Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

PubMed

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (p<0.005) and correlated with independently identified visual EEG patterns such as generalized periodic discharges (p<0.02). Receiver operating characteristic (ROC) analysis confirmed the predictive value of lower state space velocity for poor clinical outcome after cardiac arrest (AUC 80.8, 70% sensitivity, 15% false positive rate). Model-based quantitative EEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi input single output model predictive control of non-linear bio-polymerization process

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

Arumugasamy, Senthil Kumar; Ahmad, Z.

This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state spacemore » model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.« less

Stochastic simulation of predictive space–time scenarios of wind speed using observations and physical model outputs

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

Bessac, Julie; Constantinescu, Emil; Anitescu, Mihai

We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines multiple sources of past physical model outputs and measurements in order to produce a probabilistic wind speed forecast within the prediction window. We illustrate this strategy on wind speed forecasts during several months in 2012 for a region near the Great Lakes in the United States. The results show that the prediction is improved in the mean-squared sense relative to the numerical forecasts as well as in probabilistic scores. Moreover, themore » samples are shown to produce realistic wind scenarios based on sample spectra and space-time correlation structure.« less

Stochastic simulation of predictive space–time scenarios of wind speed using observations and physical model outputs

DOE PAGES

Bessac, Julie; Constantinescu, Emil; Anitescu, Mihai

2018-03-01

We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines multiple sources of past physical model outputs and measurements in order to produce a probabilistic wind speed forecast within the prediction window. We illustrate this strategy on wind speed forecasts during several months in 2012 for a region near the Great Lakes in the United States. The results show that the prediction is improved in the mean-squared sense relative to the numerical forecasts as well as in probabilistic scores. Moreover, themore » samples are shown to produce realistic wind scenarios based on sample spectra and space-time correlation structure.« less

Topology of Collisionless Relaxation

NASA Astrophysics Data System (ADS)

Pakter, Renato; Levin, Yan

2013-04-01

Using extensive molecular dynamics simulations we explore the fine-grained phase space structure of systems with long-range interactions. We find that if the initial phase space particle distribution has no holes, the final stationary distribution will also contain a compact simply connected region. The microscopic holes created by the filamentation of the initial distribution function are always restricted to the outer regions of the phase space. In general, for complex multilevel distributions it is very difficult to a priori predict the final stationary state without solving the full dynamical evolution. However, we show that, for multilevel initial distributions satisfying a generalized virial condition, it is possible to predict the particle distribution in the final stationary state using Casimir invariants of the Vlasov dynamics.

An Aircraft Vortex Spacing System (AVOSS) for Dynamical Wake Vortex Spacing Criteria

NASA Technical Reports Server (NTRS)

Hinton, D. A.

1996-01-01

A concept is presented for the development and implementation of a prototype Aircraft Vortex Spacing System (AVOSS). The purpose of the AVOSS is to use current and short-term predictions of the atmospheric state in approach and departure corridors to provide, to ATC facilities, dynamical weather dependent separation criteria with adequate stability and lead time for use in establishing arrival scheduling. The AVOSS will accomplish this task through a combination of wake vortex transport and decay predictions, weather state knowledge, defined aircraft operational procedures and corridors, and wake vortex safety sensors. Work is currently underway to address the critical disciplines and knowledge needs so as to implement and demonstrate a prototype AVOSS in the 1999/2000 time frame.

Geometric state space uncertainty as a new type of uncertainty addressing disparity in ';emergent properties' between real and modeled systems

NASA Astrophysics Data System (ADS)

Montero, J. T.; Lintz, H. E.; Sharp, D.

2013-12-01

Do emergent properties that result from models of complex systems match emergent properties from real systems? This question targets a type of uncertainty that we argue requires more attention in system modeling and validation efforts. We define an ';emergent property' to be an attribute or behavior of a modeled or real system that can be surprising or unpredictable and result from complex interactions among the components of a system. For example, thresholds are common across diverse systems and scales and can represent emergent system behavior that is difficult to predict. Thresholds or other types of emergent system behavior can be characterized by their geometry in state space (where state space is the space containing the set of all states of a dynamic system). One way to expedite our growing mechanistic understanding of how emergent properties emerge from complex systems is to compare the geometry of surfaces in state space between real and modeled systems. Here, we present an index (threshold strength) that can quantify a geometric attribute of a surface in state space. We operationally define threshold strength as how strongly a surface in state space resembles a step or an abrupt transition between two system states. First, we validated the index for application in greater than three dimensions of state space using simulated data. Then, we demonstrated application of the index in measuring geometric state space uncertainty between a real system and a deterministic, modeled system. In particular, we looked at geometric space uncertainty between climate behavior in 20th century and modeled climate behavior simulated by global climate models (GCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5). Surfaces from the climate models came from running the models over the same domain as the real data. We also created response surfaces from a real, climate data based on an empirical model that produces a geometric surface of predicted values in state space. We used a kernel regression method designed to capture the geometry of real data pattern without imposing shape assumptions a priori on the data; this kernel regression method is known as Non-parametric Multiplicative Regression (NPMR). We found that quantifying and comparing a geometric attribute in more than three dimensions of state space can discern whether the emergent nature of complex interactions in modeled systems matches that of real systems. Further, this method has potentially wider application in contexts where searching for abrupt change or ';action' in any hyperspace is desired.

Design of nonlinear PID controller and nonlinear model predictive controller for a continuous stirred tank reactor.

PubMed

Prakash, J; Srinivasan, K

2009-07-01

In this paper, the authors have represented the nonlinear system as a family of local linear state space models, local PID controllers have been designed on the basis of linear models, and the weighted sum of the output from the local PID controllers (Nonlinear PID controller) has been used to control the nonlinear process. Further, Nonlinear Model Predictive Controller using the family of local linear state space models (F-NMPC) has been developed. The effectiveness of the proposed control schemes has been demonstrated on a CSTR process, which exhibits dynamic nonlinearity.

HBC-Evo: predicting human breast cancer by exploiting amino acid sequence-based feature spaces and evolutionary ensemble system.

PubMed

Majid, Abdul; Ali, Safdar

2015-01-01

We developed genetic programming (GP)-based evolutionary ensemble system for the early diagnosis, prognosis and prediction of human breast cancer. This system has effectively exploited the diversity in feature and decision spaces. First, individual learners are trained in different feature spaces using physicochemical properties of protein amino acids. Their predictions are then stacked to develop the best solution during GP evolution process. Finally, results for HBC-Evo system are obtained with optimal threshold, which is computed using particle swarm optimization. Our novel approach has demonstrated promising results compared to state of the art approaches.

Space Weather Forecasting and Supporting Research in the USA

NASA Astrophysics Data System (ADS)

Pevtsov, A. A.

2017-12-01

In the United State, scientific research in space weather is funded by several Government Agencies including the National Science Foundation (NSF) and the National Aeronautics and Space Agency (NASA). For civilian and commercial purposes, space weather forecast is done by the Space Weather Prediction Center (SWPC) of the National Oceanic and Atmospheric Administration (NOAA). Observational data for modeling come from the network of groundbased observatories funded via various sources, as well as from the instruments on spacecraft. Numerical models used in forecast are developed in framework of individual research projects. The article provides a brief review of current state of space weather-related research and forecasting in the USA.

Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation.

PubMed

Ławryńczuk, Maciej

2017-03-01

This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearised on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimisation problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearisation gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimisation repeated at each sampling instant. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus

USGS Publications Warehouse

Beatty, William; Jay, Chadwick V.; Fischbach, Anthony S.

2016-01-01

State-space models offer researchers an objective approach to modeling complex animal location data sets, and state-space model behavior classifications are often assumed to have a link to animal behavior. In this study, we evaluated the behavioral classification accuracy of a Bayesian state-space model in Pacific walruses using Argos satellite tags with sensors to detect animal behavior in real time. We fit a two-state discrete-time continuous-space Bayesian state-space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state-space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled out) and evaluated classification accuracy with kappa statistics (κ) and root mean square error (RMSE). In addition, we compared biased random bridge utilization distributions generated with resident behavior locations to true foraging behavior locations to evaluate differences in space use patterns. Results indicated that the two-state model fairly classified true animal behavior (0.06 ≤ κ ≤ 0.26, 0.49 ≤ RMSE ≤ 0.59). Kernel overlap metrics indicated utilization distributions generated with resident behavior locations were generally smaller than utilization distributions generated with true foraging behavior locations. Consequently, we encourage researchers to carefully examine parameters and priors associated with behaviors in state-space models, and reconcile these parameters with the study species and its expected behaviors.

Controversial electronic structures and energies of Fe{sub 2}, Fe{sub 2}{sup +}, and Fe{sub 2}{sup −} resolved by RASPT2 calculations

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

Hoyer, Chad E.; Manni, Giovanni Li; Truhlar, Donald G., E-mail: truhlar@umn.edu, E-mail: gagliard@umn.edu

2014-11-28

The diatomic molecule Fe{sub 2} was investigated using restricted active space second-order perturbation theory (RASPT2). This molecule is very challenging to study computationally because predictions about the ground state and excited states depend sensitively on the choice of the quantum chemical method. For Fe{sub 2} we show that one needs to go beyond a full-valence active space in order to achieve even qualitative agreement with experiment for the dissociation energy, and we also obtain a smooth ground-state potential curve. In addition we report the first multireference study of Fe{sub 2}{sup +}, for which we predict an {sup 8}Σ{sub u}{sup −}more » ground state, which was not predicted by previous computational studies. By using an active space large enough to remove the most serious deficiencies of previous theoretical work and by explicitly investigating the interpretations of previous experimental results, this study elucidates previous difficulties and provides – for the first time – a qualitatively correct treatment of Fe{sub 2}, Fe{sub 2}{sup +}, and Fe{sub 2}{sup −}. Moreover, this study represents a record in terms of the number or active electrons and active orbitals in the active space, namely 16 electrons in 28 orbitals. Conventional CASPT2 calculations can be performed with at most 16 electrons in 16 orbitals. We were able to overcome this limit by using the RASPT2 formalism.« less

Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

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

Melin, Alexander M.; Olama, Mohammed M.; Dong, Jin

The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed tomore » estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.« less

Validation of International Space Station Electrical Performance Model via On-orbit Telemetry

NASA Technical Reports Server (NTRS)

Jannette, Anthony G.; Hojnicki, Jeffrey S.; McKissock, David B.; Fincannon, James; Kerslake, Thomas W.; Rodriguez, Carlos D.

2002-01-01

The first U.S. power module on International Space Station (ISS) was activated in December 2000. Comprised of solar arrays, nickel-hydrogen (NiH2) batteries, and a direct current power management and distribution (PMAD) system, the electric power system (EPS) supplies power to housekeeping and user electrical loads. Modeling EPS performance is needed for several reasons, but primarily to assess near-term planned and off-nominal operations and because the EPS configuration changes over the life of the ISS. The System Power Analysis for Capability Evaluation (SPACE) computer code is used to assess the ISS EPS performance. This paper describes the process of validating the SPACE EPS model via ISS on-orbit telemetry. To accomplish this goal, telemetry was first used to correct assumptions and component models in SPACE. Then on-orbit data was directly input to SPACE to facilitate comparing model predictions to telemetry. It will be shown that SPACE accurately predicts on-orbit component and system performance. For example, battery state-of-charge was predicted to within 0.6 percentage points over a 0 to 100 percent scale and solar array current was predicted to within a root mean square (RMS) error of 5.1 Amps out of a typical maximum of 220 Amps. First, SPACE model predictions are compared to telemetry for the ISS EPS components: solar arrays, NiH2 batteries, and the PMAD system. Second, SPACE predictions for the overall performance of the ISS EPS are compared to telemetry and again demonstrate model accuracy.

New Space Weather Systems Under Development and Their Contribution to Space Weather Management

NASA Astrophysics Data System (ADS)

Tobiska, W.; Bouwer, D.; Schunk, R.; Garrett, H.; Mertens, C.; Bowman, B.

2008-12-01

There have been notable successes during the past decade in the development of operational space environment systems. Examples include the Magnetospheric Specification Model (MSM) of the Earth's magnetosphere, 2000; SOLAR2000 (S2K) solar spectral irradiances, 2001; High Accuracy Satellite Drag Model (HASDM) neutral atmosphere densities, 2004; Global Assimilation of Ionospheric Measurements (GAIM) ionosphere specification, 2006; Hakamada-Akasofu-Fry (HAF) solar wind parameters, 2007; Communication Alert and Prediction System (CAPS) ionosphere, high frequency radio, and scintillation S4 index prediction, 2008; and GEO Alert and Prediction System (GAPS) geosynchronous environment satellite charging specification and forecast, 2008. Operational systems that are in active operational implementation include the Jacchia-Bowman 2006/2008 (JB2006/2008) neutral atmosphere, 2009, and the Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) aviation radiation model using the Radiation Alert and Prediction System (RAPS), 2010. U.S. national agency and commercial assets will soon reach a state where specification and prediction will become ubiquitous and where coordinated management of the space environment and space weather will become a necessity. We describe the status of the CAPS, GAPS, RAPS, and JB2008 operational development. We additionally discuss the conditions that are laying the groundwork for space weather management and estimate the unfilled needs as we move beyond specification and prediction efforts.

A dual use case study of space technologies for terrestrial medical applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cozmuta, Ioana

2017-05-01

Many challenges exist in understanding the human body as a whole, its adaptability, its resilience, its immunological response, its healing and regeneration power. New knowledge is usually obtained by exploring unique conditions and environments and space is one such variable. Primarily, these attributes have been studied in space for the purpose of understanding the effect of the space environment on long duration space travel. However a myriad of lessons learned have emerged that are important for terrestrial medicine problems such as cardiovascular changes, intracranial pressure changes, vision changes, reduced immunity, etc. For medical study purposes, the changes induced by the space environment on the human body are in general fast and predictable; they persist while in the space environment but also revert to the initial pre-flight healthy state upon return to Earth. This provides a unique cycle to study wellness and disease prediction as well as to develop more effective countermeasures for the benefit of people on earth. At a scientific level, the environment of space can be used to develop new lines of investigations and new knowledge to push the terrestrial state of the art (i.e. study of phase diagrams, identification of new system's states, etc). Moreover, the specialized requirements for space medicine have driven advances in terrestrial medical technologies in areas such as monitoring, diagnostic, prevention and treatment. This talk will provide an overview of compelling examples in key areas of interest for terrestrial medical applications.

Fracture control methods for space vehicles. Volume 2: Assessment of fracture mechanics technology for space shuttle applications

NASA Technical Reports Server (NTRS)

Ehret, R. M.

1974-01-01

The concepts explored in a state of the art review of those engineering fracture mechanics considered most applicable to the space shuttle vehicle include fracture toughness, precritical flaw growth, failure mechanisms, inspection methods (including proof test logic), and crack growth predictive analysis techniques.

Stochastic state-space temperature regulation of biochar production. Part I: Theoretical development.

PubMed

Cantrell, Keri B; Martin, Jerry H

2012-02-01

The concept of a designer biochar that targets the improvement of a specific soil property imposes the need for production processes to generate biochars with both high consistency and quality. These important production parameters can be affected by variations in process temperature that must be taken into account when controlling the pyrolysis of agricultural residues such as manures and other feedstocks. A novel stochastic state-space temperature regulator was developed to accurately match biochar batch production to a defined temperature input schedule. This was accomplished by describing the system's state-space with five temperature variables--four directly measured and one change in temperature. Relationships were derived between the observed state and the desired, controlled state. When testing the unit at two different temperatures, the actual pyrolytic temperature was within 3 °C of the control with no overshoot. This state-space regulator simultaneously controlled the indirect heat source and sample temperature by employing difficult-to-measure variables such as temperature stability in the description of the pyrolysis system's state-space. These attributes make a state-space controller an optimum control scheme for the production of a predictable, repeatable designer biochar. Published 2011 by John Wiley & Sons, Ltd.

The use of the principle of superposition in measuring and predicting the thermal characteristics of an electronic equipment operated in a space environment

NASA Technical Reports Server (NTRS)

Gale, E. H.

1980-01-01

The advantages and possible pitfalls of using a generalized method of measuring and, based on these measurements, predicting the transient or steady-state thermal response characteristics of an electronic equipment designed to operate in a space environment are reviewed. The method requires generation of a set of thermal influence coefficients by test measurement in vacuo. A implified thermal mockup isused in this test. Once this data set is measured, temperatures resulting from arbitrary steady-state or time varying power profiles can be economically calculated with the aid of a digital computer.

State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics

PubMed Central

Tse, Peter W.; Wang, Dong

2017-01-01

Bearings are widely used in various industries to support rotating shafts. Their failures accelerate failures of other adjacent components and may cause unexpected machine breakdowns. In recent years, nonlinear vibration responses collected from a dynamic rotor-bearing system have been widely analyzed for bearing diagnostics. Numerous methods have been proposed to identify different bearing faults. However, these methods are unable to predict the future health conditions of bearings. To extend bearing diagnostics to bearing prognostics, this paper reports the design of a state space formulation of nonlinear vibration responses collected from a dynamic rotor-bearing system in order to intelligently predict bearing remaining useful life (RUL). Firstly, analyses of nonlinear vibration responses were conducted to construct a bearing health indicator (BHI) so as to assess the current bearing health condition. Secondly, a state space model of the BHI was developed to mathematically track the health evolution of the BHI. Thirdly, unscented particle filtering was used to predict bearing RUL. Lastly, a new bearing acceleration life testing setup was designed to collect natural bearing degradation data, which were used to validate the effectiveness of the proposed bearing prognostic method. Results show that the prediction accuracy of the proposed bearing prognostic method is promising and the proposed bearing prognostic method is able to reflect future bearing health conditions. PMID:28216586

State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics.

PubMed

Tse, Peter W; Wang, Dong

2017-02-14

Bearings are widely used in various industries to support rotating shafts. Their failures accelerate failures of other adjacent components and may cause unexpected machine breakdowns. In recent years, nonlinear vibration responses collected from a dynamic rotor-bearing system have been widely analyzed for bearing diagnostics. Numerous methods have been proposed to identify different bearing faults. However, these methods are unable to predict the future health conditions of bearings. To extend bearing diagnostics to bearing prognostics, this paper reports the design of a state space formulation of nonlinear vibration responses collected from a dynamic rotor-bearing system in order to intelligently predict bearing remaining useful life (RUL). Firstly, analyses of nonlinear vibration responses were conducted to construct a bearing health indicator (BHI) so as to assess the current bearing health condition. Secondly, a state space model of the BHI was developed to mathematically track the health evolution of the BHI. Thirdly, unscented particle filtering was used to predict bearing RUL. Lastly, a new bearing acceleration life testing setup was designed to collect natural bearing degradation data, which were used to validate the effectiveness of the proposed bearing prognostic method. Results show that the prediction accuracy of the proposed bearing prognostic method is promising and the proposed bearing prognostic method is able to reflect future bearing health conditions.

Numerical Models for Sound Propagation in Long Spaces

NASA Astrophysics Data System (ADS)

Lai, Chenly Yuen Cheung

Both reverberation time and steady-state sound field are the key elements for assessing the acoustic condition in an enclosed space. They affect the noise propagation, speech intelligibility, clarity index, and definition. Since the sound field in a long space is non diffuse, classical room acoustics theory does not apply in this situation. The ray tracing technique and the image source methods are two common models to fathom both reverberation time and steady-state sound field in long enclosures nowadays. Although both models can give an accurate estimate of reverberation times and steady-state sound field directly or indirectly, they often involve time-consuming calculations. In order to simplify the acoustic consideration, a theoretical formulation has been developed for predicting both steady-state sound fields and reverberation times in street canyons. The prediction model is further developed to predict the steady-state sound field in a long enclosure. Apart from the straight long enclosure, there are other variations such as a cross junction, a long enclosure with a T-intersection, an U-turn long enclosure. In the present study, an theoretical and experimental investigations were conducted to develop formulae for predicting reverberation times and steady-state sound fields in a junction of a street canyon and in a long enclosure with T-intersection. The theoretical models are validated by comparing the numerical predictions with published experimental results. The theoretical results are also compared with precise indoor measurements and large-scale outdoor experimental results. In all of previous acoustical studies related to long enclosure, most of the studies are focused on the monopole sound source. Besides non-directional noise source, many noise sources in long enclosure are dipole like, such as train noise and fan noise. In order to study the characteristics of directional noise sources, a review of available dipole source was conducted. A dipole was constructed which was subsequent used for experimental studies. In additional, a theoretical model was developed for predicting dipole sound fields. The theoretical model can be used to study the effect of a dipole source on the speech intelligibility in long enclosures.

US EPA 2012 Air Quality Fused Surface for the Conterminous U.S. Map Service

EPA Pesticide Factsheets

This web service contains a polygon layer that depicts fused air quality predictions for 2012 for census tracts in the conterminous United States. Fused air quality predictions (for ozone and PM2.5) are modeled using a Bayesian space-time downscaling fusion model approach described in a series of three published journal papers: 1) (Berrocal, V., Gelfand, A. E. and Holland, D. M. (2012). Space-time fusion under error in computer model output: an application to modeling air quality. Biometrics 68, 837-848; 2) Berrocal, V., Gelfand, A. E. and Holland, D. M. (2010). A bivariate space-time downscaler under space and time misalignment. The Annals of Applied Statistics 4, 1942-1975; and 3) Berrocal, V., Gelfand, A. E., and Holland, D. M. (2010). A spatio-temporal downscaler for output from numerical models. J. of Agricultural, Biological,and Environmental Statistics 15, 176-197) is used to provide daily, predictive PM2.5 (daily average) and O3 (daily 8-hr maximum) surfaces for 2012. Summer (O3) and annual (PM2.5) means calculated and published. The downscaling fusion model uses both air quality monitoring data from the National Air Monitoring Stations/State and Local Air Monitoring Stations (NAMS/SLAMS) and numerical output from the Models-3/Community Multiscale Air Quality (CMAQ). Currently, predictions at the US census tract centroid locations within the 12 km CMAQ domain are archived. Predictions at the CMAQ grid cell centroids, or any desired set of locations co

The forecasting of menstruation based on a state-space modeling of basal body temperature time series.

PubMed

Fukaya, Keiichi; Kawamori, Ai; Osada, Yutaka; Kitazawa, Masumi; Ishiguro, Makio

2017-09-20

Women's basal body temperature (BBT) shows a periodic pattern that associates with menstrual cycle. Although this fact suggests a possibility that daily BBT time series can be useful for estimating the underlying phase state as well as for predicting the length of current menstrual cycle, little attention has been paid to model BBT time series. In this study, we propose a state-space model that involves the menstrual phase as a latent state variable to explain the daily fluctuation of BBT and the menstruation cycle length. Conditional distributions of the phase are obtained by using sequential Bayesian filtering techniques. A predictive distribution of the next menstruation day can be derived based on this conditional distribution and the model, leading to a novel statistical framework that provides a sequentially updated prediction for upcoming menstruation day. We applied this framework to a real data set of women's BBT and menstruation days and compared prediction accuracy of the proposed method with that of previous methods, showing that the proposed method generally provides a better prediction. Because BBT can be obtained with relatively small cost and effort, the proposed method can be useful for women's health management. Potential extensions of this framework as the basis of modeling and predicting events that are associated with the menstrual cycles are discussed. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Training of cosmonauts and astronauts

NASA Technical Reports Server (NTRS)

Gurovskiy, N. N.; Link, M. M.

1975-01-01

The biomedical and preflight training of spacecraft crews is discussed based on a survey of scientific and technical literature in the U.S. and U.S.S.R. Experience gained from high velocity and high altitude aircraft flights, predictions of human reactions and theoretical models of human adaptation to the new environment of space, and actual spaceflight experience provided scientists and specialists with data from which the state of human health in space could be predicted and life support measures developed.

Predictability of the geospace variations and measuring the capability to model the state of the system

NASA Astrophysics Data System (ADS)

Pulkkinen, A.

