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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, satellite vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed, or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery.

Satellites↗
NASA NTRS2016

Exploration Clinical Decision Support System: Medical Data Architecture

The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear dimension biomarkers that enable image content-based retrieval and criteria assessment. In addition, a data mining engine (DME) is applied to cross-sectional adult surveys for predicting occurrence of renal calculi, ranked by statistical significance of demographics and specific food ingestion. In addition to this precursor space flight algorithm training, the DME will utilize a feature-engineering capability for unstructured clinical text classification health discovery. The ECDS backbone is a proposed multi-tier modular architecture providing data messaging protocols, storage, management and real-time patient data access. Technology demonstrations and success metrics will be finalized in FY16.

Biomedical support↗
DOE OSTI2024

Multi-range vehicle speed prediction using vehicle connectivity for enhanced energy efficiency of vehicles

An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Amini, Mohammad Reza↗
DOE OSTI2016

SU-F-P-03: Management of Time to Treatment Inititation: Case for An Electronic Whiteboard

Purpose: To determine if data mining of an electronic whiteboard improves the management of the Time to Treatment Initiation (TTI) in radiation oncology. Methods: An electronic whiteboard designed to help in managing the planning workflow and improves communication regarding patient planning progress was used to record the dates at which each phase of the planning process began or completed. These are CT Sim date, Plan Start, Physician Review, Physicist Review, Approval for Treatment Delivery, Setup or Verification of Simulation. Results: During clinical implementation, the electronic whiteboard was able to fulfill its primary objective of providing a transparent account of the planning progress of each patient. Peer pressure also meant that individual tasks, such as contouring, were easily brought to the attention of the responsible party and prioritized accordingly. Data mining to analyze the electronic whiteboard per patient (figure 1), per diagnosis (figure 2), per treatment modality (figure 3), per physician (figure 4), per planner (figure 5), etc., added another sophisticated tool in the management of Time to Treatment Initiation without compromising quality of the plans being generated. A longer than necessary time between CT Sim and Plan Start can be discussed among the members of the treatment team as an indication of inadequate/outdated CT Simulator, Contouring Tools, Image Fusion Tools, Other Imaging Studies (MRI, PET/CT) performed, etc. The same for the Plan Start to Physician Review where an extended time than expected may be due unrealistic planning goals, limited planning system features, etc. Conclusion: An Electronic Whiteboard in radiation oncology is not only helping with organizing planning workflow, it is also a potent tool that can be used to reduce the Time to Treatment Initiation by providing the clinic with hard data about the duration of each phase treatment planning as a function of different variable affecting the planning process. The work is supported by the Global Medical Physics Institute.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Topological analysis of void space in phosphate frameworks: Assessing storage properties for the environmentally important guest molecules and ions: CO 2 , H 2 O, UO 2 , PuO 2 , U, Pu, Sr 2+ , Cs + , CH 4 , and H 2

The entrapment of environmentally important materials to enable containment of polluting wastes from industry or energy production, storage of alternative fuels, or water sanitation, is of vital and immediate importance. Many of these materials are small molecules or ions that can be encapsulated via their adsorption into framework structures to create a host-guest complex. This is an ever-growing field of study and, as such, the search for more suitable porous materials for environmental applications is fundamental to progress. However, many industrial areas that require the use of adsorbents are fraught with practical challenges such as high temperatures, rapid gas expansion, radioactivity, or repetitive gas cycling, that the host material must withstand. Inorganic phosphates have a proven history of rigid structures, thermal stability, and are suspected to possess good resistance to radiation over geologic time scales. Furthermore, various experimental studies have established their ability to adsorb small molecules, such as water. In light of this, all known crystal structures of phosphate frameworks with meta- (P 3 O 9 ) or ultra- (P 5 O 14 ) stoichiometries are combined in a data-mining survey together with all theoretically possible structures of Ln a P b O c (where a, b, c are any integer, and Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, or Tm) that are statistically likely to form. Topological patterns within these framework structures are used to assess their suitability for hosting a variety of small guest molecules or ions that are important for environmental applications: CO 2 , H 2 O, UO 2 , PuO 2 , U, Pu, Sr 2+ , Cs + , CH 4 and H 2 . A range of viable phosphate-based host-guest complexes are identified from this data-mining and pattern-based structural analysis. Moreover, distinct topological preferences for hosting such guests are found, and metaphosphate stoichiometries are generally preferred over ultraphosphate configurations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Use of Soft Computing Technologies for a Qualitative and Reliable Engine Control System for Propulsion Systems

