A Holistic Approach for Efficient Greener In-Space Propulsion

Abstract

This paper presents a comprehensive framework for designing in-space propulsion systems, integrating four criteria: global propulsive performance, environmental impact, cost efficiency, and architectural reliability. The study focuses on the emerging class of Orbital Transfer Vehicles to illustrate the application of this method. By examining the synergistic potential of OTVs and greener propellants, the paper addresses different mission scenarios, including LEO, GEO, and lunar missions, with both scientific and commercial objectives. The proposed framework aims to go beyond traditional cost-centric approaches, offering a more complete evaluation method for early design phases. A case study comparing three liquid bipropellant options, pressure-fed MON-3/MMH, 98%-HTP/RP-1, and self-pressurizing N2O/Ethane, demonstrates the utility of the tool. Findings suggest that scientific missions benefit most from 98%-HTP/RP-1, while traditional propellants remain preferable for cost-driven commercial missions to GEO and the MOON, though greener alternatives are competitive for less demanding LEO missions. This innovative framework aims to guide the selection of propulsion systems to achieve greener space missions, aligning traditional performance figures with environmental responsibility.

Full text

Acta Astronautica 223 (2024) 435–447
Available online 14 July 2024
0094-5765/© 2024 The Authors. Published by Elsevier Ltd on behalf of IAA. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
A holistic approach for efcient greener in-space propulsion
Lily Blondel-Canepari
1,*
, Alberto Sarritzu , Angelo Pasini
Universit`
a di Pisa, Department of Civil and Industrial Engineering (DICI) –AeroSpace Division, 56122, Pisa, Italy
ARTICLE INFO
Keywords:
Orbital Transfer Vehicle (OTV)
Greener propulsion
Life Cycle Assessment (LCA)
Comparative system analysis
Propulsive performance
Environmental impact
Cost efciency
Reliability of architectures
ABSTRACT
This paper presents a comprehensive framework for designing in-space propulsion systems, integrating four
criteria: global propulsive performance, environmental impact, cost efciency, and architectural reliability. The
study focuses on the emerging class of Orbital Transfer Vehicles to illustrate the application of this method. By
examining the synergistic potential of OTVs and greener propellants, the paper addresses different mission
scenarios, including LEO, GEO, and lunar missions, with both scientic and commercial objectives. The proposed
framework aims to go beyond traditional cost-centric approaches, offering a more complete evaluation method
for early design phases. A case study comparing three liquid bipropellant options, pressure-fed MON-3/MMH,
98%-HTP/RP-1, and self-pressurizing N
2
O/Ethane, demonstrates the utility of the tool. Findings suggest that
scientic missions benet most from 98%-HTP/RP-1, while traditional propellants remain preferable for cost-
driven commercial missions to GEO and the Moon, though greener alternatives are competitive for less
demanding LEO missions. This innovative framework aims to guide the selection of propulsion systems to
achieve greener space missions, aligning traditional performance gures with environmental responsibility.
1. Introduction
The increasing demand for space access and payload deployment has
intensied the need for advanced, reliable, and sustainable in-space
propulsion systems. Propulsion systems are essential for achieving
mission objectives, from precise satellite positioning to deep-space
exploration. As the space industry evolves, the focus is shifting to-
wards developing technologies that not only enhance performance but
also adhere to stringent environmental standards.
Traditionally, the design of propulsion systems has prioritized high
propulsive efciency and cost-effectiveness. Chemical thrusters, partic-
ularly those using hydrazine and its derivatives (MMH, UDMH) along
with Dinitrogen Tetroxide (NTO), have been the backbone due to their
high performance and maturity. However, these propellants are highly
toxic, posing signicant health risks during handling and necessitating
stringent safety measures that drive up operational costs [1,2].
The European Union’s classication of hydrazine as a Substance of
Very High Concern has accelerated the push towards greener alterna-
tives [3–5]. This shift is not only a regulatory response but part of a
broader industry trend towards sustainability. Indeed, modern space
missions increasingly demand propulsion solutions that balance tech-
nical performance, environmental impact, and cost.
As a central part of the spacecraft, propulsion systems are also
complex and therefore highly susceptible to failure, accounting for
approximately 50% of mission failures [6]. This failure rate reects the
complexity and sensitivity of these systems, which consist of many
active components and mechanisms. Typically, propulsion systems
include a high-thrust main engine for major orbital manoeuvres and a
low-thrust reaction control system for precise attitude adjustments, with
thrust requirements tailored to the satellite’s dimensions.
To address these challenges, this paper proposes a holistic early
design framework for in-space propulsion systems, integrating four key
metrics: global propulsive performance, environmental impact, cost ef-
ciency, and architectural reliability. By focusing on the emerging class
of Orbital Transfer Vehicles (OTVs), the study illustrates the application
of this method to various mission scenarios, including Low Earth Orbit
(LEO), Geostationary Orbit (GEO), and lunar missions with both scien-
tic and commercial objectives. This innovative framework aims to go
beyond traditional cost-centric approaches, offering a more compre-
hensive evaluation method for early design phases. The paper is struc-
tured as follows:
* Corresponding author.
E-mail address: lily.blondel@ing.unipi.it (L. Blondel-Canepari).
1
Lily Blondel-Canepari Scopus ID is: 57562046100.
Contents lists available at ScienceDirect
Acta Astronautica
journal homepage: www.elsevier.com/locate/actaastro
https://doi.org/10.1016/j.actaastro.2024.07.023
Received 31 January 2024; Received in revised form 17 June 2024; Accepted 11 July 2024

Acta Astronautica 223 (2024) 435–447
436
1. Introduction: This section outlines the evolving dynamics of space
activities, focusing on the specic requirements of orbital stages
which serve as the reference system for this study. It emphasizes the
need to expand the criteria for propulsion system selection beyond
traditional cost and performance metrics, incorporating environ-
mental impact and reliability as key considerations.
