High capacity reversible watermarking for audio by histogram shifting and predicted error expansion.

PubMed

Wang, Fei; Xie, Zhaoxin; Chen, Zuo

2014-01-01

Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution algorithm to optimize prediction coefficients and then apply prediction error expansion to output stego data. Second, in order to reduce location map bits length, we introduced histogram shifting scheme. Meanwhile, the prediction error modification threshold according to a given embedding capacity can be computed by our proposed scheme. Experiments show that this algorithm improves the SNR of embedded audio signals and embedding capacity, drastically reduces location map bits length, and enhances capacity control capability.

High Fidelity Ion Beam Simulation of High Dose Neutron Irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Was, Gary; Wirth, Brian; Motta, Athur

The objective of this proposal is to demonstrate the capability to predict the evolution of microstructure and properties of structural materials in-reactor and at high doses, using ion irradiation as a surrogate for reactor irradiations. “Properties” includes both physical properties (irradiated microstructure) and the mechanical properties of the material. Demonstration of the capability to predict properties has two components. One is ion irradiation of a set of alloys to yield an irradiated microstructure and corresponding mechanical behavior that are substantially the same as results from neutron exposure in the appropriate reactor environment. Second is the capability to predict the irradiatedmore » microstructure and corresponding mechanical behavior on the basis of improved models, validated against both ion and reactor irradiations and verified against ion irradiations. Taken together, achievement of these objectives will yield an enhanced capability for simulating the behavior of materials in reactor irradiations.« less

Improvements in analysis techniques for segmented mirror arrays

NASA Astrophysics Data System (ADS)

Michels, Gregory J.; Genberg, Victor L.; Bisson, Gary R.

2016-08-01

The employment of actively controlled segmented mirror architectures has become increasingly common in the development of current astronomical telescopes. Optomechanical analysis of such hardware presents unique issues compared to that of monolithic mirror designs. The work presented here is a review of current capabilities and improvements in the methodology of the analysis of mechanically induced surface deformation of such systems. The recent improvements include capability to differentiate surface deformation at the array and segment level. This differentiation allowing surface deformation analysis at each individual segment level offers useful insight into the mechanical behavior of the segments that is unavailable by analysis solely at the parent array level. In addition, capability to characterize the full displacement vector deformation of collections of points allows analysis of mechanical disturbance predictions of assembly interfaces relative to other assembly interfaces. This capability, called racking analysis, allows engineers to develop designs for segment-to-segment phasing performance in assembly integration, 0g release, and thermal stability of operation. The performance predicted by racking has the advantage of being comparable to the measurements used in assembly of hardware. Approaches to all of the above issues are presented and demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.

A critical evaluation of bridge scour for Michigan specific conditions

DOT National Transportation Integrated Search

2011-02-01

The overall goal of this research was to improve MDOTs bridge scour prediction capability. In : an effort to achieve this goal, the research team evaluated scour prediction methods utilized by : state DOTs, conducted a field data collection project, ...

Coating Life Prediction

NASA Technical Reports Server (NTRS)

Nesbitt, J. A.; Gedwill, M. A.

1984-01-01

Hot-section gas-turbine components typically require some form of coating for oxidation and corrosion protection. Efficient use of coatings requires reliable and accurate predictions of the protective life of the coating. Currently engine inspections and component replacements are often made on a conservative basis. As a result, there is a constant need to improve and develop the life-prediction capability of metallic coatings for use in various service environments. The purpose of this present work is aimed at developing of an improved methodology for predicting metallic coating lives in an oxidizing environment and in a corrosive environment.

High fidelity studies of exploding foil initiator bridges, Part 3: ALEGRA MHD simulations

NASA Astrophysics Data System (ADS)

Neal, William; Garasi, Christopher

2017-01-01

Simulations of high voltage detonators, such as Exploding Bridgewire (EBW) and Exploding Foil Initiators (EFI), have historically been simple, often empirical, one-dimensional models capable of predicting parameters such as current, voltage, and in the case of EFIs, flyer velocity. Experimental methods have correspondingly generally been limited to the same parameters. With the advent of complex, first principles magnetohydrodynamic codes such as ALEGRA and ALE-MHD, it is now possible to simulate these components in three dimensions, and predict a much greater range of parameters than before. A significant improvement in experimental capability was therefore required to ensure these simulations could be adequately verified. In this third paper of a three part study, the experimental results presented in part 2 are compared against 3-dimensional MHD simulations. This improved experimental capability, along with advanced simulations, offer an opportunity to gain a greater understanding of the processes behind the functioning of EBW and EFI detonators.

Experience Transitioning Models and Data at the NOAA Space Weather Prediction Center

NASA Astrophysics Data System (ADS)

Berger, Thomas

2016-07-01

The NOAA Space Weather Prediction Center has a long history of transitioning research data and models into operations and with the validation activities required. The first stage in this process involves demonstrating that the capability has sufficient value to customers to justify the cost needed to transition it and to run it continuously and reliably in operations. Once the overall value is demonstrated, a substantial effort is then required to develop the operational software from the research codes. The next stage is to implement and test the software and product generation on the operational computers. Finally, effort must be devoted to establishing long-term measures of performance, maintaining the software, and working with forecasters, customers, and researchers to improve over time the operational capabilities. This multi-stage process of identifying, transitioning, and improving operational space weather capabilities will be discussed using recent examples. Plans for future activities will also be described.

Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 2 (JMA/MRI-CPS2): atmosphere-land-ocean-sea ice coupled prediction system for operational seasonal forecasting

NASA Astrophysics Data System (ADS)

Takaya, Yuhei; Hirahara, Shoji; Yasuda, Tamaki; Matsueda, Satoko; Toyoda, Takahiro; Fujii, Yosuke; Sugimoto, Hiroyuki; Matsukawa, Chihiro; Ishikawa, Ichiro; Mori, Hirotoshi; Nagasawa, Ryoji; Kubo, Yutaro; Adachi, Noriyuki; Yamanaka, Goro; Kuragano, Tsurane; Shimpo, Akihiko; Maeda, Shuhei; Ose, Tomoaki

2018-02-01

This paper describes the Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 2 (JMA/MRI-CPS2), which was put into operation in June 2015 for the purpose of performing seasonal predictions. JMA/MRI-CPS2 has various upgrades from its predecessor, JMA/MRI-CPS1, including improved resolution and physics in its atmospheric and oceanic components, introduction of an interactive sea-ice model and realistic initialization of its land component. Verification of extensive re-forecasts covering a 30-year period (1981-2010) demonstrates that JMA/MRI-CPS2 possesses improved seasonal predictive skills for both atmospheric and oceanic interannual variability as well as key coupled variability such as the El Niño-Southern Oscillation (ENSO). For ENSO prediction, the new system better represents the forecast uncertainty and transition/duration of ENSO phases. Our analysis suggests that the enhanced predictive skills are attributable to incremental improvements resulting from all of the changes, as is apparent in the beneficial effects of sea-ice coupling and land initialization on 2-m temperature predictions. JMA/MRI-CPS2 is capable of reasonably representing the seasonal cycle and secular trends of sea ice. The sea-ice coupling remarkably enhances the predictive capability for the Arctic 2-m temperature, indicating the importance of this factor, particularly for seasonal predictions in the Arctic region.

Recent progress towards predicting aircraft ground handling performance

NASA Technical Reports Server (NTRS)

Yager, T. J.; White, E. J.

1981-01-01

Capability implemented in simulating aircraft ground handling performance is reviewed and areas for further expansion and improvement are identified. Problems associated with providing necessary simulator input data for adequate modeling of aircraft tire/runway friction behavior are discussed and efforts to improve tire/runway friction definition, and simulator fidelity are described. Aircraft braking performance data obtained on several wet runway surfaces are compared to ground vehicle friction measurements. Research to improve methods of predicting tire friction performance are discussed.

Light transport feature for SCINFUL.

PubMed

Etaati, G R; Ghal-Eh, N

2008-03-01

An extended version of the scintillator response function prediction code SCINFUL has been developed by incorporating PHOTRACK, a Monte Carlo light transport code. Comparisons of calculated and experimental results for organic scintillators exposed to neutrons show that the extended code improves the predictive capability of SCINFUL.

Computational Modeling in Concert with Laboratory Studies: Application to B Cell Differentiation

EPA Science Inventory

Remediation is expensive, so accurate prediction of dose-response is important to help control costs. Dose response is a function of biological mechanisms. Computational models of these mechanisms improve the efficiency of research and provide the capability for prediction.

The influence of a wall function on turbine blade heat transfer prediction

NASA Technical Reports Server (NTRS)

Whitaker, Kevin W.

1989-01-01

The second phase of a continuing investigation to improve the prediction of turbine blade heat transfer coefficients was completed. The present study specifically investigated how a numeric wall function in the turbulence model of a two-dimensional boundary layer code, STAN5, affected heat transfer prediction capabilities. Several sources of inaccuracy in the wall function were identified and then corrected or improved. Heat transfer coefficient predictions were then obtained using each one of the modifications to determine its effect. Results indicated that the modifications made to the wall function can significantly affect the prediction of heat transfer coefficients on turbine blades. The improvement in accuracy due the modifications is still inconclusive and is still being investigated.

Observational breakthroughs lead the way to improved hydrological predictions

NASA Astrophysics Data System (ADS)

Lettenmaier, Dennis P.

2017-04-01

New data sources are revolutionizing the hydrological sciences. The capabilities of hydrological models have advanced greatly over the last several decades, but until recently model capabilities have outstripped the spatial resolution and accuracy of model forcings (atmospheric variables at the land surface) and the hydrologic state variables (e.g., soil moisture; snow water equivalent) that the models predict. This has begun to change, as shown in two examples here: soil moisture and drought evolution over Africa as predicted by a hydrology model forced with satellite-derived precipitation, and observations of snow water equivalent at very high resolution over a river basin in California's Sierra Nevada.

Extreme-Scale Computing Project Aims to Advance Precision Oncology | Poster

Cancer.gov

Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict drug response, and improve treatments for patients.

Predictive protocol of flocks with small-world connection pattern.

PubMed

Zhang, Hai-Tao; Chen, Michael Z Q; Zhou, Tao

2009-01-01

By introducing a predictive mechanism with small-world connections, we propose a new motion protocol for self-driven flocks. The small-world connections are implemented by randomly adding long-range interactions from the leader to a few distant agents, namely, pseudoleaders. The leader can directly affect the pseudoleaders, thereby influencing all the other agents through them efficiently. Moreover, these pseudoleaders are able to predict the leader's motion several steps ahead and use this information in decision making towards coherent flocking with more stable formation. It is shown that drastic improvement can be achieved in terms of both the consensus performance and the communication cost. From the engineering point of view, the current protocol allows for a significant improvement in the cohesion and rigidity of the formation at a fairly low cost of adding a few long-range links embedded with predictive capabilities. Significantly, this work uncovers an important feature of flocks that predictive capability and long-range links can compensate for the insufficiency of each other. These conclusions are valid for both the attractive and repulsive swarm model and the Vicsek model.

Aeroservoelasticity

NASA Technical Reports Server (NTRS)

Noll, Thomas E.

1990-01-01

The paper describes recent accomplishments and current research projects along four main thrusts in aeroservoelasticity at NASA Langley. One activity focuses on enhancing the modeling and analysis procedures to accurately predict aeroservoelastic interactions. Improvements to the minimum-state method of approximating unsteady aerodynamics are shown to provide precise low-order models for design and simulation tasks. Recent extensions in aerodynamic correction-factor methodology are also described. With respect to analysis procedures, the paper reviews novel enhancements to matched filter theory and random process theory for predicting the critical gust profile and the associated time-correlated gust loads for structural design considerations. Two research projects leading towards improved design capability are also summarized: (1) an integrated structure/control design capability and (2) procedures for obtaining low-order robust digital control laws for aeroelastic applications.

How feasible is the rapid development of artificial superintelligence?

NASA Astrophysics Data System (ADS)

Sotala, Kaj

2017-11-01

What kinds of fundamental limits are there in how capable artificial intelligence (AI) systems might become? Two questions in particular are of interest: (1) How much more capable could AI become relative to humans, and (2) how easily could superhuman capability be acquired? To answer these questions, we will consider the literature on human expertise and intelligence, discuss its relevance for AI, and consider how AI could improve on humans in two major aspects of thought and expertise, namely simulation and pattern recognition. We find that although there are very real limits to prediction, it seems like AI could still substantially improve on human intelligence.

Introduction: Strengthening the foundation of wildland fire Effects prediction for research and management

Treesearch

Matthew B. Dickinson; Kevin C. Ryan

2010-01-01

As prescribed fire use increases and the options for responding to wildfires continue to expand beyond suppression, the need for improving fire effects prediction capabilities be¬comes increasingly apparent. The papers in this Fire Ecology special issue describe recent advances in fire effects prediction for key classes of direct (first-order) fire effects. Important...

EPA Project Updates: DSSTox and ToxCast Generating New Data and Data Linkages for Use in Predictive Modeling

EPA Science Inventory

EPAs National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than tr...

Development of an improved capability for predicting the response of highway bridges : final report.

DOT National Transportation Integrated Search

1986-01-01

This study compared experimental and analytical stress and deflection response of a simply-supported highway bridge as measured from a field test and as predicted from a finite-element analysis. The field test was conducted on one span of a six-span ...

Research on Nonlinear Time Series Forecasting of Time-Delay NN Embedded with Bayesian Regularization

NASA Astrophysics Data System (ADS)

Jiang, Weijin; Xu, Yusheng; Xu, Yuhui; Wang, Jianmin

Based on the idea of nonlinear prediction of phase space reconstruction, this paper presented a time delay BP neural network model, whose generalization capability was improved by Bayesian regularization. Furthermore, the model is applied to forecast the imp&exp trades in one industry. The results showed that the improved model has excellent generalization capabilities, which not only learned the historical curve, but efficiently predicted the trend of business. Comparing with common evaluation of forecasts, we put on a conclusion that nonlinear forecast can not only focus on data combination and precision improvement, it also can vividly reflect the nonlinear characteristic of the forecasting system. While analyzing the forecasting precision of the model, we give a model judgment by calculating the nonlinear characteristic value of the combined serial and original serial, proved that the forecasting model can reasonably 'catch' the dynamic characteristic of the nonlinear system which produced the origin serial.

Emerging CFD Capabilities and Outlook: A NASA Langley Perspective

NASA Technical Reports Server (NTRS)

Biedron, Robert T.; Pao, S. Paul; Thomas, James L.

2004-01-01

COMSAC goals include increasing the acceptance of CFD as a viable tool for S&C predictions, as well as to focus CFD development and improvement towards the needs of the S&C community. We view this as a symbiotic relationship, with increasing improvement of CFD promoting increasing acceptance by the S&C community, and increasing acceptance spurring further improvements. In this presentation we want to provide an overview for the non CFD expert of current CFD strengths and weaknesses, as well as to highlight a few emerging capabilities that we feel will lead toward increased usefulness in S&C applications.

Electrical test prediction using hybrid metrology and machine learning

NASA Astrophysics Data System (ADS)

Breton, Mary; Chao, Robin; Muthinti, Gangadhara Raja; de la Peña, Abraham A.; Simon, Jacques; Cepler, Aron J.; Sendelbach, Matthew; Gaudiello, John; Emans, Susan; Shifrin, Michael; Etzioni, Yoav; Urenski, Ronen; Lee, Wei Ti

2017-03-01

Electrical test measurement in the back-end of line (BEOL) is crucial for wafer and die sorting as well as comparing intended process splits. Any in-line, nondestructive technique in the process flow to accurately predict these measurements can significantly improve mean-time-to-detect (MTTD) of defects and improve cycle times for yield and process learning. Measuring after BEOL metallization is commonly done for process control and learning, particularly with scatterometry (also called OCD (Optical Critical Dimension)), which can solve for multiple profile parameters such as metal line height or sidewall angle and does so within patterned regions. This gives scatterometry an advantage over inline microscopy-based techniques, which provide top-down information, since such techniques can be insensitive to sidewall variations hidden under the metal fill of the trench. But when faced with correlation to electrical test measurements that are specific to the BEOL processing, both techniques face the additional challenge of sampling. Microscopy-based techniques are sampling-limited by their small probe size, while scatterometry is traditionally limited (for microprocessors) to scribe targets that mimic device ground rules but are not necessarily designed to be electrically testable. A solution to this sampling challenge lies in a fast reference-based machine learning capability that allows for OCD measurement directly of the electrically-testable structures, even when they are not OCD-compatible. By incorporating such direct OCD measurements, correlation to, and therefore prediction of, resistance of BEOL electrical test structures is significantly improved. Improvements in prediction capability for multiple types of in-die electrically-testable device structures is demonstrated. To further improve the quality of the prediction of the electrical resistance measurements, hybrid metrology using the OCD measurements as well as X-ray metrology (XRF) is used. Hybrid metrology is the practice of combining information from multiple sources in order to enable or improve the measurement of one or more critical parameters. Here, the XRF measurements are used to detect subtle changes in barrier layer composition and thickness that can have second-order effects on the electrical resistance of the test structures. By accounting for such effects with the aid of the X-ray-based measurements, further improvement in the OCD correlation to electrical test measurements is achieved. Using both types of solution incorporation of fast reference-based machine learning on nonOCD-compatible test structures, and hybrid metrology combining OCD with XRF technology improvement in BEOL cycle time learning could be accomplished through improved prediction capability.

High fidelity studies of exploding foil initiator bridges, Part 1: Experimental method

NASA Astrophysics Data System (ADS)

Bowden, Mike; Neal, William

2017-01-01

Simulations of high voltage detonators, such as Exploding Bridgewire (EBW) and Exploding Foil Initiators (EFI), have historically been simple, often empirical, one-dimensional models capable of predicting parameters such as current, voltage and in the case of EFIs, flyer velocity. Correspondingly, experimental methods have in general been limited to the same parameters. With the advent of complex, first principles magnetohydrodynamic codes such as ALEGRA and ALE-MHD, it is now possible to simulate these components in three dimensions, predicting a much greater range of parameters than before. A significant improvement in experimental capability was therefore required to ensure these simulations could be adequately validated. In this first paper of a three part study, the experimental method for determining the current, voltage, flyer velocity and multi-dimensional profile of detonator components is presented. This improved capability, along with high fidelity simulations, offer an opportunity to gain a greater understanding of the processes behind the functioning of EBW and EFI detonators.

Predictive Measures of Locomotor Performance on an Unstable Walking Surface

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Caldwell, E. E.; Batson, C. D.; De Dios, Y. E.; Gadd, N. E.; Goel, R.; Wood, S. J.; Cohen, H. S.;

Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance

USGS Publications Warehouse

Loman, Zachary G.; DeLuca, William; Harrison, Daniel J.; Loftin, Cynthia S.; Rolek, Brian W.; Wood, Petra B.

2018-01-01

ContextSpecies-specific models of landscape capability (LC) can inform landscape conservation design. Landscape capability is “the ability of the landscape to provide the environment […] and the local resources […] needed for survival and reproduction […] in sufficient quantity, quality and accessibility to meet the life history requirements of individuals and local populations.” Landscape capability incorporates species’ life histories, ecologies, and distributions to model habitat for current and future landscapes and climates as a proactive strategy for conservation planning.ObjectivesWe tested the ability of a set of LC models to explain variation in point occupancy and abundance for seven bird species representative of spruce-fir, mixed conifer-hardwood, and riparian and wooded wetland macrohabitats.MethodsWe compiled point count data sets used for biological inventory, species monitoring, and field studies across the northeastern United States to create an independent validation data set. Our validation explicitly accounted for underestimation in validation data using joint distance and time removal sampling.ResultsBlackpoll warbler (Setophaga striata), wood thrush (Hylocichla mustelina), and Louisiana (Parkesia motacilla) and northern waterthrush (P. noveboracensis) models were validated as predicting variation in abundance, although this varied from not biologically meaningful (1%) to strongly meaningful (59%). We verified all seven species models [including ovenbird (Seiurus aurocapilla), blackburnian (Setophaga fusca) and cerulean warbler (Setophaga cerulea)], as all were positively related to occupancy data.ConclusionsLC models represent a useful tool for conservation planning owing to their predictive ability over a regional extent. As improved remote-sensed data become available, LC layers are updated, which will improve predictions.

The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eden, H.F.; Mooers, C.N.K.

1990-06-01

The goal of COPS is to couple a program of regular observations to numerical models, through techniques of data assimilation, in order to provide a predictive capability for the US coastal ocean including the Great Lakes, estuaries, and the entire Exclusive Economic Zone (EEZ). The objectives of the program include: determining the predictability of the coastal ocean and the processes that govern the predictability; developing efficient prediction systems for the coastal ocean based on the assimilation of real-time observations into numerical models; and coupling the predictive systems for the physical behavior of the coastal ocean to predictive systems for biological,more » chemical, and geological processes to achieve an interdisciplinary capability. COPS will provide the basis for effective monitoring and prediction of coastal ocean conditions by optimizing the use of increased scientific understanding, improved observations, advanced computer models, and computer graphics to make the best possible estimates of sea level, currents, temperatures, salinities, and other properties of entire coastal regions.« less

Comprehensive Micromechanics-Analysis Code - Version 4.0

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Bednarcyk, B. A.

2005-01-01

Version 4.0 of the Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC) has been developed as an improved means of computational simulation of advanced composite materials. The previous version of MAC/GMC was described in "Comprehensive Micromechanics-Analysis Code" (LEW-16870), NASA Tech Briefs, Vol. 24, No. 6 (June 2000), page 38. To recapitulate: MAC/GMC is a computer program that predicts the elastic and inelastic thermomechanical responses of continuous and discontinuous composite materials with arbitrary internal microstructures and reinforcement shapes. The predictive capability of MAC/GMC rests on a model known as the generalized method of cells (GMC) - a continuum-based model of micromechanics that provides closed-form expressions for the macroscopic response of a composite material in terms of the properties, sizes, shapes, and responses of the individual constituents or phases that make up the material. Enhancements in version 4.0 include a capability for modeling thermomechanically and electromagnetically coupled ("smart") materials; a more-accurate (high-fidelity) version of the GMC; a capability to simulate discontinuous plies within a laminate; additional constitutive models of materials; expanded yield-surface-analysis capabilities; and expanded failure-analysis and life-prediction capabilities on both the microscopic and macroscopic scales.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nichols, T.

The Nuclear Forensics Analysis Center (NFAC) is part of Savannah River National Laboratory (SRNL) and is one of only two USG National Laboratories accredited to perform nuclear forensic analyses to the requirements of ISO 17025. SRNL NFAC is capable of analyzing nuclear and radiological samples from bulk material to ultra-trace samples. NFAC provides analytical support to the FBI's Radiological Evidence Examination Facility (REEF), which is located within SRNL. REEF gives the FBI the capability to perform traditional forensics on material that is radiological and/or is contaminated. SRNL is engaged in research and development efforts to improve the USG technical nuclearmore » forensics capabilities. Research includes improving predictive signatures and developing a database containing comparative samples.« less

A Research Program for Improving Heat Transfer Prediction Capability for the Laminar to Turbulent Transition Region of Turbine Vanes/Blades

NASA Technical Reports Server (NTRS)

Simon, Frederick F.

2007-01-01

A program sponsored by the National Aeronautics and Space Administration (NASA) for the investigation of the heat transfer in the transition region of turbine vanes and blades with the object of improving the capability for predicting heat transfer is described,. The accurate prediction of gas-side heat transfer is important to the determination of turbine longevity, engine performance and developmental costs. The need for accurate predictions will become greater as the operating temperatures and stage loading levels of advanced turbine engines increase. The present methods for predicting transition shear stress and heat transfer on turbine blades are based on incomplete knowledge and are largely empirical. To meet the objectives of the NASA program, a team approach consisting of researchers from government, universities, a research institute, and a small business is presented. The research is divided into areas of experimentation, direct numerical simulation (DNS) and turbulence modeling. A summary of the results to date is given for the above research areas in a high-disturbance environment (bypass transition) with a discussion of the model development necessary for use in numerical codes.

Environmental assessment for the Atmospheric Radiation Measurement (ARM) Program: Southern Great Plains Cloud and Radiation Testbed (CART) site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Policastro, A.J.; Pfingston, J.M.; Maloney, D.M.

The Atmospheric Radiation Measurement (ARM) Program is aimed at supplying improved predictive capability of climate change, particularly the prediction of cloud-climate feedback. The objective will be achieved by measuring the atmospheric radiation and physical and meteorological quantities that control solar radiation in the earth`s atmosphere and using this information to test global climate and related models. The proposed action is to construct and operate a Cloud and Radiation Testbed (CART) research site in the southern Great Plains as part of the Department of Energy`s Atmospheric Radiation Measurement Program whose objective is to develop an improved predictive capability of global climatemore » change. The purpose of this CART research site in southern Kansas and northern Oklahoma would be to collect meteorological and other scientific information to better characterize the processes controlling radiation transfer on a global scale. Impacts which could result from this facility are described.« less

Towards cheminformatics-based estimation of drug therapeutic index: Predicting the protective index of anticonvulsants using a new quantitative structure-index relationship approach.

PubMed

Chen, Shangying; Zhang, Peng; Liu, Xin; Qin, Chu; Tao, Lin; Zhang, Cheng; Yang, Sheng Yong; Chen, Yu Zong; Chui, Wai Keung

2016-06-01

The overall efficacy and safety profile of a new drug is partially evaluated by the therapeutic index in clinical studies and by the protective index (PI) in preclinical studies. In-silico predictive methods may facilitate the assessment of these indicators. Although QSAR and QSTR models can be used for predicting PI, their predictive capability has not been evaluated. To test this capability, we developed QSAR and QSTR models for predicting the activity and toxicity of anticonvulsants at accuracy levels above the literature-reported threshold (LT) of good QSAR models as tested by both the internal 5-fold cross validation and external validation method. These models showed significantly compromised PI predictive capability due to the cumulative errors of the QSAR and QSTR models. Therefore, in this investigation a new quantitative structure-index relationship (QSIR) model was devised and it showed improved PI predictive capability that superseded the LT of good QSAR models. The QSAR, QSTR and QSIR models were developed using support vector regression (SVR) method with the parameters optimized by using the greedy search method. The molecular descriptors relevant to the prediction of anticonvulsant activities, toxicities and PIs were analyzed by a recursive feature elimination method. The selected molecular descriptors are primarily associated with the drug-like, pharmacological and toxicological features and those used in the published anticonvulsant QSAR and QSTR models. This study suggested that QSIR is useful for estimating the therapeutic index of drug candidates. Copyright © 2016. Published by Elsevier Inc.

In silico prediction of pharmaceutical degradation pathways: a benchmarking study.

PubMed

Kleinman, Mark H; Baertschi, Steven W; Alsante, Karen M; Reid, Darren L; Mowery, Mark D; Shimanovich, Roman; Foti, Chris; Smith, William K; Reynolds, Dan W; Nefliu, Marcela; Ott, Martin A

2014-11-03

Zeneth is a new software application capable of predicting degradation products derived from small molecule active pharmaceutical ingredients. This study was aimed at understanding the current status of Zeneth's predictive capabilities and assessing gaps in predictivity. Using data from 27 small molecule drug substances from five pharmaceutical companies, the evolution of Zeneth predictions through knowledge base development since 2009 was evaluated. The experimentally observed degradation products from forced degradation, accelerated, and long-term stability studies were compared to Zeneth predictions. Steady progress in predictive performance was observed as the knowledge bases grew and were refined. Over the course of the development covered within this evaluation, the ability of Zeneth to predict experimentally observed degradants increased from 31% to 54%. In particular, gaps in predictivity were noted in the areas of epimerizations, N-dealkylation of N-alkylheteroaromatic compounds, photochemical decarboxylations, and electrocyclic reactions. The results of this study show that knowledge base development efforts have increased the ability of Zeneth to predict relevant degradation products and aid pharmaceutical research. This study has also provided valuable information to help guide further improvements to Zeneth and its knowledge base.

Improved UT1 Predictions through Low-Latency VLBI Observations

DTIC Science & Technology

2010-03-14

J Geod (2010) 84:399–402 DOI 10.1007/s00190-010-0372-8 SHORT NOTE Improved UT1 predictions through low-latency VLBI observations Brian Luzum · Axel...polar motion and nutation on UT1 determinations from VLBI Intensive obser- vations. J Geod 82(12):863. doi:10.1007/s00190-008-0212-2 Ray JR, Carter WE...Behrend D (2007) The International VLBI Service for Geodesy and Astrometry (IVS): current capabilities and future prospects. J Geod 81(6–8):479. doi

NASA Tools for Climate Impacts on Water Resources

NASA Technical Reports Server (NTRS)

Toll, David; Doorn, Brad

2010-01-01

Climate and environmental change are expected to fundamentally alter the nation's hydrological cycle and water availability. Satellites provide global or near-global coverage using instruments, allowing for consistent, well-calibrated, and equivalent-quality data of the Earth system. A major goal for NASA climate and environmental change research is to create multi-instrument data sets to span the multi-decadal time scales of climate change and to combine these data with those from modeling and surface-based observing systems to improve process understanding and predictions. NASA and Earth science data and analyses will ultimately enable more accurate climate prediction, and characterization of uncertainties. NASA's Applied Sciences Program works with other groups, including other federal agencies, to transition demonstrated observational capabilities to operational capabilities. A summary of some of NASA tools for improved water resources management will be presented.

Predicting forest attributes from climate data using a recursive partitioning and regression tree algorithm

Treesearch

Greg C. Liknes; Christopher W. Woodall; Charles H. Perry

2009-01-01

Climate information frequently is included in geospatial modeling efforts to improve the predictive capability of other data sources. The selection of an appropriate climate data source requires consideration given the number of choices available. With regard to climate data, there are a variety of parameters (e.g., temperature, humidity, precipitation), time intervals...

Thermal niche estimators and the capability of poor dispersal species to cope with climate change

NASA Astrophysics Data System (ADS)

Sánchez-Fernández, David; Rizzo, Valeria; Cieslak, Alexandra; Faille, Arnaud; Fresneda, Javier; Ribera, Ignacio

2016-03-01

For management strategies in the context of global warming, accurate predictions of species response are mandatory. However, to date most predictions are based on niche (bioclimatic) models that usually overlook biotic interactions, behavioral adjustments or adaptive evolution, and assume that species can disperse freely without constraints. The deep subterranean environment minimises these uncertainties, as it is simple, homogeneous and with constant environmental conditions. It is thus an ideal model system to study the effect of global change in species with poor dispersal capabilities. We assess the potential fate of a lineage of troglobitic beetles under global change predictions using different approaches to estimate their thermal niche: bioclimatic models, rates of thermal niche change estimated from a molecular phylogeny, and data from physiological studies. Using bioclimatic models, at most 60% of the species were predicted to have suitable conditions in 2080. Considering the rates of thermal niche change did not improve this prediction. However, physiological data suggest that subterranean species have a broad thermal tolerance, allowing them to stand temperatures never experienced through their evolutionary history. These results stress the need of experimental approaches to assess the capability of poor dispersal species to cope with temperatures outside those they currently experience.

WEB-DHM: A distributed biosphere hydrological model developed by coupling a simple biosphere scheme with a hillslope hydrological model

USDA-ARS?s Scientific Manuscript database

The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...

Fan Noise Prediction with Applications to Aircraft System Noise Assessment

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Envia, Edmane; Burley, Casey L.

2009-01-01

This paper describes an assessment of current fan noise prediction tools by comparing measured and predicted sideline acoustic levels from a benchmark fan noise wind tunnel test. Specifically, an empirical method and newly developed coupled computational approach are utilized to predict aft fan noise for a benchmark test configuration. Comparisons with sideline noise measurements are performed to assess the relative merits of the two approaches. The study identifies issues entailed in coupling the source and propagation codes, as well as provides insight into the capabilities of the tools in predicting the fan noise source and subsequent propagation and radiation. In contrast to the empirical method, the new coupled computational approach provides the ability to investigate acoustic near-field effects. The potential benefits/costs of these new methods are also compared with the existing capabilities in a current aircraft noise system prediction tool. The knowledge gained in this work provides a basis for improved fan source specification in overall aircraft system noise studies.

Shuttle TPS thermal performance and analysis methodology

NASA Technical Reports Server (NTRS)

Neuenschwander, W. E.; Mcbride, D. U.; Armour, G. A.

1983-01-01

Thermal performance of the thermal protection system was approximately as predicted. The only extensive anomalies were filler bar scorching and over-predictions in the high Delta p gap heating regions of the orbiter. A technique to predict filler bar scorching has been developed that can aid in defining a solution. Improvement in high Delta p gap heating methodology is still under study. Minor anomalies were also examined for improvements in modeling techniques and prediction capabilities. These include improved definition of low Delta p gap heating, an analytical model for inner mode line convection heat transfer, better modeling of structure, and inclusion of sneak heating. The limited number of problems related to penetration items that presented themselves during orbital flight tests were resolved expeditiously, and designs were changed and proved successful within the time frame of that program.

Predicting Great Lakes fish yields: tools and constraints

USGS Publications Warehouse

Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

1987-01-01

Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

Earth Science System of the Future: Observing, Processing, and Delivering Data Products Directly to Users

NASA Technical Reports Server (NTRS)

Crisp, David; Komar, George (Technical Monitor)

2001-01-01

Advancement of our predictive capabilities will require new scientific knowledge, improvement of our modeling capabilities, and new observation strategies to generate the complex data sets needed by coupled modeling networks. New observation strategies must support remote sensing from a variety of vantage points and will include "sensorwebs" of small satellites in low Earth orbit, large aperture sensors in Geostationary orbits, and sentinel satellites at L1 and L2 to provide day/night views of the entire globe. Onboard data processing and high speed computing and communications will enable near real-time tailoring and delivery of information products (i.e., predictions) directly to users.

Defense Acquisitions: Assessments of Selected Weapon Programs

DTIC Science & Technology

2010-03-01

improved availability for small terminals. It is to replace the Ultra High Frequency (UHF) Follow-On ( UFO ) satellite system currently in operation...of MUOS capabilities is time-critical due to the operational failures of two UFO satellites. The MUOS program has taken several steps to address...failures of two UFO satellites. Based on the current health of on-orbit satellites, UHF communication capabilities are predicted to fall below the

Spacecraft Charging and Auroral Boundary Predictions in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Minow, Joseph I.

2016-01-01

Auroral charging of spacecraft is an important class of space weather impacts on technological systems in low Earth orbit. In order for space weather models to accurately specify auroral charging environments, they must provide the appropriate plasma environment characteristics responsible for charging. Improvements in operational space weather prediction capabilities relevant to charging must be tested against charging observations.

Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

DTIC Science & Technology

2016-03-15

mutants hisC1 (PA4447), hisD (PA4448), hutH (PA5098), and PA0006. We predicted that uro - canate was depleted in these high biofilm-producing mutants and...Lam DK, Fleming L, Lo R, Whiteside MD, Yu NY, et al. PseudomonasGenome Database: improved comparative analysis and population genomics capability for

Modeling for Policy Change: A Feedback Perspective on Improving the Effectiveness of Coastal and Marine Management

ERIC Educational Resources Information Center

Robadue, Donald D., Jr.

2012-01-01

Those advocating for effective management of the use of coastal areas and ecosystems have long aspired for an approach to governance that includes information systems with the capability to predict the end results of various courses of action, monitor the impacts of decisions and compare results with those predicted by computer models in order to…

The Drought Task Force and Research on Understanding, Predicting, and Monitoring Drought

NASA Astrophysics Data System (ADS)

Barrie, D.; Mariotti, A.; Archambault, H. M.; Hoerling, M. P.; Wood, E. F.; Koster, R. D.; Svoboda, M.

2016-12-01

Drought has caused serious social and economic impacts throughout the history of the United States. All Americans are susceptible to the direct and indirect threats drought poses to the Nation. Drought challenges agricultural productivity and reduces the quantity and quality of drinking water supplies upon which communities and industries depend. Drought jeopardizes the integrity of critical infrastructure, causes extensive economic and health impacts, harms ecosystems, and increases energy costs. Ensuring the availability of clean, sufficient, and reliable water resources is a top national and NOAA priority. The Climate Program Office's Modeling, Analysis, Predictions, and Projections (MAPP) program, in partnership with the NOAA-led National Integrated Drought Information System (NIDIS), is focused on improving our understanding of drought causes, evolution, amelioration, and impacts as well as improving our capability to monitor and predict drought. These capabilities and knowledge are critical to providing communities with actionable, reliable information to increase drought preparedness and resilience. This poster will present information on the MAPP-organized Drought Task Force, a consortium of investigators funded by the MAPP program in partnership with NIDIS to advance drought understanding, monitoring, and prediction. Information on Task Force activities, products, and MAPP drought initiatives will be described in the poster, including the Task Force's ongoing focus on the California drought, its predictability, and its causes.

Recent developments in analysis of crack propagation and fracture of practical materials. [stress analysis in aircraft structures

NASA Technical Reports Server (NTRS)

Hardrath, H. F.; Newman, J. C., Jr.; Elber, W.; Poe, C. C., Jr.

1978-01-01

The limitations of linear elastic fracture mechanics in aircraft design and in the study of fatigue crack propagation in aircraft structures are discussed. NASA-Langley research to extend the capabilities of fracture mechanics to predict the maximum load that can be carried by a cracked part and to deal with aircraft design problems are reported. Achievements include: (1) improved stress intensity solutions for laboratory specimens; (2) fracture criterion for practical materials; (3) crack propagation predictions that account for mean stress and high maximum stress effects; (4) crack propagation predictions for variable amplitude loading; and (5) the prediction of crack growth and residual stress in built-up structural assemblies. These capabilities are incorporated into a first generation computerized analysis that allows for damage tolerance and tradeoffs with other disciplines to produce efficient designs that meet current airworthiness requirements.

Extreme-Scale Computing Project Aims to Advance Precision Oncology | FNLCR Staging

Cancer.gov

Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict dru

Thermal niche estimators and the capability of poor dispersal species to cope with climate change

PubMed Central

Sánchez-Fernández, David; Rizzo, Valeria; Cieslak, Alexandra; Faille, Arnaud; Fresneda, Javier; Ribera, Ignacio

2016-01-01

For management strategies in the context of global warming, accurate predictions of species response are mandatory. However, to date most predictions are based on niche (bioclimatic) models that usually overlook biotic interactions, behavioral adjustments or adaptive evolution, and assume that species can disperse freely without constraints. The deep subterranean environment minimises these uncertainties, as it is simple, homogeneous and with constant environmental conditions. It is thus an ideal model system to study the effect of global change in species with poor dispersal capabilities. We assess the potential fate of a lineage of troglobitic beetles under global change predictions using different approaches to estimate their thermal niche: bioclimatic models, rates of thermal niche change estimated from a molecular phylogeny, and data from physiological studies. Using bioclimatic models, at most 60% of the species were predicted to have suitable conditions in 2080. Considering the rates of thermal niche change did not improve this prediction. However, physiological data suggest that subterranean species have a broad thermal tolerance, allowing them to stand temperatures never experienced through their evolutionary history. These results stress the need of experimental approaches to assess the capability of poor dispersal species to cope with temperatures outside those they currently experience. PMID:26983802

NASA's Evolutionary Xenon Thruster (NEXT) Project Qualification Propellant Throughput Milestone: Performance, Erosion, and Thruster Service Life Prediction After 450 kg

NASA Technical Reports Server (NTRS)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 28,500 hr of operation and processed 466 kg of xenon throughput--more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Is the First-Year Predictive for Study Success in Subsequent Years? Findings from an Academy of Music

ERIC Educational Resources Information Center

Mennen, Josien; van der Klink, Marcel

2017-01-01

In higher education, departments are under increasing pressure to improve study success. Research in this field focusing on higher music education is scarce. The aim of this study was to gain insight into the predictive capability of the first year for study success of students at an academy of music in subsequent years. Data on study progression…

Off-Gas Adsorption Model Capabilities and Recommendations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lyon, Kevin L.; Welty, Amy K.; Law, Jack

2016-03-01

Off-gas treatment is required to reduce emissions from aqueous fuel reprocessing. Evaluating the products of innovative gas adsorption research requires increased computational simulation capability to more effectively transition from fundamental research to operational design. Early modeling efforts produced the Off-Gas SeParation and REcoverY (OSPREY) model that, while efficient in terms of computation time, was of limited value for complex systems. However, the computational and programming lessons learned in development of the initial model were used to develop Discontinuous Galerkin OSPREY (DGOSPREY), a more effective model. Initial comparisons between OSPREY and DGOSPREY show that, while OSPREY does reasonably well to capturemore » the initial breakthrough time, it displays far too much numerical dispersion to accurately capture the real shape of the breakthrough curves. DGOSPREY is a much better tool as it utilizes a more stable set of numerical methods. In addition, DGOSPREY has shown the capability to capture complex, multispecies adsorption behavior, while OSPREY currently only works for a single adsorbing species. This capability makes DGOSPREY ultimately a more practical tool for real world simulations involving many different gas species. While DGOSPREY has initially performed very well, there is still need for improvement. The current state of DGOSPREY does not include any micro-scale adsorption kinetics and therefore assumes instantaneous adsorption. This is a major source of error in predicting water vapor breakthrough because the kinetics of that adsorption mechanism is particularly slow. However, this deficiency can be remedied by building kinetic kernels into DGOSPREY. Another source of error in DGOSPREY stems from data gaps in single species, such as Kr and Xe, isotherms. Since isotherm data for each gas is currently available at a single temperature, the model is unable to predict adsorption at temperatures outside of the set of data currently available. Thus, in order to improve the predictive capabilities of the model, there is a need for more single-species adsorption isotherms at different temperatures, in addition to extending the model to include adsorption kinetics. This report provides background information about the modeling process and a path forward for further model improvement in terms of accuracy and user interface.« less

Prediction of Agglomeration, Fouling, and Corrosion Tendency of Fuels in CFB Co-Combustion

NASA Astrophysics Data System (ADS)

Barišć, Vesna; Zabetta, Edgardo Coda; Sarkki, Juha

Prediction of agglomeration, fouling, and corrosion tendency of fuels is essential to the design of any CFB boiler. During the years, tools have been successfully developed at Foster Wheeler to help with such predictions for the most commercial fuels. However, changes in fuel market and the ever-growing demand for co-combustion capabilities pose a continuous need for development. This paper presents results from recently upgraded models used at Foster Wheeler to predict agglomeration, fouling, and corrosion tendency of a variety of fuels and mixtures. The models, subject of this paper, are semi-empirical computer tools that combine the theoretical basics of agglomeration/fouling/corrosion phenomena with empirical correlations. Correlations are derived from Foster Wheeler's experience in fluidized beds, including nearly 10,000 fuel samples and over 1,000 tests in about 150 CFB units. In these models, fuels are evaluated based on their classification, their chemical and physical properties by standard analyses (proximate, ultimate, fuel ash composition, etc.;.) alongside with Foster Wheeler own characterization methods. Mixtures are then evaluated taking into account the component fuels. This paper presents the predictive capabilities of the agglomeration/fouling/corrosion probability models for selected fuels and mixtures fired in full-scale. The selected fuels include coals and different types of biomass. The models are capable to predict the behavior of most fuels and mixtures, but also offer possibilities for further improvements.

