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At least 199 records · Page 11

Challenges and Opportunities in Deep Reinforcement Learning With Graph Neural Networks: A Comprehensive Review of Algorithms and Applications

Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields, including pattern recognition, robotics, recommendation-systems, and gaming. Similarly, graph neural networks (GNN) have also demonstrated their superior performance in supervised learning for graph-structured data. In recent times, the fusion of GNN with DRL for graph-structured environments has attracted a lot of attention. Here, this paper provides a comprehensive review of these hybrid works. These works can be classified into two categories: (1) algorithmic enhancement, where DRL and GNN complement each other for better utility; (2) application-specific enhancement, where DRL and GNN support each other. This fusion effectively addresses various complex problems in engineering and life sciences. Based on the review, we further analyze the applicability and benefits of fusing these two domains, especially in terms of increasing generalizability and reducing computational complexity. Finally, the key challenges in integrating DRL and GNN, and potential future research directions are highlighted, which will be of interest to the broader machine learning community.

97 MATHEMATICS AND COMPUTING↗

Perspectives on Potential Advanced Construction Technologies for Nuclear Energy

Advanced reactor technologies have attracted considerable financial support, catalyzing innovation in the nuclear energy landscape. These next generation reactors are designed with enhanced passive safety systems and the potential for cost reductions. As these advanced reactors approach technological maturity, their commercial success also requires focused examination and essential support. Economic assessments in the nuclear energy sector often emphasize construction costs and the risk of scheduling delays as primary contributors to deployment expenditures. Traditionally, vital elements of nuclear energy deployment including civil/structural engineering, design sophistication and automation have been either undervalued or postponed in the development cycles. Additionally, the nuclear industry’s collective experience in nuclear project execution has diminished over the past several decades due to the infrequency of new plant constructions. Hence, the National Reactor Innovation Center’s (NRIC) Advanced Construction Technology Initiative (ACTI) aims to reduce cost overruns and schedule slippages that have plagued the construction of nuclear power plant projects. With this initiative, NRIC is facilitating the development of advanced nuclear plant construction technologies and approaches through partnerships that would provide game-changing benefits to the construction of advanced nuclear power plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Oxygen Compatibility of Brass-Filled PTFE Compared to Commonly Used Fluorinated Polymers for Oxygen Systems

Safe and reliable seal materials for high-pressure oxygen systems sometimes appear to be extinct species when sought out by oxygen systems designers. Materials that seal well are easy to find, but these materials are typically incompatible with oxygen, especially in cryogenic liquid form. This incompatibility can result in seals that leak, or much worse, seals that easily ignite and burn during use. Materials that are compatible with oxygen are easy to find, such as the long list of compatible metals, but these metallic materials are limiting as seal materials. A material that seals well and is oxygen compatible has been the big game in the designer's safari. Scientists at the Materials Combustion Research Facility (MCRF), part of NASA/Marshall Space Flight Center (MSFC), are constantly searching for better materials and processes to improve the safety of oxygen systems. One focus of this effort is improving the characteristics of polymers used in the presence of an oxygen enriched environment. Very few systems can be built which contain no polymeric materials; therefore, materials which have good impact resistance, low heat of combustion, high auto-ignition temperature and that maintain good mechanical properties are essential. The scientists and engineers at the Materials Combustion Research Facility, in cooperation with seal suppliers, are currently testing a new formulation of polytetrafluoroethylene (PTFE) with Brass filler. This Brass-filled PTFE is showing great promise as a seal and seat material for high pressure oxygen systems. Early research has demonstrated very encouraging results, which could rank this material as one of the best fluorinated polymers ever tested. This paper will compare the data obtained for Brass-filled PTFE with other fluorinated polymers, such as TFE-Teflon (PTFE) , Kel-F 81, Viton A, Viton A-500, Fluorel , and Algoflon . A similar metal filled fluorinated polymer, Salox-M , was tested in comparison to Brass-filled PTFE to demonstrate the importance of the metal chosen and relative percentage of filler. General conclusions on the oxygen compatibility of this formulation are drawn, with an emphasis on comparing and contrasting the materials performance to the performance of the current state-of-the-art oxygen compatible polymers.