2. Insights into the four gures of Merits: This section details the
motivation and implementation strategies for each criterion:
⁃Propulsive Performance: Assessing the efciency and capability
of propulsion systems to meet mission requirements.
⁃Cost Efciency: Considering the economic aspects of propulsion
system selection.
⁃Environmental Performance: Evaluating the environmental
impact of different propellant choices and their related systems
over their life cycle.
⁃Reliability of the Architecture: Ensuring that propulsion systems
are steady over the mission’s duration.
3. Methodology and Results: This section introduces a novel scoring
method that integrates these four gures of merits into a single score
to guide the selection process. This approach allows for a thorough
assessment that aligns the propulsion system design with the mis-
sion’s broader objectives. Results are presented for a baseline orbital
stage propulsion system, ne-tuned to each propellant combination
towards the realisation of three generic mission scenarios.
By adopting this holistic framework, the paper encourages for a shift
in propulsion system design, that prioritizes sustainability and long-term
reliability alongside traditional performance and cost metrics, thereby
addressing the contemporary challenges of designing in-space propul-
sion systems.
1.1. Space landscape &in-space propulsion
Fig. 1 illustrates the rapid expansion of space activities, showing a
119% increase in rocket launches and a 541% rise in payload de-
ployments from 2019 to 2023 [7]. This gure also reveals a signicant
jump in the payload-to-launch ratio, climbing from 4.28% in 2019 to
12.54% in 2023 [7]. Such growth indicates not only increased launcher
efciency but also advances in miniaturization technologies that allow
more payloads to be carried within a single launch. As the number of
payloads and missions increases, there is a growing need for robust
in-space logistics systems, comparable to those on Earth, to efciently
handle the inux of new systems and assist them toward potentially
longmissions. Central to this discussion is the orbital stage, which
operates similarly to Earth’s public transportation systems by offering
rideshare capabilities that reorganize the logistics of deploying and
managing payloads in space [8]. This strategy not only simplies space
operations but also meets the growing demands for on-orbit servicing.
The orbital stage therefore serves as a versatile platform, adaptable to
the diverse and evolving needs of what is now known as the New Space
era [9], ensuring operational efciency and scalability.
The numbers shown in Fig. 1 indicate a signicant increase in the
frequency of payload launches. This rise in activity necessitates the
manufacturing of more in-space propulsion systems to be integrated into
each payload, making it important to assess and mitigate the environ-
mental impact of manufacturing and using these systems to ensure the
sustainable development of space activities.
Chemical propulsion systems, particularly bipropellant ones, remain
the cornerstone for in-orbit maneuvers and interplanetary transfers due
to their proven performance, reliability and controllability [10]. While
in essence, the approach proposed here, and especially the tool, could
accommodate any type of in-space propulsion, it is primarily aimed at
and developed for chemical liquid propulsion systems. For bipropellant
systems, usually selected for Orbital Stages due to their higher perfor-
mance compared to monopropellant ones, three baseline systems are of
main interest to this study:
•The legacy hypergolic based on NTO or MON-3 as oxidizer and
MMH, a derivative of Hydrazine, as fuel.
•The “greener induced-hypergolic”based on Hydrogen Peroxide
(H
2
O
2
) typically in combination with a low-vapor-pressure hydro-
carbon. This combination becomes hypergolic after the catalytic
decomposition of Hydrogen Peroxide.
•The self-pressurizing one using Nitrous Oxide (N
2
O) usually paired
with a high vapor-pressure hydrocarbon. In this setup, the pro-
pellants are stored in saturation conditions, effectively pressurizing
themselves, by having high-enough vapor pressure to sustain a ow
in the pipelines. This design eliminates the need for external pres-
surization system required in other propellant architectures [11].
In bipropellant systems, the predominant liquid oxidizers –NTO,
HTP, and N
2
O–serve as basis for the different possible propulsion
systems. The choice of fuel, to pair with these oxidizers, is then strate-
gically important to fully leverage their respective properties [12].
1.2. Design approach: classic vs holistic
The design of spacecraft propulsion system is evolving, shifting from
a traditional focus on cost-effective solutions with high specic impulse
to a more holistic approach that includes criteria such as environmental
Nomenclature
C
2
H
6
Ethane
H
2
O
2
Hydrogen Peroxide
HTP High Test Peroxide
LRE Liquid Rocket Engine
MMH MonoMethylHydrazine
MON Mixed Oxides of Nitrogen
N
2
O Nitrous Oxide
NTO Nitrogen Tetroxide
O/F Oxidizer to Fuel ratio inside the Combustion Chamber
P
C
Pressure in the Combustion Chamber [bar]
RP-1 Rocket Propellant-1
I
sp
Specic Impulse [s]
TACS Trajectory and Attitude Control System
UDMH Unsymmetrical DiMethylHydrazine
ΔvChange of velocity required for orbit change/orbit
maintenance [m/s]
ρ
Density [kg/m
3
]
Fig. 1. Launches &Payload Evolution over the last 23 years [7].
L. Blondel-Canepari et al.

Acta Astronautica 223 (2024) 435–447
437
impact and reliability estimations from the early design phases. While
the traditional methods historically successfully met the primary re-
quirements for effective propulsion, they often overlooked broader
concerns such as environmental sustainability. For example, the wide-
spread use of hydrazine-based propellants, despite the high performance
delivered, presented and still presents serious toxicity and environ-
mental risks.
The holistic design approach proposed in this paper aims to address
these oversights by incorporating Life Cycle Analysis (LCA) and early
reliability estimations alongside the traditional measures of cost and
propulsive efciency in the design trade-offs. An example of this
expanded perspective is the global interest in developing alternative
“green”propellants, which are supposed to have reduced toxicity
compared to hydrazine. However, to ensure a genuinely sustainable
approach, it is necessary to evaluate their performance across all envi-
ronmental categories and throughout their lifecycle, employing tools
like LCA to avoid shifting the environmental burden to other areas. This
is particularly important for emerging companies during the propellant
selection phase, as this choice fundamentally inuences the design of
their propulsion system, which they will rely on for many years once
qualied for operation.