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

NASA Technical Reports Server (NTRS)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

A Coupled Surface Nudging Scheme for use in Retrospective ...

EPA Pesticide Factsheets

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem modeling. This scheme is known as the flux-adjusting surface data assimilation system (FASDAS) developed by Alapaty et al. (2008). This scheme provides continuous adjustments for soil moisture and temperature (via indirect nudging) and for surface air temperature and water vapor mixing ratio (via direct nudging). The simultaneous application of indirect and direct nudging maintains greater consistency between the soil temperature–moisture and the atmospheric surface layer mass-field variables. The new method, FASDAS, consistently improved the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as well as for high resolution regional climate predictions. This new capability has been released in WRF Version 3.8 as option grid_sfdda = 2. This new capability increased the accuracy of atmospheric inputs for use air quality, hydrology, and ecosystem modeling research to improve the accuracy of respective end-point research outcome. IMPACT: A new method, FASDAS, was implemented into the WRF model to consistently improve the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as wel

Suicide, hopelessness, and social desirability: a test of an interactive model.

PubMed

Holden, R R; Mendonca, J D; Serin, R C

1989-08-01

We examined the relationships among suicidal indices, hopelessness, and social desirability. Both hopelessness and a measure of social desirability that reflected a sense of general capability were significant indicators of suicidal manifestations. In particular, hierarchical multiple regression procedures demonstrated that hopelessness and social desirability interacted in the prediction of suicide variables. Results generalized across various clinical diagnostic subgroups of psychiatric patients and a sample of prisoners and across different clinically evaluated and self-reported indices of suicidal behavior. Findings are interpreted to mean that a sense of general capability buffers the link of hopelessness to suicidal behavior. Implications for understanding the cognitions associated with suicide and for improving prediction of persons at risk are discussed.

KSC-2015-1130

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is mated to its Delta II rocket at Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1129

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is mated to its Delta II rocket at Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1109

NASA Image and Video Library

2015-01-08

VANDENBERG AIR FORCE BASE, Calif. – Inside the Astrotech payload processing facility at Vandenberg Air Force Base in California, engineers and technicians inspect NASA's Soil Moisture Active Passive mission, or SMAP, satellite. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: Jeremy Moore, USAF Photo Squadron

KSC-2015-1111

NASA Image and Video Library

2015-01-08

VANDENBERG AIR FORCE BASE, Calif. – Inside the Astrotech payload processing facility at Vandenberg Air Force Base in California, engineers and technicians inspect NASA's Soil Moisture Active Passive mission, or SMAP, satellite. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: Jeremy Moore, USAF Photo Squadron

KSC-2015-1128

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is mated to its Delta II rocket at Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

Study on new energy development planning and absorptive capability of Xinjiang in China considering resource characteristics and demand prediction

NASA Astrophysics Data System (ADS)

Shao, Hai; Miao, Xujuan; Liu, Jinpeng; Wu, Meng; Zhao, Xuehua

2018-02-01

Xinjiang, as the area where wind energy and solar energy resources are extremely rich, with good resource development characteristics, can provide a support for regional power development and supply protection. This paper systematically analyzes the new energy resource and development characteristics of Xinjiang and carries out the demand prediction and excavation of load characteristics of Xinjiang power market. Combing the development plan of new energy of Xinjiang and considering the construction of transmission channel, it analyzes the absorptive capability of new energy. It provides certain reference for the comprehensive planning of new energy development in Xinjiang and the improvement of absorptive capacity of new energy.

Route Prediction on Tracking Data to Location-Based Services

NASA Astrophysics Data System (ADS)

Petróczi, Attila István; Gáspár-Papanek, Csaba

Wireless networks have become so widespread, it is beneficial to determine the ability of cellular networks for localization. This property enables the development of location-based services, providing useful information. These services can be improved by route prediction under the condition of using simple algorithms, because of the limited capabilities of mobile stations. This study gives alternative solutions for this problem of route prediction based on a specific graph model. Our models provide the opportunity to reach our destinations with less effort.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinilla, Maria Isabel

This report seeks to study and benchmark code predictions against experimental data; determine parameters to match MCNP-simulated detector response functions to experimental stilbene measurements; add stilbene processing capabilities to DRiFT; and improve NEUANCE detector array modeling and analysis using new MCNP6 and DRiFT features.

Extreme-Scale Computing Project Aims to Advance Precision Oncology | Frederick National Laboratory for Cancer Research

Cancer.gov

Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict dru

New Toxico-Cheminformatics & Computational Toxicology Initiatives At EPA

EPA Science Inventory

EPA’s National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than tr...

A subjective evaluation of synthesized STOL airplane noises

NASA Technical Reports Server (NTRS)

Powell, C. A., Jr.

1973-01-01

A magnitude-estimation experiment was conducted to evaluate the subjective annoyance of the noise generated by possible future turbofan STOL aircraft as compared to that of several current CTOL aircraft. In addition, some of the units used to scale the magnitude of aircraft noise were evaluated with respect to their applicability to STOL noise. Twenty test subjects rated their annoyance to a total of 119 noises over a range of 75 PNdb to 105 PNdb. Their subjective ratings were compared with acoustical analysis of the noises in terms of 28 rating scale units. The synthesized STOL noises of this experiment were found to be slightly more annoying than the conventional CTOL noises at equal levels of PNL and EPNL. Over the range of levels investigated the scaling units, with a few exceptions, were capable of predicting the points of equal annoyance for all of the noises with plus or minus 3 dB. The inclusion of duration corrections, in general, improved the predictive capabilities of the various scaling units; however, tone corrections reduced their predictive capabilities.

Identification of potential compensatory muscle strategies in a breast cancer survivor population: A combined computational and experimental approach.

PubMed

Chopp-Hurley, Jaclyn N; Brookham, Rebecca L; Dickerson, Clark R

2016-12-01

Biomechanical models are often used to estimate the muscular demands of various activities. However, specific muscle dysfunctions typical of unique clinical populations are rarely considered. Due to iatrogenic tissue damage, pectoralis major capability is markedly reduced in breast cancer population survivors, which could influence arm internal and external rotation muscular strategies. Accordingly, an optimization-based muscle force prediction model was systematically modified to emulate breast cancer population survivors through adjusting pectoralis capability and enforcing an empirical muscular co-activation relationship. Model permutations were evaluated through comparisons between predicted muscle forces and empirically measured muscle activations in survivors. Similarities between empirical data and model outputs were influenced by muscle type, hand force, pectoralis major capability and co-activation constraints. Differences in magnitude were lower when the co-activation constraint was enforced (-18.4% [31.9]) than unenforced (-23.5% [27.6]) (p<0.0001). This research demonstrates that muscle dysfunction in breast cancer population survivors can be reflected through including a capability constraint for pectoralis major. Further refinement of the co-activation constraint for survivors could improve its generalizability across this population and activities. Improving biomechanical models to more accurately represent clinical populations can provide novel information that can help in the development of optimal treatment programs for breast cancer population survivors. Copyright © 2016 Elsevier Ltd. All rights reserved.

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

PubMed

Yu, Nancy Y; Wagner, James R; Laird, Matthew R; Melli, Gabor; Rey, Sébastien; Lo, Raymond; Dao, Phuong; Sahinalp, S Cenk; Ester, Martin; Foster, Leonard J; Brinkman, Fiona S L

2010-07-01

PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. http://www.psort.org/psortb (download open source software or use the web interface). psort-mail@sfu.ca Supplementary data are available at Bioinformatics online.

Improvements to Integrated Tradespace Analysis of Communications Architectures (ITACA) Network Loading Analysis Tool

NASA Technical Reports Server (NTRS)

Lee, Nathaniel; Welch, Bryan W.

2018-01-01

NASA's SCENIC project aims to simplify and reduce the cost of space mission planning by replicating the analysis capabilities of commercially licensed software which are integrated with relevant analysis parameters specific to SCaN assets and SCaN supported user missions. SCENIC differs from current tools that perform similar analyses in that it 1) does not require any licensing fees, 2) will provide an all-in-one package for various analysis capabilities that normally requires add-ons or multiple tools to complete. As part of SCENIC's capabilities, the ITACA network loading analysis tool will be responsible for assessing the loading on a given network architecture and generating a network service schedule. ITACA will allow users to evaluate the quality of service of a given network architecture and determine whether or not the architecture will satisfy the mission's requirements. ITACA is currently under development, and the following improvements were made during the fall of 2017: optimization of runtime, augmentation of network asset pre-service configuration time, augmentation of Brent's method of root finding, augmentation of network asset FOV restrictions, augmentation of mission lifetimes, and the integration of a SCaN link budget calculation tool. The improvements resulted in (a) 25% reduction in runtime, (b) more accurate contact window predictions when compared to STK(Registered Trademark) contact window predictions, and (c) increased fidelity through the use of specific SCaN asset parameters.

The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction

NASA Astrophysics Data System (ADS)

Kunnath-Poovakka, A.; Ryu, D.; Renzullo, L. J.; George, B.

2016-04-01

Calibration of spatially distributed hydrologic models is frequently limited by the availability of ground observations. Remotely sensed (RS) hydrologic information provides an alternative source of observations to inform models and extend modelling capability beyond the limits of ground observations. This study examines the capability of RS evapotranspiration (ET) and soil moisture (SM) in calibrating a hydrologic model and its efficacy to improve streamflow predictions. SM retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and daily ET estimates from the CSIRO MODIS ReScaled potential ET (CMRSET) are used to calibrate a simplified Australian Water Resource Assessment - Landscape model (AWRA-L) for a selection of parameters. The Shuffled Complex Evolution Uncertainty Algorithm (SCE-UA) is employed for parameter estimation at eleven catchments in eastern Australia. A subset of parameters for calibration is selected based on the variance-based Sobol' sensitivity analysis. The efficacy of 15 objective functions for calibration is assessed based on streamflow predictions relative to control cases, and relative merits of each are discussed. Synthetic experiments were conducted to examine the effect of bias in RS ET observations on calibration. The objective function containing the root mean square deviation (RMSD) of ET result in best streamflow predictions and the efficacy is superior for catchments with medium to high average runoff. Synthetic experiments revealed that accurate ET product can improve the streamflow predictions in catchments with low average runoff.

Plant water potential improves prediction of empirical stomatal models.

PubMed

Anderegg, William R L; Wolf, Adam; Arango-Velez, Adriana; Choat, Brendan; Chmura, Daniel J; Jansen, Steven; Kolb, Thomas; Li, Shan; Meinzer, Frederick; Pita, Pilar; Resco de Dios, Víctor; Sperry, John S; Wolfe, Brett T; Pacala, Stephen

2017-01-01

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.

FireStem2D — A two-dimensional heat transfer model for simulating tree stem injury in fires

Treesearch

Efthalia K. Chatziefstratiou; Gil Bohrer; Anthony S. Bova; Ravishankar Subramanian; Renato P.M. Frasson; Amy Scherzer; Bret W. Butler; Matthew B. Dickinson

2013-01-01

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by...

Modeling the Malaysian motor insurance claim using artificial neural network and adaptive NeuroFuzzy inference system

NASA Astrophysics Data System (ADS)

Mohd Yunos, Zuriahati; Shamsuddin, Siti Mariyam; Ismail, Noriszura; Sallehuddin, Roselina

2013-04-01

Artificial neural network (ANN) with back propagation algorithm (BP) and ANFIS was chosen as an alternative technique in modeling motor insurance claims. In particular, an ANN and ANFIS technique is applied to model and forecast the Malaysian motor insurance data which is categorized into four claim types; third party property damage (TPPD), third party bodily injury (TPBI), own damage (OD) and theft. This study is to determine whether an ANN and ANFIS model is capable of accurately predicting motor insurance claim. There were changes made to the network structure as the number of input nodes, number of hidden nodes and pre-processing techniques are also examined and a cross-validation technique is used to improve the generalization ability of ANN and ANFIS models. Based on the empirical studies, the prediction performance of the ANN and ANFIS model is improved by using different number of input nodes and hidden nodes; and also various sizes of data. The experimental results reveal that the ANFIS model has outperformed the ANN model. Both models are capable of producing a reliable prediction for the Malaysian motor insurance claims and hence, the proposed method can be applied as an alternative to predict claim frequency and claim severity.

Species Diversity and Functional Prediction of Surface Bacterial Communities on Aging Flue-Cured Tobaccos.

PubMed

Wang, Fan; Zhao, Hongwei; Xiang, Haiying; Wu, Lijun; Men, Xiao; Qi, Chang; Chen, Guoqiang; Zhang, Haibo; Wang, Yi; Xian, Mo

2018-06-05

Microbes on aging flue-cured tobaccos (ATFs) improve the aroma and other qualities desirable in products. Understanding the relevant organisms would picture microbial community diversity, metabolic potential, and their applications. However, limited efforts have been made on characterizing the microbial quality and functional profiling. Herein, we present our investigation of the bacterial diversity and predicted potential genetic capability of the bacteria from two AFTs using 16S rRNA gene sequences and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) software. The results show that dominant bacteria from AFT surfaces were classified into 48 genera, 36 families, and 7 phyla. In addition, Bacillus spp. was found prevalent on both ATFs. Furthermore, PICRUSt predictions of bacterial community functions revealed many attractive metabolic capacities in the AFT microbiota, including several involved in the biosynthesis of flavors and fragrances and the degradation of harmful compounds, such as nicotine and nitrite. These results provide insights into the importance of AFT bacteria in determining product qualities and indicate specific microbial species with predicted enzymatic capabilities for the production of high-efficiency flavors, the degradation of undesirable compounds, and the provision of nicotine and nitrite tolerance which suggest fruitful areas of investigation into the manipulation of AFT microbiota for AFT and other product improvements.

Development and Application of Advanced Weather Prediction Technologies for the Wind Energy Industry (Invited)

NASA Astrophysics Data System (ADS)

Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.

2010-12-01

Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on individual wind turbines. The information is utilized by several technologies including: a) the Weather Research and Forecasting (WRF) model, which generates finely detailed simulations of future atmospheric conditions, b) the Real-Time Four-Dimensional Data Assimilation System (RTFDDA), which performs continuous data assimilation providing the WRF model with continuous updates of the initial atmospheric state, 3) the Dynamic Integrated Forecast System (DICast®), which statistically optimizes the forecasts using all predictors, and 4) a suite of wind-to-power algorithms that convert wind speed to power for a wide range of wind farms with varying real-time data availability capabilities. In addition to these core wind energy prediction capabilities, NCAR implemented a high-resolution (10 km grid increment) 30-member ensemble RTFDDA prediction system that provides information on the expected range of wind power over a 72-hour forecast period covering Xcel Energy’s service areas. This talk will include descriptions of these capabilities and report on several topics including initial results of next-day forecasts and nowcasts of wind energy ramp events, influence of local observations on forecast skill, and overall lessons learned to date.

Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks.

PubMed

Chande, Ruchi D; Hargraves, Rosalyn Hobson; Ortiz-Robinson, Norma; Wayne, Jennifer S

2017-01-01

Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

Transonic cascade flow prediction using the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Arnone, A.; Stecco, S. S.

1991-01-01

This paper presents results which summarize the work carried out during the last three years to improve the efficiency and accuracy of numerical predictions in turbomachinery flow calculations. A new kind of nonperiodic c-type grid is presented and a Runge-Kutta scheme with accelerating strategies is used as a flow solver. The code capability is presented by testing four different blades at different exit Mach numbers in transonic regimes. Comparison with experiments shows the very good reliability of the numerical prediction. In particular, the loss coefficient seems to be correctly predicted by using the well-known Baldwin-Lomax turbulence model.

The NASA Seasonal-to-Interannual Prediction Project (NSIPP). [Annual Report for 2000

NASA Technical Reports Server (NTRS)

Rienecker, Michele; Suarez, Max; Adamec, David; Koster, Randal; Schubert, Siegfried; Hansen, James; Koblinsky, Chester (Technical Monitor)

2001-01-01

The goal of the project is to develop an assimilation and forecast system based on a coupled atmosphere-ocean-land-surface-sea-ice model capable of using a combination of satellite and in situ data sources to improve the prediction of ENSO and other major S-I signals and their global teleconnections. The objectives of this annual report are to: (1) demonstrate the utility of satellite data, especially surface height surface winds, air-sea fluxes and soil moisture, in a coupled model prediction system; and (2) aid in the design of the observing system for short-term climate prediction by conducting OSSE's and predictability studies.

Simulating boundary layer transition with low-Reynolds-number k-epsilon turbulence models. I - An evaluation of prediction characteristics. II - An approach to improving the predictions

NASA Technical Reports Server (NTRS)

Schmidt, R. C.; Patankar, S. V.

1991-01-01

The capability of two k-epsilon low-Reynolds number (LRN) turbulence models, those of Jones and Launder (1972) and Lam and Bremhorst (1981), to predict transition in external boundary-layer flows subject to free-stream turbulence is analyzed. Both models correctly predict the basic qualitative aspects of boundary-layer transition with free stream turbulence, but for calculations started at low values of certain defined Reynolds numbers, the transition is generally predicted at unrealistically early locations. Also, the methods predict transition lengths significantly shorter than those found experimentally. An approach to overcoming these deficiencies without abandoning the basic LRN k-epsilon framework is developed. This approach limits the production term in the turbulent kinetic energy equation and is based on a simple stability criterion. It is correlated to the free-stream turbulence value. The modification is shown to improve the qualitative and quantitative characteristics of the transition predictions.

Assessment of NASA's Aircraft Noise Prediction Capability

NASA Technical Reports Server (NTRS)

Dahl, Milo D. (Editor)

2012-01-01

A goal of NASA s Fundamental Aeronautics Program is the improvement of aircraft noise prediction. This document provides an assessment, conducted from 2006 to 2009, on the current state of the art for aircraft noise prediction by carefully analyzing the results from prediction tools and from the experimental databases to determine errors and uncertainties and compare results to validate the predictions. The error analysis is included for both the predictions and the experimental data and helps identify where improvements are required. This study is restricted to prediction methods and databases developed or sponsored by NASA, although in many cases they represent the current state of the art for industry. The present document begins with an introduction giving a general background for and a discussion on the process of this assessment followed by eight chapters covering topics at both the system and the component levels. The topic areas, each with multiple contributors, are aircraft system noise, engine system noise, airframe noise, fan noise, liner physics, duct acoustics, jet noise, and propulsion airframe aeroacoustics.

Modeling the prediction of business intelligence system effectiveness.

PubMed

Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

2016-01-01

Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

Predictive Capability Maturity Model for computational modeling and simulation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

2007-10-01

The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronauticsmore » and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.« less

9-Ft By 7-Ft Supersonic Wind Tunnel Nozzle Improvement Study

NASA Technical Reports Server (NTRS)

Paciano, Eric N.

2014-01-01

Engineers at the Unitary Plan Wind Tunnel at NASA Ames Research Center have recently embarked on a project focused on improving flow quality and tunnel capabilities in the 9-ft by 7-ft supersonic wind tunnel. Collaborating with Jacobs Tech Group, the project has explored potential improvements to the nozzle design using computational fluid dynamics. Preliminary predictions suggest changes to the nozzle design could significantly improve flow quality at the lower operating range (M1.5-1.8), however potential improvements in the upper operating range have yet to be realized.

Method to predict external store carriage characteristics at transonic speeds

NASA Technical Reports Server (NTRS)

Rosen, Bruce S.

1988-01-01

Development of a computational method for prediction of external store carriage characteristics at transonic speeds is described. The geometric flexibility required for treatment of pylon-mounted stores is achieved by computing finite difference solutions on a five-level embedded grid arrangement. A completely automated grid generation procedure facilitates applications. Store modeling capability consists of bodies of revolution with multiple fore and aft fins. A body-conforming grid improves the accuracy of the computed store body flow field. A nonlinear relaxation scheme developed specifically for modified transonic small disturbance flow equations enhances the method's numerical stability and accuracy. As a result, treatment of lower aspect ratio, more highly swept and tapered wings is possible. A limited supersonic freestream capability is also provided. Pressure, load distribution, and force/moment correlations show good agreement with experimental data for several test cases. A detailed computer program description for the Transonic Store Carriage Loads Prediction (TSCLP) Code is included.

Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

PubMed Central

Yang, Yuedong; Gao, Jianzhao; Wang, Jihua; Heffernan, Rhys; Hanson, Jack; Paliwal, Kuldip; Zhou, Yaoqi

2018-01-01

Abstract Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new methods breathe new life into this field. The highest three-state accuracy without relying on structure templates is now at 82–84%, a number unthinkable just a few years ago. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. As we are approaching to the theoretical limit of three-state prediction (88–90%), alternative to secondary structure prediction (prediction of backbone torsion angles and Cα-atom-based angles and torsion angles) not only has more room for further improvement but also allows direct prediction of three-dimensional fragment structures with constantly improved accuracy. About 20% of all 40-residue fragments in a database of 1199 non-redundant proteins have <6 Å root-mean-squared distance from the native conformations by SPIDER2. More powerful deep learning methods with improved capability of capturing long-range interactions begin to emerge as the next generation of techniques for secondary structure prediction. The time has come to finish off the final stretch of the long march towards protein secondary structure prediction. PMID:28040746

Revised Reynolds Stress and Triple Product Models

NASA Technical Reports Server (NTRS)

Olsen, Michael E.; Lillard, Randolph P.

2017-01-01

Revised versions of Lag methodology Reynolds-stress and triple product models are applied to accepted test cases to assess the improvement, or lack thereof, in the prediction capability of the models. The Bachalo-Johnson bump flow is shown as an example for this abstract submission.

Development of multilayer perceptron networks for isothermal time temperature transformation prediction of U-Mo-X alloys

NASA Astrophysics Data System (ADS)

Johns, Jesse M.; Burkes, Douglas

2017-07-01

In this work, a multilayered perceptron (MLP) network is used to develop predictive isothermal time-temperature-transformation (TTT) models covering a range of U-Mo binary and ternary alloys. The selected ternary alloys for model development are U-Mo-Ru, U-Mo-Nb, U-Mo-Zr, U-Mo-Cr, and U-Mo-Re. These model's ability to predict 'novel' U-Mo alloys is shown quite well despite the discrepancies between literature sources for similar alloys which likely arise from different thermal-mechanical processing conditions. These models are developed with the primary purpose of informing experimental decisions. Additional experimental insight is necessary in order to reduce the number of experiments required to isolate ideal alloys. These models allow test planners to evaluate areas of experimental interest; once initial tests are conducted, the model can be updated and further improve follow-on testing decisions. The model also improves analysis capabilities by reducing the number of data points necessary from any particular test. For example, if one or two isotherms are measured during a test, the model can construct the rest of the TTT curve over a wide range of temperature and time. This modeling capability reduces the cost of experiments while also improving the value of the results from the tests. The reduced costs could result in improved material characterization and therefore improved fundamental understanding of TTT dynamics. As additional understanding of phenomena driving TTTs is acquired, this type of MLP model can be used to populate unknowns (such as material impurity and other thermal mechanical properties) from past literature sources.

Simulation of cryogenic turbopump annular seals

NASA Astrophysics Data System (ADS)

Palazzolo, Alan B.

1992-12-01

The goal of the current work is to develop software that can accurately predict the dynamic coefficients, forces, leakage and horsepower loss for annular seals which have a potential for affecting the rotordynamic behavior of the pumps. The fruit of last year's research was the computer code SEALPAL which included capabilities for linear tapered geometry, Moody friction factor and inlet pre-swirl. This code produced results which in most cases compared very well with check cases presented in the literature. TAMUSEAL Icode, which was written to improve SEALPAL by correcting a bug and by adding more accurate integration algorithms and additional capabilities, was then used to predict dynamic coefficients and leakage for the NASA/Pratt and Whitney Alternate Turbopump Development (ATD) LOX Pump's seal.

KSC-2014-3258

NASA Image and Video Library

2014-07-22

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is delivered to the Building 836 hangar on south Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2015-1119

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is prepared for lifting at Space Launch Complex 2 for mating to its Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1127

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is lifted at Space Launch Complex 2 for mating to its Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1116

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is transported to Space Launch Complex 2 where it will be mated to a Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1120

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is prepared for lifting at Space Launch Complex 2 for mating to its Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1115

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is transported to Space Launch Complex 2 where it will be mated to a Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1123

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is lifted at Space Launch Complex 2 for mating to its Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1117

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is transported to Space Launch Complex 2 where it will be mated to a Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1131

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – The sun sets over the Pacific Ocean as seen from Vandenberg Air Force Base in California where NASA's Soil Moisture Active Passive mission, or SMAP, satellite is being prepared for liftoff from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1121

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is prepared for lifting at Space Launch Complex 2 for mating to its Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1122

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is lifted at Space Launch Complex 2 for mating to its Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1132

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – The sun sets behind Space Launch Complex 2 at Vandenberg Air Force Base in California where NASA's Soil Moisture Active Passive mission, or SMAP, satellite is being prepared for liftoff. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1118

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is transported to Space Launch Complex 2 where it will be mated to a Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1125

NASA Image and Video Library

2015-01-13

VANDENBERG AIR FORCE BASE, Calif. – At Vandenberg Air Force Base in California, NASA's Soil Moisture Active Passive mission, or SMAP, satellite is lifted at Space Launch Complex 2 for mating to its Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

Collaborative Project: Improving the Representation of Coastal and Estuarine Processes in Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

Final Report Collaborative Project: Improving the Representation of Coastal and Estuarine Processes in Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

Beyond Climate and Weather Science: Expanding the Forecasting Family to Serve Societal Needs

NASA Astrophysics Data System (ADS)

Barron, E. J.

2009-05-01

The ability to "anticipate" the future is what makes information from the Earth sciences valuable to society - whether it is the prediction of severe weather or the future availability of water resources in response to climate change. An improved ability to anticipate or forecast has the potential to serve society by simultaneously improving our ability to (1) promote economic vitality, (2) enable environmental stewardship, (3) protect life and property, as well as (4) improve our fundamental knowledge of the earth system. The potential is enormous, yet many appear ready to move quickly toward specific mitigation and adaptation strategies assuming that the science is settled. Five important weakness must be addressed first: (1) the formation of a true "climate services" function and capability, (2) the deliberate investment in expanding the family of forecasting elements to incorporate a broader array of environmental factors and impacts, (3) the investment in the sciences that connect climate to society, (4) a deliberate focus on the problems associated with scale, in particular the difference between the scale of predictive models and the scale associated with societal decisions, and (5) the evolution from climate services and model predictions to the equivalent of "environmental intelligence centers." The objective is to bring the discipline of forecasting to a broader array of environmental challenges. Assessments of the potential impacts of global climate change on societal sectors such as water, human health, and agriculture provide good examples of this challenge. We have the potential to move from a largely reactive mode in addressing adverse health outcomes, for example, to one in which the ties between climate, land cover, infectious disease vectors, and human health are used to forecast and predict adverse human health conditions. The potential exists for a revolution in forecasting, that entrains a much broader set of societal needs and solutions. The argument is made that (for example) the current capabilities in the prediction of environmental health is similar to the capabilities (and potential) of weather forecasting in the 1960's.

Intelligent Prediction of Fan Rotation Stall in Power Plants Based on Pressure Sensor Data Measured In-Situ

PubMed Central

Xu, Xiaogang; Wang, Songling; Liu, Jinlian; Liu, Xinyu

2014-01-01

Blower and exhaust fans consume over 30% of electricity in a thermal power plant, and faults of these fans due to rotation stalls are one of the most frequent reasons for power plant outage failures. To accurately predict the occurrence of fan rotation stalls, we propose a support vector regression machine (SVRM) model that predicts the fan internal pressures during operation, leaving ample time for rotation stall detection. We train the SVRM model using experimental data samples, and perform pressure data prediction using the trained SVRM model. To prove the feasibility of using the SVRM model for rotation stall prediction, we further process the predicted pressure data via wavelet-transform-based stall detection. By comparison of the detection results from the predicted and measured pressure data, we demonstrate that the SVRM model can accurately predict the fan pressure and guarantee reliable stall detection with a time advance of up to 0.0625 s. This superior pressure data prediction capability leaves significant time for effective control and prevention of fan rotation stall faults. This model has great potential for use in intelligent fan systems with stall prevention capability, which will ensure safe operation and improve the energy efficiency of power plants. PMID:24854057

EBUS-STAT Subscore Analysis to Predict the Efficacy and Assess the Validity of Virtual Reality Simulation for EBUS-TBNA Training Among Experienced Bronchoscopists.

PubMed

Scarlata, Simone; Palermo, Patrizio; Candoli, Piero; Tofani, Ariela; Petitti, Tommasangelo; Corbetta, Lorenzo

2017-04-01

Linear endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) represents a pivotal innovation in interventional pulmonology; determining the best approach to guarantee systematic and efficient training is expected to become a main issue in the forthcoming years. Virtual reality simulators have been proposed as potential EBUS-TBNA training instruments, to avoid unskilled beginners practicing directly in real-life settings. A validated and perfected simulation program could be used before allowing beginners to practice on patients. Our goal was to test the reliability of the EBUS-Skills and Task Assessment Tool (STAT) and its subscores for measuring the competence of experienced bronchoscopists approaching EBUS-guided TBNA, using only the virtual reality simulator as both a training and an assessment tool. Fifteen experienced bronchoscopists, with poor or no experience in EBUS-TBNA, participated in this study. They were all administered the Italian version of the EBUS-STAT evaluation tool, during a high-fidelity virtual reality simulation. This was followed by a single 7-hour theoretical and practical (on simulators) session on EBUS-TBNA, at the end of which their skills were reassessed by EBUS-STAT. An overall, significant improvement in EBUS-TBNA skills was observed, thereby confirming that (a) virtual reality simulation can facilitate practical learning among practitioners, and (b) EBUS-STAT is capable of detecting these improvements. The test's overall ability to detect differences was negatively influenced by the minimal variation of the scores relating to items 1 and 2, was not influenced by the training, and improved significantly when the 2 items were not considered. Apart from these 2 items, all the remaining subscores were equally capable of revealing improvements in the learner. Lastly, we found that trainees with presimulation EBUS-STAT scores above 79 did not show any significant improvement after virtual reality training, suggesting that this score represents a cutoff value capable of predicting the likelihood that simulation can be beneficial. Virtual reality simulation is capable of providing a practical learning tool for practitioners with previous experience in flexible bronchoscopy, and the EBUS-STAT questionnaire is capable of detecting these changes. A pretraining EBUS-STAT score below 79 is a good indicator of those candidates who will benefit from the simulation training. Further studies are needed to verify whether a modified version of the questionnaire would be capable of improving its performance among experienced bronchoscopists.

The use of genetic programming to develop a predictor of swash excursion on sandy beaches

NASA Astrophysics Data System (ADS)

Passarella, Marinella; Goldstein, Evan B.; De Muro, Sandro; Coco, Giovanni

2018-02-01

We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation). Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches) and providing physical insight into coastal processes.

Neural network-based run-to-run controller using exposure and resist thickness adjustment

NASA Astrophysics Data System (ADS)

Geary, Shane; Barry, Ronan

2003-06-01

This paper describes the development of a run-to-run control algorithm using a feedforward neural network, trained using the backpropagation training method. The algorithm is used to predict the critical dimension of the next lot using previous lot information. It is compared to a common prediction algorithm - the exponentially weighted moving average (EWMA) and is shown to give superior prediction performance in simulations. The manufacturing implementation of the final neural network showed significantly improved process capability when compared to the case where no run-to-run control was utilised.

Enhancing seasonal climate prediction capacity for the Pacific countries

NASA Astrophysics Data System (ADS)

Kuleshov, Y.; Jones, D.; Hendon, H.; Charles, A.; Cottrill, A.; Lim, E.-P.; Langford, S.; de Wit, R.; Shelton, K.

2012-04-01

Seasonal and inter-annual climate variability is a major factor in determining the vulnerability of many Pacific Island Countries to climate change and there is need to improve weekly to seasonal range climate prediction capabilities beyond what is currently available from statistical models. In the seasonal climate prediction project under the Australian Government's Pacific Adaptation Strategy Assistance Program (PASAP), we describe a comprehensive project to strengthen the climate prediction capacities in National Meteorological Services in 14 Pacific Island Countries and East Timor. The intent is particularly to reduce the vulnerability of current services to a changing climate, and improve the overall level of information available assist with managing climate variability. Statistical models cannot account for aspects of climate variability and change that are not represented in the historical record. In contrast, dynamical physics-based models implicitly include the effects of a changing climate whatever its character or cause and can predict outcomes not seen previously. The transition from a statistical to a dynamical prediction system provides more valuable and applicable climate information to a wide range of climate sensitive sectors throughout the countries of the Pacific region. In this project, we have developed seasonal climate outlooks which are based upon the current dynamical model POAMA (Predictive Ocean-Atmosphere Model for Australia) seasonal forecast system. At present, meteorological services of the Pacific Island Countries largely employ statistical models for seasonal outlooks. Outcomes of the PASAP project enhanced capabilities of the Pacific Island Countries in seasonal prediction providing National Meteorological Services with an additional tool to analyse meteorological variables such as sea surface temperatures, air temperature, pressure and rainfall using POAMA outputs and prepare more accurate seasonal climate outlooks.

Bayesian framework for aerospace gas turbine engine prognostics

NASA Astrophysics Data System (ADS)

Zaidan, M. A.; Mills, A. R.; Harrison, R. F.

Prognostics is an emerging capability of modern health monitoring that aims to increase the fidelity of failure predictions. In the aerospace industry, it is a key technology to maximise aircraft availability, offering a route to increase time in-service and reduce operational disruption through improved asset management.

Uncertainty in Multimodel Water Flow Simulation Associated with Pedotransfer Functions and Weighing Methods

USDA-ARS?s Scientific Manuscript database

Multimodeling (MM) has been developed during the last decade to improve prediction capability of hydrological models. The MM combined with the pedotransfer functions (PTFs) was successfully applied to soil water flow simulations. This study examined the uncertainty in water content simulations assoc...

APPLICATION OF A FULLY DISTRIBUTED WASHOFF AND TRANSPORT MODEL FOR A GULF COAST WATERSHED

EPA Science Inventory

Advances in hydrologic modeling have been shown to improve the accuracy of rainfall runoff simulation and prediction. Building on the capabilities of distributed hydrologic modeling, a water quality model was developed to simulate buildup, washoff, and advective transport of a co...

Determination of stores pointing error due to wing flexibility under flight load

NASA Technical Reports Server (NTRS)

Lokos, William A.; Bahm, Catherine M.; Heinle, Robert A.

1995-01-01

The in-flight elastic wing twist of a fighter-type aircraft was studied to provide for an improved on-board real-time computed prediction of pointing variations of three wing store stations. This is an important capability to correct sensor pod alignment variation or to establish initial conditions of iron bombs or smart weapons prior to release. The original algorithm was based upon coarse measurements. The electro-optical Flight Deflection Measurement System measured the deformed wing shape in flight under maneuver loads to provide a higher resolution database from which an improved twist prediction algorithm could be developed. The FDMS produced excellent repeatable data. In addition, a NASTRAN finite-element analysis was performed to provide additional elastic deformation data. The FDMS data combined with the NASTRAN analysis indicated that an improved prediction algorithm could be derived by using a different set of aircraft parameters, namely normal acceleration, stores configuration, Mach number, and gross weight.

Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response

USGS Publications Warehouse

Shakesby, Richard A.; Moody, John A.; Martin, Deborah A.; Robichaud, Peter R.

2016-01-01

Advances in research into wildfire impacts on runoff and erosion have demonstrated increasing complexity of controlling factors and responses, which, combined with changing fire frequency, present challenges for modellers. We convened a conference attended by experts and practitioners in post-wildfire impacts, meteorology and related research, including modelling, to focus on priority research issues. The aim was to improve our understanding of controls and responses and the predictive capabilities of models. This conference led to the eight selected papers in this special issue. They address aspects of the distinctiveness in the controls and responses among wildfire regions, spatiotemporal rainfall variability, infiltration, runoff connectivity, debris flow formation and modelling applications. Here we summarise key findings from these papers and evaluate their contribution to improving understanding and prediction of post-wildfire runoff and erosion under changes in climate, human intervention and population pressure on wildfire-prone areas.

Modeling and simulation challenges pursued by the Consortium for Advanced Simulation of Light Water Reactors (CASL)

NASA Astrophysics Data System (ADS)

Turinsky, Paul J.; Kothe, Douglas B.

2016-05-01

The Consortium for the Advanced Simulation of Light Water Reactors (CASL), the first Energy Innovation Hub of the Department of Energy, was established in 2010 with the goal of providing modeling and simulation (M&S) capabilities that support and accelerate the improvement of nuclear energy's economic competitiveness and the reduction of spent nuclear fuel volume per unit energy, and all while assuring nuclear safety. To accomplish this requires advances in M&S capabilities in radiation transport, thermal-hydraulics, fuel performance and corrosion chemistry. To focus CASL's R&D, industry challenge problems have been defined, which equate with long standing issues of the nuclear power industry that M&S can assist in addressing. To date CASL has developed a multi-physics ;core simulator; based upon pin-resolved radiation transport and subchannel (within fuel assembly) thermal-hydraulics, capitalizing on the capabilities of high performance computing. CASL's fuel performance M&S capability can also be optionally integrated into the core simulator, yielding a coupled multi-physics capability with untapped predictive potential. Material models have been developed to enhance predictive capabilities of fuel clad creep and growth, along with deeper understanding of zirconium alloy clad oxidation and hydrogen pickup. Understanding of corrosion chemistry (e.g., CRUD formation) has evolved at all scales: micro, meso and macro. CFD R&D has focused on improvement in closure models for subcooled boiling and bubbly flow, and the formulation of robust numerical solution algorithms. For multiphysics integration, several iterative acceleration methods have been assessed, illuminating areas where further research is needed. Finally, uncertainty quantification and data assimilation techniques, based upon sampling approaches, have been made more feasible for practicing nuclear engineers via R&D on dimensional reduction and biased sampling. Industry adoption of CASL's evolving M&S capabilities, which is in progress, will assist in addressing long-standing and future operational and safety challenges of the nuclear industry.

High-fidelity modeling and impact footprint prediction for vehicle breakup analysis

NASA Astrophysics Data System (ADS)

Ling, Lisa

For decades, vehicle breakup analysis had been performed for space missions that used nuclear heater or power units in order to assess aerospace nuclear safety for potential launch failures leading to inadvertent atmospheric reentry. Such pre-launch risk analysis is imperative to assess possible environmental impacts, obtain launch approval, and for launch contingency planning. In order to accurately perform a vehicle breakup analysis, the analysis tool should include a trajectory propagation algorithm coupled with thermal and structural analyses and influences. Since such a software tool was not available commercially or in the public domain, a basic analysis tool was developed by Dr. Angus McRonald prior to this study. This legacy software consisted of low-fidelity modeling and had the capability to predict vehicle breakup, but did not predict the surface impact point of the nuclear component. Thus the main thrust of this study was to develop and verify the additional dynamics modeling and capabilities for the analysis tool with the objectives to (1) have the capability to predict impact point and footprint, (2) increase the fidelity in the prediction of vehicle breakup, and (3) reduce the effort and time required to complete an analysis. The new functions developed for predicting the impact point and footprint included 3-degrees-of-freedom trajectory propagation, the generation of non-arbitrary entry conditions, sensitivity analysis, and the calculation of impact footprint. The functions to increase the fidelity in the prediction of vehicle breakup included a panel code to calculate the hypersonic aerodynamic coefficients for an arbitrary-shaped body and the modeling of local winds. The function to reduce the effort and time required to complete an analysis included the calculation of node failure criteria. The derivation and development of these new functions are presented in this dissertation, and examples are given to demonstrate the new capabilities and the improvements made, with comparisons between the results obtained from the upgraded analysis tool and the legacy software wherever applicable.

THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY ...

EPA Pesticide Factsheets

A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. These approaches are less well-suited, however, to the challenges of global toxicity prediction, i.e., to predicting the potential toxicity of structurally diverse chemicals across a wide range of end points of regulatory and pharmaceutical concern. New approaches that have the potential to significantly improve capabilities in predictive toxicology are elaborating the “activity” portion of the SAR paradigm. Recent advances in two areas of endeavor are particularly promising. Toxicity data informatics relies on standardized data schema, developed for particular areas of toxicological study, to facilitate data integration and enable relational exploration and mining of data across both historical and new areas of toxicological investigation. Bioassay profiling refers to large-scale high-throughput screening approaches that use chemicals as probes to broadly characterize biological response space, extending the concept of chemical “properties” to the biological activity domain. The effective capture and representation of legacy and new toxicity data into mineable form and the large-scale generation of new bioassay data in relation to chemical toxicity, both employing chemical stru

OAO battery data analysis

NASA Technical Reports Server (NTRS)

Gaston, S.; Wertheim, M.; Orourke, J. A.

1973-01-01

Summary, consolidation and analysis of specifications, manufacturing process and test controls, and performance results for OAO-2 and OAO-3 lot 20 Amp-Hr sealed nickel cadmium cells and batteries are reported. Correlation of improvements in control requirements with performance is a key feature. Updates for a cell/battery computer model to improve performance prediction capability are included. Applicability of regression analysis computer techniques to relate process controls to performance is checked.

