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The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.
Today, due to great technological advancements, it is possible to study everything at the same time. This ability has given birth to “totality” studies in the fields of genomics, transcriptomics, proteomics, and metabolomics. In turn, the combined study of all these global analyses gave birth to the field of systems biology. Another “totality” field brought to life with new emerging technologies is structural genomics, an effort to determine the three-dimensional structure of every protein encoded in a genome. The Seattle Structural Genomics Center for Infectious Disease (SSGCID) is a specialized structural genomics effort composed of academic (University of Washington), government (Pacific Northwest National Laboratory), not-for-profit (Seattle BioMed), and commercial (Emerald BioStructures) institutions that is funded by the National Institute of Allergy and Infectious Diseases (Federal Contract: HHSN272200700057C and HHSN27220120025C) to apply genome-scale approaches in solving protein structures from biodefense organisms, as well as those causing emerging and re-emerging disease. In five years over 540 structures have been deposited into the Protein Data Bank (PDB) by SSGICD. About one third of all SSGCID structures contain bound ligands, many of which are metabolites or metabolite analogues present in the cell. These proteins structures are the blueprints for the structure-based design of the next generation of drugs against bacterial pathogens and other infectious diseases. Many of the selected SSGCID targets are annotated enzymes from known metabolomic pathways essential to cellular vitality since selectively “knocking-out” one of the enzymes in an important pathway with a drug may be fatal to the organism. One reason metabolomic pathways are important is because of the small molecules, or metabolites, produced at various steps in these pathways and identified by metabolomic studies. Unlike genomics, transcriptomics, and proteomics that may be influenced by epigenetic, post-transcriptional, and post-translational modifications, respectively, the metabolites present in the cell at any one time represent downstream biochemical endproducts, and therefore, metabolite profiles may be most closely associated with a phenotype and provide valuable information for infectious disease research. Metabolomic data would be even more useful if it could be linked to the vast amount of structural genomics data. Towards this goal SSGCID has created an automated website (http://apps.sbri.org/SSGCIDTargetStatus/Pathway) that assigns selected SSGCID target proteins to MetaCyc pathways (http://metacyc.org/). Details of this website will be provided here. The SSGCID-Pathway website represents a first big step towards linking metabolites and metabolic pathways to structural genomic data with the goal of accelerating the discovery of new agents to battle infectious diseases.
The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.
The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.
Frenchman Flat basin on the Nevada National Security Site (NNSS) contains Corrective Action Unit (CAU) 98, which is comprised of ten underground nuclear test locations. Environmental management of these test locations is part of the Underground Test Area (UGTA) Activity conducted by the U.S. Department of Energy (DOE) under the Federal Facility Agreement and Consent Order (FFACO) (1996, as amended) with the U.S. Department of Defense (DOD) and the State of Nevada. A Corrective Action Decision Document (CADD)/Corrective Action Plan (CAP) has been approved for CAU 98 (DOE, 2011). The CADD/CAP reports on the Corrective Action Investigation that was conducted for the CAU, which included characterization and modeling. It also presents the recommended corrective actions to address the objective of protecting human health and the environment. The recommended corrective action alternative is “Closure in Place with Modeling, Monitoring, and Institutional Controls.” The role of monitoring is to verify that Contaminants of Concern (COCs) have not exceeded the Safe Drinking Water Act (SDWA) limits (Code of Federal Regulations, 2014) at the regulatory boundary, to ensure that institutional controls are adequate, and to monitor for changed conditions that could affect the closure conditions. The long-term closure monitoring program will be planned and implemented as part of the Closure Report stage after activities specified in the CADD/CAP are complete. Groundwater at the NNSS has been monitored for decades through a variety of programs. Current activities were recently consolidated in an NNSS Integrated Sampling Plan (DOE, 2014). Although monitoring directed by the plan is not intended to meet the FFACO long-term monitoring requirements for a CAU (which will be defined in the Closure Report), the objective to ensure public health protection is similar. It is expected that data collected in accordance with the plan will support the transition to long-term monitoring at each CAU. The sampling plan is designed to ensure that monitoring activities occur in compliance with the UGTA Quality Assurance