The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to improve overall vehicle system safety, reliability, and rocket engine performance by development of a qualitative and reliable engine control system (QRECS). Specifically, this will be addressed by enhancing rocket engine control using SCT, innovative data mining tools, and sound software engineering practices used in Marshall's Flight Software Group (FSG). The principle goals for addressing the issue of quality are to improve software management, software development time, software maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control methodologies, but to provide alternative design choices for control, implementation, performance, and sustaining engineering, all relative to addressing the issue of reliability. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion (system level), software engineering for embedded flight software systems, and soft computing technologies (i.e., neural networks, fuzzy logic, data mining, and Bayesian belief networks); some of which are briefed in this paper. For this effort, the targeted demonstration rocket engine testbed is the MC-1 engine (formerly FASTRAC) which is simulated with hardware and software in the Marshall Avionics & Software Testbed (MAST) laboratory that currently resides at NASA's Marshall Space Flight Center, building 4476, and is managed by the Avionics Department. A brief plan of action for design, development, implementation, and testing a Phase One effort for QRECS is given, along with expected results. Phase One will focus on development of a Smart Start Engine Module and a Mainstage Engine Module for proper engine start and mainstage engine operations. The overall intent is to demonstrate that by employing soft computing technologies, the quality and reliability of the overall scheme to engine controller development is further improved and vehicle safety is further insured. The final product that this paper proposes is an approach to development of an alternative low cost engine controller that would be capable of performing in unique vision spacecraft vehicles requiring low cost advanced avionics architectures for autonomous operations from engine pre-start to engine shutdown.

Trevino, Luis↗
DOE OSTI2016

Seamless Digital Environment – Plan for Data Analytics Use Case Study

The U.S Department of Energy Light Water Reactor Sustainability (LWRS) Program initiated research in to what is needed in order to provide a roadmap or model for Nuclear Power Plants to reference when building an architecture that can support the growing data supply and demand flowing through their networks. The Digital Architecture project published report Digital Architecture Planning Model (Oxstrand et. al, 2016) discusses things to consider when building an architecture to support the increasing needs and demands of data throughout the plant. Once the plant is able to support the data demands it still needs to be able to provide the data in an easy, quick and reliable method. A common method is to create a “one stop shop” application that a user can go to get all the data they need. The creation of this leads to the need of creating a Seamless Digital Environment (SDE) to integrate all the “siloed” data. An SDE is the desired perception that should be presented to users by gathering the data from any data source (e.g., legacy applications and work management systems) without effort by the user. The goal for FY16 was to complete a feasibility study for data mining and analytics for employing information from computer-based procedures enabled technologies for use in developing improved business analytics. The research team collaborated with multiple organizations to identify use cases or scenarios, which could be beneficial to investigate in a feasibility study. Many interesting potential use cases were identified throughout the FY16 activity. Unfortunately, due to factors out of the research team’s control, none of the studies were initiated this year. However, the insights gained and the relationships built with both PVNGS and NextAxiom will be valuable when moving forward with future research. During the 2016 annual Nuclear Information Technology Strategic Leadership (NITSL) group meeting it was identified would be very beneficial to the industry to support a research effort focused on data analytics. It was suggested that the effort would develop and evaluate use cases for data mining and analytics for employing information from plant sensors and database for use in developing improved business analytics.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Nuclear Physics Exascale Requirements Review: An Office of Science Review sponsored jointly by Advanced Scientific Computing Research and Nuclear Physics, June 15 - 17, 2016, Gaithersburg, Maryland

Imagine being able to predict — with unprecedented accuracy and precision — the structure of the proton and neutron, and the forces between them, directly from the dynamics of quarks and gluons, and then using this information in calculations of the structure and reactions of atomic nuclei and of the properties of dense neutron stars (NSs). Also imagine discovering new and exotic states of matter, and new laws of nature, by being able to collect more experimental data than we dream possible today, analyzing it in real time to feed back into an experiment, and curating the data with full tracking capabilities and with fully distributed data mining capabilities. Making this vision a reality would improve basic scientific understanding, enabling us to precisely calculate, for example, the spectrum of gravity waves emitted during NS coalescence, and would have important societal applications in nuclear energy research, stockpile stewardship, and other areas. This review presents the components and characteristics of the exascale computing ecosystems necessary to realize this vision.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2014

Effects of Long Duration Spaceflight on Venous and Arterial Compliance in Astronants