2012-12-01

Empirical modeling has been the workhorse of the past decades in predicting the state of the geospace. For example, numerous empirical studies have shown that global geoeffectiveness indices such as Kp and Dst are generally well predictable from the solar wind input. These successes have been facilitated partly by the strongly externally driven nature of the system. Although characterizing the general state of the system is valuable and empirical modeling will continue playing an important role, refined physics-based quantification of the state of the system has been the obvious next step in moving toward more mature science. Importantly, more refined and localized products are needed also for space weather purposes. Predictions of local physical quantities are necessary to make physics-based links to the impacts on specific systems. As we have introduced more localized predictions of the geospace state one central question is how predictable these local quantities are? This complex question can be addressed by rigorously measuring the model performance against the observed data. Space sciences community has made great advanced on this topic over the past few years and there are ongoing efforts in SHINE, CEDAR and GEM to carry out community-wide evaluations of the state-of-the-art solar and heliospheric, ionosphere-thermosphere and geospace models, respectively. These efforts will help establish benchmarks and thus provide means to measure the progress in the field analogous to monitoring of the improvement in lower atmospheric weather predictions carried out rigorously since 1980s. In this paper we will discuss some of the latest advancements in predicting the local geospace parameters and give an overview of some of the community efforts to rigorously measure the model performances. We will also briefly discuss some of the future opportunities for advancing the geospace modeling capability. These will include further development in data assimilation and ensemble modeling (e.g. taking into account uncertainty in the inflow boundary conditions).

Physics-based Space Weather Forecasting in the Project for Solar-Terrestrial Environment Prediction (PSTEP) in Japan

NASA Astrophysics Data System (ADS)

Kusano, K.

2016-12-01

Project for Solar-Terrestrial Environment Prediction (PSTEP) is a Japanese nation-wide research collaboration, which was recently launched. PSTEP aims to develop a synergistic interaction between predictive and scientific studies of the solar-terrestrial environment and to establish the basis for next-generation space weather forecasting using the state-of-the-art observation systems and the physics-based models. For this project, we coordinate the four research groups, which develop (1) the integration of space weather forecast system, (2) the physics-based solar storm prediction, (3) the predictive models of magnetosphere and ionosphere dynamics, and (4) the model of solar cycle activity and its impact on climate, respectively. In this project, we will build the coordinated physics-based model to answer the fundamental questions concerning the onset of solar eruptions and the mechanism for radiation belt dynamics in the Earth's magnetosphere. In this paper, we will show the strategy of PSTEP, and discuss about the role and prospect of the physics-based space weather forecasting system being developed by PSTEP.

Multiconfiguration Pair-Density Functional Theory Predicts Spin-State Ordering in Iron Complexes with the Same Accuracy as Complete Active Space Second-Order Perturbation Theory at a Significantly Reduced Computational Cost.

PubMed

Wilbraham, Liam; Verma, Pragya; Truhlar, Donald G; Gagliardi, Laura; Ciofini, Ilaria

2017-05-04

The spin-state orderings in nine Fe(II) and Fe(III) complexes with ligands of diverse ligand-field strength were investigated with multiconfiguration pair-density functional theory (MC-PDFT). The performance of this method was compared to that of complete active space second-order perturbation theory (CASPT2) and Kohn-Sham density functional theory. We also investigated the dependence of CASPT2 and MC-PDFT results on the size of the active-space. MC-PDFT reproduces the CASPT2 spin-state ordering, the dependence on the ligand field strength, and the dependence on active space at a computational cost that is significantly reduced as compared to CASPT2.

Sensor Systems for Vehicle Environment Perception in a Highway Intelligent Space System

PubMed Central

Tang, Xiaofeng; Gao, Feng; Xu, Guoyan; Ding, Nenggen; Cai, Yao; Ma, Mingming; Liu, Jianxing

2014-01-01

A Highway Intelligent Space System (HISS) is proposed to study vehicle environment perception in this paper. The nature of HISS is that a space sensors system using laser, ultrasonic or radar sensors are installed in a highway environment and communication technology is used to realize the information exchange between the HISS server and vehicles, which provides vehicles with the surrounding road information. Considering the high-speed feature of vehicles on highways, when vehicles will be passing a road ahead that is prone to accidents, the vehicle driving state should be predicted to ensure drivers have road environment perception information in advance, thereby ensuring vehicle driving safety and stability. In order to verify the accuracy and feasibility of the HISS, a traditional vehicle-mounted sensor system for environment perception is used to obtain the relative driving state. Furthermore, an inter-vehicle dynamics model is built and model predictive control approach is used to predict the driving state in the following period. Finally, the simulation results shows that using the HISS for environment perception can arrive at the same results detected by a traditional vehicle-mounted sensors system. Meanwhile, we can further draw the conclusion that using HISS to realize vehicle environment perception can ensure system stability, thereby demonstrating the method's feasibility. PMID:24834907

Distributions in the error space: goal-directed movements described in time and state-space representations.

PubMed

Fisher, Moria E; Huang, Felix C; Wright, Zachary A; Patton, James L

2014-01-01

Manipulation of error feedback has been of great interest to recent studies in motor control and rehabilitation. Typically, motor adaptation is shown as a change in performance with a single scalar metric for each trial, yet such an approach might overlook details about how error evolves through the movement. We believe that statistical distributions of movement error through the extent of the trajectory can reveal unique patterns of adaption and possibly reveal clues to how the motor system processes information about error. This paper describes different possible ordinate domains, focusing on representations in time and state-space, used to quantify reaching errors. We hypothesized that the domain with the lowest amount of variability would lead to a predictive model of reaching error with the highest accuracy. Here we showed that errors represented in a time domain demonstrate the least variance and allow for the highest predictive model of reaching errors. These predictive models will give rise to more specialized methods of robotic feedback and improve previous techniques of error augmentation.

Tank System Integrated Model: A Cryogenic Tank Performance Prediction Program

NASA Technical Reports Server (NTRS)

Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Sutherlin, S. G.; Schnell, A. R.; Moder, J. P.

2017-01-01

Accurate predictions of the thermodynamic state of the cryogenic propellants, pressurization rate, and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning for future space exploration missions. This Technical Memorandum (TM) presents the analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, mixing, and condensation on the tank wall. This TM also includes comparisons of TankSIM program predictions with the test data andexamples of multiphase mission calculations.

Space-time modeling of timber prices

Treesearch

Mo Zhou; Joseph Buongriorno

2006-01-01

A space-time econometric model was developed for pine sawtimber timber prices of 21 geographically contiguous regions in the southern United States. The correlations between prices in neighboring regions helped predict future prices. The impulse response analysis showed that although southern pine sawtimber markets were not globally integrated, local supply and demand...

Clustering of neural code words revealed by a first-order phase transition

NASA Astrophysics Data System (ADS)

Huang, Haiping; Toyoizumi, Taro

2016-06-01

A network of neurons in the central nervous system collectively represents information by its spiking activity states. Typically observed states, i.e., code words, occupy only a limited portion of the state space due to constraints imposed by network interactions. Geometrical organization of code words in the state space, critical for neural information processing, is poorly understood due to its high dimensionality. Here, we explore the organization of neural code words using retinal data by computing the entropy of code words as a function of Hamming distance from a particular reference codeword. Specifically, we report that the retinal code words in the state space are divided into multiple distinct clusters separated by entropy-gaps, and that this structure is shared with well-known associative memory networks in a recallable phase. Our analysis also elucidates a special nature of the all-silent state. The all-silent state is surrounded by the densest cluster of code words and located within a reachable distance from most code words. This code-word space structure quantitatively predicts typical deviation of a state-trajectory from its initial state. Altogether, our findings reveal a non-trivial heterogeneous structure of the code-word space that shapes information representation in a biological network.

Improved Orbit Determination and Forecasts with an Assimilative Tool for Satellite Drag Specification

NASA Astrophysics Data System (ADS)

Pilinski, M.; Crowley, G.; Sutton, E.; Codrescu, M.

2016-09-01

Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by the variability in density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of LEO satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. As the population of satellites in Earth orbit grows, higher space-weather prediction accuracy is required for critical missions, such as accurate catalog maintenance, collision avoidance for manned and unmanned space flight, reentry prediction, satellite lifetime prediction, defining on-board fuel requirements, and satellite attitude dynamics. We describe ongoing work to build a comprehensive nowcast and forecast system for specifying the neutral atmospheric state related to orbital drag conditions. The system outputs include neutral density, winds, temperature, composition, and the satellite drag derived from these parameters. This modeling tool is based on several state-of-the-art coupled models of the thermosphere-ionosphere as well as several empirical models running in real-time and uses assimilative techniques to produce a thermospheric nowcast. This software will also produce 72 hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition and using near real-time and predicted space weather data and indices as the inputs. In this paper, we will review the driving requirements for our model, summarize the model design and assimilative architecture, and present preliminary validation results. Validation results will be presented in the context of satellite orbit errors and compared with several leading atmospheric models. As part of the analysis, we compare the drag observed by a variety of satellites which were not used as part of the assimilation-dataset and whose perigee altitudes span a range from 200 km to 700 km.

State space model approach for forecasting the use of electrical energy (a case study on: PT. PLN (Persero) district of Kroya)

NASA Astrophysics Data System (ADS)

Kurniati, Devi; Hoyyi, Abdul; Widiharih, Tatik

2018-05-01

Time series data is a series of data taken or measured based on observations at the same time interval. Time series data analysis is used to perform data analysis considering the effect of time. The purpose of time series analysis is to know the characteristics and patterns of a data and predict a data value in some future period based on data in the past. One of the forecasting methods used for time series data is the state space model. This study discusses the modeling and forecasting of electric energy consumption using the state space model for univariate data. The modeling stage is began with optimal Autoregressive (AR) order selection, determination of state vector through canonical correlation analysis, estimation of parameter, and forecasting. The result of this research shows that modeling of electric energy consumption using state space model of order 4 with Mean Absolute Percentage Error (MAPE) value 3.655%, so the model is very good forecasting category.

Space Particle Hazard Measurement and Modeling

DTIC Science & Technology

2016-09-01

understand the interactions of the physical processes driving, then specify and ultimately predict the state of the energetic particle populations...Hudson, and B. T. Kress (2013), Direct observation of the CRAND proton radiation belt source, J. Geophys. Res. Space Physics , 118, doi:10.1002...anticritical temperature for spacecraft charging, J. Geophys Res.: Space Physics , 113, 2156-2202, doi: 10.1029/2008JA013161 2010 – Tested basic

Personalized State-space Modeling of Glucose Dynamics for Type 1 Diabetes Using Continuously Monitored Glucose, Insulin Dose, and Meal Intake: An Extended Kalman Filter Approach.

PubMed

Wang, Qian; Molenaar, Peter; Harsh, Saurabh; Freeman, Kenneth; Xie, Jinyu; Gold, Carol; Rovine, Mike; Ulbrecht, Jan

2014-03-01

An essential component of any artificial pancreas is on the prediction of blood glucose levels as a function of exogenous and endogenous perturbations such as insulin dose, meal intake, and physical activity and emotional tone under natural living conditions. In this article, we present a new data-driven state-space dynamic model with time-varying coefficients that are used to explicitly quantify the time-varying patient-specific effects of insulin dose and meal intake on blood glucose fluctuations. Using the 3-variate time series of glucose level, insulin dose, and meal intake of an individual type 1 diabetic subject, we apply an extended Kalman filter (EKF) to estimate time-varying coefficients of the patient-specific state-space model. We evaluate our empirical modeling using (1) the FDA-approved UVa/Padova simulator with 30 virtual patients and (2) clinical data of 5 type 1 diabetic patients under natural living conditions. Compared to a forgetting-factor-based recursive ARX model of the same order, the EKF model predictions have higher fit, and significantly better temporal gain and J index and thus are superior in early detection of upward and downward trends in glucose. The EKF based state-space model developed in this article is particularly suitable for model-based state-feedback control designs since the Kalman filter estimates the state variable of the glucose dynamics based on the measured glucose time series. In addition, since the model parameters are estimated in real time, this model is also suitable for adaptive control. © 2014 Diabetes Technology Society.

Study of Uncertainties of Predicting Space Shuttle Thermal Environment. [impact of heating rate prediction errors on weight of thermal protection system

NASA Technical Reports Server (NTRS)

Fehrman, A. L.; Masek, R. V.

1972-01-01

Quantitative estimates of the uncertainty in predicting aerodynamic heating rates for a fully reusable space shuttle system are developed and the impact of these uncertainties on Thermal Protection System (TPS) weight are discussed. The study approach consisted of statistical evaluations of the scatter of heating data on shuttle configurations about state-of-the-art heating prediction methods to define the uncertainty in these heating predictions. The uncertainties were then applied as heating rate increments to the nominal predicted heating rate to define the uncertainty in TPS weight. Separate evaluations were made for the booster and orbiter, for trajectories which included boost through reentry and touchdown. For purposes of analysis, the vehicle configuration is divided into areas in which a given prediction method is expected to apply, and separate uncertainty factors and corresponding uncertainty in TPS weight derived for each area.

Characterization of the space shuttle reaction control system engine

NASA Technical Reports Server (NTRS)

Wilson, M. S.; Stechman, R. C.; Edelman, R. B.; Fortune, O. F.; Economos, C.

1972-01-01

A computer program was developed and written in FORTRAN 5 which predicts the transient and steady state performance and heat transfer characteristics of a pulsing GO2/GH2 rocket engine. This program predicts the dynamic flow and ignition characteristics which, when combined in a quasi-steady state manner with the combustion and mixing analysis program, will provide the thrust and specific impulse of the engine as a function of time. The program also predicts the transient and steady state heat transfer characteristics of the engine using various cooling concepts. The computer program, test case, and documentation are presented. The program is applicable to any system capable of utilizing the FORTRAN 4 or FORTRAN 5 language.

Simulation of the Effect of Realistic Space Vehicle Environments on Binary Metal Alloys

NASA Technical Reports Server (NTRS)

Westra, Douglas G.; Poirier, D. R.; Heinrich, J. C.; Sung, P. K.; Felicelli, S. D.; Phelps, Lisa (Technical Monitor)

2001-01-01

Simulations that assess the effect of space vehicle acceleration environments on the solidification of Pb-Sb alloys are reported. Space microgravity missions are designed to provide a near zero-g acceleration environment for various types of scientific experiments. Realistically. these space missions cannot provide a perfect environment. Vibrations caused by crew activity, on-board experiments, support systems stems (pumps, fans, etc.), periodic orbital maneuvers, and water dumps can all cause perturbations to the microgravity environment. In addition, the drag on the space vehicle is a source of acceleration. Therefore, it is necessary to predict the impact of these vibration-perturbations and the steady-state drag acceleration on the experiments. These predictions can be used to design mission timelines. so that the experiment is run during times that the impact of the acceleration environment is acceptable for the experiment of interest. The simulations reported herein were conducted using a finite element model that includes mass, species, momentum, and energy conservation. This model predicts the existence of "channels" within the processing mushy zone and subsequently "freckles" within the fully processed solid, which are the effects of thermosolutal convection. It is necessary to mitigate thermosolutal convection during space experiments of metal alloys, in order to study and characterize diffusion-controlled transport phenomena (microsegregation) that are normally coupled with macrosegregation. The model allows simulation of steady-state and transient acceleration values ranging from no acceleration (0 g). to microgravity conditions (10(exp -6) to 10(exp -3) g), to terrestrial gravity conditions (1 g). The transient acceleration environments simulated were from the STS-89 SpaceHAB mission and from the STS-94 SpaceLAB mission. with on-orbit accelerometer data during different mission periods used as inputs for the simulation model. Periods of crew exercise, quiet (no crew activity), and nominal conditions from STS-89 were used as simulation inputs as were periods of nominal. overboard water-dump, and free-drift (no orbit maneuvering operations) from STS-94. Steady-state acceleration environments of 0.0 and 10(exp -6) to 10(exp -1) g were also simulated, to serve as a comparison to the transient data and to assess an acceptable magnitude for the steady-state vehicle drag

Towards the Next Generation of Space Environment Prediction Capabilities.

NASA Astrophysics Data System (ADS)

Kuznetsova, M. M.

2015-12-01

Since its establishment more than 15 years ago, the Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) is serving as an assess point to expanding collection of state-of-the-art space environment models and frameworks as well as a hub for collaborative development of next generation space weather forecasting systems. In partnership with model developers and international research and operational communities the CCMC integrates new data streams and models from diverse sources into end-to-end space weather impacts predictive systems, identifies week links in data-model & model-model coupling and leads community efforts to fill those gaps. The presentation will highlight latest developments, progress in CCMC-led community-wide projects on testing, prototyping, and validation of models, forecasting techniques and procedures and outline ideas on accelerating implementation of new capabilities in space weather operations.

Atmospheric Turbulence Relative to Aviation, Missile, and Space Programs

NASA Technical Reports Server (NTRS)

Camp, Dennis W. (Editor); Frost, Walter (Editor)

1987-01-01

The purpose of the workshop was to bring together various disciplines of the aviation, missile, and space programs involved in predicting, measuring, modeling, and understanding the processes of atmospheric turbulence. Working committees re-examined the current state of knowledge, identified present and future needs, and documented and prioritized integrated and cooperative research programs.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction.

PubMed

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-06-15

Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence-structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM-HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods. Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx : xin.gao@kaust.edu.sa Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

A Generalized Timeline Representation, Services, and Interface for Automating Space Mission Operations

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Johnston, Mark; Frank, Jeremy; Giuliano, Mark; Kavelaars, Alicia; Lenzen, Christoph; Policella, Nicola

2012-01-01

Numerous automated and semi-automated planning & scheduling systems have been developed for space applications. Most of these systems are model-based in that they encode domain knowledge necessary to predict spacecraft state and resources based on initial conditions and a proposed activity plan. The spacecraft state and resources as often modeled as a series of timelines, with a timeline or set of timelines to represent a state or resource key in the operations of the spacecraft. In this paper, we first describe a basic timeline representation that can represent a set of state, resource, timing, and transition constraints. We describe a number of planning and scheduling systems designed for space applications (and in many cases deployed for use of ongoing missions) and describe how they do and do not map onto this timeline model.

Electrochemical carbon dioxide concentrator subsystem math model. [for manned space station

NASA Technical Reports Server (NTRS)

Marshall, R. D.; Carlson, J. N.; Schubert, F. H.

1974-01-01

A steady state computer simulation model has been developed to describe the performance of a total six man, self-contained electrochemical carbon dioxide concentrator subsystem built for the space station prototype. The math model combines expressions describing the performance of the electrochemical depolarized carbon dioxide concentrator cells and modules previously developed with expressions describing the performance of the other major CS-6 components. The model is capable of accurately predicting CS-6 performance over EDC operating ranges and the computer simulation results agree with experimental data obtained over the prediction range.

Multi-label learning with fuzzy hypergraph regularization for protein subcellular location prediction.

PubMed

Chen, Jing; Tang, Yuan Yan; Chen, C L Philip; Fang, Bin; Lin, Yuewei; Shang, Zhaowei

2014-12-01

Protein subcellular location prediction aims to predict the location where a protein resides within a cell using computational methods. Considering the main limitations of the existing methods, we propose a hierarchical multi-label learning model FHML for both single-location proteins and multi-location proteins. The latent concepts are extracted through feature space decomposition and label space decomposition under the nonnegative data factorization framework. The extracted latent concepts are used as the codebook to indirectly connect the protein features to their annotations. We construct dual fuzzy hypergraphs to capture the intrinsic high-order relations embedded in not only feature space, but also label space. Finally, the subcellular location annotation information is propagated from the labeled proteins to the unlabeled proteins by performing dual fuzzy hypergraph Laplacian regularization. The experimental results on the six protein benchmark datasets demonstrate the superiority of our proposed method by comparing it with the state-of-the-art methods, and illustrate the benefit of exploiting both feature correlations and label correlations.

Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

USGS Publications Warehouse

Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

1997-01-01

One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

Extended Kalman Filter for Estimation of Parameters in Nonlinear State-Space Models of Biochemical Networks

PubMed Central

Sun, Xiaodian; Jin, Li; Xiong, Momiao

2008-01-01

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks. PMID:19018286

Peak Pc Prediction in Conjunction Analysis: Conjunction Assessment Risk Analysis. Pc Behavior Prediction Models

NASA Technical Reports Server (NTRS)

Vallejo, J.J.; Hejduk, M.D.; Stamey, J. D.

2015-01-01

Satellite conjunction risk typically evaluated through the probability of collision (Pc). Considers both conjunction geometry and uncertainties in both state estimates. Conjunction events initially discovered through Joint Space Operations Center (JSpOC) screenings, usually seven days before Time of Closest Approach (TCA). However, JSpOC continues to track objects and issue conjunction updates. Changes in state estimate and reduced propagation time cause Pc to change as event develops. These changes a combination of potentially predictable development and unpredictable changes in state estimate covariance. Operationally useful datum: the peak Pc. If it can reasonably be inferred that the peak Pc value has passed, then risk assessment can be conducted against this peak value. If this value is below remediation level, then event intensity can be relaxed. Can the peak Pc location be reasonably predicted?

Close Approach Prediction Analysis of the Earth Science Constellation with the Fengyun-1C Debris

NASA Technical Reports Server (NTRS)

Duncan, Matthew; Rand, David K.

2008-01-01

Routine satellite operations for the Earth Science Constellation (ESC) include collision risk assessment between members of the constellation and other orbiting space objects. Each day, close approach predictions are generated by a U.S. Department of Defense Joint Space Operations Center Orbital Safety Analyst using the high accuracy Space Object Catalog maintained by the Air Force's 1" Space Control Squadron. Prediction results and other ancillary data such as state vector information are sent to NASAJGoddard Space Flight Center's (GSFC's) Collision Risk Assessment analysis team for review. Collision analysis is performed and the GSFC team works with the ESC member missions to develop risk reduction strategies as necessary. This paper presents various close approach statistics for the ESC. The ESC missions have been affected by debris from the recent anti-satellite test which destroyed the Chinese Fengyun- 1 C satellite. The paper also presents the percentage of close approach events induced by the Fengyun-1C debris, and presents analysis results which predict the future effects on the ESC caused by this event. Specifically, the Fengyun-1C debris is propagated for twenty years using high-performance computing technology and close approach predictions are generated for the ESC. The percent increase in the total number of conjunction events is considered to be an estimate of the collision risk due to the Fengyun-1C break- UP.

A Sequential Ensemble Prediction System at Convection Permitting Scales

NASA Astrophysics Data System (ADS)

Milan, M.; Simmer, C.

2012-04-01

A Sequential Assimilation Method (SAM) following some aspects of particle filtering with resampling, also called SIR (Sequential Importance Resampling), is introduced and applied in the framework of an Ensemble Prediction System (EPS) for weather forecasting on convection permitting scales, with focus to precipitation forecast. At this scale and beyond, the atmosphere increasingly exhibits chaotic behaviour and non linear state space evolution due to convectively driven processes. One way to take full account of non linear state developments are particle filter methods, their basic idea is the representation of the model probability density function by a number of ensemble members weighted by their likelihood with the observations. In particular particle filter with resampling abandons ensemble members (particles) with low weights restoring the original number of particles adding multiple copies of the members with high weights. In our SIR-like implementation we substitute the likelihood way to define weights and introduce a metric which quantifies the "distance" between the observed atmospheric state and the states simulated by the ensemble members. We also introduce a methodology to counteract filter degeneracy, i.e. the collapse of the simulated state space. To this goal we propose a combination of resampling taking account of simulated state space clustering and nudging. By keeping cluster representatives during resampling and filtering, the method maintains the potential for non linear system state development. We assume that a particle cluster with initially low likelihood may evolve in a state space with higher likelihood in a subsequent filter time thus mimicking non linear system state developments (e.g. sudden convection initiation) and remedies timing errors for convection due to model errors and/or imperfect initial condition. We apply a simplified version of the resampling, the particles with highest weights in each cluster are duplicated; for the model evolution for each particle pair one particle evolves using the forward model; the second particle, however, is nudged to the radar and satellite observation during its evolution based on the forward model.

R3 Index for Four-Dimensional N =2 Field Theories

NASA Astrophysics Data System (ADS)

Alexandrov, Sergei; Moore, Gregory W.; Neitzke, Andrew; Pioline, Boris

2015-03-01

In theories with N =2 supersymmetry on R3 ,1, supersymmetric bound states can decay across walls of marginal stability in the space of Coulomb branch parameters, leading to discontinuities in the BPS indices Ω (γ ,u ) . We consider a supersymmetric index I which receives contributions from 1 /2 -BPS states, generalizing the familiar Witten index Tr (-1 )Fe-β H . We expect I to be smooth away from loci where massless particles appear, thanks to contributions from the continuum of multiparticle states. Taking inspiration from a similar phenomenon in the hypermultiplet moduli space of N =2 string vacua, we conjecture a formula expressing I in terms of the BPS indices Ω (γ ,u ), which is continuous across the walls and exhibits the expected contributions from single particle states at large β . This gives a universal prediction for the contributions of multiparticle states to the index I . This index is naturally a function on the moduli space after reduction on a circle, closely related to the canonical hyperkähler metric and hyperholomorphic connection on this space.

