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Algorithm for determining number of vertices contained in single contact network corresponding to transmission function
Fiber-based materials are extensively used to protect spacecraft during entry. Insulative fibers, often in a fiber network or woven, provide rigidity, strength, and control of material anisotropy and density. Woven thermal protection materials, such as ADEPT (Adaptable, Deployable Entry and Placement Technology), 3D-MAT (3-Dimensional Multifunctional Ablative Thermal Protection), and 3MDCP (3D Woven Mid-Density Carbon Phenolic), enable missions with stronger and denser materials for entry profiles with high shear and heat flux. Vulnerabilities to woven thermal protection materials include manufacturing-induced material property variation, and impact from micrometeoroids. Simulating woven materials under these conditions require models that can resolve hierarchal structures, thermomechanical behavior, and failure. To address this, we simulate weave thermal conduction and mechanical deformation. We simulate the full weave with a coarse-grained yarn model is presented. The model combines a validated, high-resolution single 3MDCP yarn model and phenolic resin model. Instead of modeling every fiber, each yarn ply with order 10, instead of order 1000, fibers. The discrete element bonded particle model (DEM-BPM) of fibers captures the thermal and mechanical behavior within and between fibers. We study the proportion of heat transfer and stress via the contact network, fiber bonds, and overall weave geometry.
Computational self-sufficiency - the making of communication decisions on the basis of locally available information that is already in place, rather than on the basis of information residing at other entities - is a fundamental principle of Delay-Tolerant Networking. Contact Graph Routing is an attempt to apply this principle to the problem of dynamic routing in an interplanetary DTN. Testing continues, but preliminary results are promising.
Applications requiring materials with layer-to-layer strength, from basketry to thermal protection systems, use interlaced, three-dimensional woven materials. NASA is developing and deploying woven material heat shields for missions, including Artemis I (3D-MAT for compression pads) and potentially Mars Sample Return - Earth Entry System. These materials are complex, hierarchical and must protect from extreme environments and phenomena, such as deformation, impact and high-enthalpy heating. Woven material performance depends on microstructure, damage and weave geometry. Therefore, fiber-specific models are needed to simulate fiber contacts within the weave hierarchical geometry (fiber to tow to yarn to weave) and the inherent directionality of fibers. Explicit fiber models can simulate how weave microstructure evolution affects thermal and mechanical properties. We parameterize a discrete element bonded particle models (DEM-BPM) of fibers to capture thermal and mechanical behavior within and between fibers, with bonded and contact forces, respectively. We study the proportion of heat transfer and stress via the contact network, fiber bonds and the weave geometry, for example, with respect to yarn warp-weft identity (whether it interlaces weave layers). Our results demonstrate the importance of explicit fiber modeling for connecting microstructure with thermal and mechanical properties.
Applications requiring materials with layer-to-layer strength, from basketry to thermal protection systems, use interlaced, three-dimensional woven materials. NASA is developing and deploying woven material heat shields for missions, including Artemis I (3D-MAT for compression pads) and potentially Mars Sample Return - Earth Entry System. These materials are complex, hierarchical and must protect from extreme environments and phenomena, such as deformation, impact and high-enthalpy heating. Woven material performance depends on microstructure, damage and weave geometry. Therefore, fiber-specific models are needed to simulate fiber contacts within the weave hierarchical geometry (fiber to tow to yarn to weave) and the inherent directionality of fibers. Explicit fiber models can simulate how weave microstructure evolution affects thermal and mechanical properties. We parameterize a discrete element bonded particle models (DEM-BPM) of fibers to capture thermal and mechanical behavior within and between fibers, with bonded and contact forces, respectively. We study the proportion of heat transfer and stress via the contact network, fiber bonds and the weave geometry, for example, with respect to yarn warp-weft identity (whether it interlaces weave layers). Our results demonstrate the importance of explicit fiber modeling for connecting microstructure with thermal and mechanical properties.
Satellites are leaving the realms of niche use, extending our day-to-day networked infrastructure to space – thereby forcing a generalization of network architectures. The Delay Tolerant Networking (DTN) protocol is being developed to give rise to this new Solar System Internet. Predominantly, DTNs in space use globally-distributed contact tables to compute routes. In this paper, we propose and analyze a novel optimized approach for route computations that improves upon traditional approaches. As the general DTN will always include some scheduled links, our new algorithm enables greater scalability and practicality of DTN routing. These contact tables include windows when two nodes can communicate and were classically organized into a contact graph, where the vertices represent contact opportunities. Because the complexity of a contact graph grows with the number of contacts, pathfinding on it does not scale. A new structure using multigraphs with the same data is proposed. We show that a multigraph-based approach, which we call contact multigraph routing, exhibits performance superior to routing based on contact graphs, allowing greater scaling to schedule-based routing. In this paper, the multigraph-based algorithm is detailed and a proof is included showing it outperforms the previous algorithm given the same input. Pseudocode is included, as are simulation results. We conclude with suggested future work.
