Incorporating Uncertainty Into Conceptual Design of Space System Architectures

The environment in which space systems are developed and operated can be classified as nothing less than dynamic. However, it is clear that the methods and tools relied on in conceptual design are based on static assumptions and leave little room for anything more than snapshots of the product and its environment. This paper introduces an approach to challenge that model and instead quantify and compare space system architectures around the central theme of uncertainty, with emphasis on policy uncertainty, as well as, technical and market uncertainty. Two cases of implementation are presented and three generalized principles are proposed that flow from the analysis: 1) engineering systems must be designed with uncertainty as one of the central organizing principles, 2) since engineering systems have management and social dimensions and thus involve human interactions, there is an irreducible uncertainty associated with these dimensions that will affect the design of the system, and 3) uncertainty in use may allow the engineering system to satisfy quite different missions from the original one intended

Technology Portfolio Planning by Weighted Graph Analysis of System Architectures

Many systems undergo significant architecture-level change throughout their lifecycles in order to adapt to new operating and funding contexts, to react to failed technology development, or to incorporate new technologies. In all cases early architecture selection and technology investment decisions will constrain the system to certain regions of the tradespace, which can limit the evolvability of the system and its robustness to exogenous changes. In this paper we present a method for charting development pathways within a tradespace of potential architectures, with a view to enabling robustness to technology portfolio realization and later architectural changes. The tradespace is first transformed into a weighted, directed graph of architecture nodes with connectivity determined by relationships between technology portfolios and functional architecture. The tradespace exploration problem is then restated as a shortest path problem through this graph. This method is applied to the tradespace of in-space transportation architectures for missions to Mars, finding that knowledge of pathways through the tradespace can identify negative coupling between functional architectures and particular technologies, as well as identify ways to prioritize future technology investments.Skolkovo Institute of Science and Technolog

Architectural optimization framework for earth-observing heterogeneous constellations : marine weather forecast case

Earth observation satellite programs are currently facing, for some applications, the need to deliver hourly revisit times, subkilometric spatial resolutions, and near-real-time data access times. These stringent requirements, combined with the consolidation of small-satellite platforms and novel distributed architecture approaches, are stressing the need to study the design of new, heterogeneous, and heavily networked satellite systems that can potentially replace or complement traditional space assets. In this context, this paper presents partial results from ONION, a research project devoted to studying distributed satellite systems and their architecting characteristics. A design-oriented framework that allows selecting optimal architectures for the given user needs is presented in this paper. The framework has been used in the study of a strategic use-case and its results are hereby presented. From an initial design space of 5586 potential architectures, the framework has been able to preselect 28 candidate designs by an exhaustive analysis of their performance and by quantifying their quality attributes. This very exploration of architectures and the characteristics of the solution space are presented in this paper along with the selected solution and the results of a detailed performance analysis.Postprint (author's final draft

Multi-attributes tradespace exploration for survivability: Application to satellite radar

Multi-Attribute Tradespace Exploration (MATE) for Survivability is introduced as a general methodology for survivability analysis and demonstrated through an application to a satellite radar system. MATE for Survivability applies decision theory to the parametric modeling of thousands of design alternatives across representative distributions of disturbance environments. Survivability considerations are incorporated into the existing MATE process (i.e., a solution-generating and decision-making framework that applies decision theory to model-based design) by applying empirically-validated survivability design principles and value-based survivability metrics to concept generation and concept evaluation activities, respectively. MATE for Survivability consists of eight iterative phases: (1) define system value proposition, (2) generate concepts, (3) specify disturbances, (4) apply survivability principles, (5) model baseline system performance, (6) model impact of disturbances on dynamic system performance, (7) apply survivability metrics, and (8) select designs for further analysis. The application of MATE for Survivability to satellite radar demonstrates the importance of incorporating survivability considerations into conceptual design for identifying inherently survivable architectures that efficiently balance competing performance metrics of lifecycle cost, mission utility, and operational survivability

Tradespace Investigation of a Telescope Architecture for Next-generation Space Astronomy and Exploration