R^{3} index for four-dimensional (N)=2 field theories.

PubMed

Alexandrov, Sergei; Moore, Gregory W; Neitzke, Andrew; Pioline, Boris

2015-03-27

In theories with N=2 supersymmetry on R^{3,1}, supersymmetric bound states can decay across walls of marginal stability in the space of Coulomb branch parameters, leading to discontinuities in the BPS indices Ω(γ,u). We consider a supersymmetric index I which receives contributions from 1/2-BPS states, generalizing the familiar Witten index Tr(-1)^{F}e^{-βH}. We expect I to be smooth away from loci where massless particles appear, thanks to contributions from the continuum of multiparticle states. Taking inspiration from a similar phenomenon in the hypermultiplet moduli space of N=2 string vacua, we conjecture a formula expressing I in terms of the BPS indices Ω(γ,u), which is continuous across the walls and exhibits the expected contributions from single particle states at large β. This gives a universal prediction for the contributions of multiparticle states to the index I. This index is naturally a function on the moduli space after reduction on a circle, closely related to the canonical hyperkähler metric and hyperholomorphic connection on this space.

From local uncertainty to global predictions: Making predictions on fractal basins

PubMed Central

2018-01-01

In nonlinear systems long term dynamics is governed by the attractors present in phase space. The presence of a chaotic saddle gives rise to basins of attraction with fractal boundaries and sometimes even to Wada boundaries. These two phenomena involve extreme difficulties in the prediction of the future state of the system. However, we show here that it is possible to make statistical predictions even if we do not have any previous knowledge of the initial conditions or the time series of the system until it reaches its final state. In this work, we develop a general method to make statistical predictions in systems with fractal basins. In particular, we have applied this new method to the Duffing oscillator for a choice of parameters where the system possesses the Wada property. We have computed the statistical properties of the Duffing oscillator for different phase space resolutions, to obtain information about the global dynamics of the system. The key idea is that the fraction of initial conditions that evolve towards each attractor is scale free—which we illustrate numerically. We have also shown numerically how having partial information about the initial conditions of the system does not improve in general the predictions in the Wada regions. PMID:29668687

Web of Objects Based Ambient Assisted Living Framework for Emergency Psychiatric State Prediction

PubMed Central

Alam, Md Golam Rabiul; Abedin, Sarder Fakhrul; Al Ameen, Moshaddique; Hong, Choong Seon

2016-01-01

Ambient assisted living can facilitate optimum health and wellness by aiding physical, mental and social well-being. In this paper, patients’ psychiatric symptoms are collected through lightweight biosensors and web-based psychiatric screening scales in a smart home environment and then analyzed through machine learning algorithms to provide ambient intelligence in a psychiatric emergency. The psychiatric states are modeled through a Hidden Markov Model (HMM), and the model parameters are estimated using a Viterbi path counting and scalable Stochastic Variational Inference (SVI)-based training algorithm. The most likely psychiatric state sequence of the corresponding observation sequence is determined, and an emergency psychiatric state is predicted through the proposed algorithm. Moreover, to enable personalized psychiatric emergency care, a service a web of objects-based framework is proposed for a smart-home environment. In this framework, the biosensor observations and the psychiatric rating scales are objectified and virtualized in the web space. Then, the web of objects of sensor observations and psychiatric rating scores are used to assess the dweller’s mental health status and to predict an emergency psychiatric state. The proposed psychiatric state prediction algorithm reported 83.03 percent prediction accuracy in an empirical performance study. PMID:27608023

Space-for-time substitution in predicting the state of picoplankton and nanoplankton in a changing Arctic Ocean

NASA Astrophysics Data System (ADS)

Li, William K. W.; Carmack, Eddy C.; McLaughlin, Fiona A.; Nelson, R. John; Williams, William J.

2013-10-01

The Arctic Ocean is changing rapidly but there are no long-term time series observations on the state of the phytoplankton community that could allow a link to be made from physical/chemical pressures to the impact on marine ecosystems. Here, we test the idea that space-for-time (SFT) substitution might predict temporal change in the Canada Basin premised on differences in the present state of phytoplankton in other geographic zones, specifically the ratio in the abundance of picophytoplankton to nanophytoplankton (Pico:Nano). We compared the change in Pico:Nano observed in the Canada Basin from 2004 to 2012 to the different average states of this ratio in 26 other ocean ecological regions. Our results show that as upper ocean nitrate concentration changed in the Canada Basin from year to year, the concomitant change in Pico:Nano was statistically commensurate with the difference that this ratio exhibits between Longhurst ecological provinces in relation to nitrate concentration. Lower average concentration of nitrate in the upper water column is associated with a higher value of Pico:Nano, a result consistent with resource control of phytoplankton size structure in the ocean. We suggest that SFT substitution allows an explanation of temporal progression from spatial pattern as a test of mechanism, but such statistical prediction is not necessarily a projection of future states.

Prediction modeling of physiological responses and human performance in the heat with application to space operations

NASA Technical Reports Server (NTRS)

Pandolf, Kent B.; Stroschein, Leander A.; Gonzalez, Richard R.; Sawka, Michael N.

1994-01-01

This institute has developed a comprehensive USARIEM heat strain model for predicting physiological responses and soldier performance in the heat which has been programmed for use by hand-held calculators, personal computers, and incorporated into the development of a heat strain decision aid. This model deals directly with five major inputs: the clothing worn, the physical work intensity, the state of heat acclimation, the ambient environment (air temperature, relative humidity, wind speed, and solar load), and the accepted heat casualty level. In addition to predicting rectal temperature, heart rate, and sweat loss given the above inputs, our model predicts the expected physical work/rest cycle, the maximum safe physical work time, the estimated recovery time from maximal physical work, and the drinking water requirements associated with each of these situations. This model provides heat injury risk management guidance based on thermal strain predictions from the user specified environmental conditions, soldier characteristics, clothing worn, and the physical work intensity. If heat transfer values for space operations' clothing are known, NASA can use this prediction model to help avoid undue heat strain in astronauts during space flight.

Efficient Calibration of Distributed Catchment Models Using Perceptual Understanding and Hydrologic Signatures

NASA Astrophysics Data System (ADS)

Hutton, C.; Wagener, T.; Freer, J. E.; Duffy, C.; Han, D.

2015-12-01

Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models may contain a large number of model parameters which are computationally expensive to calibrate. Even when calibration is possible, insufficient data can result in model parameter and structural equifinality. In order to help reduce the space of feasible models and supplement traditional outlet discharge calibration data, semi-quantitative information (e.g. knowledge of relative groundwater levels), may also be used to identify behavioural models when applied to constrain spatially distributed predictions of states and fluxes. The challenge is to combine these different sources of information together to identify a behavioural region of state-space, and efficiently search a large, complex parameter space to identify behavioural parameter sets that produce predictions that fall within this behavioural region. Here we present a methodology to incorporate different sources of data to efficiently calibrate distributed catchment models. Metrics of model performance may be derived from multiple sources of data (e.g. perceptual understanding and measured or regionalised hydrologic signatures). For each metric, an interval or inequality is used to define the behaviour of the catchment system, accounting for data uncertainties. These intervals are then combined to produce a hyper-volume in state space. The state space is then recast as a multi-objective optimisation problem, and the Borg MOEA is applied to first find, and then populate the hyper-volume, thereby identifying acceptable model parameter sets. We apply the methodology to calibrate the PIHM model at Plynlimon, UK by incorporating perceptual and hydrologic data into the calibration problem. Furthermore, we explore how to improve calibration efficiency through search initialisation from shorter model runs.

Solar Cycle Predictions

NASA Technical Reports Server (NTRS)

Pesnell, William Dean

2012-01-01

Solar cycle predictions are needed to plan long-term space missions; just like weather predictions are needed to plan the launch. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on LEO spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory as you consume the reduced propellant load more rapidly. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Solar cycle predictions also anticipate the shortwave emissions that cause degradation of solar panels. Testing solar dynamo theories by quantitative predictions of what will happen in 5-20 years is the next arena for solar cycle predictions. A summary and analysis of 75 predictions of the amplitude of the upcoming Solar Cycle 24 is presented. The current state of solar cycle predictions and some anticipations how those predictions could be made more accurate in the future will be discussed.

Floquet resonant states and validity of the Floquet-Magnus expansion in the periodically driven Friedrichs models

NASA Astrophysics Data System (ADS)

Mori, Takashi

2015-02-01

The Floquet eigenvalue problem is analyzed for periodically driven Friedrichs models on discrete and continuous space. In the high-frequency regime, there exists a Floquet bound state consistent with the Floquet-Magnus expansion in the discrete Friedrichs model, while it is not the case in the continuous model. In the latter case, however, the bound state predicted by the Floquet-Magnus expansion appears as a metastable state whose lifetime diverges in the limit of large frequencies. We obtain the lifetime by evaluating the imaginary part of the quasienergy of the Floquet resonant state. In the low-frequency regime, there is no Floquet bound state and instead the Floquet resonant state with exponentially small imaginary part of the quasienergy appears, which is understood as the quantum tunneling in the energy space.

Complex sample survey estimation in static state-space

Treesearch

Raymond L. Czaplewski

2010-01-01

Increased use of remotely sensed data is a key strategy adopted by the Forest Inventory and Analysis Program. However, multiple sensor technologies require complex sampling units and sampling designs. The Recursive Restriction Estimator (RRE) accommodates this complexity. It is a design-consistent Empirical Best Linear Unbiased Prediction for the state-vector, which...

Bifurcation of rotating liquid drops: Results from USML-1 experiments in space

NASA Technical Reports Server (NTRS)

Wang, Taylor G.; Anilkumar, A. V.; Lee, C. P.; Lin, K. C.

1994-01-01

Experiments on rotational bifurcation of liquid drops, in which the drops were levitated and spun using acoustic fields in a low-gravity environment, were conducted during the first United States Microgravity Laboratory (USML-1) Space Shuttle flight. The experiments have successfully resolved the discrepancies existing between the previous experimental results and the theoretical predictions. In the case of a spherical drop, for which theory exists, the results agree well with the predictions. In the case of flattened drops, the experiments have extablished a family of curves, with the spherical drop as the limiting case.

Using state-space models to predict the abundance of juvenile and adult sea lice on Atlantic salmon.

PubMed

Elghafghuf, Adel; Vanderstichel, Raphael; St-Hilaire, Sophie; Stryhn, Henrik

2018-04-11

Sea lice are marine parasites affecting salmon farms, and are considered one of the most costly pests of the salmon aquaculture industry. Infestations of sea lice on farms significantly increase opportunities for the parasite to spread in the surrounding ecosystem, making control of this pest a challenging issue for salmon producers. The complexity of controlling sea lice on salmon farms requires frequent monitoring of the abundance of different sea lice stages over time. Industry-based data sets of counts of lice are amenable to multivariate time-series data analyses. In this study, two sets of multivariate autoregressive state-space models were applied to Chilean sea lice data from six Atlantic salmon production cycles on five isolated farms (at least 20 km seaway distance away from other known active farms), to evaluate the utility of these models for predicting sea lice abundance over time on farms. The models were constructed with different parameter configurations, and the analysis demonstrated large heterogeneity between production cycles for the autoregressive parameter, the effects of chemotherapeutant bath treatments, and the process-error variance. A model allowing for different parameters across production cycles had the best fit and the smallest overall prediction errors. However, pooling information across cycles for the drift and observation error parameters did not substantially affect model performance, thus reducing the number of necessary parameters in the model. Bath treatments had strong but variable effects for reducing sea lice burdens, and these effects were stronger for adult lice than juvenile lice. Our multivariate state-space models were able to handle different sea lice stages and provide predictions for sea lice abundance with reasonable accuracy up to five weeks out. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Fast metabolite identification with Input Output Kernel Regression.

PubMed

Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

2016-06-15

An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. celine.brouard@aalto.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Fast metabolite identification with Input Output Kernel Regression

PubMed Central

Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

2016-01-01

Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628

Latent degradation indicators estimation and prediction: A Monte Carlo approach

NASA Astrophysics Data System (ADS)

Zhou, Yifan; Sun, Yong; Mathew, Joseph; Wolff, Rodney; Ma, Lin

2011-01-01

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.

Three-body effects in the Hoyle-state decay

NASA Astrophysics Data System (ADS)

Refsgaard, J.; Fynbo, H. O. U.; Kirsebom, O. S.; Riisager, K.

2018-04-01

We use a sequential R-matrix model to describe the breakup of the Hoyle state into three α particles via the ground state of 8Be. It is shown that even in a sequential picture, features resembling a direct breakup branch appear in the phase-space distribution of the α particles. We construct a toy model to describe the Coulomb interaction in the three-body final state and its effects on the decay spectrum are investigated. The framework is also used to predict the phase-space distribution of the α particles emitted in a direct breakup of the Hoyle state and the possibility of interference between a direct and sequential branch is discussed. Our numerical results are compared to the current upper limit on the direct decay branch determined in recent experiments.

Real-space mapping of electronic orbitals.

PubMed

Löffler, Stefan; Bugnet, Matthieu; Gauquelin, Nicolas; Lazar, Sorin; Assmann, Elias; Held, Karsten; Botton, Gianluigi A; Schattschneider, Peter

2017-06-01

Electronic states are responsible for most material properties, including chemical bonds, electrical and thermal conductivity, as well as optical and magnetic properties. Experimentally, however, they remain mostly elusive. Here, we report the real-space mapping of selected transitions between p and d states on the Ångström scale in bulk rutile (TiO 2 ) using electron energy-loss spectrometry (EELS), revealing information on individual bonds between atoms. On the one hand, this enables the experimental verification of theoretical predictions about electronic states. On the other hand, it paves the way for directly investigating electronic states under conditions that are at the limit of the current capabilities of numerical simulations such as, e.g., the electronic states at defects, interfaces, and quantum dots. Copyright © 2017 Elsevier B.V. All rights reserved.

[Human venous hemodynamics in microgravity and prediction of orthostatic tolerance in flight].

PubMed

Kotovskaya, A R; Fomina, G A

2013-01-01

The paper presents the results of investigating the lower limbs venous status in cosmonauts (n = 13) with the use of occlusion plethysmography in 6-month missions to the Russian segment of the International space station (ISS). An interrelation of shifts in venous capacitance, compliance and filling with orthostatic tolerance (OT) in the lower body negative pressure test (LBNP) was stated. OT predictability by the leg vein status in the course of space flight was demonstrated. The objective changes of veins predictive of OT reduction were identified. There are 3 levels of changes in venous capacitance, compliance and filling that prognosticate respective reductions in LBNP tolerance and were attested in 91% of the in-flight LBNP testing.

Cognitive appraisal of environmental stimuli induces emotion-like states in fish.

PubMed

Cerqueira, M; Millot, S; Castanheira, M F; Félix, A S; Silva, T; Oliveira, G A; Oliveira, C C; Martins, C I M; Oliveira, R F

2017-10-13

The occurrence of emotions in non-human animals has been the focus of debate over the years. Recently, an interest in expanding this debate to non-tetrapod vertebrates and to invertebrates has emerged. Within vertebrates, the study of emotion in teleosts is particularly interesting since they represent a divergent evolutionary radiation from that of tetrapods, and thus they provide an insight into the evolution of the biological mechanisms of emotion. We report that Sea Bream exposed to stimuli that vary according to valence (positive, negative) and salience (predictable, unpredictable) exhibit different behavioural, physiological and neuromolecular states. Since according to the dimensional theory of emotion valence and salience define a two-dimensional affective space, our data can be interpreted as evidence for the occurrence of distinctive affective states in fish corresponding to each the four quadrants of the core affective space. Moreover, the fact that the same stimuli presented in a predictable vs. unpredictable way elicited different behavioural, physiological and neuromolecular states, suggests that stimulus appraisal by the individual, rather than an intrinsic characteristic of the stimulus, has triggered the observed responses. Therefore, our data supports the occurrence of emotion-like states in fish that are regulated by the individual's perception of environmental stimuli.

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

Liu Kun; Zhao Hongmei; Wang Caixia

Bromoiodomethane photodissociation in the low-lying excited states has been characterized using unrestricted Hartree-Fock, configuration-interaction-singles, and complete active space self-consistent field calculations with the SDB-aug-cc-pVTZ, aug-cc-pVTZ, and 3-21g** basis sets. According to the results of the vertical excited energies and oscillator strengths of these low-lying excited states, bond selectivity is predicted. Subsequently, the minimum energy paths of the first excited singlet state and the third excited state for the dissociation reactions were calculated using the complete active space self-consistent field method with 3-21g** basis set. Good agreement is found between the calculations and experimental data. The relationships of excitations, the electronicmore » structures at Franck-Condon points, and bond selectivity are discussed.« less

A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury

PubMed Central

Kohonen, Pekka; Parkkinen, Juuso A.; Willighagen, Egon L.; Ceder, Rebecca; Wennerberg, Krister; Kaski, Samuel; Grafström, Roland C.

2017-01-01

Predicting unanticipated harmful effects of chemicals and drug molecules is a difficult and costly task. Here we utilize a ‘big data compacting and data fusion’—concept to capture diverse adverse outcomes on cellular and organismal levels. The approach generates from transcriptomics data set a ‘predictive toxicogenomics space’ (PTGS) tool composed of 1,331 genes distributed over 14 overlapping cytotoxicity-related gene space components. Involving ∼2.5 × 108 data points and 1,300 compounds to construct and validate the PTGS, the tool serves to: explain dose-dependent cytotoxicity effects, provide a virtual cytotoxicity probability estimate intrinsic to omics data, predict chemically-induced pathological states in liver resulting from repeated dosing of rats, and furthermore, predict human drug-induced liver injury (DILI) from hepatocyte experiments. Analysing 68 DILI-annotated drugs, the PTGS tool outperforms and complements existing tests, leading to a hereto-unseen level of DILI prediction accuracy. PMID:28671182

Trial wave functions for ring-trapped ions and neutral atoms: Microscopic description of the quantum space-time crystal

NASA Astrophysics Data System (ADS)

Yannouleas, Constantine; Landman, Uzi

2017-10-01

A constructive theoretical platform for the description of quantum space-time crystals uncovers for N interacting and ring-confined rotating particles the existence of low-lying states with proper space-time crystal behavior. The construction of the corresponding many-body trial wave functions proceeds first via symmetry breaking at the mean-field level followed by symmetry restoration using projection techniques. The ensuing correlated many-body wave functions are stationary states and preserve the rotational symmetries, and at the same time they reflect the point-group symmetries of the mean-field crystals. This behavior results in the emergence of sequences of select magic angular momenta Lm. For angular-momenta away from the magic values, the trial functions vanish. Symmetry breaking beyond the mean-field level can be induced by superpositions of such good-Lm many-body stationary states. We show that superposing a pair of adjacent magic angular momenta states leads to formation of special broken-symmetry states exhibiting quantum space-time-crystal behavior. In particular, the corresponding particle densities rotate around the ring, showing undamped and nondispersed periodic crystalline evolution in both space and time. The experimental synthesis of such quantum space-time-crystal wave packets is predicted to be favored in the vicinity of ground-state energy crossings of the Aharonov-Bohm-type spectra accessed via an externally applied, natural or synthetic, magnetic field. These results are illustrated here for Coulomb-repelling fermionic ions and for a lump of contact-interaction attracting bosons.

Measurement and Characterization of the Acceleration Environment on Board the Space Station

NASA Technical Reports Server (NTRS)

Baugher, Charles R. (Editor)

1990-01-01

This workshop provides a comprehensive overview of the work and status of each of these areas to provide a basis for establishing a systematic approach to the challenge of avoiding these difficulties during the Space Station era of materials experimentation. The discussions were arranged in the order of: the scientific understanding of the requirements for a micro-gravity environment, a history of acceleration measurements on spacecraft, the state of accelerometer technology, and the current understanding of the predicted Space Station environment.

The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction.

PubMed

Casey, M

1996-08-15

Recurrent neural networks (RNNs) can learn to perform finite state computations. It is shown that an RNN performing a finite state computation must organize its state space to mimic the states in the minimal deterministic finite state machine that can perform that computation, and a precise description of the attractor structure of such systems is given. This knowledge effectively predicts activation space dynamics, which allows one to understand RNN computation dynamics in spite of complexity in activation dynamics. This theory provides a theoretical framework for understanding finite state machine (FSM) extraction techniques and can be used to improve training methods for RNNs performing FSM computations. This provides an example of a successful approach to understanding a general class of complex systems that has not been explicitly designed, e.g., systems that have evolved or learned their internal structure.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

NASA Astrophysics Data System (ADS)

Hong, S.-M.; Jung, B.-H.; Ruan, D.

2011-03-01

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

PubMed

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Mediterranean space-time extremes of wind wave sea states

NASA Astrophysics Data System (ADS)

Barbariol, Francesco; Carniel, Sandro; Sclavo, Mauro; Marcello Falcieri, Francesco; Bonaldo, Davide; Bergamasco, Andrea; Benetazzo, Alvise

2014-05-01

Traditionally, wind wave sea states during storms have been observed, modeled, and predicted mostly in the time domain, i.e. at a fixed point. In fact, the standard statistical models used in ocean waves analysis rely on the implicit assumption of long-crested waves. Nevertheless, waves in storms are mainly short-crested. Hence, spatio-temporal features of the wave field are crucial to accurately model the sea state characteristics and to provide reliable predictions, particurly of wave extremes. Indeed, the experimental evidence provided by novel instrumentations, e.g. WASS (Wave Acquisition Stereo System), showed that the maximum sea surface elevation gathered in time over an area, i.e. the space-time extreme, is larger than that one measured in time at a point, i.e. the time extreme. Recently, stochastic models used to estimate maxima of multidimensional Gaussian random fields have been applied to ocean waves statistics. These models are based either on Piterbarg's theorem or Adler and Taylor's Euler Characteristics approach. Besides a probability of exceedance of a certain threshold, they can provide the expected space-time extreme of a sea state, as long as space-time wave features (i.e. some parameters of the directional variance density spectrum) are known. These models have been recently validated against WASS observation from fixed and moving platforms. In this context, our focus was modeling and predicting extremes of wind waves during storms. Thus, to intensively gather space-time extremes data over the Mediterranean region, we used directional spectra provided by the numerical wave model SWAN (Simulating WAves Nearshore). Therefore, we set up a 6x6 km2 resolution grid entailing most of the Mediterranean Sea and we forced it with COSMO-I7 high resolution (7x7 km2) hourly wind fields, within 2007-2013 period. To obtain the space-time features, i.e. the spectral parameters, at each grid node and over the 6 simulated years, we developed a modified version of the SWAN model, the SWAN Space-Time (SWAN-ST). SWAN-ST results were post-processed to obtain the expected space-time extremes over the model domain. To this end, we applied the stochastic model of Fedele, developed starting from Adler and Taylor's approach, which we found to be more accurate and versatile with respect to Piterbarg's theorem. Results we obtained provide an alternative sight on Mediterranean extreme wave climate, which could represent the first step towards operationl forecasting of space-time wave extremes, on the one hand, and the basis for a novel statistical standard wave model, on the other. These results may benefit marine designers, seafarers and other subjects operating at sea and exposed to the frequent and severe hazard represented by extreme wave conditions.

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

State-space decoding of primary afferent neuron firing rates

NASA Astrophysics Data System (ADS)

Wagenaar, J. B.; Ventura, V.; Weber, D. J.

2011-02-01

Kinematic state feedback is important for neuroprostheses to generate stable and adaptive movements of an extremity. State information, represented in the firing rates of populations of primary afferent (PA) neurons, can be recorded at the level of the dorsal root ganglia (DRG). Previous work in cats showed the feasibility of using DRG recordings to predict the kinematic state of the hind limb using reverse regression. Although accurate decoding results were attained, reverse regression does not make efficient use of the information embedded in the firing rates of the neural population. In this paper, we present decoding results based on state-space modeling, and show that it is a more principled and more efficient method for decoding the firing rates in an ensemble of PA neurons. In particular, we show that we can extract confounded information from neurons that respond to multiple kinematic parameters, and that including velocity components in the firing rate models significantly increases the accuracy of the decoded trajectory. We show that, on average, state-space decoding is twice as efficient as reverse regression for decoding joint and endpoint kinematics.