Herald, Stephen D.↗

Southwest Water Resources: Monitoring Surface Water Extents of Remote Stock Ponds in the Southwestern United States Using Earth Observing Systems for Enhanced Water Resources Management

Due to increasingly frequent and severe drought conditions in the southwestern US, land managers and livestock producers need to monitor stock ponds with increasing regularity. The ability to assess stock pond water levels with Earth observing satellite systems would enhance monitoring efforts of partners at the US Forest Service, Arizona Department of Game and Fish, and the Diablo Trust. This study employed Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) to monitor surface water extent for hundreds of critical stock ponds in Arizona. Using methods adapted from previously developed image processing workflows, this project conducted a time-series analysis to capture seasonal and interannual variations in surface water area between 2013 to 2021. In addition, end users can monitor the surface water extent of stock ponds through the developed Google Earth Engine software tool called Surface Water Identification and Forecasting Tool (SWIFT). SWIFT incorporates the Automated Water Extraction Index, Modified Normalized Difference Water Index, and Tasseled Cap-Wetness Index for optical imagery and the incidence angle, VV and VH polarization bands for Sentinel-1 imagery to detect small water bodies in the study area with an overall accuracy range of 88-93%. These tools will empower our partners to monitor the extents of water in their stock ponds remotely, enabling them to develop data-informed and sustainable management solutions for decades to come.

Rainey Aberle↗

ADVANCED CONSTRUCTION TECHNOLOGY INITIATIVE (ACTI)

Advanced reactor technologies have attracted considerable financial support, catalyzing innovation in the nuclear energy landscape. These next generation reactors are designed with enhanced passive safety systems and the potential for cost reductions. As these advanced reactors approach technological maturity, their commercial success also requires focused examination and essential support. Economic assessments in the nuclear energy sector often emphasize construction costs and the risk of scheduling delays as primary contributors to deployment expenditures. Traditionally, vital elements of nuclear energy deployment including civil/structural engineering, design sophistication and automation have been either undervalued or postponed in the development cycles. Additionally, the nuclear industry’s collective experience in nuclear project execution has diminished over the past several decades due to the infrequency of new plant constructions. Hence, The National Reactor Innovation Center’s (NRIC) Advanced Construction Technology Initiative (ACTI) program aims to reduce cost overruns and schedule slippages that have plagued the construction of nuclear power plant projects. With this initiative, NRIC is facilitating the development of advanced nuclear plant construction technologies and approaches through partnerships that would provide game-changing benefits to the construction of advanced nuclear power plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

GIS Data Based Automatic High-Fidelity 3D Road Network Modeling

3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks

Wang, Jie↗

Economic analysis of precious metal recovery from electronic waste through gas-assisted microflow extraction

The recycling of end-of-life (EoL) electronic products is motivated by the enormous investment of resources in their creation and the environmental concerns associated with electronic waste (e-waste). Hydrometallurgical methods that utilize conventional leaching and solvent extraction are often applied to extract target materials from e-waste; however, these techniques have significant technical and economic limitations when extracting high-value, low concentration metals from complex waste streams. This study proposes and evaluates a novel process based on gas-assisted microflow extraction (GAME) that efficiently recovers precious metals from waste printed circuit boards (WPCBs). Further, an economic analysis is conducted to verify the economic feasibility of the GAME-based process at an industrial scale. The economic outputs are further investigated to identify the most cost-effective production strategies, particularly with respect to the plant feedstock rate. It is envisioned that this study may establish a paradigm for making economically-informed decisions for sustainable technologies.

42 ENGINEERING↗

Theory of Collective Intelligence

In this chapter an analysis of the behavior of an arbitrary (perhaps massive) collective of computational processes in terms of an associated "world" utility function is presented We concentrate on the situation where each process in the collective can be viewed as though it were striving to maximize its own private utility function. For such situations the central design issue is how to initialize/update the collective's structure, and in particular the private utility functions, so as to induce the overall collective to behave in a way that has large values of the world utility. Traditional "team game" approaches to this problem simply set each private utility function equal to the world utility function. The "Collective Intelligence" (COIN) framework is a semi-formal set of heuristics that recently have been used to construct private utility. functions that in many experiments have resulted in world utility values up to orders of magnitude superior to that ensuing from use of the team game utility. In this paper we introduce a formal mathematics for analyzing and designing collectives. We also use this mathematics to suggest new private utilities that should outperform the COIN heuristics in certain kinds of domains. In accompanying work we use that mathematics to explain previous experimental results concerning the superiority of COIN heuristics. In that accompanying work we also use the mathematics to make numerical predictions, some of which we then test. In this way these two papers establish the study of collectives as a proper science, involving theory, explanation of old experiments, prediction concerning new experiments, and engineering insights.