Plan (DOE, 2012). The sampling plan should be referenced for Quality Assurance (QA) elements and procedures governing sampling activities. The NNSS Integrated Sampling Plan specifies the groundwater monitoring that will occur in CAU 98 until the long-term monitoring program is approved in the Closure Report. The plan specifies the wells that must be monitored and categorizes them by their sampling objective with the associated analytical requirements and frequency. Possible sample collection methods and required standard operating procedures are also presented. The intent of this handbook is to augment the NNSS Integrated Sampling Plan by providing well-specific details for the sampling professional implementing the Sampling Plan in CAU 98, Frenchman Flat. This handbook includes each CAU 98 well designated for sampling in the NNSS Integrated Sampling Plan. The following information is provided in the individual well sections: 1. The purpose of sampling. 2. A physical description of the well. 3. The chemical characteristics of the formation water. 4. Recommended protocols for purging and sampling. The well-specific information has been gathered from numerous historical and current sources cited in each section, but two particularly valuable resources merit special mention. These are the USGS NNSS website (http://nevada.usgs.gov/doe_nv/ntsarea5.cfm) and the UGTA Field Operations website (https://ugta.nv.doe.gov/sites/Field%20Operations/default.aspx). 2 Land surface elevation and measuring point for water level measurements in Frenchman Flat were a focus during CAU investigations (see Appendix B, Attachment 1 in Navarro-Intera, 2014). Both websites listed above provide information on the accepted datum for each well. A summary is found on the home page for the well on the USGS website. Additional information is available through a link in the “Available Data” section to an “MP diagram” with a photo annotated with the datum information. On the UGTA Field Operations well page, the same information is in the “Wellhead Diagram” link. Well RNM-2s does not have an annotated photo at this time. All of the CAU 98 monitoring wells are located within Area 5 of Frenchman Flat, with the exception of ER-11-2 in Area 11 (Figure 1). The wells are clustered in two areas: the northern area (Figure 2) and the central area (Figure 3). Each well is discussed below in geographic order from north to south as follows: ER-11-2, ER-5-3 shallow piezometer, ER-5-3-2, ER-5-5, RNM-1, RNM-2s, and UE-5n.
The mission goals, control parameters, and instrumentation for the Galileo entry probe are described. The goal for the probe is to penetrate the Jovian atmosphere to 10 bars, begin data gathering and transmission at about 0.1 bar, and make as many in-situ cloud measurements as possible. The probe will pass through a 16,000 K shock layer, which has led to a ratio of 5 kg of heat shield to every kg of instrumentation on the probe. An entry angle between -7.0 to -10.2 deg will be used, and possible targets with respect to declinations associated with a 1986 launch are discussed. The preentry mission phase, entry/descent sequence, and the baseline mission relay link performance are outlined. Data may be available down to 20 bars, and the probe performance will aid in design goals for subsequent Saturn and Uranus probes.
Phycobilisomes (PBSs) are the major photosynthetic light-harvesting complexes in cyanobacteria and red algae. PBS, a multisubunit protein complex, has two major interfaces that comprise intrinsically disordered regions (IDRs): rod–core and core-membrane. IDRs do not form regular, three-dimensional structures on their own. Their presence in the photosynthetic pigment–protein complexes portends their structural and functional importance. A recent model suggests that PB-loop, an IDR located on the PBS subunit ApcE and C-terminal extension (CTE) of the PBS subunit ApcG, forms a structural protrusion on the PBS core-membrane side, facing the thylakoid membrane. Here, the structural synergy between the rod–core region and the core-membrane region was investigated using quantitative mass spectrometry (MS). The AlphaFold-predicted CpcG-CTE structure was first modeled onto the PBS rod–core region, guided and justified by the isotopically encoded structural MS data. Quantitative cross-linking MS analysis revealed that the structural proximity of the PB-loop in ApcE and ApcG-CTE is significantly disturbed in the absence of six PBS rods, which are attached to PBS via CpcG-CTE, indicative of drastic conformational changes and decreased structural integrity. Furthermore, these results suggest that CpcG-rod attachment on the PBS rod–core side is essentially required for the PBS core-membrane structural assembly. The hypothesized long-range synergy between the rod–core interface (where the orange carotenoid protein also functions) and the terminal energy emitter of PBS must have important regulatory roles in PBS core assembly, light-harvesting, and excitation energy transmission. These data also lend strategies that genetic truncation of the light-harvesting antennas aimed for improved photosynthetic productivity must rely on an in-depth understanding of their global structural integrity.