Multiscale approach to the determination of the photoactive yellow protein signaling state ensemble.

PubMed

A Rohrdanz, Mary; Zheng, Wenwei; Lambeth, Bradley; Vreede, Jocelyne; Clementi, Cecilia

2014-10-01

The nature of the optical cycle of photoactive yellow protein (PYP) makes its elucidation challenging for both experiment and theory. The long transition times render conventional simulation methods ineffective, and yet the short signaling-state lifetime makes experimental data difficult to obtain and interpret. Here, through an innovative combination of computational methods, a prediction and analysis of the biological signaling state of PYP is presented. Coarse-grained modeling and locally scaled diffusion map are first used to obtain a rough bird's-eye view of the free energy landscape of photo-activated PYP. Then all-atom reconstruction, followed by an enhanced sampling scheme; diffusion map-directed-molecular dynamics are used to focus in on the signaling-state region of configuration space and obtain an ensemble of signaling state structures. To the best of our knowledge, this is the first time an all-atom reconstruction from a coarse grained model has been performed in a relatively unexplored region of molecular configuration space. We compare our signaling state prediction with previous computational and more recent experimental results, and the comparison is favorable, which validates the method presented. This approach provides additional insight to understand the PYP photo cycle, and can be applied to other systems for which more direct methods are impractical.

Kalman filters for fractional discrete-time stochastic systems along with time-delay in the observation signal

NASA Astrophysics Data System (ADS)

Torabi, H.; Pariz, N.; Karimpour, A.

2016-02-01

This paper investigates fractional Kalman filters when time-delay is entered in the observation signal in the discrete-time stochastic fractional order state-space representation. After investigating the common fractional Kalman filter, we try to derive a fractional Kalman filter for time-delay fractional systems. A detailed derivation is given. Fractional Kalman filters will be used to estimate recursively the states of fractional order state-space systems based on minimizing the cost function when there is a constant time delay (d) in the observation signal. The problem will be solved by converting the filtering problem to a usual d-step prediction problem for delay-free fractional systems.

Operating Deflection Shapes for the Space Shuttle Partial Stack Rollout

NASA Technical Reports Server (NTRS)

Buehrle, Ralph D.; Kappus, Kathy

2005-01-01

In November of 2003 a rollout test was performed to gain a better understanding of the dynamic environment for the Space Shuttle during transportation from the Vehicle Assembly Building to the launch pad. This was part of a study evaluating the methodology for including the rollout dynamic loads in the Space Shuttle fatigue life predictions. The rollout test was conducted with a partial stack consisting of the Crawler Transporter, Mobile Launch Platform, and the Solid Rocket Boosters with an interconnecting crossbeam. Instrumentation included over 100 accelerometers. Data was recorded for steady state speeds, start-ups and stops, and ambient wind excitations with the vehicle at idle. This paper will describe the operating deflection shape analysis performed using the measured acceleration response data. The response data for the steady state speed runs were dominated by harmonics of the forcing frequencies, which were proportional to the vehicle speed. Assuming a broadband excitation for the wind, analyses of the data sets with the vehicle at idle were used to estimate the natural frequencies and corresponding mode shapes. Comparisons of the measured modal properties with numerical predictions are presented.

TankSIM: A Cryogenic Tank Performance Prediction Program

NASA Technical Reports Server (NTRS)

Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Moder, J. P.; Schnell, A. R.; Sutherlin, S. G.

2015-01-01

Accurate prediction of the thermodynamic state of the cryogenic propellants in launch vehicle tanks is necessary for mission planning and successful execution. Cryogenic propellant storage and transfer in space environments requires that tank pressure be controlled. The pressure rise rate is determined by the complex interaction of external heat leak, fluid temperature stratification, and interfacial heat and mass transfer. If the required storage duration of a space mission is longer than the period in which the tank pressure reaches its allowable maximum, an appropriate pressure control method must be applied. Therefore, predictions of the pressurization rate and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning of future space exploration missions. This paper describes an analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. It is written in the FORTRAN 90 language and can be compiled with any Visual FORTRAN compiler. A thermodynamic vent system (TVS) is used to achieve tank pressure control. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, and mixing. Details of the TankSIM program and comparisons of its predictions with test data for liquid hydrogen and liquid methane will be presented in the final paper.

A Survey of Space Robotics

NASA Technical Reports Server (NTRS)

Pedersen, L.; Kortenkamp, D.; Wettergreen, D.; Nourbakhsh, I.; Korsmeyer, David (Technical Monitor)

2003-01-01

In this paper we summarize a survey conducted by NASA to determine the state-of-the-art in space robotics and to predict future robotic capabilities under either nominal and intensive development effort. The space robotics assessment study examined both in-space operations including assembly, inspection, and maintenance and planetary surface operations like mobility and exploration. Applications of robotic autonomy and human-robot cooperation were considered. The study group devised a decomposition of robotic capabilities and then suggested metrics to specify the technical challenges associated with each. The conclusion of this paper identifies possible areas in which investment in space robotics could lead to significant advances of important technologies.

Space Weather Impacts to Conjunction Assessment: A NASA Robotic Orbital Safety Perspective

NASA Technical Reports Server (NTRS)

Ghrist, Richard; Ghrist, Richard; DeHart, Russel; Newman, Lauri

2013-01-01

National Aeronautics and Space Administration (NASA) recognizes the risk of on-orbit collisions from other satellites and debris objects and has instituted a process to identify and react to close approaches. The charter of the NASA Robotic Conjunction Assessment Risk Analysis (CARA) task is to protect NASA robotic (unmanned) assets from threats posed by other space objects. Monitoring for potential collisions requires formulating close-approach predictions a week or more in the future to determine analyze, and respond to orbital conjunction events of interest. These predictions require propagation of the latest state vector and covariance assuming a predicted atmospheric density and ballistic coefficient. Any differences between the predicted drag used for propagation and the actual drag experienced by the space objects can potentially affect the conjunction event. Therefore, the space environment itself, in particular how space weather impacts atmospheric drag, is an essential element to understand in order effectively to assess the risk of conjunction events. The focus of this research is to develop a better understanding of the impact of space weather on conjunction assessment activities: both accurately determining the current risk and assessing how that risk may change under dynamic space weather conditions. We are engaged in a data-- ]mining exercise to corroborate whether or not observed changes in a conjunction event's dynamics appear consistent with space weather changes and are interested in developing a framework to respond appropriately to uncertainty in predicted space weather. In particular, we use historical conjunction event data products to search for dynamical effects on satellite orbits from changing atmospheric drag. Increased drag is expected to lower the satellite specific energy and will result in the satellite's being 'later' than expected, which can affect satellite conjunctions in a number of ways depending on the two satellites' orbits and the geometry of the conjunction. These satellite time offsets can form the basis of a new technique under development to determine whether space weather perturbations, such as coronal mass ejections, are likely to increase, decrease, or have a neutral effect on the collision risk due to a particular close approach.

Space Weather: What is it, and Why Should a Meteorologist Care?

NASA Technical Reports Server (NTRS)

SaintCyr, Chris; Murtagh, Bill

2008-01-01

"Space weather" is a term coined almost 15 years ago to describe environmental conditions ABOVE Earth's atmosphere that affect satellites and astronauts. As society has become more dependent on technology, we nave found that space weather conditions increasingly affect numerous commercial and infrastructure sectors: airline operations, the precision positioning industry, and the electric power grid, to name a few. Similar to meteorology where "weather" often refers to severe conditions, "space weather" includes geomagnetic storms, radiation storms, and radio blackouts. But almost all space weather conditions begin at the Sun--our middle-age, magnetically-variable star. At NASA, the science behind space weather takes place in the Heliophysics Division. The Space Weather Prediction Center in Boulder, Colorado, is manned jointly by NCAA and US Air Force personnel, and it provides space weather alerts and warnings for disturbances that can affect people and equipment working in space and on Earth. Organizationally, it resides in NOAA's National Weather Service as one of the National Centers for Environmental Prediction. In this seminar we hope to give the audience a brief introduction to the causes of space weather, discuss some of the effects, and describe the state of the art in forecasting. Our goal is to highlight that meteorologists are increasingly becoming the "first responders" to questions about space weather causes and effects.

Space Shuttle booster thrust imbalance analysis

NASA Technical Reports Server (NTRS)

Bailey, W. R.; Blackwell, D. L.

1985-01-01

An analysis of the Shuttle SRM thrust imbalance during the steady-state and tailoff portions of the boost phase of flight are presented. Results from flights STS-1 through STS-13 are included. A statistical analysis of the observed thrust imbalance data is presented. A 3 sigma thrust imbalance history versus time was generated from the observed data and is compared to the vehicle design requirements. The effect on Shuttle thrust imbalance from the use of replacement SRM segments is predicted. Comparisons of observed thrust imbalances with respect to predicted imbalances are presented for the two space shuttle flights which used replacement aft segments (STS-9 and STS-13).

Predicting Space Weather Effects on Close Approach Events

NASA Technical Reports Server (NTRS)

Hejduk, Matthew D.; Newman, Lauri K.; Besser, Rebecca L.; Pachura, Daniel A.

2015-01-01

The NASA Robotic Conjunction Assessment Risk Analysis (CARA) team sends ephemeris data to the Joint Space Operations Center (JSpOC) for conjunction assessment screening against the JSpOC high accuracy catalog and then assesses risk posed to protected assets from predicted close approaches. Since most spacecraft supported by the CARA team are located in LEO orbits, atmospheric drag is the primary source of state estimate uncertainty. Drag magnitude and uncertainty is directly governed by atmospheric density and thus space weather. At present the actual effect of space weather on atmospheric density cannot be accurately predicted because most atmospheric density models are empirical in nature, which do not perform well in prediction. The Jacchia-Bowman-HASDM 2009 (JBH09) atmospheric density model used at the JSpOC employs a solar storm active compensation feature that predicts storm sizes and arrival times and thus the resulting neutral density alterations. With this feature, estimation errors can occur in either direction (i.e., over- or under-estimation of density and thus drag). Although the exact effect of a solar storm on atmospheric drag cannot be determined, one can explore the effects of JBH09 model error on conjuncting objects' trajectories to determine if a conjunction is likely to become riskier, less risky, or pass unaffected. The CARA team has constructed a Space Weather Trade-Space tool that systematically alters the drag situation for the conjuncting objects and recalculates the probability of collision for each case to determine the range of possible effects on the collision risk. In addition to a review of the theory and the particulars of the tool, the different types of observed output will be explained, along with statistics of their frequency.

Knotty: Efficient and Accurate Prediction of Complex RNA Pseudoknot Structures.

PubMed

Jabbari, Hosna; Wark, Ian; Montemagno, Carlo; Will, Sebastian

2018-06-01

The computational prediction of RNA secondary structure by free energy minimization has become an important tool in RNA research. However in practice, energy minimization is mostly limited to pseudoknot-free structures or rather simple pseudoknots, not covering many biologically important structures such as kissing hairpins. Algorithms capable of predicting sufficiently complex pseudoknots (for sequences of length n) used to have extreme complexities, e.g. Pknots (Rivas and Eddy, 1999) has O(n6) time and O(n4) space complexity. The algorithm CCJ (Chen et al., 2009) dramatically improves the asymptotic run time for predicting complex pseudoknots (handling almost all relevant pseudoknots, while being slightly less general than Pknots), but this came at the cost of large constant factors in space and time, which strongly limited its practical application (∼200 bases already require 256GB space). We present a CCJ-type algorithm, Knotty, that handles the same comprehensive pseudoknot class of structures as CCJ with improved space complexity of Θ(n3 + Z)-due to the applied technique of sparsification, the number of "candidates", Z, appears to grow significantly slower than n4 on our benchmark set (which include pseudoknotted RNAs up to 400 nucleotides). In terms of run time over this benchmark, Knotty clearly outperforms Pknots and the original CCJ implementation, CCJ 1.0; Knotty's space consumption fundamentally improves over CCJ 1.0, being on a par with the space-economic Pknots. By comparing to CCJ 2.0, our unsparsified Knotty variant, we demonstrate the isolated effect of sparsification. Moreover, Knotty employs the state-of-the-art energy model of "HotKnots DP09", which results in superior prediction accuracy over Pknots. Our software is available at https://github.com/HosnaJabbari/Knotty. will@tbi.unvie.ac.at. Supplementary data are available at Bioinformatics online.

Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

2016-08-01

Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Uncertainty propagation for statistical impact prediction of space debris

NASA Astrophysics Data System (ADS)

Hoogendoorn, R.; Mooij, E.; Geul, J.

2018-01-01

Predictions of the impact time and location of space debris in a decaying trajectory are highly influenced by uncertainties. The traditional Monte Carlo (MC) method can be used to perform accurate statistical impact predictions, but requires a large computational effort. A method is investigated that directly propagates a Probability Density Function (PDF) in time, which has the potential to obtain more accurate results with less computational effort. The decaying trajectory of Delta-K rocket stages was used to test the methods using a six degrees-of-freedom state model. The PDF of the state of the body was propagated in time to obtain impact-time distributions. This Direct PDF Propagation (DPP) method results in a multi-dimensional scattered dataset of the PDF of the state, which is highly challenging to process. No accurate results could be obtained, because of the structure of the DPP data and the high dimensionality. Therefore, the DPP method is less suitable for practical uncontrolled entry problems and the traditional MC method remains superior. Additionally, the MC method was used with two improved uncertainty models to obtain impact-time distributions, which were validated using observations of true impacts. For one of the two uncertainty models, statistically more valid impact-time distributions were obtained than in previous research.

Dynamics of Entropy in Quantum-like Model of Decision Making

NASA Astrophysics Data System (ADS)

Basieva, Irina; Khrennikov, Andrei; Asano, Masanari; Ohya, Masanori; Tanaka, Yoshiharu

2011-03-01

We present a quantum-like model of decision making in games of the Prisoner's Dilemma type. By this model the brain processes information by using representation of mental states in complex Hilbert space. Driven by the master equation the mental state of a player, say Alice, approaches an equilibrium point in the space of density matrices. By using this equilibrium point Alice determines her mixed (i.e., probabilistic) strategy with respect to Bob. Thus our model is a model of thinking through decoherence of initially pure mental state. Decoherence is induced by interaction with memory and external environment. In this paper we study (numerically) dynamics of quantum entropy of Alice's state in the process of decision making. Our analysis demonstrates that this dynamics depends nontrivially on the initial state of Alice's mind on her own actions and her prediction state (for possible actions of Bob.)

A theoretical study of bond selective photochemistry in CH2BrI

NASA Astrophysics Data System (ADS)

Liu, Kun; Zhao, Hongmei; Wang, Caixia; Zhang, Aihua; Ma, Siyu; Li, Zonghe

2005-01-01

Bromoiodomethane photodissociation in the low-lying excited states has been characterized using unrestricted Hartree-Fock, configuration-interaction-singles, and complete active space self-consistent field calculations with the SDB-aug-cc-pVTZ, aug-cc-pVTZ, and 3-21g** basis sets. According to the results of the vertical excited energies and oscillator strengths of these low-lying excited states, bond selectivity is predicted. Subsequently, the minimum energy paths of the first excited singlet state and the third excited state for the dissociation reactions were calculated using the complete active space self-consistent field method with 3-21g** basis set. Good agreement is found between the calculations and experimental data. The relationships of excitations, the electronic structures at Franck-Condon points, and bond selectivity are discussed.

Towards feasible and effective predictive wavefront control for adaptive optics

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

Poyneer, L A; Veran, J

We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.

Space shuttle propulsion parameter estimation using optimal estimation techniques

NASA Technical Reports Server (NTRS)

1983-01-01

The first twelve system state variables are presented with the necessary mathematical developments for incorporating them into the filter/smoother algorithm. Other state variables, i.e., aerodynamic coefficients can be easily incorporated into the estimation algorithm, representing uncertain parameters, but for initial checkout purposes are treated as known quantities. An approach for incorporating the NASA propulsion predictive model results into the optimal estimation algorithm was identified. This approach utilizes numerical derivatives and nominal predictions within the algorithm with global iterations of the algorithm. The iterative process is terminated when the quality of the estimates provided no longer significantly improves.

A compound reconstructed prediction model for nonstationary climate processes

NASA Astrophysics Data System (ADS)

Wang, Geli; Yang, Peicai

2005-07-01

Based on the idea of climate hierarchy and the theory of state space reconstruction, a local approximation prediction model with the compound structure is built for predicting some nonstationary climate process. By means of this model and the data sets consisting of north Indian Ocean sea-surface temperature, Asian zonal circulation index and monthly mean precipitation anomaly from 37 observation stations in the Inner Mongolia area of China (IMC), a regional prediction experiment for the winter precipitation of IMC is also carried out. When using the same sign ratio R between the prediction field and the actual field to measure the prediction accuracy, an averaged R of 63% given by 10 predictions samples is reached.

Enhanced sampling of molecular dynamics simulation of peptides and proteins by double coupling to thermal bath.

PubMed

Chen, Changjun; Huang, Yanzhao; Xiao, Yi

2013-01-01

Low sampling efficiency in conformational space is the well-known problem for conventional molecular dynamics. It greatly increases the difficulty for molecules to find the transition path to native state, and costs amount of CPU time. To accelerate the sampling, in this paper, we re-couple the critical degrees of freedom in the molecule to environment temperature, like dihedrals in generalized coordinates or nonhydrogen atoms in Cartesian coordinate. After applying to ALA dipeptide model, we find that this modified molecular dynamics greatly enhances the sampling behavior in the conformational space and provides more information about the state-to-state transition, while conventional molecular dynamics fails to do so. Moreover, from the results of 16 independent 100 ns simulations by the new method, it shows that trpzip2 has one-half chances to reach the naive state in all the trajectories, which is greatly higher than conventional molecular dynamics. Such an improvement would provide a potential way for searching the conformational space or predicting the most stable states of peptides and proteins.

Model Adaptation in Parametric Space for POD-Galerkin Models

NASA Astrophysics Data System (ADS)

Gao, Haotian; Wei, Mingjun

2017-11-01

The development of low-order POD-Galerkin models is largely motivated by the expectation to use the model developed with a set of parameters at their native values to predict the dynamic behaviors of the same system under different parametric values, in other words, a successful model adaptation in parametric space. However, most of time, even small deviation of parameters from their original value may lead to large deviation or unstable results. It has been shown that adding more information (e.g. a steady state, mean value of a different unsteady state, or an entire different set of POD modes) may improve the prediction of flow with other parametric states. For a simple case of the flow passing a fixed cylinder, an orthogonal mean mode at a different Reynolds number may stabilize the POD-Galerkin model when Reynolds number is changed. For a more complicated case of the flow passing an oscillatory cylinder, a global POD-Galerkin model is first applied to handle the moving boundaries, then more information (e.g. more POD modes) is required to predicate the flow under different oscillatory frequencies. Supported by ARL.

Solar Drivers for Space Weather Operations (Invited)

NASA Astrophysics Data System (ADS)

White, S. M.

2013-12-01

Most space weather effects can be tied back to the Sun, and major research efforts are devoted to understanding the physics of the relevant phenomena with a long-term view of predicting their occurrence. This talk will focus on the current state of knowledge regarding the solar drivers of space weather, and in particular the connection between the science and operational needs. Topics covered will include the effects of solar ionizing flux on communications and navigation, radio interference, flare forecasting, the solar wind and the arrival of coronal mass ejections at Earth.

Bayesian state space models for dynamic genetic network construction across multiple tissues.

PubMed

Liang, Yulan; Kelemen, Arpad

2016-08-01

Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

Comparing the line broadened quasilinear model to Vlasov code

NASA Astrophysics Data System (ADS)

Ghantous, K.; Berk, H. L.; Gorelenkov, N. N.

2014-03-01

The Line Broadened Quasilinear (LBQ) model is revisited to study its predicted saturation level as compared with predictions of a Vlasov solver BOT [Lilley et al., Phys. Rev. Lett. 102, 195003 (2009) and M. Lilley, BOT Manual. The parametric dependencies of the model are modified to achieve more accuracy compared to the results of the Vlasov solver both in regards to a mode amplitude's time evolution to a saturated state and its final steady state amplitude in the parameter space of the model's applicability. However, the regions of stability as predicted by LBQ model and BOT are found to significantly differ from each other. The solutions of the BOT simulations are found to have a larger region of instability than the LBQ simulations.

Global Space Weather Observational Network: Challenges and China's Contribution

NASA Astrophysics Data System (ADS)

Wang, C.

2017-12-01

To understand space weather physical processes and predict space weather accurately, global space-borne and ground-based space weather observational network, making simultaneous observations from the Sun to geo-space (magnetosphere, ionosphere and atmosphere), plays an essential role. In this talk, we will present the advances of the Chinese space weather science missions, including the ASO-S (Advanced Space-borne Solar Observatory), MIT (Magnetosphere - Ionosphere- Thermosphere Coupling Exploration), and the ESA-China joint space weather science mission SMILE (Solar wind - Magnetosphere - Ionosphere Link Explore), a new mission to image the magnetosphere. Compared to satellites, ground-based monitors are cheap, convenient, and provide continuous real-time data. We will also introduce the Chinese Meridian Project (CMP), a ground-based program fully utilizing the geographic location of the Chinese landmass to monitor the geo-space environment. CMP is just one arm of a larger program that Chinese scientists are proposing to the international community. The International Meridian Circle Program (IMCP) for space weather hopes to connect chains of ground-based monitors at the longitudinal meridians 120 deg E and 60 deg W. IMCP takes advantage of the fact that these meridians already have the most monitors of any on Earth, with monitors in Russia, Australia, Brazil, the United States, Canada, and other countries. This data will greatly enhance the ability of scientists to monitor and predict the space weather worldwide.

Operational Space Weather Activities in the US

NASA Astrophysics Data System (ADS)

Berger, Thomas; Singer, Howard; Onsager, Terrance; Viereck, Rodney; Murtagh, William; Rutledge, Robert

2016-07-01

We review the current activities in the civil operational space weather forecasting enterprise of the United States. The NOAA/Space Weather Prediction Center is the nation's official source of space weather watches, warnings, and alerts, working with partners in the Air Force as well as international operational forecast services to provide predictions, data, and products on a large variety of space weather phenomena and impacts. In October 2015, the White House Office of Science and Technology Policy released the National Space Weather Strategy (NSWS) and associated Space Weather Action Plan (SWAP) that define how the nation will better forecast, mitigate, and respond to an extreme space weather event. The SWAP defines actions involving multiple federal agencies and mandates coordination and collaboration with academia, the private sector, and international bodies to, among other things, develop and sustain an operational space weather observing system; develop and deploy new models of space weather impacts to critical infrastructure systems; define new mechanisms for the transition of research models to operations and to ensure that the research community is supported for, and has access to, operational model upgrade paths; and to enhance fundamental understanding of space weather through support of research models and observations. The SWAP will guide significant aspects of space weather operational and research activities for the next decade, with opportunities to revisit the strategy in the coming years through the auspices of the National Science and Technology Council.

Characterizing Transitions Between Decadal States of the Tropical Pacific using State Space Reconstruction

NASA Astrophysics Data System (ADS)

Ramesh, N.; Cane, M. A.

2017-12-01

The complex coupled ocean-atmosphere system of the Tropical Pacific generates variability on timescales from intraseasonal to multidecadal. Pacific Decadal Variability (PDV) is among the key drivers of global climate, with effects on hydroclimate on several continents, marine ecosystems, and the rate of global mean surface temperature rise under anthropogenic greenhouse gas forcing. Predicting phase shifts in the PDV would therefore be highly useful. However, the small number of PDV phase shifts that have occurred in the observational record pose a substantial challenge to developing an understanding of the mechanisms that underlie decadal variability. In this study, we use a 100,000-year unforced simulation from an intermediate-complexity model of the Tropical Pacific region that has been shown to produce PDV comparable to that in the real world. We apply the Simplex Projection method to the NINO3 index from this model to reconstruct a shadow manifold that preserves the topology of the true attractor of this system. We find that the high- and low-variance phases of PDV emerge as a pair of regimes in a 3-dimensional state space, and that the transitions between decadal states lie in a highly predictable region of the attractor. We then use a random forest algorithm to develop a physical interpretation of the processes associated with these highly-predictable transitions. We find that transitions to low-variance states are most likely to occur approximately 2.5 years after an El Nino event, and that ocean-atmosphere variables in the southeastern Tropical Pacific play a crucial role in driving these transitions.