Nash equilibrium↗

NASA's Space Launch System: One Vehicle, Many Destinations

The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is making progress toward delivering a new capability for exploration beyond Earth orbit (BEO). Developed with the goals of safety, affordability and sustainability in mind, SLS will start with 10 percent more thrust than the Saturn V rocket that launched astronauts to the Moon 40 years ago. From there it will evolve into the most powerful launch vehicle ever flown, via an upgrade approach that will provide building blocks for future space exploration and development. The International Space Exploration Coordination Group, representing 12 of the world's space agencies, has worked together to create the Global Exploration Roadmap, which outlines paths towards a human landing on Mars, beginning with capability-demonstrating missions to the Moon or an asteroid. The Roadmap and corresponding NASA research outline the requirements for reference missions for all three destinations. This paper will explore the requirements needed for missions to BEO destinations, and the capability of SLS to meet those requirements and enable those missions. It will explain how NASA will execute this development within flat budgetary guidelines by using existing engines assets and heritage technology, from the initial 70 metric ton (t) lift capability through a block upgrade approach to an evolved 130-t capability. The SLS will offer a robust way to transport international crews and the air, water, food, and equipment they would need for extended trips to asteroids, the Moon, and Mars. In addition, this paper will detail SLS's capability to support missions beyond the human exploration roadmap, including robotic precursor missions to other worlds or uniquely high-mass space operation facilities in Earth orbit. As this paper will explain, the SLS provides game-changing mass and volume lift capability that makes it enhancing or enabling for a variety of unprecedented human and robotic missions.

May, Todd A.↗

A Cooperative Game Theory-based Approach to Under-frequency Load Shedding Control

This paper proposes a cooperative game theory-based under-frequency load shedding (UFLS) approach for frequency stability and control in power systems. UFLS is a crucial factor for frequency stability and control especially in power grids with high penetration of renewable energy sources and restructured power systems. Conventional UFLS methods, most of which are off-line, usually shed fixed amounts of predetermined loads based on a predetermined schedule which can lead to over or under curtailment of load. This paper presents a co-operative game theory-based two-stage strategy to effectively and precisely determine locations and amounts of loads to be shed for UFLS control. In the first stage, the total amount of loads to be shed, also referred to as deficit in generation or the disturbance power, is computed using the initial rate of change of frequency (ROCOF) referred to the equivalent inertial center. In the second stage, the Shapley value, one of the solution concepts of cooperative game theory, is used to determine load shedding amounts and locations. The proposed method is implemented on the reduced 9-bus 3-machine Western Electricity Coordinating Council (WECC) system and simulated on Real-time Digital Simulators (RTDS). The results show that the proposed UFLS approach can effectively return the system to normal state after disturbances.

42 ENGINEERING↗

graphenv: a Python library for reinforcement learning on graph search spaces

Many important and challenging problems in combinatorial optimization (CO) can be expressed as graph search problems, in which graph vertices represent full or partial solutions and edges represent decisions that connect them. Graph structure not only introduces strong relational inductive biases for learning (Battaglia et al., 2018) - in this context, by providing a way to explicitly model the value of transitioning (along edges) between one search state (vertex) and the next - but lends itself to problems both with and without clearly defined algebraic structure. For example, classic CO problems on graphs such as the Traveling Salesman Problem (TSP) can be expressed as either pure graph search or integer programs. Other problems, however, such as molecular optimization, do no have concise algebraic formulations and yet are readily implemented as a graph search (V. et al., 2022; Zhou et al., 2019). Such "model-free" problems constitute a large fraction of modern reinforcement learning (RL) research owing to the fact that it is often much easier to write a forward simulation that expresses all of the state transitions and rewards, than to write down the precise mathematical expression of the full optimization problem. In the case of molecular optimization, for example, one can use domain knowledge alongside existing software libraries to model the effect of adding a single bond or atom to an existing but incomplete molecule, and let the RL algorithm build a model of how good a given decision is by "experiencing" the simulated environment many times through. In contrast, a model-based mathematical formulation that fully expresses all the chemical and physical constraints is intractable. In recent years, RL has emerged as an effective paradigm for optimizing searches over graphs and led to state-of-the-art heuristics for games like Go and chess, as well as for classical CO problems such as the TSP. This combination of graph search and RL, while powerful, requires non-trivial software to execute, especially when combining advanced state representations such as Graph Neural Networks (GNN) with scalable RL algorithms.