Integrated Modeling and Analysis of Physical Oceanographic and Acoustic Processes

DTIC Science & Technology

2015-09-30

goal is to improve ocean physical state and acoustic state predictive capabilities. The goal fitting the scope of this project is the creation of... Project -scale objectives are to complete targeted studies of oceanographic processes in a few regimes, accompanied by studies of acoustic propagation...by the basic research efforts of this project . An additional objective is to develop improved computational tools for acoustics and for the

Modeling and simulation challenges pursued by the Consortium for Advanced Simulation of Light Water Reactors (CASL)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turinsky, Paul J., E-mail: turinsky@ncsu.edu; Kothe, Douglas B., E-mail: kothe@ornl.gov

The Consortium for the Advanced Simulation of Light Water Reactors (CASL), the first Energy Innovation Hub of the Department of Energy, was established in 2010 with the goal of providing modeling and simulation (M&S) capabilities that support and accelerate the improvement of nuclear energy's economic competitiveness and the reduction of spent nuclear fuel volume per unit energy, and all while assuring nuclear safety. To accomplish this requires advances in M&S capabilities in radiation transport, thermal-hydraulics, fuel performance and corrosion chemistry. To focus CASL's R&D, industry challenge problems have been defined, which equate with long standing issues of the nuclear powermore » industry that M&S can assist in addressing. To date CASL has developed a multi-physics “core simulator” based upon pin-resolved radiation transport and subchannel (within fuel assembly) thermal-hydraulics, capitalizing on the capabilities of high performance computing. CASL's fuel performance M&S capability can also be optionally integrated into the core simulator, yielding a coupled multi-physics capability with untapped predictive potential. Material models have been developed to enhance predictive capabilities of fuel clad creep and growth, along with deeper understanding of zirconium alloy clad oxidation and hydrogen pickup. Understanding of corrosion chemistry (e.g., CRUD formation) has evolved at all scales: micro, meso and macro. CFD R&D has focused on improvement in closure models for subcooled boiling and bubbly flow, and the formulation of robust numerical solution algorithms. For multiphysics integration, several iterative acceleration methods have been assessed, illuminating areas where further research is needed. Finally, uncertainty quantification and data assimilation techniques, based upon sampling approaches, have been made more feasible for practicing nuclear engineers via R&D on dimensional reduction and biased sampling. Industry adoption of CASL's evolving M&S capabilities, which is in progress, will assist in addressing long-standing and future operational and safety challenges of the nuclear industry. - Highlights: • Complexity of physics based modeling of light water reactor cores being addressed. • Capability developed to help address problems that have challenged the nuclear power industry. • Simulation capabilities that take advantage of high performance computing developed.« less

Large Eddy Simulation Modeling of Flashback and Flame Stabilization in Hydrogen-Rich Gas Turbines Using a Hierarchical Validation Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clemens, Noel

This project was a combined computational and experimental effort to improve predictive capability for boundary layer flashback of premixed swirl flames relevant to gas-turbine power plants operating with high-hydrogen-content fuels. During the course of this project, significant progress in modeling was made on four major fronts: 1) use of direct numerical simulation of turbulent flames to understand the coupling between the flame and the turbulent boundary layer; 2) improved modeling capability for flame propagation in stratified pre-mixtures; 3) improved portability of computer codes using the OpenFOAM platform to facilitate transfer to industry and other researchers; and 4) application of LESmore » to flashback in swirl combustors, and a detailed assessment of its capabilities and limitations for predictive purposes. A major component of the project was an experimental program that focused on developing a rich experimental database of boundary layer flashback in swirl flames. Both methane and high-hydrogen fuels, including effects of elevated pressure (1 to 5 atm), were explored. For this project, a new model swirl combustor was developed. Kilohertz-rate stereoscopic PIV and chemiluminescence imaging were used to investigate the flame propagation dynamics. In addition to the planar measurements, a technique capable of detecting the instantaneous, time-resolved 3D flame front topography was developed and applied successfully to investigate the flow-flame interaction. The UT measurements and legacy data were used in a hierarchical validation approach where flows with increasingly complex physics were used for validation. First component models were validated with DNS and literature data in simplified configurations, and this was followed by validation with the UT 1-atm flashback cases, and then the UT high-pressure flashback cases. The new models and portable code represent a major improvement over what was available before this project was initiated.« less

Status of the NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test After 30,352 Hours of Operation

NASA Technical Reports Server (NTRS)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 30,352 hr of operation and processed 490 kg of xenon throughput--surpassing the NSTAR Extended Life Test hours demonstrated and more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Application of a multi-block CFD code to investigate the impact of geometry modeling on centrifugal compressor flow field predictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hathaway, M.D.; Wood, J.R.

1997-10-01

CFD codes capable of utilizing multi-block grids provide the capability to analyze the complete geometry of centrifugal compressors. Attendant with this increased capability is potentially increased grid setup time and more computational overhead with the resultant increase in wall clock time to obtain a solution. If the increase in difficulty of obtaining a solution significantly improves the solution from that obtained by modeling the features of the tip clearance flow or the typical bluntness of a centrifugal compressor`s trailing edge, then the additional burden is worthwhile. However, if the additional information obtained is of marginal use, then modeling of certainmore » features of the geometry may provide reasonable solutions for designers to make comparative choices when pursuing a new design. In this spirit a sequence of grids were generated to study the relative importance of modeling versus detailed gridding of the tip gap and blunt trailing edge regions of the NASA large low-speed centrifugal compressor for which there is considerable detailed internal laser anemometry data available for comparison. The results indicate: (1) There is no significant difference in predicted tip clearance mass flow rate whether the tip gap is gridded or modeled. (2) Gridding rather than modeling the trailing edge results in better predictions of some flow details downstream of the impeller, but otherwise appears to offer no great benefits. (3) The pitchwise variation of absolute flow angle decreases rapidly up to 8% impeller radius ratio and much more slowly thereafter. Although some improvements in prediction of flow field details are realized as a result of analyzing the actual geometry there is no clear consensus that any of the grids investigated produced superior results in every case when compared to the measurements. However, if a multi-block code is available, it should be used, as it has the propensity for enabling better predictions than a single block code.« less

EPA DSSTox and ToxCast Project Updates: Generating New Data and Linkages in Support of Public Toxico-Cheminformatics Efforts

EPA Science Inventory

EPA’s National Center for Computational Toxicology is generating data and capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized fo...

Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China

PubMed Central

Liu, Tao; Zhu, Guanghu; Lin, Hualiang; Zhang, Yonghui; He, Jianfeng; Deng, Aiping; Peng, Zhiqiang; Xiao, Jianpeng; Rutherford, Shannon; Xie, Runsheng; Zeng, Weilin; Li, Xing; Ma, Wenjun

2017-01-01

Background Dengue fever (DF) in Guangzhou, Guangdong province in China is an important public health issue. The problem was highlighted in 2014 by a large, unprecedented outbreak. In order to respond in a more timely manner and hence better control such potential outbreaks in the future, this study develops an early warning model that integrates internet-based query data into traditional surveillance data. Methodology and principal findings A Dengue Baidu Search Index (DBSI) was collected from the Baidu website for developing a predictive model of dengue fever in combination with meteorological and demographic factors. Generalized additive models (GAM) with or without DBSI were established. The generalized cross validation (GCV) score and deviance explained indexes, intraclass correlation coefficient (ICC) and root mean squared error (RMSE), were respectively applied to measure the fitness and the prediction capability of the models. Our results show that the DBSI with one-week lag has a positive linear relationship with the local DF occurrence, and the model with DBSI (ICC:0.94 and RMSE:59.86) has a better prediction capability than the model without DBSI (ICC:0.72 and RMSE:203.29). Conclusions Our study suggests that a DSBI combined with traditional disease surveillance and meteorological data can improve the dengue early warning system in Guangzhou. PMID:28263988

Implementation and Verification of the Chen Prediction Technique for Forecasting Large Nonrecurrent Storms*

NASA Astrophysics Data System (ADS)

Arge, C. N.; Chen, J.; Slinker, S.; Pizzo, V. J.

2000-05-01

The method of Chen et al. [1997, JGR, 101, 27499] is designed to accurately identify and predict the occurrence, duration, and strength of largegeomagnetic storms using real-time solar wind data. The method estimates the IMF and the geoeffectiveness of the solar wind upstream of a monitor and can provide warning times that range from a few hours to more than 10 hours. The model uses physical features of solar wind structures that cause large storms: long durations of southward interplanetary magnetic field. It is currently undergoing testing, improvement, and validation at NOAA/SEC in effort to transition it into a real-time space weather forecasting tool. The original version of the model has modified so that it now makes hourly (as opposed to daily) predictions and has been improved in effort to enhance both its predictive capability and reliability. In this paper, we report on the results of a 2-year historical verification study of the model using ACE real-time data. The prediction performances of the original and improved versions of the model are then compared. A real-time prediction web page has been developed and is on line at NOAA/SEC. *Work supported by ONR.

KSC-2014-3284

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is transported from the Building 836 hangar to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2015-1114

NASA Image and Video Library

2015-01-08

VANDENBERG AIR FORCE BASE, Calif. – Inside the Astrotech payload processing facility at Vandenberg Air Force Base in California, engineers and technicians place a protective cover over NASA's Soil Moisture Active Passive mission, or SMAP, satellite prior the spacecraft being transported to the launch pad. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: Jeremy Moore, USAF Photo Squadron

KSC-2014-3166

NASA Image and Video Library

2014-07-17

VANDENBERG AIR FORCE BASE, Calif. – NASA's Soil Moisture Active Passive mission, or SMAP, is scheduled to launch in November 2014 from Space Launch Complex 2 on Vandenberg Air Force Base in California, seen here on a temperate, fog-free summer's day. A United Launch Alliance Delta II rocket will be used to deliver SMAP into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3364

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – Workers guide the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, onto the launcher adjacent to the fixed umbilical tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3290

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, accomplishes some tight turns on its approach to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3276

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The first stage of a United Launch Alliance Delta II rocket arrives at NASA hangar 836 on Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2014-3291

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, passes the mobile service tower at Space Launch Complex 2 on its way to the Horizontal Processing Facility on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3360

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – A crane transfers the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, into the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3577

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – A crane hoists the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, into a vertical position alongside the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Tony Vauccin, USAF

KSC-2014-3357

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is hoisted into a vertical position for its move into the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3350

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – Preparations are underway at Space Launch Complex 2 on Vandenberg Air Force Base in California for the arrival of the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2015-1112

NASA Image and Video Library

2015-01-08

VANDENBERG AIR FORCE BASE, Calif. – Inside the Astrotech payload processing facility at Vandenberg Air Force Base in California, engineers and technicians place a protective cover over NASA's Soil Moisture Active Passive mission, or SMAP, satellite prior the spacecraft being transported to the launch pad. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: Jeremy Moore, USAF Photo Squadron

KSC-2014-3355

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – Workers oversee the preparations to lift the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, into the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3275

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The first stage of a United Launch Alliance Delta II rocket arrives at NASA hangar 836 on Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2014-3580

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – A crane transfers the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, into the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Tony Vauccin, USAF

KSC-2015-1113

NASA Image and Video Library

2015-01-08

VANDENBERG AIR FORCE BASE, Calif. – Inside the Astrotech payload processing facility at Vandenberg Air Force Base in California, engineers and technicians place a protective cover over NASA's Soil Moisture Active Passive mission, or SMAP, satellite prior the spacecraft being transported to the launch pad. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: Jeremy Moore, USAF Photo Squadron

The STEREO Mission: A New Approach to Space Weather Research

NASA Technical Reports Server (NTRS)

Kaiser, michael L.

2006-01-01

With the launch of the twin STEREO spacecraft in July 2006, a new capability will exist for both real-time space weather predictions and for advances in space weather research. Whereas previous spacecraft monitors of the sun such as ACE and SOH0 have been essentially on the sun-Earth line, the STEREO spacecraft will be in 1 AU orbits around the sun on either side of Earth and will be viewing the solar activity from distinctly different vantage points. As seen from the sun, the two spacecraft will separate at a rate of 45 degrees per year, with Earth bisecting the angle. The instrument complement on the two spacecraft will consist of a package of optical instruments capable of imaging the sun in the visible and ultraviolet from essentially the surface to 1 AU and beyond, a radio burst receiver capable of tracking solar eruptive events from an altitude of 2-3 Rs to 1 AU, and a comprehensive set of fields and particles instruments capable of measuring in situ solar events such as interplanetary magnetic clouds. In addition to normal daily recorded data transmissions, each spacecraft is equipped with a real-time beacon that will provide 1 to 5 minute snapshots or averages of the data from the various instruments. This beacon data will be received by NOAA and NASA tracking stations and then relayed to the STEREO Science Center located at Goddard Space Flight Center in Maryland where the data will be processed and made available within a goal of 5 minutes of receipt on the ground. With STEREO's instrumentation and unique view geometry, we believe considerable improvement can be made in space weather prediction capability as well as improved understanding of the three dimensional structure of solar transient events.

At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration

DOE PAGES

Stegen, James C.

2018-04-10

To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modelingmore » frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. Here, we can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.« less

Study on model current predictive control method of PV grid- connected inverters systems with voltage sag

NASA Astrophysics Data System (ADS)

Jin, N.; Yang, F.; Shang, S. Y.; Tao, T.; Liu, J. S.

2016-08-01

According to the limitations of the LVRT technology of traditional photovoltaic inverter existed, this paper proposes a low voltage ride through (LVRT) control method based on model current predictive control (MCPC). This method can effectively improve the photovoltaic inverter output characteristics and response speed. The MCPC method of photovoltaic grid-connected inverter designed, the sum of the absolute value of the predictive current and the given current error is adopted as the cost function with the model predictive control method. According to the MCPC, the optimal space voltage vector is selected. Photovoltaic inverter has achieved automatically switches of priority active or reactive power control of two control modes according to the different operating states, which effectively improve the inverter capability of LVRT. The simulation and experimental results proves that the proposed method is correct and effective.

A high-throughput exploration of magnetic materials by using structure predicting methods

NASA Astrophysics Data System (ADS)

Arapan, S.; Nieves, P.; Cuesta-López, S.

2018-02-01

We study the capability of a structure predicting method based on genetic/evolutionary algorithm for a high-throughput exploration of magnetic materials. We use the USPEX and VASP codes to predict stable and generate low-energy meta-stable structures for a set of representative magnetic structures comprising intermetallic alloys, oxides, interstitial compounds, and systems containing rare-earths elements, and for both types of ferromagnetic and antiferromagnetic ordering. We have modified the interface between USPEX and VASP codes to improve the performance of structural optimization as well as to perform calculations in a high-throughput manner. We show that exploring the structure phase space with a structure predicting technique reveals large sets of low-energy metastable structures, which not only improve currently exiting databases, but also may provide understanding and solutions to stabilize and synthesize magnetic materials suitable for permanent magnet applications.

At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stegen, James C.

To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modelingmore » frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. Here, we can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.« less

At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration.

PubMed

Stegen, James C

2018-01-01

To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modeling frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. We can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.

Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

NASA Technical Reports Server (NTRS)

Downs, Meghan E.; Lee, Stuart M. C.; Ploutz-Snyder, Lori; Feiveson, Alan

2016-01-01

Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

Study of Earthquake Disaster Prediction System of Langfang city Based on GIS

NASA Astrophysics Data System (ADS)

Huang, Meng; Zhang, Dian; Li, Pan; Zhang, YunHui; Zhang, RuoFei

2017-07-01

In this paper, according to the status of China’s need to improve the ability of earthquake disaster prevention, this paper puts forward the implementation plan of earthquake disaster prediction system of Langfang city based on GIS. Based on the GIS spatial database, coordinate transformation technology, GIS spatial analysis technology and PHP development technology, the seismic damage factor algorithm is used to predict the damage of the city under different intensity earthquake disaster conditions. The earthquake disaster prediction system of Langfang city is based on the B / S system architecture. Degree and spatial distribution and two-dimensional visualization display, comprehensive query analysis and efficient auxiliary decision-making function to determine the weak earthquake in the city and rapid warning. The system has realized the transformation of the city’s earthquake disaster reduction work from static planning to dynamic management, and improved the city’s earthquake and disaster prevention capability.

Development of multilayer perceptron networks for isothermal time temperature transformation prediction of U-Mo-X alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johns, Jesse M.; Burkes, Douglas

In this work, a multilayered perceptron (MLP) network is used to develop predictive isothermal time-temperature-transformation (TTT) models covering a range of U-Mo binary and ternary alloys. The selected ternary alloys for model development are U-Mo-Ru, U-Mo-Nb, U-Mo-Zr, U-Mo-Cr, and U-Mo-Re. These model’s ability to predict 'novel' U-Mo alloys is shown quite well despite the discrepancies between literature sources for similar alloys which likely arise from different thermal-mechanical processing conditions. These models are developed with the primary purpose of informing experimental decisions. Additional experimental insight is necessary in order to reduce the number of experiments required to isolate ideal alloys. Thesemore » models allow test planners to evaluate areas of experimental interest; once initial tests are conducted, the model can be updated and further improve follow-on testing decisions. The model also improves analysis capabilities by reducing the number of data points necessary from any particular test. For example, if one or two isotherms are measured during a test, the model can construct the rest of the TTT curve over a wide range of temperature and time. This modeling capability reduces the cost of experiments while also improving the value of the results from the tests. The reduced costs could result in improved material characterization and therefore improved fundamental understanding of TTT dynamics. As additional understanding of phenomena driving TTTs is acquired, this type of MLP model can be used to populate unknowns (such as material impurity and other thermal mechanical properties) from past literature sources.« less

Simulating urban-scale air pollutants and their predicting capabilities over the Seoul metropolitan area.

PubMed

Park, Il-Soo; Lee, Suk-Jo; Kim, Cheol-Hee; Yoo, Chul; Lee, Yong-Hee

2004-06-01

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter > or = 10 microm, and ozone (O3) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km x 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of approximately 0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.

Seismographs, sensors, and satellites: Better technology for safer communities

USGS Publications Warehouse

Groat, C.G.

2004-01-01

In the past 25 years, our ability to measure, monitor, and model the processes that lead to natural disasters has increased dramatically. Equally important has been the improvement in our technological capability to communicate information about hazards to those whose lives may be affected. These innovations in tracking and communicating the changes-floods, earthquakes, wildfires, volcanic eruptions-in our dynamic planet, supported by a deeper understanding of earth processes, enable us to expand our predictive capabilities and point the way to a safer future. ?? 2004 Elsevier Ltd. All rights reserved.

Performance upgrades to the MCNP6 burnup capability for large scale depletion calculations

DOE PAGES

Fensin, M. L.; Galloway, J. D.; James, M. R.

2015-04-11

The first MCNP based inline Monte Carlo depletion capability was officially released from the Radiation Safety Information and Computational Center as MCNPX 2.6.0. With the merger of MCNPX and MCNP5, MCNP6 combined the capability of both simulation tools, as well as providing new advanced technology, in a single radiation transport code. The new MCNP6 depletion capability was first showcased at the International Congress for Advancements in Nuclear Power Plants (ICAPP) meeting in 2012. At that conference the new capabilities addressed included the combined distributive and shared memory parallel architecture for the burnup capability, improved memory management, physics enhancements, and newmore » predictability as compared to the H.B Robinson Benchmark. At Los Alamos National Laboratory, a special purpose cluster named “tebow,” was constructed such to maximize available RAM per CPU, as well as leveraging swap space with solid state hard drives, to allow larger scale depletion calculations (allowing for significantly more burnable regions than previously examined). As the MCNP6 burnup capability was scaled to larger numbers of burnable regions, a noticeable slowdown was realized.This paper details two specific computational performance strategies for improving calculation speedup: (1) retrieving cross sections during transport; and (2) tallying mechanisms specific to burnup in MCNP. To combat this slowdown new performance upgrades were developed and integrated into MCNP6 1.2.« less

Snow on Sea Ice Workshop - An Icy Meeting of the Minds: Modelers and Measurers

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Snow on Sea Ice Workshop - An Icy Meeting of the Minds...workshop was to promote more seamless and better integration between measurements and modeling of snow on sea ice , thereby improving our predictive...capabilities for sea ice . OBJECTIVES The key objective was to improve the ability of modelers and measurers work together closely. To that end, we

An analytical method to predict efficiency of aircraft gearboxes

NASA Technical Reports Server (NTRS)

Anderson, N. E.; Loewenthal, S. H.; Black, J. D.

1984-01-01

A spur gear efficiency prediction method previously developed by the authors was extended to include power loss of planetary gearsets. A friction coefficient model was developed for MIL-L-7808 oil based on disc machine data. This combined with the recent capability of predicting losses in spur gears of nonstandard proportions allows the calculation of power loss for complete aircraft gearboxes that utilize spur gears. The method was applied to the T56/501 turboprop gearbox and compared with measured test data. Bearing losses were calculated with large scale computer programs. Breakdowns of the gearbox losses point out areas for possible improvement.

Optimization of a novel biophysical model using large scale in vivo antisense hybridization data displays improved prediction capabilities of structurally accessible RNA regions

PubMed Central

Vazquez-Anderson, Jorge; Mihailovic, Mia K.; Baldridge, Kevin C.; Reyes, Kristofer G.; Haning, Katie; Cho, Seung Hee; Amador, Paul; Powell, Warren B.

2017-01-01

Abstract Current approaches to design efficient antisense RNAs (asRNAs) rely primarily on a thermodynamic understanding of RNA–RNA interactions. However, these approaches depend on structure predictions and have limited accuracy, arguably due to overlooking important cellular environment factors. In this work, we develop a biophysical model to describe asRNA–RNA hybridization that incorporates in vivo factors using large-scale experimental hybridization data for three model RNAs: a group I intron, CsrB and a tRNA. A unique element of our model is the estimation of the availability of the target region to interact with a given asRNA using a differential entropic consideration of suboptimal structures. We showcase the utility of this model by evaluating its prediction capabilities in four additional RNAs: a group II intron, Spinach II, 2-MS2 binding domain and glgC 5΄ UTR. Additionally, we demonstrate the applicability of this approach to other bacterial species by predicting sRNA–mRNA binding regions in two newly discovered, though uncharacterized, regulatory RNAs. PMID:28334800

The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine.

PubMed

Xiao, Chuncai; Hao, Kuangrong; Ding, Yongsheng

2014-12-30

This paper creates a bi-directional prediction model to predict the performance of carbon fiber and the productive parameters based on a support vector machine (SVM) and improved particle swarm optimization (IPSO) algorithm (SVM-IPSO). In the SVM, it is crucial to select the parameters that have an important impact on the performance of prediction. The IPSO is proposed to optimize them, and then the SVM-IPSO model is applied to the bi-directional prediction of carbon fiber production. The predictive accuracy of SVM is mainly dependent on its parameters, and IPSO is thus exploited to seek the optimal parameters for SVM in order to improve its prediction capability. Inspired by a cell communication mechanism, we propose IPSO by incorporating information of the global best solution into the search strategy to improve exploitation, and we employ IPSO to establish the bi-directional prediction model: in the direction of the forward prediction, we consider productive parameters as input and property indexes as output; in the direction of the backward prediction, we consider property indexes as input and productive parameters as output, and in this case, the model becomes a scheme design for novel style carbon fibers. The results from a set of the experimental data show that the proposed model can outperform the radial basis function neural network (RNN), the basic particle swarm optimization (PSO) method and the hybrid approach of genetic algorithm and improved particle swarm optimization (GA-IPSO) method in most of the experiments. In other words, simulation results demonstrate the effectiveness and advantages of the SVM-IPSO model in dealing with the problem of forecasting.

Handling Trajectory Uncertainties for Airborne Conflict Management

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Doble, Nathan A.; Karr, David; Palmer, Michael T.

2005-01-01

Airborne conflict management is an enabling capability for NASA's Distributed Air-Ground Traffic Management (DAG-TM) concept. DAGTM has the goal of significantly increasing capacity within the National Airspace System, while maintaining or improving safety. Under DAG-TM, autonomous aircraft maintain separation from each other and from managed aircraft unequipped for autonomous flight. NASA Langley Research Center has developed the Autonomous Operations Planner (AOP), an onboard decision support system that provides airborne conflict management (ACM) and strategic flight planning support for autonomous aircraft pilots. The AOP performs conflict detection, prevention, and resolution from nearby traffic aircraft and area hazards. Traffic trajectory information is assumed to be provided by Automatic Dependent Surveillance Broadcast (ADS-B). Reliable trajectory prediction is a key capability for providing effective ACM functions. Trajectory uncertainties due to environmental effects, differences in aircraft systems and performance, and unknown intent information lead to prediction errors that can adversely affect AOP performance. To accommodate these uncertainties, the AOP has been enhanced to create cross-track, vertical, and along-track buffers along the predicted trajectories of both ownship and traffic aircraft. These buffers will be structured based on prediction errors noted from previous simulations such as a recent Joint Experiment between NASA Ames and Langley Research Centers and from other outside studies. Currently defined ADS-B parameters related to navigation capability, trajectory type, and path conformance will be used to support the algorithms that generate the buffers.

Full-Scale Turbofan-Engine Turbine-Transfer Function Determination Using Three Internal Sensors

NASA Technical Reports Server (NTRS)

Hultgren, Lennart S.

2012-01-01

Noise-source separation techniques, using three engine-internal sensors, are applied to existing static-engine test data to determine the turbine transfer function for the currently subdominant combustion noise. The results are used to assess the combustion-noise prediction capability of the Aircraft Noise Prediction Program (ANOPP) and an improvement to the combustion-noise module GECOR is suggested. The work was carried out in response to the NASA Fundamental Aeronautics Subsonic Fixed Wing Program s Reduced-Perceived-Noise Technical Challenge.

Demonstrating the Operational Value of Atmospheric Infrared Sounder (AIRS) Profiles in the Pre-Convective Environment

NASA Technical Reports Server (NTRS)

Kozlowski, Danielle; Zavodsky, Bradley; Stano, Geoffrey; Jedlovec, Gary

2011-01-01

The Short-term Prediction Research and Transition (SPoRT) is a project to transition those NASA observations and research capabilities to the weather forecasting community to improve the short-term regional forecasts. This poster reviews the work to demonstrate the value to these forecasts of profiles from the Atmospheric Infrared Sounder (AIRS) instrument on board the Aqua satellite with particular assistance in predicting thunderstorm forecasts by the profiles of the pre-convective environment.

The Development of PIPA: An Integrated and Automated Pipeline for Genome-Wide Protein Function Annotation

DTIC Science & Technology

2008-01-25

limitations and plans for improvement Perhaps, one of PIPA’s main limitations is that all of its currently integrated resources to predict protein function...are planning on expending PIPA’s function prediction capabilities by incorporating comparative analysis approaches, e.g., phy- logenetic tree analysis...tools and services. Nucleic Acids Res 2005/12/31 edition. 2006, 34(Database issue):D247-51. 6. Bru C, Courcelle E, Carrere S, Beausse Y, Dalmar S

Project SAFE: A Blueprint for Flight Standards. Part 1.

DTIC Science & Technology

1985-01-01

nwanage quota utilization and scheduling was designed to meet a more stable and predictable training environmtent than that which now exists in the Flight...accurate and timely reporting of field office activities, and f. Provide improved capability to conduct national level analyses to predict and prevent...and analysis of the task prfocmd tV filw "lht B tanderds Lstms aIOUMaMM (Brief descriotion ci 7aj project is wIg ;,ude0-01n ’Te objective of the Ml

Predictions for Proteins, RNAs and DNAs with the Gaussian Dielectric Function Using DelPhiPKa

PubMed Central

Wang, Lin; Li, Lin; Alexov, Emil

2015-01-01

We developed a Poisson-Boltzmann based approach to calculate the PKa values of protein ionizable residues (Glu, Asp, His, Lys and Arg), nucleotides of RNA and single stranded DNA. Two novel features were utilized: the dielectric properties of the macromolecules and water phase were modeled via the smooth Gaussian-based dielectric function in DelPhi and the corresponding electrostatic energies were calculated without defining the molecular surface. We tested the algorithm by calculating PKa values for more than 300 residues from 32 proteins from the PPD dataset and achieved an overall RMSD of 0.77. Particularly, the RMSD of 0.55 was achieved for surface residues, while the RMSD of 1.1 for buried residues. The approach was also found capable of capturing the large PKa shifts of various single point mutations in staphylococcal nuclease (SNase) from PKa -cooperative dataset, resulting in an overall RMSD of 1.6 for this set of pKa’s. Investigations showed that predictions for most of buried mutant residues of SNase could be improved by using higher dielectric constant values. Furthermore, an option to generate different hydrogen positions also improves PKa predictions for buried carboxyl residues. Finally, the PKa calculations on two RNAs demonstrated the capability of this approach for other types of biomolecules. PMID:26408449

Improving orbit prediction accuracy through supervised machine learning

NASA Astrophysics Data System (ADS)

Peng, Hao; Bai, Xiaoli

2018-05-01

Due to the lack of information such as the space environment condition and resident space objects' (RSOs') body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This paper presents a methodology to predict RSOs' trajectories with higher accuracy than that of the current methods. Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors. Using a simulation-based space catalog environment as the test bed, the paper demonstrates three types of generalization capability for the proposed ML approach: (1) the ML model can be used to improve the same RSO's orbit information that is not available during the learning process but shares the same time interval as the training data; (2) the ML model can be used to improve predictions of the same RSO at future epochs; and (3) the ML model based on a RSO can be applied to other RSOs that share some common features.

Prediction of response factors for gas chromatography with flame ionization detection: Algorithm improvement, extension to silylated compounds, and application to the quantification of metabolites

PubMed Central

de Saint Laumer, Jean‐Yves; Leocata, Sabine; Tissot, Emeline; Baroux, Lucie; Kampf, David M.; Merle, Philippe; Boschung, Alain; Seyfried, Markus

2015-01-01

We previously showed that the relative response factors of volatile compounds were predictable from either combustion enthalpies or their molecular formulae only 1. We now extend this prediction to silylated derivatives by adding an increment in the ab initio calculation of combustion enthalpies. The accuracy of the experimental relative response factors database was also improved and its population increased to 490 values. In particular, more brominated compounds were measured, and their prediction accuracy was improved by adding a correction factor in the algorithm. The correlation coefficient between predicted and measured values increased from 0.936 to 0.972, leading to a mean prediction accuracy of ± 6%. Thus, 93% of the relative response factors values were predicted with an accuracy of better than ± 10%. The capabilities of the extended algorithm are exemplified by (i) the quick and accurate quantification of hydroxylated metabolites resulting from a biodegradation test after silylation and prediction of their relative response factors, without having the reference substances available; and (ii) the rapid purity determinations of volatile compounds. This study confirms that Gas chromatography with a flame ionization detector and using predicted relative response factors is one of the few techniques that enables quantification of volatile compounds without calibrating the instrument with the pure reference substance. PMID:26179324

Pyrolysis Model Development for a Multilayer Floor Covering

PubMed Central

McKinnon, Mark B.; Stoliarov, Stanislav I.

2015-01-01

Comprehensive pyrolysis models that are integral to computational fire codes have improved significantly over the past decade as the demand for improved predictive capabilities has increased. High fidelity pyrolysis models may improve the design of engineered materials for better fire response, the design of the built environment, and may be used in forensic investigations of fire events. A major limitation to widespread use of comprehensive pyrolysis models is the large number of parameters required to fully define a material and the lack of effective methodologies for measurement of these parameters, especially for complex materials. The work presented here details a methodology used to characterize the pyrolysis of a low-pile carpet tile, an engineered composite material that is common in commercial and institutional occupancies. The studied material includes three distinct layers of varying composition and physical structure. The methodology utilized a comprehensive pyrolysis model (ThermaKin) to conduct inverse analyses on data collected through several experimental techniques. Each layer of the composite was individually parameterized to identify its contribution to the overall response of the composite. The set of properties measured to define the carpet composite were validated against mass loss rate curves collected at conditions outside the range of calibration conditions to demonstrate the predictive capabilities of the model. The mean error between the predicted curve and the mean experimental mass loss rate curve was calculated as approximately 20% on average for heat fluxes ranging from 30 to 70 kW·m−2, which is within the mean experimental uncertainty. PMID:28793556

SENSITIVITY OF OZONE AND AEROSOL PREDICTIONS TO THE TRANSPORT ALGORITHMS IN THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODELING SYSTEM

EPA Science Inventory

EPA's Models-3 CMAQ system is intended to provide a community modeling paradigm that allows continuous improvement of the one-atmosphere modeling capability in a unified fashion. CMAQ's modular design promotes incorporation of several sets of science process modules representing ...

Improved Life Prediction of Turbine Engine Components Using a Finite Element Based Software Called Zencrack

DTIC Science & Technology

2003-09-01

application .................................................. 5-42 5.10 Different materials within crack-block...5-30 Figure 5-29 - Application of required user edge node sets... applications . Users have at their disposal all of the capabilities within these finite element programs and may, if desired, include any number of

Bankruptcy prediction based on financial ratios using Jordan Recurrent Neural Networks: a case study in Polish companies

NASA Astrophysics Data System (ADS)

Hardinata, Lingga; Warsito, Budi; Suparti

2018-05-01

Complexity of bankruptcy causes the accurate models of bankruptcy prediction difficult to be achieved. Various prediction models have been developed to improve the accuracy of bankruptcy predictions. Machine learning has been widely used to predict because of its adaptive capabilities. Artificial Neural Networks (ANN) is one of machine learning which proved able to complete inference tasks such as prediction and classification especially in data mining. In this paper, we propose the implementation of Jordan Recurrent Neural Networks (JRNN) to classify and predict corporate bankruptcy based on financial ratios. Feedback interconnection in JRNN enable to make the network keep important information well allowing the network to work more effectively. The result analysis showed that JRNN works very well in bankruptcy prediction with average success rate of 81.3785%.

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.

PubMed

Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola

2016-07-01

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.

Modeling the viscosity of polydisperse suspensions: Improvements in prediction of limiting behavior

NASA Astrophysics Data System (ADS)

Mwasame, Paul M.; Wagner, Norman J.; Beris, Antony N.

2016-06-01

The present study develops a fully consistent extension of the approach pioneered by Farris ["Prediction of the viscosity of multimodal suspensions from unimodal viscosity data," Trans. Soc. Rheol. 12, 281-301 (1968)] to describe the viscosity of polydisperse suspensions significantly improving upon our previous model [P. M. Mwasame, N. J. Wagner, and A. N. Beris, "Modeling the effects of polydispersity on the viscosity of noncolloidal hard sphere suspensions," J. Rheol. 60, 225-240 (2016)]. The new model captures the Farris limit of large size differences between consecutive particle size classes in a suspension. Moreover, the new model includes a further generalization that enables its application to real, complex suspensions that deviate from ideal non-colloidal suspension behavior. The capability of the new model to predict the viscosity of complex suspensions is illustrated by comparison against experimental data.

An entropy and viscosity corrected potential method for rotor performance prediction

NASA Technical Reports Server (NTRS)

Bridgeman, John O.; Strawn, Roger C.; Caradonna, Francis X.

1988-01-01

An unsteady Full-Potential Rotor code (FPR) has been enhanced with modifications directed at improving its drag prediction capability. The shock generated entropy has been included to provide solutions comparable to the Euler equations. A weakly interacted integral boundary layer has also been coupled to FPR in order to estimate skin-friction drag. Pressure distributions, shock positions, and drag comparisons are made with various data sets derived from two-dimensional airfoil, hovering, and advancing high speed rotor tests. In all these comparisons, the effect of the nonisentropic modification improves (i.e., weakens) the shock strength and wave drag. In addition, the boundary layer method yields reasonable estimates of skin-friction drag. Airfoil drag and hover torque data comparisons are excellent, as are predicted shock strength and positions for a high speed advancing rotor.

Applicability of a panel method, which includes nonlinear effects, to a forward-swept-wing aircraft

NASA Technical Reports Server (NTRS)

Ross, J. C.

1984-01-01

The ability of a lower order panel method VSAERO, to accurately predict the lift and pitching moment of a complete forward-swept-wing/canard configuration was investigated. The program can simulate nonlinear effects including boundary-layer displacement thickness, wake roll up, and to a limited extent, separated wakes. The predictions were compared with experimental data obtained using a small-scale model in the 7- by 10- Foot Wind Tunnel at NASA Ames Research Center. For the particular configuration under investigation, wake roll up had only a small effect on the force and moment predictions. The effect of the displacement thickness modeling was to reduce the lift curve slope slightly, thus bringing the predicted lift into good agreement with the measured value. Pitching moment predictions were also improved by the boundary-layer simulation. The separation modeling was found to be sensitive to user inputs, but appears to give a reasonable representation of a separated wake. In general, the nonlinear capabilities of the code were found to improve the agreement with experimental data. The usefullness of the code would be enhanced by improving the reliability of the separated wake modeling and by the addition of a leading edge separation model.

KSC-2014-3324

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is transported from the Building 836 hangar to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/U.S. Air Force 30th Space Wing

KSC-2014-3287

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – A worker is stationed on the transporter carrying the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, from the Building 836 hangar to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3576

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is raised off its transporter into a vertical position for its transfer into the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Tony Vauccin, USAF

KSC-2014-3578

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is hoisted into a vertical position for its transfer into the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Tony Vauccin, USAF

KSC-2014-3277

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – Technicians prepare to offload the first stage of a United Launch Alliance Delta II rocket following its arrival at NASA hangar 836 on Vandenberg Air Force Base in California. The launch vehicle will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2014-3282

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – Technicians assist in offloading the first stage of a United Launch Alliance Delta II rocket following its arrival at NASA hangar 836 on Vandenberg Air Force Base in California. The launch vehicle will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2014-3361

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is positioned in the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California in preparation for mating with the rocket's second stage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3351

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is readied for the short trip from the Horizontal Processing Facility to the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3356

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, is elevated off its transporter into a vertical position for its move into the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3278

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – A crane is positioned to offload the first stage of a United Launch Alliance Delta II rocket following its arrival at NASA hangar 836 on Vandenberg Air Force Base in California. The launch vehicle will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2014-3257

NASA Image and Video Library

2014-07-16

VANDENBERG AIR FORCE BASE, Calif. – The nozzle has been installed on the second stage of the United Launch Alliance Delta II rocket in the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. The Delta II will be used to loft NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3160

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The second stage, or upper stage, of a United Launch Alliance Delta II rocket arrives at the Building 836 hangar on south Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit from Vandenberg's Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3325

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, makes its way along the roadways on Vandenberg Air Force Base in California from the Building 836 hangar to the Horizontal Processing Facility at Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/U.S. Air Force 30th Space Wing

KSC-2014-3359

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – Workers steady the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, after it is lifted into a vertical position beside the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3279

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – A crane is used to offload the first stage of a United Launch Alliance Delta II rocket following its arrival at NASA hangar 836 on Vandenberg Air Force Base in California. The launch vehicle will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2014-3363

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The nozzle on the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, comes into view as the booster is lowered onto the launcher adjacent to the fixed umbilical tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

Focused Assessment of State-of-the-Art CFD Capabilities for Prediction of Subsonic Fixed Wing Aircraft Aerodynamics

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Wahls, Richard A.

2008-01-01

Several recent workshops and studies are used to make an assessment of the current status of CFD for subsonic fixed wing aerodynamics. Uncertainty quantification plays a significant role in the assessment, so terms associated with verification and validation are given and some methodology and research areas are highlighted. For high-subsonic-speed cruise through buffet onset, the series of drag prediction workshops and NASA/Boeing buffet onset studies are described. For low-speed flow control for high lift, a circulation control workshop and a synthetic jet flow control workshop are described. Along with a few specific recommendations, gaps and needs identified through the workshops and studies are used to develop a list of broad recommendations to improve CFD capabilities and processes for this discipline in the future.

On improvement to the Shock Propagation Model (SPM) applied to interplanetary shock transit time forecasting

NASA Astrophysics Data System (ADS)

Li, H. J.; Wei, F. S.; Feng, X. S.; Xie, Y. Q.

2008-09-01

This paper investigates methods to improve the predictions of Shock Arrival Time (SAT) of the original Shock Propagation Model (SPM). According to the classical blast wave theory adopted in the SPM, the shock propagating speed is determined by the total energy of the original explosion together with the background solar wind speed. Noting that there exists an intrinsic limit to the transit times computed by the SPM predictions for a specified ambient solar wind, we present a statistical analysis on the forecasting capability of the SPM using this intrinsic property. Two facts about SPM are found: (1) the error in shock energy estimation is not the only cause of the prediction errors and we should not expect that the accuracy of SPM to be improved drastically by an exact shock energy input; and (2) there are systematic differences in prediction results both for the strong shocks propagating into a slow ambient solar wind and for the weak shocks into a fast medium. Statistical analyses indicate the physical details of shock propagation and thus clearly point out directions of the future improvement of the SPM. A simple modification is presented here, which shows that there is room for improvement of SPM and thus that the original SPM is worthy of further development.

A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

NASA Astrophysics Data System (ADS)

Coyne, Kevin Anthony

The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional branching events and provide a better representation of the IDAC cognitive model. An operator decision-making engine capable of responding to dynamic changes in situational context was implemented. The IDAC human performance model was fully integrated with a detailed nuclear plant model in order to realistically simulate plant accident scenarios. Finally, the improved ADS-IDAC model was calibrated, validated, and updated using actual nuclear plant crew performance data. This research led to the following general conclusions: (1) A relatively small number of branching rules are capable of efficiently capturing a wide spectrum of crew-to-crew variabilities. (2) Compared to traditional static risk assessment methods, ADS-IDAC can provide a more realistic and integrated assessment of human error events by directly determining the effect of operator behaviors on plant thermal hydraulic parameters. (3) The ADS-IDAC approach provides an efficient framework for capturing actual operator performance data such as timing of operator actions, mental models, and decision-making activities.

An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction

NASA Astrophysics Data System (ADS)

Dash, Rajashree

2017-11-01

Forecasting purchasing power of one currency with respect to another currency is always an interesting topic in the field of financial time series prediction. Despite the existence of several traditional and computational models for currency exchange rate forecasting, there is always a need for developing simpler and more efficient model, which will produce better prediction capability. In this paper, an evolutionary framework is proposed by using an improved shuffled frog leaping (ISFL) algorithm with a computationally efficient functional link artificial neural network (CEFLANN) for prediction of currency exchange rate. The model is validated by observing the monthly prediction measures obtained for three currency exchange data sets such as USD/CAD, USD/CHF, and USD/JPY accumulated within same period of time. The model performance is also compared with two other evolutionary learning techniques such as Shuffled frog leaping algorithm and Particle Swarm optimization algorithm. Practical analysis of results suggest that, the proposed model developed using the ISFL algorithm with CEFLANN network is a promising predictor model for currency exchange rate prediction compared to other models included in the study.

Improving Prediction Accuracy of “Central Line-Associated Blood Stream Infections” Using Data Mining Models

PubMed Central

Noaman, Amin Y.; Jamjoom, Arwa; Al-Abdullah, Nabeela; Nasir, Mahreen; Ali, Anser G.

2017-01-01

Prediction of nosocomial infections among patients is an important part of clinical surveillance programs to enable the related personnel to take preventive actions in advance. Designing a clinical surveillance program with capability of predicting nosocomial infections is a challenging task due to several reasons, including high dimensionality of medical data, heterogenous data representation, and special knowledge required to extract patterns for prediction. In this paper, we present details of six data mining methods implemented using cross industry standard process for data mining to predict central line-associated blood stream infections. For our study, we selected datasets of healthcare-associated infections from US National Healthcare Safety Network and consumer survey data from Hospital Consumer Assessment of Healthcare Providers and Systems. Our experiments show that central line-associated blood stream infections (CLABSIs) can be successfully predicted using AdaBoost method with an accuracy up to 89.7%. This will help in implementing effective clinical surveillance programs for infection control, as well as improving the accuracy detection of CLABSIs. Also, this reduces patients' hospital stay cost and maintains patients' safety. PMID:29085836

Open Rotor Noise Prediction at NASA Langley - Capabilities, Research and Development

NASA Technical Reports Server (NTRS)

Farassat, Fereidoun

2010-01-01

The high fuel prices of recent years have caused the operating cost of the airlines to soar. In an effort to bring down the fuel consumption, the major aircraft engine manufacturers are now taking a fresh look at open rotors for the propulsion of future airliners. Open rotors, also known as propfans or unducted fans, can offer up to 30 per cent improvement in efficiency compared to high bypass engines of 1980 vintage currently in use in most civilian aircraft. NASA Langley researchers have contributed significantly to the development of aeroacoustic technology of open rotors. This report discusses the current noise prediction technology at Langley and reviews the input data requirements, strengths and limitations of each method as well as the associated problems in need of attention by the researchers. We present a brief history of research on the aeroacoustics of rotating blade machinery at Langley Research Center. We then discuss the available noise prediction codes for open rotors developed at NASA Langley and their capabilities. In particular, we present the two useful formulations used for the computation of noise from subsonic and supersonic surfaces. Here we discuss the open rotor noise prediction codes ASSPIN and one based on Ffowcs Williams-Hawkings equation with penetrable data surface (FW - Hpds). The scattering of sound from surfaces near the rotor are calculated using the fast scattering code (FSC) which is also discussed in this report. Plans for further improvements of these codes are given.

