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At least 55 records · Page 3

Analyzing SCM Grid Benefits from Electric Transportation [Slides]

Increasing adoption of EVs and expanding unmanaged charging loads could increase the cost of transportation energy due to increasing load variability and shrinking infrastructure capacity. The actual cost of transportation energy, such as charging an EV, depends on several factors including energy costs, charging infrastructure costs, and applicable grid upgrades. Based on studies from past DOE projects; RECHARGE, DirectXFC, FUSE and 21st Century Truck Partnership (21CTP) the EV-CENTS project will develop a transportation energy cost metric to better quantify these factors and provide a framework for assessing the value potential of new technology solutions, such as smart charge management (SCM), which could reduce these costs for all stakeholders. The initial assessment will focus on the cost of charging, which will vary across vehicle classes such as light-duty vehicles (LDV) or medium and heavy-duty vehicles (MHDV), as well as across different vocations resulting in many different use cases for this metric. Cost of charging results will be developed for each use case in both uncontrolled and controlled scenarios to understand the value potential of different SCM objective functions and their ability to optimize the cost of energy and delay or eliminate the need for electrical upgrades.

33 ADVANCED PROPULSION SYSTEMS↗

Bio-project “derisking” through development of systematic methodologies and frameworks for risk assessment

One of the primary hindrances to producing a viable, sustainable domestic biomass industry for renewable biofuels, bio-products and bio-power is the lack of understanding and quantification of the risks associated with both the biomass supply chain and preprocessing and conversion technologies. Currently a consistent method for assessing, comparing, and quantifying risks in biomass supply chains does not exist, creating a major investment barrier to bioenergy projects in the U.S. The lack of a standardized approach has resulted in bioenergy stakeholders independently using inconsistent approaches and evaluation criteria, leading to unreliable and incomparable assessments of risks and financing barriers to bio-project development. Along with the challenges of inconsistent risk assessment for supply chain risk, technology specific risks based on variability in biomass properties are not fully understood and can pose significant unforeseen challenges for bioenergy projects. In many cases these properties have not yet been identified and the impacts on the proposed technology and products unquantified. This is particularly challenging for emerging preprocessing and conversion technologies. Without a firm understanding of the preprocessing/conversion technology-specific critical properties, the risk of a proposed bio-project cannot be fully evaluated. To address inconsistent risk evaluation in the biomass supply chain supporting project financing, a Biomass Supply Chain Risk Standards (BSCRS) framework was developed. The BSCRS framework includes a comprehensive list of known and perceived risks (Risk Indicators) to the supply chain developed through 100’s of interviews with bioenergy industry experts spanning from feedstock growers and suppliers to representatives from the financial sector. These risks have been organized into a manageable hierarchy of Risk Categories and Risk Factors that can be practically assessed. This BSCRS framework also provides mitigation strategies for multiple Risk Indicators from best available industry practices and research findings. Additionally, a risk quantification methodology for each Risk Factor, Risk Category, and the bio-project as a whole was developed to enable capital markets to assess feedstock risk more efficiently and more accurately. Multiple case studies representing existing bio-projects have been used to evaluate and verify the BSCRS framework and scoring methodology. To address technological risk along with the supply chain risk captured in the developed BSCRS framework, this work also focuses on development of a systematic criticality assessment tool using well-accepted, quantitative risk analysis methods to evaluate bioenergy feedstock critical properties impacting system unit operations. The proposed Failure Mode and Effect Analysis (FMEA) approach uses a team of subject area experts (SAEs) for each targeted unit operation within a system. Collectively, the team will develop and use a quantitative scoring system to assess the material attributes, process parameters, and quality attributes for key unit operations that have already been identified. The FMEA process generates Risk Priority Numbers (RPNs) for the various failures and predominant causes for each material/process unit/product combination resulting in a semi-quantitative, standardized methodology for assessing technological risk and biomass properties contributing to that risk.

09 BIOMASS FUELS↗

NASA's Surface Deformation and Change Mission Study

The National Academies of Science, Engineering and Medicine 2017 Decadal Survey of Earth Science and Applications identified geodetic measurements of surface deformation and related change as one of the top five "observables" to be prioritized in NASA's program going forward. In response, NASA commissioned a multi-center Surface Deformation and Change (SDC) team to perform a five year study of mission architectures that would support SDC observables and provide the most value to the diverse science and applications communities it serves. The study is being conducted in phases, in which the science and applications capabilities identified in the Decadal Survey are interpreted and refined, candidate mission architectures and associated technologies to support these needs are identified, architectures are assessed against a science value framework specific to SDC, and recommendations to NASA are made. Ultimately, NASA will decide which amongst these recommendations will proceed to mission formulation. As synthetic aperture radar (SAR) was identified as the prime sensor technology to satisfy SDC observational needs, a key component of the SDC study is to assess the current state of the art in SAR sensor and spacecraft systems and components. The number of SAR systems, both civil and commercial, is growing rapidly, requiring that mission architectures not only consider technology, but availability of data from other missions, possible partnerships or collaborations, and even data purchase. The mechanism for assessment involves development of an end-to-end science performance evaluation tool for multi-satellite constellations, which feeds into a science value framework that considers science performance, technological programmatic risks, and cost. This paper will present an overview of the ongoing study including the architectures under consideration and the technology road map needed to achieve the objectives of the mission.