97 MATHEMATICS AND COMPUTING↗

Low-Enriched Uranium Nuclear Thermal Propulsion Systems

The fundamental capability of Nuclear Thermal Propulsion (NTP) is game changing for space exploration. For example, using NTP for human Mars missions can provide faster transit and/or round trip times for crew; larger mission payloads; off nominal mission opportunities (including wider injection windows); and crew mission abort options not available from other architectures. The use of NTP can also reduce required earth-to-orbit launches, reducing cost and improving ground logistics. In addition to enabling robust human Mars mission architectures, NTP can be used on exploration missions throughout the solar system. A first generation NTP system could provide high thrust at a specific impulse above 900 s, roughly double that of state of the art chemical engines. Characteristics of fission and NTP indicate that useful first generation systems will provide a foundation for future systems with extremely high performance. Progress made under the NTP project could also help enable high performance fission power systems and Nuclear Electric Propulsion (NEP). Guidance, navigation, and control of NTP may have some unique but manageable characteristics.

Fission↗

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

The Predictive Simulation Capability development team of the STMD Game Changing Development sponsored PSI project is implementing computational simulation capability for the efficient and accurate prediction of Plume-Surface Interaction induced surface erosion and cratering in Martian and Lunar environments. The status of the Focus Area 3 of the PSI project in the generation and efficient application of accurate soil particle composition modeling in the Gas-Granular Flow Solver (GGFS) computational framework is presented. The process of constitutive closure model database generation using DEM particle interaction modeling for capturing the effects of irregular particle shape and poly-disperse mixture distribution effects is outlined. This capability has now been ported to NASA supercomputer assets and NASA engineers successfully demonstrated technology and skillset transfer in model generation for spherical and irregularly shaped, mono-disperse and bi-disperse mixture compositions. Assessment of the computational efficiency and practicality of the academic serially executed DEM tools on NASA supercomputers identified the need to migrate to a DEM framework capable of performing parallel simulations in a simultaneous process orchestrated in an automated setup, execution, database extraction, and dataset delivery ready for application simulations. The LIGGGHTS DEM toolset has been selected as the most suitable tool to migrate the DEM simulations. Once the soil model generation process is implemented, models capturing the shape and poly-dispersity effects will be generated to perform much refined validation simulations against the experiments performed under the PSI project. The application readiness of the soil models currently operational in GGFS was presented for the example of a full scale, 3-D simulation of the plume induced erosion and crater formation of the Apollo LM at an elevation of 5m above ground in a low pressure, near vacuum background.

Peter A Liever↗

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

The Predictive Simulation Capability development team of the STMD Game Changing Development sponsored PSI project is implementing computational simulation capability for the efficient and accurate prediction of Plume-Surface Interaction induced surface erosion and cratering in Martian and Lunar environments. The status of the Focus Area 3 of the PSI project in the generation and efficient application of accurate soil particle composition modeling in the Gas-Granular Flow Solver (GGFS) computational framework is presented. The process of constitutive closure model database generation using DEM particle interaction modeling for capturing the effects of irregular particle shape and poly-disperse mixture distribution effects is outlined. This capability has now been ported to NASA supercomputer assets and NASA engineers successfully demonstrated technology and skillset transfer in model generation for spherical and irregularly shaped, mono-disperse and bi-disperse mixture compositions. Assessment of the computational efficiency and practicality of the academic serially executed DEM tools on NASA supercomputers identified the need to migrate to a DEM framework capable of performing parallel simulations in a simultaneous process orchestrated in an automated setup, execution, database extraction, and dataset delivery ready for application simulations. The LIGGGHTS DEM toolset has been selected as the most suitable tool to migrate the DEM simulations. Once the soil model generation process is implemented, models capturing the shape and poly-dispersity effects will be generated to perform much refined validation simulations against the experiments performed under the PSI project. The application readiness of the soil models currently operational in GGFS was presented for the example of a full scale, 3-D simulation of the plume induced erosion and crater formation of the Apollo LM at an elevation of 5m above ground in a low pressure, near vacuum background.

