On Orbit Refueling Repositioning

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Roadmap Overview


On-orbit refueling and repositioning (ORR) is rooted in the need to alter spacecraft and their orbital parameters after launch. Dating back to applications for the Russian Mir Space Station and early uses for the International Space Station (ISS), OOR has taken many forms during the space age. Recent interest in the need to refuel and reposition satellites for reasons ranging from adhering to deorbit laws to wanting to extend functional satellite lifetimes has increased the need to understand OOR and predict its maturation. To this end, this technology roadmap (TMR) focuses on the capability to refuel and reposition satellite systems in orbit. This roadmap considers both traditional systems (e.g. space station resupply missions including astronaut support) as well as modernized methods (e.g. autonomous/robotic refueling operations). To carry out this analysis, a level 1 roadmap of the OOR global marketplace is captured, allowing a level 2 analysis of specific OOR products and services, which is complemented by a level 3 decomposition of OOR subsystems and components.

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DSM Allocation (interdependencies with others roadmaps)


When attempting to roadmap any technology, it is highly beneficial to map interdependencies of other roadmaps and technologies. This approach educates the architects on the system and subsystem components while also informing viewers of strong dependencies, technology pushers and pullers, and items that may have the strongest benefit to performance if improved. To this end, a DSM of OOR satellite systems is shown below. Tiers are broken down into the following categories:

Tier 1: OOR Satellite System

Tier 2: Refueling Satellite, Client Satellite, Ground Control Segment, Launch Vehicle/ Space Access, and Astronauts / Facilitators

Tier 3: Corresponding subcomponents of all Tier 2 items

Upon viewing the results shown in the DSM diagram, there are multiple notable insights gained:

Client satellites are one of the largest technology “pullers” in the DSM, highlighting their representation of stakeholder's needs and potential impact in advancing the receptivity and compatibility of client systems

Command and control (C2) of systems, for both launch vehicle and satellite systems, are a dominant reliance within the system (red boxes)

C2 serves as both a strong technology pusher as well as a puller, highlighting the potential impact on OOR capabilities if advancements are seen in C2 capabilities/technologies

The compatibility of refueler/servicer and client satellite systems (yellow box) is a strong dependency that will likely require coordination and standardization to sustain improved technology development and maturation

The transition from astronauts to autonomous/robotic systems transfers dependencies, further increasing C2 needs while reducing the risk of life/limb of humans, and likely reducing overall mission cost

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Using the knowledge gained from generating this DSM, the authors believe advancements in the following related technologies will have great benefit to the maturation of OOR systems:

Launch Vehicle Technology

C2 Capabilities

Satellite Autonomous Functions

Space Robotics

Remote Proximity Operations (RPO)

Standardized Docking Interfaces


Roadmap Model using OPM (ISO 19450)


Transitioning to an OPM diagram of On-Orbit Refueling, OPCloud was used to build the graphic below. One fundamental takeaway from this diagram is that there are limited physical aspects within the system, including the two satellites, operational ground stations, and the launch vehicle (which is outside the boundary of the system but still affects it). Notably, the Figures of Merit (FOMs) were not included in this diagram and instead are covered in the next section of this webpage. The traceability of key functions in this OPM diagram draws attention to the docking, interfacing, and overall compatibility of the servicer and client satellite systems. The functional takeaway from this figure is that refueling is the action being completed, which transits and transfers fuel from the servicer satellite to the client satellite. This fulfills the need to refuel/reposition the client satellite so that it may maneuver for a longer period of time (fixing the problem of not being able to maneuver without additional fuel). Items that are in dashed boxes still impact the system under consideration but are considered outside the scope/boundary of the system itself.

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It is powerful to provide traceability between the DSM and OPM diagram approaches, as we see in this technology. The combined importance of servicer and client compatibility, seen in both the dependencies of the DSM and the operational flow of the OPM diagram, further emphasizes the importance of mating, docking, and satellite compatibility as an enabler for broader OOR advancement.

Figures of Merit (FOM):


Looking to the figures of merit selected for this technology, these figures were chosen to track the technology's progression over time. To inform a discussion on the FOMs selected, the table below displays the selected FOMs and descriptions of the figures.

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With this technology having a unique consideration of capturing both a product as well as a service that is needed (in the form of the technology), the authors elected to analyze and track the traceability of qualities needed, how the FOMs are informed, and which stakeholder needs are identified for the technology. This level of traceability allows us to ensure stakeholder requirements are met, that we properly capture the product-service relationship, and that the FOMs created harness executable and available data and metrics.