Humanity’s endeavor to further its scientific understanding of the celestial heavens has led to the creation and evolution of increasingly powerful and complex space telescopes. Space telescopes provide a view of the solar system, galaxy, and universe unobstructed by Earth’s atmosphere and have profoundly changed the way people view space. In an effort to further advance space telescope capability and achieve the accompanying scientific understanding, the Massachusetts Institute of Technology (MIT), specifically, course 16.89 Space Systems Engineering, explored the tradespace of architectural enumerations encompassed within the design of an ultraviolet-optical-infrared (UVOIR) space telescope located at Sun-Earth Lagrangian Point Two (SE-L2). SE-L2 presents several advantages as an operating location for a UVOIR telescope such as a thermally stable environment and an orbit that allows the telescope to maintain a constant orientation with respect to all of the primary sources of heat and light. The main disadvantages associated with SE-L2 are caused by its relatively large distance from Earth, which marginalizes the effectiveness of real-time telerobotics because of latency and increases the cost of communications, launch, and servicing. Course 16.89 believes that, for this UVOIR application, the strengths of this operating location outweigh its weaknesses and therefore decided to explore the family of opportunities associated with SE-L2. This course used appropriate performance and system metrics to quantify the effectiveness of the aforementioned architectures and create a Pareto front of viable architectures. Evaluating the designs along the Pareto front allowed the course to characterize and group architectures and present these group-types to stakeholders for the selection of an optimal space telescope according to stakeholder requirements and resources. This course also developed sensitivity analysis, which allowed for a greater understanding of how architectural decisions affect the performance of the satellite. Segmentation, modularity, assembly, autonomy, and servicing were key aspects of this multidimensional analysis given the 16.8-meter class size and location of the telescope. Within the respective operating environment and for a spacecraft of similar characteristics, this model will allow stakeholders to predict the long-term operational effectiveness of different space telescope architectures and capture the synergistic effects of combining various architectural decisions into a spacecraft design. The following sections step through the aforesaid analysis and design efforts conducted in 16.89 beginning with Section III, which explicitly performs the stakeholder analysis and articulates the requirements of the mission. Section IV gives an overview of past designs and expands upon the architecture enumerations pertinent to this project, while Section V presents the methods and metrics by which those architectures will be evaluated and the system metrics which will be balanced and optimized in the creation of this space telescope. Section VI will present the model validation of this project and Section VII will discuss the results and analyses of the project. Finally, Section VIII will explore the future work opportunities of this project, while Section IX will present the conclusions and recommendations drawn from this project.MIT Department of Aeronautics and Astronautic

Multi-Attribute Tradespace Exploration for Survivability

Multi-Attribute Tradespace Exploration for Survivability is a system design and analysis methodology that incorporates survivability considerations into the tradespace exploration process (i.e., a solution-generating and decision-making framework that applies decision theory to model-based design). During the concept generation phase of tradespace exploration, the methodology applies seventeen empirically validated survivability design principles spanning susceptibility reduction, vulnerability reduction, and resilience enhancement. During subsequent concept evaluation, the methodology adds value-based survivability metrics to traditional architectural evaluation criteria of mission utility and lifecycle cost. Applied to a satellite radar mission, the methodology allowed operational survivability to be statistically evaluated across representative distributions of naturally occurring disturbances in the space environment and for survivability to be incorporated as a decision factor earlier in the design process. Constellations in the illustrative example are shown to be the most survivable, mitigating disturbances architecturally, rather than through additive features.Massachusetts Institute of Technology (Systems Engineering Advancement Research Initiative (SEAri))Massachusetts Institute of Technology. Program on Emerging Technologie