Predicting the payload capability of cable logging systems including the effect of partial suspension

Treesearch

Gary D. Falk

1981-01-01

A systematic procedure for predicting the payload capability of running, live, and standing skylines is presented. Three hand-held calculator programs are used to predict payload capability that includes the effect of partial suspension. The programs allow for predictions for downhill yarding and for yarding away from the yarder. The equations and basic principles...

Serum peroxiredoxin 4: a marker of oxidative stress associated with mortality in type 2 diabetes (ZODIAC-28).

PubMed

Gerrits, Esther G; Alkhalaf, Alaa; Landman, Gijs W D; van Hateren, Kornelis J J; Groenier, Klaas H; Struck, Joachim; Schulte, Janin; Gans, Reinold O B; Bakker, Stephan J L; Kleefstra, Nanne; Bilo, Henk J G

2014-01-01

Oxidative stress plays an underlying pathophysiologic role in the development of diabetes complications. The aim of this study was to investigate peroxiredoxin 4 (Prx4), a proposed novel biomarker of oxidative stress, and its association with and capability as a biomarker in predicting (cardiovascular) mortality in type 2 diabetes mellitus. Prx4 was assessed in baseline serum samples of 1161 type 2 diabetes patients. Cox proportional hazard models were used to evaluate the relationship between Prx4 and (cardiovascular) mortality. Risk prediction capabilities of Prx4 for (cardiovascular) mortality were assessed with Harrell's C statistic, the integrated discrimination improvement and net reclassification improvement. Mean age was 67 and the median diabetes duration was 4.0 years. After a median follow-up period of 5.8 years, 327 patients died; 137 cardiovascular deaths. Prx4 was associated with (cardiovascular) mortality. The Cox proportional hazard models added the variables: Prx4 (model 1); age and gender (model 2), and BMI, creatinine, smoking, diabetes duration, systolic blood pressure, cholesterol-HDL ratio, history of macrovascular complications, and albuminuria (model 3). Hazard ratios (HR) (95% CI) for cardiovascular mortality were 1.93 (1.57 - 2.38), 1.75 (1.39 - 2.20), and 1.63 (1.28 - 2.09) for models 1, 2 and 3, respectively. HR for all-cause mortality were 1.73 (1.50 - 1.99), 1.50 (1.29 - 1.75), and 1.44 (1.23 - 1.67) for models 1, 2 and 3, respectively. Addition of Prx4 to the traditional risk factors slightly improved risk prediction of (cardiovascular) mortality. Prx4 is independently associated with (cardiovascular) mortality in type 2 diabetes patients. After addition of Prx4 to the traditional risk factors, there was a slightly improvement in risk prediction of (cardiovascular) mortality in this patient group.

Enumerating bone marrow blasts from nonerythroid cellularity improves outcome prediction in myelodysplastic syndromes and permits a better definition of the intermediate risk category of the Revised International Prognostic Scoring System (IPSS-R).

PubMed

Calvo, Xavier; Arenillas, Leonor; Luño, Elisa; Senent, Leonor; Arnan, Montserrat; Ramos, Fernando; Pedro, Carme; Tormo, Mar; Montoro, Julia; Díez-Campelo, María; Blanco, María Laura; Arrizabalaga, Beatriz; Xicoy, Blanca; Bonanad, Santiago; Jerez, Andrés; Nomdedeu, Meritxell; Ferrer, Ana; Sanz, Guillermo F; Florensa, Lourdes

2017-07-01

The Revised International Prognostic Scoring System (IPSS-R) has been recognized as the score with the best outcome prediction capability in MDS, but this brought new concerns about the accurate prognostication of patients classified into the intermediate risk category. The correct enumeration of blasts is essential in prognostication of MDS. Recent data evidenced that considering blasts from nonerythroid cellularity (NECs) improves outcome prediction in the context of IPSS and WHO classification. We assessed the percentage of blasts from total nucleated cells (TNCs) and NECs in 3924 MDS patients from the GESMD, 498 of whom were MDS with erythroid predominance (MDS-E). We assessed if calculating IPSS-R by enumerating blasts from NECs improves prognostication of MDS. Twenty-four percent of patients classified into the intermediate category were reclassified into higher-risk categories and showed shorter overall survival (OS) and time to AML evolution than those who remained into the intermediate one. Likewise, a better distribution of patients was observed, since lower-risk patients showed longer survivals than previously whereas higher-risk ones maintained the outcome expected in this poor prognostic group (median OS < 20 months). Furthermore, our approach was particularly useful for detecting patients at risk of dying with AML. Regarding MDS-E, 51% patients classified into the intermediate category were reclassified into higher-risk ones and showed shorter OS and time to AML. In this subgroup of MDS, IPSS-R was capable of splitting our series in five groups with significant differences in OS only when blasts were assessed from NECs. In conclusion, our easy-applicable approach improves prognostic assessment of MDS patients. © 2017 Wiley Periodicals, Inc.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giuliani, Sarah E; Frank, Ashley M; Corgliano, Danielle M

Abstract Background: Transporter proteins are one of an organism s primary interfaces with the environment. The expressed set of transporters mediates cellular metabolic capabilities and influences signal transduction pathways and regulatory networks. The functional annotation of most transporters is currently limited to general classification into families. The development of capabilities to map ligands with specific transporters would improve our knowledge of the function of these proteins, improve the annotation of related genomes, and facilitate predictions for their role in cellular responses to environmental changes. Results: To improve the utility of the functional annotation for ABC transporters, we expressed and purifiedmore » the set of solute binding proteins from Rhodopseudomonas palustris and characterized their ligand-binding specificity. Our approach utilized ligand libraries consisting of environmental and cellular metabolic compounds, and fluorescence thermal shift based high throughput ligand binding screens. This process resulted in the identification of specific binding ligands for approximately 64% of the purified and screened proteins. The collection of binding ligands is representative of common functionalities associated with many bacterial organisms as well as specific capabilities linked to the ecological niche occupied by R. palustris. Conclusion: The functional screen identified specific ligands that bound to ABC transporter periplasmic binding subunits from R. palustris. These assignments provide unique insight for the metabolic capabilities of this organism and are consistent with the ecological niche of strain isolation. This functional insight can be used to improve the annotation of related organisms and provides a route to evaluate the evolution of this important and diverse group of transporter proteins.« less

Can we predict age at natural menopause using ovarian reserve tests or mother's age at menopause? A systematic literature review.

PubMed

Depmann, Martine; Broer, Simone L; van der Schouw, Yvonne T; Tehrani, Fahimeh R; Eijkemans, Marinus J; Mol, Ben W; Broekmans, Frank J

2016-02-01

This review aimed to appraise data on prediction of age at natural menopause (ANM) based on antimüllerian hormone (AMH), antral follicle count (AFC), and mother's ANM to evaluate clinical usefulness and to identify directions for further research. We conducted three systematic reviews of the literature to identify studies of menopause prediction based on AMH, AFC, or mother's ANM, corrected for baseline age. Six studies selected in the search for AMH all consistently demonstrated AMH as being capable of predicting ANM (hazard ratio, 5.6-9.2). The sole study reporting on mother's ANM indicated that AMH was capable of predicting ANM (hazard ratio, 9.1-9.3). Two studies provided analyses of AFC and yielded conflicting results, making this marker less strong. AMH is currently the most promising marker for ANM prediction. The predictive capacity of mother's ANM demonstrated in a single study makes this marker a promising contributor to AMH for menopause prediction. Models, however, do not predict the extremes of menopause age very well and have wide prediction interval. These markers clearly need improvement before they can be used for individual prediction of menopause in the clinical setting. Moreover, potential limitations for such use include variations in AMH assays used and a lack of correction for factors or diseases affecting AMH levels or ANM. Future studies should include women of a broad age range (irrespective of cycle regularity) and should base predictions on repeated AMH measurements. Furthermore, currently unknown candidate predictors need to be identified.

High Performance Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System at NASA/GSFC

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Kumar, S. V.; Santanello, J. A.; Tian, Y.; Rodell, M.; Mocko, D.; Reichle, R.

2008-12-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters-Lidard et al., 2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. The LIS software was the co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts - North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell et al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of these systems, now use specific configurations of the LIS software in their current implementations. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through 'plugins'. In addition to these capabilities, LIS has also been demonstrated for parameter estimation (Peters-Lidard et al., 2008; Santanello et al., 2007) and data assimilation (Kumar et al., 2008). Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, land data assimilation and parameter estimation will be presented.

Gas House Autonomous System Monitoring

NASA Technical Reports Server (NTRS)

Miller, Luke; Edsall, Ashley

2015-01-01

Gas House Autonomous System Monitoring (GHASM) will employ Integrated System Health Monitoring (ISHM) of cryogenic fluids in the High Pressure Gas Facility at Stennis Space Center. The preliminary focus of development incorporates the passive monitoring and eventual commanding of the Nitrogen System. ISHM offers generic system awareness, adept at using concepts rather than specific error cases. As an enabler for autonomy, ISHM provides capabilities inclusive of anomaly detection, diagnosis, and abnormality prediction. Advancing ISHM and Autonomous Operation functional capabilities enhances quality of data, optimizes safety, improves cost effectiveness, and has direct benefits to a wide spectrum of aerospace applications.

Machine learning for outcome prediction of acute ischemic stroke post intra-arterial therapy.

PubMed

Asadi, Hamed; Dowling, Richard; Yan, Bernard; Mitchell, Peter

2014-01-01

Stroke is a major cause of death and disability. Accurately predicting stroke outcome from a set of predictive variables may identify high-risk patients and guide treatment approaches, leading to decreased morbidity. Logistic regression models allow for the identification and validation of predictive variables. However, advanced machine learning algorithms offer an alternative, in particular, for large-scale multi-institutional data, with the advantage of easily incorporating newly available data to improve prediction performance. Our aim was to design and compare different machine learning methods, capable of predicting the outcome of endovascular intervention in acute anterior circulation ischaemic stroke. We conducted a retrospective study of a prospectively collected database of acute ischaemic stroke treated by endovascular intervention. Using SPSS®, MATLAB®, and Rapidminer®, classical statistics as well as artificial neural network and support vector algorithms were applied to design a supervised machine capable of classifying these predictors into potential good and poor outcomes. These algorithms were trained, validated and tested using randomly divided data. We included 107 consecutive acute anterior circulation ischaemic stroke patients treated by endovascular technique. Sixty-six were male and the mean age of 65.3. All the available demographic, procedural and clinical factors were included into the models. The final confusion matrix of the neural network, demonstrated an overall congruency of ∼ 80% between the target and output classes, with favourable receiving operative characteristics. However, after optimisation, the support vector machine had a relatively better performance, with a root mean squared error of 2.064 (SD: ± 0.408). We showed promising accuracy of outcome prediction, using supervised machine learning algorithms, with potential for incorporation of larger multicenter datasets, likely further improving prediction. Finally, we propose that a robust machine learning system can potentially optimise the selection process for endovascular versus medical treatment in the management of acute stroke.

Improving in vitro to in vivo extrapolation (IVIVE) by incorporation of toxicokinetic measurements: a case study with lindane induced seizures.

EPA Science Inventory

In vitro toxicokinetic assessments are needed to maximize the capability of in vitro toxicity assays to predict in vivo outcomes. The purpose of this study was to determine the in vitro distribution of lindane, a non-competitive GABAA receptor antagonist, in rat primary neocortic...

Energy, atmospheric chemistry, and global climate

NASA Technical Reports Server (NTRS)

Levine, Joel S.

1991-01-01

Global atmospheric changes due to ozone destruction and the greenhouse effect are discussed. The work of the Intergovernmental Panel on Climate Change is reviewed, including its judgements regarding global warming and its recommendations for improving predictive capability. The chemistry of ozone destruction and the global atmospheric budget of nitrous oxide are reviewed, and the global sources of nitrous oxide are described.

Advanced Multi-Moment Microphysics for Precipitation and Tropical Cyclone Forecast Improvement within COAMPS

DTIC Science & Technology

2011-09-30

capable of predicting up to three moments of hydrometeor particle size distributions (PSDs) inside the Navy’s Coupled Ocean/Atmosphere Mesoscale...Sobash, P. T. Marsh, A. R. Dean, M. Xue, F. Kong, K. W. Thomas, J. Du, D. R. Novak, F. E. Barthold, M. J. Bodner, J. J. Levit , C. B. Entwistle, T. Jensen

A review of methods for predicting air pollution dispersion

NASA Technical Reports Server (NTRS)

Mathis, J. J., Jr.; Grose, W. L.

1973-01-01

Air pollution modeling, and problem areas in air pollution dispersion modeling were surveyed. Emission source inventory, meteorological data, and turbulent diffusion are discussed in terms of developing a dispersion model. Existing mathematical models of urban air pollution, and highway and airport models are discussed along with their limitations. Recommendations for improving modeling capabilities are included.

Ceramic Matrix Composites (CMC) Life Prediction Development

NASA Technical Reports Server (NTRS)

Levine, Stanley R.; Verrilli, Michael J.; Thomas, David J.; Halbig, Michael C.; Calomino, Anthony M.; Ellis, John R.; Opila, Elizabeth J.

1990-01-01

Advanced launch systems will very likely incorporate fiber reinforced ceramic matrix composites (CMC) in critical propulsion and airframe components. The use of CMC will save weight, increase operating margin, safety and performance, and improve reuse capability. For reusable and single mission use, accurate life prediction is critical to success. The tools to accomplish this are immature and not oriented toward the behavior of carbon fiber reinforced silicon carbide (C/SiC), the primary system of interest for many applications. This paper describes an approach and progress made to satisfy the need to develop an integrated life prediction system that addresses mechanical durability and environmental degradation.

Propeller flow visualization techniques

NASA Technical Reports Server (NTRS)

Stefko, G. L.; Paulovich, F. J.; Greissing, J. P.; Walker, E. D.

1982-01-01

Propeller flow visualization techniques were tested. The actual operating blade shape as it determines the actual propeller performance and noise was established. The ability to photographically determine the advanced propeller blade tip deflections, local flow field conditions, and gain insight into aeroelastic instability is demonstrated. The analytical prediction methods which are being developed can be compared with experimental data. These comparisons contribute to the verification of these improved methods and give improved capability for designing future advanced propellers with enhanced performance and noise characteristics.

The Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) Toolset

NASA Technical Reports Server (NTRS)

Zank, G. P.; Spann, J.

2014-01-01

We outline a plan to develop a physics based predictive toolset RISCS to describe the interplanetary energetic particle and radiation environment throughout the inner heliosphere, including at the Earth. To forecast and "nowcast" the radiation environment requires the fusing of three components: 1) the ability to provide probabilities for incipient solar activity; 2) the use of these probabilities and daily coronal and solar wind observations to model the 3D spatial and temporal heliosphere, including magnetic field structure and transients, within 10 AU; and 3) the ability to model the acceleration and transport of energetic particles based on current and anticipated coronal and heliospheric conditions. We describe how to address 1) - 3) based on our existing, well developed, and validated codes and models. The goal of RISCS toolset is to provide an operational forecast and "nowcast" capability that will a) predict solar energetic particle (SEP) intensities; b) spectra for protons and heavy ions; c) predict maximum energies and their duration; d) SEP composition; e) cosmic ray intensities, and f) plasma parameters, including shock arrival times, strength and obliquity at any given heliospheric location and time. The toolset would have a 72 hour predicative capability, with associated probabilistic bounds, that would be updated hourly thereafter to improve the predicted event(s) and reduce the associated probability bounds. The RISCS toolset would be highly adaptable and portable, capable of running on a variety of platforms to accommodate various operational needs and requirements.

Evaluating the Capabilities of Soil Enthalpy, Soil Moisture and Soil Temperature in Predicting Seasonal Precipitation

NASA Astrophysics Data System (ADS)

Zhao, Changyu; Chen, Haishan; Sun, Shanlei

2018-04-01

Soil enthalpy ( H) contains the combined effects of both soil moisture ( w) and soil temperature ( T) in the land surface hydrothermal process. In this study, the sensitivities of H to w and T are investigated using the multi-linear regression method. Results indicate that T generally makes positive contributions to H, while w exhibits different (positive or negative) impacts due to soil ice effects. For example, w negatively contributes to H if soil contains more ice; however, after soil ice melts, w exerts positive contributions. In particular, due to lower w interannual variabilities in the deep soil layer (i.e., the fifth layer), H is more sensitive to T than to w. Moreover, to compare the potential capabilities of H, w and T in precipitation ( P) prediction, the Huanghe-Huaihe Basin (HHB) and Southeast China (SEC), with similar sensitivities of H to w and T, are selected. Analyses show that, despite similar spatial distributions of H-P and T-P correlation coefficients, the former values are always higher than the latter ones. Furthermore, H provides the most effective signals for P prediction over HHB and SEC, i.e., a significant leading correlation between May H and early summer (June) P. In summary, H, which integrates the effects of T and w as an independent variable, has greater capabilities in monitoring land surface heating and improving seasonal P prediction relative to individual land surface factors (e.g., T and w).

3D Protein structure prediction with genetic tabu search algorithm

PubMed Central

2010-01-01

Background Protein structure prediction (PSP) has important applications in different fields, such as drug design, disease prediction, and so on. In protein structure prediction, there are two important issues. The first one is the design of the structure model and the second one is the design of the optimization technology. Because of the complexity of the realistic protein structure, the structure model adopted in this paper is a simplified model, which is called off-lattice AB model. After the structure model is assumed, optimization technology is needed for searching the best conformation of a protein sequence based on the assumed structure model. However, PSP is an NP-hard problem even if the simplest model is assumed. Thus, many algorithms have been developed to solve the global optimization problem. In this paper, a hybrid algorithm, which combines genetic algorithm (GA) and tabu search (TS) algorithm, is developed to complete this task. Results In order to develop an efficient optimization algorithm, several improved strategies are developed for the proposed genetic tabu search algorithm. The combined use of these strategies can improve the efficiency of the algorithm. In these strategies, tabu search introduced into the crossover and mutation operators can improve the local search capability, the adoption of variable population size strategy can maintain the diversity of the population, and the ranking selection strategy can improve the possibility of an individual with low energy value entering into next generation. Experiments are performed with Fibonacci sequences and real protein sequences. Experimental results show that the lowest energy obtained by the proposed GATS algorithm is lower than that obtained by previous methods. Conclusions The hybrid algorithm has the advantages from both genetic algorithm and tabu search algorithm. It makes use of the advantage of multiple search points in genetic algorithm, and can overcome poor hill-climbing capability in the conventional genetic algorithm by using the flexible memory functions of TS. Compared with some previous algorithms, GATS algorithm has better performance in global optimization and can predict 3D protein structure more effectively. PMID:20522256

Implementation of the Land, Atmosphere Near Real-Time Capability for EOS (LANCE)

NASA Technical Reports Server (NTRS)

Michael, Karen; Murphy, Kevin; Lowe, Dawn; Masuoka, Edward; Vollmer, Bruce; Tilmes, Curt; Teague, Michael; Ye, Gang; Maiden, Martha; Goodman, H. Michael;

Self-Aware Vehicles: Mission and Performance Adaptation to System Health

NASA Technical Reports Server (NTRS)

Gregory, Irene M.; Leonard, Charles; Scotti, Stephen J.

2016-01-01

Advances in sensing (miniaturization, distributed sensor networks) combined with improvements in computational power leading to significant gains in perception, real-time decision making/reasoning and dynamic planning under uncertainty as well as big data predictive analysis have set the stage for realization of autonomous system capability. These advances open the design and operating space for self-aware vehicles that are able to assess their own capabilities and adjust their behavior to either complete the assigned mission or to modify the mission to reflect their current capabilities. This paper discusses the self-aware vehicle concept and associated technologies necessary for full exploitation of the concept. A self-aware aircraft, spacecraft or system is one that is aware of its internal state, has situational awareness of its environment, can assess its capabilities currently and project them into the future, understands its mission objectives, and can make decisions under uncertainty regarding its ability to achieve its mission objectives.

Evaluation of APREQCFR Coordination Procedures for Charlotte Douglas International Airport

NASA Technical Reports Server (NTRS)

Stevens, Lindsay K. S.; Parke, Bonny K.; Chevalley, Eric; Lee, Hanbong; Martin, Lynne H.; Jobe, Kimberly K.; Verma, Savita A.; Dulchinos, Victoria Lee

2017-01-01

NASA has been collaborating with the Federal Aviation Administration (FAA) and aviation industry partners to develop and demonstrate new concepts and technologies for the Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the goal of The IADS capabilities in the ATD-2 project is to increase predictability and increase throughput via improving TMI compliance. The IADS capabilities that will impact TMI compliance are built upon previous NASA research, the Precision Departure Release Capability (PDRC). The proposed paper will evaluate the APREQCFR process between ATC Tower and Center and information sharing between ATC Tower and the airline Ramp tower. Subjective measures collected from the HITL surveys (e.g., workload, situational awareness, acceptability, usability) and performance metrics such as TMI, TMAT, and pushback advisory compliance from APREQCFR flights and will be reported.

AFRPL Graphite Performance Prediction Program. Improved Capability for the Design and Ablation Performance Prediction of Advanced Air Force Solid Propellant Rocket Nozzles

DTIC Science & Technology

1976-12-01

corrosive attack by both acids and alkali and, in addition, is provided with a special Dynel veil for protection against fluoride attack. 3.1.4...throat region, namely , the entrance, center, and exit. In addition, at each station, the diameters were determined at two angular positions 90° apart. The...characterization test matrix. 3.2.1.1 Rocket Motor Environments Rocket motor environments were based on three advanced MX propellants, namely , * XLDB * HTPB * PEG

[Arterial pressure curve and fluid status].

PubMed

Pestel, G; Fukui, K

2009-04-01

Fluid optimization is a major contributor to improved outcome in patients. Unfortunately, anesthesiologists are often in doubt whether an additional fluid bolus will improve the hemodynamics of the patient or not as excess fluid may even jeopardize the condition. This article discusses physiological concepts of liberal versus restrictive fluid management followed by a discussion on the respective capabilities of various monitors to predict fluid responsiveness. The parameter difference in pulse pressure (dPP), derived from heart-lung interaction in mechanically ventilated patients is discussed in detail. The dPP cutoff value of 13% to predict fluid responsiveness is presented together with several assessment techniques of dPP. Finally, confounding variables on dPP measurements, such as ventilation parameters, pneumoperitoneum and use of norepinephrine are also mentioned.

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.

Development of a Higher Fidelity Model for the Cascade Distillation Subsystem (CDS)

NASA Technical Reports Server (NTRS)

Perry, Bruce; Anderson, Molly

2014-01-01

Significant improvements have been made to the ACM model of the CDS, enabling accurate predictions of dynamic operations with fewer assumptions. The model has been utilized to predict how CDS performance would be impacted by changing operating parameters, revealing performance trade-offs and possibilities for improvement. CDS efficiency is driven by the THP coefficient of performance, which in turn is dependent on heat transfer within the system. Based on the remaining limitations of the simulation, priorities for further model development include: center dot Relaxing the assumption of total condensation center dot Incorporating dynamic simulation capability for the buildup of dissolved inert gasses in condensers center dot Examining CDS operation with more complex feeds center dot Extending heat transfer analysis to all surfaces

The role of thermal and lubricant boundary layers in the transient thermal analysis of spur gears

NASA Technical Reports Server (NTRS)

El-Bayoumy, L. E.; Akin, L. S.; Townsend, D. P.; Choy, F. C.

1989-01-01

An improved convection heat-transfer model has been developed for the prediction of the transient tooth surface temperature of spur gears. The dissipative quality of the lubricating fluid is shown to be limited to the capacity extent of the thermal boundary layer. This phenomenon can be of significance in the determination of the thermal limit of gears accelerating to the point where gear scoring occurs. Steady-state temperature prediction is improved considerably through the use of a variable integration time step that substantially reduces computer time. Computer-generated plots of temperature contours enable the user to animate the propagation of the thermal wave as the gears come into and out of contact, thus contributing to better understanding of this complex problem. This model has a much better capability at predicting gear-tooth temperatures than previous models.

Improved Geothermometry Through Multivariate Reaction-path Modeling and Evaluation of Geomicrobiological Influences on Geochemical Temperature Indicators: Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mattson, Earl; Smith, Robert; Fujita, Yoshiko

2015-03-01

The project was aimed at demonstrating that the geothermometric predictions can be improved through the application of multi-element reaction path modeling that accounts for lithologic and tectonic settings, while also accounting for biological influences on geochemical temperature indicators. The limited utilization of chemical signatures by individual traditional geothermometer in the development of reservoir temperature estimates may have been constraining their reliability for evaluation of potential geothermal resources. This project, however, was intended to build a geothermometry tool which can integrate multi-component reaction path modeling with process-optimization capability that can be applied to dilute, low-temperature water samples to consistently predict reservoirmore » temperature within ±30 °C. The project was also intended to evaluate the extent to which microbiological processes can modulate the geochemical signals in some thermal waters and influence the geothermometric predictions.« less

Optimization of a novel biophysical model using large scale in vivo antisense hybridization data displays improved prediction capabilities of structurally accessible RNA regions.

PubMed

Vazquez-Anderson, Jorge; Mihailovic, Mia K; Baldridge, Kevin C; Reyes, Kristofer G; Haning, Katie; Cho, Seung Hee; Amador, Paul; Powell, Warren B; Contreras, Lydia M

2017-05-19

Current approaches to design efficient antisense RNAs (asRNAs) rely primarily on a thermodynamic understanding of RNA-RNA interactions. However, these approaches depend on structure predictions and have limited accuracy, arguably due to overlooking important cellular environment factors. In this work, we develop a biophysical model to describe asRNA-RNA hybridization that incorporates in vivo factors using large-scale experimental hybridization data for three model RNAs: a group I intron, CsrB and a tRNA. A unique element of our model is the estimation of the availability of the target region to interact with a given asRNA using a differential entropic consideration of suboptimal structures. We showcase the utility of this model by evaluating its prediction capabilities in four additional RNAs: a group II intron, Spinach II, 2-MS2 binding domain and glgC 5΄ UTR. Additionally, we demonstrate the applicability of this approach to other bacterial species by predicting sRNA-mRNA binding regions in two newly discovered, though uncharacterized, regulatory RNAs. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2015-10-01

Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

KSC-2014-2842

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Preparations are underway to move a section of the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, onto a transportation cradle in the Building 836 high bay on south Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3161

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The transportation trailer carrying the second stage, or upper stage, of a United Launch Alliance Delta II rocket backs into the Building 836 hangar on south Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit from Vandenberg's Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2833

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Workers hoist the lid off the transportation trailer containing the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3163

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – Preparations are underway to lift the second stage, or upper stage, of a United Launch Alliance Delta II rocket from its transportation trailer in the Building 836 hangar on south Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit from Vandenberg's Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2838

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Workers lift a section of the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, from a transportation trailer in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2844

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Workers move a section of the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, from a hardware dolly toward a transportation cradle in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians mount NASA's Soil Moisture Active Passive, or SMAP, spacecraft on a work platform. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2015-1226

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Kim Shiflett

KSC-2015-1236

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://www.nasa.gov/smap. Photo credit: NASA/Randy Beaudoin

KSC-2015-1227

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Kim Shiflett

KSC-2015-1228

NASA Image and Video Library

2015-01-29

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Kim Shiflett

KSC-2015-1225

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Kim Shiflett

KSC-2015-1235

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://www.nasa.gov/smap. Photo credit: NASA/Randy Beaudoin

KSC-2015-1238

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://www.nasa.gov/smap. Photo credit: NASA/Randy Beaudoin

KSC-2014-3180

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The second stage, or upper stage, of a United Launch Alliance Delta II rocket winds its way along the roads from Building 836 to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2015-1234

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://www.nasa.gov/smap. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians rotate NASA's Soil Moisture Active Passive, or SMAP, spacecraft to begin processing. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-2840

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Workers prepare to rotate a section of the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, in a lifting device in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Lift to CR

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians have rotated NASA's Soil Moisture Active Passive, or SMAP, spacecraft to begin processing. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-3186

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The second stage, or upper stage, of a United Launch Alliance Delta II rocket arrives at the Horizontal Processing Facility near the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians inspect NASA's Soil Moisture Active Passive, or SMAP, spacecraft. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians begin processing of NASA's Soil Moisture Active Passive, or SMAP, spacecraft. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-2837

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Workers prepare to lift the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, from a transportation trailer in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3184

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The second stage, or upper stage, of a United Launch Alliance Delta II rocket arrives at Space Launch Complex 2 on Vandenberg Air Force Base in California where it will undergo preparations for launch in the Horizontal Processing Facility. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, an engineer inspects NASA's Soil Moisture Active Passive, or SMAP, spacecraft. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians remove a protective covering from NASA's Soil Moisture Active Passive, or SMAP, spacecraft. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2015-1224

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Kim Shiflett

KSC-2014-3326

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, crosses a railroad bridge on its move from the Building 836 hangar to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/U.S. Air Force 30th Space Wing

KSC-2014-2832

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – The transportation trailer containing the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, arrives in the Building 836 high bay on south Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2834

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – The lid is lifted from the transportation trailer containing the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Arrives at Astrotech

NASA Image and Video Library

2014-10-14

Workers push the pallet supporting the transportation container protecting NASA's Soil Moisture Active Passive, or SMAP, spacecraft into the Astrotech payload processing facility on Vandenberg Air Force Base in California. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-2836

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – The lid is removed from the transportation trailer containing the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3179

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The second stage, or upper stage, of a United Launch Alliance Delta II rocket is on its way from Building 836 on south Vandenberg Air Force Base in California to the Horizontal Processing Facility at Space Launch Complex 2. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Lift to CR

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians prepare a component of NASA's Soil Moisture Active Passive, or SMAP, spacecraft for a lift by a crane. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

SMAP Lift to CR

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians rotate NASA's Soil Moisture Active Passive, or SMAP, spacecraft to begin processing. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians use a crane to move NASA's Soil Moisture Active Passive, or SMAP, spacecraft. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-3182

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The second stage, or upper stage, of a United Launch Alliance Delta II rocket is towed along the roadway from Building 836 to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2843

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – A section of the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, secured to a lifting device, glides across the floor of the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3181

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – A security detail accompanies the second stage, or upper stage, of a United Launch Alliance Delta II rocket on its move from Building 836 to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3255

NASA Image and Video Library

2014-07-16

VANDENBERG AIR FORCE BASE, Calif. – It takes teamwork to lift the nozzle for the second stage of a United Launch Alliance Delta II rocket from its work stand in the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. The Delta II will be used to loft NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians have rotated NASA's Soil Moisture Active Passive, or SMAP, spacecraft to begin processing. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-3288

NASA Image and Video Library

2014-07-23

VANDENBERG AIR FORCE BASE, Calif. – The U.S. Air Force 30th Security Forces Squadron is responsible for the safety of the first stage of the United Launch Alliance Delta II rocket for NASA's Soil Moisture Active Passive mission, or SMAP, on its move from the Building 836 hangar to the Horizontal Processing Facility at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3178

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The second stage, or upper stage, of a United Launch Alliance Delta II rocket begins its journey from Building 836 on south Vandenberg Air Force Base in California to the Horizontal Processing Facility at Space Launch Complex 2. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians prepare a component of NASA's Soil Moisture Active Passive, or SMAP, spacecraft for a lift by a crane. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

SMAP Lift to CR

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians remove a protective covering from NASA's Soil Moisture Active Passive, or SMAP, spacecraft. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

SMAP Spacecraft Rotate & Placed on Fixture

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, processing has begun on NASA's Soil Moisture Active Passive, or SMAP, spacecraft. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2015-1223

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Kim Shiflett

SMAP Lift to CR

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians inspect NASA's Soil Moisture Active Passive, or SMAP, spacecraft. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-2841

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Workers rotate a section of the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, in a lifting device in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Lift to CR

NASA Image and Video Library

2014-10-16

Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians use a crane to move a component of NASA's Soil Moisture Active Passive, or SMAP, spacecraft for a lift by a crane. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

SMAP Spacecraft Arrives at Astrotech

NASA Image and Video Library

2014-10-14

The truck transporting NASA's Soil Moisture Active Passive, or SMAP, spacecraft arrives at the Astrotech payload processing facility on Vandenberg Air Force Base in California. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

High fidelity studies of exploding foil initiator bridges, Part 2: Experimental results

NASA Astrophysics Data System (ADS)

Neal, William; Bowden, Mike

2017-01-01

Simulations of high voltage detonators, such as Exploding Bridgewire (EBW) and Exploding Foil Initiators (EFI), have historically been simple, often empirical, one-dimensional models capable of predicting parameters such as current, voltage, and in the case of EFIs, flyer velocity. Experimental methods have correspondingly generally been limited to the same parameters. With the advent of complex, first principles magnetohydrodynamic codes such as ALEGRA MHD, it is now possible to simulate these components in three dimensions and predict greater range of parameters than before. A significant improvement in experimental capability was therefore required to ensure these simulations could be adequately verified. In this second paper of a three part study, data is presented from a flexible foil EFI header experiment. This study has shown that there is significant bridge expansion before time of peak voltage and that heating within the bridge material is spatially affected by the microstructure of the metal foil.

SMAP Spacecraft Offload

NASA Image and Video Library

2014-10-15

NASA's Soil Moisture Active Passive, or SMAP, spacecraft is delivered by truck from the Jet Propulsion Laboratory in Pasadena, California, to the Astrotech payload processing facility on Vandenberg Air Force Base in California. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-3461

NASA Image and Video Library

2014-08-07

VANDENBERG AIR FORCE BASE, Calif. – The half sections of the 10-foot-diameter fairing for NASA's Soil Moisture Active Passive mission, or SMAP, are delivered to the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for no earlier than November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3462

NASA Image and Video Library

2014-08-07

VANDENBERG AIR FORCE BASE, Calif. – The half sections of the 10-foot-diameter fairing for NASA's Soil Moisture Active Passive mission, or SMAP, arrive at the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for no earlier than November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2015-1229

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Kim Shiflett

KSC-2015-1233

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://www.nasa.gov/smap. Photo credit: NASA/Randy Beaudoin

KSC-2015-1237

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The launch gantry is rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at Space Launch Complex 2 on Vandenberg Air Force Base in California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://www.nasa.gov/smap. Photo credit: NASA/Randy Beaudoin

Status of Computational Aerodynamic Modeling Tools for Aircraft Loss-of-Control

NASA Technical Reports Server (NTRS)

Frink, Neal T.; Murphy, Patrick C.; Atkins, Harold L.; Viken, Sally A.; Petrilli, Justin L.; Gopalarathnam, Ashok; Paul, Ryan C.

2016-01-01

A concerted effort has been underway over the past several years to evolve computational capabilities for modeling aircraft loss-of-control under the NASA Aviation Safety Program. A principal goal has been to develop reliable computational tools for predicting and analyzing the non-linear stability & control characteristics of aircraft near stall boundaries affecting safe flight, and for utilizing those predictions for creating augmented flight simulation models that improve pilot training. Pursuing such an ambitious task with limited resources required the forging of close collaborative relationships with a diverse body of computational aerodynamicists and flight simulation experts to leverage their respective research efforts into the creation of NASA tools to meet this goal. Considerable progress has been made and work remains to be done. This paper summarizes the status of the NASA effort to establish computational capabilities for modeling aircraft loss-of-control and offers recommendations for future work.

KSC-2014-3162

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The lid is removed from the transportation trailer containing the second stage, or upper stage, of a United Launch Alliance Delta II rocket in the Building 836 hangar on south Vandenberg Air Force Base in California. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit from Vandenberg's Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2835

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – A worker steadies the lid of the transportation trailer containing the fairing for NASA's Soil Moisture Active Passive mission, or SMAP, in the Building 836 high bay on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

A Robust Compositional Architecture for Autonomous Systems

NASA Technical Reports Server (NTRS)

Brat, Guillaume; Deney, Ewen; Farrell, Kimberley; Giannakopoulos, Dimitra; Jonsson, Ari; Frank, Jeremy; Bobby, Mark; Carpenter, Todd; Estlin, Tara

2006-01-01

Space exploration applications can benefit greatly from autonomous systems. Great distances, limited communications and high costs make direct operations impossible while mandating operations reliability and efficiency beyond what traditional commanding can provide. Autonomous systems can improve reliability and enhance spacecraft capability significantly. However, there is reluctance to utilizing autonomous systems. In part this is due to general hesitation about new technologies, but a more tangible concern is that of reliability of predictability of autonomous software. In this paper, we describe ongoing work aimed at increasing robustness and predictability of autonomous software, with the ultimate goal of building trust in such systems. The work combines state-of-the-art technologies and capabilities in autonomous systems with advanced validation and synthesis techniques. The focus of this paper is on the autonomous system architecture that has been defined, and on how it enables the application of validation techniques for resulting autonomous systems.

Morphodynamic data assimilation used to understand changing coasts

USGS Publications Warehouse

Plant, Nathaniel G.; Long, Joseph W.

2015-01-01

Morphodynamic data assimilation blends observations with model predictions and comes in many forms, including linear regression, Kalman filter, brute-force parameter estimation, variational assimilation, and Bayesian analysis. Importantly, data assimilation can be used to identify sources of prediction errors that lead to improved fundamental understanding. Overall, models incorporating data assimilation yield better information to the people who must make decisions impacting safety and wellbeing in coastal regions that experience hazards due to storms, sea-level rise, and erosion. We present examples of data assimilation associated with morphologic change. We conclude that enough morphodynamic predictive capability is available now to be useful to people, and that we will increase our understanding and the level of detail of our predictions through assimilation of observations and numerical-statistical models.

Improve SSME power balance model

NASA Technical Reports Server (NTRS)

Karr, Gerald R.

1992-01-01

Effort was dedicated to development and testing of a formal strategy for reconciling uncertain test data with physically limited computational prediction. Specific weaknesses in the logical structure of the current Power Balance Model (PBM) version are described with emphasis given to the main routing subroutines BAL and DATRED. Selected results from a variational analysis of PBM predictions are compared to Technology Test Bed (TTB) variational study results to assess PBM predictive capability. The motivation for systematic integration of uncertain test data with computational predictions based on limited physical models is provided. The theoretical foundation for the reconciliation strategy developed in this effort is presented, and results of a reconciliation analysis of the Space Shuttle Main Engine (SSME) high pressure fuel side turbopump subsystem are examined.

pKa predictions for proteins, RNAs, and DNAs with the Gaussian dielectric function using DelPhi pKa.

PubMed

Wang, Lin; Li, Lin; Alexov, Emil

2015-12-01

We developed a Poisson-Boltzmann based approach to calculate the pKa values of protein ionizable residues (Glu, Asp, His, Lys and Arg), nucleotides of RNA and single stranded DNA. Two novel features were utilized: the dielectric properties of the macromolecules and water phase were modeled via the smooth Gaussian-based dielectric function in DelPhi and the corresponding electrostatic energies were calculated without defining the molecular surface. We tested the algorithm by calculating pKa values for more than 300 residues from 32 proteins from the PPD dataset and achieved an overall RMSD of 0.77. Particularly, the RMSD of 0.55 was achieved for surface residues, while the RMSD of 1.1 for buried residues. The approach was also found capable of capturing the large pKa shifts of various single point mutations in staphylococcal nuclease (SNase) from pKa-cooperative dataset, resulting in an overall RMSD of 1.6 for this set of pKa's. Investigations showed that predictions for most of buried mutant residues of SNase could be improved by using higher dielectric constant values. Furthermore, an option to generate different hydrogen positions also improves pKa predictions for buried carboxyl residues. Finally, the pKa calculations on two RNAs demonstrated the capability of this approach for other types of biomolecules. © 2015 Wiley Periodicals, Inc.

Assessing the performance of MM/PBSA and MM/GBSA methods. 8. Predicting binding free energies and poses of protein-RNA complexes.

PubMed

Chen, Fu; Sun, Huiyong; Wang, Junmei; Zhu, Feng; Liu, Hui; Wang, Zhe; Lei, Tailong; Li, Youyong; Hou, Tingjun

2018-06-21

Molecular docking provides a computationally efficient way to predict the atomic structural details of protein-RNA interactions (PRI), but accurate prediction of the three-dimensional structures and binding affinities for PRI is still notoriously difficult, partly due to the unreliability of the existing scoring functions for PRI. MM/PBSA and MM/GBSA are more theoretically rigorous than most scoring functions for protein-RNA docking, but their prediction performance for protein-RNA systems remains unclear. Here, we systemically evaluated the capability of MM/PBSA and MM/GBSA to predict the binding affinities and recognize the near-native binding structures for protein-RNA systems with different solvent models and interior dielectric constants (ϵ in ). For predicting the binding affinities, the predictions given by MM/GBSA based on the minimized structures in explicit solvent and the GBGBn1 model with ϵ in = 2 yielded the highest correlation with the experimental data. Moreover, the MM/GBSA calculations based on the minimized structures in implicit solvent and the GBGBn1 model distinguished the near-native binding structures within the top 10 decoys for 118 out of the 149 protein-RNA systems (79.2%). This performance is better than all docking scoring functions studied here. Therefore, the MM/GBSA rescoring is an efficient way to improve the prediction capability of scoring functions for protein-RNA systems. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

A method of predicting the energy-absorption capability of composite subfloor beams

NASA Technical Reports Server (NTRS)

Farley, Gary L.

1987-01-01

A simple method of predicting the energy-absorption capability of composite subfloor beam structure was developed. The method is based upon the weighted sum of the energy-absorption capability of constituent elements of a subfloor beam. An empirical data base of energy absorption results from circular and square cross section tube specimens were used in the prediction capability. The procedure is applicable to a wide range of subfloor beam structure. The procedure was demonstrated on three subfloor beam concepts. Agreement between test and prediction was within seven percent for all three cases.

A research program for improving heat transfer prediction for the laminar to turbulent transition region of turbine vanes/blades

NASA Technical Reports Server (NTRS)

Simon, Frederick F.