In Delay Tolerant Networking (DTN), the standard routing algorithm used to navigate time-varying networks has been Contact Graph Routing (CGR). In CGR, a globally distributed list of contacts, periods during which two DTN nodes may communicate, is used to construct a contact graph, in which contacts are vertices. A version of Dijkstra’s algorithm can then be used to find paths through this model of the timevarying network. However, since contact graphs may be large compared to the network, potentially growing with the square of the number of network nodes and linearly with the time interval represented, the resulting algorithm does not scale well with the size of the network or time. Any improvement to the routing algorithm will bring significant returns to scale. In a previous paper, we briefly introduced an alternative to the contact graph model for routing. This alternative model is based on a multigraph (a graph in which there may be multiple edges between a pair of vertices) where vertices represent network nodes instead of contacts. A version of Dijkstra’s algorithm in these multigraph models reduces the time needed to perform the same routing computations done in the existing CGR algorithm. Moreover, a modified version of Yen’s algorithm for multigraphs is included. Our variation of CGR, which we call Contact Multigraph Routing (CMR), provides an in-line replacement for the previously used pathfinding algorithms. This paper describes an implementation created based on the CMR approach, and experimental comparisons to traditional CGR are given. In addition, we explore some additional modifications to the routing pipeline traditionally assumed in CGR. These modifications range from the theoretical to the practical in terms of size and scope. We step forward our understanding of sheaftheoretic networking and describe how to model the routing pipeline using sheaves. We detail some enhanced route selection criteria that addresses some of the added complexity of DTNbased systems. We also include a future works section on future improvements and implementations that would be of service to the broader DTN community.
Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology composed of scheduled, bounded communication contacts in a network built on the Delay-Tolerant Networking (DTN) architecture. It is designed to support operations in a space network based on DTN, but it also could be used in terrestrial applications where operation according to a predefined schedule is preferable to opportunistic communication, as in a low-power sensor network. This paper will describe the operation of the CGR system and explain how it can enable data delivery over scheduled transmission opportunities, fully utilizing the available transmission capacity, without knowing the current state of any bundle protocol node (other than the local node itself) and without exhausting processing resources at any bundle router.
This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.
The Almahata Sitta ureilite, derived from asteroid 2008 TC3, consists of many individual fragments recovered from the Nubian dessert strewn field [1]. Like most ureilites, it contains abundant carbon and exhibits examples of disequilibrium textures that record a late reduction event accompanied by rapid cooling (tens of degC/h) from high temperatures (1150-1300 C). Variations in Fe/Mg of silicate minerals are accompanied by variations in Fe/Mn, indicating loss of Fe into metal [2]. In coarser-grained fragments of Almahata Sitta, olivine exhibits irregular high mg# rims in contact with networks of interstitial metal 5- 20 microns in typical thickness. This is a common ureilite texture thought to be driven by the reaction of graphite to a CO gas phase and the concurrent reduction of FeO in olivine to Fe metal, with excess silica going primarily into pyroxene (2MgFeSiO4 + C approaches MgSiO4 + MgSiO3 + 2Fe + CO) [3, see also 4,5,6]. Other fragments of Almahata Sitta exhibit anomalous textures such as fine grain size, high porosity, and abundant graphite. Within these fragments pyroxene locally exhibits high-mg# rims in contact with metal and a discreet silica phase, suggesting that the reduction mechanism MgFeSi2O6 + C approaches MgSiO3 + Fe + SiO2 + CO. Metals in Almahata Sitta are particularly unaltered in comparison to ureilite finds. Variations in minor and trace element composition of this metal might partly result from localized dilution as iron is supplied by reduction of silicates.
Thiamin pyrophosphate (TPP)-dependent enzymes are a divergent family of TPP and metal ion binding proteins that perform a wide range of functions with the common decarboxylation steps of a -(O=)C-C(OH)- fragment of alpha-ketoacids and alpha- hydroxyaldehydes. To determine how structure and catalytic action are conserved in the context of large sequence differences existing within this family of enzymes, we have carried out an analysis of TPP-dependent enzymes of known structures. The common structure of TPP-dependent enzymes is formed at the interface of four alpha/beta domains from at least two subunits, which provide for two metal and TPP-binding sites. Residues around these catalytic sites are conserved for functional purpose, while those further away from TPP are conserved for structural reasons. Together they provide a network of contacts required for flip-flop catalytic action within TPP-dependent enzymes. Thus our analysis defines a TPP-action motif that is proposed for annotating TPP-dependent enzymes for advancing functional proteomics.