This early-stage integration of diverse criteria allows for a more
balanced and informed decision-making process in propulsion system
selection, aligning with the specic goals and constraints of a mission.
For example, the European Space Agency’s (ESA) Clean Space initiative
exemplies this approach, aiming to minimize space debris and to
reduce the environmental footprint of space missions.
In essence, this transition towards a more holistic design philosophy
in spacecraft propulsion systems marks a signicant paradigm shift in
how space missions are planned and executed. It reects a growing
awareness of the need for sustainability and reliability in space explo-
ration, ensuring that propulsion systems are adaptable, environmentally
compatible, and durable for increasingly complex missions. This inte-
grated approach encourages towards a new phase in space exploration,
where technical performance, cost-efciency, environmental consider-
ations, and long-term reliability are all weighed against the specic
requirements and objectives of a mission in its early denition stage.
1.3. The reference system: the Orbital Stage
An Orbital Stage is chosen as the reference system for this study.
Although the proposed approach is broadly applicable to different types
of in-space propulsion, it is particularly benecial for the Orbital Stage
due to its potential to enhance the logistics of the contemporary space
sector. In recent years, a new class of platforms known as Kick Stages (KS)
or Orbital Stages has emerged as a transformative technology. Indeed,
these Orbital Transfer Vehicles are essential to future space missions for
their ability to facilitate complex orbital manoeuvres and logistics. They
act as additional modules to standard launch vehicles, signicantly aiding
in the accurate delivery of payloads to specic orbits.
As a new category of systems, OTVs are ideal for integrating inno-
vative technologies, making them perfect candidates for implementing
“greener”propellants. Fig. 2 indeed illustrates the growing trend to-
wards utilizing these “environmentally friendly”propellants in Kick
Stages propulsion systems worldwide. One primary objective of this
study is to demonstrate the feasibility and benets of greener propulsion
in future missions, which is why the Kick Stage is selected as the refer-
ence system.
Kick Stages represent a unique class of spaceborne vehicles that
redene space access by accurately positioning payloads into specic
orbits, signicantly simplifying space mission logistics. For instance,
Rocket Lab’s collaboration with Kin´
eis aims to deploy 25 Internet of
Things (IoT) satellites across ve missions, starting in the second quarter
of 2023. The Electron’s kick stage will act as an orbital transfer vehicle,
delivering each satellite to a 650 km altitude orbit, thus maximizing the
spacecraft’s payload capacity and accelerating its transition to opera-
tional service. The proven accuracy and reliability of Rocket Lab’s kick
stage, with over 100 satellite deployments, demonstrate its capability to
manage intricate deployment patterns with high precision [13–16].
In Europe, advancements in Kick Stage technology are also
reshaping space missions, through projects such as the development of
the Ariane 6’s ASTRIS kick stage and of its successor, LunaNova,
implementing a greener propellant combination, for Ariane 6 Evolu-
tion [17]. These orbital stages enhance Ariane 6’s capabilities,
enabling complex orbital transfers, and reducing the propulsion system
burden on satellite manufacturers, which facilitates launching satellite
constellations, and supports deep space and lunar missions. Their
modular architectures can be tailored for specic mission re-
quirements, positioning Europe strategically in the global space market
[18–20]. Building on this concept, this study highlights the synergistic
benets of pairing orbital stages with greener propulsion technologies,
which not only minimize environmental impact but could also enhance
performance. The transition to less toxic and more manageable pro-
pellants like hydrogen peroxide and self-pressurized systems repre-
sents a signicant shift in propulsion methods which facilitates the
development of innovative space vehicle designs and boosts the overall
efciency of space missions.
2. Insights into the four gures of merits
This section methodically examines each of the four gures of merit
in the analysis. It digs into the underlying rationale behind their selec-
tion and implementation, offering a concise overview of their respective
methodologies. The discussion is structured to provide a clear under-
standing of why each gure of merit is crucial to the analysis and how
each one contributes to the overall evaluation process.
2.1. The propulsive performance
The evaluation of global propulsive performance extends beyond
simply maximizing specic impulse, acknowledging that system con-
straints and/or other parameters may inuence the selection of a pro-
pulsion system that does not necessarily align with the one optimizing
the specic impulse. This broader metric incorporates criteria such as
oxidizer-to-fuel ratios, propellant densities, and propulsive architecture
congurations that promote efcient mass balance and facilitate pro-
pellant storage in tanks of comparable volumes. As a result, the payload
ratio, dened as mpayload/m0(where m
0
represents the total mass of the
kick stage), is selected as primary output of this function. This metric
measures the mass fraction of a spacecraft that can be dedicated to the
payload. An increased payload ratio indicates higher mission capability
by reducing the mass allocated to propulsion, m
propulsion
, thereby
improving the mass efciency of the propulsive system. The objective is
therefore for each system to maximize its payload ratio and to establish a
benchmark for comparing the various propulsion options under
consideration.
Fig. 2. Comparison of kick stage liquid propulsion systems in US and in Europe.
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Acta Astronautica 223 (2024) 435–447
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The starting point of the study was a propulsion trade-off study
aiming at evaluating the cost impact of transitioning from the legacy
MON-3/MMH to a greener 98%-HTP/Kerosene for classic kick stage
missions. The study detailed the system mass breakdown as follows
[19]:
m0=mstructure +mpayload +mpropulsion (1)
Where the total mass of the kick stage was divided into its structural
mass mstructure, payload mass mpayload , and propulsive system mass
mpropulsion. The performance of the different propellant options was
assessed in terms of payload-to-launch gain or loss and of their corre-
sponding costs, calculated through internal computations considering
the projected missions for the kick stage. Table 1 shows that tran-
sitioning from ASTRIS to LunaNova and shifting from traditional MON-
3/MMH to the more environmentally friendly 98%-HTP/Kerosene pro-
pellants, consistently reduces the payload capacity, m
payload
, across all
mission types.