Rosen, Paul↗

On Noise Assessment for Blended Wing Body Aircraft

A system noise study is presented for the blended-wing-body (BWB) aircraft configured with advanced technologies that are projected to be available in the 2025 timeframe of the NASA N+2 definition. This system noise assessment shows that the noise levels of the baseline configuration, measured by the cumulative Effective Perceived Noise Level (EPNL), have a large margin of 34 dB to the aircraft noise regulation of Stage 4. This confirms the acoustic benefits of the BWB shielding of engine noise, as well as other projected noise reduction technologies, but the noise margins are less than previously published assessments and are short of meeting the NASA N+2 noise goal. In establishing the relevance of the acoustic assessment framework, the design of the BWB configuration, the technical approach of the noise analysis, the databases and prediction tools used in the assessment are first described and discussed. The predicted noise levels and the component decomposition are then analyzed to identify the ranking order of importance of various noise components, revealing the prominence of airframe noise, which holds up the levels at all three noise certification locations and renders engine noise reduction technologies less effective. When projected airframe component noise reduction is added to the HWB configuration, it is shown that the cumulative noise margin to Stage 4 can reach 41.6 dB, nearly at the NASA goal. These results are compared with a previous NASA assessment with a different study framework. The approaches that yield projections of such low noise levels are discussed including aggressive assumptions on future technologies, assumptions on flight profile management, engine installation, and component noise reduction technologies. It is shown that reliable predictions of component noise also play an important role in the system noise assessment. The comparisons and discussions illustrate the importance of practical feasibilities and constraints in aircraft system noise studies, which include aerodynamic performance, propulsion efficiency, flight profile limitation and many other factors. For a future aircraft concept to achieve the NASA N+2 noise goal it will require a range of fully successful noise reduction technology developments.

Guo, Yueping↗

NASA’s Surface Deformation and Change Mission Study

The National Academies of Science, Engineering and Medicine 2017 Decadal Survey of Earth Science and Applications identified geodetic measurements of surface deformation and related change as one of the top five “observables” to be prioritized in NASA’s future program. In response, NASA commissioned a multi-center Surface Deformation and Change(SDC) team to perform a five year study of mission architectures that would support SDC observables and provide the most value to the diverse science and applications communities it serves. The study is being conducted in phases, in which the science and applications capabilities identified in the Decadal Survey are refined, candidate architectures and associated technologies to support these needs are identified, architectures are assessed against a science value framework specific to SDC, and recommendations to NASA are made. Ultimately, NASA will decide which amongst these recommendations will proceed to mission formulation. As synthetic aperture radar (SAR) was identified as the prime sensor technology to satisfy SDC observational needs, a key component of the SDC study is to assess the current state of the art in SAR sensor and supporting technology. The number of SAR systems, both civil and commercial, is growing rapidly, requiring that mission architectures not only consider technology, but availability of data from other missions, possible partnerships or collaborations, and even data purchase. The mechanism for assessment involves development of an end-to-end science performance evaluation tool for multi-satellite con-stellations, which feeds into a science value framework that con-siders science performance, technological programmatic risks, and cost. This paper will present an overview of the ongoing study including the candidate architectures and the technology road map needed to achieve the objectives of the mission.

Stephen Horst↗

Survey and documentation of emerging technologies for the Satellite Power System (SPS)

The genesis of the solar power satellite (SPS) concept is reviewed historically and the original assumptions and guidelines which led to development of the SPS reference system design concept are discussed. Some guidelines are applicable to almost any SPS design, but others can be changed, leading to new and perhaps preferable systems. In order to stimulate new SPS concepts and to facilitate comparative assessment of emerging SPS technologies, one useful approach is to break the overall system into functional parts. The system functions which must be performed by any SPS concept and the interrelations between them are discussed and a systematic framework is presented for assessing the wide variety of system concepts and subsystem technologies which have been proposed. About 80 alternative SPS technologies are reviewed.