1993-01-01

A program sponsored by NASA for the investigation of the heat transfer in the transition region of turbine vanes and blades with the objective of improving the capability for predicting heat transfer is described. The accurate prediction of gas-side heat transfer is important to the determination of turbine longevity, engine performance, and developmental costs. The need for accurate predictions will become greater as the operating temperatures and stage loading levels of advanced turbine engines increase. The present methods for predicting transition shear stress and heat transfer on turbine blades are based on incomplete knowledge and are largely empirical. To meet the objective of the NASA program, a team approach consisting of researchers from government, universities, a research institute, and a small business is presented. The research is divided into the areas of experiments, direct numerical simulations (DNS), and turbulence modeling. A summary of the results to date is given for the above research areas in a high-disturbance environment (bypass transition) with a discussion of the model development necessary for use in numerical codes.

Reduced and Validated Kinetic Mechanisms for Hydrogen-CO-sir Combustion in Gas Turbines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yiguang Ju; Frederick Dryer

2009-02-07

Rigorous experimental, theoretical, and numerical investigation of various issues relevant to the development of reduced, validated kinetic mechanisms for synthetic gas combustion in gas turbines was carried out - including the construction of new radiation models for combusting flows, improvement of flame speed measurement techniques, measurements and chemical kinetic analysis of H{sub 2}/CO/CO{sub 2}/O{sub 2}/diluent mixtures, revision of the H{sub 2}/O{sub 2} kinetic model to improve flame speed prediction capabilities, and development of a multi-time scale algorithm to improve computational efficiency in reacting flow simulations.

Assessment of Arctic and Antarctic Sea Ice Predictability in CMIP5 Decadal Hindcasts

NASA Technical Reports Server (NTRS)

Yang, Chao-Yuan; Liu, Jiping (Inventor); Hu, Yongyun; Horton, Radley M.; Chen, Liqi; Cheng, Xiao

2016-01-01

This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea ice. We analyze decadal hindcasts/predictions of 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Decadal hindcasts exhibit a large multimodel spread in the simulated sea ice extent, with some models deviating significantly from the observations as the predicted ice extent quickly drifts away from the initial constraint. The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Sea ice extent in the North Pacific has better predictive skill than that in the North Atlantic (particularly at a lead time of 3-7 years), but there is a reemerging predictive skill in the North Atlantic at a lead time of 6-8 years. In contrast to the Arctic, Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales, and there is no obvious improvement linking the areal extent of significant predictive skill to lead time increase. This might be because nearly all the models predict a retreating Antarctic sea ice cover, opposite to the observations. For the Arctic, the predictive skill of the multi-model ensemble mean outperforms most models and the persistence prediction at longer timescales, which is not the case for the Antarctic. Overall, for the Arctic, initialized decadal hindcasts show improved predictive skill compared to uninitialized simulations, although this improvement is not present in the Antarctic.

NTF and the Department of Defense

NASA Technical Reports Server (NTRS)

Siewert, R. F.

1981-01-01

The relationship of the National Transonic Facility (NTF) to the Department of Defense (DOD) is discussed. Recognition of the need for the NTF capabilities were first encountered in military aircraft development. Several tactical aircrafts experienced the after body drag which was higher than predicted by small scale tests, resulting in less than desired transonic acceleration performance. It is necessary to understand the problem because flight efficiency is more important for military aircrafts. Improved cruise performance is required for the whole range of military mission. Factors that make cruise efficiency important include: (1) rapid deployment airlift capability; (2) self-deployment capability for tactical aircraft; (3) reduced tanker dependence for strategic aircraft. It is concluded that the continuing escalating cost of fuel mandates to develop aircraft that are as fuel efficient as possible. Other uses for NTF are outlined.

Taking a fresh look at boiling heat transfer on the road to improved nuclear economics and efficiency

DOE PAGES

Pointer, William David; Baglietto, Emilio

2016-05-01

Here, in the effort to reinvigorate innovation in the way we design, build, and operate the nuclear power generating stations of today and tomorrow, nothing can be taken for granted. Not even the seemingly familiar physics of boiling water. The Consortium for the Advanced Simulation of Light Water Reactors, or CASL, is focused on the deployment of advanced modeling and simulation capabilities to enable the nuclear industry to reduce uncertainties in the prediction of multi-physics phenomena and continue to improve the performance of today’s Light Water Reactors and their fuel. An important part of the CASL mission is the developmentmore » of a next generation thermal hydraulics simulation capability, integrating the history of engineering models based on experimental experience with the computing technology of the future.« less

Perspectives On Dilution Jet Mixing

NASA Technical Reports Server (NTRS)

Holdeman, J. D.; Srinivasan, R.

1990-01-01

NASA recently completed program of measurements and modeling of mixing of transverse jets with ducted crossflow, motivated by need to design or tailor temperature pattern at combustor exit in gas turbine engines. Objectives of program to identify dominant physical mechanisms governing mixing, extend empirical models to provide near-term predictive capability, and compare numerical code calculations with data to guide future analysis improvement efforts.

Advancing investigation and physical modeling of first-order fire effects on soils

Treesearch

William J. Massman; John M. Frank; Sacha J. Mooney

2010-01-01

Heating soil during intense wildland fires or slash-pile burns can alter the soil irreversibly, resulting in many significant long-term biological, chemical, physical, and hydrological effects. To better understand these long-term effects, it is necessary to improve modeling capability and prediction of the more immediate, or first-order, effects that fire can have on...

Mechanistic Computational Model of Steroidgenesis in H295R Cells: Role of (Oxysterols and Cell Proliferation to Improve Predictability of Biochemical Response to Endocrine Active Chemical-Metyrapone

EPA Science Inventory

The human adrenocortical carcinoma cell line H295R is being used as an in vitro steroidogenesis screening assay to assess the impact of endocrine active chemicals (EACs) capable of altering steroid biosynthesis. To enhance the interpretation and quantitative application of measur...

New Toxico-Cheminformatics & Computational Toxicology ...

EPA Pesticide Factsheets

EPA’s National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than traditionally employed in SAR modeling, and in ways that facilitate data-mining, and data read-across. The DSSTox Structure-Browser provides structure searchability across all published DSSTox toxicity-related inventory, and is enabling linkages between previously isolated toxicity data resources. As of early March 2008, the public DSSTox inventory has been integrated into PubChem, allowing a user to take full advantage of PubChem structure-activity and bioassay clustering features. The most recent DSSTox version of the Carcinogenic Potency Database file (CPDBAS) illustrates ways in which various summary definitions of carcinogenic activity can be employed in modeling and data mining. Phase I of the ToxCastTM project is generating high-throughput screening data from several hundred biochemical and cell-based assays for a set of 320 chemicals, mostly pesticide actives, with rich toxicology profiles. Incorporating and expanding traditional SAR concepts into this new high-throughput and data-rich world pose conceptual and practical challenges, but also holds great promise for improving predictive capabilities.

A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models.

PubMed

Miskovic, Ljubisa; Alff-Tuomala, Susanne; Soh, Keng Cher; Barth, Dorothee; Salusjärvi, Laura; Pitkänen, Juha-Pekka; Ruohonen, Laura; Penttilä, Merja; Hatzimanikatis, Vassily

2017-01-01

Recent advancements in omics measurement technologies have led to an ever-increasing amount of available experimental data that necessitate systems-oriented methodologies for efficient and systematic integration of data into consistent large-scale kinetic models. These models can help us to uncover new insights into cellular physiology and also to assist in the rational design of bioreactor or fermentation processes. Optimization and Risk Analysis of Complex Living Entities (ORACLE) framework for the construction of large-scale kinetic models can be used as guidance for formulating alternative metabolic engineering strategies. We used ORACLE in a metabolic engineering problem: improvement of the xylose uptake rate during mixed glucose-xylose consumption in a recombinant Saccharomyces cerevisiae strain. Using the data from bioreactor fermentations, we characterized network flux and concentration profiles representing possible physiological states of the analyzed strain. We then identified enzymes that could lead to improved flux through xylose transporters (XTR). For some of the identified enzymes, including hexokinase (HXK), we could not deduce if their control over XTR was positive or negative. We thus performed a follow-up experiment, and we found out that HXK2 deletion improves xylose uptake rate. The data from the performed experiments were then used to prune the kinetic models, and the predictions of the pruned population of kinetic models were in agreement with the experimental data collected on the HXK2 -deficient S. cerevisiae strain. We present a design-build-test cycle composed of modeling efforts and experiments with a glucose-xylose co-utilizing recombinant S. cerevisiae and its HXK2 -deficient mutant that allowed us to uncover interdependencies between upper glycolysis and xylose uptake pathway. Through this cycle, we also obtained kinetic models with improved prediction capabilities. The present study demonstrates the potential of integrated "modeling and experiments" systems biology approaches that can be applied for diverse applications ranging from biotechnology to drug discovery.

Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

USGS Publications Warehouse

Christensen, Nikolaj K; Minsley, Burke J.; Christensen, Steen

2017-01-01

We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

NASA Astrophysics Data System (ADS)

Christensen, N. K.; Minsley, B. J.; Christensen, S.

2017-02-01

We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

Genome-to-Watershed Predictive Understanding of Terrestrial Environments

NASA Astrophysics Data System (ADS)

Hubbard, S. S.; Agarwal, D.; Banfield, J. F.; Beller, H. R.; Brodie, E.; Long, P.; Nico, P. S.; Steefel, C. I.; Tokunaga, T. K.; Williams, K. H.

2014-12-01

Although terrestrial environments play a critical role in cycling water, greenhouse gasses, and other life-critical elements, the complexity of interactions among component microbes, plants, minerals, migrating fluids and dissolved constituents hinders predictive understanding of system behavior. The 'Sustainable Systems 2.0' project is developing genome-to-watershed scale predictive capabilities to quantify how the microbiome affects biogeochemical watershed functioning, how watershed-scale hydro-biogeochemical processes affect microbial functioning, and how these interactions co-evolve with climate and land-use changes. Development of such predictive capabilities is critical for guiding the optimal management of water resources, contaminant remediation, carbon stabilization, and agricultural sustainability - now and with global change. Initial investigations are focused on floodplains in the Colorado River Basin, and include iterative model development, experiments and observations with an early emphasis on subsurface aspects. Field experiments include local-scale experiments at Rifle CO to quantify spatiotemporal metabolic and geochemical responses to O2and nitrate amendments as well as floodplain-scale monitoring to quantify genomic and biogeochemical response to natural hydrological perturbations. Information obtained from such experiments are represented within GEWaSC, a Genome-Enabled Watershed Simulation Capability, which is being developed to allow mechanistic interrogation of how genomic information stored in a subsurface microbiome affects biogeochemical cycling. This presentation will describe the genome-to-watershed scale approach as well as early highlights associated with the project. Highlights include: first insights into the diversity of the subsurface microbiome and metabolic roles of organisms involved in subsurface nitrogen, sulfur and hydrogen and carbon cycling; the extreme variability of subsurface DOC and hydrological controls on carbon and nitrogen cycling; geophysical identification of floodplain hotspots that are useful for model parameterization; and GEWaSC demonstration of how incorporation of identified microbial metabolic processes improves prediction of the larger system biogeochemical behavior.

NOAA's National Air Quality Predictions and Development of Aerosol and Atmospheric Composition Prediction Components for the Next Generation Global Prediction System

NASA Astrophysics Data System (ADS)

Stajner, I.; Hou, Y. T.; McQueen, J.; Lee, P.; Stein, A. F.; Tong, D.; Pan, L.; Huang, J.; Huang, H. C.; Upadhayay, S.

2016-12-01

NOAA provides operational air quality predictions using the National Air Quality Forecast Capability (NAQFC): ozone and wildfire smoke for the United States and airborne dust for the contiguous 48 states at http://airquality.weather.gov. NOAA's predictions of fine particulate matter (PM2.5) became publicly available in February 2016. Ozone and PM2.5 predictions are produced using a system that operationally links the Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the North American mesoscale forecast Model (NAM). Smoke and dust predictions are provided using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Current NAQFC focus is on updating CMAQ to version 5.0.2, improving PM2.5 predictions, and updating emissions estimates, especially for NOx using recently observed trends. Wildfire smoke emissions from a newer version of the USFS BlueSky system are being included in a new configuration of the NAQFC NAM-CMAQ system, which is re-run for the previous 24 hours when the wildfires were observed from satellites, to better represent wildfire emissions prior to initiating predictions for the next 48 hours. In addition, NOAA is developing the Next Generation Global Prediction System (NGGPS) to represent the earth system for extended weather prediction. NGGPS will include a representation of atmospheric dynamics, physics, aerosols and atmospheric composition as well as coupling with ocean, wave, ice and land components. NGGPS is being developed with a broad community involvement, including community developed components and academic research to develop and test potential improvements for potentially inclusion in NGGPS. Several investigators at NOAA's research laboratories and in academia are working to improve the aerosol and gaseous chemistry representation for NGGPS, to develop and evaluate the representation of atmospheric composition, and to establish and improve the coupling with radiation and microphysics. Additional efforts may include the improved use of predicted atmospheric composition in assimilation of observations and the linkage of full global atmospheric composition predictions with national air quality predictions.

Analysis of information systems for hydropower operations

NASA Technical Reports Server (NTRS)

Sohn, R. L.; Becker, L.; Estes, J.; Simonett, D.; Yeh, W. W. G.

1976-01-01

The operations of hydropower systems were analyzed with emphasis on water resource management, to determine how aerospace derived information system technologies can increase energy output. Better utilization of water resources was sought through improved reservoir inflow forecasting based on use of hydrometeorologic information systems with new or improved sensors, satellite data relay systems, and use of advanced scheduling techniques for water release. Specific mechanisms for increased energy output were determined, principally the use of more timely and accurate short term (0-7 days) inflow information to reduce spillage caused by unanticipated dynamic high inflow events. The hydrometeorologic models used in predicting inflows were examined to determine the sensitivity of inflow prediction accuracy to the many variables employed in the models, and the results used to establish information system requirements. Sensor and data handling system capabilities were reviewed and compared to the requirements, and an improved information system concept outlined.

Recent Progress Towards Predicting Aircraft Ground Handling Performance

NASA Technical Reports Server (NTRS)

Yager, T. J.; White, E. J.

1981-01-01

The significant progress which has been achieved in development of aircraft ground handling simulation capability is reviewed and additional improvements in software modeling identified. The problem associated with providing necessary simulator input data for adequate modeling of aircraft tire/runway friction behavior is discussed and efforts to improve this complex model, and hence simulator fidelity, are described. Aircraft braking performance data obtained on several wet runway surfaces is compared to ground vehicle friction measurements and, by use of empirically derived methods, good agreement between actual and estimated aircraft braking friction from ground vehilce data is shown. The performance of a relatively new friction measuring device, the friction tester, showed great promise in providing data applicable to aircraft friction performance. Additional research efforts to improve methods of predicting tire friction performance are discussed including use of an instrumented tire test vehicle to expand the tire friction data bank and a study of surface texture measurement techniques.

Analysis of information systems for hydropower operations: Executive summary

NASA Technical Reports Server (NTRS)

Sohn, R. L.; Becker, L.; Estes, J.; Simonett, D.; Yeh, W.

1976-01-01

An analysis was performed of the operations of hydropower systems, with emphasis on water resource management, to determine how aerospace derived information system technologies can effectively increase energy output. Better utilization of water resources was sought through improved reservoir inflow forecasting based on use of hydrometeorologic information systems with new or improved sensors, satellite data relay systems, and use of advanced scheduling techniques for water release. Specific mechanisms for increased energy output were determined, principally the use of more timely and accurate short term (0-7 days) inflow information to reduce spillage caused by unanticipated dynamic high inflow events. The hydrometeorologic models used in predicting inflows were examined in detail to determine the sensitivity of inflow prediction accuracy to the many variables employed in the models, and the results were used to establish information system requirements. Sensor and data handling system capabilities were reviewed and compared to the requirements, and an improved information system concept was outlined.

An evolution-based DNA-binding residue predictor using a dynamic query-driven learning scheme.

PubMed

Chai, H; Zhang, J; Yang, G; Ma, Z

2016-11-15

DNA-binding proteins play a pivotal role in various biological activities. Identification of DNA-binding residues (DBRs) is of great importance for understanding the mechanism of gene regulations and chromatin remodeling. Most traditional computational methods usually construct their predictors on static non-redundant datasets. They excluded many homologous DNA-binding proteins so as to guarantee the generalization capability of their models. However, those ignored samples may potentially provide useful clues when studying protein-DNA interactions, which have not obtained enough attention. In view of this, we propose a novel method, namely DQPred-DBR, to fill the gap of DBR predictions. First, a large-scale extensible sample pool was compiled. Second, evolution-based features in the form of a relative position specific score matrix and covariant evolutionary conservation descriptors were used to encode the feature space. Third, a dynamic query-driven learning scheme was designed to make more use of proteins with known structure and functions. In comparison with a traditional static model, the introduction of dynamic models could obviously improve the prediction performance. Experimental results from the benchmark and independent datasets proved that our DQPred-DBR had promising generalization capability. It was capable of producing decent predictions and outperforms many state-of-the-art methods. For the convenience of academic use, our proposed method was also implemented as a web server at .

Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production.

PubMed

Del Rio-Chanona, Ehecatl A; Liu, Jiao; Wagner, Jonathan L; Zhang, Dongda; Meng, Yingying; Xue, Song; Shah, Nilay

2018-02-01

Biodiesel produced from microalgae has been extensively studied due to its potentially outstanding advantages over traditional transportation fuels. In order to facilitate its industrialization and improve the process profitability, it is vital to construct highly accurate models capable of predicting the complex behavior of the investigated biosystem for process optimization and control, which forms the current research goal. Three original contributions are described in this paper. Firstly, a dynamic model is constructed to simulate the complicated effect of light intensity, nutrient supply and light attenuation on both biomass growth and biolipid production. Secondly, chlorophyll fluorescence, an instantly measurable variable and indicator of photosynthetic activity, is embedded into the model to monitor and update model accuracy especially for the purpose of future process optimal control, and its correlation between intracellular nitrogen content is quantified, which to the best of our knowledge has never been addressed so far. Thirdly, a thorough experimental verification is conducted under different scenarios including both continuous illumination and light/dark cycle conditions to testify the model predictive capability particularly for long-term operation, and it is concluded that the current model is characterized by a high level of predictive capability. Based on the model, the optimal light intensity for algal biomass growth and lipid synthesis is estimated. This work, therefore, paves the way to forward future process design and real-time optimization. © 2017 Wiley Periodicals, Inc.

Improving Air Quality (and Weather) Predictions using Advanced Data Assimilation Techniques Applied to Coupled Models during KORUS-AQ

NASA Astrophysics Data System (ADS)

Carmichael, G. R.; Saide, P. E.; Gao, M.; Streets, D. G.; Kim, J.; Woo, J. H.

2017-12-01

Ambient aerosols are important air pollutants with direct impacts on human health and on the Earth's weather and climate systems through their interactions with radiation and clouds. Their role is dependent on their distributions of size, number, phase and composition, which vary significantly in space and time. There remain large uncertainties in simulated aerosol distributions due to uncertainties in emission estimates and in chemical and physical processes associated with their formation and removal. These uncertainties lead to large uncertainties in weather and air quality predictions and in estimates of health and climate change impacts. Despite these uncertainties and challenges, regional-scale coupled chemistry-meteorological models such as WRF-Chem have significant capabilities in predicting aerosol distributions and explaining aerosol-weather interactions. We explore the hypothesis that new advances in on-line, coupled atmospheric chemistry/meteorological models, and new emission inversion and data assimilation techniques applicable to such coupled models, can be applied in innovative ways using current and evolving observation systems to improve predictions of aerosol distributions at regional scales. We investigate the impacts of assimilating AOD from geostationary satellite (GOCI) and surface PM2.5 measurements on predictions of AOD and PM in Korea during KORUS-AQ through a series of experiments. The results suggest assimilating datasets from multiple platforms can improve the predictions of aerosol temporal and spatial distributions.

Applications of NASA and NOAA Satellite Observations by NASA's Short-term Prediction Research and Transition (SPoRT) Center in Response to Natural Disasters

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Jedlovec, Gary J.

2012-01-01

NASA s Short-term Prediction Research and Transition (SPoRT) Center supports the transition of unique NASA and NOAA research activities to the operational weather forecasting community. SPoRT emphasizes real-time analysis and prediction out to 48 hours. SPoRT partners with NOAA s National Weather Service (NWS) Weather Forecast Offices (WFOs) and National Centers to improve current products, demonstrate future satellite capabilities and explore new data assimilation techniques. Recently, the SPoRT Center has been involved in several activities related to disaster response, in collaboration with NOAA s National Weather Service, NASA s Applied Sciences Disasters Program, and other partners.

Anisotropic constitutive modeling for nickel base single crystal superalloys using a crystallographic approach

NASA Technical Reports Server (NTRS)

Stouffer, D. C.; Sheh, M. Y.

1988-01-01

A micromechanical model based on crystallographic slip theory was formulated for nickel-base single crystal superalloys. The current equations include both drag stress and back stress state variables to model the local inelastic flow. Specially designed experiments have been conducted to evaluate the effect of back stress in single crystals. The results showed that (1) the back stress is orientation dependent; and (2) the back stress state variable in the inelastic flow equation is necessary for predicting anelastic behavior of the material. The model also demonstrated improved fatigue predictive capability. Model predictions and experimental data are presented for single crystal superalloy Rene N4 at 982 C.

Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

PubMed

Enshaei, A; Robson, C N; Edmondson, R J

2015-11-01

The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict outcome (complete/optimal cytoreduction vs. suboptimal cytoreduction) with 77 % accuracy and an AUC of 0.73. These data are encouraging and demonstrate that artificial intelligence systems may have a role in providing prognostic and predictive data for patients. The performance of these systems likely will improve with increasing data set size, and this needs further investigation.

Autonomous system for launch vehicle range safety

NASA Astrophysics Data System (ADS)

Ferrell, Bob; Haley, Sam

2001-02-01

The Autonomous Flight Safety System (AFSS) is a launch vehicle subsystem whose ultimate goal is an autonomous capability to assure range safety (people and valuable resources), flight personnel safety, flight assets safety (recovery of valuable vehicles and cargo), and global coverage with a dramatic simplification of range infrastructure. The AFSS is capable of determining current vehicle position and predicting the impact point with respect to flight restriction zones. Additionally, it is able to discern whether or not the launch vehicle is an immediate threat to public safety, and initiate the appropriate range safety response. These features provide for a dramatic cost reduction in range operations and improved reliability of mission success. .

Vortex information display system program description manual. [data acquisition from laser Doppler velocimeters and real time operation

NASA Technical Reports Server (NTRS)

Conway, R.; Matuck, G. N.; Roe, J. M.; Taylor, J.; Turner, A.

1975-01-01

A vortex information display system is described which provides flexible control through system-user interaction for collecting wing-tip-trailing vortex data, processing this data in real time, displaying the processed data, storing raw data on magnetic tape, and post processing raw data. The data is received from two asynchronous laser Doppler velocimeters (LDV's) and includes position, velocity, and intensity information. The raw data is written onto magnetic tape for permanent storage and is also processed in real time to locate vortices and plot their positions as a function of time. The interactive capability enables the user to make real time adjustments in processing data and provides a better definition of vortex behavior. Displaying the vortex information in real time produces a feedback capability to the LDV system operator allowing adjustments to be made in the collection of raw data. Both raw data and processing can be continually upgraded during flyby testing to improve vortex behavior studies. The post-analysis capability permits the analyst to perform in-depth studies of test data and to modify vortex behavior models to improve transport predictions.

HART-II: Prediction of Blade-Vortex Interaction Loading

NASA Technical Reports Server (NTRS)

Lim, Joon W.; Tung, Chee; Yu, Yung H.; Burley, Casey L.; Brooks, Thomas; Boyd, Doug; vanderWall, Berend; Schneider, Oliver; Richard, Hugues; Raffel, Markus

2003-01-01

During the HART-I data analysis, the need for comprehensive wake data was found including vortex creation and aging, and its re-development after blade-vortex interaction. In October 2001, US Army AFDD, NASA Langley, German DLR, French ONERA and Dutch DNW performed the HART-II test as an international joint effort. The main objective was to focus on rotor wake measurement using a PIV technique along with the comprehensive data of blade deflections, airloads, and acoustics. Three prediction teams made preliminary correlation efforts with HART-II data: a joint US team of US Army AFDD and NASA Langley, German DLR, and French ONERA. The predicted results showed significant improvements over the HART-I predicted results, computed about several years ago, which indicated that there has been better understanding of complicated wake modeling in the comprehensive rotorcraft analysis. All three teams demonstrated satisfactory prediction capabilities, in general, though there were slight deviations of prediction accuracies for various disciplines.

An object programming based environment for protein secondary structure prediction.

PubMed

Giacomini, M; Ruggiero, C; Sacile, R

1996-01-01

The most frequently used methods for protein secondary structure prediction are empirical statistical methods and rule based methods. A consensus system based on object-oriented programming is presented, which integrates the two approaches with the aim of improving the prediction quality. This system uses an object-oriented knowledge representation based on the concepts of conformation, residue and protein, where the conformation class is the basis, the residue class derives from it and the protein class derives from the residue class. The system has been tested with satisfactory results on several proteins of the Brookhaven Protein Data Bank. Its results have been compared with the results of the most widely used prediction methods, and they show a higher prediction capability and greater stability. Moreover, the system itself provides an index of the reliability of its current prediction. This system can also be regarded as a basis structure for programs of this kind.

Economic consequences of improved temperature forecasts: An experiment with the Florida citrus growers (control group results). Executive summary. [weather forecasting

NASA Technical Reports Server (NTRS)

1977-01-01

A demonstration experiment is being planned to show that frost and freeze prediction improvements are possible utilizing timely Synchronous Meteorological Satellite temperature measurements and that this information can affect Florida citrus grower operations and decisions so as to significantly reduce the cost for frost and freeze protection and crop losses. The design and implementation of the first phase of an economic experiment which will monitor citrus growers decisions, actions, costs and losses, and meteorological forecasts and actual weather events was carried out. The economic experiment was designed to measure the change in annual protection costs and crop losses which are the direct result of improved temperature forecasts. To estimate the benefits that may result from improved temperature forecasting capability, control and test groups were established with effective separation being accomplished temporally. The control group, utilizing current forecasting capability, was observed during the 1976-77 frost season and the results are reported. A brief overview is given of the economic experiment, the results obtained to date, and the work which still remains to be done.

Strontium-90 Biokinetics from Simulated Wound Intakes in Non-human Primates Compared with Combined Model Predictions from National Council on Radiation Protection and Measurements Report 156 and International Commission on Radiological Protection Publication 67.

PubMed

Allen, Mark B; Brey, Richard R; Gesell, Thomas; Derryberry, Dewayne; Poudel, Deepesh

2016-01-01

This study had a goal to evaluate the predictive capabilities of the National Council on Radiation Protection and Measurements (NCRP) wound model coupled to the International Commission on Radiological Protection (ICRP) systemic model for 90Sr-contaminated wounds using non-human primate data. Studies were conducted on 13 macaque (Macaca mulatta) monkeys, each receiving one-time intramuscular injections of 90Sr solution. Urine and feces samples were collected up to 28 d post-injection and analyzed for 90Sr activity. Integrated Modules for Bioassay Analysis (IMBA) software was configured with default NCRP and ICRP model transfer coefficients to calculate predicted 90Sr intake via the wound based on the radioactivity measured in bioassay samples. The default parameters of the combined models produced adequate fits of the bioassay data, but maximum likelihood predictions of intake were overestimated by a factor of 1.0 to 2.9 when bioassay data were used as predictors. Skeletal retention was also over-predicted, suggesting an underestimation of the excretion fraction. Bayesian statistics and Monte Carlo sampling were applied using IMBA to vary the default parameters, producing updated transfer coefficients for individual monkeys that improved model fit and predicted intake and skeletal retention. The geometric means of the optimized transfer rates for the 11 cases were computed, and these optimized sample population parameters were tested on two independent monkey cases and on the 11 monkeys from which the optimized parameters were derived. The optimized model parameters did not improve the model fit in most cases, and the predicted skeletal activity produced improvements in three of the 11 cases. The optimized parameters improved the predicted intake in all cases but still over-predicted the intake by an average of 50%. The results suggest that the modified transfer rates were not always an improvement over the default NCRP and ICRP model values.

The Utility of a Geostationary Doppler radar applied to the hurricane analysis and prediction problem: A Report on the 1st Nexrad in Space Workshop

NASA Astrophysics Data System (ADS)

Tripoli, G. J.; Chandrasekar, V.; Chen, S. S.; Holland, G. J.; Im, E.; Kakar, R.; Lewis, W. E.; Marks, F. D.; Smith, E. A.; Tanelli, S.

2007-12-01

Last April the first Nexrad in Space (NIS) workshop was held in Miami, Florida to discuss the value and requirements for a possible satellite mission featuring a Doppler radar in geostationary orbit capable of measuring the internal structure of tropical cyclones over a circular scan area 50 degrees latitude in diameter. The proposed NIS technology, based on the PR2 radar design developed at JPL and an innovative deployable antenna design developed at UCLA would be capable of 3D volume sampling with 12 km horizontal and 300 m vertical resolution and 1 hour scan period. The workshop participants consisted of the JPL and UCLA design teams and cross section of tropical cyclone forecasters, researchers and modelers who could potentially benefit from this technology. The consensus of the workshop included: (a) the NIS technology would provide observations to benefit hurricane forecasters, real time weather prediction models and model researchers, (b) the most important feature of NIS was its high frequency coverage together with its 3D observation capability. These features were found to fill a data gap, now developing within cloud resolving analysis and prediction systems for which there is no other proposed solution, particularly over the oceans where TCs form. Closing this data gap is important to the improvement of TC intensity prediction. A complete description of the potential benefits and recommended goals for this technology concluded by the workshop participants will be given at the oral presentation.

Development of Standard Fuel Models in Boreal Forests of Northeast China through Calibration and Validation

PubMed Central

Cai, Longyan; He, Hong S.; Wu, Zhiwei; Lewis, Benard L.; Liang, Yu

2014-01-01

Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management. PMID:24714164

California Drought and the 2015-2016 El Niño

NASA Astrophysics Data System (ADS)

Cash, B.

2017-12-01

California winter rainfall is examined in observations and data from the North American Multi-Model Ensemble (NMME) and Project Metis, a new suite of seasonal integrations made using the operational European Centre for Medium-Range Weather Forecasts model. We focus on the 2015-2016 season, and the non-canonical response to the major El Niño event that occurred. We show that the Metis ensemble mean is capable of distinguishing between the response to the 1997/98 and 2015/16 events, while the two events are more similar in the NMME. We also show that unpredicted variations in the atmospheric circulation in the north Pacific significantly affect southern California rainfall totals. Improving prediction of these variations is thus a key target for improving seasonal rainfall predictions for this region.

Applicability of linear regression equation for prediction of chlorophyll content in rice leaves

NASA Astrophysics Data System (ADS)

Li, Yunmei

2005-09-01

A modeling approach is used to assess the applicability of the derived equations which are capable to predict chlorophyll content of rice leaves at a given view direction. Two radiative transfer models, including PROSPECT model operated at leaf level and FCR model operated at canopy level, are used in the study. The study is consisted of three steps: (1) Simulation of bidirectional reflectance from canopy with different leaf chlorophyll contents, leaf-area-index (LAI) and under storey configurations; (2) Establishment of prediction relations of chlorophyll content by stepwise regression; and (3) Assessment of the applicability of these relations. The result shows that the accuracy of prediction is affected by different under storey configurations and, however, the accuracy tends to be greatly improved with increase of LAI.

Landing Gear Noise Prediction and Analysis for Tube-and-Wing and Hybrid-Wing-Body Aircraft

NASA Technical Reports Server (NTRS)

Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

2016-01-01

Improvements and extensions to landing gear noise prediction methods are developed. New features include installation effects such as reflection from the aircraft, gear truck angle effect, local flow calculation at the landing gear locations, gear size effect, and directivity for various gear designs. These new features have not only significantly improved the accuracy and robustness of the prediction tools, but also have enabled applications to unconventional aircraft designs and installations. Systematic validations of the improved prediction capability are then presented, including parametric validations in functional trends as well as validations in absolute amplitudes, covering a wide variety of landing gear designs, sizes, and testing conditions. The new method is then applied to selected concept aircraft configurations in the portfolio of the NASA Environmentally Responsible Aviation Project envisioned for the timeframe of 2025. The landing gear noise levels are on the order of 2 to 4 dB higher than previously reported predictions due to increased fidelity in accounting for installation effects and gear design details. With the new method, it is now possible to reveal and assess the unique noise characteristics of landing gear systems for each type of aircraft. To address the inevitable uncertainties in predictions of landing gear noise models for future aircraft, an uncertainty analysis is given, using the method of Monte Carlo simulation. The standard deviation of the uncertainty in predicting the absolute level of landing gear noise is quantified and determined to be 1.4 EPNL dB.

Simulation of Atmospheric-Entry Capsules in the Subsonic Regime

NASA Technical Reports Server (NTRS)

Murman, Scott M.; Childs, Robert E.; Garcia, Joseph A.

2015-01-01

The accuracy of Computational Fluid Dynamics predictions of subsonic capsule aerodynamics is examined by comparison against recent NASA wind-tunnel data at high-Reynolds-number flight conditions. Several aspects of numerical and physical modeling are considered, including inviscid numerical scheme, mesh adaptation, rough-wall modeling, rotation and curvature corrections for eddy-viscosity models, and Detached-Eddy Simulations of the unsteady wake. All of these are considered in isolation against relevant data where possible. The results indicate that an improved predictive capability is developed by considering physics-based approaches and validating the results against flight-relevant experimental data.

Low frequency vibration isolation technology for microgravity space experiments

NASA Technical Reports Server (NTRS)

Grodsinsky, Carlos M.; Brown, Gerald V.

1989-01-01

The dynamic acceleration environment observed on Space Shuttle flights to date and predicted for the Space Station has complicated the analysis of prior microgravity experiments and prompted concern for the viability of proposed space experiments requiring long-term, low-g environments. Isolation systems capable of providing significant improvements in this environment exist, but have not been demonstrated in flight configurations. This paper presents a summary of the theoretical evaluation for two one degree-of-freedom (DOF) active magnetic isolators and their predicted response to both direct and base excitations, that can be used to isolate acceleration sensitive microgravity space experiments.

Finite element analysis of the stiffness of fabric reinforced composites

NASA Technical Reports Server (NTRS)

Foye, R. L.

1992-01-01

The objective of this work is the prediction of all three dimensional elastic moduli of textile fabric reinforced composites. The analysis is general enough for use with complex reinforcing geometries and capable of subsequent improvements. It places no restrictions on fabric microgeometry except that the unit cell be determinate and rectangular. The unit cell is divided into rectangular subcells in which the reinforcing geometries are easier to define and analyze. The analysis, based on inhomogeneous finite elements, is applied to a variety of weave, braid, and knit reinforced composites. Some of these predictions are correlated to test data.

Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2016-01-01

Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for the Liuxihe model parameter optimization effectively and could improve the model capability largely in catchment flood forecasting, thus proving that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological models. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for the Liuxihe model catchment flood forecasting are 20 and 30 respectively.

Data Assimilation in the Solar Wind: Challenges and First Results.

PubMed

Lang, Matthew; Browne, Philip; van Leeuwen, Peter Jan; Owens, Mathew

2017-11-01

Data assimilation (DA) is used extensively in numerical weather prediction (NWP) to improve forecast skill. Indeed, improvements in forecast skill in NWP models over the past 30 years have directly coincided with improvements in DA schemes. At present, due to data availability and technical challenges, DA is underused in space weather applications, particularly for solar wind prediction. This paper investigates the potential of advanced DA methods currently used in operational NWP centers to improve solar wind prediction. To develop the technical capability, as well as quantify the potential benefit, twin experiments are conducted to assess the performance of the Local Ensemble Transform Kalman Filter (LETKF) in the solar wind model ENLIL. Boundary conditions are provided by the Wang-Sheeley-Arge coronal model and synthetic observations of density, temperature, and momentum generated every 4.5 h at 0.6 AU. While in situ spacecraft observations are unlikely to be routinely available at 0.6 AU, these techniques can be applied to remote sensing of the solar wind, such as with Heliospheric Imagers or interplanetary scintillation. The LETKF can be seen to improve the state at the observation location and advect that improvement toward the Earth, leading to an improvement in forecast skill in near-Earth space for both the observed and unobserved variables. However, sharp gradients caused by the analysis of a single observation in space resulted in artificial wavelike structures being advected toward Earth. This paper is the first attempt to apply DA to solar wind prediction and provides the first in-depth analysis of the challenges and potential solutions.

Data Assimilation in the Solar Wind: Challenges and First Results

NASA Astrophysics Data System (ADS)

Lang, Matthew; Browne, Philip; van Leeuwen, Peter Jan; Owens, Mathew

2017-11-01

Data assimilation (DA) is used extensively in numerical weather prediction (NWP) to improve forecast skill. Indeed, improvements in forecast skill in NWP models over the past 30 years have directly coincided with improvements in DA schemes. At present, due to data availability and technical challenges, DA is underused in space weather applications, particularly for solar wind prediction. This paper investigates the potential of advanced DA methods currently used in operational NWP centers to improve solar wind prediction. To develop the technical capability, as well as quantify the potential benefit, twin experiments are conducted to assess the performance of the Local Ensemble Transform Kalman Filter (LETKF) in the solar wind model ENLIL. Boundary conditions are provided by the Wang-Sheeley-Arge coronal model and synthetic observations of density, temperature, and momentum generated every 4.5 h at 0.6 AU. While in situ spacecraft observations are unlikely to be routinely available at 0.6 AU, these techniques can be applied to remote sensing of the solar wind, such as with Heliospheric Imagers or interplanetary scintillation. The LETKF can be seen to improve the state at the observation location and advect that improvement toward the Earth, leading to an improvement in forecast skill in near-Earth space for both the observed and unobserved variables. However, sharp gradients caused by the analysis of a single observation in space resulted in artificial wavelike structures being advected toward Earth. This paper is the first attempt to apply DA to solar wind prediction and provides the first in-depth analysis of the challenges and potential solutions.

Prediction task guided representation learning of medical codes in EHR.

PubMed

Cui, Liwen; Xie, Xiaolei; Shen, Zuojun

2018-06-18

There have been rapidly growing applications using machine learning models for predictive analytics in Electronic Health Records (EHR) to improve the quality of hospital services and the efficiency of healthcare resource utilization. A fundamental and crucial step in developing such models is to convert medical codes in EHR to feature vectors. These medical codes are used to represent diagnoses or procedures. Their vector representations have a tremendous impact on the performance of machine learning models. Recently, some researchers have utilized representation learning methods from Natural Language Processing (NLP) to learn vector representations of medical codes. However, most previous approaches are unsupervised, i.e. the generation of medical code vectors is independent from prediction tasks. Thus, the obtained feature vectors may be inappropriate for a specific prediction task. Moreover, unsupervised methods often require a lot of samples to obtain reliable results, but most practical problems have very limited patient samples. In this paper, we develop a new method called Prediction Task Guided Health Record Aggregation (PTGHRA), which aggregates health records guided by prediction tasks, to construct training corpus for various representation learning models. Compared with unsupervised approaches, representation learning models integrated with PTGHRA yield a significant improvement in predictive capability of generated medical code vectors, especially for limited training samples. Copyright © 2018. Published by Elsevier Inc.

Customizing Countermeasure Prescriptions using Predictive Measures of Sensorimotor Adaptability

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Miller, C. A.; Batson, C. D.; Wood, S. J.; Guined, J. R.; Cohen, H. S.; Buccello-Stout, R.; DeDios, Y. E.;

A research study for the preliminary definition of an aerophysics free-flight laboratory facility

NASA Technical Reports Server (NTRS)

Canning, Thomas N.

1988-01-01

A renewed interest in hypervelocity vehicles requires an increase in the knowledge of aerodynamic phenomena. Tests conducted with ground-based facilities can be used both to better understand the physics of hypervelocity flight, and to calibrate and validate computer codes designed to predict vehicle performance in the hypervelocity environment. This research reviews the requirements for aerothermodynamic testing and discusses the ballistic range and its capabilities. Examples of the kinds of testing performed in typical high performance ballistic ranges are described. We draw heavily on experience obtained in the ballistics facilities at NASA Ames Research Center, Moffett Field, California. Prospects for improving the capabilities of the ballistic range by using advanced instrumentation are discussed. Finally, recent developments in gun technology and their application to extend the capability of the ballistic range are summarized.

Reacting Multi-Species Gas Capability for USM3D Flow Solver

NASA Technical Reports Server (NTRS)

Frink, Neal T.; Schuster, David M.

2012-01-01

The USM3D Navier-Stokes flow solver contributed heavily to the NASA Constellation Project (CxP) as a highly productive computational tool for generating the aerodynamic databases for the Ares I and V launch vehicles and Orion launch abort vehicle (LAV). USM3D is currently limited to ideal-gas flows, which are not adequate for modeling the chemistry or temperature effects of hot-gas jet flows. This task was initiated to create an efficient implementation of multi-species gas and equilibrium chemistry into the USM3D code to improve its predictive capabilities for hot jet impingement effects. The goal of this NASA Engineering and Safety Center (NESC) assessment was to implement and validate a simulation capability to handle real-gas effects in the USM3D code. This document contains the outcome of the NESC assessment.

Can beaches survive climate change?

USGS Publications Warehouse

Vitousek, Sean; Barnard, Patrick L.; Limber, Patrick W.

2017-01-01

Anthropogenic climate change is driving sea level rise, leading to numerous impacts on the coastal zone, such as increased coastal flooding, beach erosion, cliff failure, saltwater intrusion in aquifers, and groundwater inundation. Many beaches around the world are currently experiencing chronic erosion as a result of gradual, present-day rates of sea level rise (about 3 mm/year) and human-driven restrictions in sand supply (e.g., harbor dredging and river damming). Accelerated sea level rise threatens to worsen coastal erosion and challenge the very existence of natural beaches throughout the world. Understanding and predicting the rates of sea level rise and coastal erosion depends on integrating data on natural systems with computer simulations. Although many computer modeling approaches are available to simulate shoreline change, few are capable of making reliable long-term predictions needed for full adaption or to enhance resilience. Recent advancements have allowed convincing decadal to centennial-scale predictions of shoreline evolution. For example, along 500 km of the Southern California coast, a new model featuring data assimilation predicts that up to 67% of beaches may completely erode by 2100 without large-scale human interventions. In spite of recent advancements, coastal evolution models must continue to improve in their theoretical framework, quantification of accuracy and uncertainty, computational efficiency, predictive capability, and integration with observed data, in order to meet the scientific and engineering challenges produced by a changing climate.