Confronted with these results indicating the relatively lower per-
formance of “greener”propellants compared to their legacy counter-
parts, the motivation arose to further detail the initial mass breakdown
of the propulsion system from Equation 1 to Equation 2. In terms of
propulsive performance estimation, this assessment focuses on reducing
the different mass gures contributing to the inert propulsive mass, with
the ongoing objective of maximizing the payload ratio.
m0=msc dry +mfeeding system +mpressurant +minert propulsion +mpropellant +mpayload
(2)
The primary objective of this rst optimization metric is to improve
the efciency of the propulsive system. This goal is achieved by reducing
the inert mass allocated for propulsion and increasing the available mass
and volume for the payload. The efciency of propellant combinations,
as measured by specic impulses, is calculated using the Rocket Pro-
pulsion Analysis tool (RPA) [21]. These calculations are based on
operational parameters specic to the propellant combination and on
the mission scenario. In terms of feeding architectures, four possibilities
are implemented: blow-down, pressure-fed, electric pump fed [22] and
self-pressurizing. Naturally, certain propellant combinations are only
compatible with certain types of feeding systems.
For different architectural designs, the masses of tanks, thrusters, and
pressurizing systems are computed and compared based on the
following considerations:
- In self-pressurizing systems, the mass of the pressurizing system is set
to zero.
- For e-pump systems, the mass of the pressurizing system includes
both the pumps and the associated solar panels for power supply.
- In systems requiring pressurizing gas, such as pressure-fed and
electric pump-fed congurations, Helium is utilized and stored in a
spherical titanium alloy tank with carbon bre reinforced polymer
(CFRP) overwrap. The tank’s wall thickness and mass calculation are
derived from minimum thickness relationships, considering the
required gas mass to pressurize the propellant, an initial pressure of
200 bars, and a 20% safety margin on the nal operational pressure
in the propellant tanks.
The characteristics of the propellant tanks, including thickness,
mass, and volume, are determined by two main factors: the amount of
propellant required to fulll the mission and the pressure needed in the
propellant tank to achieve the desired operational pressure in the
combustion chamber. For the pressure-fed systems analysed in this
paper, the combustion chamber pressure is set at 15 bars, assuming a
30–35% pressure drop from the propellant tanks to the combustion
chamber. All the propellant tanks considered in this study are cylindrical
with hemispherical heads. Tanks for MON-3/MMH are made in titanium
alloy, the self-pressurized ones for N
2
O/Ethane are produced in titanium
allow with CFRP overwrap with an initial pressure of 60 bars while tanks
for 98%-HTP/RP-1 are constructed from aluminium alloy 6060 with
CFRP overwrap.
Additionally, a xed dry mass msc dry, accounting for 15% of the
spacecraft total wet mass m
0
, is allocated for structural components and
electronics, aspects not covered in this study.
This section of the tool also considers conguration aspects, aiming
to achieve similar tank volumes for both oxidizer and fuel while main-
taining a balanced mass distribution. As illustrated in Table 2, the sig-
nicant differences in the densities and oxidizer-to-fuel ratios across the
various combinations highlight the necessity for distinct congurations.
In addition to the values reported in Table 2, it is important to
highlight that, within the range of temperature considered during op-
erations, physical characteristics of the propellants are assumed to be
constant. In the case of common storable liquids such as MON-3/MMH
and 98%-HTP/RP-1, the hypothesis is justied, while for N
2
O/Ethane
combination additional care should be given to the maximum expected
temperature. Indeed, the propellants are stored in saturation equilib-
rium, and the density and pressure of N
2
O and Ethane can change
signicantly (by a factor of 1.4–1.6) as they approach 36◦C and 32◦C,
respectively. Therefore, the maximum expected temperature greatly
impacts the mass and volume budget, with higher temperatures leading
to worse performance and the need for more robust components. As a
result, self-pressurizing systems become much less competitive when the
expected maximum temperature increases.
Table 3 introduces the three generic mission scenarios considered in
this study: an orbital stage performing multi-orbit and multi-payload
deliveries to Low Earth Orbit (LEO), Geostationary Orbit (GEO), and
to the MOON. The metric to compare these systems is the payload ratio.
Results indicate that while greener propellant systems show similar
capabilities to the legacy one for LEO missions, signicant differences
emerge as the mission becomes more demanding in terms of Δv re-
quirements. Indeed, as mission demands increase, the proportion of
mass allocated to the propulsive system also increases because of the
growing need for propellant, reducing the space available for the
payload. Therefore, the performance of the propulsion system for highly
demanding missions is increasingly driven by the I
sp
.
Table 1
Loss in payload mass capacity, mpayload, for LunaNova missions due to replacing
conventional propellants (MON3/MMH) by greener ones (98%-HTP/RP-1) [19].
Percentage of Payload Capacity Penalty [%]
Lunar Orbits NRHO 4.1
LLO 4.1
Earth Orbits SSO 0.8
A62 GEO 4.4
A64 GEO 4.1
A62 MEO 4.3
A64 MEO 4.0
A64 GEO 3.6
Table 2
Properties of Three Representative Propellant Combinations for Orbital Stages [21,23]. Combustion Pressure of 15 bars.
I
sp
[s] Oxidizer Density [kg.m
−3
] at 20 ◦C Fuel Density [kg.m
−3
] at 20 ◦C Optimal O/F
MON3/MMH 325 1440 875 1.65
98%-HTP/RP-1 305 1437 800 7.5
N
2
O/Ethane 295 785 340 7.0
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2.2. The cost efciency
This second metric focuses on evaluating the cost efciency of
various propulsive options in terms of their intrinsic costs. Once the
propulsive architecture is established and the payload capacity is
derived, the latter is translated into cost following a similar approach to
the one outlined in Section 2.1. The subsequent computation includes
the costs of: propellants, tanks, thrusters and feeding systems based on
their masses (as derived in 2.1) and on their estimated maturity levels.
The cost estimation for these components, excluding propellants, relies
on historical cost data and considers whether the system already exists
or needs to be developed from scratch, considering qualication costs.