1. Project Overview Visual impairment and intracranial pressure (VIIP) is a spaceflight-associated medical condition affecting at least a third of American astronauts who have flown International Space Station (ISS) missions. VIIP is defined primarily by visual acuity deficits and anatomical changes to eye structures. In some astronauts, eye-related changes do not revert back to the preflight state upon return to Earth. Our team will study some of the possible causes for this syndrome. This will be achieved by reviewing previous astronaut data for factors that may predispose astronauts to higher rates of developing this syndrome or greater severity of symptoms. Additionally, we will conduct 3 separate experiments that will characterize vessels in the head and neck and measure the effects of the experimental conditions on ocular structures and function. 2. Technical Summary The primary objective of this study is to determine whether vascular compliance is altered by spaceflight and whether such adaptations are related to the incidence of the VIIP. In particular, we will measure ocular parameters and vascular compliance in vessels of the head and neck in astronauts who have no spaceflight experience (Ground), in astronauts before, during, and after spaceflight (Flight), and in bed rest subjects with conditions similar to spaceflight (Bed Rest). Additionally, we will analyze astronaut data from the Lifetime Surveillance of Astronaut Health (LSAH) archives to determine which factors might be predictive of the development of VIIP (Data Mining). The project will be conducted in four separate, but related parts. Hypothesis The central hypothesis of this proposal is that exposure to the spaceflight environment aboard the ISS may lead to development of the VIIP syndrome (increased intracranial pressure and impaired visual acuity) and that this may be related to alterations in venous and/or arterial compliance in the head and neck. Specific Aims 1. To determine whether noninvasive measures of venous and arterial compliance are altered by long-duration spaceflight exposure in ISS astronauts and whether these changes are related to the development of the VIIP syndrome. (Flight) 2. To determine whether previous spaceflight experience predispose astronauts to lower venous compliance and/or the development of the VIIP syndrome. (Ground + Flight) 3. To use a 14-day, 6deg head-down-tilt bed rest as a model of spaceflight, to evaluate the effect of aging on vascular compliance using a subject population similar to younger (25-35 yr) and older (45-55 yr) astronaut cohorts. (Bed Rest) 4. To determine what factors contribute to lower venous compliance and/or the development of the VIIP syndrome in astronauts. (Data Mining) 3. Earth Applications This research may inform the mechanisms that regulate blood/fluid flow in and out of the brain in the head and neck. This information may help with understanding of the mechanisms behind idiopathic intracranial hypertension. 4. Link to NASA Taskbook Entry Not Yet Available

Platts, Steven↗
DOE OSTI2020

Landscape composition and configuration have scale-dependent effects on agricultural pest suppression

Increasing landscape heterogeneity (composition and configuration) can enhance natural enemy populations and support pest suppression in agricultural landscapes. Using a network-based data mining approach, we examined independent gradients of landscape composition and configuration at six spatial scales that were associated with pest suppression services measured at 32 sites in Michigan and Wisconsin, USA. We compared the relative effects of landscape composition and configuration across scales with those of local crop type (corn or grassland). We found that multiple gradients of configurational heterogeneity were independent of composition and strongly associated with pest suppression, with different configuration metrics being predictive of pest suppression depending on the spatial scales and regions considered. Landscapes that were more configurationally heterogeneous at smaller spatial scales consistently supported higher pest suppression. In Michigan, pest suppression increased in landscapes with high edge contrast between annual crops and surrounding habitats and high edge density of grassland within 250-500 m radii. In Wisconsin, pest suppression increased with large core area of grassland and high field density within a 250 m radius. The main compositional effect we found was a positive relationship between grassland cover and pest suppression occurring at larger spatial scales (1000-1500 m) and occurring in Wisconsin but not in Michigan. Our findings demonstrate that effects of landscape composition and configuration on pest suppression differ across spatial scales and vary regionally. The network-based data mining techniques used here could be useful for disentangling intercorrelated landscape metrics in a variety of other contexts in landscape ecology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Prostate cancer invasion and metastasis: Insights from mining genomic data

Prostate cancer (PCa) is the second most commonly diagnosed malignancy in men in the Western world and the second leading cause of cancer-related deaths among men worldwide. Although most cancers have the potential to metastasize under appropriate conditions, PCa favors the skeleton as a primary site of metastasis, suggesting that the bone microenvironment is conducive to its growth. PCa metastasis proceeds through a complex series of molecular events that include angiogenesis at the site of the original tumor, local migration within the primary site, intravasation into the blood stream, survival within the circulation, extravasation of the tumor cells to the target organ and colonization of those cells within the new site. In turn, each one of these steps involves a complicated chain of events that utilize multiple protein–protein interactions, protein signaling cascades and transcriptional changes. Despite the urgent need to improve current biomarkers for diagnosis, prognosis and drug resistance, advances have been slow. Global gene expression methods such as gene microarrays and RNA sequencing enable the study of thousands of genes simultaneously and allow scientists to examine molecular pathways of cancer pathogenesis. In this review, we summarize the current literature that explored high-throughput transcriptome analysis toward the advancement of biomarker discovery for PCa. Novel biomarkers are strongly needed to enable more accurate detection of PCa, improve prediction of tumor aggressiveness and facilitate the discovery of new therapeutic targets for tailored medicine. Furthermore, promising molecular markers identified from gene expression profiling studies include HPN, CLU1, WT1, WNT5A, AURKA and SPARC.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