Glaser, P.↗

Electrolyzers in the System Advisor Model (SAM): A Techno-Economic Potential Study

A technoeconomic analysis of grid to low temperature electrolysis (Grid-LTE), photovoltaic to low temperature electrolysis (PV-LTE), concentrating solar power to high temperature electrolysis (CSP-HTSE) and a concentrating solar power with PV to high temperature electrolysis (CSP-PV-HTSE) centralized hydrogen production systems are analyzed to assess the economics of system and to provide a baseline for comparing these technologies against hydrogen production cost targets. A framework integrating the system advisor model (SAM) and US Department of Energy hydrogen production models (H2A) is developed to assess these systems. The hydrogen levelized cost given current and future assumptions for technology cost and performance is evaluated at optimal system configurations. The framework described in this report integrates SAM with H2A electrolyzer technologies and provides analysts a detailed technoeconomic method to analyze concentrating and photovoltaic solar technologies to produce energy that are directly coupled to LTE and HTSEs that use that energy to split water into hydrogen and oxygen. The baseline hydrogen levelized cost (HLCs) for the GRID-LTE, PV-LTE, CSP-HTSE, and CSP-PV-HTSE systems in Daggett, CA are 2.82, 3.86, 3.68, and 2.90 $\$$USD 2016/kg H2 and 2.50, 2.13, 2.84, 2.15 $\$$USD 2016/kg H2 in the 2020 and 2050 scenarios respectively. To achieve the $\$$2/kg H2 target in locations with excellent solar resources, cost parameters values aligned with aggressive R&D targets will need to be achieved for all the systems configurations. In Daggett, PV costs of $\$$0.68 /Wac or moderate ATB PV CAPEX projections result in HLCs of $\$$2 /kg H2. Similarly for PV-MSALT-HTSE systems, $\$$0.60 /Wac result in $\$$2/kg H2. For the MSALT-HTSE systems, better than aggressive 2050 ATB salt tower CAPEX projections would be needed to reach $\$$2/kg H2. Molten salt tower capital costs of $\$$2400/kW would enable $\$$2/kg H2 in 2050.

08 HYDROGEN↗

A Model-based Framework for Risk Assessment in Human-Computer Controlled Systems

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems. This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions. Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

Hatanaka, Iwao↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

decarbonizing↗

Evaluating Technology Adoption Risks in Early-Stage Materials Research

Development of new technologies often begins with fundamental materials science research. Decisions at this stage can shape factors related to the eventual adoption readiness of the technology, such as process scalability or materials availability. Here we present the early-Stage Technology Evaluation for Adoption Risks (STEAR) framework as a method for qualitatively assessing metrics spanning four categories of adoption risks: value proposition, market acceptance, resource maturity, and license to operate. We conduct a case study applying STEAR to different methanol production processes at a range of technology readiness levels and demonstrate how the assessment identifies key challenges related to adoption readiness. Finally, we discuss efforts to expand the applicability and utility of STEAR, including focus group feedback and complementary quantitative analysis methods.

36 MATERIALS SCIENCE↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

Consequence Based Framework for Deployment of Cloud Solutions in the Digital Energy Transition

This study proposes a framework for evaluating cloud computing deployment in the electric sector, focusing on the digital transition of energy systems. It assesses the implications of cloud technology adoption, particularly in terms of security, operational resilience, and efficiency. The paper introduces a framework for consequence-driven applied risk analysis, enabling utilities to prioritize and mitigate potential threats effectively, and responsibly deploy cloud applications. It also discusses the shared responsibility model in cloud computing, highlighting the need for collaborative security efforts. The research aims to provide utilities with a strategic assessment tool for cloud adoption, emphasizing the importance of security culture in enhancing cloud computing's role in critical infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enabling Entry Technologies for Ice Giant Missions

The highest priority science goals for Ice Giant missions are: 1) Interior structure of the Planet, and 2) Bulk composition that includes isotopes and noble gases. The interaction between the planetary interior and the atmosphere requires sustained global measurements. Noble gas and Isotope measurements require in situ measurement. Drag modulated aerocapture utilizing ADEPT offers more mass delivered to the Ice Giants than with propulsive orbit insertion. The Galileo Probe entered at a ‘hot’ spot which created interpretation challenges. Juno is providing valuable orbital measurements, but without in situ measurements the story is incomplete. Planetary scientists interested in Ice Giant missions should perform mission design studies with these new Entry System technologies to assess the feasibility within the context of the international collaboration framework. A mission architecture that includes probe(s) along with an orbiting spacecraft can deploy the probes at the desired location while taking simultaneous measurements from orbit to provide invaluable data that can correlate both global and local measurements. Entry System Technologies currently being developed by NASA are poised to enable missions that position the Orbiter & Probes through drag modulated aerocapture (ADEPT), and HEEET enables the Probes to survive the extreme environments encountered for entry into the atmospheric interior.

