1,720,969 research outputs found
A knowledge based tool-kit for collaborative tradespace exploration: A front-end support to concurrent decisionmaking
No full textConcurrent engineering has reached a huge popularity among companies and agencies, especially when compared with classic design approaches in early design phases. This trend is caused by all the benefits observable in early design performances. Examples are given by reduced design time, reduced costs and improvement of design quality. These qualities are also proven by the space agencies' experiences. Indeed, agencies are currently adopting the concurrent approach as their state of the art approach for conceptual and preliminary design of their future space missions. Despite all the benefits obtained by the concurrent approach, designers currently don't have a clear view of all the alternatives that can be evaluated when designing a space system. The manuscript presents a Microsoft Excel® add-on, which can be integrated with a concurrent engineering open source software, such as the European Space Agency's Open Concurrent Design Tool. The aim is to assist the designers via a graphical user interface which integrates two main tools: autonomous generation and exploration of the concurrent tradespace and domain knowledge exploration. The generated tradespace is constrained to the choices of the other designers. In fact, the generation is obtained by the analysis of the data shared within the design team and by the applicable knowledge when components database and mission information are addressed. The proposed tool is also flexible with the environment of application, from the academic one to industrial mission design and optimization. Indeed, it could be used in either academic or industrial environment, aiming to both assisting during the design phase and assisting the training activities. The users can explore the sensitivity of their choices and learn how an actual decision on their domain influences all the other technical domains involved with the design. The tool offers also the capability of learning and exploring new concepts thanks to the assistance provided by the expert's knowledge that can be applied when a specific context is under analysis. Furthermore, in an industrial environment, the tool demonstrates its benefits. Examples are given by stored and updatable knowledge and guided tradespace optimization which entails reduced design time and costs. These benefits are obtained thanks to a clear and complete visualization of the design alternatives with a quantitative measure of their outcomes. Finally, the paper presents the decision-making tool within a university concurrent design facility exploring in details the peculiar characteristic and benefits given to the design sessions
Deep learning for event detection: Autonomous operations for interplanetary missions
No full textThe history of Artificial Intelligence covers more than five decades, alternating periods of great enthusiasm and prosperity with periods of scepticism. In recent years, Artificial Intelligence has entered a new period of scientific relevance, with countless applications being developed in several scientific fields: medicine, security, speech recognition, image classification and more. The reason behind this progress is clear: Artificial Intelligence allows the implementation of algorithms that origin directly from human knowledge, emulating human behaviours and improving them. Despite the diffusion of these algorithms in several fields, Artificial Intelligence in space engineering has yet to find a defined sphere where it emerges from the competition of other algorithms. Nonetheless, several key directions where Artificial Intelligence has been applied have shown incredible progress in the last decade: mission replanning, fault detection, payload data selection and prioritization can be cited. The paper presents the key advancements and applications developed at Politecnico di Torino in the field of Artificial Intelligence for Space Mission Autonomy, focusing in particular on autonomous event detection during interplanetary missions. The key technology that lies behind the presented research falls in the category of Machine Learning, and in particular in the field of Deep Learning. This technology is used to perform event detection for missions around asteroid and comet objects, performing autonomous detection of key events such as plumes, impacts and changes in brightness. The algorithm, developed in Matlab, is presented and described into details, covering aspects of the design of the network, considerations on its performances, training dataset construction and training strategies. Finally, the algorithm is ported on an embedded board representing the spacecraft Command and Data Handling subsystem. The resulting Hardware-in-the-Loop simulation is described, where a CMOS Image Sensor is used as a sensor to perform the event detection in situ during the mission. The research demonstrates the feasibility of the presented training approach thanks to the embedded implementation described
On applying AI-driven flight data analysis for operational spacecraft model-based diagnostics
No full textThis paper presents new perspectives on the application of Artificial Intelligence (AI) solutions to process Spacecraft (S/C) flight data in order to augment currently used operational S/C health monitoring and diagnostics systems. It captures the growing general interest in the usage of such techniques in the Space engineering domain and applications. Jointly with the AI approach, the operational usage of S/C simulation models (referred to as “discipline models”) is also explored. During S/C development and testing activities, significant efforts are made by the discipline experts to build such models. However, using discipline-specific knowledge to support complex S/C operational activities (e.g., anomaly root cause analysis) remains a challenging task. Based on the current needs of Space Agencies and Industry and by exploiting the advances in AI-based solutions and technologies, this paper proposes an operational S/C model-based diagnostics framework, which can serve as basis for future developments. Such framework combines AI-based techniques, S/C flight data information, and discipline models. Three main needs are addressed: S/C anomaly root cause analysis, S/C prediction behavior, and discipline model refinement. Concrete operational case studies from the Project for On-Board Autonomy (PROBA) satellite family are presented to show the applicability of the proposed framework
STARSIM: a stand-alone tool for "in-the-loop" verification
No full textIn the last decades, systems have strongly increased their complexity remarking the importance of defining methods and tools that improve the design, verification and validation of the system process: effectiveness and costs reduction without loss of confidence in the final product are the objectives that have to be pursued. Within the System Engineering context, the modern Model and Simulation based approach is a promising strategy because it reduces the wasted resources with respect to the traditional methods. Considering a wild range of simulations architectures and methods, crucial stages are defined by algorithm in the loop (AIL), software in the loop (SIL), hardware in the loop (HIL). This paper presents an in-house tool, developed at Politecnico di Torino, able to perform different simulation sessions in any phase of the space product life-cycle using a unique and self-contained platform, called StarSim: modularity, flexibility, real time operation, fidelity with real world, ease of data management, effectiveness and congruence of the outputs with respect to the inputs are StarSim sought-after features. The main issue is to guarantee the possibility to verify the behavior of the system under test thanks to virtual models, that substitute all those elements not yet available and all the non-reproducible dynamics and environmental conditions. Progressively, pieces of the on board software and hardware can be introduced without stopping the process of design and verification, avoiding delays and loss of resources. StarSim has been applied for the first time on the e-st@r-II Cubesat, developed the "CubeSat Team Polito" within the ESA Education Office initiative called "Fly Your Satellite". StarSim has been mainly used for the payload development, an Active Attitude Determination and Control System, but StarSim's capabilities have also been updated to evaluate functionalities, operations and performances of the entire satellite. AIL, SIL, HIL simulations have been constantly performed, successfully verifying a great number of functional and operational requirements. In particular, attitude determination algorithms, control laws, modes of operation have been selected and verified; software has been developed step by step and the bugs-free executable files have been loaded on the micro- controller. Actuators, logic and electrical circuits have been designed, built and tested and sensors calibrated. Problems such as real time and synchronization have been solved, allowing, at the end of the process, a complete hardware in the loop simulation test for the entire satellite. The case study has allowed the successfully validation of the first release of StarSim
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Considerazioni cliniche sull’asportazione di un corpo estraneo dal canale vertebrale di un cane
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