In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.
Historically, it has been the case that SWaP placed such severe constraints on radios that the links between spacecraft and the ground were relatively slow. This meant that the radio link was normally a significant bottleneck in returning scientific data. Over recent years, however, a combination of more efficient radio design, intelligent waveforms, and highly directed, high-frequency RF / optical systems have led to a rapid increase in the amount of data that can be pushed through radio and optical links. This has led to some cases where the radio links are capable of moving data much more quickly than the spacecraft and instruments are capable of actually generating it! In some instances, scientific data can therefore be lost not because the downlink is too slow to support the data rate, but instead because the spacecraft was not designed in a way that would let it fully utilize both the radio and the networking services available to it.The High Data Rate Architecture (HiDRA) project describes a packet-based approach to building modern, distributed spacecraft systems. It presents a means for spacecraft and other assets to participate in both present and future Delay Tolerant Networks (DTN), while simultaneously ensuring that the asset is able to fully utilize the new, high-speed links that have been seeing more widespread development and deployment in recent years. With this in mind, this paper begins with a discussion regarding HiDRA's evolution. Next, it discusses the capabilities and limitations of NASA's present DTN-enabled networks. Of particular note is the way in which principles of network design at the terrestrial level (e.g. use of programmable networks / software-defined networks, separation between data and control plane, infusion of COTS Ethernet switch chips, etc.) can all be translated into the space environment as well. After this, the paper discusses the design and implementation of a present prototype reference implementation of High-Rate DTN (HDTN), which is intended to demonstrate future high-rate networking concepts as part of a coherent demonstration on the International Space Station (ISS). The goal, of both the research and of this implementation, is to help develop a ready-made toolbox of ideas, approaches, and examples from which mission designers can draw when putting together new missions. Assuming all goes as planned, this should not only work to reduce the cost of individual mission design, but also improve the rate at which science data can be returned for mission participants to review.
Previous work has shown that Ka-band attenuation due to rainfall and corresponding S-band reflectivity are highly correlated. This paper reports on work whose goal is to determine the feasibility of estimation and, by extension, prediction of one parameter from the other using the Florida ACTS propagation terminal (APT) and the nearby WSR-88D S-band Doppler weather radar facility operated by the National Weather Service. This work is distinguished from previous efforts in this area by (1) the use of a single-polarized radar, preventing estimation of the drop size distribution (e.g., with dual polarization) and (2) the fact that the radar and APT sites are not co-located. Our approach consists of locating the radar volume elements along the satellite slant path and then, from measured reflectivity, estimating the specific attenuation for each associated path segment. The sum of these contributions yields an estimation of the millimeter-wave attenuation on the space-ground link. Seven days of data from both systems are analyzed using this procedure. The results indicate that definite correlation of S-band reflectivity and Ka-band attenuation exists even under the restriciton of this experiment. Based on these results, it appears possible to estimate Ka-band attenuation using widely available operational weather radar data. Conversely, it may be possible to augment current radar reflectivity data and coverage with low-cost attenuation or sky temperature data to improve the estimation of rain rates.