In pursuit of autonomous distributed satellite systems

A la pàgina 265 diu: "In an effort to facilitate the reproduction of results, both the source code of the simulation environment and the configuration files that were prepared for the design characterisation are available in an open repository: https://github.com/carlesaraguz/aeossSatellite imagery has become an essential resource for environmental, humanitarian, and industrial endeavours. As a means to satisfy the requirements of new applications and user needs, novel Earth Observation (EO) systems are exploring the suitability of Distributed Satellite Systems (DSS) in which multiple observation assets concurrently sense the Earth. Given the temporal and spatial resolution requirements of EO products, DSS are often envisioned as large-scale systems with multiple sensing capabilities operating in a networked manner. Enabled by the consolidation of small satellite platforms and fostered by the emerging capabilities of distributed systems, these new architectures pose multiple design and operational challenges. Two of them are the main pillars of this research, namely, the conception of decision-support tools to assist the architecting process of a DSS, and the design of autonomous operational frameworks based on decentralised, on-board decision-making. The first part of this dissertation addresses the architecting of heterogeneous, networked DSS architectures that hybridise small satellite platforms with traditional EO assets. We present a generic design-oriented optimisation framework based on tradespace exploration methodologies. The goals of this framework are twofold: to select the most optimal constellation design; and to facilitate the identification of design trends, unfeasible regions, and tensions among architectural attributes. Oftentimes in EO DSS, system requirements and stakeholder preferences are not only articulated through functional attributes (i.e. resolution, revisit time, etc.) or monetary constraints, but also through qualitative traits such as flexibility, evolvability, robustness, or resiliency, amongst others. In line with that, the architecting framework defines a single figure of merit that aggregates quantitative attributes and qualitative ones-the so-called ilities of a system. With that, designers can steer the design of DSS both in terms of performance or cost, and in terms of their high-level characteristics. The application of this optimisation framework has been illustrated in two timely use-cases identified in the context of the EU-funded ONION project: a system that measures ocean and ice parameters in Polar regions to facilitate weather forecast and off-shore operations; and a system that provides agricultural variables crucial for global management of water stress, crop state, and draughts. The analysis of architectural features facilitated a comprehensive understanding of the functional and operational characteristics of DSS. With that, this thesis continues to delve into the design of DSS by focusing on one particular functional trait: autonomy. The minimisation of human-operator intervention has been traditionally sought in other space systems and can be especially critical for large-scale, structurally dynamic, heterogeneous DSS. In DSS, autonomy is expected to cope with the likely inability to operate very large-scale systems in a centralised manner, to improve the science return, and to leverage many of their emerging capabilities (e.g. tolerance to failures, adaptability to changing structures and user needs, responsiveness). We propose an autonomous operational framework that provides decentralised decision-making capabilities to DSS by means of local reasoning and individual resource allocation, and satellite-to-satellite interactions. In contrast to previous works, the autonomous decision-making framework is evaluated in this dissertation for generic constellation designs the goal of which is to minimise global revisit times. As part of the characterisation of our solution, we stressed the implications that autonomous operations can have upon satellite platforms with stringent resource constraints (e.g. power, memory, communications capabilities) and evaluated the behaviour of the solution for a large-scale DSS composed of 117 CubeSat-like satellite units.La imatgeria per satèl·lit ha esdevingut un recurs essencial per assolir tasques ambientals, humanitàries o industrials. Per tal de satisfer els requeriments de les noves aplicacions i usuaris, els sistemes d’observació de la Terra (OT) estan explorant la idoneïtat dels Sistemes de Satèl·lit Distribuïts (SSD), on múltiples observatoris espacials mesuren el planeta simultàniament. Degut al les resolucions temporals i espacials requerides, els SSD sovint es conceben com sistemes de gran escala que operen en xarxa. Aquestes noves arquitectures promouen les capacitats emergents dels sistemes distribuïts i, tot i que són possibles gràcies a l’acceptació de les plataformes de satèl·lits petits, encara presenten molts reptes en quant al disseny i operacions. Dos d’ells són els pilars principals d’aquesta tesi, en concret, la concepció d’eines de suport a la presa de decisions pel disseny de SSD, i la definició d’operacions autònomes basades en gestió descentralitzada a bord dels satèl·lits. La primera part d’aquesta dissertació es centra en el disseny arquitectural de SSD heterogenis i en xarxa, imbricant tecnologies de petits satèl·lits amb actius tradicionals. Es presenta un entorn d’optimització orientat al disseny basat en metodologies d’exploració i comparació de solucions. Els objectius d’aquest entorn són: la selecció el disseny de constel·lació més òptim; i facilitar la identificació de tendències de disseny, regions d’incompatibilitat, i tensions entre atributs arquitecturals. Sovint en els SSD d’OT, els requeriments del sistema i l’expressió de prioritats no només s’articulen en quant als atributs funcionals o les restriccions monetàries, sinó també a través de les característiques qualitatives com la flexibilitat, l’evolucionabilitat, la robustesa, o la resiliència, entre d’altres. En línia amb això, l’entorn d’optimització defineix una única figura de mèrit que agrega rendiment, cost i atributs qualitatius. Així l’equip de disseny pot influir en les solucions del procés d’optimització tant en els aspectes quantitatius, com en les característiques dalt nivell. L’aplicació d’aquest entorn d’optimització s’il·lustra en dos casos d’ús actuals identificats en context del projecte europeu ONION: un sistema que mesura paràmetres de l’oceà i gel als pols per millorar la predicció meteorològica i les operacions marines; i un sistema que obté mesures agronòmiques vitals per la gestió global de l’aigua, l’estimació d’estat dels cultius, i la gestió de sequeres. L’anàlisi de propietats arquitecturals ha permès copsar de manera exhaustiva les característiques funcionals i operacionals d’aquests sistemes. Amb això, la tesi ha seguit aprofundint en el disseny de SSD centrant-se, particularment, en un tret funcional: l’autonomia. Minimitzar la intervenció de l’operador humà és comú en altres sistemes espacials i podria ser especialment crític pels SSD de gran escala, d’estructura dinàmica i heterogenis. En els SSD s’espera que l’autonomia solucioni la possible incapacitat d’operar sistemes de gran escala de forma centralitzada, que millori el retorn científic i que n’apuntali les seves propietats emergents (e.g. tolerància a errors, adaptabilitat a canvis estructural i de necessitats d’usuari, capacitat de resposta). Es proposa un sistema d’operacions autònomes que atorga la capacitat de gestionar els sistemes de forma descentralitzada, a través del raonament local, l’assignació individual de recursos, i les interaccions satèl·lit-a-satèl·lit. Al contrari que treballs anteriors, la presa de decisions autònoma s’avalua per constel·lacions que tenen com a objectius de missió la minimització del temps de revisita global.Postprint (published version