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One of the largest benefits highlighted by the figure above is the correlation and dependency of shared technology metrics and growth related to the figures of merit. By tracing the FOMs, we see that there is available and quantifiable data to inform the figures and that they directly support not only client or servicer stakeholder needs but the combination of both as a product-service system. This knowledge further increases our confidence that the selected FOMs will effectively track the technology progression over time.


To further educate a discussion of the FOMs, the table below shows units and nominal values that the authors propose to track the technology progression over time using engineering-based data. Upon searching available literature for the required data and direct FOMs, some were easily located, while others were limited in availability or difficult to calculate. Sources used to generate nominal values and value ranges are noted in the citation column, drawing attention to real-world missions or near-term prototypes. Of the selected FOMs, the Fuel Mass Ratio was easiest to quantify, while the Mean Refuel Rate proved to be the most difficult, with total refueling time for historic missions difficult to locate for multiple missions. Even with this being the case, the authors will continue to explore this metric and attempt to capture more data in this area.

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To gather data, multiple online sources, including databases, news articles, FCC filings, and user manuals were used. The figure below (left) shows all unfiltered data found on satellite refuelers and related technology demonstrations for fuel-mass-ratios of refueling satellites. Mission dates range from 1978 to future missions in 2025. For satellites in the future, projected or advertised values were used to generate their fuel-mass-ratio values. It is also important to note that for three of the data points, calculations of fuel onboard were completed to gather the required data point. Due to the competitive landscape of on-orbit refueling, some companies limit the publicly available data to alternative metrics (e.g. lifetime extension time) that require calculation of fuel mass. These calculations were completed for the MEV-1 and MEP systems. For ease of viewing, a vertical dashed black line is included in the figures below to highlight the current day. Once the data was fully generated and plotted, a line-fit was applied to attempt to find a mathematical/quantitative rate of improvement. We see that in the left figure, a linear fit provided the most accurate prediction but is somewhat poor in overall fit with an R2 value of 0.1. To overcome this limitation, it was necessary to filter the data points to those that are most valid for the analysis.

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When selecting which data points were valid, it was necessary to track which satellites were considered state-of-the-art while also having the sole intent of transferring maximal amounts of fuel. With some of the satellites developed as prototypes to prove specific aspects of refueling in orbit, they were not built with the intent of maximizing fuel transferred, as would be the case in a fully functioning system. To account for this, any satellite that was not focused on fuel transfer or advancing the state-of-the-art in refueling was removed from the analysis to provide a more accurate view of technology trending, as seen in the above right figure. Looking at the progression trend of the filtered data, we find that a polynomial line fit is moderately effective at capturing the technology advancement, with an R2 value of 0.78. This type of line fit also better informs where the technology is likely in its maturation phase. With the FOM stagnating from 1978 to the mid-2000’s, we see a notable increase in capability in the current day as well as the near-term projected future. Bounding this within the theoretical limit (discussed later), this leads us to believe that on-orbit refueling is in the innovators / early adopters phase of its lifecycle, as covered in the MIT 16.887 class lecture (Technology Roadmapping & Development). Using the same figure from Lecture 7 (Technological Diffusion and Disruption), we assert that on-orbit refueling is within the bounds of the green box in the figure below.

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To aid this discussion, a dashed green line of technology capability was added to the figure to show a more aggressive increase in technological capability. With on-orbit refueling offering significant capabilities but also introducing significant risk to satellite systems, the authors believe there is a need to validate and more robustly verify OOR capabilities before it will be widely adopted, as seen when comparing the green dashed line with the blue customer adoption line. It is important to note that although this one FOM shows a steep increase in performance, other FOM preliminary results show somewhat similar advancement in trends. Knowing this, the S-curve of capability for on-orbit refueling is anticipated to be steeper than the one shown in yellow, validating the need for the green dashed line representation.


The final aspect of the fuel-mass-ratio plots is the theoretical limit imposed by the system on the FOM. Considering that a higher fuel-mass ratio is better for the system, this value will likely continue to improve over time but is limited by the design of satellite systems. Advancements in material sciences can make satellite components smaller and/or lighter, but there will always be a need for satellite subsystems, including structures, fuel tanks, thrusters, communications systems, etc. These systems require a portion of the mass budget on a satellite system. To account for potential advancements in space systems and related materials sciences, this theoretical limit was placed at 95% of the satellite mass (meaning 95% of the satellite mass could be fuel). Any ratio beyond this is thought to be impossible due to the mass needs of the other satellite subsystems for a fully functioning refueling system.

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