For the development of new tanks, thrusters, or other components, the
estimated cost is projected to be three to four times the cost of an
existing system.
This evaluation provides a baseline comparison of the relative cost-
effectiveness of each propulsion option. While current operational
costs, which uctuate based on logistics and market factors, are not yet
integrated into this analysis, it offers an initial cost estimation of the
propulsive architecture selected under the rst metric. Indeed, both
recurring and non-recurring costs are evaluated together with most of
the components used in each architecture. It is important to note that
current cost estimations do not yet account for the variable costs asso-
ciated with different tank materials. This aspect will be an essential
addition, offering a more nuanced and accurate cost analysis that re-
ects the full spectrum of material and design choices in spacecraft
propulsion systems.
Overall, this cost efciency analysis aims to provide stakeholders
with a clear, quantiable understanding of the nancial implications of
different propulsion congurations, aiding in the decision-making pro-
cess for space missions. The output of this metric is the relative cost of
the different propulsion architectures, rather than the absolute ones.
Table 4 presents the estimated relative costs of the three different
propulsion architectures considered across the three generic mission
scenarios. Although the self-pressurized architecture saves costs by
eliminating the need for an external pressurizing tank, it remains the
most expensive option for both LEO and GEO missions. This higher cost
is due to its early development stage, which incurs signicant quali-
cation expenses. These qualication costs bring a disadvantage for novel
propulsion systems as compared to established ones. Additionally, the
propellant tanks for N
2
O/Ethane are notably heavy, further increasing
costs. However, the low cost of the self-pressurized propellants helps to
balance this aspect as mission demands increase, like for the MOON
mission.
2.3. The environmental performance
The third metric addresses the environmental impact of various
propulsion systems, evaluated through Life Cycle Analysis (LCA). This
analysis, conducted at the European Space Agency with the SimaPro
software, uses data on propellants and materials specic to space ap-
plications. Due to the numerous impact indicators involved in this
metric, a unied environmental score has rst been developed. This
score normalizes and weights all indicators into a single nal output,
Table 3
Mass breakdown for the three propulsion systems evaluated across the three generic mission scenarios.
Table 4
Cost comparison of the three propulsive systems under study evaluated across the three generic mission scenarios considered.
Relative cost gures are expressed as percentages of the most expensive one. More detailed computations can be found in the
related publication [24].
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Acta Astronautica 223 (2024) 435–447
440
offering an alternative to the one of the Product Environmental Foot-
print (PEF) typically used in LCA. Unlike the PEF’s one, which is not
specic to space applications, this unied score provides tailored
weights and considerations that are thought more relevant and accurate
for evaluating the environmental impact of space propulsion systems.
Environmental scores are derived using “damage-based indicators”and
are quantied in “Points”.
The development of this single score method involved two rounds of
surveys, conducted using the Analytical Hierarchy Process (AHP) [8,
25], and sent to research institutes, aerospace industries, and the LCA
community. The AHP is a decision-making tool that simplies complex
choices by breaking them down into smaller, more manageable com-
parisons. It involves identifying a main goal, establishing
decision-making criteria (here, the seventeen impact indicators),
ranking these criteria through pairwise comparisons, and then using the
established framework to evaluate different options. This process is ideal
for informed and systematic decision-making in scenarios with multiple
factors and options, ensuring clarity and consistency in selecting the best
alternative [8,25].
In Life Cycle Assessment, two types of indicators are commonly used:
midpoint and endpoint indicators. Midpoint indicators focus on specic
environmental problems, such as use of fossil fuel resources or air
acidication. They are more immediate and, in general, easier to mea-
sure. Endpoint indicators, on the other hand, represent the broader and
nal impacts of environmental aspects on areas like human health,
biodiversity, and resource scarcity. These are more aggregated and
interpret the ultimate consequences of environmental issues but also
come with increased uncertainty due to their broader scope. In sum-
mary, midpoint indicators provide a closer look at specic environ-
mental impacts, while endpoint indicators give an overall picture of the
nal effects on key areas of concern [26].
By categorizing the 17 midpoint impact indicators of Fig. 3 into 5
endpoint groups, the survey process was simplied, reducing the num-
ber of required questions from 136 to just 31. Grouping the indicators
eliminated the need to compare each of the 17 indicators against the
other 16. Indeed, in a traditional two-by-two AHP comparison, 17 in-
dicators would require 136 pairwise comparisons.
However, by separating the indicators into 5 groups, with each group
containing either 3 or 4 sub-impact indicators, the number of pairwise
comparisons needed was reduced to 31. From the 50 responses received
it was notably observed that greater emphasis was placed on toxicity,
contingent upon resource use, compared to the weights provided by
PEF. This shift could be explained by the framework of the survey,
propulsion, which is in general associated with explosion, danger and
toxic compounds. However, there was a common agreement that Global
Warming remains the prominent concern.
The goal of introducing this metric is to standardize green labelling
for propellants and to understand their overall environmental impact,
rather than focusing solely on reducing toxicity. The Globally Harmo-
nized System of Classication and Labelling of Chemicals (GHS) offers a
1:5 toxicity scale [27], but it is considered insufcient for distinguishing
the environmental benets of greener propellants. Hence, a more
comprehensive environmental efciency metric is being developed,
particularly for propellants aimed at replacing hydrazine for
in-space-propulsion. This approach aims to provide a deeper and more
holistic understanding of environmental impacts beyond just toxicity
levels.
For in-space propulsion, the study is performed from cradle-to-gate,
incorporating the different ground life phases displayed in Fig. 4 when
referred to as “loading”.
The gures relevant to this section are based on the “Space Propel-
lant Life Cycle Assessment”study conducted by the European Space
Agency in 2016 [28]. The database developed then has been expanded
to include new propellants of interest and updated to reect the current
trends for existing ones.