Imaging the dynamics of free-electron Landau states

PubMed Central

Schattschneider, P.; Schachinger, Th.; Stöger-Pollach, M.; Löffler, S.; Steiger-Thirsfeld, A.; Bliokh, K. Y.; Nori, Franco

2014-01-01

Landau levels and states of electrons in a magnetic field are fundamental quantum entities underlying the quantum Hall and related effects in condensed matter physics. However, the real-space properties and observation of Landau wave functions remain elusive. Here we report the real-space observation of Landau states and the internal rotational dynamics of free electrons. States with different quantum numbers are produced using nanometre-sized electron vortex beams, with a radius chosen to match the waist of the Landau states, in a quasi-uniform magnetic field. Scanning the beams along the propagation direction, we reconstruct the rotational dynamics of the Landau wave functions with angular frequency ~100 GHz. We observe that Landau modes with different azimuthal quantum numbers belong to three classes, which are characterized by rotations with zero, Larmor and cyclotron frequencies, respectively. This is in sharp contrast to the uniform cyclotron rotation of classical electrons, and in perfect agreement with recent theoretical predictions. PMID:25105563

Tunable Optical Filters for Space Exploration

NASA Technical Reports Server (NTRS)

Crandall, Charles; Clark, Natalie; Davis, Patricia P.

2007-01-01

Spectrally tunable liquid crystal filters provide numerous advantages and several challenges in space applications. We discuss the tradeoffs in design elements for tunable liquid crystal birefringent filters with special consideration required for space exploration applications. In this paper we present a summary of our development of tunable filters for NASA space exploration. In particular we discuss the application of tunable liquid crystals in guidance navigation and control in space exploration programs. We present a summary of design considerations for improving speed, field of view, transmission of liquid crystal tunable filters for space exploration. In conclusion, the current state of the art of several NASA LaRC assembled filters is presented and their performance compared to the predicted spectra using our PolarTools modeling software.

Orbital State Uncertainty Realism

NASA Astrophysics Data System (ADS)

Horwood, J.; Poore, A. B.

2012-09-01

Fundamental to the success of the space situational awareness (SSA) mission is the rigorous inclusion of uncertainty in the space surveillance network. The *proper characterization of uncertainty* in the orbital state of a space object is a common requirement to many SSA functions including tracking and data association, resolution of uncorrelated tracks (UCTs), conjunction analysis and probability of collision, sensor resource management, and anomaly detection. While tracking environments, such as air and missile defense, make extensive use of Gaussian and local linearity assumptions within algorithms for uncertainty management, space surveillance is inherently different due to long time gaps between updates, high misdetection rates, nonlinear and non-conservative dynamics, and non-Gaussian phenomena. The latter implies that "covariance realism" is not always sufficient. SSA also requires "uncertainty realism"; the proper characterization of both the state and covariance and all non-zero higher-order cumulants. In other words, a proper characterization of a space object's full state *probability density function (PDF)* is required. In order to provide a more statistically rigorous treatment of uncertainty in the space surveillance tracking environment and to better support the aforementioned SSA functions, a new class of multivariate PDFs are formulated which more accurately characterize the uncertainty of a space object's state or orbit. The new distribution contains a parameter set controlling the higher-order cumulants which gives the level sets a distinctive "banana" or "boomerang" shape and degenerates to a Gaussian in a suitable limit. Using the new class of PDFs within the general Bayesian nonlinear filter, the resulting filter prediction step (i.e., uncertainty propagation) is shown to have the *same computational cost as the traditional unscented Kalman filter* with the former able to maintain a proper characterization of the uncertainty for up to *ten times as long* as the latter. The filter correction step also furnishes a statistically rigorous *prediction error* which appears in the likelihood ratios for scoring the association of one report or observation to another. Thus, the new filter can be used to support multi-target tracking within a general multiple hypothesis tracking framework. Additionally, the new distribution admits a distance metric which extends the classical Mahalanobis distance (chi^2 statistic). This metric provides a test for statistical significance and facilitates single-frame data association methods with the potential to easily extend the covariance-based track association algorithm of Hill, Sabol, and Alfriend. The filtering, data fusion, and association methods using the new class of orbital state PDFs are shown to be mathematically tractable and operationally viable.

Attracting Dynamics of Frontal Cortex Ensembles during Memory-Guided Decision-Making

PubMed Central

Seamans, Jeremy K.; Durstewitz, Daniel

2011-01-01

A common theoretical view is that attractor-like properties of neuronal dynamics underlie cognitive processing. However, although often proposed theoretically, direct experimental support for the convergence of neural activity to stable population patterns as a signature of attracting states has been sparse so far, especially in higher cortical areas. Combining state space reconstruction theorems and statistical learning techniques, we were able to resolve details of anterior cingulate cortex (ACC) multiple single-unit activity (MSUA) ensemble dynamics during a higher cognitive task which were not accessible previously. The approach worked by constructing high-dimensional state spaces from delays of the original single-unit firing rate variables and the interactions among them, which were then statistically analyzed using kernel methods. We observed cognitive-epoch-specific neural ensemble states in ACC which were stable across many trials (in the sense of being predictive) and depended on behavioral performance. More interestingly, attracting properties of these cognitively defined ensemble states became apparent in high-dimensional expansions of the MSUA spaces due to a proper unfolding of the neural activity flow, with properties common across different animals. These results therefore suggest that ACC networks may process different subcomponents of higher cognitive tasks by transiting among different attracting states. PMID:21625577

Using Clustering to Establish Climate Regimes from PCM Output

NASA Technical Reports Server (NTRS)

Oglesby, Robert; Arnold, James E. (Technical Monitor); Hoffman, Forrest; Hargrove, W. W.; Erickson, D.

2002-01-01

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Controls on SOC across space and time: Models with different acclimation schemes make similar spatial predictions but divergent warming predictions

NASA Astrophysics Data System (ADS)

Abramoff, R. Z.; Torn, M. S.; Georgiou, K.; Tang, J.; Riley, W. J.

2017-12-01

Researchers use spatial gradients to estimate long-term ecosystem responses to perturbations. This approach is commonly applied to soil organic carbon (SOC) stocks which change slowly but store the majority of terrestrial carbon. Climate warming may reduce SOC stocks if higher temperatures increase decomposition rates. Yet, it is uncertain how vulnerable SOC is to warming, and whether the same factors - such as organo-mineral associations, climate, or plant inputs - determine SOC stocks across space and time. In order to test the "space for time" concept, we developed two versions of the Substrate-Mineral-Microbe Soil (SuMMS) model - one with microbial temperature acclimation and one without - to analyze observed SOC stocks at 24 sites spanning a wide range of soil types and climate. Both model predictions of SOC were strongly correlated with observations (R2 > 0.9), because mineral sorption capacity was the dominant control over steady-state SOC stock as determined by a Random Forest model. However, the two model versions made fundamentally different predictions of the change in SOC following 5°C soil warming from 2016 to 2100 because the initial mean annual temperature (MAT) was the dominant control over the SOC response. The model with microbial acclimation predicted that SOC would decline 10% at all sites along the transect, while the model with no acclimation predicted large surface SOC losses at high latitude sites and SOC gains at low latitude sites where microbial exoenzymes were already at or near their temperature optimum. These simulations suggest that gradient studies cannot be used to infer site-level responses to warming, because the dominant controls on SOC at steady state (i.e., mineral sorption capacity) are different than the dominant controls on the SOC response to a warming perturbation (i.e., initial MAT, capacity for acclimation).

System definition study of deployable, non-metallic space structures

NASA Technical Reports Server (NTRS)

Stimler, F. J.

1984-01-01

The state of the art for nonmetallic materials and fabrication techniques suitable for future space structures are summarized. Typical subsystems and systems of interest to the space community that are reviewed include: (1) inflatable/rigidized space hangar; (2) flexible/storable acoustic barrier; (3) deployable fabric bulkhead in a space habitat; (4) extendible tunnel for soft docking; (5) deployable space recovery/re-entry systems for personnel or materials; (6) a manned habitat for a space station; (7) storage enclosures external to the space station habitat; (8) attachable work stations; and (9) safe haven structures. Performance parameters examined include micrometeoroid protection; leakage rate prediction and control; rigidization of flexible structures in the space environment; flammability and offgassing; lifetime for nonmetallic materials; crack propagation prevention; and the effects of atomic oxygen and space debris. An expandable airlock for shuttle flight experiments and potential tethered experiments from shuttle are discussed.

Primary Dendrite Arm Spacing and Trunk Diameter in Al-7-Weight-Percentage Si Alloy Directionally Solidified Aboard the International Space Station

NASA Technical Reports Server (NTRS)

Ghods, M.; Tewari, S. N.; Lauer, M.; Poirier, D. R.; Grugel, R. N.

2016-01-01

Under a NASA-ESA collaborative research project, three Al-7-weight-percentage Si samples (MICAST-6, MICAST-7 and MICAST 2-12) were directionally solidified aboard the International Space Station to determine the effect of mitigating convection on the primary dendrite array. The samples were approximately 25 centimeters in length with a diameter of 7.8 millimeter-diameter cylinders that were machined from [100] oriented terrestrially grown dendritic Al-7Si samples and inserted into alumina ampoules within the Sample Cartridge Assembly (SCA) inserts of the Low Gradient Furnace (LGF). The feed rods were partially remelted in space and directionally solidified to effect the [100] dendrite-orientation. MICAST-6 was grown at 5 microns per second for 3.75 centimeters and then at 50 microns per second for its remaining 11.2 centimeters of its length. MICAST-7 was grown at 20 microns per second for 8.5 centimeters and then at 10 microns per second for 9 centimeters of its remaining length. MICAST2-12 was grown at 40 microns per second for 11 centimeters. The thermal gradient at the liquidus temperature varied from 22 to 14 degrees Kelvin per centimeter during growth of MICAST-6, from 26 to 24 degrees Kelvin per centimeter for MICAST-7 and from 33 to 31 degrees Kelvin per centimeter for MICAST2-12. Microstructures on the transverse sections along the sample length were analyzed to determine nearest-neighbor spacing of the primary dendrite arms and trunk diameters of the primary dendrite-arrays. This was done along the lengths where steady-state growth prevailed and also during the transients associated with the speed-changes. The observed nearest-neighbor spacings during steady-state growth of the MICAST samples show a very good agreement with predictions from the Hunt-Lu primary spacing model for diffusion controlled growth. The observed primary dendrite trunk diameters during steady-state growth of these samples also agree with predictions from a coarsening-based model. The radial macrosegregation and "steepling" caused by thermosolutal convection during terrestrial growth of the Al-7Si was not observed in the space-grown MICAST samples.

Bayesian Framework Approach for Prognostic Studies in Electrolytic Capacitor under Thermal Overstress Conditions

DTIC Science & Technology

2012-09-01

make end of life ( EOL ) and remaining useful life (RUL) estimations. Model-based prognostics approaches perform these tasks with the help of first...in parameters Degradation Modeling Parameter estimation Prediction Thermal / Electrical Stress Experimental Data State Space model RUL EOL ...distribution at given single time point kP , and use this for multi-step predictions to EOL . There are several methods which exits for selecting the sigma

Internal state variable approach for predicting stiffness reductions in fibrous laminated composites with matrix cracks

NASA Technical Reports Server (NTRS)

Lee, Jong-Won; Allen, D. H.; Harris, C. E.

1989-01-01

A mathematical model utilizing the internal state variable concept is proposed for predicting the upper bound of the reduced axial stiffnesses in cross-ply laminates with matrix cracks. The axial crack opening displacement is explicitly expressed in terms of the observable axial strain and the undamaged material properties. A crack parameter representing the effect of matrix cracks on the observable axial Young's modulus is calculated for glass/epoxy and graphite/epoxy material systems. The results show that the matrix crack opening displacement and the effective Young's modulus depend not on the crack length, but on its ratio to the crack spacing.

Models and applications for space weather forecasting and analysis at the Community Coordinated Modeling Center.

NASA Astrophysics Data System (ADS)

Kuznetsova, Maria

The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) was established at the dawn of the new millennium as a long-term flexible solution to the problem of transition of progress in space environment modeling to operational space weather forecasting. CCMC hosts an expanding collection of state-of-the-art space weather models developed by the international space science community. Over the years the CCMC acquired the unique experience in preparing complex models and model chains for operational environment and developing and maintaining custom displays and powerful web-based systems and tools ready to be used by researchers, space weather service providers and decision makers. In support of space weather needs of NASA users CCMC is developing highly-tailored applications and services that target specific orbits or locations in space and partnering with NASA mission specialists on linking CCMC space environment modeling with impacts on biological and technological systems in space. Confidence assessment of model predictions is an essential element of space environment modeling. CCMC facilitates interaction between model owners and users in defining physical parameters and metrics formats relevant to specific applications and leads community efforts to quantify models ability to simulate and predict space environment events. Interactive on-line model validation systems developed at CCMC make validation a seamless part of model development circle. The talk will showcase innovative solutions for space weather research, validation, anomaly analysis and forecasting and review on-going community-wide model validation initiatives enabled by CCMC applications.

Evaluating a fish monitoring protocol using state-space hierarchical models

USGS Publications Warehouse

Russell, Robin E.; Schmetterling, David A.; Guy, Chris S.; Shepard, Bradley B.; McFarland, Robert; Skaar, Donald

2012-01-01

Using data collected from three river reaches in Montana, we evaluated our ability to detect population trends and predict fish future fish abundance. Data were collected as part of a long-term monitoring program conducted by Montana Fish, Wildlife and Parks to primarily estimate rainbow (Oncorhynchus mykiss) and brown trout (Salmo trutta) abundance in numerous rivers across Montana. We used a hierarchical Bayesian mark-recapture model to estimate fish abundance over time in each of the three river reaches. We then fit a state-space Gompertz model to estimate current trends and future fish populations. Density dependent effects were detected in 1 of the 6 fish populations. Predictions of future fish populations displayed wide credible intervals. Our simulations indicated that given the observed variation in the abundance estimates, the probability of detecting a 30% decline in fish populations over a five-year period was less than 50%. We recommend a monitoring program that is closely tied to management objectives and reflects the precision necessary to make informed management decisions.

Analytical Tools for Space Suit Design

NASA Technical Reports Server (NTRS)

Aitchison, Lindsay

2011-01-01

As indicated by the implementation of multiple small project teams within the agency, NASA is adopting a lean approach to hardware development that emphasizes quick product realization and rapid response to shifting program and agency goals. Over the past two decades, space suit design has been evolutionary in approach with emphasis on building prototypes then testing with the largest practical range of subjects possible. The results of these efforts show continuous improvement but make scaled design and performance predictions almost impossible with limited budgets and little time. Thus, in an effort to start changing the way NASA approaches space suit design and analysis, the Advanced Space Suit group has initiated the development of an integrated design and analysis tool. It is a multi-year-if not decadal-development effort that, when fully implemented, is envisioned to generate analysis of any given space suit architecture or, conversely, predictions of ideal space suit architectures given specific mission parameters. The master tool will exchange information to and from a set of five sub-tool groups in order to generate the desired output. The basic functions of each sub-tool group, the initial relationships between the sub-tools, and a comparison to state of the art software and tools are discussed.

Design of a final approach spacing tool for TRACON air traffic control

NASA Technical Reports Server (NTRS)

Davis, Thomas J.; Erzberger, Heinz; Bergeron, Hugh

1989-01-01

This paper describes an automation tool that assists air traffic controllers in the Terminal Radar Approach Control (TRACON) Facilities in providing safe and efficient sequencing and spacing of arrival traffic. The automation tool, referred to as the Final Approach Spacing Tool (FAST), allows the controller to interactively choose various levels of automation and advisory information ranging from predicted time errors to speed and heading advisories for controlling time error. FAST also uses a timeline to display current scheduling and sequencing information for all aircraft in the TRACON airspace. FAST combines accurate predictive algorithms and state-of-the-art mouse and graphical interface technology to present advisory information to the controller. Furthermore, FAST exchanges various types of traffic information and communicates with automation tools being developed for the Air Route Traffic Control Center. Thus it is part of an integrated traffic management system for arrival traffic at major terminal areas.

Cold flow testing of the Space Shuttle Main Engine high pressure fuel turbine model

NASA Technical Reports Server (NTRS)

Hudson, Susan T.; Gaddis, Stephen W.; Johnson, P. D.; Boynton, James L.

1991-01-01

In order to experimentally determine the performance of the Space Shuttle Main Engine (SSME) High Pressure Fuel Turbopump (HPFTP) turbine, a 'cold' air flow turbine test program was established at NASA's Marshall Space Flight Center. As part of this test program, a baseline test of Rocketdyne's HPFTP turbine has been completed. The turbine performance and turbine diagnostics such as airfoil surface static pressure distributions, static pressure drops through the turbine, and exit swirl angles were investigated at the turbine design point, over its operating range, and at extreme off-design points. The data was compared to pretest predictions with good results. The test data has been used to improve meanline prediction codes and is now being used to validate various three-dimensional codes. The data will also be scaled to engine conditions and used to improve the SSME steady-state performance model.

The SupraThermal Ion Monitor for space weather predictions.

PubMed

Allegrini, F; Desai, M I; Livi, S; McComas, D J; Ho, G C

2014-05-01

Measurement of suprathermal energy ions in the heliosphere has always been challenging because (1) these ions are situated in the energy regime only a few times higher than the solar wind plasma, where intensities are orders of magnitude higher and (2) ion energies are below or close to the threshold of state-of-art solid-state detectors. Suprathermal ions accelerated at coronal mass ejection-driven shocks propagate out ahead of the shocks. These shocks can cause geomagnetic storms in the Earth's magnetosphere that can affect spacecraft and ground-based power and communication systems. An instrument with sufficient sensitivity to measure these ions can be used to predict the arrival of the shocks and provide an advance warning for potentially geo-effective space weather. In this paper, we present a novel energy analyzer concept, the Suprathermal Ion Monitor (STIM) that is designed to measure suprathermal ions with high sensitivity. We show results from a laboratory prototype and demonstrate the feasibility of the concept. A list of key performances is given, as well as a discussion of various possible detectors at the back end. STIM is an ideal candidate for a future space weather monitor in orbit upstream of the near-earth environment, for example, around L1. A scaled-down version is suitable for a CubeSat mission. Such a platform allows proofing the concept and demonstrating its performance in the space environment.

Topological superconductivity in monolayer transition metal dichalcogenides.

PubMed

Hsu, Yi-Ting; Vaezi, Abolhassan; Fischer, Mark H; Kim, Eun-Ah

2017-04-11

Theoretically, it has been known that breaking spin degeneracy and effectively realizing spinless fermions is a promising path to topological superconductors. Yet, topological superconductors are rare to date. Here we propose to realize spinless fermions by splitting the spin degeneracy in momentum space. Specifically, we identify monolayer hole-doped transition metal dichalcogenide (TMD)s as candidates for topological superconductors out of such momentum-space-split spinless fermions. Although electron-doped TMDs have recently been found superconducting, the observed superconductivity is unlikely topological because of the near spin degeneracy. Meanwhile, hole-doped TMDs with momentum-space-split spinless fermions remain unexplored. Employing a renormalization group analysis, we propose that the unusual spin-valley locking in hole-doped TMDs together with repulsive interactions selectively favours two topological superconducting states: interpocket paired state with Chern number 2 and intrapocket paired state with finite pair momentum. A confirmation of our predictions will open up possibilities for manipulating topological superconductors on the device-friendly platform of monolayer TMDs.

Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

NASA Astrophysics Data System (ADS)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

Large numbers hypothesis. IV - The cosmological constant and quantum physics

NASA Technical Reports Server (NTRS)

Adams, P. J.

1983-01-01

In standard physics quantum field theory is based on a flat vacuum space-time. This quantum field theory predicts a nonzero cosmological constant. Hence the gravitational field equations do not admit a flat vacuum space-time. This dilemma is resolved using the units covariant gravitational field equations. This paper shows that the field equations admit a flat vacuum space-time with nonzero cosmological constant if and only if the canonical LNH is valid. This allows an interpretation of the LNH phenomena in terms of a time-dependent vacuum state. If this is correct then the cosmological constant must be positive.

Why NASA and the Space Electronics Community Cares About Cyclotrons

NASA Technical Reports Server (NTRS)

LaBel, Kenneth A.

2017-01-01

NASA and the space community are faced with the harsh reality of operating electronic systems in the space radiation environment. Systems need to work reliably (as expected for as long as expected) and be available during critical operations such as docking or firing a thruster. This talk will provide a snapshot of the import of ground-based research on the radiation performance of electronics. Discussion topics include: 1) The space radiation environment hazard, 2) Radiation effects on electronics, 3) Simulation of effects with cyclotrons (and other sources), 4) Risk prediction for space missions, and, 5) Real-life examples of both ground-based testing and space-based anomalies and electronics performance. The talk will conclude with a discussion of the current state of radiation facilities in North America for ground-based electronics testing.

Specification of the Surface Charging Environment with SHIELDS

NASA Astrophysics Data System (ADS)

Jordanova, V.; Delzanno, G. L.; Henderson, M. G.; Godinez, H. C.; Jeffery, C. A.; Lawrence, E. C.; Meierbachtol, C.; Moulton, J. D.; Vernon, L.; Woodroffe, J. R.; Brito, T.; Toth, G.; Welling, D. T.; Yu, Y.; Albert, J.; Birn, J.; Borovsky, J.; Denton, M.; Horne, R. B.; Lemon, C.; Markidis, S.; Thomsen, M. F.; Young, S. L.

2016-12-01

Predicting variations in the near-Earth space environment that can lead to spacecraft damage and failure, i.e. "space weather", remains a big space physics challenge. A recently funded project through the Los Alamos National Laboratory (LANL) Directed Research and Development (LDRD) program aims at developing a new capability to understand, model, and predict Space Hazards Induced near Earth by Large Dynamic Storms, the SHIELDS framework. The project goals are to understand the dynamics of the surface charging environment (SCE), the hot (keV) electrons representing the source and seed populations for the radiation belts, on both macro- and microscale. Important physics questions related to rapid particle injection and acceleration associated with magnetospheric storms and substorms as well as plasma waves are investigated. These challenging problems are addressed using a team of world-class experts in the fields of space science and computational plasma physics, and state-of-the-art models and computational facilities. In addition to physics-based models (like RAM-SCB, BATS-R-US, and iPIC3D), new data assimilation techniques employing data from LANL instruments on the Van Allen Probes and geosynchronous satellites are developed. Simulations with the SHIELDS framework of the near-Earth space environment where operational satellites reside are presented. Further model development and the organization of a "Spacecraft Charging Environment Challenge" by the SHIELDS project at LANL in collaboration with the NSF Geospace Environment Modeling (GEM) Workshop and the multi-agency Community Coordinated Modeling Center (CCMC) to assess the accuracy of SCE predictions are discussed.

Cortical connective field estimates from resting state fMRI activity.

PubMed

Gravel, Nicolás; Harvey, Ben; Nordhjem, Barbara; Haak, Koen V; Dumoulin, Serge O; Renken, Remco; Curčić-Blake, Branislava; Cornelissen, Frans W

2014-01-01

One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that-despite some variability in CF estimates between RS scans-neural properties such as CF maps and CF size can be derived from resting state data.

A Nonlinear Dynamical Systems based Model for Stochastic Simulation of Streamflow

NASA Astrophysics Data System (ADS)

Erkyihun, S. T.; Rajagopalan, B.; Zagona, E. A.

2014-12-01

Traditional time series methods model the evolution of the underlying process as a linear or nonlinear function of the autocorrelation. These methods capture the distributional statistics but are incapable of providing insights into the dynamics of the process, the potential regimes, and predictability. This work develops a nonlinear dynamical model for stochastic simulation of streamflows. In this, first a wavelet spectral analysis is employed on the flow series to isolate dominant orthogonal quasi periodic timeseries components. The periodic bands are added denoting the 'signal' component of the time series and the residual being the 'noise' component. Next, the underlying nonlinear dynamics of this combined band time series is recovered. For this the univariate time series is embedded in a d-dimensional space with an appropriate lag T to recover the state space in which the dynamics unfolds. Predictability is assessed by quantifying the divergence of trajectories in the state space with time, as Lyapunov exponents. The nonlinear dynamics in conjunction with a K-nearest neighbor time resampling is used to simulate the combined band, to which the noise component is added to simulate the timeseries. We demonstrate this method by applying it to the data at Lees Ferry that comprises of both the paleo reconstructed and naturalized historic annual flow spanning 1490-2010. We identify interesting dynamics of the signal in the flow series and epochal behavior of predictability. These will be of immense use for water resources planning and management.