Artificial Intelligence for Small Satellites Mission Autonomy

Space mission engineering has always been recognized as a very challenging and innovative branch of engineering: since the beginning of the space race, numerous milestones, key successes and failures, improvements, and connections with other engineering domains have been reached. Despite its relative young age, space engineering discipline has not gone through homogeneous times: alternation of leading nations, shifts in public and private interests, allocations of resources to different domains and goals are all examples of an intrinsic dynamism that characterized this discipline. The dynamism is even more striking in the last two decades, in which several factors contributed to the fervour of this period. Two of the most important ones were certainly the increased presence and push of the commercial and private sector and the overall intent of reducing the size of the spacecraft while maintaining comparable level of performances. A key example of the second driver is the introduction, in 1999, of a new category of space systems called CubeSats. Envisioned and designed to ease the access to space for universities, by standardizing the development of the spacecraft and by ensuring high probabilities of acceptance as piggyback customers in launches, the standard was quickly adopted not only by universities, but also by agencies and private companies. CubeSats turned out to be a disruptive innovation, and the space mission ecosystem was deeply changed by this. New mission concepts and architectures are being developed: CubeSats are now considered as secondary payloads of bigger missions, constellations are being deployed in Low Earth Orbit to perform observation missions to a performance level considered to be only achievable by traditional, fully-sized spacecraft. CubeSats, and more in general the small satellites technology, had to overcome important challenges in the last few years that were constraining and reducing the diffusion and adoption potential of smaller spacecraft for scientific and technology demonstration missions. Among these challenges were: the miniaturization of propulsion technologies, to enable concepts such as Rendezvous and Docking, or interplanetary missions; the improvement of telecommunication state of the art for small satellites, to enable the downlink to Earth of all the data acquired during the mission; and the miniaturization of scientific instruments, to be able to exploit CubeSats in more meaningful, scientific, ways. With the size reduction and with the consolidation of the technology, many aspects of a space mission are reduced in consequence: among these, costs, development and launch times can be cited. An important aspect that has not been demonstrated to scale accordingly is operations: even for small satellite missions, human operators and performant ground control centres are needed. In addition, with the possibility of having constellations or interplanetary distributed missions, a redesign of how operations are management is required, to cope with the innovation in space mission architectures. The present work has been carried out to address the issue of operations for small satellite missions. The thesis presents a research, carried out in several institutions (Politecnico di Torino, MIT, NASA JPL), aimed at improving the autonomy level of space missions, and in particular of small satellites. The key technology exploited in the research is Artificial Intelligence, a computer science branch that has gained extreme interest in research disciplines such as medicine, security, image recognition and language processing, and is currently making its way in space engineering as well. The thesis focuses on three topics, and three related applications have been developed and are here presented: autonomous operations by means of event detection algorithms, intelligent failure detection on small satellite actuator systems, and decision-making support thanks to intelligent tradespace exploration during the preliminary design of space missions. The Artificial Intelligent technologies explored are: Machine Learning, and in particular Neural Networks; Knowledge-based Systems, and in particular Fuzzy Logics; Evolutionary Algorithms, and in particular Genetic Algorithms. The thesis covers the domain (small satellites), the technology (Artificial Intelligence), the focus (mission autonomy) and presents three case studies, that demonstrate the feasibility of employing Artificial Intelligence to enhance how missions are currently operated and designed