Applying LCA to space missions is notably complex due to the goal-
oriented nature of these missions and the unique production processes,
scales, and methods used in the space industry. Another signicant
challenge is the collection and modeling of data, particularly given the
uncertainties regarding the precise consumption of energy and resources
or of potential contaminations. To address these uncertainties, Monte
Carlo uncertainty analysis is applied to the data quality inputs of various
data points. For example, Fig. 5 illustrates the Global Warming Potential
(GWP), impact identied as most concerning by both PEF and the AHP
survey, which quanties how much CO
2
is emitted to produce 1 kg of
each propellant. The results, normalized to the CO
2
emissions of pro-
ducing 1 kg of Hydrazine show that all propellants considered in this
study, except MMH, are less impactful than Hydrazine in terms of GWP.
Each environmental indicator uses a specic method to convert in-
ventory values into actual environmental impacts. These methods are
standardized and enable the quantication of resultant environmental
effects.
A key feature of an LCA study is its reliance on a functional unit. For
propellant LCAs, this unit typically represents “loading 1 kg of
Fig. 3. Seventeen Midpoint Indicators Considered in the Study and their Respective Groups.
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Fig. 4. Ground Life Phases from Production to Gate. Phases to Consider for LCA of in-space propellants.
Fig. 5. Monte Carlo Uncertainty Analysis of the Global Warming Potential (GWP) in terms of kg of CO
2
equivalent to produce 1 kg of the different propellants
considered. Mean values are expressed in percentage of the CO
2
equivalent mass emitted for producing 1 kg of Hydrazine.
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propellant”into the launcher. However, as outlined in Table 2, different
propellants exhibit varying propulsive performances. Therefore, the
tool’s mission-specic purpose integrates a system-wide perspective,
accounting for the total mass of propellants needed to full the mission,
based on the selected combination and on its operative mixture ratio.
This approach is illustrated in Table 5, which reports the environmental
impact of loading the entire propellant mass required for the three
propulsion options to full the three mission scenarios. Similar to the
cost analysis, the relative impact is normalized to the most impactful
combination. The latter is consistently the legacy MON-3/MMH
conguration, primarily due to the space-specic, energy-intensive
production process of MMH.
2.4. The reliability target
The fourth gure of merit evaluates the reliability of the propulsive
architecture selected in Section 2.1. This criterion aims to simplify the
architecture to increase its reliability, thereby ensuring it meets the
specic reliability targets required by the mission scenario under
consideration. Initially, the architecture’s reliability is calculated based
on the minimum number of components necessary for nominal opera-
tion. Starting from this, redundancy is integrated at critical points to
address operational demands and propellant characteristics specic to
the mission.
The rationale for this approach is supported by two studies. The rst
study, an analysis of space launch vehicle failures from 2006 to 2021
highlighted a critical insight: out of 1363 launch attempts, 5.8% resulted
in failures. Although this failure rate is relatively low, a signicant
portion, 54% as shown in Fig. 6, of these failures were linked to pro-
pulsion system malfunctions, pinpointing it as a critical area for
improvement. Notably, the majority (30 out of 31) of these propulsion-
related failures involved Liquid Rocket Engines (LREs). Further inves-
tigation revealed that 65% [6] of these LRE failures originated from
issues within the feeding systems or associated components such as
Table 5
Relative environmental impact of loading the necessary propellant quantities for three mission scenarios for the three different
propulsion systems. Values are normalized and presented as percentages relative to the highest impact option, MON-3/MMH,
for all scenarios. These values were primarily derived from the single-score total impact, combining results from 15 impact
indicators, as detailed in the related publication [29].
Fig. 6. Launch Failures from 2006 to 2021 classied by subsystem [6].
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valves, as reported in Fig. 7. The same study showed that 2020 experi-
enced the lowest launch success rate in 15 years, stressing the necessity
of focusing on reliability improvements in propulsion systems.
A second study examining Earth-orbiting satellites launched between
1990 and 2008 [30] revealed that thruster and fuel component failures
were principal contributors to early satellite malfunctions, particularly
in the rst year of operation as shown in Table 6. This trend, known as
the “infant mortality phenomenon”, highlights the necessity for a
reliability-focused approach during the initial design stages of space-
crafts [31].
Given the high incidence of propulsion system failures in launch
vehicles and early failures in satellite propulsion systems, it is crucial to
integrate reliability assessment early in the design process. Traditional
methods often delay these assessments to later stages, whereas the
present tool aims at introducing them already during the preliminary
design phases, signicantly increasing the system’s overall robustness
downstream.
For orbital transfer vehicles, which bridge the complexity gap be-
tween launch vehicles and satellites, prioritizing reliability is even more
imperative due to their role as service provider for multiple customers.
By integrating reliability as a key gure from the early design phases,
potential risks can be mitigated, enhancing the success rates of space
missions. This approach aims not only at boosting the likelihood of
mission success but also fostering the development of more reliable
space propulsion technologies.
The methodology to implement the reliability estimation is based on
the development of baseline architectures for the different propellant
combinations and determining their overall reliability over one year of
operation. The architectures are designed with the minimal number of
components necessary for efcient engine operation and their reliability
is assessed through fundamental equations. The propulsive architecture
is broken down into block diagrams, composed of the single
Fig. 7. Launch failures caused by malfunctions of Liquid Rocket Engine (LRE),
classied by components [6].
Table 6
Failures by subsystem [30].
SUBSYSTEM 30 days 1 year
Thruster/Fuel 13 % 20 %
Table 7
Reliability block diagram representations. The conguration of the architecture selected in the rst metric is decomposed into series and parallel components.
Type Block Diagram Representation System Reliability (RS)
Series
R
S=RARB
RA=reliability, component A
RB=reliability, component B
Parallel
R
S=1− (1−RA)(1−RB)
Series - Parallel
R
S= [1− (1−RA)(1−RB)]•
[1− (1−RC)(1−RD)]
RC=reliability, component C
RD=reliability, component D
Parallel - Series
R
S=1− (1−RARC) • (1−RBRD)
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components. The blocks are considered in series for nominal operation,
and the reliability calculated with the formulas in Table 7. This method
facilitates an overall reliability estimation of the baseline propulsive
architecture. While it does not yet identify potential failure points, it
provides an estimation of the necessary mitigation strategies to imple-
ment in terms of redundancies.