The update of ORDEM2000, the NASA Orbital Debris Engineering Model, to its new version ORDEM2010, is nearly complete. As a part of the ORDEM upgrade, this paper addresses the simulation of micro-debris (greater than 10 m and smaller than 1 mm in size) populations in low Earth orbit. The principal data used in the modeling of the micron-sized debris populations are in-situ hypervelocity impact records, accumulated in post-flight damage surveys on the space-exposed surfaces of returned spacecrafts. The development of the micro-debris model populations follows the general approach to deriving other ORDEM2010-required input populations for various components and types of debris. This paper describes the key elements and major steps in the statistical inference of the ORDEM2010 micro-debris populations. A crucial step is the construction of a degradation/ejecta source model to provide prior information on the micron-sized objects (such as orbital and object-size distributions). Another critical step is to link model populations with data, which is rather involved. It demands detailed information on area-time/directionality for all the space-exposed elements of a shuttle orbiter and damage laws, which relate impact damage with the physical properties of a projectile and impact conditions such as impact angle and velocity. Also needed are model-predicted debris fluxes as a function of object size and impact velocity from all possible directions. In spite of the very limited quantity of the available shuttle impact data, the population-derivation process is satisfactorily stable. Final modeling results obtained from shuttle window and radiator impact data are reasonably convergent and consistent, especially for the debris populations with object-size thresholds at 10 and 100 m.
The update of ORDEM2000, the NASA Orbital Debris Engineering Model, to its new version . ORDEM2010, is nearly complete. As a part of the ORDEM upgrade, this paper addresses the simulation of micro-debris (greater than 10 micron and smaller than 1 mm in size) populations in low Earth orbit. The principal data used in the modeling of the micron-sized debris populations are in-situ hypervelocity impact records, accumulated in post-flight damage surveys on the space-exposed surfaces of returned spacecrafts. The development of the micro-debris model populations follows the general approach to deriving other ORDEM2010-required input populations for various components and types of debris. This paper describes the key elements and major steps in the statistical inference of the ORDEM2010 micro-debris populations. A crucial step is the construction of a degradation/ejecta source model to provide prior information on the micron-sized objects (such as orbital and object-size distributions). Another critical step is to link model populations with data, which is rather involved. It demands detailed information on area-time/directionality for all the space-exposed elements of a shuttle orbiter and damage laws, which relate impact damage with the physical properties of a projectile and impact conditions such as impact angle and velocity. Also needed are model-predicted debris fluxes as a function of object size and impact velocity from all possible directions. In spite of the very limited quantity of the available shuttle impact data, the population-derivation process is satisfactorily stable. Final modeling results obtained from shuttle window and radiator impact data are reasonably convergent and consistent, especially for the debris populations with object-size thresholds at 10 and 100 micron.
Spacecraft subsystem design, performance evaluation, and system tradeoffs are presented for the LANDSAT follow-on mission (LF/O) spacecraft to TDRSS link for the transmission of thematic mapper (TM) and multispectral scanner (MSS) data and for the LF/O spacecraft to STDN and other direct users link for the transmission of TM data. Included are requirements definition, link analysis, subsystem and hardware tradeoffs, conceptual selection, hardware definition, and identification of required new technology. Cost estimates of the recommended communication system including both recurring and non recurring costs are discussed.
In recent years, network bandwidth requirements have scaled multiple folds, pushing the need for the development of data exchange mechanisms at 100 Gb/s and beyond. High performance computing, climate modeling, large-scale storage, and collaborative scientific research are examples of applications that can greatly benefit by leveraging high bandwidth capabilities of the order of 100 Gb/s. Such requirements and advances in IEEE Ethernet standards, Optical Transport Unit4 (OTU4), and host-system interconnects demand a network infrastructure supporting throughput rates of the order of 100 Gb/s with a single wavelength. To address such a demand Acadia Optronics in collaboration with the University of New Mexico, proposed and developed a end-system Network Interface Controller (NIC) for the 100Gbps WANs. Acadia’s 100G NIC employs an FPGA based system with a high-performance processor interconnect (PCIe 3.0) and a high capacity optical transmission link (CXP) to provide data transmission at the rate of 100 Gbps.