Peter A Liever↗

Nuclear Thermal Propulsion Development Risks

There are clear advantages of development of a Nuclear Thermal Propulsion (NTP) for a crewed mission to Mars. NTP for in-space propulsion enables more ambitious space missions by providing high thrust at high specific impulse ((is) approximately 900 sec) that is 2 times the best theoretical performance possible for chemical rockets. Missions can be optimized for maximum payload capability to take more payload with reduced total mass to orbit; saving cost on reduction of the number of launch vehicles needed. Or missions can be optimized to minimize trip time significantly to reduce the deep space radiation exposure to the crew. NTR propulsion technology is a game changer for space exploration to Mars and beyond. However, 'NUCLEAR' is a word that is feared and vilified by some groups and the hostility towards development of any nuclear systems can meet great opposition by the public as well as from national leaders and people in authority. The public often associates the 'nuclear' word with weapons of mass destruction. The development NTP is at risk due to unwarranted public fears and clear honest communication of nuclear safety will be critical to the success of the development of the NTP technology. Reducing cost to NTP development is critical to its acceptance and funding. In the past, highly inflated cost estimates of a full-scale development nuclear engine due to Category I nuclear security requirements and costly regulatory requirements have put the NTP technology as a low priority. Innovative approaches utilizing low enriched uranium (LEU). Even though NTP can be a small source of radiation to the crew, NTP can facilitate significant reduction of crew exposure to solar and cosmic radiation by reducing trip times by 3-4 months. Current Human Mars Mission (HMM) trajectories with conventional propulsion systems and fuel-efficient transfer orbits exceed astronaut radiation exposure limits. Utilizing extra propellant from one additional SLS launch and available energy in the NTP fuel, HMM radiation exposure can be reduced significantly.

Kim, Tony↗

Reinforcement learning for bluff body active flow control in experiments and simulations

Significance Reinforcement learning (RL) has been applied effectively in games and robotic manipulation. We demonstrate the effectiveness of RL in experimental fluid mechanics by applying it to reduce the drag of circular cylinders in turbulent flow, a canonical fluid–structure interaction problem. Although physics agnostic, RL managed to reduce the drag by 30 % or reach another specified optimum point very quickly. Following this discovery, we used high-fidelity simulations to probe the underlying physical mechanisms so that the discovered control techniques can be generalized to other similar flow problems. More broadly, RL-guided active control can lead to efficient exploration of additional flow-control strategies in experimental fluid mechanics, potentially paving the way for accelerating scientific discovery and different designs in flow-related engineering problems.

42 ENGINEERING↗

NASA's Space Launch System: Payload Opportunities for Lunar Exploration, Science Missions

