for input to NASCAP. Because of the uncertainty or variability in the values of these parameters, it was necessary to explore a range around the nominal value in order to determine the variation in current collection. The flight data from PIX 2 were also compared with the results of the NASCAP simulation.

Roche, J. C.↗

Spatial and Temporal Scaling of Thermal Infrared Remote Sensing Data

Although remote sensing has a central role to play in the acquisition of synoptic data obtained at multiple spatial and temporal scales to facilitate our understanding of local and regional processes as they influence the global climate, the use of thermal infrared (TIR) remote sensing data in this capacity has received only minimal attention. This results from some fundamental challenges that are associated with employing TIR data collected at different space and time scales, either with the same or different sensing systems, and also from other problems that arise in applying a multiple scaled approach to the measurement of surface temperatures. In this paper, we describe some of the more important problems associated with using TIR remote sensing data obtained at different spatial and temporal scales, examine why these problems appear as impediments to using multiple scaled TIR data, and provide some suggestions for future research activities that may address these problems. We elucidate the fundamental concept of scale as it relates to remote sensing and explore how space and time relationships affect TIR data from a problem-dependency perspective. We also describe how linearity and non-linearity observation versus parameter relationships affect the quantitative analysis of TIR data. Some insight is given on how the atmosphere between target and sensor influences the accurate measurement of surface temperatures and how these effects will be compounded in analyzing multiple scaled TIR data. Last, we describe some of the challenges in modeling TIR data obtained at different space and time scales and discuss how multiple scaled TIR data can be used to provide new and important information for measuring and modeling land-atmosphere energy balance processes.

Quattrochi, Dale A.↗

Soft-Fault Detection Technologies Developed for Electrical Power Systems

The NASA Glenn Research Center, partner universities, and defense contractors are working to develop intelligent power management and distribution (PMAD) technologies for future spacecraft and launch vehicles. The goals are to provide higher performance (efficiency, transient response, and stability), higher fault tolerance, and higher reliability through the application of digital control and communication technologies. It is also expected that these technologies will eventually reduce the design, development, manufacturing, and integration costs for large, electrical power systems for space vehicles. The main focus of this research has been to incorporate digital control, communications, and intelligent algorithms into power electronic devices such as direct-current to direct-current (dc-dc) converters and protective switchgear. These technologies, in turn, will enable revolutionary changes in the way electrical power systems are designed, developed, configured, and integrated in aerospace vehicles and satellites. Initial successes in integrating modern, digital controllers have proven that transient response performance can be improved using advanced nonlinear control algorithms. One technology being developed includes the detection of "soft faults," those not typically covered by current systems in use today. Soft faults include arcing faults, corona discharge faults, and undetected leakage currents. Using digital control and advanced signal analysis algorithms, we have shown that it is possible to reliably detect arcing faults in high-voltage dc power distribution systems (see the preceding photograph). Another research effort has shown that low-level leakage faults and cable degradation can be detected by analyzing power system parameters over time. This additional fault detection capability will result in higher reliability for long-lived power systems such as reusable launch vehicles and space exploration missions.

Button, Robert M.↗

The Chaotic Long-Term X-Ray Variability of 4U 1705-44

The low-mass X-ray binary 4U1705-44 exhibits dramatic long-term X-ray time variability with a time-scale of several hundred days. The All-SkyMonitor (ASM) aboard the Rossi X-ray Timing Explorer (RXTE) and the Japanese Monitor of All-sky X-ray Image (MAXI) aboard the International Space Station together have continuously observed the source from 1995 December through 2014 May. The combined ASM-MAXI data provide a continuous time series over 50 times the length of the time-scale of interest. Topological analysis can help us identify 'fingerprints' in the phase space of a system unique to its equations of motion. The Birman-Williams theorem postulates that if such fingerprints are the same between two systems, then their equations of motion must be closely related. The phase-space embedding of the source light curve shows a strong resemblance to the double-welled non-linear Duffing oscillator. We explore a range of parameters for which the Duffing oscillator closely mirrors the time evolution of 4U1705-44. We extract low period, unstable periodic orbits from the 4U1705-44 and Duffing time series and compare their topological information. The Duffing and 4U1705-44 topological properties are identical, providing strong evidence that they share the same underlying template. This suggests that we can look to the Duffing equation to help guide the development of a physical model to describe the long-term X-ray variability of this and other similarly behaved X-ray binary systems.

Rossi X-ray Timing Explorer (RXTE)↗

Identifying geologic characteristics and operational decisions to meet global carbon sequestration goals

Geologic carbon sequestration is the process of injecting and storing CO 2 in subsurface reservoirs and is an essential technology for global environmental security (e.g., climate change mitigation) and economic security (e.g., CO 2 tax credits). To meet energy, economic, and environmental goals, society will have to identify vast volumes of high-capacity, low-cost, and viable storage reservoirs for sequestering CO 2 . In turn, this requires understanding how major geologic characteristics (such as reservoir depth, thickness, permeability, porosity, and temperature) and design and operational decisions (such as injection well spacing) impact CO 2 injection rates, storage capacity, and economics. Although many numerical simulation tools exist, they cannot repeat the required thousands or millions of simulations to identify ideal reservoir properties and the sensitivity and interaction between geologic parameters and operational decisions. Here, we use SCO 2 T—a fast-running, reduced-order modeling framework—to explore the sensitivity of major geologic parameters and operational decisions to engineering (CO 2 injection rates, plume dimensions, and storage capacities and effectiveness) and costs. Our results show, for the first time, benefits and impacts such as allowing CO 2 plumes to overlap, how different well spacing patterns affect CO 2 sequestration, the effects on costs of including brine treatment and disposal, and the effect of restricting injection rates to 1 MtCO 2 per y based on well limitations. We reveal multiple novel and unintuitive findings including: (i) deeper reservoirs have reduced carbon sequestration costs until injection rates reach 1 MtCO 2 per y, at which point deeper reservoirs become more expensive, (ii) thicker formations allow for increased injection rates and storage capacity, but thickness barely impacts plume areas, (iii) higher geothermal gradients result in reduced sequestration costs, unless brine treatment/disposal costs are included, at which point reservoirs having lower geothermal gradients are more economical because they produce less brine for each unit of injected CO 2 , and (iv) allowing plumes to overlap has a significantly positive impact of increasing storage capacities but has only a small influence on reducing sequestration costs. Altogether, our results illustrate new scientific conclusions to help identify suitable sites to inject and store CO 2 , to help understand the complex interaction between geology and resulting costs, and to help support the pursuit of meeting global sequestration targets.

58 GEOSCIENCES↗