SEURAT-1 liver gold reference compounds: a mechanism-based review.

PubMed

Jennings, Paul; Schwarz, Michael; Landesmann, Brigitte; Maggioni, Silvia; Goumenou, Marina; Bower, David; Leonard, Martin O; Wiseman, Jeffrey S

2014-12-01

There is an urgent need for the development of alternative methods to replace animal testing for the prediction of repeat dose chemical toxicity. To address this need, the European Commission and Cosmetics Europe have jointly funded a research program for 'Safety Evaluation Ultimately Replacing Animal Testing.' The goal of this program was the development of in vitro cellular systems and associated computational capabilities for the prediction of hepatic, cardiac, renal, neuronal, muscle, and skin toxicities. An essential component of this effort is the choice of appropriate reference compounds that can be used in the development and validation of assays. In this review, we focus on the selection of reference compounds for liver pathologies in the broad categories of cytotoxicity and lipid disorders. Mitochondrial impairment, oxidative stress, and apoptosis are considered under the category of cytotoxicity, while steatosis, cholestasis, and phospholipidosis are considered under the category of lipid dysregulation. We focused on four compound classes capable of initiating such events, i.e., chemically reactive compounds, compounds with specific cellular targets, compounds that modulate lipid regulatory networks, and compounds that disrupt the plasma membrane. We describe the molecular mechanisms of these compounds and the cellular response networks which they elicit. This information will be helpful to both improve our understanding of mode of action and help in the selection of appropriate mechanistic biomarkers, allowing us to progress the development of animal-free models with improved predictivity to the human situation.

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model

PubMed Central

Li, Xiaoqing; Wang, Yu

2018-01-01

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing technology. PMID:29351254

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model.

PubMed

Xin, Jingzhou; Zhou, Jianting; Yang, Simon X; Li, Xiaoqing; Wang, Yu

2018-01-19

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing technology.

Improving short-term air quality predictions over the U.S. using chemical data assimilation

NASA Astrophysics Data System (ADS)

Kumar, R.; Delle Monache, L.; Alessandrini, S.; Saide, P.; Lin, H. C.; Liu, Z.; Pfister, G.; Edwards, D. P.; Baker, B.; Tang, Y.; Lee, P.; Djalalova, I.; Wilczak, J. M.

2017-12-01

State and local air quality forecasters across the United States use air quality forecasts from the National Air Quality Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) as one of the key tools to protect the public from adverse air pollution related health effects by dispensing timely information about air pollution episodes. This project funded by the National Aeronautics and Space Administration (NASA) aims to enhance the decision-making process by improving the accuracy of NAQFC short-term predictions of ground-level particulate matter of less than 2.5 µm in diameter (PM2.5) by exploiting NASA Earth Science Data with chemical data assimilation. The NAQFC is based on the Community Multiscale Air Quality (CMAQ) model. To improve the initialization of PM2.5 in CMAQ, we developed a new capability in the community Gridpoint Statistical Interpolation (GSI) system to assimilate Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals in CMAQ. Specifically, we developed new capabilities within GSI to read/write CMAQ data, a forward operator that calculates AOD at 550 nm from CMAQ aerosol chemical composition and an adjoint of the forward operator that translates the changes in AOD to aerosol chemical composition. A generalized background error covariance program called "GEN_BE" has been extended to calculate background error covariance using CMAQ output. The background error variances are generated using a combination of both emissions and meteorological perturbations to better capture sources of uncertainties in PM2.5 simulations. The newly developed CMAQ-GSI system is used to perform daily 24-h PM2.5 forecasts with and without data assimilation from 15 July to 14 August 2014, and the resulting forecasts are compared against AirNOW PM2.5 measurements at 550 stations across the U. S. We find that the assimilation of MODIS AOD retrievals improves initialization of the CMAQ model in terms of improved correlation coefficient and reduced bias. However, we notice a large bias in nighttime PM2.5 simulations which is primarily associated with very shallow boundary layer in the model. The developments and results will be discussed in detail during the presentation.

A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.

PubMed

Hong, Huixiao; Shen, Jie; Ng, Hui Wen; Sakkiah, Sugunadevi; Ye, Hao; Ge, Weigong; Gong, Ping; Xiao, Wenming; Tong, Weida

2016-03-25

Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold² software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed.

Establishing Esri ArcGIS Enterprise Platform Capabilities to Support Response Activities of the NASA Earth Science Disasters Program

NASA Astrophysics Data System (ADS)

Molthan, A.; Seepersad, J.; Shute, J.; Carriere, L.; Duffy, D.; Tisdale, B.; Kirschbaum, D.; Green, D. S.; Schwizer, L.

2017-12-01

NASA's Earth Science Disasters Program promotes the use of Earth observations to improve the prediction of, preparation for, response to, and recovery from natural and technological disasters. NASA Earth observations and those of domestic and international partners are combined with in situ observations and models by NASA scientists and partners to develop products supporting disaster mitigation, response, and recovery activities among several end-user partners. These products are accompanied by training to ensure proper integration and use of these materials in their organizations. Many products are integrated along with other observations available from other sources in GIS-capable formats to improve situational awareness and response efforts before, during and after a disaster. Large volumes of NASA observations support the generation of disaster response products by NASA field center scientists, partners in academia, and other institutions. For example, a prediction of high streamflows and inundation from a NASA-supported model may provide spatial detail of flood extent that can be combined with GIS information on population density, infrastructure, and land value to facilitate a prediction of who will be affected, and the economic impact. To facilitate the sharing of these outputs in a common framework that can be easily ingested by downstream partners, the NASA Earth Science Disasters Program partnered with Esri and the NASA Center for Climate Simulation (NCCS) to establish a suite of Esri/ArcGIS services to support the dissemination of routine and event-specific products to end users. This capability has been demonstrated to key partners including the Federal Emergency Management Agency using a case-study example of Hurricane Matthew, and will also help to support future domestic and international disaster events. The Earth Science Disasters Program has also established a longer-term vision to leverage scientists' expertise in the development and delivery of end-user training, increase public awareness of NASA's Disasters Program, and facilitate new partnerships with disaster response organizations. Future research and development will foster generation of products that leverage NASA's Earth observations for disaster prediction, preparation and mitigation, response, and recovery.

Normalized Rotational Multiple Yield Surface Framework (NRMYSF) stress-strain curve prediction method based on small strain triaxial test data on undisturbed Auckland residual clay soils

NASA Astrophysics Data System (ADS)

Noor, M. J. Md; Ibrahim, A.; Rahman, A. S. A.

2018-04-01

Small strain triaxial test measurement is considered to be significantly accurate compared to the external strain measurement using conventional method due to systematic errors normally associated with the test. Three submersible miniature linear variable differential transducer (LVDT) mounted on yokes which clamped directly onto the soil sample at equally 120° from the others. The device setup using 0.4 N resolution load cell and 16 bit AD converter was capable of consistently resolving displacement of less than 1µm and measuring axial strains ranging from less than 0.001% to 2.5%. Further analysis of small strain local measurement data was performed using new Normalized Multiple Yield Surface Framework (NRMYSF) method and compared with existing Rotational Multiple Yield Surface Framework (RMYSF) prediction method. The prediction of shear strength based on combined intrinsic curvilinear shear strength envelope using small strain triaxial test data confirmed the significant improvement and reliability of the measurement and analysis methods. Moreover, the NRMYSF method shows an excellent data prediction and significant improvement toward more reliable prediction of soil strength that can reduce the cost and time of experimental laboratory test.

A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Shengzhi; Ming, Bo; Huang, Qiang

It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecastingmore » models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.« less

Bringing modeling to the masses: A web based system to predict potential species distributions

USGS Publications Warehouse

Graham, Jim; Newman, Greg; Kumar, Sunil; Jarnevich, Catherine S.; Young, Nick; Crall, Alycia W.; Stohlgren, Thomas J.; Evangelista, Paul

2010-01-01

Predicting current and potential species distributions and abundance is critical for managing invasive species, preserving threatened and endangered species, and conserving native species and habitats. Accurate predictive models are needed at local, regional, and national scales to guide field surveys, improve monitoring, and set priorities for conservation and restoration. Modeling capabilities, however, are often limited by access to software and environmental data required for predictions. To address these needs, we built a comprehensive web-based system that: (1) maintains a large database of field data; (2) provides access to field data and a wealth of environmental data; (3) accesses values in rasters representing environmental characteristics; (4) runs statistical spatial models; and (5) creates maps that predict the potential species distribution. The system is available online at www.niiss.org, and provides web-based tools for stakeholders to create potential species distribution models and maps under current and future climate scenarios.

The Defense Threat Reduction Agency's Technical Nuclear Forensics Research and Development Program

NASA Astrophysics Data System (ADS)

Franks, J.

2015-12-01

The Defense Threat Reduction Agency (DTRA) Technical Nuclear Forensics (TNF) Research and Development (R&D) Program's overarching goal is to design, develop, demonstrate, and transition advanced technologies and methodologies that improve the interagency operational capability to provide forensics conclusions after the detonation of a nuclear device. This goal is attained through the execution of three focus areas covering the span of the TNF process to enable strategic decision-making (attribution): Nuclear Forensic Materials Exploitation - Development of targeted technologies, methodologies and tools enabling the timely collection, analysis and interpretation of detonation materials.Prompt Nuclear Effects Exploitation - Improve ground-based capabilities to collect prompt nuclear device outputs and effects data for rapid, complementary and corroborative information.Nuclear Forensics Device Characterization - Development of a validated and verified capability to reverse model a nuclear device with high confidence from observables (e.g., prompt diagnostics, sample analysis, etc.) seen after an attack. This presentation will outline DTRA's TNF R&D strategy and current investments, with efforts focusing on: (1) introducing new technical data collection capabilities (e.g., ground-based prompt diagnostics sensor systems; innovative debris collection and analysis); (2) developing new TNF process paradigms and concepts of operations to decrease timelines and uncertainties, and increase results confidence; (3) enhanced validation and verification (V&V) of capabilities through technology evaluations and demonstrations; and (4) updated weapon output predictions to account for the modern threat environment. A key challenge to expanding these efforts to a global capability is the need for increased post-detonation TNF international cooperation, collaboration and peer reviews.

Panel management, team culture, and worklife experience.

PubMed

Willard-Grace, Rachel; Dubé, Kate; Hessler, Danielle; O'Brien, Bridget; Earnest, Gillian; Gupta, Reena; Shunk, Rebecca; Grumbach, Kevin

2015-09-01

Burnout and professional dissatisfaction are threats to the primary care workforce. We investigated the relationship between panel management capability, team culture, cynicism, and perceived "do-ability" of primary care among primary care providers (PCPs) and staff in primary care practices. We surveyed 326 PCPs and 142 staff members in 10 county-administered, 6 university-run, and 3 Veterans Affairs primary care clinics in a large urban area in 2013. Predictor variables included capability for performing panel management and perception of team culture. Outcome variables included 2 work experience measures--the Maslach Burnout Inventory cynicism scale and a 1-item measure of the "do-ability" of primary care this year compared with last year. Generalized Estimation Equation (GEE) models were used to account for clustering at the clinic level. Greater panel management capability and higher team culture were associated with lower cynicism among PCPs and staff and higher reported "do-ability" of primary care among PCPs. Panel management capability and team culture interacted to predict the 2 work experience outcomes. Among PCPs and staff reporting high team culture, there was little association between panel management capability and the outcomes, which were uniformly positive. However, there was a strong relationship between greater panel management capability and improved work experience outcomes for PCPs and staff reporting low team culture. Team-based processes of care such as panel management may be an important strategy to protect against cynicism and dissatisfaction in primary care, particularly in settings that are still working to improve their team culture. (c) 2015 APA, all rights reserved).

Predicting concrete corrosion of sewers using artificial neural network.

PubMed

Jiang, Guangming; Keller, Jurg; Bond, Philip L; Yuan, Zhiguo

2016-04-01

Corrosion is often a major failure mechanism for concrete sewers and under such circumstances the sewer service life is largely determined by the progression of microbially induced concrete corrosion. The modelling of sewer processes has become possible due to the improved understanding of in-sewer transformation. Recent systematic studies about the correlation between the corrosion processes and sewer environment factors should be utilized to improve the prediction capability of service life by sewer models. This paper presents an artificial neural network (ANN)-based approach for modelling the concrete corrosion processes in sewers. The approach included predicting the time for the corrosion to initiate and then predicting the corrosion rate after the initiation period. The ANN model was trained and validated with long-term (4.5 years) corrosion data obtained in laboratory corrosion chambers, and further verified with field measurements in real sewers across Australia. The trained model estimated the corrosion initiation time and corrosion rates very close to those measured in Australian sewers. The ANN model performed better than a multiple regression model also developed on the same dataset. Additionally, the ANN model can serve as a prediction framework for sewer service life, which can be progressively improved and expanded by including corrosion rates measured in different sewer conditions. Furthermore, the proposed methodology holds promise to facilitate the construction of analytical models associated with corrosion processes of concrete sewers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Robust multiscale prediction of Po River discharge using a twofold AR-NN approach

NASA Astrophysics Data System (ADS)

Alessio, Silvia; Taricco, Carla; Rubinetti, Sara; Zanchettin, Davide; Rubino, Angelo; Mancuso, Salvatore

2017-04-01

The Mediterranean area is among the regions most exposed to hydroclimatic changes, with a likely increase of frequency and duration of droughts in the last decades and potentially substantial future drying according to climate projections. However, significant decadal variability is often superposed or even dominates these long-term hydrological trend as observed, for instance, in North Italian precipitation and river discharge records. The capability to accurately predict such decadal changes is, therefore, of utmost environmental and social importance. In order to forecast short and noisy hydroclimatic time series, we apply a twofold statistical approach that we improved with respect to previous works [1]. Our prediction strategy consists in the application of two independent methods that use autoregressive models and feed-forward neural networks. Since all prediction methods work better on clean signals, the predictions are not performed directly on the series, but rather on each significant variability components extracted with Singular Spectrum Analysis (SSA). In this contribution, we will illustrate the multiscale prediction approach and its application to the case of decadal prediction of annual-average Po River discharges (Italy). The discharge record is available for the last 209 years and allows to work with both interannual and decadal time-scale components. Fifteen-year forecasts obtained with both methods robustly indicate a prominent dry period in the second half of the 2020s. We will discuss advantages and limitations of the proposed statistical approach in the light of the current capabilities of decadal climate prediction systems based on numerical climate models, toward an integrated dynamical and statistical approach for the interannual-to-decadal prediction of hydroclimate variability in medium-size river basins. [1] Alessio et. al., Natural variability and anthropogenic effects in a Central Mediterranean core, Clim. of the Past, 8, 831-839, 2012.

Overview of the NASA Subsonic Rotary Wing Aeronautics Research Program in Rotorcraft Crashworthiness

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Kellas, Sotiris; Fuchs, Yvonne T.

2009-01-01

This paper provides an overview of rotorcraft crashworthiness research being conducted at NASA Langley Research Center under sponsorship of the Subsonic Rotary Wing (SRW) Aeronautics Program. The research is focused in two areas: development of an externally deployable energy attenuating concept and improved prediction of rotorcraft crashworthiness. The deployable energy absorber (DEA) is a composite honeycomb structure, with a unique flexible hinge design that allows the honeycomb to be packaged and remain flat until needed for deployment. The capabilities of the DEA have been demonstrated through component crush tests and vertical drop tests of a retrofitted fuselage section onto different surfaces or terrain. The research on improved prediction of rotorcraft crashworthiness is focused in several areas including simulating occupant responses and injury risk assessment, predicting multi-terrain impact, and utilizing probabilistic analysis methods. A final task is to perform a system-integrated simulation of a full-scale helicopter crash test onto a rigid surface. A brief description of each research task is provided along with a summary of recent accomplishments.

Overview of the NASA Subsonic Rotary Wing Aeronautics Research Program in Rotorcraft Crashworthiness

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fuchs, Yvonne T.; Kellas, Sotiris

2008-01-01

This paper provides an overview of rotorcraft crashworthiness research being conducted at NASA Langley Research Center under sponsorship of the Subsonic Rotary Wing (SRW) Aeronautics Program. The research is focused in two areas: development of an externally deployable energy attenuating concept and improved prediction of rotorcraft crashworthiness. The deployable energy absorber (DEA) is a composite honeycomb structure, with a unique flexible hinge design that allows the honeycomb to be packaged and remain flat until needed for deployment. The capabilities of the DEA have been demonstrated through component crush tests and vertical drop tests of a retrofitted fuselage section onto different surfaces or terrain. The research on improved prediction of rotorcraft crashworthiness is focused in several areas including simulating occupant responses and injury risk assessment, predicting multi-terrain impact, and utilizing probabilistic analysis methods. A final task is to perform a system-integrated simulation of a full-scale helicopter crash test onto a rigid surface. A brief description of each research task is provided along with a summary of recent accomplishments.

Adding-point strategy for reduced-order hypersonic aerothermodynamics modeling based on fuzzy clustering

NASA Astrophysics Data System (ADS)

Chen, Xin; Liu, Li; Zhou, Sida; Yue, Zhenjiang

2016-09-01

Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.

In Pursuit of Improving Airburst and Ground Damage Predictions: Recent Advances in Multi-Body Aerodynamic Testing and Computational Tools Validation

NASA Technical Reports Server (NTRS)

Venkatapathy, Ethiraj; Gulhan, Ali; Aftosmis, Michael; Brock, Joseph; Mathias, Donovan; Need, Dominic; Rodriguez, David; Seltner, Patrick; Stern, Eric; Wiles, Sebastian

2017-01-01

An airburst from a large asteroid during entry can cause significant ground damage. The damage depends on the energy and the altitude of airburst. Breakup of asteroids into fragments and their lateral spread have been observed. Modeling the underlying physics of fragmented bodies interacting at hypersonic speeds and the spread of fragments is needed for a true predictive capability. Current models use heuristic arguments and assumptions such as pancaking or point source explosive energy release at pre-determined altitude or an assumed fragmentation spread rate to predict airburst damage. A multi-year collaboration between German Aerospace Center (DLR) and NASA has been established to develop validated computational tools to address the above challenge.

Preliminary analysis of STS-2 entry flight data

NASA Technical Reports Server (NTRS)

1982-01-01

A preliminary analysis of the data obtained during the entry of the STS-2 flight was completed. The stability and control derivatives from STS-2 were examined. Questions still remain throughout the flight envelope and the area below Mach 3 needs more study. With three controls operating in a high gain feedback system, it is difficult to separate the individual effects of each of the controls. Analysis of the aerothermal data shows that wing structural-temperature measurements are generally repeatable and consistent with the trajectories. The measured wing upper surface temperatures are in reasonable agreement with Dryden predictions but wing lower surface temperatures are higher than Dryden predictions. Heating and heat transfer models will be adjusted to improve the temperature prediction capability for future trajectories.

FN-DFE: Fuzzy-Neural Data Fusion Engine for Enhanced State-Awareness of Resilient Hybrid Energy System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ondrej Linda; Dumidu Wijayasekara; Milos Manic

Resiliency and improved state-awareness of modern critical infrastructures, such as energy production and industrial systems, is becoming increasingly important. As control systems become increasingly complex, the number of inputs and outputs increase. Therefore, in order to maintain sufficient levels of state-awareness, a robust system state monitoring must be implemented that correctly identifies system behavior even when one or more sensors are faulty. Furthermore, as intelligent cyber adversaries become more capable, incorrect values may be fed to the operators. To address these needs, this paper proposes a Fuzzy-Neural Data Fusion Engine (FN-DFE) for resilient state-awareness of control systems. The designed FN-DFEmore » is composed of a three-layered system consisting of: 1) traditional threshold based alarms, 2) anomalous behavior detector using self-organizing fuzzy logic system, and 3) artificial neural network based system modeling and prediction. The improved control system state-awareness is achieved via fusing input data from multiple sources and combining them into robust anomaly indicators. In addition, the neural network based signal predictions are used to augment the resiliency of the system and provide coherent state-awareness despite temporary unavailability of sensory data. The proposed system was integrated and tested with a model of the Idaho National Laboratory’s (INL) hybrid energy system facility know as HYTEST. Experimental results demonstrate that the proposed FN-DFE provides timely plant performance monitoring and anomaly detection capabilities. It was shown that the system is capable of identifying intrusive behavior significantly earlier than conventional threshold based alarm systems.« less

A review and update of the NASA aircraft noise prediction program propeller analysis system

NASA Technical Reports Server (NTRS)

Golub, Robert A.; Nguyen, L. Cathy

1989-01-01

The National Aeronautics and Space Administration (NASA) Aircraft Noise Prediction Program (ANOPP) Propeller Analysis System (PAS) is a set of computational modules for predicting the aerodynamics, performance, and noise of propellers. The ANOPP PAS has the capability to predict noise levels for propeller aircraft certification and produce parametric scaling laws for the adjustment of measured data to reference conditions. A technical overview of the prediction techniques incorporated into the system is presented. The prediction system has been applied to predict the noise signature of a variety of propeller configurations including the effects of propeller angle of attack. A summary of these validation studies is discussed with emphasis being placed on the wind tunnel and flight test programs sponsored by the Federal Aviation Administration (FAA) for the Piper Cherokee Lance aircraft. A number of modifications and improvements have been made to the system and both DEC VAX and IBM-PC versions of the system have been added to the original CDC NOS version.

Investigation of a Parabolic Iterative Solver for Three-dimensional Configurations

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Watson, Willie R.; Mani, Ramani

2007-01-01

A parabolic iterative solution procedure is investigated that seeks to extend the parabolic approximation used within the internal propagation module of the duct noise propagation and radiation code CDUCT-LaRC. The governing convected Helmholtz equation is split into a set of coupled equations governing propagation in the positive and negative directions. The proposed method utilizes an iterative procedure to solve the coupled equations in an attempt to account for possible reflections from internal bifurcations, impedance discontinuities, and duct terminations. A geometry consistent with the NASA Langley Curved Duct Test Rig is considered and the effects of acoustic treatment and non-anechoic termination are included. Two numerical implementations are studied and preliminary results indicate that improved accuracy in predicted amplitude and phase can be obtained for modes at a cut-off ratio of 1.7. Further predictions for modes at a cut-off ratio of 1.1 show improvement in predicted phase at the expense of increased amplitude error. Possible methods of improvement are suggested based on analytic and numerical analysis. It is hoped that coupling the parabolic iterative approach with less efficient, high fidelity finite element approaches will ultimately provide the capability to perform efficient, higher fidelity acoustic calculations within complex 3-D geometries for impedance eduction and noise propagation and radiation predictions.

bpRNA: large-scale automated annotation and analysis of RNA secondary structure.

PubMed

Danaee, Padideh; Rouches, Mason; Wiley, Michelle; Deng, Dezhong; Huang, Liang; Hendrix, David

2018-05-09

While RNA secondary structure prediction from sequence data has made remarkable progress, there is a need for improved strategies for annotating the features of RNA secondary structures. Here, we present bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature. We also introduce several new informative representations of RNA structure types to improve structure visualization and interpretation. We have further used bpRNA to generate a web-accessible meta-database, 'bpRNA-1m', of over 100 000 single-molecule, known secondary structures; this is both more fully and accurately annotated and over 20-times larger than existing databases. We use a subset of the database with highly similar (≥90% identical) sequences filtered out to report on statistical trends in sequence, flanking base pairs, and length. Both the bpRNA method and the bpRNA-1m database will be valuable resources both for specific analysis of individual RNA molecules and large-scale analyses such as are useful for updating RNA energy parameters for computational thermodynamic predictions, improving machine learning models for structure prediction, and for benchmarking structure-prediction algorithms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dahlburg, Jill; Corones, James; Batchelor, Donald

Fusion is potentially an inexhaustible energy source whose exploitation requires a basic understanding of high-temperature plasmas. The development of a science-based predictive capability for fusion-relevant plasmas is a challenge central to fusion energy science, in which numerical modeling has played a vital role for more than four decades. A combination of the very wide range in temporal and spatial scales, extreme anisotropy, the importance of geometric detail, and the requirement of causality which makes it impossible to parallelize over time, makes this problem one of the most challenging in computational physics. Sophisticated computational models are under development for many individualmore » features of magnetically confined plasmas and increases in the scope and reliability of feasible simulations have been enabled by increased scientific understanding and improvements in computer technology. However, full predictive modeling of fusion plasmas will require qualitative improvements and innovations to enable cross coupling of a wider variety of physical processes and to allow solution over a larger range of space and time scales. The exponential growth of computer speed, coupled with the high cost of large-scale experimental facilities, makes an integrated fusion simulation initiative a timely and cost-effective opportunity. Worldwide progress in laboratory fusion experiments provides the basis for a recent FESAC recommendation to proceed with a burning plasma experiment (see FESAC Review of Burning Plasma Physics Report, September 2001). Such an experiment, at the frontier of the physics of complex systems, would be a huge step in establishing the potential of magnetic fusion energy to contribute to the world’s energy security. An integrated simulation capability would dramatically enhance the utilization of such a facility and lead to optimization of toroidal fusion plasmas in general. This science-based predictive capability, which was cited in the FESAC integrated planning document (IPPA, 2000), represents a significant opportunity for the DOE Office of Science to further the understanding of fusion plasmas to a level unparalleled worldwide.« less

Benchmarking of Neutron Production of Heavy-Ion Transport Codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Remec, Igor; Ronningen, Reginald M.; Heilbronn, Lawrence

Accurate prediction of radiation fields generated by heavy ion interactions is important in medical applications, space missions, and in design and operation of rare isotope research facilities. In recent years, several well-established computer codes in widespread use for particle and radiation transport calculations have been equipped with the capability to simulate heavy ion transport and interactions. To assess and validate these capabilities, we performed simulations of a series of benchmark-quality heavy ion experiments with the computer codes FLUKA, MARS15, MCNPX, and PHITS. We focus on the comparisons of secondary neutron production. Results are encouraging; however, further improvements in models andmore » codes and additional benchmarking are required.« less

Benchmarking of Heavy Ion Transport Codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Remec, Igor; Ronningen, Reginald M.; Heilbronn, Lawrence

Accurate prediction of radiation fields generated by heavy ion interactions is important in medical applications, space missions, and in designing and operation of rare isotope research facilities. In recent years, several well-established computer codes in widespread use for particle and radiation transport calculations have been equipped with the capability to simulate heavy ion transport and interactions. To assess and validate these capabilities, we performed simulations of a series of benchmark-quality heavy ion experiments with the computer codes FLUKA, MARS15, MCNPX, and PHITS. We focus on the comparisons of secondary neutron production. Results are encouraging; however, further improvements in models andmore » codes and additional benchmarking are required.« less

KSC-2014-4236

NASA Image and Video Library

2014-10-15

VANDENBERG AIR FORCE BASE, Calif. – The truck transporting NASA's Soil Moisture Active Passive, or SMAP, spacecraft arrives at the Astrotech payload processing facility on Vandenberg Air Force Base in California. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2872

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – The lid is removed from the transportation trailer containing a half section of the 10-foot-diameter fairing for NASA's Soil Moisture Active Passive mission, or SMAP, in the Building 836 high bay on south Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/U.S. Air Force 30th Space Wing

KSC-2014-4244

NASA Image and Video Library

2014-10-15

VANDENBERG AIR FORCE BASE, Calif. – Workers push the pallet supporting the transportation container protecting NASA's Soil Moisture Active Passive, or SMAP, spacecraft into the Astrotech payload processing facility on Vandenberg Air Force Base in California. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3333

NASA Image and Video Library

2014-07-31

VANDENBERG AIR FORCE BASE, Calif. – The Delta II interstage adapter, or ISA, for NASA's Soil Moisture Active Passive mission, or SMAP, is lowered onto the flatbed of the truck that will transport it from the Building 836 hangar on south Vandenberg Air Force Base in California to the pad. A United Launch Alliance Delta II rocket will loft SMAP into orbit from Vandenberg's Space Launch Complex 2. The ISA connects the Delta II first and second stages and encloses the second stage engine and thrust section. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Offload

NASA Image and Video Library

2014-10-15

NASA's Soil Moisture Active Passive, or SMAP, spacecraft, enclosed in a transportation container, is offloaded from the truck on which it traveled from the Jet Propulsion Laboratory in Pasadena, California, to the Astrotech payload processing facility on Vandenberg Air Force Base in California. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-3171

NASA Image and Video Library

2014-06-20

VANDENBERG AIR FORCE BASE, Calif. – Workers prepare to lift the canister containing the interstage adapter, or ISA, for NASA's Soil Moisture Active Passive mission, or SMAP, from its transportation trailer in the high bay of the Building 836 hangar on south Vandenberg Air Force Base in California. A United Launch Alliance Delta II rocket will loft SMAP into orbit from Vandenberg's Space Launch Complex 2. The ISA connects the Delta II first and second stages and encloses the second stage engine and thrust section. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-4243

NASA Image and Video Library

2014-10-15

VANDENBERG AIR FORCE BASE, Calif. – Workers push the pallet supporting the transportation container protecting NASA's Soil Moisture Active Passive, or SMAP, spacecraft into the Astrotech payload processing facility on Vandenberg Air Force Base in California. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3169

NASA Image and Video Library

2014-06-20

VANDENBERG AIR FORCE BASE, Calif. – As the cover of the transportation trailer is lifted in the high bay of the Building 836 hangar on south Vandenberg Air Force Base in California, the canister containing the interstage adapter, or ISA, for NASA's Soil Moisture Active Passive mission, or SMAP, comes into view. A United Launch Alliance Delta II rocket will loft SMAP into orbit from Vandenberg's Space Launch Complex 2. The ISA connects the Delta II first and second stages and encloses the second stage engine and thrust section. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

SMAP Spacecraft Arrives at Astrotech

NASA Image and Video Library

2014-10-14

The transportation container protecting NASA's Soil Moisture Active Passive, or SMAP, spacecraft is offloaded from the truck that delivered it from the Jet Propulsion Laboratory in Pasadena, California, to the Astrotech payload processing facility on Vandenberg Air Force Base in California with the aid of a forklift. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015.

KSC-2014-3172

NASA Image and Video Library

2014-06-20

VANDENBERG AIR FORCE BASE, Calif. – The canister containing the interstage adapter, or ISA, for NASA's Soil Moisture Active Passive mission, or SMAP, is lifted out of its transportation trailer in the high bay of the Building 836 hangar on south Vandenberg Air Force Base in California. A United Launch Alliance Delta II rocket will loft SMAP into orbit from Vandenberg's Space Launch Complex 2. The ISA connects the Delta II first and second stages and encloses the second stage engine and thrust section. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3460

NASA Image and Video Library

2014-08-07

VANDENBERG AIR FORCE BASE, Calif. – Preparations are underway to transport a half section of the 10-foot-diameter fairing for NASA's Soil Moisture Active Passive mission, or SMAP, from the Horizontal Integration Facility to the nearby mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for no earlier than November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3332

NASA Image and Video Library

2014-07-31

VANDENBERG AIR FORCE BASE, Calif. – The Delta II interstage adapter, or ISA, for NASA's Soil Moisture Active Passive mission, or SMAP, glides in a vertical position across the Building 836 hangar on south Vandenberg Air Force Base in California toward the truck that will transport it to the pad. A United Launch Alliance Delta II rocket will loft SMAP into orbit from Vandenberg's Space Launch Complex 2. The ISA connects the Delta II first and second stages and encloses the second stage engine and thrust section. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3334

NASA Image and Video Library

2014-07-31

VANDENBERG AIR FORCE BASE, Calif. – Workers secure the Delta II interstage adapter, or ISA, for NASA's Soil Moisture Active Passive mission, or SMAP, onto the flatbed of the truck that will transport it to the pad from the Building 836 hangar on south Vandenberg Air Force Base in California. A United Launch Alliance Delta II rocket will loft SMAP into orbit from Vandenberg's Space Launch Complex 2. The ISA connects the Delta II first and second stages and encloses the second stage engine and thrust section. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2873

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Workers prepare to lift a half section of the 10-foot-diameter fairing for NASA's Soil Moisture Active Passive mission, or SMAP, from a transportation trailer in the Building 836 high bay on south Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/U.S. Air Force 30th Space Wing

KSC-2014-3164

NASA Image and Video Library

2014-07-14

VANDENBERG AIR FORCE BASE, Calif. – The second stage, or upper stage, of a United Launch Alliance Delta II rocket and the transporter to which it is attached are lifted out of a transportation trailer in the Building 836 hangar on south Vandenberg Air Force Base in California. The stage will be moved to the Horizontal Integration Facility at Space Launch Complex 2 for further processing. The Delta II rocket will be used to deliver NASA's Soil Moisture Active Passive mission, or SMAP, into orbit. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-2874

NASA Image and Video Library

2014-06-03

VANDENBERG AIR FORCE BASE, Calif. – Workers attach a half section of the 10-foot-diameter fairing for NASA's Soil Moisture Active Passive mission, or SMAP, to an overhead crane to lift it from a transportation trailer in the Building 836 high bay on south Vandenberg Air Force Base in California. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket from Space Launch Complex 2. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/U.S. Air Force 30th Space Wing

KSC-2014-3471

NASA Image and Video Library

2014-08-07

VANDENBERG AIR FORCE BASE, Calif. – A half section of the 10-foot-diameter fairing for NASA's Soil Moisture Active Passive mission, or SMAP, is transferred into the environmental enclosure at the top of the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California where it will be stowed until arrival of the spacecraft. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for no earlier than November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3502

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The Delta II interstage adapter, or ISA, for NASA's Soil Moisture Active Passive mission, or SMAP, is transferred into the environmental enclosure in the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. Processing of the United Launch Alliance Delta II rocket that will loft SMAP into orbit is underway at the pad. The ISA connects the Delta II first and second stages and encloses the second stage engine and thrust section. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

KSC-2014-3470

NASA Image and Video Library

2014-08-07

VANDENBERG AIR FORCE BASE, Calif. – A half section of the 10-foot-diameter fairing for NASA's Soil Moisture Active Passive mission, or SMAP, is hoisted to the top of the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California where it will be transferred into the environmental enclosure and stowed until arrival of the spacecraft. The fairing will protect the SMAP spacecraft from the heat and aerodynamic pressure generated during its ascent to orbit aboard a United Launch Alliance Delta II rocket. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data will also be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for no earlier than November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

Modelling bloom formation of the toxic dinoflagellates Dinophysis acuminata and Dinophysis caudata in a highly modified estuary, south eastern Australia

NASA Astrophysics Data System (ADS)

Ajani, Penelope; Larsson, Michaela E.; Rubio, Ana; Bush, Stephen; Brett, Steve; Farrell, Hazel

2016-12-01

Dinoflagellates belonging to the toxigenic genus Dinophysis are increasing in abundance in the Hawkesbury River, south-eastern Australia. This study investigates a twelve year time series of abundance and physico-chemical data to model these blooms. Four species were reported over the sampling campaign - Dinophysis acuminata, Dinophysis caudata, Dinophysis fortii and Dinophysis tripos-with D. acuminata and D. caudata being most abundant. Highest abundance of D. acuminata occurred in the austral spring (max. abundance 4500 cells l-1), whilst highest D. caudata occurred in the summer to autumn (max. 12,000 cells l-1). Generalised additive models revealed abundance of D. acuminata was significantly linked to season, thermal stratification and nutrients, whilst D. caudata was associated with nutrients, salinity and dissolved oxygen. The models' predictive capability was up to 60% for D. acuminata and 53% for D. caudata. Altering sampling strategies during blooms accompanied with in situ high resolution monitoring will further improve Dinophysis bloom prediction capability.

KSC-2015-1231

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The sun sets over the West Cost prior to the launch gantry being rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1230

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The sun sets over the West Cost prior to the launch gantry being rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2015-1232

NASA Image and Video Library

2015-01-28

VANDENBERG AIR FORCE BASE, Calif. – The sun sets over the West Cost prior to the launch gantry being rolled back to reveal the United Launch Alliance Delta II rocket with the Soil Moisture Active Passive, or SMAP, satellite aboard, at the Space Launch Complex 2 at Vandenberg Air Force Base, California. SMAP is a remote sensing mission designed to measure and map the Earth's soil moisture distribution and freeze/thaw stat with unprecedented accuracy, resolution and coverage. SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/Randy Beaudoin

KSC-2014-4287

NASA Image and Video Library

2014-10-16

VANDENBERG AIR FORCE BASE, Calif. – Inside the Astrotech payload processing facility on Vandenberg Air Force Base in California, engineers and technicians mount NASA's Soil Moisture Active Passive, or SMAP, spacecraft on a work platform. SMAP will launch on a Delta II 7320 configuration vehicle featuring a United Launch Alliance first stage booster powered by an Aerojet Rocketdyne RS-27A main engine and three Alliant Techsystems, or ATK, strap-on solid rocket motors. Once on station in Earth orbit, SMAP will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP data also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch from Space Launch Complex 2 is targeted for Jan. 29, 2015. To learn more about SMAP, visit http://smap.jpl.nasa.gov Photo credit: NASA/ Randy Beaudoin

Predicting IVF Outcome: A Proposed Web-based System Using Artificial Intelligence.

PubMed

Siristatidis, Charalampos; Vogiatzi, Paraskevi; Pouliakis, Abraham; Trivella, Marialenna; Papantoniou, Nikolaos; Bettocchi, Stefano

2016-01-01

To propose a functional in vitro fertilization (IVF) prediction model to assist clinicians in tailoring personalized treatment of subfertile couples and improve assisted reproduction outcome. Construction and evaluation of an enhanced web-based system with a novel Artificial Neural Network (ANN) architecture and conformed input and output parameters according to the clinical and bibliographical standards, driven by a complete data set and "trained" by a network expert in an IVF setting. The system is capable to act as a routine information technology platform for the IVF unit and is capable of recalling and evaluating a vast amount of information in a rapid and automated manner to provide an objective indication on the outcome of an artificial reproductive cycle. ANNs are an exceptional candidate in providing the fertility specialist with numerical estimates to promote personalization of healthcare and adaptation of the course of treatment according to the indications. Copyright © 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

KSC-2014-3496

NASA Image and Video Library

2014-08-04

VANDENBERG AIR FORCE BASE, Calif. – The Delta II interstage adapter, or ISA, for NASA's Soil Moisture Active Passive mission, or SMAP, is ready to be lifted into the mobile service tower at Space Launch Complex 2 on Vandenberg Air Force Base in California. A United Launch Alliance Delta II rocket will loft SMAP into orbit. The ISA connects the Delta II first and second stages and encloses the second stage engine and thrust section. The spacecraft will provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The data returned also will be used to quantify net carbon flux in boreal landscapes and to develop improved flood prediction and drought monitoring capabilities. Launch is scheduled for November 2014. To learn more about SMAP, visit http://smap.jpl.nasa.gov. Photo credit: NASA/Randy Beaudoin

European Science Notes Information Bulletin.

DTIC Science & Technology

1992-12-01

presented at Toulouse 󈨠, as a pure success. Wavelet theory is not the "poly- 6. I. Daubechies, Ten Lectures on Wavelets (Soci- water of mathematics," as...methodology was described for reducing NO, emissions while keeping that of other pollut - One major theme of this year’s meeting was ants (e.g., carbon...reported improved capability maintenance methodologies, and pollution control). to predict unsteady heat transfer in turbomachinery lows. A team of

Rapid Prediction of Unsteady Three-Dimensional Viscous Flows in Turbopump Geometries

NASA Technical Reports Server (NTRS)

Dorney, Daniel J.

1998-01-01

A program is underway to improve the efficiency of a three-dimensional Navier-Stokes code and generalize it for nozzle and turbopump geometries. Code modifications have included the implementation of parallel processing software, incorporation of new physical models and generalization of the multiblock capability. The final report contains details of code modifications, numerical results for several nozzle and turbopump geometries, and the implementation of the parallelization software.

Evaluation program for secondary spacecraft cells

NASA Technical Reports Server (NTRS)

Christy, D. E.; Harkness, J. D.

1973-01-01

A life cycle test of secondary electric batteries for spacecraft applications was conducted. A sample number of nickel cadmium batteries were subjected to general performance tests to determine the limit of their actual capabilities. Weaknesses discovered in cell design are reported and aid in research and development efforts toward improving the reliability of spacecraft batteries. A statistical analysis of the life cycle prediction and cause of failure versus test conditions is provided.

Towards a National Space Weather Predictive Capability

NASA Astrophysics Data System (ADS)

Fox, N. J.; Lindstrom, K. L.; Ryschkewitsch, M. G.; Anderson, B. J.; Gjerloev, J. W.; Merkin, V. G.; Kelly, M. A.; Miller, E. S.; Sitnov, M. I.; Ukhorskiy, A. Y.; Erlandson, R. E.; Barnes, R. J.; Paxton, L. J.; Sotirelis, T.; Stephens, G.; Comberiate, J.

2014-12-01

National needs in the area of space weather informational and predictive tools are growing rapidly. Adverse conditions in the space environment can cause disruption of satellite operations, communications, navigation, and electric power distribution grids, leading to a variety of socio-economic losses and impacts on our security. Future space exploration and most modern human endeavors will require major advances in physical understanding and improved transition of space research to operations. At present, only a small fraction of the latest research and development results from NASA, NOAA, NSF and DoD investments are being used to improve space weather forecasting and to develop operational tools. The power of modern research and space weather model development needs to be better utilized to enable comprehensive, timely, and accurate operational space weather tools. The mere production of space weather information is not sufficient to address the needs of those who are affected by space weather. A coordinated effort is required to support research-to-applications transition efforts and to develop the tools required those who rely on this information. In this presentation we will review datasets, tools and models that have resulted from research by scientists at JHU/APL, and examine how they could be applied to support space weather applications in coordination with other community assets and capabilities.

EPA Project Updates: DSSTox and ToxCast Generating New ...

EPA Pesticide Factsheets

EPAs National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than traditionally employed in SAR modeling, and in ways that facilitate data-mining, and data read-across. The DSSTox Structure-Browser, launched in September 2007, provides structure searchability across all published DSSTox toxicity-related inventory, and is enabling linkages between previously isolated toxicity data resources. As of early March 2008, the public DSSTox inventory as been integrated into PubChem, allowing a user to take full advantage of PubChem structure-activity and bioassay clustering features. The most recent DSSTox version of Carcinogenic Potency Database file (CPDBAS) illustrates ways in which various summary definitions of carcinogenic activity can be employed in modeling and data mining. Phase I of the ToxCast project is generating high-throughput screening data from several hundred biochemical and cell-based assays for a set of 320 chemicals, mostly pesticide actives, with rich toxicology profiles. Incorporating and expanding traditional SAR Concepts into this new high-throughput and data-rich would pose conceptual and practical challenges, but also holds great promise for improving predictive capabilities. EPA's National Center for Computational Toxicology is bu

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

NASA Astrophysics Data System (ADS)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

Advanced quantitative magnetic nondestructive evaluation methods - Theory and experiment

NASA Technical Reports Server (NTRS)

Barton, J. R.; Kusenberger, F. N.; Beissner, R. E.; Matzkanin, G. A.