The Colorado School of Mines (CSM) was awarded a grant by the National Energy Technology Laboratory (NETL), Department of Energy (DOE) to conduct a research project en- titled GIS- and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development in October of 2008. The ultimate goal of this research project is to develop a water resource geo-spatial infrastructure that serves as “baseline data” for creating solutions on water resource management and for supporting decisions making on oil shale resource development. The project came to the end on September 30, 2012. This final project report will report the key findings from the project activity, major accomplishments, and expected impacts of the research. At meantime, the gamma version (also known as Version 4.0) of the geodatabase as well as other various deliverables stored on digital storage media will be send to the program manager at NETL, DOE via express mail. The key findings from the project activity include the quantitative spatial and temporal distribution of the water resource throughout the Piceance Basin, water consumption with respect to oil shale production, and data gaps identified. Major accomplishments of this project include the creation of a relational geodatabase, automated data processing scripts (Matlab) for database link with surface water and geological model, ArcGIS Model for hydrogeologic data processing for groundwater model input, a 3D geological model, surface water/groundwater models, energy resource development systems model, as well as a web-based geo-spatial infrastructure for data exploration, visualization and dissemination. This research will have broad impacts of the devel- opment of the oil shale resources in the US. The geodatabase provides a “baseline” data for fur- ther study of the oil shale development and identification of further data collection needs. The 3D geological model provides better understanding through data interpolation and visualization techniques of the Piceance Basin structure spatial distribution of the oil shale resources. The sur- face water/groundwater models quantify the water shortage and better understanding the spatial distribution of the available water resources. The energy resource development systems model reveals the phase shift of water usage and the oil shale production, which will facilitate better planning for oil shale development. Detailed descriptions about the key findings from the project activity, major accomplishments, and expected impacts of the research will be given in the sec- tion of “ACCOMPLISHMENTS, RESULTS, AND DISCUSSION” of this report.
The ecological importance of viruses is now widely recognized, yet our limited knowledge of viral sequence space and virus–host interactions precludes accurate prediction of their roles and impacts. In this study, we mined publicly available bacterial and archaeal genomic data sets to identify 12,498 high-confidence viral genomes linked to their microbial hosts. These data augment public data sets 10-fold, provide first viral sequences for 13 new bacterial phyla including ecologically abundant phyla, and help taxonomically identify 7–38% of ‘unknown’ sequence space in viromes. Genome- and network-based classification was largely consistent with accepted viral taxonomy and suggested that (i) 264 new viral genera were identified (doubling known genera) and (ii) cross-taxon genomic recombination is limited. Further analyses provided empirical data on extrachromosomal prophages and coinfection prevalences, as well as evaluation of in silico virus–host linkage predictions. Together these findings illustrate the value of mining viral signal from microbial genomes.
We propose a network architecture with a separate quantum dataplane and a conventional control plane: (a) Quantum Data Plane: The Quantum Data plane consists of links of dark fibers connecting quantum switches and repeaters, which in turn, connect to quantum computers, memory and sensors. Since the current reach is limited to local areas, it will begin as a collection of site networks at laboratories, (b) Conventional Control Plane: The Control plane provides management access to quantum devices for configuration and provisioning via control nodes with firewall and encryption capabilities. Continuous Test and Transition Infrastructure: We propose an infrastructure with a control plane connecting multiple sites via encrypted tunnels over conventional networks consisting of the following: (a) Site Quantum Networks: Individual site networks supported by their fiber plants connect laboratories that house and connect to their quantum devices for testing and interoperability.(b) Site Control Planes: Sites are connected over individual control planes with control hosts with Software Defined Networking capabilities, which can be peered with other networks via ESnet.(c) Progressive Expansion: Initially, sites will develop individual data planes with their specific quantum devices and fiber connections, and mechanisms to interface with conventional networks. They progressively expand and interconnect, under a wide-area ecosystem of peered control planes for device testing, interoperability development and roll off into production environments.