Oscillators that sync and swarm.

PubMed

O'Keeffe, Kevin P; Hong, Hyunsuk; Strogatz, Steven H

2017-11-15

Synchronization occurs in many natural and technological systems, from cardiac pacemaker cells to coupled lasers. In the synchronized state, the individual cells or lasers coordinate the timing of their oscillations, but they do not move through space. A complementary form of self-organization occurs among swarming insects, flocking birds, or schooling fish; now the individuals move through space, but without conspicuously altering their internal states. Here we explore systems in which both synchronization and swarming occur together. Specifically, we consider oscillators whose phase dynamics and spatial dynamics are coupled. We call them swarmalators, to highlight their dual character. A case study of a generalized Kuramoto model predicts five collective states as possible long-term modes of organization. These states may be observable in groups of sperm, Japanese tree frogs, colloidal suspensions of magnetic particles, and other biological and physical systems in which self-assembly and synchronization interact.

Uncertainty Quantification in Remaining Useful Life of Aerospace Components using State Space Models and Inverse FORM

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Goebel, Kai

2013-01-01

This paper investigates the use of the inverse first-order reliability method (inverse- FORM) to quantify the uncertainty in the remaining useful life (RUL) of aerospace components. The prediction of remaining useful life is an integral part of system health prognosis, and directly helps in online health monitoring and decision-making. However, the prediction of remaining useful life is affected by several sources of uncertainty, and therefore it is necessary to quantify the uncertainty in the remaining useful life prediction. While system parameter uncertainty and physical variability can be easily included in inverse-FORM, this paper extends the methodology to include: (1) future loading uncertainty, (2) process noise; and (3) uncertainty in the state estimate. The inverse-FORM method has been used in this paper to (1) quickly obtain probability bounds on the remaining useful life prediction; and (2) calculate the entire probability distribution of remaining useful life prediction, and the results are verified against Monte Carlo sampling. The proposed methodology is illustrated using a numerical example.

Overview of the SHIELDS Project at LANL

NASA Astrophysics Data System (ADS)

Jordanova, V.; Delzanno, G. L.; Henderson, M. G.; Godinez, H. C.; Jeffery, C. A.; Lawrence, E. C.; Meierbachtol, C.; Moulton, D.; Vernon, L.; Woodroffe, J. R.; Toth, G.; Welling, D. T.; Yu, Y.; Birn, J.; Thomsen, M. F.; Borovsky, J.; Denton, M.; Albert, J.; Horne, R. B.; Lemon, C. L.; Markidis, S.; Young, S. L.

2015-12-01

The near-Earth space environment is a highly dynamic and coupled system through a complex set of physical processes over a large range of scales, which responds nonlinearly to driving by the time-varying solar wind. Predicting variations in this environment that can affect technologies in space and on Earth, i.e. "space weather", remains a big space physics challenge. We present a recently funded project through the Los Alamos National Laboratory (LANL) Directed Research and Development (LDRD) program that is developing a new capability to understand, model, and predict Space Hazards Induced near Earth by Large Dynamic Storms, the SHIELDS framework. The project goals are to specify the dynamics of the hot (keV) particles (the seed population for the radiation belts) on both macro- and micro-scale, including important physics of rapid particle injection and acceleration associated with magnetospheric storms/substorms and plasma waves. This challenging problem is addressed using a team of world-class experts in the fields of space science and computational plasma physics and state-of-the-art models and computational facilities. New data assimilation techniques employing data from LANL instruments on the Van Allen Probes and geosynchronous satellites are developed in addition to physics-based models. This research will provide a framework for understanding of key radiation belt drivers that may accelerate particles to relativistic energies and lead to spacecraft damage and failure. The ability to reliably distinguish between various modes of failure is critically important in anomaly resolution and forensics. SHIELDS will enhance our capability to accurately specify and predict the near-Earth space environment where operational satellites reside.

The scientific challenges to forecasting and nowcasting the magnetospheric response to space weather (Invited)

NASA Astrophysics Data System (ADS)

Hesse, M.; Kuznetsova, M. M.; Birn, J.; Pulkkinen, A. A.

2013-12-01

Space weather is different from terrestrial weather in an essential way. Terrestrial weather has benefitted from a long history of research, which has led to a deep and detailed level of understanding. In comparison, space weather is scientifically in its infancy. Many key processes in the causal chains from processes on the Sun to space weather effects in various locations in the heliosphere remain either poorly understood or not understood at all. Space weather is therefore, and will remain in the foreseeable future, primarily a research field. Extensive further research efforts are needed before we can reasonably expect the precision and fidelity of weather forecasts. For space weather within the Earth's magnetosphere, the coupling between solar wind and magnetosphere is of crucial importance. While past research has provided answers, often on qualitative levels, to some of the most fundamental questions, answers to some of the latter and the ability to predict quantitatively remain elusive. This presentation will provide an overview of pertinent aspects of solar wind-magnetospheric coupling, its importance for space weather near the Earth, and it will analyze the state of our ability to describe and predict its efficiency. It will conclude with a discussion of research activities, which are aimed at improving our ability to quantitatively forecast coupling processes.

Prediction and verification of creep behavior in metallic materials and components, for the space shuttle thermal protection system. Volume 1, phase 1: Cyclic materials creep predictions

NASA Technical Reports Server (NTRS)

Davis, J. W.; Cramer, B. A.

1974-01-01

Cyclic creep response was investigated and design methods applicable to thermal protection system structures were developed. The steady-state (constant temperature and load) and cyclic creep response characteristics of four alloys were studied. Steady-state creep data were gathered through a literature survey to establish reference data bases. These data bases were used to develop empirical equations describing creep as a function of time, temperature, and stress and as a basis of comparison for test data. Steady-state creep tests and tensile cyclic tests were conducted. The following factors were investigated: material thickness and rolling direction; material cyclic creep response under varying loads and temperatures; constant stress and temperature cycles representing flight conditions; changing stresses present in a creeping beam as a result of stress redistribution; and complex stress and temperature profiles representative of space shuttle orbiter trajectories. A computer program was written, applying creep hardening theories and empirical equations for creep, to aid in analysis of test data. Results are considered applicable to a variety of structures which are cyclicly exposed to creep producing thermal environments.

Use of Crystal Structure Informatics for Defining the Conformational Space Needed for Predicting Crystal Structures of Pharmaceutical Molecules.

PubMed

Iuzzolino, Luca; Reilly, Anthony M; McCabe, Patrick; Price, Sarah L

2017-10-10

Determining the range of conformations that a flexible pharmaceutical-like molecule could plausibly adopt in a crystal structure is a key to successful crystal structure prediction (CSP) studies. We aim to use conformational information from the crystal structures in the Cambridge Structural Database (CSD) to facilitate this task. The conformations produced by the CSD Conformer Generator are reduced in number by considering the underlying rotamer distributions, an analysis of changes in molecular shape, and a minimal number of molecular ab initio calculations. This method is tested for five pharmaceutical-like molecules where an extensive CSP study has already been performed. The CSD informatics-derived set of crystal structure searches generates almost all the low-energy crystal structures previously found, including all experimental structures. The workflow effectively combines information on individual torsion angles and then eliminates the combinations that are too high in energy to be found in the solid state, reducing the resources needed to cover the solid-state conformational space of a molecule. This provides insights into how the low-energy solid-state and isolated-molecule conformations are related to the properties of the individual flexible torsion angles.

Real-space mapping of topological invariants using artificial neural networks

NASA Astrophysics Data System (ADS)

Carvalho, D.; García-Martínez, N. A.; Lado, J. L.; Fernández-Rossier, J.

2018-03-01

Topological invariants allow one to characterize Hamiltonians, predicting the existence of topologically protected in-gap modes. Those invariants can be computed by tracing the evolution of the occupied wave functions under twisted boundary conditions. However, those procedures do not allow one to calculate a topological invariant by evaluating the system locally, and thus require information about the wave functions in the whole system. Here we show that artificial neural networks can be trained to identify the topological order by evaluating a local projection of the density matrix. We demonstrate this for two different models, a one-dimensional topological superconductor and a two-dimensional quantum anomalous Hall state, both with spatially modulated parameters. Our neural network correctly identifies the different topological domains in real space, predicting the location of in-gap states. By combining a neural network with a calculation of the electronic states that uses the kernel polynomial method, we show that the local evaluation of the invariant can be carried out by evaluating a local quantity, in particular for systems without translational symmetry consisting of tens of thousands of atoms. Our results show that supervised learning is an efficient methodology to characterize the local topology of a system.

Theoretical derivation of laser-dressed atomic states by using a fractal space

NASA Astrophysics Data System (ADS)

Duchateau, Guillaume

2018-05-01

The derivation of approximate wave functions for an electron submitted to both a Coulomb and a time-dependent laser electric fields, the so-called Coulomb-Volkov (CV) state, is addressed. Despite its derivation for continuum states does not exhibit any particular problem within the framework of the standard theory of quantum mechanics (QM), difficulties arise when considering an initially bound atomic state. Indeed the natural way of translating the unperturbed momentum by the laser vector potential is no longer possible since a bound state does not exhibit a plane wave form explicitly including a momentum. The use of a fractal space permits to naturally define a momentum for a bound wave function. Within this framework, it is shown how the derivation of laser-dressed bound states can be performed. Based on a generalized eikonal approach, a new expression for the laser-dressed states is also derived, fully symmetric relative to the continuum or bound nature of the initial unperturbed wave function. It includes an additional crossed term in the Volkov phase which was not obtained within the standard theory of quantum mechanics. The derivations within this fractal framework have highlighted other possible ways to derive approximate laser-dressed states in QM. After comparing the various obtained wave functions, an application to the prediction of the ionization probability of hydrogen targets by attosecond XUV pulses within the sudden approximation is provided. This approach allows to make predictions in various regimes depending on the laser intensity, going from the non-resonant multiphoton absorption to tunneling and barrier-suppression ionization.

Benefits of Applying Predictive Intelligence to the Space Situational Awareness (SSA) Mission

NASA Astrophysics Data System (ADS)

Lane, B.; Mann, B.; Millard, C.

Recent events have heightened the interest in providing improved Space Situational Awareness (SSA) to the warfighter using novel techniques that are affordable and effective. The current Space Surveillance Network (SSN) detects, tracks, catalogs and identifies artificial objects orbiting earth and provides information on Resident Space Objects (RSO) as well as new foreign launch (NFL) satellites. The reactive nature of the SSN provides little to no warning on changes to the expected states of these RSOs or NFLs. This paper will detail the use of the historical data collected on RSOs to characterize what their steady state is, proactively help identify when changes or anomalies have occurred using a pattern-of-like activity based intelligence approach, and apply dynamic, adaptive mission planning to the observables that lead up to a NFL. Multiple hypotheses will be carried along with the intent or the changes to the steady state to assist the SSN in tasking the various sensors in the network to collect the relevant data needed to help prune the number of hypotheses by assigning likelihood to each of those activities. Depending on the hypothesis and thresholds set, these likelihoods will then be used in turn to alert the SSN operator with changes to the steady state, prioritize additional data collections, and provide a watch list of likely next activities.

Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) for Conformational Space Search of Peptide and Miniprotein

PubMed Central

Hao, Ge-Fei; Xu, Wei-Fang; Yang, Sheng-Gang; Yang, Guang-Fu

2015-01-01

Protein and peptide structure predictions are of paramount importance for understanding their functions, as well as the interactions with other molecules. However, the use of molecular simulation techniques to directly predict the peptide structure from the primary amino acid sequence is always hindered by the rough topology of the conformational space and the limited simulation time scale. We developed here a new strategy, named Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) to identify the native states of a peptide and miniprotein. A cluster of near native structures could be obtained by using the MSA-MD method, which turned out to be significantly more efficient in reaching the native structure compared to continuous MD and conventional SA-MD simulation. PMID:26492886

Realtime Knowledge Management (RKM): From an International Space Station (ISS) Point of View

NASA Technical Reports Server (NTRS)

Robinson, Peter I.; McDermott, William; Alena, Richard L.

2004-01-01

We are developing automated methods to provide realtime access to spacecraft domain knowledge relevant a spacecraft's current operational state. The method is based upon analyzing state-transition signatures in the telemetry stream. A key insight is that documentation relevant to a specific failure mode or operational state is related to the structure and function of spacecraft systems. This means that diagnostic dependency and state models can provide a roadmap for effective documentation navigation and presentation. Diagnostic models consume the telemetry and derive a high-level state description of the spacecraft. Each potential spacecraft state description is matched against the predictions of models that were developed from information found in the pages and sections in the relevant International Space Station (ISS) documentation and reference materials. By annotating each model fragment with the domain knowledge sources from which it was derived we can develop a system that automatically selects those documents representing the domain knowledge encapsulated by the models that compute the current spacecraft state. In this manner, when the spacecraft state changes, the relevant documentation context and presentation will also change.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

NASA Astrophysics Data System (ADS)

Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

2009-12-01

Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

Towards a Global Hub and a Network for Collaborative Advancing of Space Weather Predictive Capabilities.

NASA Astrophysics Data System (ADS)

Kuznetsova, M. M.; Heynderickz, D.; Grande, M.; Opgenoorth, H. J.

2017-12-01

The COSPAR/ILWS roadmap on space weather published in 2015 (Advances in Space Research, 2015: DOI: 10.1016/j.asr.2015.03.023) prioritizes steps to be taken to advance understanding of space environment phenomena and to improve space weather forecasting capabilities. General recommendations include development of a comprehensive space environment specification, assessment of the state of the field on a 5-yr basis, standardization of meta-data and product metrics. To facilitate progress towards roadmap goals there is a need for a global hub for collaborative space weather capabilities assessment and development that brings together research, engineering, operational, educational, and end-user communities. The COSPAR Panel on Space Weather is aiming to build upon past progress and to facilitate coordination of established and new international space weather research and development initiatives. Keys to the success include creating flexible, collaborative, inclusive environment and engaging motivated groups and individuals committed to active participation in international multi-disciplinary teams focused on topics addressing emerging needs and challenges in the rapidly growing field of space weather. Near term focus includes comprehensive assessment of the state of the field and establishing an internationally recognized process to quantify and track progress over time, development of a global network of distributed web-based resources and interconnected interactive services required for space weather research, analysis, forecasting and education.

Configuration interaction singles natural orbitals: An orbital basis for an efficient and size intensive multireference description of electronic excited states

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

Shu, Yinan; Levine, Benjamin G., E-mail: levine@chemistry.msu.edu; Hohenstein, Edward G.

2015-01-14

Multireference quantum chemical methods, such as the complete active space self-consistent field (CASSCF) method, have long been the state of the art for computing regions of potential energy surfaces (PESs) where complex, multiconfigurational wavefunctions are required, such as near conical intersections. Herein, we present a computationally efficient alternative to the widely used CASSCF method based on a complete active space configuration interaction (CASCI) expansion built from the state-averaged natural orbitals of configuration interaction singles calculations (CISNOs). This CISNO-CASCI approach is shown to predict vertical excitation energies of molecules with closed-shell ground states similar to those predicted by state averaged (SA)-CASSCFmore » in many cases and to provide an excellent reference for a perturbative treatment of dynamic electron correlation. Absolute energies computed at the CISNO-CASCI level are found to be variationally superior, on average, to other CASCI methods. Unlike SA-CASSCF, CISNO-CASCI provides vertical excitation energies which are both size intensive and size consistent, thus suggesting that CISNO-CASCI would be preferable to SA-CASSCF for the study of systems with multiple excitable centers. The fact that SA-CASSCF and some other CASCI methods do not provide a size intensive/consistent description of excited states is attributed to changes in the orbitals that occur upon introduction of non-interacting subsystems. Finally, CISNO-CASCI is found to provide a suitable description of the PES surrounding a biradicaloid conical intersection in ethylene.« less

Prediction of renal crystalline size distributions in space using a PBE analytic model. 2. Effect of dietary countermeasures.

PubMed

Kassemi, Mohammad; Thompson, David

2016-09-01

An analytic Population Balance Equation model is used to assess the efficacy of citrate, pyrophosphate, and augmented fluid intake as dietary countermeasures aimed at reducing the risk of renal stone formation for astronauts. The model uses the measured biochemical profile of the astronauts as input and predicts the steady-state size distribution of the nucleating, growing, and agglomerating renal calculi subject to biochemical changes brought about by administration of these dietary countermeasures. Numerical predictions indicate that an increase in citrate levels beyond its average normal ground-based urinary values is beneficial but only to a limited extent. Unfortunately, results also indicate that any decline in the citrate levels during space travel below its normal urinary values on Earth can easily move the astronaut into the stone-forming risk category. Pyrophosphate is found to be an effective inhibitor since numerical predictions indicate that even at quite small urinary concentrations, it has the potential of shifting the maximum crystal aggregate size to a much smaller and plausibly safer range. Finally, our numerical results predict a decline in urinary volume below 1.5 liters/day can act as a dangerous promoter of renal stone development in microgravity while urinary volume levels of 2.5-3 liters/day can serve as effective space countermeasures. Copyright © 2016 the American Physiological Society.

United States Air Force Academy get-away-special flexible beam experiment

NASA Technical Reports Server (NTRS)

Bubb, Keith W.; Lamberson, Steven E.; Lash, Thomas A.

1989-01-01

The Department of Astronautics at the United States Air Force Academy is currently planning to fly an experiment in a NASA Get-Away-Special (GAS) canister. The experiment was named the flex beam experiment. The primary technical objective of the flex beam experiment is to measure the damping of a thin beam in the vacuum and zero G environment of space. By measuring the damping in space, it is hoped to determine the amount of damping the beam normally experiences due to the gravitational forces present on Earth. This will allow validation of models which predict the dynamics of thin beams in the space environment. The experiment will also allow the Academy to develop and improve its ability to perform experiments within the confines of a NASA GAS canister. Several experiments, of limited technical difficulty, were flown by the Academy. More complex experiments are currently planned and it is hoped to learn techniques with each space shuttle flight.

Space charge effects for multipactor in coaxial lines

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

Sorolla, E., E-mail: eden.sorolla@xlim.fr; Sounas, A.; Mattes, M.

2015-03-15

Multipactor is a hazardous vacuum discharge produced by secondary electron emission within microwave devices of particle accelerators and telecommunication satellites. This work analyzes the dynamics of the multipactor discharge within a coaxial line for the mono-energetic electron emission model taking into account the space charge effects. The steady-state is predicted by the proposed model and an analytical expression for the maximum number of electrons released by the discharge presented. This could help to link simulations to experiments and define a multipactor onset criterion.

The Scintillation Prediction Observations Research Task (SPORT): A Multinational Science Mission using a CubeSat

NASA Astrophysics Data System (ADS)

Spann, J. F.; Habash Krause, L.; Swenson, C.; Heelis, R. A.; Bishop, R. L.; Le, G.; Abdu, M. A.; Durão, O.; Loures, L.; De Nardin, C. M.; Shibuya, L.; Casas, J.; Nash-STevenson, S.; Muralikrishana, P.; Costa, J. E. R.; Wrasse, C. M.; Fry, C. D.

2017-12-01

The Scintillation Prediction Observations Research Task (SPORT) is a 6U CubeSat pathfinder mission to address the very compelling but difficult problem of understanding the preconditions leading to equatorial plasma bubbles. The scientific literature describes the preconditions in both the plasma drifts and the density profiles related to bubble formations that occur several hours later in the evening. Most of the scientific discovery has resulted from observations at the Jicamarca Radio Observatory from Peru, a single site, within a single longitude sector. SPORT will provide a systematic study of the state of the pre-bubble conditions at all longitudes sectors to allow us to understand the differences between geography and magnetic geometry. This talk will present an overview of the mission and the anticipated data products. Products include global maps of scintillation occurrence as a function of local time, and magnetic conjugacy occurrence observations. SPORT is a multinational partnership between NASA, the Brazilian National Institute for Space Research (INPE), and the Technical Aeronautics Institute under the Brazilian Air Force Command Department (DCTA/ITA). It has been encouraged by U.S. Southern Command (SOUTHCOM) to foster increased cooperation and ties between academics, civilian space programs and the militaries. NASA Marshall Space Flight Center is coordinating this investigation by overseeing the launch to orbit and the flight instruments, which are being built by the Aerospace Corporation, University of Texas Dallas, Utah State University, and NASA Goddard Space Flight Center. The Brazilian partners are contributing the spacecraft, observatory integration and test, ground observation networks, and mission operations and data management. The science data will be distributed from and archived at the INPE/EMBRACE regional space-weather forecasting center in Brazil, and mirrored at the NASA GSFC Space Physics Data Facility (SPDF).

Space Medicine

NASA Technical Reports Server (NTRS)

Pool, Sam L.

2000-01-01

The National Academy of Sciences Committee on Space Biology and Medicine points out that space medicine is unique among space sciences, because in addition to addressing questions of fundamental scientific interest, it must address clinical or human health and safety issues as well. Efforts to identify how microgravity affects human physiology began in earnest by the United States in 1960 with the establishment of the National Aeronautics and Space Administration (NASA's) Life Sciences program. Before the first human space missions, prediction about the physiological effects of microgravity in space ranged from extremely severe to none at all. The understanding that has developed from our experiences in space to date allows us to be guardedly optimistic about the ultimate accommodations of humans to space flight. Only by our travels into the microgravity environment of space have we begun to unravel the mysteries associated with gravity's role in shaping human physiology. Space medicine is still at its very earliest stages. Development of this field has been slow for several reasons, including the limited number of space flights, the small number of research subjects, and the competition within the life sciences community and other disciplines for flight opportunities. The physiological changes incurred during space flight may have a dramatic effect on the course of an injury or illness. These physiological changes present an exciting challenge for the field of space medicine: how to best preserve human health and safety while simultaneously deciphering the effects of microgravity on human performance. As the United States considers the future of humans in long-term space travel, it is essential that the many mysteries as to how microgravity affects human systems be addressed with vigor. Based on the current state of our knowledge, the justification is excellent indeed compelling- for NASA to develop a sophisticated capability in space medicine. Teams of physicians and scientists should be actively engaged in fundamental and applied research designed to ensure that it is safe for humans to routinely and repeatedly stay and work in the microgravity environment of space.

Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation.

PubMed

Reagan, Andrew J; Dubief, Yves; Dodds, Peter Sheridan; Danforth, Christopher M

2016-01-01

A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth's weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA) methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF) to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD) of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction.

Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation

PubMed Central

Reagan, Andrew J.; Dubief, Yves; Dodds, Peter Sheridan; Danforth, Christopher M.

2016-01-01

A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth’s weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA) methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF) to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD) of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction. PMID:26849061

Prediction of renal crystalline size distributions in space using a PBE analytic model. 1. Effect of microgravity-induced biochemical alterations.

PubMed

Kassemi, Mohammad; Thompson, David

2016-09-01

An analytical Population Balance Equation model is developed and used to assess the risk of critical renal stone formation for astronauts during future space missions. The model uses the renal biochemical profile of the subject as input and predicts the steady-state size distribution of the nucleating, growing, and agglomerating calcium oxalate crystals during their transit through the kidney. The model is verified through comparison with published results of several crystallization experiments. Numerical results indicate that the model is successful in clearly distinguishing between 1-G normal and 1-G recurrent stone-former subjects based solely on their published 24-h urine biochemical profiles. Numerical case studies further show that the predicted renal calculi size distribution for a microgravity astronaut is closer to that of a recurrent stone former on Earth rather than to a normal subject in 1 G. This interestingly implies that the increase in renal stone risk level in microgravity is relatively more significant for a normal person than a stone former. However, numerical predictions still underscore that the stone-former subject carries by far the highest absolute risk of critical stone formation during space travel. Copyright © 2016 the American Physiological Society.

Observing spatio-temporal dynamics of excitable media using reservoir computing

NASA Astrophysics Data System (ADS)

Zimmermann, Roland S.; Parlitz, Ulrich

2018-04-01

We present a dynamical observer for two dimensional partial differential equation models describing excitable media, where the required cross prediction from observed time series to not measured state variables is provided by Echo State Networks receiving input from local regions in space, only. The efficacy of this approach is demonstrated for (noisy) data from a (cubic) Barkley model and the Bueno-Orovio-Cherry-Fenton model describing chaotic electrical wave propagation in cardiac tissue.