1979-01-01

The paper reviews the scale of fatigue crack phenomena in relation to the size detection capabilities of nondestructive evaluation methods. An assessment of several features of fatigue in relation to the inspection of ball and roller bearings suggested the use of magnetic methods; magnetic domain phenomena including the interaction of domains and inclusions, and the influence of stress and magnetic field on domains are discussed. Experimental results indicate that simplified calculations can be used to predict many features of these results; the data predicted by analytic models which use finite element computer analysis predictions do not agree with respect to certain features. Experimental analyses obtained on rod-type fatigue specimens which show experimental magnetic measurements in relation to the crack opening displacement and volume and crack depth should provide methods for improved crack characterization in relation to fracture mechanics and life prediction.

Surrogate modeling of joint flood risk across coastal watersheds

NASA Astrophysics Data System (ADS)

Bass, Benjamin; Bedient, Philip

2018-03-01

This study discusses the development and performance of a rapid prediction system capable of representing the joint rainfall-runoff and storm surge flood response of tropical cyclones (TCs) for probabilistic risk analysis. Due to the computational demand required for accurately representing storm surge with the high-fidelity ADvanced CIRCulation (ADCIRC) hydrodynamic model and its coupling with additional numerical models to represent rainfall-runoff, a surrogate or statistical model was trained to represent the relationship between hurricane wind- and pressure-field characteristics and their peak joint flood response typically determined from physics based numerical models. This builds upon past studies that have only evaluated surrogate models for predicting peak surge, and provides the first system capable of probabilistically representing joint flood levels from TCs. The utility of this joint flood prediction system is then demonstrated by improving upon probabilistic TC flood risk products, which currently account for storm surge but do not take into account TC associated rainfall-runoff. Results demonstrate the source apportionment of rainfall-runoff versus storm surge and highlight that slight increases in flood risk levels may occur due to the interaction between rainfall-runoff and storm surge as compared to the Federal Emergency Management Association's (FEMAs) current practices.

Seamless Modeling for Research & Predictability of Severe Tropical Storms from Weather-to-Climate Timescales

NASA Astrophysics Data System (ADS)

Ramaswamy, V.; Chen, J. H.; Delworth, T. L.; Knutson, T. R.; Lin, S. J.; Murakami, H.; Vecchi, G. A.

2017-12-01

Damages from catastrophic tropical storms such as the 2017 destructive hurricanes compel an acceleration of scientific advancements to understand the genesis, underlying mechanisms, frequency, track, intensity, and landfall of these storms. The advances are crucial to provide improved early information for planners and responders. We discuss the development and utilization of a global modeling capability based on a novel atmospheric dynamical core ("Finite-Volume Cubed Sphere or FV3") which captures the realism of the recent tropical storms and is a part of the NOAA Next-Generation Global Prediction System. This capability is also part of an emerging seamless modeling system at NOAA/ Geophysical Fluid Dynamics Laboratory for simulating the frequency of storms on seasonal and longer timescales with high fidelity e.g., Atlantic hurricane frequency over the past decades. In addition, the same modeling system has also been employed to evaluate the nature of projected storms on the multi-decadal scales under the influence of anthropogenic factors such as greenhouse gases and aerosols. The seamless modeling system thus facilitates research into and the predictability of severe tropical storms across diverse timescales of practical interest to several societal sectors.

California Drought and the 2015-2016 El Niño: Implications for Seasonal Forecasts

NASA Astrophysics Data System (ADS)

Cash, B.

2017-12-01

California winter rainfall is examined in observations and data from the North American Multi-Model Ensemble (NMME) and Project Metis, a new suite of seasonal integrations made using the operational European Centre for Medium-Range Weather Forecasts model. We focus on the 2015-2016 season, and the non-canonical response to the major El Niño event that occurred. We show that the Metis ensemble mean is capable of distinguishing between the response to the 1997/98 and 2015/16 events, while the two events are more similar in the NMME. We also show that unpredicted variations in the atmospheric circulation in the north Pacific significantly affect southern California rainfall totals. Improving prediction of these variations is thus a key target for improving seasonal rainfall predictions for this region.

Development and Transition of the Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) Toolset

NASA Technical Reports Server (NTRS)

Spann, James F.; Zank, G.

2014-01-01

We outline a plan to develop and transition a physics based predictive toolset called The Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) to describe the interplanetary energetic particle and radiation environment throughout the inner heliosphere, including at the Earth. To forecast and "nowcast" the radiation environment requires the fusing of three components: 1) the ability to provide probabilities for incipient solar activity; 2) the use of these probabilities and daily coronal and solar wind observations to model the 3D spatial and temporal heliosphere, including magnetic field structure and transients, within 10 Astronomical Units; and 3) the ability to model the acceleration and transport of energetic particles based on current and anticipated coronal and heliospheric conditions. We describe how to address 1) - 3) based on our existing, well developed, and validated codes and models. The goal of RISCS toolset is to provide an operational forecast and "nowcast" capability that will a) predict solar energetic particle (SEP) intensities; b) spectra for protons and heavy ions; c) predict maximum energies and their duration; d) SEP composition; e) cosmic ray intensities, and f) plasma parameters, including shock arrival times, strength and obliquity at any given heliospheric location and time. The toolset would have a 72 hour predicative capability, with associated probabilistic bounds, that would be updated hourly thereafter to improve the predicted event(s) and reduce the associated probability bounds. The RISCS toolset would be highly adaptable and portable, capable of running on a variety of platforms to accommodate various operational needs and requirements. The described transition plan is based on a well established approach developed in the Earth Science discipline that ensures that the customer has a tool that meets their needs

An enhanced MMW and SMMW/THz imaging system performance prediction and analysis tool for concealed weapon detection and pilotage obstacle avoidance

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Jacobs, Eddie L.; Franck, Charmaine C.; Petkie, Douglas T.; De Lucia, Frank C.

2015-10-01

The U.S. Army Research Laboratory (ARL) has continued to develop and enhance a millimeter-wave (MMW) and submillimeter- wave (SMMW)/terahertz (THz)-band imaging system performance prediction and analysis tool for both the detection and identification of concealed weaponry, and for pilotage obstacle avoidance. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security and Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). Further development of this tool that includes a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures was reported on at the 2011 SPIE Europe Security and Defence Symposium (Prague). This paper provides a comprehensive review of a newly enhanced MMW and SMMW/THz imaging system analysis and design tool that now includes an improved noise sub-model for more accurate and reliable performance predictions, the capability to account for postcapture image contrast enhancement, and the capability to account for concealment material backscatter with active-illumination- based systems. Present plans for additional expansion of the model's predictive capabilities are also outlined.

Use of Air Quality Observations by the National Air Quality Forecast Capability

NASA Astrophysics Data System (ADS)

Stajner, I.; McQueen, J.; Lee, P.; Stein, A. F.; Kondragunta, S.; Ruminski, M.; Tong, D.; Pan, L.; Huang, J. P.; Shafran, P.; Huang, H. C.; Dickerson, P.; Upadhayay, S.

2015-12-01

The National Air Quality Forecast Capability (NAQFC) operational predictions of ozone and wildfire smoke for the United States (U.S.) and predictions of airborne dust for continental U.S. are available at http://airquality.weather.gov/. NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) weather predictions are combined with the Community Multiscale Air Quality (CMAQ) model to produce the ozone predictions and test fine particulate matter (PM2.5) predictions. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model provides smoke and dust predictions. Air quality observations constrain emissions used by NAQFC predictions. NAQFC NOx emissions from mobile sources were updated using National Emissions Inventory (NEI) projections for year 2012. These updates were evaluated over large U.S. cities by comparing observed changes in OMI NO2 observations and NOx measured by surface monitors. The rate of decrease in NOx emission projections from year 2005 to year 2012 is in good agreement with the observed changes over the same period. Smoke emissions rely on the fire locations detected from satellite observations obtained from NESDIS Hazard Mapping System (HMS). Dust emissions rely on a climatology of areas with a potential for dust emissions based on MODIS Deep Blue aerosol retrievals. Verification of NAQFC predictions uses AIRNow compilation of surface measurements for ozone and PM2.5. Retrievals of smoke from GOES satellites are used for verification of smoke predictions. Retrievals of dust from MODIS are used for verification of dust predictions. In summary, observations are the basis for the emissions inputs for NAQFC, they are critical for evaluation of performance of NAQFC predictions, and furthermore they are used in real-time testing of bias correction of PM2.5 predictions, as we continue to work on improving modeling and emissions important for representation of PM2.5.

Prediction of Tissue Outcome and Assessment of Treatment Effect in Acute Ischemic Stroke Using Deep Learning.

PubMed

Nielsen, Anne; Hansen, Mikkel Bo; Tietze, Anna; Mouridsen, Kim

2018-06-01

Treatment options for patients with acute ischemic stroke depend on the volume of salvageable tissue. This volume assessment is currently based on fixed thresholds and single imagine modalities, limiting accuracy. We wish to develop and validate a predictive model capable of automatically identifying and combining acute imaging features to accurately predict final lesion volume. Using acute magnetic resonance imaging, we developed and trained a deep convolutional neural network (CNN deep ) to predict final imaging outcome. A total of 222 patients were included, of which 187 were treated with rtPA (recombinant tissue-type plasminogen activator). The performance of CNN deep was compared with a shallow CNN based on the perfusion-weighted imaging biomarker Tmax (CNN Tmax ), a shallow CNN based on a combination of 9 different biomarkers (CNN shallow ), a generalized linear model, and thresholding of the diffusion-weighted imaging biomarker apparent diffusion coefficient (ADC) at 600×10 -6 mm 2 /s (ADC thres ). To assess whether CNN deep is capable of differentiating outcomes of ±intravenous rtPA, patients not receiving intravenous rtPA were included to train CNN deep, -rtpa to access a treatment effect. The networks' performances were evaluated using visual inspection, area under the receiver operating characteristic curve (AUC), and contrast. CNN deep yields significantly better performance in predicting final outcome (AUC=0.88±0.12) than generalized linear model (AUC=0.78±0.12; P =0.005), CNN Tmax (AUC=0.72±0.14; P <0.003), and ADC thres (AUC=0.66±0.13; P <0.0001) and a substantially better performance than CNN shallow (AUC=0.85±0.11; P =0.063). Measured by contrast, CNN deep improves the predictions significantly, showing superiority to all other methods ( P ≤0.003). CNN deep also seems to be able to differentiate outcomes based on treatment strategy with the volume of final infarct being significantly different ( P =0.048). The considerable prediction improvement accuracy over current state of the art increases the potential for automated decision support in providing recommendations for personalized treatment plans. © 2018 American Heart Association, Inc.

Assessment and preliminary design of an energy buffer for regenerative braking in electric vehicles

NASA Technical Reports Server (NTRS)

Buchholz, R.; Mathur, A. K.

1979-01-01

Energy buffer systems, capable of storing the vehicle energy during braking and reusing this stored energy during acceleration, were examined. Some of these buffer systems when incorporated in an electric vehicle would result in an improvement in the performance and range under stop and go driving conditions. Buffer systems considered included flywheels, hydropneumatic, pneumatic, spring, and regenerative braking. Buffer ranking and rating criteria were established. Buffer systems were rated based on predicted range improvements, consumer acceptance, driveability, safety, reliability and durability, and initial and life cycle costs. A hydropneumatic buffer system was selected.

Small UAV Research and Evolution in Long Endurance Electric Powered Vehicles

NASA Technical Reports Server (NTRS)

Logan, Michael J.; Chu, Julio; Motter, Mark A.; Carter, Dennis L.; Ol, Michael; Zeune, Cale

2007-01-01

This paper describes recent research into the advancement of small, electric powered unmanned aerial vehicle (UAV) capabilities. Specifically, topics include the improvements made in battery technology, design methodologies, avionics architectures and algorithms, materials and structural concepts, propulsion system performance prediction, and others. The results of prototype vehicle designs and flight tests are discussed in the context of their usefulness in defining and validating progress in the various technology areas. Further areas of research need are also identified. These include the need for more robust operating regimes (wind, gust, etc.), and continued improvement in payload fraction vs. endurance.

Improving Ionic Conductivity and Lithium-Ion Transference Number in Lithium-Ion Battery Separators.

PubMed

Zahn, Raphael; Lagadec, Marie Francine; Hess, Michael; Wood, Vanessa

2016-12-07

The microstructure of lithium-ion battery separators plays an important role in separator performance; however, here we show that a geometrical analysis falls short in predicting the lithium-ion transport in the electrolyte-filled pore space. By systematically modifying the surface chemistry of a commercial polyethylene separator while keeping its microstructure unchanged, we demonstrate that surface chemistry, which alters separator-electrolyte interactions, influences ionic conductivity and lithium-ion transference number. Changes in separator surface chemistry, particularly those that increase lithium-ion transference numbers can reduce voltage drops across the separator and improve C-rate capability.

A computer system to analyze showers in nuclear emulsions: Center Director's discretionary fund report

NASA Technical Reports Server (NTRS)

Meegan, C. A.; Fountain, W. F.; Berry, F. A., Jr.

1987-01-01

A system to rapidly digitize data from showers in nuclear emulsions is described. A TV camera views the emulsions though a microscope. The TV output is superimposed on the monitor of a minicomputer. The operator uses the computer's graphics capability to mark the positions of particle tracks. The coordinates of each track are stored on a disk. The computer then predicts the coordinates of each track through successive layers of emulsion. The operator, guided by the predictions, thus tracks and stores the development of the shower. The system provides a significant improvement over purely manual methods of recording shower development in nuclear emulsion stacks.

An improved numerical model for wave rotor design and analysis

NASA Technical Reports Server (NTRS)

Paxson, Daniel E.; Wilson, Jack

1993-01-01

A numerical model has been developed which can predict both the unsteady flows within a wave rotor and the steady averaged flows in the ports. The model is based on the assumptions of one-dimensional, unsteady, and perfect gas flow. Besides the dominant wave behavior, it is also capable of predicting the effects of finite tube opening time, leakage from the tube ends, and viscosity. The relative simplicity of the model makes it useful for design, optimization, and analysis of wave rotor cycles for any application. This paper discusses some details of the model and presents comparisons between the model and two laboratory wave rotor experiments.

An improved numerical model for wave rotor design and analysis

NASA Technical Reports Server (NTRS)

Paxson, Daniel E.; Wilson, Jack

1992-01-01

A numerical model has been developed which can predict both the unsteady flows within a wave rotor and the steady averaged flows in the ports. The model is based on the assumptions of one-dimensional, unsteady, and perfect gas flow. Besides the dominant wave behavior, it is also capable of predicting the effects of finite tube opening time, leakage from the tube ends, and viscosity. The relative simplicity of the model makes it useful for design, optimization, and analysis of wave rotor cycles for any application. This paper discusses some details of the model and presents comparisons between the model and two laboratory wave rotor experiments.

An approach to adjustment of relativistic mean field model parameters

NASA Astrophysics Data System (ADS)

Bayram, Tuncay; Akkoyun, Serkan

2017-09-01

The Relativistic Mean Field (RMF) model with a small number of adjusted parameters is powerful tool for correct predictions of various ground-state nuclear properties of nuclei. Its success for describing nuclear properties of nuclei is directly related with adjustment of its parameters by using experimental data. In the present study, the Artificial Neural Network (ANN) method which mimics brain functionality has been employed for improvement of the RMF model parameters. In particular, the understanding capability of the ANN method for relations between the RMF model parameters and their predictions for binding energies (BEs) of 58Ni and 208Pb have been found in agreement with the literature values.

Advanced prediction technique for the low speed aerodynamics of V/STOL aircraft. Volume 2: User's manual

NASA Technical Reports Server (NTRS)

Beatty, T. D.; Worthey, M. K.

1984-01-01

A computerized prediction method known as the Vought V/STOL Aircraft Propulsive Effects computer program (VAPE) for propulsive induced forces and moments in transition and Short TakeOff and Landing (STOL) flight is improved and evaluated. The VAPE program is capable of evaluating: (1) effects of relative wind about an aircraft, (2) effects of propulsive lift jet entrainment, vorticity and flow blockage, (3) effects of engine inlet flow on the aircraft flow field, (4) engine inlet forces and moments including inlet separation, (5) ground effects in the STOL region of flight, and (6) viscous effects on lifting surfaces.

Survival Regression Modeling Strategies in CVD Prediction.

PubMed

Barkhordari, Mahnaz; Padyab, Mojgan; Sardarinia, Mahsa; Hadaegh, Farzad; Azizi, Fereidoun; Bozorgmanesh, Mohammadreza

2016-04-01

A fundamental part of prevention is prediction. Potential predictors are the sine qua non of prediction models. However, whether incorporating novel predictors to prediction models could be directly translated to added predictive value remains an area of dispute. The difference between the predictive power of a predictive model with (enhanced model) and without (baseline model) a certain predictor is generally regarded as an indicator of the predictive value added by that predictor. Indices such as discrimination and calibration have long been used in this regard. Recently, the use of added predictive value has been suggested while comparing the predictive performances of the predictive models with and without novel biomarkers. User-friendly statistical software capable of implementing novel statistical procedures is conspicuously lacking. This shortcoming has restricted implementation of such novel model assessment methods. We aimed to construct Stata commands to help researchers obtain the aforementioned statistical indices. We have written Stata commands that are intended to help researchers obtain the following. 1, Nam-D'Agostino X 2 goodness of fit test; 2, Cut point-free and cut point-based net reclassification improvement index (NRI), relative absolute integrated discriminatory improvement index (IDI), and survival-based regression analyses. We applied the commands to real data on women participating in the Tehran lipid and glucose study (TLGS) to examine if information relating to a family history of premature cardiovascular disease (CVD), waist circumference, and fasting plasma glucose can improve predictive performance of Framingham's general CVD risk algorithm. The command is adpredsurv for survival models. Herein we have described the Stata package "adpredsurv" for calculation of the Nam-D'Agostino X 2 goodness of fit test as well as cut point-free and cut point-based NRI, relative and absolute IDI, and survival-based regression analyses. We hope this work encourages the use of novel methods in examining predictive capacity of the emerging plethora of novel biomarkers.

A Man-Machine System for Contemporary Counseling Practice: Diagnosis and Prediction.

ERIC Educational Resources Information Center

Roach, Arthur J.

This paper looks at present and future capabilities for diagnosis and prediction in computer-based guidance efforts and reviews the problems and potentials which will accompany the implementation of such capabilities. In addition to necessary procedural refinement in prediction, future developments in computer-based educational and career…

Final Report Collaborative Project. Improving the Representation of Coastal and Estuarine Processes in Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. Tomore » develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.« less

Upper-Tropospheric Winds Derived from Geostationary Satellite Water Vapor Observations

NASA Technical Reports Server (NTRS)

Velden, Christopher S.; Hayden, Christopher M.; Nieman, Steven J.; Menzel, W. Paul; Wanzong, Steven; Goerss, James S.

1997-01-01

The coverage and quality of remotely sensed upper-tropospheric moisture parameters have improved considerably with the deployment of a new generation of operational geostationary meteorological satellites: GOES-8/9 and GMS-5. The GOES-8/9 water vapor imaging capabilities have increased as a result of improved radiometric sensitivity and higher spatial resolution. The addition of a water vapor sensing channel on the latest GMS permits nearly global viewing of upper-tropospheric water vapor (when joined with GOES and Meteosat) and enhances the commonality of geostationary meteorological satellite observing capabilities. Upper-tropospheric motions derived from sequential water vapor imagery provided by these satellites can be objectively extracted by automated techniques. Wind fields can be deduced in both cloudy and cloud-free environments. In addition to the spatially coherent nature of these vector fields, the GOES-8/9 multispectral water vapor sensing capabilities allow for determination of wind fields over multiple tropospheric layers in cloud-free environments. This article provides an update on the latest efforts to extract water vapor motion displacements over meteorological scales ranging from subsynoptic to global. The potential applications of these data to impact operations, numerical assimilation and prediction, and research studies are discussed.

Public health surveillance and infectious disease detection.

PubMed

Morse, Stephen S

2012-03-01

Emerging infectious diseases, such as HIV/AIDS, SARS, and pandemic influenza, and the anthrax attacks of 2001, have demonstrated that we remain vulnerable to health threats caused by infectious diseases. The importance of strengthening global public health surveillance to provide early warning has been the primary recommendation of expert groups for at least the past 2 decades. However, despite improvements in the past decade, public health surveillance capabilities remain limited and fragmented, with uneven global coverage. Recent initiatives provide hope of addressing this issue, and new technological and conceptual advances could, for the first time, place capability for global surveillance within reach. Such advances include the revised International Health Regulations (IHR 2005) and the use of new data sources and methods to improve global coverage, sensitivity, and timeliness, which show promise for providing capabilities to extend and complement the existing infrastructure. One example is syndromic surveillance, using nontraditional and often automated data sources. Over the past 20 years, other initiatives, including ProMED-mail, GPHIN, and HealthMap, have demonstrated new mechanisms for acquiring surveillance data. In 2009 the U.S. Agency for International Development (USAID) began the Emerging Pandemic Threats (EPT) program, which includes the PREDICT project, to build global capacity for surveillance of novel infections that have pandemic potential (originating in wildlife and at the animal-human interface) and to develop a framework for risk assessment. Improved understanding of factors driving infectious disease emergence and new technological capabilities in modeling, diagnostics and pathogen identification, and communications, such as using the increasing global coverage of cellphones for public health surveillance, can further enhance global surveillance.

USGS science in Menlo Park -- a science strategy for the U.S. Geological Survey Menlo Park Science Center, 2005-2015

USGS Publications Warehouse

Brocher, Thomas M.; Carr, Michael D.; Halsing, David L.; John, David A.; Langenheim, V.E.; Mangan, Margaret T.; Marvin-DiPasquale, Mark C.; Takekawa, John Y.; Tiedeman, Claire

2006-01-01

In the spring of 2004, the U.S. Geological Survey (USGS) Menlo Park Center Council commissioned an interdisciplinary working group to develop a forward-looking science strategy for the USGS Menlo Park Science Center in California (hereafter also referred to as "the Center"). The Center has been the flagship research center for the USGS in the western United States for more than 50 years, and the Council recognizes that science priorities must be the primary consideration guiding critical decisions made about the future evolution of the Center. In developing this strategy, the working group consulted widely within the USGS and with external clients and collaborators, so that most stakeholders had an opportunity to influence the science goals and operational objectives.The Science Goals are to: Natural Hazards: Conduct natural-hazard research and assessments critical to effective mitigation planning, short-term forecasting, and event response. Ecosystem Change: Develop a predictive understanding of ecosystem change that advances ecosystem restoration and adaptive management. Natural Resources: Advance the understanding of natural resources in a geologic, hydrologic, economic, environmental, and global context. Modeling Earth System Processes: Increase and improve capabilities for quantitative simulation, prediction, and assessment of Earth system processes.The strategy presents seven key Operational Objectives with specific actions to achieve the scientific goals. These Operational Objectives are to:Provide a hub for technology, laboratories, and library services to support science in the Western Region. Increase advanced computing capabilities and promote sharing of these resources. Enhance the intellectual diversity, vibrancy, and capacity of the work force through improved recruitment and retention. Strengthen client and collaborative relationships in the community at an institutional level.Expand monitoring capability by increasing density, sensitivity, and efficiency and reducing costs of instruments and networks. Encourage a breadth of scientific capabilities in Menlo Park to foster interdisciplinary science. Communicate USGS science to a diverse audience.

DSSTOX WEBSITE LAUNCH: IMPROVING PUBLIC ACCESS ...

EPA Pesticide Factsheets

DSSTox Website Launch: Improving Public Access to Databases for Building Structure-Toxicity Prediction ModelsAnn M. RichardUS Environmental Protection Agency, Research Triangle Park, NC, USADistributed: Decentralized set of standardized, field-delimited databases, each separatelyauthored and maintained, that are able to accommodate diverse toxicity data content;Structure-Searchable: Standard format (SDF) structure-data files that can be readily imported into available chemical relational databases and structure-searched;Tox: Toxicity data as it exists in widely disparate forms in current public databases, spanning diverse toxicity endpoints, test systems, levels of biological content, degrees of summarization, and information content.INTRODUCTIONThe economic and social pressures to reduce the need for animal testing and to better anticipate the potential for human and eco-toxicity of environmental, industrial, or pharmaceutical chemicals are as pressing today as at any time prior. However, the goal of predicting chemical toxicity in its many manifestations, the `T' in 'ADMET' (adsorption, distribution, metabolism, elimination, toxicity), remains one of the most difficult and largely unmet challenges in a chemical screening paradigm [1]. It is widely acknowledged that the single greatest hurdle to improving structure-activity relationship (SAR) toxicity prediction capabilities, in both the pharmaceutical and environmental regulation arenas, is the lack of suffici

Orbit Determination for the Lunar Reconnaissance Orbiter Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Slojkowski, Steven; Lowe, Jonathan; Woodburn, James

2015-01-01

Orbit determination (OD) analysis results are presented for the Lunar Reconnaissance Orbiter (LRO) using a commercially available Extended Kalman Filter, Analytical Graphics' Orbit Determination Tool Kit (ODTK). Process noise models for lunar gravity and solar radiation pressure (SRP) are described and OD results employing the models are presented. Definitive accuracy using ODTK meets mission requirements and is better than that achieved using the operational LRO OD tool, the Goddard Trajectory Determination System (GTDS). Results demonstrate that a Vasicek stochastic model produces better estimates of the coefficient of solar radiation pressure than a Gauss-Markov model, and prediction accuracy using a Vasicek model meets mission requirements over the analysis span. Modeling the effect of antenna motion on range-rate tracking considerably improves residuals and filter-smoother consistency. Inclusion of off-axis SRP process noise and generalized process noise improves filter performance for both definitive and predicted accuracy. Definitive accuracy from the smoother is better than achieved using GTDS and is close to that achieved by precision OD methods used to generate definitive science orbits. Use of a multi-plate dynamic spacecraft area model with ODTK's force model plugin capability provides additional improvements in predicted accuracy.

Interpreting Disruption Prediction Models to Improve Plasma Control

NASA Astrophysics Data System (ADS)

Parsons, Matthew

2017-10-01

In order for the tokamak to be a feasible design for a fusion reactor, it is necessary to minimize damage to the machine caused by plasma disruptions. Accurately predicting disruptions is a critical capability for triggering any mitigative actions, and a modest amount of attention has been given to efforts that employ machine learning techniques to make these predictions. By monitoring diagnostic signals during a discharge, such predictive models look for signs that the plasma is about to disrupt. Typically these predictive models are interpreted simply to give a `yes' or `no' response as to whether a disruption is approaching. However, it is possible to extract further information from these models to indicate which input signals are more strongly correlated with the plasma approaching a disruption. If highly accurate predictive models can be developed, this information could be used in plasma control schemes to make better decisions about disruption avoidance. This work was supported by a Grant from the 2016-2017 Fulbright U.S. Student Program, administered by the Franco-American Fulbright Commission in France.

The value of oxygen-isotope data and multiple discharge records in calibrating a fully-distributed, physically-based rainfall-runoff model (CRUM3) to improve predictive capability

NASA Astrophysics Data System (ADS)

Neill, Aaron; Reaney, Sim

2015-04-01

Fully-distributed, physically-based rainfall-runoff models attempt to capture some of the complexity of the runoff processes that operate within a catchment, and have been used to address a variety of issues including water quality and the effect of climate change on flood frequency. Two key issues are prevalent, however, which call into question the predictive capability of such models. The first is the issue of parameter equifinality which can be responsible for large amounts of uncertainty. The second is whether such models make the right predictions for the right reasons - are the processes operating within a catchment correctly represented, or do the predictive abilities of these models result only from the calibration process? The use of additional data sources, such as environmental tracers, has been shown to help address both of these issues, by allowing for multi-criteria model calibration to be undertaken, and by permitting a greater understanding of the processes operating in a catchment and hence a more thorough evaluation of how well catchment processes are represented in a model. Using discharge and oxygen-18 data sets, the ability of the fully-distributed, physically-based CRUM3 model to represent the runoff processes in three sub-catchments in Cumbria, NW England has been evaluated. These catchments (Morland, Dacre and Pow) are part of the of the River Eden demonstration test catchment project. The oxygen-18 data set was firstly used to derive transit-time distributions and mean residence times of water for each of the catchments to gain an integrated overview of the types of processes that were operating. A generalised likelihood uncertainty estimation procedure was then used to calibrate the CRUM3 model for each catchment based on a single discharge data set from each catchment. Transit-time distributions and mean residence times of water obtained from the model using the top 100 behavioural parameter sets for each catchment were then compared to those derived from the oxygen-18 data to see how well the model captured catchment dynamics. The value of incorporating the oxygen-18 data set, as well as discharge data sets from multiple as opposed to single gauging stations in each catchment, in the calibration process to improve the predictive capability of the model was then investigated. This was achieved by assessing by how much the identifiability of the model parameters and the ability of the model to represent the runoff processes operating in each catchment improved with the inclusion of the additional data sets with respect to the likely costs that would be incurred in obtaining the data sets themselves.

iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE.

PubMed

Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M

2018-01-01

Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.

A Deep Space Orbit Determination Software: Overview and Event Prediction Capability

NASA Astrophysics Data System (ADS)

Kim, Youngkwang; Park, Sang-Young; Lee, Eunji; Kim, Minsik

2017-06-01

This paper presents an overview of deep space orbit determination software (DSODS), as well as validation and verification results on its event prediction capabilities. DSODS was developed in the MATLAB object-oriented programming environment to support the Korea Pathfinder Lunar Orbiter (KPLO) mission. DSODS has three major capabilities: celestial event prediction for spacecraft, orbit determination with deep space network (DSN) tracking data, and DSN tracking data simulation. To achieve its functionality requirements, DSODS consists of four modules: orbit propagation (OP), event prediction (EP), data simulation (DS), and orbit determination (OD) modules. This paper explains the highest-level data flows between modules in event prediction, orbit determination, and tracking data simulation processes. Furthermore, to address the event prediction capability of DSODS, this paper introduces OP and EP modules. The role of the OP module is to handle time and coordinate system conversions, to propagate spacecraft trajectories, and to handle the ephemerides of spacecraft and celestial bodies. Currently, the OP module utilizes the General Mission Analysis Tool (GMAT) as a third-party software component for highfidelity deep space propagation, as well as time and coordinate system conversions. The role of the EP module is to predict celestial events, including eclipses, and ground station visibilities, and this paper presents the functionality requirements of the EP module. The validation and verification results show that, for most cases, event prediction errors were less than 10 millisec when compared with flight proven mission analysis tools such as GMAT and Systems Tool Kit (STK). Thus, we conclude that DSODS is capable of predicting events for the KPLO in real mission applications.

Electroluminescence Studies on Longwavelength Indium Arsenide Quantum Dot Microcavities Grown on Gallium Arsenide

DTIC Science & Technology

2011-12-01

communication links using VCSEL arrays [1, 2], medical imaging using super luminescent diodes [3], and tunable lasers capable of remotely sensing...increase the efficiency of solar cells [6, 7, 8], vastly improve photo detector sensitivity [9], and provide optical memory storage densities predicted...semiconductor lasers” Applied Physics B: Lasers and Optics, Volume 90, Number 2, 2008, Pages 339-343. 6. Nozik, A.J. “Quantum dot solar cells

Benchmarking hydrological model predictive capability for UK River flows and flood peaks.

NASA Astrophysics Data System (ADS)

Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten

2017-04-01

Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results improve our understanding of the predictive capability of simple conceptual hydrological models across the UK and help us to identify where further effort is needed to develop modelling approaches to better represent different catchment and climate typologies.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

A low order flow/acoustics interaction method for the prediction of sound propagation using 3D adaptive hybrid grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kallinderis, Yannis, E-mail: kallind@otenet.gr; Vitsas, Panagiotis A.; Menounou, Penelope

2012-07-15

A low-order flow/acoustics interaction method for the prediction of sound propagation and diffraction in unsteady subsonic compressible flow using adaptive 3-D hybrid grids is investigated. The total field is decomposed into the flow field described by the Euler equations, and the acoustics part described by the Nonlinear Perturbation Equations. The method is shown capable of predicting monopole sound propagation, while employment of acoustics-guided adapted grid refinement improves the accuracy of capturing the acoustic field. Interaction of sound with solid boundaries is also examined in terms of reflection, and diffraction. Sound propagation through an unsteady flow field is examined using staticmore » and dynamic flow/acoustics coupling demonstrating the importance of the latter.« less

Route Optimization for Offloading Congested Meter Fixes

NASA Technical Reports Server (NTRS)

Xue, Min; Zelinski, Shannon

2016-01-01

The Optimized Route Capability (ORC) concept proposed by the FAA facilitates traffic managers to identify and resolve arrival flight delays caused by bottlenecks formed at arrival meter fixes when there exists imbalance between arrival fixes and runways. ORC makes use of the prediction capability of existing automation tools, monitors the traffic delays based on these predictions, and searches the best reroutes upstream of the meter fixes based on the predictions and estimated arrival schedules when delays are over a predefined threshold. Initial implementation and evaluation of the ORC concept considered only reroutes available at the time arrival congestion was first predicted. This work extends previous work by introducing an additional dimension in reroute options such that ORC can find the best time to reroute and overcome the 'firstcome- first-reroute' phenomenon. To deal with the enlarged reroute solution space, a genetic algorithm was developed to solve this problem. Experiments were conducted using the same traffic scenario used in previous work, when an arrival rush was created for one of the four arrival meter fixes at George Bush Intercontinental Houston Airport. Results showed the new approach further improved delay savings. The suggested route changes from the new approach were on average 30 minutes later than those using other approaches, and fewer numbers of reroutes were required. Fewer numbers of reroutes reduce operational complexity and later reroutes help decision makers deal with uncertain situations.

An artificial neural network improves prediction of observed survival in patients with laryngeal squamous carcinoma.

PubMed

Jones, Andrew S; Taktak, Azzam G F; Helliwell, Timothy R; Fenton, John E; Birchall, Martin A; Husband, David J; Fisher, Anthony C

2006-06-01

The accepted method of modelling and predicting failure/survival, Cox's proportional hazards model, is theoretically inferior to neural network derived models for analysing highly complex systems with large datasets. A blinded comparison of the neural network versus the Cox's model in predicting survival utilising data from 873 treated patients with laryngeal cancer. These were divided randomly and equally into a training set and a study set and Cox's and neural network models applied in turn. Data were then divided into seven sets of binary covariates and the analysis repeated. Overall survival was not significantly different on Kaplan-Meier plot, or with either test model. Although the network produced qualitatively similar results to Cox's model it was significantly more sensitive to differences in survival curves for age and N stage. We propose that neural networks are capable of prediction in systems involving complex interactions between variables and non-linearity.

Predicting and explaining the movement of mesoscale oceanographic features using CLIPS

NASA Technical Reports Server (NTRS)

Bridges, Susan; Chen, Liang-Chun; Lybanon, Matthew

1994-01-01

The Naval Research Laboratory has developed an oceanographic expert system that describes the evolution of mesoscale features in the Gulf Stream region of the northwest Atlantic Ocean. These features include the Gulf Stream current and the warm and cold core eddies associated with the Gulf Stream. An explanation capability was added to the eddy prediction component of the expert system in order to allow the system to justify the reasoning process it uses to make predictions. The eddy prediction and explanation components of the system have recently been redesigned and translated from OPS83 to C and CLIPS and the new system is called WATE (Where Are Those Eddies). The new design has improved the system's readability, understandability and maintainability and will also allow the system to be incorporated into the Semi-Automated Mesoscale Analysis System which will eventually be embedded into the Navy's Tactical Environmental Support System, Third Generation, TESS(3).

Estimation of brain network ictogenicity predicts outcome from epilepsy surgery

NASA Astrophysics Data System (ADS)

Goodfellow, M.; Rummel, C.; Abela, E.; Richardson, M. P.; Schindler, K.; Terry, J. R.

2016-07-01

Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal brain lesions or the presence of epileptiform rhythms, do not necessarily predict the best resection strategy. We validate our framework by analysing electrocorticogram (ECoG) recordings from patients who have undergone epilepsy surgery. We find that when post-operative outcome is good, model predictions for optimal strategies align better with the actual surgery undertaken than when post-operative outcome is poor. Crucially, this allows the prediction of optimal surgical strategies and the provision of quantitative prognoses for patients undergoing epilepsy surgery.

Development and verification of NRC`s single-rod fuel performance codes FRAPCON-3 AND FRAPTRAN

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beyer, C.E.; Cunningham, M.E.; Lanning, D.D.

1998-03-01

The FRAPCON and FRAP-T code series, developed in the 1970s and early 1980s, are used by the US Nuclear Regulatory Commission (NRC) to predict fuel performance during steady-state and transient power conditions, respectively. Both code series are now being updated by Pacific Northwest National Laboratory to improve their predictive capabilities at high burnup levels. The newest versions of the codes are called FRAPCON-3 and FRAPTRAN. The updates to fuel property and behavior models are focusing on providing best estimate predictions under steady-state and fast transient power conditions up to extended fuel burnups (> 55 GWd/MTU). Both codes will be assessedmore » against a data base independent of the data base used for code benchmarking and an estimate of code predictive uncertainties will be made based on comparisons to the benchmark and independent data bases.« less

Chesapeake Inundation Prediction System (CIPS): A regional prototype for a national problem

USGS Publications Warehouse

Stamey, B.; Smith, W.; Carey, K.; Garbin, D.; Klein, F.; Wang, Hongfang; Shen, J.; Gong, W.; Cho, J.; Forrest, D.; Friedrichs, C.; Boicourt, W.; Li, M.; Koterba, M.; King, D.; Titlow, J.; Smith, E.; Siebers, A.; Billet, J.; Lee, J.; Manning, Douglas R.; Szatkowski, G.; Wilson, D.; Ahnert, P.; Ostrowski, J.

2007-01-01

Recent Hurricanes Katrina and Isabel, among others, not only demonstrated their immense destructive power, but also revealed the obvious, crucial need for improved storm surge forecasting and information delivery to save lives and property in future storms. Current operational methods and the storm surge and inundation products do not adequately meet requirements needed by Emergency Managers (EMs) at local, state, and federal levels to protect and inform our citizens. The Chesapeake Bay Inundation Prediction System (CIPS) is being developed to improve the accuracy, reliability, and capability of flooding forecasts for tropical cyclones and non-tropical wind systems such as nor'easters by modeling and visualizing expected on-land storm-surge inundation along the Chesapeake Bay and its tributaries. An initial prototype has been developed by a team of government, academic and industry partners through the Chesapeake Bay Observing System (CBOS) of the Mid-Atlantic Coastal Ocean Observing Regional Association (MACOORA) within the Integrated Ocean Observing System (IOOS). For demonstration purposes, this initial prototype was developed for the tidal Potomac River in the Washington, DC metropolitan area. The preliminary information from this prototype shows great potential as a mechanism by which NOAA National Weather Service (NWS) Forecast Offices (WFOs) can provide more specific and timely forecasts of likely inundation in individual localities from significant storm surge events. This prototype system has shown the potential to indicate flooding at the street level, at time intervals of an hour or less, and with vertical resolution of one foot or less. This information will significantly improve the ability of EMs and first responders to mitigate life and property loss and improve evacuation capabilities in individual communities. This paper provides an update and expansion of the initial prototype that was presented at the Oceans 2006 MTS/IEEE Conference in Boston, MA. ??2007 MTS.

Benchmarking of neutron production of heavy-ion transport codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Remec, I.; Ronningen, R. M.; Heilbronn, L.

Document available in abstract form only, full text of document follows: Accurate prediction of radiation fields generated by heavy ion interactions is important in medical applications, space missions, and in design and operation of rare isotope research facilities. In recent years, several well-established computer codes in widespread use for particle and radiation transport calculations have been equipped with the capability to simulate heavy ion transport and interactions. To assess and validate these capabilities, we performed simulations of a series of benchmark-quality heavy ion experiments with the computer codes FLUKA, MARS15, MCNPX, and PHITS. We focus on the comparisons of secondarymore » neutron production. Results are encouraging; however, further improvements in models and codes and additional benchmarking are required. (authors)« less

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining

PubMed Central

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-01-01

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing. PMID:27854322

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining.

PubMed

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-11-16

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

Meteor Shower Forecast Improvements from a Survey of All-Sky Network Observations

NASA Technical Reports Server (NTRS)

Moorhead, Althea V.; Sugar, Glenn; Brown, Peter G.; Cooke, William J.

2015-01-01

Meteoroid impacts are capable of damaging spacecraft and potentially ending missions. In order to help spacecraft programs mitigate these risks, NASA's Meteoroid Environment Office (MEO) monitors and predicts meteoroid activity. Temporal variations in near-Earth space are described by the MEO's annual meteor shower forecast, which is based on both past shower activity and model predictions. The MEO and the University of Western Ontario operate sister networks of all-sky meteor cameras. These networks have been in operation for more than 7 years and have computed more than 20,000 meteor orbits. Using these data, we conduct a survey of meteor shower activity in the "fireball" size regime using DBSCAN. For each shower detected in our survey, we compute the date of peak activity and characterize the growth and decay of the shower's activity before and after the peak. These parameters are then incorporated into the annual forecast for an improved treatment of annual activity.

Trajectory-Based Takeoff Time Predictions Applied to Tactical Departure Scheduling: Concept Description, System Design, and Initial Observations

NASA Technical Reports Server (NTRS)

Engelland, Shawn A.; Capps, Alan

2011-01-01

Current aircraft departure release times are based on manual estimates of aircraft takeoff times. Uncertainty in takeoff time estimates may result in missed opportunities to merge into constrained en route streams and lead to lost throughput. However, technology exists to improve takeoff time estimates by using the aircraft surface trajectory predictions that enable air traffic control tower (ATCT) decision support tools. NASA s Precision Departure Release Capability (PDRC) is designed to use automated surface trajectory-based takeoff time estimates to improve en route tactical departure scheduling. This is accomplished by integrating an ATCT decision support tool with an en route tactical departure scheduling decision support tool. The PDRC concept and prototype software have been developed, and an initial test was completed at air traffic control facilities in Dallas/Fort Worth. This paper describes the PDRC operational concept, system design, and initial observations.

A candidate concept for display of forward-looking wind shear information

NASA Technical Reports Server (NTRS)

Hinton, David A.

1989-01-01

A concept is proposed which integrates forward-look wind shear information with airplane performance capabilities to predict future airplane energy state as a function of range. The information could be displayed to a crew either in terms of energy height or airspeed deviations. The anticipated benefits of the proposed display information concept are: (1) a wind shear hazard product that scales directly to the performance impact on the airplane and that has intuitive meaning to flight crews; (2) a reduction in flight crew workload by automatic processing of relevant hazard parameters; and (3) a continuous display of predicted airplane energy state if the approach is continued. Such a display may be used to improve pilot situational awareness or improve pilot confidence in wind shear alerts generated by other systems. The display is described and the algorithms necessary for implementation in a simulation system are provided.