The Mars Reconnaissance Orbiter (MRO) was launched on August 12, 2005 by an Atlas V launch vehicle from Cape Canaveral Air Force Station. MRO will carry a rich set of science instruments to Mars and provide global, regional survey, and targeted observations. In addition, a set of engineering instruments providing optical navigation, Ka band telecommunication and UHF relay services to future Mars missions are part of the MRO payload. During the mission, the MRO operations teams are presented with two major challenges - unprecedented high data rate and data volumes, and complex science planning and resource sharing. MRO has the capability to communicate with earth at a maximum of six Megabits per second (> 50 times any previous Mars missions). With the current Deep Space Network (DSN) contact schedule of 19 eight-hour tracks per week, the baseline mission plan is for MRO to return 34 Terabits of raw science data during the two year primary science phase. Each of the science instruments has its unique requirements for global mapping, regional survey, and targeted observations. Some instruments prefer nadir-only observations, while others require off-nadir observations (especially for stereo viewing). The requirements from these Mars viewing instruments presented a significant challenge for the operations team to design the complex science planning and resource sharing/allocation process. This paper describes what MRO project is implementing to solve these challenges.
Over the years, pollution prevention has proven to be a means to comply with environmental regulations, improve product performance and reduce costs. The NASA Acquisition Pollution Prevention (AP2) Program was created to help individual NASA Centers and programs work together to evaluate and adopt environmentally preferable technologies and practices. The AP2 Program accomplishes its mission using a variety of tools such as networking, information/technology exchange and partnering. Due to its extensive network of contacts, the AP2 Program is an excellent resource for finding existing solutions to problems. If no solution is readily known, the AP2 Program works to identify potential solutions and partners for demonstration/ validation projects. Partnering to prevent pollution is a cornerstone of NASA's prime mission and the One NASA Initiative. This annual newsletter highlights some of our program's collaborative efforts. I believe you will discover how the AP2 Program is responsive in meeting the Agency's environmental management strategic plans.
A nanofiber composite sensor for detecting alkanes can include a network of contacting nanofibers having multiple contact points. Each contact point can form an interfiber interface of interdigitated alkyl chains. Alkanes can be adsorbed at the interfiber interface which results in an increased interfiber distance between first and second nanofibers and a decreased charge transfer efficiency. The detected alkanes can be in a vapor or liquid phase.
Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology of scheduled communication contacts in a network based on the DTN (Delay-Tolerant Networking) architecture. It is designed to enable dynamic selection of data transmission routes in a space network based on DTN. This dynamic responsiveness in route computation should be significantly more effective and less expensive than static routing, increasing total data return while at the same time reducing mission operations cost and risk. The basic strategy of CGR is to take advantage of the fact that, since flight mission communication operations are planned in detail, the communication routes between any pair of bundle agents in a population of nodes that have all been informed of one another's plans can be inferred from those plans rather than discovered via dialogue (which is impractical over long one-way-light-time space links). Messages that convey this planning information are used to construct contact graphs (time-varying models of network connectivity) from which CGR automatically computes efficient routes for bundles. Automatic route selection increases the flexibility and resilience of the space network, simplifying cross-support and reducing mission management costs. Note that there are no routing tables in Contact Graph Routing. The best route for a bundle destined for a given node may routinely be different from the best route for a different bundle destined for the same node, depending on bundle priority, bundle expiration time, and changes in the current lengths of transmission queues for neighboring nodes; routes must be computed individually for each bundle, from the Bundle Protocol agent's current network connectivity model for the bundle s destination node (the contact graph). Clearly this places a premium on optimizing the implementation of the route computation algorithm. The scalability of CGR to very large networks remains a research topic. The information carried by CGR contact plan messages is useful not only for dynamic route computation, but also for the implementation of rate control, congestion forecasting, transmission episode initiation and termination, timeout interval computation, and retransmission timer suspension and resumption.
Routing in Delay-/Disruption-Tolerant Networking (DTN) has long been recognized as a challenging research topic. The difficulty lies in the fact that link intermittency and network partitioning, possibly coupled with long delays, prevent the use of Internet solutions based on an up-to-date comprehensive knowledge of network topology, as communicated by routing protocols. In the literature on DTN routing, there is a dichotomy between solutions designed for deterministic (e.g., space flight) networks, such as Contact Graph Routing (CGR), and the wide variety of protocols designed for opportunistic terrestrial networks. After a discussion of the origin and motivations of this duality, the paper presents an opportunistic extension of CGR (OCGR). The aim is to try to resolve the DTN routing dichotomy by providing a unified approach suitable for all DTN environments.
Routing in networks where nodes move randomly is particularly challenging due their potentially unpredictable, and rapidly changing topology. Several routing algorithms have been presented in the literature to address the needs of such networks, most of them implementing variants of controlled network flooding in the hope of successful data delivery. In this note, we compare the results of previous routing algorithms with Opportunistic Contact Graph Routing (OCGR), an enhanced version of Contact Graph Routing (CGR) that is suitable for networks where contacts cannot always be scheduled ahead of time. To perform the benchmark, we simulate a network of nodes moving in a certain space according to the Random Waypoint Mobility Model, and then take measurements of bundle delivery probabilty and overhead ratio as metrics of performance and cost respectively. Through this exercise, we demonstrate that the performance of OCGR is highly dependent on the type of network under consideration (e.g. very sparse vs. densely connected) and the assumed mobility model.