Venkatapathy, E.↗

Circular Economy Modeling Efforts at NREL: Circular Economy Lifecycle Analysis and Visualization (CELAVI) and the Circular Economy Agent-Based Model (ABM)

Circular Economy (CE) aims at decoupling human activities from economic growth and resource use. While CE economic and environmental benefits are often touted by its proponents, increased circularity and improved sustainability do not necessarily go hand-in-hand. The Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates the transition of renewable energy technology supply chains towards circularity and quantifies spatially explicit environmental impacts and supply chain costs. Using wind blade end-of-life (EOL) management as a case study, this presentation will highlight CELAVI's features. Furthermore, envisioned extension to the framework could improve the stakeholder decision model by accounting for logistical and other factors. The CELAVI framework could be leveraged to answer crucial questions regarding renewables EOL management.

circular economy↗

Deep Space Habitat Concept of Operations for Extended Duration Transit Missions

NASA's Capability-Driven Framework (CDF) describes an approach for progressively extending human exploration missions farther into the Solar System for longer periods of time as allowed by developments in technology and spacecraft systems. Within this framework design reference missions (DRMs) targeted for several specific destinations are being used to assess different combinations of vehicles, operations, and advanced technologies to help understand which combination will best support expanded human exploration both efficiently and sustainably. Several of the identified destinations have been found to require missions with a round trip duration exceeding one year. These mission durations exceed the capabilities of current human-rated spacecraft if resupply from Earth is not possible. This makes the design of an efficient and reliable Deep Space Habitat (DSH) critical for reaching these destinations. The paper will describe the current understanding of DSH capabilities and functions that must be exhibited by any future habitat design for these missions. This description of the DSH is presented in the form of a concept of operation, which focuses on the functions that any DSH must provide, as opposed to a specific DSH design concept. Development of a concept of operations, based on DRM features, provides a common basis for assessing the viability of design concepts incorporating differing configurations and technologies. A study team with representation from several NASA Centers and relevant engineering and scientific disciplines collaborated to develop this DSH concept of operations for the transit phases of these missions. The transit phase of a mission is defined as the time after leaving Earth but before arrival at the destination and the time after leaving the destination but before arriving back at Earth. These transit phases were found to have many common features across all of the destinations being assessed for the CDF and thus arguing for a common concept of operations for all of the associated DRMs. The paper first describes the CDF and potential destinations being considered within this framework. DRMs representative of those currently being assessed will then be discussed to illustrate the range of capabilities that the DSH must support. The 18 functions identified by the multi-discipline analysis team are then described at a summary level. Several specific examples of the potential use for this concept of operations are described.

Hoffman, Stephen J.↗

Adoption Readiness Level Assessment of Redox Flow Batteries

Adoption readiness levels (ARLs) were developed by the Department of Energy’s Office of Technology Transitions (OTT) to holistically capture barriers to market adoption for a technology. The framework consists of 17 risk dimensions falling into 4 broad categories: Value Proposition, Market Acceptance, Resource Maturity, and License to Operate. OTT’s Commercial Adoption Readiness Assessment Tool (CARAT) can be used to evaluate a technology’s ARL. This work applies CARAT to redox flow batteries to evaluate the level of risk for this technology class across the 17 dimensions. Redox flow batteries were found to bear 1-2 high risk dimensions, 10-11 medium risk dimensions, 5 low risk dimensions, and scored an overall low readiness on the CARAT scoring scale (ranges reflect variation with flow battery chemistry). Herein, we describe the factors and evaluation across the dimensions leading to this score for redox flow batteries.

25 ENERGY STORAGE↗

CCUS Perspectives: Assessing Historical Contexts, Current Realities, and Future Prospects

CCUS technologies are crucial solutions for mitigating climate change by reducing CO2 emissions from industrial operations and energy sectors. This review critically examines the current state of CCUS technologies, and highlights advancements, challenges, regulatory frameworks, and future directions. It comprehensively analyzes carbon capture methods, such as pre-combustion, post-combustion, and oxy-fuel combustion capture, while comparing their efficiencies and limitations. The review also explores carbon utilization techniques, such as direct and indirect utilization, emphasizing their potential applications and technological constraints. Additionally, it assesses various carbon storage methods, focusing on geological, ocean, and mineralization storage, and discusses their capacity, feasibility, and environmental implications. The study reviews the policy and regulatory frameworks, economic viability, market trends, and environmental sustainability of CCUS. By identifying research gaps and recommending future research priorities, this review aims to guide the development of more efficient/effective, and cost-effective CCUS technology, ensuring their role in a sustaining low-carbon future. This review provides a forward-looking perspective, a critical and interdisciplinary analysis that assesses the current state of CCUS technologies, and further provides a roadmap for future development.

Energy & Fuels↗