Unfolding and melting of DNA (RNA) hairpins: the concept of structure-specific 2D dynamic landscapes.

PubMed

Lin, Milo M; Meinhold, Lars; Shorokhov, Dmitry; Zewail, Ahmed H

2008-08-07

A 2D free-energy landscape model is presented to describe the (un)folding transition of DNA/RNA hairpins, together with molecular dynamics simulations and experimental findings. The dependence of the (un)folding transition on the stem sequence and the loop length is shown in the enthalpic and entropic contributions to the free energy. Intermediate structures are well defined by the two coordinates of the landscape during (un)zipping. Both the free-energy landscape model and the extensive molecular dynamics simulations totaling over 10 mus predict the existence of temperature-dependent kinetic intermediate states during hairpin (un)zipping and provide the theoretical description of recent ultrafast temperature-jump studies which indicate that hairpin (un)zipping is, in general, not a two-state process. The model allows for lucid prediction of the collapsed state(s) in simple 2D space and we term it the kinetic intermediate structure (KIS) model.

Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.

PubMed

Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad

2016-12-01

Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.

First-principles theory of cation and intercalation ordering in Li xCoO 2

NASA Astrophysics Data System (ADS)

Wolverton, C.; Zunger, Alex

Several types of cation- and vacancy-ordering are of interest in the Li xCoO 2 battery cathode material since they can have a profound effect on the battery voltage. We present a first-principles theoretical approach which can be used to calculate both cation- and vacancy-ordering patterns at both zero and finite temperatures. This theory also provides quantum-mechanical predictions (i.e., without the use of any experimental input) of battery voltages of both ordered and disordered Li xCoO 2/Li cells from the energetics of the Li intercalation reactions. Our calculations allow us to search the entire configurational space to predict the lowest-energy ground-state structures, search for large voltage cathodes, explore metastable low-energy states, and extend our calculations to finite temperatures, thereby searching for order-disorder transitions and states of partial disorder. We present the first prediction of the stable spinel structure LiCo 2O 4 for the 50% delithiated Li 0.5CoO 2.

Prognostics for Ground Support Systems: Case Study on Pneumatic Valves

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Goebel, Kai

2011-01-01

Prognostics technologies determine the health (or damage) state of a component or sub-system, and make end of life (EOL) and remaining useful life (RUL) predictions. Such information enables system operators to make informed maintenance decisions and streamline operational and mission-level activities. We develop a model-based prognostics methodology for pneumatic valves used in ground support equipment for cryogenic propellant loading operations. These valves are used to control the flow of propellant, so failures may have a significant impact on launch availability. Therefore, correctly predicting when valves will fail enables timely maintenance that avoids launch delays and aborts. The approach utilizes mathematical models describing the underlying physics of valve degradation, and, employing the particle filtering algorithm for joint state-parameter estimation, determines the health state of the valve and the rate of damage progression, from which EOL and RUL predictions are made. We develop a prototype user interface for valve prognostics, and demonstrate the prognostics approach using historical pneumatic valve data from the Space Shuttle refueling system.

Ultra-sparse dielectric nanowire grids as wideband reflectors and polarizers.

PubMed

Yoon, Jae Woong; Lee, Kyu Jin; Magnusson, Robert

2015-11-02

Engaging both theory and experiment, we investigate resonant photonic lattices in which the duty cycle tends to zero. Corresponding dielectric nanowire grids are mostly empty space if operated as membranes in vacuum or air. These grids are shown to be effective wideband reflectors with impressive polarizing properties. We provide computed results predicting nearly complete reflection and attendant polarization extinction in multiple spectral regions. Experimental results with Si nanowire arrays with 10% duty cycle show ~200-nm-wide band of high reflection for one polarization state and free transmission for the orthogonal state. These results agree quantitatively with theoretical predictions. It is fundamentally extremely significant that the wideband spectral expressions presented can be generated in these minimal systems.

Theory of the control of structures by low authority controllers

NASA Technical Reports Server (NTRS)

Aubrun, J. N.

1978-01-01

The novel idea presented is based on the observation that if a structure is controlled by distributed systems of sensors and actuators with limited authority, i.e., if the controller is allowed to modify only moderately the natural modes and frequencies of the structure, then it should be possible to apply root perturbation techniques to predict analytically the behavior of the total system. Attention is given to the root perturbation formula first derived by Jacobi for infinitesimal perturbations which neglect the induced eigenvector perturbation, a more general form of Jacobi's formula, first-order structural equations and modal state vectors, state-space equations for damper-augmented structures, and modal damping prediction formulas.

Psychological issues relevant to astronaut selection for long-duration space flight: a review of the literature.

PubMed

Collins, Daniel L

2003-01-01

This technical paper reviews the current literature on psychological issues relevant to astronaut selection for long-duration space flights. Interpersonal problems have been and remain a recurring problem for both short and long-duration space flights. Even after completion of the space mission, intense psychological aftereffects are reported. The specific behavioral problems experienced during United States and Soviet Union space flights are reviewed, specifically addressing contentious episodes and impaired judgments that occurred during the Mercury, Apollo, and Skylab missions. Psychological tests used in the selection process for the space program have focused primarily on the detection of gross psychopathologies in potential candidates. Although these psychological instruments excluded some people from becoming astronauts, the battery of tests failed to predict which individuals would manifest behavioral aberrations in judgment, cooperative functioning, overt irritability, or destructive interpersonal actions.

Lamb Shift in the Near Field of Hyperbolic Metamaterial Half Space

NASA Astrophysics Data System (ADS)

Deng, Nai Jing; Yu, Kin Wah

2013-03-01

Hyperbolic metamaterials give a large magnification of the density of states in a specific frequency ranges, and has motivated various applications in emission lifetime reduction, strong absorption, and extraordinary black body radiation, etc. The boost of vacuum energy, which is proportional to the density of states, is expected in hyperbolic metamaterial. We have studied the Lamb shift in vacuum-hyperbolic-metamterial half spaces and shown the non-trivial role of vacuum energy. In our calculation, the easy-fabricated multilayer structure is employed to generate a hyperbolic dispersion relation. The spectrum of hydrogen atoms is calculated with a perturbation method after quantizing the half spaces with a complete mode expansion. It appears that the shift of spectrum is mainly contributed by the terahertz response of materials, which has been well described and predicted in both theories and experiments. Work supported by the General Research Fund of the Hong Kong SAR Government

Mir Cooperative Solar Array

NASA Technical Reports Server (NTRS)

Skor, Mike; Hoffman, Dave J.

1997-01-01

The Mir Cooperative Solar Array (MCSA), produced jointly by the United States and Russia, was deployed on the Mir Russian space station on May 25, 1996. The MCSA is a photovoltaic electrical power system that can generate up to 6 kW. The power from the MCSA is needed to extend Mir's lifetime and to support experiments conducted there by visiting U.S. astronauts. The MCSA was brought to Mir via the Space Shuttle Atlantis on the STS-74 mission, launched November 12, 1995. This cooperative venture combined the best technology of both countries: the United States provided high-efficiency, lightweight photovoltaic panel modules, whereas Russia provided the array structure and deployment mechanism. Technology developed in the Space Station Freedom Program, and now being used in the International Space Station, was used to develop MCSA's photovoltaic panel. Performance data obtained from MCSA operation on Mir will help engineers better understand the performance of the photovoltaic panel modules in orbit. This information will be used to more accurately predict the performance of the International Space Station solar arrays. Managed by the NASA Lewis Research Center for NASA's International Space Station Program Office in Houston, Texas, the MCSA Project was completed on time and under budget despite a very aggressive schedule.

Concepts and challenges in cancer risk prediction for the space radiation environment.

PubMed

Barcellos-Hoff, Mary Helen; Blakely, Eleanor A; Burma, Sandeep; Fornace, Albert J; Gerson, Stanton; Hlatky, Lynn; Kirsch, David G; Luderer, Ulrike; Shay, Jerry; Wang, Ya; Weil, Michael M

2015-07-01

Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program. Copyright © 2015 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.

The Scientific Foundations of Forecasting Magnetospheric Space Weather

NASA Astrophysics Data System (ADS)

Eastwood, J. P.; Nakamura, R.; Turc, L.; Mejnertsen, L.; Hesse, M.

2017-11-01

The magnetosphere is the lens through which solar space weather phenomena are focused and directed towards the Earth. In particular, the non-linear interaction of the solar wind with the Earth's magnetic field leads to the formation of highly inhomogenous electrical currents in the ionosphere which can ultimately result in damage to and problems with the operation of power distribution networks. Since electric power is the fundamental cornerstone of modern life, the interruption of power is the primary pathway by which space weather has impact on human activity and technology. Consequently, in the context of space weather, it is the ability to predict geomagnetic activity that is of key importance. This is usually stated in terms of geomagnetic storms, but we argue that in fact it is the substorm phenomenon which contains the crucial physics, and therefore prediction of substorm occurrence, severity and duration, either within the context of a longer-lasting geomagnetic storm, but potentially also as an isolated event, is of critical importance. Here we review the physics of the magnetosphere in the frame of space weather forecasting, focusing on recent results, current understanding, and an assessment of probable future developments.

Concepts and challenges in cancer risk prediction for the space radiation environment

NASA Astrophysics Data System (ADS)

Barcellos-Hoff, Mary Helen; Blakely, Eleanor A.; Burma, Sandeep; Fornace, Albert J.; Gerson, Stanton; Hlatky, Lynn; Kirsch, David G.; Luderer, Ulrike; Shay, Jerry; Wang, Ya; Weil, Michael M.

2015-07-01

Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program.

Phase diagram of single vesicle dynamical states in shear flow.

PubMed

Deschamps, J; Kantsler, V; Steinberg, V

2009-03-20

We report the first experimental phase diagram of vesicle dynamical states in a shear flow presented in a space of two dimensionless parameters suggested recently by V. Lebedev et al. To reduce errors in the control parameters, 3D geometrical reconstruction and determination of the viscosity contrast of a vesicle in situ in a plane Couette flow device prior to the experiment are developed. Our results are in accord with the theory predicting three distinctly separating regions of vesicle dynamical states in the plane of just two self-similar parameters.

Experimental Trapped-ion Quantum Simulation of the Kibble-Zurek dynamics in momentum space

PubMed Central

Cui, Jin-Ming; Huang, Yun-Feng; Wang, Zhao; Cao, Dong-Yang; Wang, Jian; Lv, Wei-Min; Luo, Le; del Campo, Adolfo; Han, Yong-Jian; Li, Chuan-Feng; Guo, Guang-Can

2016-01-01

The Kibble-Zurek mechanism is the paradigm to account for the nonadiabatic dynamics of a system across a continuous phase transition. Its study in the quantum regime is hindered by the requisite of ground state cooling. We report the experimental quantum simulation of critical dynamics in the transverse-field Ising model by a set of Landau-Zener crossings in pseudo-momentum space, that can be probed with high accuracy using a single trapped ion. We test the Kibble-Zurek mechanism in the quantum regime in the momentum space and find the measured scaling of excitations is in accordance with the theoretical prediction. PMID:27633087

A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks

PubMed Central

Yin, Junming; Ho, Qirong; Xing, Eric P.

2014-01-01

We propose a scalable approach for making inference about latent spaces of large networks. With a succinct representation of networks as a bag of triangular motifs, a parsimonious statistical model, and an efficient stochastic variational inference algorithm, we are able to analyze real networks with over a million vertices and hundreds of latent roles on a single machine in a matter of hours, a setting that is out of reach for many existing methods. When compared to the state-of-the-art probabilistic approaches, our method is several orders of magnitude faster, with competitive or improved accuracy for latent space recovery and link prediction. PMID:25400487

Electroweak Symmetry Breaking and the Higgs Boson: Confronting Theories at Colliders

NASA Astrophysics Data System (ADS)

Azatov, Aleksandr; Galloway, Jamison

2013-01-01

In this review, we discuss methods of parsing direct information from collider experiments regarding the Higgs boson and describe simple ways in which experimental likelihoods can be consistently reconstructed and interfaced with model predictions in pertinent parameter spaces. We review prevalent scenarios for extending the electroweak symmetry breaking sector and emphasize their predictions for nonstandard Higgs phenomenology that could be observed in large hadron collider (LHC) data if naturalness is realized in particular ways. Specifically we identify how measurements of Higgs couplings can be used to imply the existence of new physics at particular scales within various contexts. The most dominant production and decay modes of the Higgs-like state observed in the early data sets have proven to be consistent with predictions of the Higgs boson of the Standard Model, though interesting directions in subdominant channels still exist and will require our careful attention in further experimental tests. Slightly anomalous rates in certain channels at the early LHC have spurred effort in model building and spectra analyses of particular theories, and we discuss these developments in some detail. Finally, we highlight some parameter spaces of interest in order to give examples of how the data surrounding the new state can most effectively be used to constrain specific models of weak scale physics.

Numerical Estimation of Balanced and Falling States for Constrained Legged Systems

NASA Astrophysics Data System (ADS)

Mummolo, Carlotta; Mangialardi, Luigi; Kim, Joo H.

2017-08-01

Instability and risk of fall during standing and walking are common challenges for biped robots. While existing criteria from state-space dynamical systems approach or ground reference points are useful in some applications, complete system models and constraints have not been taken into account for prediction and indication of fall for general legged robots. In this study, a general numerical framework that estimates the balanced and falling states of legged systems is introduced. The overall approach is based on the integration of joint-space and Cartesian-space dynamics of a legged system model. The full-body constrained joint-space dynamics includes the contact forces and moments term due to current foot (or feet) support and another term due to altered contact configuration. According to the refined notions of balanced, falling, and fallen, the system parameters, physical constraints, and initial/final/boundary conditions for balancing are incorporated into constrained nonlinear optimization problems to solve for the velocity extrema (representing the maximum perturbation allowed to maintain balance without changing contacts) in the Cartesian space at each center-of-mass (COM) position within its workspace. The iterative algorithm constructs the stability boundary as a COM state-space partition between balanced and falling states. Inclusion in the resulting six-dimensional manifold is a necessary condition for a state of the given system to be balanced under the given contact configuration, while exclusion is a sufficient condition for falling. The framework is used to analyze the balance stability of example systems with various degrees of complexities. The manifold for a 1-degree-of-freedom (DOF) legged system is consistent with the experimental and simulation results in the existing studies for specific controller designs. The results for a 2-DOF system demonstrate the dependency of the COM state-space partition upon joint-space configuration (elbow-up vs. elbow-down). For both 1- and 2-DOF systems, the results are validated in simulation environments. Finally, the manifold for a biped walking robot is constructed and illustrated against its single-support walking trajectories. The manifold identified by the proposed framework for any given legged system can be evaluated beforehand as a system property and serves as a map for either a specified state or a specific controller's performance.

Symmetry breaking gives rise to energy spectra of three states of matter

PubMed Central

Bolmatov, Dima; Musaev, Edvard T.; Trachenko, K.

2013-01-01

A fundamental task of statistical physics is to start with a microscopic Hamiltonian, predict the system's statistical properties and compare them with observable data. A notable current fundamental challenge is to tell whether and how an interacting Hamiltonian predicts different energy spectra, including solid, liquid and gas phases. Here, we propose a new idea that enables a unified description of all three states of matter. We introduce a generic form of an interacting phonon Hamiltonian with ground state configurations minimising the potential. Symmetry breaking SO(3) to SO(2), from the group of rotations in reciprocal space to its subgroup, leads to emergence of energy gaps of shear excitations as a consequence of the Goldstone theorem, and readily results in the emergence of energy spectra of solid, liquid and gas phases. PMID:24077388

Historical aspects of the early Soviet/Russian manned space program.

PubMed

West, J B

2001-10-01

Human spaceflight was one of the great physiological and engineering triumphs of the 20th century. Although the history of the United States manned space program is well known, the Soviet program was shrouded in secrecy until recently. Konstantin Edvardovich Tsiolkovsky (1857-1935) was an extraordinary Russian visionary who made remarkable predictions about space travel in the late 19th century. Sergei Pavlovich Korolev (1907-1966) was the brilliant "Chief Designer" who was responsible for many of the Soviet firsts, including the first artificial satellite and the first human being in space. The dramatic flight of Sputnik 1 was followed within a month by the launch of the dog Laika, the first living creature in space. Remarkably, the engineering work for this payload was all done in less than 4 wk. Korolev's greatest triumph was the flight of Yuri Alekseyevich Gagarin (1934-1968) on April 12, 1961. Another extraordinary feat was the first extravehicular activity by Aleksei Arkhipovich Leonov (1934-) using a flexible airlock that emphasized the entrepreneurial attitude of the Soviet engineers. By the mid-1960s, the Soviet program was overtaken by the United States program and attempts to launch a manned mission to the Moon failed. However, the early Soviet manned space program has a preeminent place in the history of space physiology.

Deviation diagnosis and analysis of hull flat block assembly based on a state space model

NASA Astrophysics Data System (ADS)

Zhang, Zhiying; Dai, Yinfang; Li, Zhen

2012-09-01

Dimensional control is one of the most important challenges in the shipbuilding industry. In order to predict assembly dimensional variation in hull flat block construction, a variation stream model based on state space was presented in this paper which can be further applied to accuracy control in shipbuilding. Part accumulative error, locating error, and welding deformation were taken into consideration in this model, and variation propagation mechanisms and the accumulative rule in the assembly process were analyzed. Then, a model was developed to describe the variation propagation throughout the assembly process. Finally, an example of flat block construction from an actual shipyard was given. The result shows that this method is effective and useful.

Space radiator simulation manual for computer code

NASA Technical Reports Server (NTRS)

Black, W. Z.; Wulff, W.

1972-01-01

A computer program that simulates the performance of a space radiator is presented. The program basically consists of a rigorous analysis which analyzes a symmetrical fin panel and an approximate analysis that predicts system characteristics for cases of non-symmetrical operation. The rigorous analysis accounts for both transient and steady state performance including aerodynamic and radiant heating of the radiator system. The approximate analysis considers only steady state operation with no aerodynamic heating. A description of the radiator system and instructions to the user for program operation is included. The input required for the execution of all program options is described. Several examples of program output are contained in this section. Sample output includes the radiator performance during ascent, reentry and orbit.

Solar Storm GIC Forecasting: Solar Shield Extension Development of the End-User Forecasting System Requirements

NASA Technical Reports Server (NTRS)

Pulkkinen, A.; Mahmood, S.; Ngwira, C.; Balch, C.; Lordan, R.; Fugate, D.; Jacobs, W.; Honkonen, I.

2015-01-01

A NASA Goddard Space Flight Center Heliophysics Science Division-led team that includes NOAA Space Weather Prediction Center, the Catholic University of America, Electric Power Research Institute (EPRI), and Electric Research and Management, Inc., recently partnered with the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) to better understand the impact of Geomagnetically Induced Currents (GIC) on the electric power industry. This effort builds on a previous NASA-sponsored Applied Sciences Program for predicting GIC, known as Solar Shield. The focus of the new DHS S&T funded effort is to revise and extend the existing Solar Shield system to enhance its forecasting capability and provide tailored, timely, actionable information for electric utility decision makers. To enhance the forecasting capabilities of the new Solar Shield, a key undertaking is to extend the prediction system coverage across Contiguous United States (CONUS), as the previous version was only applicable to high latitudes. The team also leverages the latest enhancements in space weather modeling capacity residing at Community Coordinated Modeling Center to increase the Technological Readiness Level, or Applications Readiness Level of the system http://www.nasa.gov/sites/default/files/files/ExpandedARLDefinitions4813.pdf.

A survey of numerical models for wind prediction

NASA Technical Reports Server (NTRS)

Schonfeld, D.

1980-01-01

A literature review is presented of the work done in the numerical modeling of wind flows. Pertinent computational techniques are described, as well as the necessary assumptions used to simplify the governing equations. A steady state model is outlined, based on the data obtained at the Deep Space Communications complex at Goldstone, California.

Expanding the Targeting Process into the Space Domain

DTIC Science & Technology

2008-06-01

planning and operations. The process is a continuous method by which information is converted into intelligence and made available to users...Targeting personnel and organizations consume intelligence produced by various agencies and organizations. Actionable and predictive intelligence applies to... intelligence and operations communities (Figure 1). 1 United States Department of Defense Joint

Conway's Game of Life is a near-critical metastable state in the multiverse of cellular automata.

PubMed

Reia, Sandro M; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ = 0) and an active phase density, with ρ = 0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ(2D) ≈ 0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

Computer Model Used to Help Customize Medicine

NASA Technical Reports Server (NTRS)

Stauber, Laurel J.; Veris, Jenise

2001-01-01

Dr. Radhakrishnan, a researcher at the NASA Glenn Research Center, in collaboration with biomedical researchers at the Case Western Reserve University School of Medicine and Rainbow Babies and Children's Hospital, is developing computational models of human physiology that quantitate metabolism and its regulation, in both healthy and pathological states. These models can help predict the effects of stresses or interventions, such as drug therapies, and contribute to the development of customized medicine. Customized medical treatment protocols can give more comprehensive evaluations and lead to more specific and effective treatments for patients, reducing treatment time and cost. Commercial applications of this research may help the pharmaceutical industry identify therapeutic needs and predict drug-drug interactions. Researchers will be able to study human metabolic reactions to particular treatments while in different environments as well as establish more definite blood metabolite concentration ranges in normal and pathological states. These computational models may help NASA provide the background for developing strategies to monitor and safeguard the health of astronauts and civilians in space stations and colonies. They may also help to develop countermeasures that ameliorate the effects of both acute and chronic space exposure.

Conway's game of life is a near-critical metastable state in the multiverse of cellular automata

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ =0) and an active phase density, with ρ =0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ2D≈0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

Steepest-entropy-ascent quantum thermodynamic modeling of the relaxation process of isolated chemically reactive systems using density of states and the concept of hypoequilibrium state

NASA Astrophysics Data System (ADS)

Li, Guanchen; von Spakovsky, Michael R.

2016-01-01

This paper presents a study of the nonequilibrium relaxation process of chemically reactive systems using steepest-entropy-ascent quantum thermodynamics (SEAQT). The trajectory of the chemical reaction, i.e., the accessible intermediate states, is predicted and discussed. The prediction is made using a thermodynamic-ensemble approach, which does not require detailed information about the particle mechanics involved (e.g., the collision of particles). Instead, modeling the kinetics and dynamics of the relaxation process is based on the principle of steepest-entropy ascent (SEA) or maximum-entropy production, which suggests a constrained gradient dynamics in state space. The SEAQT framework is based on general definitions for energy and entropy and at least theoretically enables the prediction of the nonequilibrium relaxation of system state at all temporal and spatial scales. However, to make this not just theoretically but computationally possible, the concept of density of states is introduced to simplify the application of the relaxation model, which in effect extends the application of the SEAQT framework even to infinite energy eigenlevel systems. The energy eigenstructure of the reactive system considered here consists of an extremely large number of such levels (on the order of 10130) and yields to the quasicontinuous assumption. The principle of SEA results in a unique trajectory of system thermodynamic state evolution in Hilbert space in the nonequilibrium realm, even far from equilibrium. To describe this trajectory, the concepts of subsystem hypoequilibrium state and temperature are introduced and used to characterize each system-level, nonequilibrium state. This definition of temperature is fundamental rather than phenomenological and is a generalization of the temperature defined at stable equilibrium. In addition, to deal with the large number of energy eigenlevels, the equation of motion is formulated on the basis of the density of states and a set of associated degeneracies. Their significance for the nonequilibrium evolution of system state is discussed. For the application presented, the numerical method used is described and is based on the density of states, which is specifically developed to solve the SEAQT equation of motion. Results for different kinds of initial nonequilibrium conditions, i.e., those for gamma and Maxwellian distributions, are studied. The advantage of the concept of hypoequilibrium state in studying nonequilibrium trajectories is discussed.

International Space Station Electric Power System Performance Code-SPACE

NASA Technical Reports Server (NTRS)

Hojnicki, Jeffrey; McKissock, David; Fincannon, James; Green, Robert; Kerslake, Thomas; Delleur, Ann; Follo, Jeffrey; Trudell, Jeffrey; Hoffman, David J.; Jannette, Anthony;

Solar Atmosphere to Earth's Surface: Long Lead Time dB/dt Predictions with the Space Weather Modeling Framework

NASA Astrophysics Data System (ADS)

Welling, D. T.; Manchester, W.; Savani, N.; Sokolov, I.; van der Holst, B.; Jin, M.; Toth, G.; Liemohn, M. W.; Gombosi, T. I.