The calculations are based on several assumptions: a constant failure
rate, an exponential distribution for reliability, statistical independence
of events, steady-state operation, binary basic events (either “fully
functional”or “failed”), the absence of failed components at the start (t
=0), immediate transitions between binary states, non-repairable
components, and all components being operative initially. The reli-
ability of an individual component with a constant failure rate, λ, is then
given by:
R(t) = e−λt(3)
Here, trepresents the operating time. For a more thorough reliability
assessment, more complex failure rate probability distribution functions
should be implemented.
The study considers as baseline the simple bipropellant architecture
displayed in Fig. 8 with one tank per propellant and no redundancy in
place.
After the initial reliability assessment, the impact of introducing
parallel redundancies is studied for specic components, excluding the
main thruster, electric-pump and tanks from these redundancy schemes.
The computations show that, as expected, adding redundancies to
components with the most signicant inuence on system reliability
brings the greatest improvement. Specically, the addition of pressure
measurements has an unexpected impact because these components are
particularly prone to failure.
In conclusion, the fourth metric produces an estimated reliability
score for the different possible propulsive congurations, determined by
its layout and by the number of components involved. It is designed to
function synergistically with the rst, second and third metrics (pro-
pulsive efciency, cost and environmental impact), enabling an analysis
of how various congurations might reduce mass, cost and environ-
mental impact while still achieving the desired reliability standards.
Table 8 presents the reliability estimations for the baseline propul-
sive architecture shown in Fig. 8, ne-tuned to the different propellant
combinations. The results are normalized to the most reliable congu-
ration, the self-pressurized system. As anticipated, the self-pressurized
architecture, characterized by fewer components and a simpler design,
exhibits higher reliability. Nonetheless, the reliability disparity with
other systems is small.
Fig. 8. Baseline Bipropellant Propulsive Architecture: Solid lines indicate components common to all three types of propulsion systems, whereas dashed lines identify
components unique to specic propellant combinations [31].
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3. Reaching an outcome
The approach outlined in previous sections is designed to align a
specic mission scenario with its most suitable propulsion system. This
methodology is currently being developed within a Python-based tool
environment. Its framework is visually illustrated in Fig. 9, with the four
key gures of merit marked in orange. This graphical representation
illustrates the iterative process of rening the architecture congura-
tions through the interplay of these four gures of merit. Upon
completion of these iterations, the objective is to arrive at a denitive
conclusion that aligns with the specic goals of the mission being ana-
lysed. This section is dedicated to achieving that precise outcome,
focusing on how the integration of these elements leads to an optimized
propulsion system choice for the mission in question.
3.1. Single score to reect the purpose of the mission
Upon completing the exploration of all pertinent estimations and
conguration loops, with the objective of selecting and rening poten-
tial congurations, the process advances to the selection stage. Future
research aims to integrate an optimization process for the selected sys-
tem and its operational parameters, though this is not currently within
the scope of the tool. Presently, the concluding phase employs a single-
score methodology, designed to facilitate a denitive choice of system,
aligned with the specic objectives of the mission. This approach en-
sures a targeted and efcient selection process based on the mission’s
unique requirements.
This single-score methodology once again utilizes the Analytic Hi-
erarchy Process, which is briey outlined in Section 2.3. However, in
this instance, the criteria being compared are the four key metrics:
propulsive performance, cost efciency, environmental impact, and
reliability. This approach differs from the previous application of the
process, where it weighted the 17 impact indicators against the 16
others. Building on the AHP methodology, this section consolidates the
ndings from the previous four sections into a unied score, applying
AHP to the author’s inputs. To illustrate this, two distinct purposes and
their respective weights (Table 9) are considered.
•Missions with Scientic Purposes: In these missions, the payload
ratio and reliability are considered most important, with cost being
less of a priority. This reects the focus on the scientic mission’s
objectives, where the primary concern is ensuring the optimal
functioning and safety of the precious payload rather than budget
constraints.
•Missions with Commercial Purposes: In these scenarios, the pri-
mary emphasis on cost reduction necessitates maximizing the
payload ratio, thereby enhancing cost efciency. While environ-
mental performance is recognized, it is not prioritized over economic
considerations.
This application of AHP allows for a nuanced evaluation tailored to
the specic objectives and priorities of different mission types, whether
they are scientic or commercial. While the present study considers only
these two types as examples, other ranking and priorities are possible.
Table 8
Reliability estimation for the three propulsive systems under study over 1 year of operation. Relative reli-
ability gures are expressed as percentages of the most reliable one. More detailed computations can be
found in the related publication [24].
Fig. 9. Architecture of the quick-analysis tool.
Table 9
Weighting Factors used for the Single-Scores, depending on the purpose of the
Mission. The coefcients are derived from the simplied AHP methodology
applied on the author’s input [24].
Science Mission Commercial Mission
Payload Ratio 0.42 0.37
Environmental Impact 0.21 0.05
Reliability of the Architecture 0.32 0.21
Cost Estimation 0.05 0.37
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3.2. Results for generic orbital stage missions
To better illustrate the paper’s discussions on the four gures of
merit and the single-score methodology, results for three generic
mission scenarios, to Low Earth Orbit (LEO), Geostationary Orbit (GEO),
and the Moon, are presented in Fig. 10. For these missions, the required
Δv is calculated using basic mission analysis computations and reported
in Table 3. These estimations are then compared against the three pro-
pellant combinations which were introduced earlier in the paper and
detailed in Table 2. As reminder, the propellant combinations under
consideration are:
•Pressure-fed MON-3/MMH (Mixed Oxides of Nitrogen/
Monomethylhydrazine),
•Pressure-fed 98%-HTP (High Test Peroxide)/RP-1 (Rocket Propel-
lant-1),
•Self-pressurized N
2
O (Nitrous Oxide)/C
2
H
6
(Ethane).