In pursuit of autonomous distributed satellite systems

Satellite imagery has become an essential resource for environmental, humanitarian, and industrial endeavours. As a means to satisfy the requirements of new applications and user needs, novel Earth Observation (EO) systems are exploring the suitability of Distributed Satellite Systems (DSS) in which multiple observation assets concurrently sense the Earth. Given the temporal and spatial resolution requirements of EO products, DSS are often envisioned as large-scale systems with multiple sensing capabilities operating in a networked manner. Enabled by the consolidation of small satellite platforms and fostered by the emerging capabilities of distributed systems, these new architectures pose multiple design and operational challenges. Two of them are the main pillars of this research, namely, the conception of decision-support tools to assist the architecting process of a DSS, and the design of autonomous operational frameworks based on decentralised, on-board decision-making. The first part of this dissertation addresses the architecting of heterogeneous, networked DSS architectures that hybridise small satellite platforms with traditional EO assets. We present a generic design-oriented optimisation framework based on tradespace exploration methodologies. The goals of this framework are twofold: to select the most optimal constellation design; and to facilitate the identification of design trends, unfeasible regions, and tensions among architectural attributes. Oftentimes in EO DSS, system requirements and stakeholder preferences are not only articulated through functional attributes (i.e. resolution, revisit time, etc.) or monetary constraints, but also through qualitative traits such as flexibility, evolvability, robustness, or resiliency, amongst others. In line with that, the architecting framework defines a single figure of merit that aggregates quantitative attributes and qualitative ones-the so-called ilities of a system. With that, designers can steer the design of DSS both in terms of performance or cost, and in terms of their high-level characteristics. The application of this optimisation framework has been illustrated in two timely use-cases identified in the context of the EU-funded ONION project: a system that measures ocean and ice parameters in Polar regions to facilitate weather forecast and off-shore operations; and a system that provides agricultural variables crucial for global management of water stress, crop state, and draughts. The analysis of architectural features facilitated a comprehensive understanding of the functional and operational characteristics of DSS. With that, this thesis continues to delve into the design of DSS by focusing on one particular functional trait: autonomy. The minimisation of human-operator intervention has been traditionally sought in other space systems and can be especially critical for large-scale, structurally dynamic, heterogeneous DSS. In DSS, autonomy is expected to cope with the likely inability to operate very large-scale systems in a centralised manner, to improve the science return, and to leverage many of their emerging capabilities (e.g. tolerance to failures, adaptability to changing structures and user needs, responsiveness). We propose an autonomous operational framework that provides decentralised decision-making capabilities to DSS by means of local reasoning and individual resource allocation, and satellite-to-satellite interactions. In contrast to previous works, the autonomous decision-making framework is evaluated in this dissertation for generic constellation designs the goal of which is to minimise global revisit times. As part of the characterisation of our solution, we stressed the implications that autonomous operations can have upon satellite platforms with stringent resource constraints (e.g. power, memory, communications capabilities) and evaluated the behaviour of the solution for a large-scale DSS composed of 117 CubeSat-like satellite units.La imatgeria per satèl·lit ha esdevingut un recurs essencial per assolir tasques ambientals, humanitàries o industrials. Per tal de satisfer els requeriments de les noves aplicacions i usuaris, els sistemes d’observació de la Terra (OT) estan explorant la idoneïtat dels Sistemes de Satèl·lit Distribuïts (SSD), on múltiples observatoris espacials mesuren el planeta simultàniament. Degut al les resolucions temporals i espacials requerides, els SSD sovint es conceben com sistemes de gran escala que operen en xarxa. Aquestes noves arquitectures promouen les capacitats emergents dels sistemes distribuïts i, tot i que són possibles gràcies a l’acceptació de les plataformes de satèl·lits petits, encara presenten molts reptes en quant al disseny i operacions. Dos d’ells són els pilars principals d’aquesta tesi, en concret, la concepció d’eines de suport a la presa de decisions pel disseny de SSD, i la definició d’operacions autònomes basades en gestió descentralitzada a bord dels satèl·lits. La primera part d’aquesta dissertació es centra en el disseny arquitectural de SSD heterogenis i en xarxa, imbricant tecnologies de petits satèl·lits amb actius tradicionals. Es presenta un entorn d’optimització orientat al disseny basat en metodologies d’exploració i comparació de solucions. Els objectius d’aquest entorn són: la selecció el disseny de constel·lació més òptim; i facilitar la identificació de tendències de disseny, regions d’incompatibilitat, i tensions entre atributs arquitecturals. Sovint en els SSD d’OT, els requeriments del sistema i l’expressió de prioritats no només s’articulen en quant als atributs funcionals o les restriccions monetàries, sinó també a través de les característiques qualitatives com la flexibilitat, l’evolucionabilitat, la robustesa, o la resiliència, entre d’altres. En línia amb això, l’entorn d’optimització defineix una única figura de mèrit que agrega rendiment, cost i atributs qualitatius. Així l’equip de disseny pot influir en les solucions del procés d’optimització tant en els aspectes quantitatius, com en les característiques dalt nivell. L’aplicació d’aquest entorn d’optimització s’il·lustra en dos casos d’ús actuals identificats en context del projecte europeu ONION: un sistema que mesura paràmetres de l’oceà i gel als pols per millorar la predicció meteorològica i les operacions marines; i un sistema que obté mesures agronòmiques vitals per la gestió global de l’aigua, l’estimació d’estat dels cultius, i la gestió de sequeres. L’anàlisi de propietats arquitecturals ha permès copsar de manera exhaustiva les característiques funcionals i operacionals d’aquests sistemes. Amb això, la tesi ha seguit aprofundint en el disseny de SSD centrant-se, particularment, en un tret funcional: l’autonomia. Minimitzar la intervenció de l’operador humà és comú en altres sistemes espacials i podria ser especialment crític pels SSD de gran escala, d’estructura dinàmica i heterogenis. En els SSD s’espera que l’autonomia solucioni la possible incapacitat d’operar sistemes de gran escala de forma centralitzada, que millori el retorn científic i que n’apuntali les seves propietats emergents (e.g. tolerància a errors, adaptabilitat a canvis estructural i de necessitats d’usuari, capacitat de resposta). Es proposa un sistema d’operacions autònomes que atorga la capacitat de gestionar els sistemes de forma descentralitzada, a través del raonament local, l’assignació individual de recursos, i les interaccions satèl·lit-a-satèl·lit. Al contrari que treballs anteriors, la presa de decisions autònoma s’avalua per constel·lacions que tenen com a objectius de missió la minimització del temps de revisita global

