1,150 research outputs found
Prototyping Operational Autonomy for Space Traffic Management
Current state of the art in Space Traffic Management (STM) relies on a handful of providers for surveillance and collision prediction, and manual coordination between operators. Neither is scalable to support the expected 10x increase in spacecraft population in less than 10 years, nor does it support automated manuever planning. We present a software prototype of an STM architecture based on open Application Programming Interfaces (APIs), drawing on previous work by NASA to develop an architecture for low-altitude Unmanned Aerial System Traffic Management. The STM architecture is designed to provide structure to the interactions between spacecraft operators, various regulatory bodies, and service suppliers, while maintaining flexibility of these interactions and the ability for new market participants to enter easily. Autonomy is an indispensable part of the proposed architecture in enabling efficient data sharing, coordination between STM participants and safe flight operations. Examples of autonomy within STM include syncing multiple non-authoritative catalogs of resident space objects, or determining which spacecraft maneuvers when preventing impending conjunctions between multiple spacecraft. The STM prototype is based on modern micro-service architecture adhering to OpenAPI standards and deployed in industry standard Docker containers, facilitating easy communication between different participants or services. The system architecture is designed to facilitate adding and replacing services with minimal disruption. We have implemented some example participant services (e.g. a space situational awareness provider/SSA, a conjunction assessment supplier/CAS, an automated maneuver advisor/AMA) within the prototype. Different services, with creative algorithms folded into then, can fulfil similar functional roles within the STM architecture by flexibly connecting to it using pre-defined APIs and data models, thereby lowering the barrier to entry of new players in the STM marketplace. We demonstrate the STM prototype on a multiple conjunction scenario with multiple maneuverable spacecraft, where an example CAS and AMA can recommend optimal maneuvers to the spacecraft operators, based on a predefined reward function. Such tools can intelligently search the space of potential collision avoidance maneuvers with varying parameters like lead time and propellant usage, optimize a customized reward function, and be implemented as a scheduling service within the STM architecture. The case study shows an example of autonomous maneuver planning is possible using the API-based framework. As satellite populations and predicted conjunctions increase, an STM architecture can facilitate seamless information exchange related to collision prediction and mitigation among various service applications on different platforms and servers. The availability of such an STM network also opens up new research topics on satellite maneuver planning, scheduling and negotiation across disjoint entities
On Recurrent Reachability for Continuous Linear Dynamical Systems
The continuous evolution of a wide variety of systems, including
continuous-time Markov chains and linear hybrid automata, can be described in
terms of linear differential equations. In this paper we study the decision
problem of whether the solution of a system of linear
differential equations reaches a target
halfspace infinitely often. This recurrent reachability problem can
equivalently be formulated as the following Infinite Zeros Problem: does a
real-valued function satisfying a
given linear differential equation have infinitely many zeros? Our main
decidability result is that if the differential equation has order at most ,
then the Infinite Zeros Problem is decidable. On the other hand, we show that a
decision procedure for the Infinite Zeros Problem at order (and above)
would entail a major breakthrough in Diophantine Approximation, specifically an
algorithm for computing the Lagrange constants of arbitrary real algebraic
numbers to arbitrary precision.Comment: Full version of paper at LICS'1
Addressing structural uncertainty of groundwater model predictions with ensemble of automatically generated models from AEM geophysical data and borehole data
Biosensor Integration Development ExMC/Canadian Space Agency Collaboration
In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development
Probability Distribution of Rician K-Factor in Urban, Suburban and Rural Areas Using Real World Captured Data
YesThe Rician K-factor of the vehicle-to-vehicle (V2V) wireless propagation channel is estimated using a moment-based method on the envelope of measured pulse data. The measurements were carried out under vehicle-to-vehicle wireless communication channel condition with car rooftop antenna heights at one end of the link and very low antenna height at the other end. Data captured from typical urban, suburban and rural areas are analyzed and the K-factor probability density function is generated for each scenario to give an insight into the V2V channel behavior. For all three areas, the majority of K values are found to be within the range of -10 to +10 dB. The K-factor distributions are close to normal with mean values of 1.8, 2.6 and 3 dB respectively for urban, suburban and rural area
An axiomatic approach to the non-linear theory of generalized functions and consistency of Laplace transforms
We offer an axiomatic definition of a differential algebra of generalized
functions over an algebraically closed non-Archimedean field. This algebra is
of Colombeau type in the sense that it contains a copy of the space of Schwartz
distributions. We study the uniqueness of the objects we define and the
consistency of our axioms. Next, we identify an inconsistency in the
conventional Laplace transform theory. As an application we offer a free of
contradictions alternative in the framework of our algebra of generalized
functions. The article is aimed at mathematicians, physicists and engineers who
are interested in the non-linear theory of generalized functions, but who are
not necessarily familiar with the original Colombeau theory. We assume,
however, some basic familiarity with the Schwartz theory of distributions.Comment: 23 page
Magma-driven, high-grade metamorphism in the Sveconorwegian Province, southwest Norway, during the terminal stages of Fennoscandian Shield evolution
Recently it has been argued that the Sveconorwegian orogeny in southwest Fennoscandia comprised a series of accretionary events between 1140 and 920 Ma, behind a long-lived, active continental margin characterized by voluminous magmatism and high-grade metamorphism. Voluminous magnesian granitic magmatism is recorded between 1070 and 1010 Ma (Sirdal Magmatic Belt, SMB), with an apparent drop in activity ca. 1010-1000 Ma. Granitic magmatism resumed ca. 1000-990 Ma, but with more ferroan (A type) compositions (hornblende-biotite granites). This ferroan granitic magmatism was continuous until 920 Ma, and included emplacement of an AMCG (anorthosite-mangerite-charnockite-granite) complex (Rogaland Igneous Complex). Mafic rocks with ages corresponding to the spatially associated granites suggest that heat from underplated mafic magma was the main driving force for lower crustal melting and long-lived granitic magmatism. The change from magnesian to ferroan compositions may reflect an increasingly depleted and dehydrated lower crustal source. High-grade metamorphic rocks more than ~20 km away from the Rogaland Igneous Complex yield metamorphic ages of 1070-1015 Ma, corresponding to SMB magmatism, whereas similar rocks closer to the Rogaland Igneous Complex yield ages between 1100 and 920 Ma, with an apparent age peak ca. 1000 Ma. Ti-in-zircon temperatures from these rocks increase from ~760 to 820 °C ca. 970 Ma, well before the inferred emplacement age of the Rogaland Igneous Complex (930 Ma), suggesting that long-lived, high-grade metamorphism was not directly linked to the emplacement of the latter, but rather to the same mafic underplating that was driving lower crustal melting. Structural data suggest that the present-day regional distribution of high- and low-grade rocks reflects late-stage orogenic doming
Medical Data Architecture Project Status
The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements
- …