SU-E-T-240: Design and Implement of An Electronic Records Function for Treatment Plan Checked Meeting

Purpose: To replace the paper records, we designed an electronic records function for plan checked meeting in our in-house developed radiotherapy information management system(RTIMS). Methods: Since 2007, the RTIMS has been developed on a database and web service of Apache+PHP+MySQL, and almost all computers and smartphones could access the RTIMS through IE browser, to input, search, count, and print the data. In 2012, we also established an radiation therapy case conference multi-media system(RTCCMMS) based on Windows Remote Desktop feature. Since 2013, we have carried out the treatment plan checked meeting of the physics division in every afternoon for about half an hour. In 2014, we designed an electronic records function, which includes a meeting information record and a checked plan record. And the meeting record includes the following items: meeting date, name, place, length, status, attendee, content, etc. The plan record includes the followings: meeting date, meeting name, patient ID, gender, age, patient name, course, plan, purpose, position, technique, CTsim type, plan type, primary doctor, other doctor, primary physicist, other physicist, difficulty, quality, score, opinion, status, note, etc. Results: In the past year, the electronic meeting records function has been successfully developed and implemented in the division, and it could be accessed from an smartphone. Almost all items have the corresponding pull-down menu selection, and each option would try to intelligently inherit default value from the former record or other form. According to the items, we could do big data mining to the input data. It also has both Chinese and English two versions. Conclusion: It was demonstrated to be user-friendly and was proven to significantly improve the clinical efficiency and quality of treatment plan. Since the RTIMS is an in-house developed system, more functions can be added or modified to further enhance its potentials in research and clinical practice. Project supported by the National Natural Science Foundation of China (Grant No.81101694)

60 APPLIED LIFE SCIENCES↗
NASA NTRS1998

Mining for Data

AbTech Corporation used an F-18 HARV (High Alpha Research Vehicle) simulation developed by NASA to create an interactive computer-based prototype of the MQ (Model Quest) SV (System Validator) tool. Dryden Flight Research Center provided support to develop, test, and rapidly reprogram the validation function. AbTech's ModelQuest Enterprises highly automated and outperforms other modeling techniques to quickly discover meaningful relationships, patterns, and trends in databases. Applications include technical and business professionals in finance, marketing, business, banking, retail, healthcare, and aerospace.

Source record↗
NASA NTRS2002

Mining Marketing Data

MarketMiner(R) Products, a line of automated marketing analysis tools manufactured by MarketMiner, Inc., can benefit organizations that perform significant amounts of direct marketing. MarketMiner received a Small Business Innovation Research (SBIR) contract from NASA's Johnson Space Center to develop the software as a data modeling tool for space mission applications. The technology was then built into the company current products to provide decision support for business and marketing applications. With the tool, users gain valuable information about customers and prospects from existing data in order to increase sales and profitability. MarketMiner(R) is a registered trademark of MarketMiner, Inc.

Source record↗
NASA NTRS2005

Tools and Data Services from the NASA Earth Satellite Observations for Climate Applications

Climate science and applications require access to vast amounts of archived high quality data, software tools and services for data manipulation and information extraction. These on the other hand require gaining detailed understanding of the data's internal structure and physical implementation to data reduction, combination and data product production. This time-consuming task must be undertaken before the core investigation can begin and is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets of different formats, structures, and resolutions. In order to address these issues the Goddard Space Flight Center (GSFC) Earth Sciences (GES), Data and Information Service Center (DISC) Distributed Active Archive Center (DAAC) has made great progress in facilitating science and applications research by developing innovative tools and data services applied to the Earth sciences atmospheric and climate data. The GES/DISC/DAAC has successfully implemented and maintained a long-term climate satellite data archive and developed tools and services to a variety of atmospheric science missions including AIRS, AVHRR, MODIS, SeaWiFS, SORCE, TOMS, TOVS, TRMM, and UARS and Aura instruments providing researchers with excellent opportunities to acquire accurate and continuous atmospheric measurements. Since the number of climate science products from these various missions is steadily increasing as a result of more sophisticated sensors and new science algorithms, the main challenge for data centers like the GES/DISC/DAAC is to guide users through the variety of data sets and products, provide tools to visualize and reduce the volume of the data and secure uninterrupted and reliable access to data and related products. This presentation will describe the effort at the GES/DISC/DAAC to build a bridge between multi-sensor data and the effective scientific use of the data, with an emphasis on the heritage satellite observations and science products for climate applications. The intent is to inform users of the existence of this large collection of data and products; suggest starting points for cross-platform science projects and data mining activities and provide data services and tools information. More information about the GES/DISC/DAAC satellite data and products, tools, and services can be found at http://daac.gsfc.nasa.gov.

Vicente, Gilberto A.↗