Using Improved Equation of State to Model Simultaneous Nucleation and Bubble Growth in Thermoplastic Foams

NASA Astrophysics Data System (ADS)

Khan, Irfan; Costeux, Stephane; Adrian, David; Cristancho, Diego

2013-11-01

Due to environmental regulations carbon-dioxide (CO2) is increasingly being used to replace traditional blowing agents in thermoplastic foams. CO2 is dissolved in the polymer matrix under supercritical conditions. In order to predict the effect of process parameters on foam properties using numerical modeling, the P-V-T relationship of the blowing agents should accurately be represented at the supercritical state. Previous studies in the area of foam modeling have all used ideal gas equation of state to predict the behavior of the blowing agent. In this work the Peng-Robinson equation of state is being used to model the blowing agent during its diffusion into the growing bubble. The model is based on the popular ``Influence Volume Approach,'' which assumes a growing boundary layer with depleted blowing agent surrounds each bubble. Classical nucleation theory is used to predict the rate of nucleation of bubbles. By solving the mass balance, momentum balance and species conservation equations for each bubble, the model is capable of predicting average bubble size, bubble size distribution and bulk porosity. The effect of the improved model on the bubble growth and foam properties are discussed.

Intermolecular shielding contributions studied by modeling the 13C chemical-shift tensors of organic single crystals with plane waves

PubMed Central

Johnston, Jessica C.; Iuliucci, Robbie J.; Facelli, Julio C.; Fitzgerald, George; Mueller, Karl T.

2009-01-01

In order to predict accurately the chemical shift of NMR-active nuclei in solid phase systems, magnetic shielding calculations must be capable of considering the complete lattice structure. Here we assess the accuracy of the density functional theory gauge-including projector augmented wave method, which uses pseudopotentials to approximate the nodal structure of the core electrons, to determine the magnetic properties of crystals by predicting the full chemical-shift tensors of all 13C nuclides in 14 organic single crystals from which experimental tensors have previously been reported. Plane-wave methods use periodic boundary conditions to incorporate the lattice structure, providing a substantial improvement for modeling the chemical shifts in hydrogen-bonded systems. Principal tensor components can now be predicted to an accuracy that approaches the typical experimental uncertainty. Moreover, methods that include the full solid-phase structure enable geometry optimizations to be performed on the input structures prior to calculation of the shielding. Improvement after optimization is noted here even when neutron diffraction data are used for determining the initial structures. After geometry optimization, the isotropic shift can be predicted to within 1 ppm. PMID:19831448

The combination of circle topology and leaky integrator neurons remarkably improves the performance of echo state network on time series prediction.

PubMed

Xue, Fangzheng; Li, Qian; Li, Xiumin

2017-01-01

Recently, echo state network (ESN) has attracted a great deal of attention due to its high accuracy and efficient learning performance. Compared with the traditional random structure and classical sigmoid units, simple circle topology and leaky integrator neurons have more advantages on reservoir computing of ESN. In this paper, we propose a new model of ESN with both circle reservoir structure and leaky integrator units. By comparing the prediction capability on Mackey-Glass chaotic time series of four ESN models: classical ESN, circle ESN, traditional leaky integrator ESN, circle leaky integrator ESN, we find that our circle leaky integrator ESN shows significantly better performance than other ESNs with roughly 2 orders of magnitude reduction of the predictive error. Moreover, this model has stronger ability to approximate nonlinear dynamics and resist noise than conventional ESN and ESN with only simple circle structure or leaky integrator neurons. Our results show that the combination of circle topology and leaky integrator neurons can remarkably increase dynamical diversity and meanwhile decrease the correlation of reservoir states, which contribute to the significant improvement of computational performance of Echo state network on time series prediction.

A hierarchical spatial model for well yield in complex aquifers

NASA Astrophysics Data System (ADS)

Montgomery, J.; O'sullivan, F.

2017-12-01

Efficiently siting and managing groundwater wells requires reliable estimates of the amount of water that can be produced, or the well yield. This can be challenging to predict in highly complex, heterogeneous fractured aquifers due to the uncertainty around local hydraulic properties. Promising statistical approaches have been advanced in recent years. For instance, kriging and multivariate regression analysis have been applied to well test data with limited but encouraging levels of prediction accuracy. Additionally, some analytical solutions to diffusion in homogeneous porous media have been used to infer "effective" properties consistent with observed flow rates or drawdown. However, this is an under-specified inverse problem with substantial and irreducible uncertainty. We describe a flexible machine learning approach capable of combining diverse datasets with constraining physical and geostatistical models for improved well yield prediction accuracy and uncertainty quantification. Our approach can be implemented within a hierarchical Bayesian framework using Markov Chain Monte Carlo, which allows for additional sources of information to be incorporated in priors to further constrain and improve predictions and reduce the model order. We demonstrate the usefulness of this approach using data from over 7,000 wells in a fractured bedrock aquifer.

Advanced Simulation and Computing Fiscal Year 14 Implementation Plan, Rev. 0.5

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meisner, Robert; McCoy, Michel; Archer, Bill

2013-09-11

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities andmore » computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is now focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Moreover, ASC’s business model is integrated and focused on requirements-driven products that address long-standing technical questions related to enhanced predictive capability in the simulation tools.« less

A two-stage predictive model to simultaneous control of trihalomethanes in water treatment plants and distribution systems: adaptability to treatment processes.

PubMed

Domínguez-Tello, Antonio; Arias-Borrego, Ana; García-Barrera, Tamara; Gómez-Ariza, José Luis

2017-10-01

The trihalomethanes (TTHMs) and others disinfection by-products (DBPs) are formed in drinking water by the reaction of chlorine with organic precursors contained in the source water, in two consecutive and linked stages, that starts at the treatment plant and continues in second stage along the distribution system (DS) by reaction of residual chlorine with organic precursors not removed. Following this approach, this study aimed at developing a two-stage empirical model for predicting the formation of TTHMs in the water treatment plant and subsequently their evolution along the water distribution system (WDS). The aim of the two-stage model was to improve the predictive capability for a wide range of scenarios of water treatments and distribution systems. The two-stage model was developed using multiple regression analysis from a database (January 2007 to July 2012) using three different treatment processes (conventional and advanced) in the water supply system of Aljaraque area (southwest of Spain). Then, the new model was validated using a recent database from the same water supply system (January 2011 to May 2015). The validation results indicated no significant difference in the predictive and observed values of TTHM (R 2 0.874, analytical variance <17%). The new model was applied to three different supply systems with different treatment processes and different characteristics. Acceptable predictions were obtained in the three distribution systems studied, proving the adaptability of the new model to the boundary conditions. Finally the predictive capability of the new model was compared with 17 other models selected from the literature, showing satisfactory results prediction and excellent adaptability to treatment processes.

Advancing Environmental Prediction Capabilities for the Polar Regions and Beyond during The Year of Polar Prediction

NASA Astrophysics Data System (ADS)

Werner, Kirstin; Goessling, Helge; Hoke, Winfried; Kirchhoff, Katharina; Jung, Thomas

2017-04-01

Environmental changes in polar regions open up new opportunities for economic and societal operations such as vessel traffic related to scientific, fishery and tourism activities, and in the case of the Arctic also enhanced resource development. The availability of current and accurate weather and environmental information and forecasts will therefore play an increasingly important role in aiding risk reduction and safety management around the poles. The Year of Polar Prediction (YOPP) has been established by the World Meteorological Organization's World Weather Research Programme as the key activity of the ten-year Polar Prediction Project (PPP; see more on www.polarprediction.net). YOPP is an internationally coordinated initiative to significantly advance our environmental prediction capabilities for the polar regions and beyond, supporting improved weather and climate services. Scheduled to take place from mid-2017 to mid-2019, the YOPP core phase covers an extended period of intensive observing, modelling, prediction, verification, user-engagement and education activities in the Arctic and Antarctic, on a wide range of time scales from hours to seasons. The Year of Polar Prediction will entail periods of enhanced observational and modelling campaigns in both polar regions. With the purpose to close the gaps in the conventional polar observing systems in regions where the observation network is sparse, routine observations will be enhanced during Special Observing Periods for an extended period of time (several weeks) during YOPP. This will allow carrying out subsequent forecasting system experiments aimed at optimizing observing systems in the polar regions and providing insight into the impact of better polar observations on forecast skills in lower latitudes. With various activities and the involvement of a wide range of stakeholders, YOPP will contribute to the knowledge base needed to managing the opportunities and risks that come with polar climate change.

NEW IMPROVEMENTS TO MFIRE TO ENHANCE FIRE MODELING CAPABILITIES.

PubMed

Zhou, L; Smith, A C; Yuan, L

2016-06-01

NIOSH's mine fire simulation program, MFIRE, is widely accepted as a standard for assessing and predicting the impact of a fire on the mine ventilation system and the spread of fire contaminants in coal and metal/nonmetal mines, which has been used by U.S. and international companies to simulate fires for planning and response purposes. MFIRE is a dynamic, transient-state, mine ventilation network simulation program that performs normal planning calculations. It can also be used to analyze ventilation networks under thermal and mechanical influence such as changes in ventilation parameters, external influences such as changes in temperature, and internal influences such as a fire. The program output can be used to analyze the effects of these influences on the ventilation system. Since its original development by Michigan Technological University for the Bureau of Mines in the 1970s, several updates have been released over the years. In 2012, NIOSH completed a major redesign and restructuring of the program with the release of MFIRE 3.0. MFIRE's outdated FORTRAN programming language was replaced with an object-oriented C++ language and packaged into a dynamic link library (DLL). However, the MFIRE 3.0 release made no attempt to change or improve the fire modeling algorithms inherited from its previous version, MFIRE 2.20. This paper reports on improvements that have been made to the fire modeling capabilities of MFIRE 3.0 since its release. These improvements include the addition of fire source models of the t-squared fire and heat release rate curve data file, the addition of a moving fire source for conveyor belt fire simulations, improvement of the fire location algorithm, and the identification and prediction of smoke rollback phenomena. All the improvements discussed in this paper will be termed as MFIRE 3.1 and released by NIOSH in the near future.

Web-based applications for building, managing and analysing kinetic models of biological systems.

PubMed

Lee, Dong-Yup; Saha, Rajib; Yusufi, Faraaz Noor Khan; Park, Wonjun; Karimi, Iftekhar A

2009-01-01

Mathematical modelling and computational analysis play an essential role in improving our capability to elucidate the functions and characteristics of complex biological systems such as metabolic, regulatory and cell signalling pathways. The modelling and concomitant simulation render it possible to predict the cellular behaviour of systems under various genetically and/or environmentally perturbed conditions. This motivates systems biologists/bioengineers/bioinformaticians to develop new tools and applications, allowing non-experts to easily conduct such modelling and analysis. However, among a multitude of systems biology tools developed to date, only a handful of projects have adopted a web-based approach to kinetic modelling. In this report, we evaluate the capabilities and characteristics of current web-based tools in systems biology and identify desirable features, limitations and bottlenecks for further improvements in terms of usability and functionality. A short discussion on software architecture issues involved in web-based applications and the approaches taken by existing tools is included for those interested in developing their own simulation applications.

xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heroux, Michael A.; Bartlett, Roscoe; Demeshko, Irina

Here, extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundationmore » for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.« less

Cooperative photometric redshift estimation

NASA Astrophysics Data System (ADS)

Cavuoti, S.; Tortora, C.; Brescia, M.; Longo, G.; Radovich, M.; Napolitano, N. R.; Amaro, V.; Vellucci, C.

2017-06-01

In the modern galaxy surveys photometric redshifts play a central role in a broad range of studies, from gravitational lensing and dark matter distribution to galaxy evolution. Using a dataset of ~ 25,000 galaxies from the second data release of the Kilo Degree Survey (KiDS) we obtain photometric redshifts with five different methods: (i) Random forest, (ii) Multi Layer Perceptron with Quasi Newton Algorithm, (iii) Multi Layer Perceptron with an optimization network based on the Levenberg-Marquardt learning rule, (iv) the Bayesian Photometric Redshift model (or BPZ) and (v) a classical SED template fitting procedure (Le Phare). We show how SED fitting techniques could provide useful information on the galaxy spectral type which can be used to improve the capability of machine learning methods constraining systematic errors and reduce the occurrence of catastrophic outliers. We use such classification to train specialized regression estimators, by demonstrating that such hybrid approach, involving SED fitting and machine learning in a single collaborative framework, is capable to improve the overall prediction accuracy of photometric redshifts.

xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit

DOE PAGES

Heroux, Michael A.; Bartlett, Roscoe; Demeshko, Irina; ...

2017-03-01

Here, extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundationmore » for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.« less

NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 736 kg of Propellant Throughput

NASA Technical Reports Server (NTRS)

Shastry, Rohit; Herman, Daniel A.; Soulas, George C.; Patterson, Michael J.

2012-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar-electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced mission capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to qualify the thruster propellant throughput capability. The thruster has set electric propulsion records for the longest operating duration, highest propellant throughput, and most total impulse demonstrated. At the time of this publication, the NEXT LDT has surpassed 42,100 h of operation, processed more than 736 kg of xenon propellant, and demonstrated greater than 28.1 MN s total impulse. Thruster performance has been steady with negligible degradation. The NEXT thruster design has mitigated several lifetime limiting mechanisms encountered in the NSTAR design, including the NSTAR first failure mode, thereby drastically improving thruster capabilities. Component erosion rates and the progression of the predicted life-limiting erosion mechanism for the thruster compare favorably to pretest predictions based upon semi-empirical ion thruster models used in the thruster service life assessment. Service life model validation has been accomplished by the NEXT LDT. Assuming full-power operation until test article failure, the models and extrapolated erosion data predict penetration of the accelerator grid grooves after more than 45,000 hours of operation while processing over 800 kg of xenon propellant. Thruster failure due to degradation of the accelerator grid structural integrity is expected after groove penetration.

NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 736 kg of Propellant Throughput

NASA Technical Reports Server (NTRS)

Shastry, Rohit; Herman, Daniel A.; Soulas, George C.; Patterson, Michael J.

2012-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar-electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced mission capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to qualify the thruster propellant throughput capability. The thruster has set electric propulsion records for the longest operating duration, highest propellant throughput, and most total impulse demonstrated. At the time of this publication, the NEXT LDT has surpassed 42,100 h of operation, processed more than 736 kg of xenon propellant, and demonstrated greater than 28.1 MN s total impulse. Thruster performance has been steady with negligible degradation. The NEXT thruster design has mitigated several lifetime limiting mechanisms encountered in the NSTAR design, including the NSTAR first failure mode, thereby drastically improving thruster capabilities. Component erosion rates and the progression of the predicted life-limiting erosion mechanism for the thruster compare favorably to pretest predictions based upon semi-empirical ion thruster models used in the thruster service life assessment. Service life model validation has been accomplished by the NEXT LDT. Assuming full-power operation until test article failure, the models and extrapolated erosion data predict penetration of the accelerator grid grooves after more than 45,000 hours of operation while processing over 800 kg of xenon propellant. Thruster failure due to degradation of the accelerator grid structural integrity is expected after

A method for testing whether model predictions fall within a prescribed factor of true values, with an application to pesticide leaching

USGS Publications Warehouse

Parrish, Rudolph S.; Smith, Charles N.

1990-01-01

A quantitative method is described for testing whether model predictions fall within a specified factor of true values. The technique is based on classical theory for confidence regions on unknown population parameters and can be related to hypothesis testing in both univariate and multivariate situations. A capability index is defined that can be used as a measure of predictive capability of a model, and its properties are discussed. The testing approach and the capability index should facilitate model validation efforts and permit comparisons among competing models. An example is given for a pesticide leaching model that predicts chemical concentrations in the soil profile.

Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 1 (JMA/MRI-CPS1) for operational seasonal forecasting

NASA Astrophysics Data System (ADS)

Takaya, Yuhei; Yasuda, Tamaki; Fujii, Yosuke; Matsumoto, Satoshi; Soga, Taizo; Mori, Hirotoshi; Hirai, Masayuki; Ishikawa, Ichiro; Sato, Hitoshi; Shimpo, Akihiko; Kamachi, Masafumi; Ose, Tomoaki

2017-01-01

This paper describes the operational seasonal prediction system of the Japan Meteorological Agency (JMA), the Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 1 (JMA/MRI-CPS1), which was in operation at JMA during the period between February 2010 and May 2015. The predictive skill of the system was assessed with a set of retrospective seasonal predictions (reforecasts) covering 30 years (1981-2010). JMA/MRI-CPS1 showed reasonable predictive skill for the El Niño-Southern Oscillation, comparable to the skills of other state-of-the-art systems. The one-tiered approach adopted in JMA/MRI-CPS1 improved its overall predictive skills for atmospheric predictions over those of the two-tiered approach of the previous uncoupled system. For 3-month predictions with a 1-month lead, JMA/MRI-CPS1 showed statistically significant skills in predicting 500-hPa geopotential height and 2-m temperature in East Asia in most seasons; thus, it is capable of providing skillful seasonal predictions for that region. Furthermore, JMA/MRI-CPS1 was superior overall to the previous system for atmospheric predictions with longer (4-month) lead times. In particular, JMA/MRI-CPS1 was much better able to predict the Asian Summer Monsoon than the previous two-tiered system. This enhanced performance was attributed to the system's ability to represent atmosphere-ocean coupled variability over the Indian Ocean and the western North Pacific from boreal winter to summer following winter El Niño events, which in turn influences the East Asian summer climate through the Pacific-Japan teleconnection pattern. These substantial improvements obtained by using an atmosphere-ocean coupled general circulation model underpin its success in providing more skillful seasonal forecasts on an operational basis.

Multiple Sensitivity Testing for Regional Air Quality Model in summer 2014

NASA Astrophysics Data System (ADS)

Tang, Y.; Lee, P.; Pan, L.; Tong, D.; Kim, H. C.; Huang, M.; Wang, J.; McQueen, J.; Lu, C. H.; Artz, R. S.

2015-12-01

The NOAA Air Resources laboratory leads to improve the performance of the U.S. Air Quality Forecasting Capability (NAQFC). It is operational in NOAA National Centers for Environmental Prediction (NCEP) which focuses on predicting surface ozone and PM2.5. In order to improve its performance, we tested several approaches, including NOAA Environmental Modeling System Global Aerosol Component (NGAC) simulation derived ozone and aerosol lateral boundary conditions (LBC), bi-direction NH3 emission and HMS(Hazard Mapping System)-BlueSky emission with the latest U.S. EPA Community Multi-scale Air Quality model (CMAQ) version and the U.S EPA National Emission Inventory (NEI)-2011 anthropogenic emissions. The operational NAQFC uses static profiles for its lateral boundary condition (LBC), which does not impose severe issue for near-surface air quality prediction. However, its degraded performance for the upper layer (e.g. above 3km) is evident when comparing with aircraft measured ozone. NCEP's Global Forecast System (GFS) has tracer O3 prediction treated as 3-D prognostic variable (Moorthi and Iredell, 1998) after being initialized with Solar Backscatter Ultra Violet-2 (SBUV-2) satellite data. We applied that ozone LBC to the CMAQ's upper layers and yield more reasonable O3 prediction than that with static LBC comparing with the aircraft data in Discover-AQ Colorado campaign. NGAC's aerosol LBC also improved the PM2.5 prediction with more realistic background aerosols. The bi-direction NH3 emission used in CMAQ also help reduce the NH3 and nitrate under-prediction issue. During summer 2014, strong wildfires occurred in northwestern USA, and we used the US Forest Service's BlueSky fire emission with HMS fire counts to drive CMAQ and tested the difference of day-1 and day-2 fire emission estimation. Other related issues were also discussed.

Incorporating metacognition into morbidity and mortality rounds: The next frontier in quality improvement.

PubMed

Katz, David; Detsky, Allan S

2016-02-01

This Perspective proposes the introduction of metacognition (thinking about thinking) into the existing format of hospital-based morbidity and mortality rounds. It is placed in the context of historical movements to advance quality improvement by expanding the spectrum of the causes of medical error from systems-based issues to flawed human decision-making capabilities. We suggest that the current approach that focuses on systems-based issues can be improved by exploiting the opportunities to educate physicians about predictable errors committed by reliance on cognitive heuristics. In addition, because the field of educating clinicians about cognitive heuristics has shown mixed results, this proposal represents fertile ground for further research. Educating clinicians about cognitive heuristics may improve metacognition and perhaps be the next frontier in quality improvement. © 2015 Society of Hospital Medicine.

Assessment of Predictive Capabilities of L1 Orbiters using Realtime Solar Wind Data

NASA Astrophysics Data System (ADS)

Holmes, J.; Kasper, J. C.; Welling, D. T.

2017-12-01

Realtime measurements of solar wind conditions at L1 point allow us to predict geomagnetic activity at Earth up to an hour in advance. These predictions are quantified in the form of geomagnetic indices such as Kp and Ap, allowing for a concise, standardized prediction and measurement system. For years, the Space Weather Prediction Center used ACE realtime solar wind data to develop its one and four-hour Kp forecasts, but has in the past year switched to using DSCOVR data as its source. In this study, the performance of both orbiters in predicting Kp over the course of one month was assessed in an attempt to determine whether or not switching to DSCOVR data has resulted in improved forecasts. The period of study was chosen to encompass a time when the satellites were close to each other, and when moderate to high activity was observed. Kp predictions were made using the Geospace Model, part of the Space Weather Modeling Framework, to simulate conditions based on observed solar wind parameters. The performance of each satellite was assessed by comparing the model output to observed data.

Acoustic Prediction Methodology and Test Validation for an Efficient Low-Noise Hybrid Wing Body Subsonic Transport

NASA Technical Reports Server (NTRS)

Kawai, Ronald T. (Compiler)

2011-01-01

This investigation was conducted to: (1) Develop a hybrid wing body subsonic transport configuration with noise prediction methods to meet the circa 2007 NASA Subsonic Fixed Wing (SFW) N+2 noise goal of -52 dB cum relative to FAR 36 Stage 3 (-42 dB cum re: Stage 4) while achieving a -25% fuel burned compared to current transports (re :B737/B767); (2) Develop improved noise prediction methods for ANOPP2 for use in predicting FAR 36 noise; (3) Design and fabricate a wind tunnel model for testing in the LaRC 14 x 22 ft low speed wind tunnel to validate noise predictions and determine low speed aero characteristics for an efficient low noise Hybrid Wing Body configuration. A medium wide body cargo freighter was selected to represent a logical need for an initial operational capability in the 2020 time frame. The Efficient Low Noise Hybrid Wing Body (ELNHWB) configuration N2A-EXTE was evolved meeting the circa 2007 NRA N+2 fuel burn and noise goals. The noise estimates were made using improvements in jet noise shielding and noise shielding prediction methods developed by UC Irvine and MIT. From this the Quiet Ultra Integrated Efficient Test Research Aircraft #1 (QUIET-R1) 5.8% wind tunnel model was designed and fabricated.

Building a Predictive Capability for Decision-Making that Supports MultiPEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carmichael, Joshua Daniel

Multi-phenomenological explosion monitoring (multiPEM) is a developing science that uses multiple geophysical signatures of explosions to better identify and characterize their sources. MultiPEM researchers seek to integrate explosion signatures together to provide stronger detection, parameter estimation, or screening capabilities between different sources or processes. This talk will address forming a predictive capability for screening waveform explosion signatures to support multiPEM.

Crack Growth Simulation and Residual Strength Prediction in Airplane Fuselages

NASA Technical Reports Server (NTRS)

Chen, Chuin-Shan; Wawrzynek, Paul A.; Ingraffea, Anthony R.

1999-01-01

This is the final report for the NASA funded project entitled "Crack Growth Prediction Methodology for Multi-Site Damage." The primary objective of the project was to create a capability to simulate curvilinear fatigue crack growth and ductile tearing in aircraft fuselages subjected to widespread fatigue damage. The second objective was to validate the capability by way of comparisons to experimental results. Both objectives have been achieved and the results are detailed herein. In the first part of the report, the crack tip opening angle (CTOA) fracture criterion, obtained and correlated from coupon tests to predict fracture behavior and residual strength of built-up aircraft fuselages, is discussed. Geometrically nonlinear, elastic-plastic, thin shell finite element analyses are used to simulate stable crack growth and to predict residual strength. Both measured and predicted results of laboratory flat panel tests and full-scale fuselage panel tests show substantial reduction of residual strength due to the occurrence of multi-site damage (MSD). Detailed comparisons of n stable crack growth history, and residual strength between the predicted and experimental results are used to assess the validity of the analysis methodology. In the second part of the report, issues related to crack trajectory prediction in thin shells; an evolving methodology uses the crack turning phenomenon to improve the structural integrity of aircraft structures are discussed, A directional criterion is developed based on the maximum tangential stress theory, but taking into account the effect of T-stress and fracture toughness orthotropy. Possible extensions of the current crack growth directional criterion to handle geometrically and materially nonlinear problems are discussed. The path independent contour integral method for T-stress evaluation is derived and its accuracy is assessed using a p- and hp-version adaptive finite element method. Curvilinear crack growth is simulated in coupon tests and in full-scale fuselage panel tests. Both T-stress and fracture toughness orthotropy are found to be essential to predict the observed crack paths. The analysis methodology and software program (FRANC3D/STAGS) developed herein allows engineers to maintain aging aircraft economically while insuring continuous airworthiness. Consequently, it will improve the technology to support the safe operation of the current aircraft fleet as well as the design of more damage-tolerant aircraft for the next generation fleet.

Voxel inversion of airborne electromagnetic data for improved groundwater model construction and prediction accuracy

NASA Astrophysics Data System (ADS)

Kruse Christensen, Nikolaj; Ferre, Ty Paul A.; Fiandaca, Gianluca; Christensen, Steen

2017-03-01

We present a workflow for efficient construction and calibration of large-scale groundwater models that includes the integration of airborne electromagnetic (AEM) data and hydrological data. In the first step, the AEM data are inverted to form a 3-D geophysical model. In the second step, the 3-D geophysical model is translated, using a spatially dependent petrophysical relationship, to form a 3-D hydraulic conductivity distribution. The geophysical models and the hydrological data are used to estimate spatially distributed petrophysical shape factors. The shape factors primarily work as translators between resistivity and hydraulic conductivity, but they can also compensate for structural defects in the geophysical model. The method is demonstrated for a synthetic case study with sharp transitions among various types of deposits. Besides demonstrating the methodology, we demonstrate the importance of using geophysical regularization constraints that conform well to the depositional environment. This is done by inverting the AEM data using either smoothness (smooth) constraints or minimum gradient support (sharp) constraints, where the use of sharp constraints conforms best to the environment. The dependency on AEM data quality is also tested by inverting the geophysical model using data corrupted with four different levels of background noise. Subsequently, the geophysical models are used to construct competing groundwater models for which the shape factors are calibrated. The performance of each groundwater model is tested with respect to four types of prediction that are beyond the calibration base: a pumping well's recharge area and groundwater age, respectively, are predicted by applying the same stress as for the hydrologic model calibration; and head and stream discharge are predicted for a different stress situation. As expected, in this case the predictive capability of a groundwater model is better when it is based on a sharp geophysical model instead of a smoothness constraint. This is true for predictions of recharge area, head change, and stream discharge, while we find no improvement for prediction of groundwater age. Furthermore, we show that the model prediction accuracy improves with AEM data quality for predictions of recharge area, head change, and stream discharge, while there appears to be no accuracy improvement for the prediction of groundwater age.

Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

PubMed

Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

2018-02-01

Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

Predictive modeling capabilities from incident powder and laser to mechanical properties for laser directed energy deposition

NASA Astrophysics Data System (ADS)

Shin, Yung C.; Bailey, Neil; Katinas, Christopher; Tan, Wenda

2018-05-01

This paper presents an overview of vertically integrated comprehensive predictive modeling capabilities for directed energy deposition processes, which have been developed at Purdue University. The overall predictive models consist of vertically integrated several modules, including powder flow model, molten pool model, microstructure prediction model and residual stress model, which can be used for predicting mechanical properties of additively manufactured parts by directed energy deposition processes with blown powder as well as other additive manufacturing processes. Critical governing equations of each model and how various modules are connected are illustrated. Various illustrative results along with corresponding experimental validation results are presented to illustrate the capabilities and fidelity of the models. The good correlations with experimental results prove the integrated models can be used to design the metal additive manufacturing processes and predict the resultant microstructure and mechanical properties.

Predictive modeling capabilities from incident powder and laser to mechanical properties for laser directed energy deposition

NASA Astrophysics Data System (ADS)

Shin, Yung C.; Bailey, Neil; Katinas, Christopher; Tan, Wenda

2018-01-01

This paper presents an overview of vertically integrated comprehensive predictive modeling capabilities for directed energy deposition processes, which have been developed at Purdue University. The overall predictive models consist of vertically integrated several modules, including powder flow model, molten pool model, microstructure prediction model and residual stress model, which can be used for predicting mechanical properties of additively manufactured parts by directed energy deposition processes with blown powder as well as other additive manufacturing processes. Critical governing equations of each model and how various modules are connected are illustrated. Various illustrative results along with corresponding experimental validation results are presented to illustrate the capabilities and fidelity of the models. The good correlations with experimental results prove the integrated models can be used to design the metal additive manufacturing processes and predict the resultant microstructure and mechanical properties.

Survey Of Wind Tunnels At Langley Research Center

NASA Technical Reports Server (NTRS)

Bower, Robert E.

1989-01-01

Report presented at AIAA 14th Aerodynamic Testing Conference on current capabilities and planned improvements at NASA Langley Research Center's major wind tunnels. Focuses on 14 major tunnels, 8 unique in world, 3 unique in country. Covers Langley Spin Tunnel. Includes new National Transonic Facility (NTF). Also surveys Langley Unitary Plan Wind Tunnel (UPWT). Addresses resurgence of inexpensive simple-to-operate research tunnels. Predicts no shortage of tools for aerospace researcher and engineer in next decade or two.

Rapid Prediction of Unsteady Three-Dimensional Viscous Flows in Turbopump Geometries

NASA Technical Reports Server (NTRS)

Dorney, Daniel J.

1998-01-01

A program is underway to improve the efficiency of a three-dimensional Navier-Stokes code and generalize it for nozzle and turbopump geometries. Code modifications will include the implementation of parallel processing software, incorporating new physical models and generalizing the multi-block capability to allow the simultaneous simulation of nozzle and turbopump configurations. The current report contains details of code modifications, numerical results of several flow simulations and the status of the parallelization effort.

Predicting Risk for Suicide: A Preliminary Examination of Non-Suicidal Self-Injury and the Acquired Capability Construct in a College Sample.

PubMed

Brackman, Emily H; Morris, Blair W; Andover, Margaret S

2016-01-01

The interpersonal psychological theory of suicide provides a useful framework for considering the relationship between non-suicidal self-injury and suicide. Researchers propose that NSSI increases acquired capability for suicide. We predicted that both NSSI frequency and the IPTS acquired capability construct (decreased fear of death and increased pain tolerance) would separately interact with suicidal ideation to predict suicide attempts. Undergraduate students (N = 113) completed self-report questionnaires, and a subsample (n = 66) also completed a pain sensitivity task. NSSI frequency significantly moderated the association between suicidal ideation and suicide attempts. However, in a separate model, acquired capability did not moderate this relationship. Our understanding of the relationship between suicidal ideation and suicidal behavior can be enhanced by factors associated with NSSI that are distinct from the acquired capability construct.

FireStem2D – A Two-Dimensional Heat Transfer Model for Simulating Tree Stem Injury in Fires

PubMed Central

Chatziefstratiou, Efthalia K.; Bohrer, Gil; Bova, Anthony S.; Subramanian, Ravishankar; Frasson, Renato P. M.; Scherzer, Amy; Butler, Bret W.; Dickinson, Matthew B.

2013-01-01

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by resolving stem moisture loss, temperatures through the stem, degree of bark charring, and necrotic depth around the stem. We present the results of numerical parameterization and model evaluation experiments for FireStem2D that simulate laboratory stem-heating experiments of 52 tree sections from 25 trees. We also conducted a set of virtual sensitivity analysis experiments to test the effects of unevenness of heating around the stem and with aboveground height using data from two studies: a low-intensity surface fire and a more intense crown fire. The model allows for improved understanding and prediction of the effects of wildland fire on injury and mortality of trees of different species and sizes. PMID:23894599

Forecast Verification: Identification of small changes in weather forecasting skill

NASA Astrophysics Data System (ADS)

Weatherhead, E. C.; Jensen, T. L.

2017-12-01

Global and regonal weather forecasts have improved over the past seven decades most often because of small, incrmental improvements. The identificaiton and verification of forecast improvement due to proposed small changes in forecasting can be expensive and, if not carried out efficiently, can slow progress in forecasting development. This presentation will look at the skill of commonly used verification techniques and show how the ability to detect improvements can depend on the magnitude of the improvement, the number of runs used to test the improvement, the location on the Earth and the statistical techniques used. For continuous variables, such as temperture, wind and humidity, the skill of a forecast can be directly compared using a pair-wise statistical test that accommodates the natural autocorrelation and magnitude of variability. For discrete variables, such as tornado outbreaks, or icing events, the challenges is to reduce the false alarm rate while improving the rate of correctly identifying th discrete event. For both continuus and discrete verification results, proper statistical approaches can reduce the number of runs needed to identify a small improvement in forecasting skill. Verification within the Next Generation Global Prediction System is an important component to the many small decisions needed to make stat-of-the-art improvements to weather forecasting capabilities. The comparison of multiple skill scores with often conflicting results requires not only appropriate testing, but also scientific judgment to assure that the choices are appropriate not only for improvements in today's forecasting capabilities, but allow improvements that will come in the future.

An improved advertising CTR prediction approach based on the fuzzy deep neural network

PubMed Central

Gao, Shu; Li, Mingjiang

2018-01-01

Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise. PMID:29727443

Elevated temperature biaxial fatigue

NASA Technical Reports Server (NTRS)

Jordan, E. H.

1984-01-01

A three year experimental program for studying elevated temperature biaxial fatigue of a nickel based alloy Hastelloy-X has been completed. A new high temperature fatigue test facility with unique capabilities has been developed. Effort was directed toward understanding multiaxial fatigue and correlating the experimental data to the existing theories of fatigue failure. The difficult task of predicting fatigue lives for non-proportional loading was used as an ultimate test for various life prediction methods being considered. The primary means of reaching improved undertanding were through several critical non-proportional loading experiments. It was discovered that the cracking mode switched from primarily cracking on the maximum shear planes at room temperature to cracking on the maximum normal strain planes at 649 C.

An improved advertising CTR prediction approach based on the fuzzy deep neural network.

PubMed

Jiang, Zilong; Gao, Shu; Li, Mingjiang

2018-01-01

Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise.

Activated carbon adsorption of quinolone antibiotics in water: Performance, mechanism, and modeling.

PubMed

Fu, Hao; Li, Xuebing; Wang, Jun; Lin, Pengfei; Chen, Chao; Zhang, Xiaojian; Suffet, I H Mel

2017-06-01

The extensive use of antibiotics has led to their presence in the aquatic environment, and introduces potential impacts on human and ecological health. The capability of powdered activated carbon (PAC) to remove six frequently used quinolone (QN) antibiotics during water treatment was evaluated to improve drinking water safety. The kinetics of QN adsorption by PAC was best described by a pseudo second-order equation, and the adsorption capacity was well described by the Freundlich isotherm equation. Isotherms measured at different pH showed that hydrophobic interaction, electrostatic interaction, and π-π dispersion force were the main mechanisms for adsorption of QNs by PAC. A pH-dependent isotherm model based on the Freundlich equation was developed to predict the adsorption capacity of QNs by PAC at different pH values. This model had excellent prediction capabilities under different laboratory scenarios. Small relative standard derivations (RSDs), i.e., 0.59%-0.92% for ciprofloxacin and 0.09%-3.89% for enrofloxacin, were observed for equilibrium concentrations above the 0.3mg/L level. The RSDs increased to 11.9% for ciprofloxacin and 32.1% for enrofloxacin at μg/L equilibrium levels, which is still acceptable. This model could be applied to predict the adsorption of other chemicals having different ionized forms. Copyright © 2016. Published by Elsevier B.V.

Fractional viscoelasticity of soft elastomers and auxetic foams

NASA Astrophysics Data System (ADS)

Solheim, Hannah; Stanisauskis, Eugenia; Miles, Paul; Oates, William

2018-03-01

Dielectric elastomers are commonly implemented in adaptive structures due to their unique capabilities for real time control of a structure's shape, stiffness, and damping. These active polymers are often used in applications where actuator control or dynamic tunability are important, making an accurate understanding of the viscoelastic behavior critical. This challenge is complicated as these elastomers often operate over a broad range of deformation rates. Whereas research has demonstrated success in applying a nonlinear viscoelastic constitutive model to characterize the behavior of Very High Bond (VHB) 4910, robust predictions of the viscoelastic response over the entire range of time scales is still a significant challenge. An alternative formulation for viscoelastic modeling using fractional order calculus has shown significant improvement in predictive capabilities. While fractional calculus has been explored theoretically in the field of linear viscoelasticity, limited experimental validation and statistical evaluation of the underlying phenomena have been considered. In the present study, predictions across several orders of magnitude in deformation rates are validated against data using a single set of model parameters. Moreover, we illustrate the fractional order is material dependent by running complementary experiments and parameter estimation on the elastomer VHB 4949 as well as an auxetic foam. All results are statistically validated using Bayesian uncertainty methods to obtain posterior densities for the fractional order as well as the hyperelastic parameters.

Organizational Leadership and Adaptive Reserve in Blood Pressure Control: The Heart Health NOW Study.

PubMed

Henderson, Kamal H; DeWalt, Darren A; Halladay, Jacquie; Weiner, Bryan J; Kim, Jung I; Fine, Jason; Cykert, Samuel

2018-04-01

Our purpose was to assess whether a practice's adaptive reserve and high leadership capability in quality improvement are associated with population blood pressure control. We divided practices into quartiles of blood pressure control performance and considered the top quartile as the benchmark for comparison. Using abstracted clinical data from electronic health records, we performed a cross-sectional study to assess the association of top quartile hypertension control and (1) the baseline practice adaptive reserve (PAR) scores and (2) baseline practice leadership scores, using modified Poisson regression models adjusting for practice-level characteristics. Among 181 practices, 46 were in the top quartile, which averaged 68% or better blood pressure control. Practices with higher PAR scores compared with lower PAR scores were not more likely to reside in the top quartile of performance (prevalence ratio [PR] = 1.92 for highest quartile; 95% CI, 0.9-4.1). Similarly, high quality improvement leadership capability compared with lower capability did not predict better blood pressure control performance (PR = 0.94; 95% CI, 0.57-1.56). Practices with higher proportions of commercially insured patients were more likely than practices with lower proportions of commercially insured patients to have top quartile performance (37% vs 26%, P =.002), whereas lower proportions of the uninsured (8% vs 14%, P =.055) were associated with better performance. Our findings show that adaptive reserve and leadership capability in quality improvement implementation are not statistically associated with achieving top quartile practice-level hypertension control at baseline in the Heart Health NOW project. Our findings, however, may be limited by a lack of patient-related factors and small sample size to preclude strong conclusions. © 2018 Annals of Family Medicine, Inc.

Revalidation of the Huygens Descent Control Sub-System

NASA Technical Reports Server (NTRS)

2005-01-01

The Huygens probe, part of the Cassini mission to Saturn, is designed to investigate the atmosphere of Titan, Saturn's largest moon. The passage of the probe through the atmosphere is controlled by the Descent Control Sub-System (DCSS), which consists of three parachutes and associated mechanisms. The Cassini / Huygens mission was launched in October 1997 and was designed during the early 1990's. During the time since the design and launch, analysis capabilities have improved significantly, knowledge of the Titan environment has improved and the baseline mission has been modified. Consequently, a study was performed to revalidate the DCSS design against the current predictions.

Spectral Resolution and Coverage Impact on Advanced Sounder Information Content

NASA Technical Reports Server (NTRS)

Larar, Allen M.; Liu, Xu; Zhou, Daniel K.; Smith, William L.

2010-01-01

Advanced satellite sensors are tasked with improving global measurements of the Earth s atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Achieving such measurement improvements requires instrument system advancements. This presentation focuses on the impact of spectral resolution and coverage changes on remote sensing system information content, with a specific emphasis on thermodynamic state and trace species variables obtainable from advanced atmospheric sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) systems on the MetOp and NPP/NPOESS series of satellites. Key words: remote sensing, advanced sounders, information content, IASI, CrIS

The Role of Interdisciplinary Earth Science in the Assessment of Regional Land Subsidence Hazards: Toward Sustainable Management of Global Land and Subsurface-Fluid Resources

NASA Astrophysics Data System (ADS)

Galloway, D. L.

2012-12-01

Land-level lowering or land subsidence is a consequence of many local- and regional-scale physical, chemical or biologic processes affecting soils and geologic materials. The principal processes can be natural or anthropogenic, and include consolidation or compaction, karst or pseudokarst, hydrocompaction of collapsible soils, mining, oxidation of organic soils, erosive piping, tectonism, and volcanism. In terms of affected area, there are two principal regional-scale anthropogenic processes—compaction of compressible subsurface materials owing to the extraction of subsurface fluids (principally groundwater, oil and gas) and oxidation and compaction accompanying drainage of organic soils—which cause significant hazards related to flooding and infrastructure damage that are amenable to resource management measures. The importance of even small magnitude (< 10 mm/yr) subsidence rates in coastal areas is amplified by its contribution to relative sea-level rise compared to estimated rates of rising eustatic sea levels (2-3 mm/yr) attributed to global climate change. Multi- or interdisciplinary [scientific] studies, including those focused on geodetic, geologic, geophysical, hydrologic, hydrogeologic, geomechanical, geochemical, and biologic factors, improve understanding of these subsidence processes. Examples include geodetic measurement and analysis techniques, such as Global Positioning System (GPS), Light Detection and Ranging (LiDAR) and Interferometric Synthetic Aperture Radar (InSAR), which have advanced our capabilities to detect, measure and monitor land-surface motion at multiple scales. Improved means for simulating aquifer-system and hydrocarbon-reservoir deformation, and the oxidation and compaction of organic soils are leading to refined predictive capabilities. The role of interdisciplinary earth science in improving the characterization of land subsidence attributed to subsurface fluid withdrawals and the oxidation and compaction of organic soils is examined. How these improved capabilities are translating into improved sustainable management of regional land and water resources in a few select areas worldwide are presented. The importance of incorporating these improved capabilities in coherent resource management strategies to control the depletion of resources and attendant hazards also are discussed.