Computational Tradespace Exploration, Analysis, and Decision-Making: A Proposed Framework for Organizational Self-Assessment

The ability to assess technical feasibility, project risk, technical readiness, and realistic performance expectations in early-phase conceptual design is a challenging mission-critical task for large procurement projects. At present, there is not a well-defined framework for evaluating current practices of organizations performing computational trade studies. One such organization is the US Army Ground Vehicle Systems Center (GVSC). When defining requirements and priorities for the next-generation autonomy-enabled ground vehicle system, GVSC is faced with the challenge of an increasingly complex programmatic tradespace due to emerging complexities of ground vehicle systems. This thesis aims to document and evaluate tradespace processes, methods, and tools within GVSC. A systematic review of the literature was conducted to investigate existing gaps, limitations, and potential growth opportunities related to tradespace activities reflecting the greater body of knowledge observed in the literature. Following this review, an interview-based study was developed through which a series of interviews with GVSC personnel was conducted and subsequently benchmarked against the baseline established in the literature. In addition to characterizing the current practices of tradespace exploration and analysis within GVSC, the analysis of the collected interview data revealed current capability gaps, areas of excellence, and potential avenues for improvement within GVSC. Through this thesis, other organizations can perform similar self-assessments to improve internal capabilities with respect to tradespace studies