System Modeling of Lunar Oxygen Production Using Fission Surface Power: Mass and Power Requirements

Steffen, Christopher J.; Freeh, Joshua E.; Linne, Diane L.; Faykus, Eric W.; Gallo, Christopher A.; Green, Robert D.

doi:10.13182/nt09-a8838

Cited by 5 publications

(4 citation statements)

References 5 publications

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“…This tool has already enabled the ISRU team to understand where peak power requirements develop, and how the use of parallel reactors, for example, can significantly reduce peak power by splitting up times for reactor fill and dump, regolith heating, and oxygen extraction. 5,6 Component models that comprise this end-to-end system tool are also being used to aid in the design of prototype hardware and predict expected performance for various anticipated regolith simulants.…”

Section: Introductionmentioning

confidence: 99%

Component and System Sensitivity Considerations for Design of a Lunar ISRU Oxygen Production Plant

Linne

Gökoğlu

Hegde³

et al. 2009

47th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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Component and system sensitivities of some design parameters of ISRU system components are analyzed. The differences between terrestrial and lunar excavation are discussed, and a qualitative comparison of large and small excavators is started. The effect of excavator size on the size of the ISRU plant's regolith hoppers is presented. Optimum operating conditions of both hydrogen and carbothermal reduction reactors are explored using recently developed analytical models. Design parameters such as batch size, conversion fraction, and maximum particle size are considered for a hydrogen reduction reactor while batch size, conversion fraction, number of melt zones, and methane flow rate are considered for a carbothermal reduction reactor. For both reactor types the effect of reactor operation on system energy and regolith delivery requirements is presented.

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Section: Introductionmentioning

confidence: 99%

Component and System Sensitivity Considerations for Design of a Lunar ISRU Oxygen Production Plant

Linne

Gökoğlu

Hegde³

et al. 2009

47th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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“…Other ISRU modeling to date has incorporated previously reported data and analyses of ISRU chemical processes with economic models to provide a higher-level ISRU scenario analysis tool. 10 NASA's ISRU system model discussed in this paper integrates detailed engineering analyses of the technology components that comprise a variety of oxygen production systems 2,3 . It captures the system-level interactions of specific subsystems and also allows for testing different types of subsystems (i.e.…”

Section: Introductionmentioning

confidence: 99%

Architecture Modeling of In-Situ Oxygen Production and its Impacts on Lunar Campaigns

Chepko

Weck

Linne

et al. 2008

AIAA SPACE 2008 Conference &Amp; Exposition

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In-situ lunar oxygen production has the potential to reduce the cargo mass launched from Earth necessary to sustain a lunar base. As research and development in lunar oxygen production continue, modeling tools are being used to help characterize the many possible system architectures and guide decisions for future plant designs. Using the previously built NASA In-Situ Resource Utilization (ISRU) System Model, an optimization tool was developed to facilitate exploration of the design space of the different system architectures represented in the model. For each architecture, an optimization of the continuous design space is performed using a gradient-based search. In instances when the gradient-based search cannot converge, the tool changes to simulated annealing, a heuristic method. Nine primary lunar oxygen production system architectures were optimized to minimize system mass for oxygen production levels from 500 kg/yr to 6000 kg/yr. Good designs minimized mass and maximized produced oxygen with system masses in the range of 100 kg to 700 kg. Preliminary results show that two particular architectures populate the Pareto-optimal front of best designs for most production levels, making them attractive for further investigation. An economy of scale of .837 was found using a power law regression, indicating that some economy of scale exists (values less than one have economy of scale) and that launching fewer, higher-capacity plants will be less massive overall than many small-capacity plants to achieve the same total production level. A simplified comparison of lunar-produced oxygen for crew breathing supply and ECLSS (environmental control and life support systems) technologies was performed with a space logistics planning tool, SpaceNet. For all but the most advanced ECLSS technologies, use of in-situ oxygen over a 10-year campaign resulted in more than 12,000 kg of consumables cargo launch mass savings. Nomenclature = economy of scale C = investment cost

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“…Oxygen is a consumable resource used to supply crew air and oxidizer in rocket propellant that can be extracted from the lunar regolith. Systems to perform lunar oxygen extraction are being studied and built by NASA, including the development of a system modeling tool that captures the many architecture alternatives in the system selection and design 2,3 . Several chemical processes can be used to produce oxygen from the metal oxides and glasses present in lunar soil, but because there is no historical data to draw from in the design of these systems, a detailed set of engineering models has been constructed to help assess the systemlevel trades of some of these processes.…”

Section: Introductionmentioning

confidence: 99%

“…The set of choices that comprise a system configuration are treated as discrete design variables, and the trade space is explored using a genetic algorithm. Lunar oxygen production is a good application for this architecture selection approach, because the oxygen production system can be functionally broken down into subsystems and components, a plant design involves a combination of existing and new technologies in a new environment (no historical background), and a set of models for the various subsystems already exist to populate the system model framework 2,4,5 .…”

Section: Introductionmentioning

confidence: 99%

A Modeling Framework for Applying Discrete Optimization to System Architecture Selection and Application to In-Situ Resource Utilization

Chepko

Weck

Crossley

et al. 2008

12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference

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This paper presents an approach to apply optimization to the selection of a system architecture. Early-stage design decisions that define the subsystem and component technologies that comprise a system architecture are often made with information generated from a limited number of trade studies and a historical background. These decisions can lock in a design too early, resulting in a sub-optimal or even infeasible design. Decisions for systems that have little or no historical background, such as lunar in-situ resource utilization (ISRU) systems, have only analyses and tests to be based on. To enable a wider search of the design space, a modeling framework is discussed that decomposes a system in a hierarchical fashion to describe primary subsystem functions and their technology implementation alternatives. This framework allows a system model to be built that captures all of the subsystem technology alternatives in one reconfigurable model for which the categorical, discrete technology decisions can be treated as design variables in an optimization routine. The NASA ISRU System Model follows this framework and is used as an application of system architecture optimization. A genetic algorithm is used to explore both the discrete and continuous design space of the model. Because the current ISRU System Model has a small set of discrete variables, the performance and computational cost of the genetic algorithm search are compared to a previously developed ISRU optimization scheme that involves full enumeration of the discrete variables followed by gradient-based optimization with the continuous variables. The initial tests of the genetic algorithm approach provide comparable results to the previously used approach, requiring 5100 function evaluations compared to a range of 4800-10,000 function evaluations with the enumeration methods.

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System Modeling of Lunar Oxygen Production Using Fission Surface Power: Mass and Power Requirements

Cited by 5 publications

References 5 publications

Component and System Sensitivity Considerations for Design of a Lunar ISRU Oxygen Production Plant

Component and System Sensitivity Considerations for Design of a Lunar ISRU Oxygen Production Plant

Architecture Modeling of In-Situ Oxygen Production and its Impacts on Lunar Campaigns

A Modeling Framework for Applying Discrete Optimization to System Architecture Selection and Application to In-Situ Resource Utilization

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