This comparative analysis aims to provide a clearer understanding of
how different propellant choices impact the mission’s overall perfor-
mance, especially in terms of efciency and feasibility for the specic
destination orbits.
To obtain the results presented in Fig. 10, the output of each function
is normalized to the most favourable value obtained among the three
propulsive combinations under comparison. Specically, this involves
normalizing to the minimum gures obtained for cost and environ-
mental impact but to the maximum ones obtained for reliability and
payload ratio. These normalized values are then weighted with the co-
efcients reported in Table 9 to obtain the following single-score:
Single Score =∑
4
i=1
wi⋅vnorm,i(4)
where iindexes the different categories. This method allows for a
reasonable comparison of different propellant combinations by scaling
all metrics to the most signicant observed value, thereby highlighting
the most efcient options.
The preliminary ndings shown in Fig. 10 reveal clear trends in
propulsion system preferences across various mission types. For science
missions, the pressure-fed 98%-HTP/RP-1 is favored due to its satis-
factory propulsive performance and signicantly lower environmental
impact. However, this advantage declines with increasing Δv re-
quirements, a trend also observed with the self-pressurized option.
While competitive (2nd) for less demanding LEO missions, its
competitiveness declines for missions requiring higher Δv, where the
overall performance is dictated by the specic impulse. Here, the legacy
MON-3/MMH combination predominates due to its higher specic im-
pulse and lower estimated cost attributed to the use of already qualied
components.
This analysis underscores a notable dichotomy in propulsion system
preferences: environmentally friendly options are preferred for science
missions, while commercial missions lean towards legacy systems. In
commercial GEO and MOON missions, the preference for legacy systems
is also driven by established infrastructure, risk aversion, and the
absence of strong incentives for adopting greener technologies. Legacy
systems’performance characteristics, which align better with specic
mission requirements, along with their proven reliability and cost-
effectiveness, solidify their favorability despite their environmental
risks. Yet, for commercial LEO missions, the focus shifts towards the
promising performance and reliability offered by the 98%-HTP/RP-1
option.
While seemingly constant, the pressure-fed MON-3/MMH system
exhibits small variability in overall performance, maintaining high
consistency even in demanding missions due to its higher specic im-
pulse. Indeed, in the analysis presented in this paper, it achieves the
highest relative propulsive performance score of 100% across the three
mission scenarios. When including additional gures of merit, its overall
scores remain high for both scientic and commercial missions, indi-
cating its competitiveness.
However, greener propellants can overtake legacy toxic ones in
overall performance when cost is not set as main driver anymore, which
might be more representative of the current trend towards environ-
mental sustainability.
4. Conclusion
As space activities continue to grow exponentially, the sector faces
pressing demands for systems that are not only more performant and
accessible but also cost-effective. This has catalysed a notable transition
within the space industry. The rst aspect of this transition focuses on
enhancing the logistics of space missions through the development of
orbital transfer vehicles. These vehicles aim to reduce the propulsive
burden placed on satellite manufacturers and optimize payload delivery
to their designated orbits in a single launch. The second aspect em-
phasizes the sustainable development of space activities, encouraging
the adoption of greener solutions and especially of the so-called “green”
propellants.
Fig. 10. Comparison of the Single-Score Global Performance of the Different Propellant Combinations for Three Indicative Mission Scenarios, either with Science or
Commercial Purposes, to LEO, GEO and MOON [24].
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As mission requirements become more stringent, the transition to
greener chemical propulsion is gaining attention. As the sector evolves,
pure performance is no longer the sole criterion of interest, making the
search for optimal future solutions a pressing and yet unresolved ques-
tion. This paper explores the synergistic potential of orbital transfer
vehicles and greener propellants in executing missions to LEO, GEO, and
the Moon, with varying scientic and commercial objectives.
A holisic evaluation framework is proposed for the early design
phases of these missions that extends beyond traditional cost-centric
approaches. This framework instead integrates four gures of merit:
propulsive performance, cost-efciency, environmental impact, and the
reliability of the propulsive architecture. This paper specically presents
the outline of this framework, discusses the rationale for integrating
each metric, and describes the methodology used for their
implementation.
A case study is presented to demonstrate the utility of this tool,
comparing three prevalent liquid bipropellant options for an orbital
stage reference system: pressure-fed MON-3/MMH, 98%-HTP/RP-1, and
the self-pressurizing N
2
O/Ethane. The ndings indicate that for missions
with a primary focus on environmental impact, scientic missions, 98%-
HTP/RP-1 emerges as the optimal choice. On the other hand, for com-
mercial missions driven by cost, the traditional propulsion systems
remain preferable for GEO and Moon missions, though greener alter-
natives are still preferred for less demanding missions such as LEO.
These results are promising, suggesting that selecting greener pro-
pulsion systems does not necessarily compromise performance. By
employing a holistic approach and adjusting the weighting of the
different gures of merit according to mission objectives, the established
framework can be tuned for each mission type and the most suitable
propulsion system can be identied. This approach may pave the way
for more sustainable advancements in in-space propulsion, aligning
technological progress with environmental responsibility.
CRediT authorship contribution statement
Lily Blondel-Canepari: Conceptualization, Data curation, Formal
analysis, Investigation, Methodology, Resources, Software, Validation,
Visualization, Writing –original draft, Writing –review &editing.
Alberto Sarritzu: Visualization, Writing –original draft, Writing –re-
view &editing. Angelo Pasini: Supervision.
Declaration of competing interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
Acknowledgement
The study presented here is carried out under the project ASCenSIon
(Advancing Space Access Capabilities - Reusability and Multiple Satel-
lite Injection project) funded by the European Union’s Horizon 2020
research and innovation programme under the Marie Skłodowska-Curie
grant agreement No 860956 (ASCenSIon Website).
Special thank you goes to the ESTEC CleanSpace-EcoDesign and
Propulsion teams for their support in dening the environmental per-
formance assessment part of the tool.
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