Nearing its first launch, the Space Launch System (SLS), NASA’s new super heavy-lift launch vehicle, offers highly energetic launches that deliver more mass and provide more volume in 8.4 m-diameter and potentially larger fairings to make a new generation of deep space missions possible. An evolvable launcher available in crew, crew with a co-manifested payload (CPL) and cargo-only configurations, SLS is a crucial capability to enable astronauts to return to the Moon, but it also offers key benefits for science missions. NASA’s 21st-century return to the Moon recently received a formal name: the Artemis program. In addition to the core enabling capabilities of SLS and the Orion crew spacecraft, NASA will also enlist international and commercial partnerships for Artemis. The Agency intends to build a scientific outpost in lunar orbit, the Gateway, from which human and robotic missions to and from the surface can rendezvous. SLS will launch Orion on a series of missions leading to landing the first woman and the next man on the Moon as part of Artemis. SLS uses proven propulsion systems: two solid rocket boosters and four RS-25s engines that have been upgraded to provide more thrust and operate in the SLS environment. SLS Block 1 uses a modified Delta IV Heavy upper stage, called the Interim Cryogenic Propulsion Stage (ICPS) and lifts at least 26 metric tons (t) to trans-lunar injection (TLI). The Block 1 vehicle can also be outfitted with a 5 m-diameter fairing. Block 1B, the next major variant, also uses solid rocket boosters and RS-25 engines to achieve Earth escape velocity, but replaces the single-engine liquid hydrogen (LH2)/liquid oxygen (LOX) ICPS with a four-engine LH2/LOX Exploration Upper Stage (EUS) to increase mass to TLI to 34-37 t, depending on crew or cargo configuration. In the Block 1B crew configuration, a 10 m-tall Universal Stage Adapter (USA) connects the vehicle to Orion and can carry a CPL up to 10 t. The USA provides 286 m3 of unpressurized volume for payloads. For large payloads, 8.4 m- and 10 m-diameter cargo fairings in 19.1 m and 27.4 m lengths are possible. The ultimate SLS vehicle, Block 2, incorporates evolved boosters to reach a lift capacity of more than 45 t to TLI. The capabilities of SLS not only make new missions to the Moon possible, but also game-changing science missions, such as deployment of large-aperture space telescopes, spacecraft to the ice giants or even probes to the interstellar medium. This paper will discuss the capabilities of SLS, the vehicle’s planned evolution, missions that can effectively utilize the vehicle and manufacturing status of the vehicle.

Creech, Stephen D.↗

NASA's Space Launch System: Payload Opportunities for Lunar Exploration, Science Missions

Nearing its first launch, the Space Launch System (SLS), NASA’s new super heavy-lift launch vehicle, offers highly energetic launches that deliver more mass and provide more volume in 8.4 m-diameter and potentially larger fairings to make a new generation of deep space missions possible. An evolvable launcher available in crew, crew with a co-manifested payload (CPL) and cargo-only configurations, SLS is a crucial capability to enable astronauts to return to the Moon, but it also offers key benefits for science missions. NASA’s 21st-century return to the Moon recently received a formal name: the Artemis program. In addition to the core enabling capabilities of SLS and the Orion crew spacecraft, NASA will also enlist international and commercial partnerships for Artemis. The Agency intends to build a scientific outpost in lunar orbit, the Gateway, from which human and robotic missions to and from the surface can rendezvous. SLS will launch Orion on a series of missions leading to landing the first woman and the next man on the Moon as part of Artemis. SLS uses proven propulsion systems: two solid rocket boosters and four RS-25s engines that have been upgraded to provide more thrust and operate in the SLS environment. SLS Block 1 uses a modified Delta IV Heavy upper stage, called the Interim Cryogenic Propulsion Stage (ICPS) and lifts at least 26 metric tons (t) to trans-lunar injection (TLI). The Block 1 vehicle can also be outfitted with a 5 m-diameter fairing. Block 1B, the next major variant, also uses solid rocket boosters and RS-25 engines to achieve Earth escape velocity, but replaces the single-engine liquid hydrogen (LH2)/liquid oxygen (LOX) ICPS with a four-engine LH2/LOX Exploration Upper Stage (EUS) to increase mass to TLI to 34-37 t, depending on crew or cargo configuration. In the Block 1B crew configuration, a 10 m-tall Universal Stage Adapter (USA) connects the vehicle to Orion and can carry a CPL up to 10 t. The USA provides 286 m3 of unpressurized volume for payloads. For large payloads, 8.4 m- and 10 m-diameter cargo fairings in 19.1 m and 27.4 m lengths are possible. The ultimate SLS vehicle, Block 2, incorporates evolved boosters to reach a lift capacity of more than 45 t to TLI. The capabilities of SLS not only make new missions to the Moon possible, but also game-changing science missions, such as deployment of large-aperture space telescopes, spacecraft to the ice giants or even probes to the interstellar medium. This paper will discuss the capabilities of SLS, the vehicle’s planned evolution, missions that can effectively utilize the vehicle and manufacturing status of the vehicle.

Creech, Steve↗