2017-12-01

The future of space weather prediction depends on the community's ability to predict L1 values from observations of the solar atmosphere, which can yield hours of lead time. While both empirical and physics-based L1 forecast methods exist, it is not yet known if this nascent capability can translate to skilled dB/dt forecasts at the Earth's surface. This paper shows results for the first forecast-quality, solar-atmosphere-to-Earth's-surface dB/dt predictions. Two methods are used to predict solar wind and IMF conditions at L1 for several real-world coronal mass ejection events. The first method is an empirical and observationally based system to estimate the plasma characteristics. The magnetic field predictions are based on the Bz4Cast system which assumes that the CME has a cylindrical flux rope geometry locally around Earth's trajectory. The remaining plasma parameters of density, temperature and velocity are estimated from white-light coronagraphs via a variety of triangulation methods and forward based modelling. The second is a first-principles-based approach that combines the Eruptive Event Generator using Gibson-Low configuration (EEGGL) model with the Alfven Wave Solar Model (AWSoM). EEGGL specifies parameters for the Gibson-Low flux rope such that it erupts, driving a CME in the coronal model that reproduces coronagraph observations and propagates to 1AU. The resulting solar wind predictions are used to drive the operational Space Weather Modeling Framework (SWMF) for geospace. Following the configuration used by NOAA's Space Weather Prediction Center, this setup couples the BATS-R-US global magnetohydromagnetic model to the Rice Convection Model (RCM) ring current model and a height-integrated ionosphere electrodynamics model. The long lead time predictions of dB/dt are compared to model results that are driven by L1 solar wind observations. Both are compared to real-world observations from surface magnetometers at a variety of geomagnetic latitudes. Metrics are calculated to examine how the simulated solar wind drivers impact forecast skill. These results illustrate the current state of long-lead-time forecasting and the promise of this technology for operational use.

The aerodynamic challenges of the design and development of the space shuttle orbiter

NASA Technical Reports Server (NTRS)

Young, J. C.; Underwood, J. M.; Hillje, E. R.; Whitnah, A. M.; Romere, P. O.; Gamble, J. D.; Roberts, B. B.; Ware, G. M.; Scallion, W. I.; Spencer, B., Jr.

1985-01-01

The major aerodynamic design challenge at the beginning of the United States Space Transportation System (STS) research and development phase was to design a vehicle that would fly as a spacecraft during early entry and as an aircraft during the final phase of entry. The design was further complicated because the envisioned vehicle was statically unstable during a portion of the aircraft mode of operation. The second challenge was the development of preflight aerodynamic predictions with an accuracy consistent with conducting a manned flight on the initial orbital flight. A brief history of the early contractual studies is presented highlighting the technical results and management decisions influencing the aerodynamic challenges. The configuration evolution and the development of preflight aerodynamic predictions will be reviewed. The results from the first four test flights shows excellent agreement with the preflight aerodynamic predictions over the majority of the flight regimes. The only regimes showing significant disagreement is confined primarily to early entry, where prediction of the basic vehicle trim and the influence of the reaction control system jets on the flow field were found to be deficient. Postflight results are analyzed to explain these prediction deficiencies.

Probability Forecasting Using Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Duncan, M.; Frisbee, J.; Wysack, J.

2014-09-01

Space Situational Awareness (SSA) is defined as the knowledge and characterization of all aspects of space. SSA is now a fundamental and critical component of space operations. Increased dependence on our space assets has in turn lead to a greater need for accurate, near real-time knowledge of all space activities. With the growth of the orbital debris population, satellite operators are performing collision avoidance maneuvers more frequently. Frequent maneuver execution expends fuel and reduces the operational lifetime of the spacecraft. Thus the need for new, more sophisticated collision threat characterization methods must be implemented. The collision probability metric is used operationally to quantify the collision risk. The collision probability is typically calculated days into the future, so that high risk and potential high risk conjunction events are identified early enough to develop an appropriate course of action. As the time horizon to the conjunction event is reduced, the collision probability changes. A significant change in the collision probability will change the satellite mission stakeholder's course of action. So constructing a method for estimating how the collision probability will evolve improves operations by providing satellite operators with a new piece of information, namely an estimate or 'forecast' of how the risk will change as time to the event is reduced. Collision probability forecasting is a predictive process where the future risk of a conjunction event is estimated. The method utilizes a Monte Carlo simulation that produces a likelihood distribution for a given collision threshold. Using known state and state uncertainty information, the simulation generates a set possible trajectories for a given space object pair. Each new trajectory produces a unique event geometry at the time of close approach. Given state uncertainty information for both objects, a collision probability value can be computed for every trail. This yields a collision probability distribution given known, predicted uncertainty. This paper presents the details of the collision probability forecasting method. We examine various conjunction event scenarios and numerically demonstrate the utility of this approach in typical event scenarios. We explore the utility of a probability-based track scenario simulation that models expected tracking data frequency as the tasking levels are increased. The resulting orbital uncertainty is subsequently used in the forecasting algorithm.

Harnessing Orbital Debris to Sense the Space Environment

NASA Astrophysics Data System (ADS)

Mutschler, S.; Axelrad, P.; Matsuo, T.

A key requirement for accurate space situational awareness (SSA) is knowledge of the non-conservative forces that act on space objects. These effects vary temporally and spatially, driven by the dynamical behavior of space weather. Existing SSA algorithms adjust space weather models based on observations of calibration satellites. However, lack of sufficient data and mismodeling of non-conservative forces cause inaccuracies in space object motion prediction. The uncontrolled nature of debris makes it particularly sensitive to the variations in space weather. Our research takes advantage of this behavior by inverting observations of debris objects to infer the space environment parameters causing their motion. In addition, this research will produce more accurate predictions of the motion of debris objects. The hypothesis of this research is that it is possible to utilize a "cluster" of debris objects, objects within relatively close proximity of each other, to sense their local environment. We focus on deriving parameters of an atmospheric density model to more precisely predict the drag force on LEO objects. An Ensemble Kalman Filter (EnKF) is used for assimilation; the prior ensemble to the posterior ensemble is transformed during the measurement update in a manner that does not require inversion of large matrices. A prior ensemble is utilized to empirically determine the nonlinear relationship between measurements and density parameters. The filter estimates an extended state that includes position and velocity of the debris object, and atmospheric density parameters. The density is parameterized as a grid of values, distributed by latitude and local sidereal time over a spherical shell encompassing Earth. This research focuses on LEO object motion, but it can also be extended to additional orbital regimes for observation and refinement of magnetic field and solar radiation models. An observability analysis of the proposed approach is presented in terms of the measurement cadence necessary to estimate the local space environment.

Prediction of three sigma maximum dispersed density for aerospace applications

NASA Technical Reports Server (NTRS)

Charles, Terri L.; Nitschke, Michael D.

1993-01-01

Free molecular heating (FMH) is caused by the transfer of energy during collisions between the upper atmosphere molecules and a space vehicle. The dispersed free molecular heating on a surface is an important constraint for space vehicle thermal analyses since it can be a significant source of heating. To reduce FMH to a spacecraft, the parking orbit is often designed to a higher altitude at the expense of payload capability. Dispersed FMH is a function of both space vehicle velocity and atmospheric density, however, the space vehicle velocity variations are insignificant when compared to the atmospheric density variations. The density of the upper atmosphere molecules is a function of altitude, but also varies with other environmental factors, such as solar activity, geomagnetic activity, location, and time. A method has been developed to predict three sigma maximum dispersed density for up to 15 years into the future. This method uses a state-of-the-art atmospheric density code, MSIS 86, along with 50 years of solar data, NASA and NOAA solar activity predictions for the next 15 years, and an Aerospace Corporation correlation to account for density code inaccuracies to generate dispersed maximum density ratios denoted as 'K-factors'. The calculated K-factors can be used on a mission unique basis to calculate dispersed density, and hence dispersed free molecular heating rates. These more accurate K-factors can allow lower parking orbit altitudes, resulting in increased payload capability.

Predicting the possibility of not yet observed situations as higher goal of space environment standards.

NASA Astrophysics Data System (ADS)

Nymmik, Rikho

Space environment models are intended for fairly describing the quantitative behavior of nature space environment. Usually, they are constructed on the basis of some experimental data set generalization, which is characteristic of the conditions that were taking place during measurement period. It is often to see that such models state and postulate realities of the past. The typical example of this point of view is the situation around extremely SEP events. During dozens of years models of such events have been based on the largest occurrences observed, which features were measured by some instruments with the reliability that was not always analyzed. It is obvious, that this way does not agree with reality, because any new extreme event conflicts with it. From this follow that space environment models can not be created by using numerical observed data only, when such data are changing in time, or have the probability nature. The model's goal is not only describing the average environment characteristics, but the predicting of extreme ones too. Such a prediction can only be result of analyzing the causes that stimulate environment change and taking them into account in model parameters. In this report we present the analysis of radiation environment formed by solar-generated high energy particles. A progresses and failures of SEP event modeling attempts are also shown and analyzed.

Improved Orbit Determination and Forecasts with an Assimilative Tool for Atmospheric Density and Satellite Drag Specification

NASA Astrophysics Data System (ADS)

Crowley, G.; Pilinski, M.; Sutton, E. K.; Codrescu, M.; Fuller-Rowell, T. J.; Matsuo, T.; Fedrizzi, M.; Solomon, S. C.; Qian, L.; Thayer, J. P.

2016-12-01

Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by the variability in density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of LEO satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. We describe ongoing work to build a comprehensive nowcast and forecast system for specifying the neutral atmospheric state related to orbital drag conditions. The system outputs include neutral density, winds, temperature, composition, and the satellite drag derived from these parameters. This modeling tool is based on several state-of-the-art coupled models of the thermosphere-ionosphere as well as several empirical models running in real-time and uses assimilative techniques to produce a thermospheric nowcast. This software will also produce 72 hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition and using near real-time and predicted space weather data and indices as the inputs. Features of this technique include: • Satellite drag specifications with errors lower than current models • Altitude coverage up to 1000km • Background state representation using both first principles and empirical models • Assimilation of satellite drag and other datatypes • Real time capability • Ability to produce 72-hour forecasts of the atmospheric state In this paper, we will summarize the model design and assimilative architecture, and present preliminary validation results. Validation results will be presented in the context of satellite orbit errors and compared with several leading atmospheric models including the High Accuracy Satellite Drag Model, which is currently used operationally by the Air Force to specify neutral densities. As part of the analysis, we compare the drag observed by a variety of satellites which were not used as part of the assimilation-dataset and whose perigee altitudes span a range from 200km to 700 km.

Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.

PubMed

Zhang, Wen; Chen, Yanlin; Li, Dingfang

2017-11-25

Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.

Quantitative controls on submarine slope failure morphology

USGS Publications Warehouse

Lee, H.J.; Schwab, W.C.; Edwards, B.D.; Kayen, R.E.

1991-01-01

The concept of the steady-state of deformation can be applied to predicting the ultimate form a landslide will take. The steady-state condition, defined by a line in void ratio-effective stress space, exists at large levels of strain and remolding. Conceptually, if sediment initially exists with void ratio-effective stress conditions above the steady-state line, the sediment shear strength will decrease during a transient loading event, such as an earthquake or storm. If the reduced shear strength existing at the steady state is less than the downslope shear stress induced by gravity, then large-scale internal deformation, disintegration, and flow will occur. -from Authors

Multispectral Image Processing for Plants

NASA Technical Reports Server (NTRS)

Miles, Gaines E.

1991-01-01

The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

Universal broadening of the Bardeen-Cooper-Schrieffer coherence peak of disordered superconducting films.

PubMed

Feigel'man, M V; Skvortsov, M A

2012-10-05

In disordered superconductors, the local pairing field fluctuates in space, leading to the smearing of the BCS peak in the density of states and the appearance of the subgap tail states. We analyze the universal mesoscopic contributions to these effects and show that they are enhanced by the Coulomb repulsion. In the vicinity of the quantum critical point, where superconductivity is suppressed by the "fermionic mechanism," strong smearing of the peak due to mesoscopic fluctuations is predicted.

A Monte Carlo Analysis of the Thrust Imbalance for the Space Launch System Booster During Both the Ignition Transient and Steady State Operation

NASA Technical Reports Server (NTRS)

Foster, Winfred A., Jr.; Crowder, Winston; Steadman, Todd E.

2014-01-01

This paper presents the results of statistical analyses performed to predict the thrust imbalance between two solid rocket motor boosters to be used on the Space Launch System (SLS) vehicle. Two legacy internal ballistics codes developed for the Space Shuttle program were coupled with a Monte Carlo analysis code to determine a thrust imbalance envelope for the SLS vehicle based on the performance of 1000 motor pairs. Thirty three variables which could impact the performance of the motors during the ignition transient and thirty eight variables which could impact the performance of the motors during steady state operation of the motor were identified and treated as statistical variables for the analyses. The effects of motor to motor variation as well as variations between motors of a single pair were included in the analyses. The statistical variations of the variables were defined based on data provided by NASA's Marshall Space Flight Center for the upgraded five segment booster and from the Space Shuttle booster when appropriate. The results obtained for the statistical envelope are compared with the design specification thrust imbalance limits for the SLS launch vehicle.

Charmonium excited state spectrum in lattice QCD

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

Jozef Dudek; Robert Edwards; Nilmani Mathur

2008-02-01

Working with a large basis of covariant derivative-based meson interpolating fields we demonstrate the feasibility of reliably extracting multiple excited states using a variational method. The study is performed on quenched anisotropic lattices with clover quarks at the charm mass. We demonstrate how a knowledge of the continuum limit of a lattice interpolating field can give additional spin-assignment information, even at a single lattice spacing, via the overlap factors of interpolating field and state. Excited state masses are systematically high with respect to quark potential model predictions and, where they exist, experimental states. We conclude that this is most likelymore » a result of the quenched approximation.« less

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure.

PubMed

Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

2017-03-01

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

Atomic Oxygen Erosion Yield Prediction for Spacecraft Polymers in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Backus, Jane A.; Manno, Michael V.; Waters, Deborah L.; Cameron, Kevin C.; deGroh, Kim K.

2009-01-01

The ability to predict the atomic oxygen erosion yield of polymers based on their chemistry and physical properties has been only partially successful because of a lack of reliable low Earth orbit (LEO) erosion yield data. Unfortunately, many of the early experiments did not utilize dehydrated mass loss measurements for erosion yield determination, and the resulting mass loss due to atomic oxygen exposure may have been compromised because samples were often not in consistent states of dehydration during the pre-flight and post-flight mass measurements. This is a particular problem for short duration mission exposures or low erosion yield materials. However, as a result of the retrieval of the Polymer Erosion and Contamination Experiment (PEACE) flown as part of the Materials International Space Station Experiment 2 (MISSE 2), the erosion yields of 38 polymers and pyrolytic graphite were accurately measured. The experiment was exposed to the LEO environment for 3.95 years from August 16, 2001 to July 30, 2005 and was successfully retrieved during a space walk on July 30, 2005 during Discovery s STS-114 Return to Flight mission. The 40 different materials tested (including Kapton H fluence witness samples) were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The MISSE 2 PEACE Polymers experiment used carefully dehydrated mass measurements, as well as accurate density measurements to obtain accurate erosion yield data for high-fluence (8.43 1021 atoms/sq cm). The resulting data was used to develop an erosion yield predictive tool with a correlation coefficient of 0.895 and uncertainty of +/-6.3 10(exp -25)cu cm/atom. The predictive tool utilizes the chemical structures and physical properties of polymers to predict in-space atomic oxygen erosion yields. A predictive tool concept (September 2009 version) is presented which represents an improvement over an earlier (December 2008) version.

Assessing Individual Differences in Adaptation to Extreme Environments: A 36-Hour Sleep Deprivation Study

NASA Technical Reports Server (NTRS)

Martinez, Jacqueline; Cowings, Patricia S.; Toscano, William B.

2012-01-01

In space, astronauts may experience effects of cumulative sleep loss due to demanding work schedules that can result in cognitive performance impairments, mood state deteriorations, and sleep-wake cycle disruption. Individuals who experience sleep deprivation of six hours beyond normal sleep times experience detrimental changes in their mood and performance states. Hence, the potential for life threatening errors increases exponentially with sleep deprivation. We explored the effects of 36-hours of sleep deprivation on cognitive performance, mood states, and physiological responses to identify which metrics may best predict fatigue induced performance decrements of individuals.

On the nonlocal predictions of quantum optics

NASA Technical Reports Server (NTRS)

Marshall, Trevor W.; Santos, Emilio; Vidiella-Barranco, Antonio

1994-01-01

We give a definition of locality in quantum optics based upon Bell's work, and show that locality has been violated in no experiment performed up to now. We argue that the interpretation of the Wigner function as a probability density gives a very attractive local realistic picture of quantum optics provided that this function is nonnegative. We conjecture that this is the case for all states which can be realized in the laboratory. In particular, we believe that the usual representation of 'single photon states' by a Fock state of the Hilbert space is not correct and that a more physical, although less simple mathematically, representation involves density matrices. We study in some detail the experiment showing anticorrelation after a beam splitter and prove that it naturally involves a positive Wigner function. Our (quantum) predictions for this experiment disagree with the ones reported in the literature.

Major Hurricane Matthew Seen from Space on This Week @NASA – October 7, 2016

NASA Image and Video Library

2016-10-07

Cameras outside the International Space Station captured views of Hurricane Matthew during several passes over the major storm, as it made its way north through the Caribbean Sea during the week of Oct. 3. The storm, which reached Category 4 status with winds up to about 145 miles per hour, impacted Haiti, eastern Cuba and the Bahamas. Forecasters predicted Matthew would threaten the southeast coast of the United States, including Florida’s Space Coast. As a precaution, NASA’s Kennedy Space Center closed Oct. 5 after preparing facilities for what could be a direct hit from the storm. Also, One Mars Year of Science for MAVEN, SLS Hardware Being Stacked for Stress Test, Oceans Melting Greenland, Aspira con NASA, and NASA at White House Events!

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

Dunham, Kylee; Grand, James B.

2016-01-01

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence

PubMed Central

McLeish, Tom C. B.

2015-01-01

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity—the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity—essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution. PMID:26640648

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence.

PubMed

McLeish, Tom C B

2015-12-06

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity-the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity-essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution.

Embedding of multidimensional time-dependent observations.

PubMed

Barnard, J P; Aldrich, C; Gerber, M

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Embedding of multidimensional time-dependent observations

NASA Astrophysics Data System (ADS)

Barnard, Jakobus P.; Aldrich, Chris; Gerber, Marius

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Predicting the intensity of recreational use of oak woodland preserves

Treesearch

Sarah E. Reed; Kimberly A. Seymour

2008-01-01

People value proximity and easy access to protected areas in urban landscapes, including state and regional parks, wildlife refuges, and open space preserves. The popularity of outdoor recreation activities such as hiking and birdwatching has more than doubled in the past 20 years, and surveys indicate that proximity to natural areas is an important factor determining...

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems.

PubMed

Ghosh, Soumen; Cramer, Christopher J; Truhlar, Donald G; Gagliardi, Laura

2017-04-01

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e. , systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. We recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functional theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet-triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet-triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.

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-2014-3325

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

GPC-Based Stable Reconfigurable Control

NASA Technical Reports Server (NTRS)

Soloway, Don; Shi, Jian-Jun; Kelkar, Atul

2004-01-01

This paper presents development of multi-input multi-output (MIMO) Generalized Pre-dictive Control (GPC) law and its application to reconfigurable control design in the event of actuator saturation. A Controlled Auto-Regressive Integrating Moving Average (CARIMA) model is used to describe the plant dynamics. The control law is derived using input-output description of the system and is also related to the state-space form of the model. The stability of the GPC control law without reconfiguration is first established using Riccati-based approach and state-space formulation. A novel reconfiguration strategy is developed for the systems which have actuator redundancy and are faced with actuator saturation type failure. An elegant reconfigurable control design is presented with stability proof. Several numerical examples are presented to demonstrate the application of various results.

RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning.

PubMed

Gao, Yujuan; Wang, Sheng; Deng, Minghua; Xu, Jinbo

2018-05-08

Protein dihedral angles provide a detailed description of protein local conformation. Predicted dihedral angles can be used to narrow down the conformational space of the whole polypeptide chain significantly, thus aiding protein tertiary structure prediction. However, direct angle prediction from sequence alone is challenging. In this article, we present a novel method (named RaptorX-Angle) to predict real-valued angles by combining clustering and deep learning. Tested on a subset of PDB25 and the targets in the latest two Critical Assessment of protein Structure Prediction (CASP), our method outperforms the existing state-of-art method SPIDER2 in terms of Pearson Correlation Coefficient (PCC) and Mean Absolute Error (MAE). Our result also shows approximately linear relationship between the real prediction errors and our estimated bounds. That is, the real prediction error can be well approximated by our estimated bounds. Our study provides an alternative and more accurate prediction of dihedral angles, which may facilitate protein structure prediction and functional study.

Orbiting space debris: Dangers, measurement and mitigation

NASA Astrophysics Data System (ADS)

McNutt, Ross T.

1992-06-01

Space debris is a growing environmental problem. Accumulation of objects in earth orbit threatens space systems through the possibility of collisions and runaway debris multiplication. The amount of debris in orbit is uncertain due to the lack of information on the population of debris between 1 and 10 centimeters diameter. Collisions with debris even smaller than 1 cm can be catastrophic due to the high orbital velocities involved. Research efforts are under way at NASA, United States Space Command and the Air Force Phillips Laboratory to detect and catalog the debris population in near-earth space. Current international and national laws are inadequate to control the proliferation of space debris. Space debris is a serious problem with large economic, military, technical and diplomatic components. Actions need to be taken now to: determine the full extent of the orbital debris problem; accurately predict the future evolution of the debris population; decide the extent of the debris mitigation procedures required; implement these policies on a global basis via an international treaty. Action must be initiated now, before the loss of critical space systems such as the space shuttle or the space station.

Phase-space reaction network on a multisaddle energy landscape: HCN isomerization.

PubMed

Li, Chun-Biu; Matsunaga, Yasuhiro; Toda, Mikito; Komatsuzaki, Tamiki

2005-11-08

By using the HCN/CNH isomerization reaction as an illustrative vehicle of chemical reactions on multisaddle energy landscapes, we give explicit visualizations of molecular motions associated with a straight-through reaction tube in the phase space inside which all reactive trajectories pass from one basin to another, with eliminating recrossing trajectories in the configuration space. This visualization provides us with a chemical intuition of how chemical species "walk along" the reaction-rate slope in the multidimensional phase space compared with the intrinsic reaction path in the configuration space. The distinct nonergodic features in the two different HCN and CNH wells can be easily demonstrated by a section of Poincare surface of section in those potential minima, which predicts in a priori the pattern of trajectories residing in the potential well. We elucidate the global phase-space structure which gives rise to the non-Markovian dynamics or the dynamical correlation of sequential multisaddle chemical reactions. The phase-space structure relevant to the controllability of the product state in chemical reactions is also discussed.

Statistical prediction of space motion sickness

NASA Technical Reports Server (NTRS)

Reschke, Millard F.

1990-01-01

Studies designed to empirically examine the etiology of motion sickness to develop a foundation for enhancing its prediction are discussed. Topics addressed include early attempts to predict space motion sickness, multiple test data base that uses provocative and vestibular function tests, and data base subjects; reliability of provocative tests of motion sickness susceptibility; prediction of space motion sickness using linear discriminate analysis; and prediction of space motion sickness susceptibility using the logistic model.

Disease Prediction based on Functional Connectomes using a Scalable and Spatially-Informed Support Vector Machine

PubMed Central

Watanabe, Takanori; Kessler, Daniel; Scott, Clayton; Angstadt, Michael; Sripada, Chandra

2014-01-01

Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D “connectome space,” offering an additional layer of interpretability that could provide new insights about various disease processes. PMID:24704268

Highlights of Space Weather Services/Capabilities at NASA/GSFC Space Weather Center

NASA Technical Reports Server (NTRS)

Fok, Mei-Ching; Zheng, Yihua; Hesse, Michael; Kuznetsova, Maria; Pulkkinen, Antti; Taktakishvili, Aleksandre; Mays, Leila; Chulaki, Anna; Lee, Hyesook

2012-01-01

The importance of space weather has been recognized world-wide. Our society depends increasingly on technological infrastructure, including the power grid as well as satellites used for communication and navigation. Such technologies, however, are vulnerable to space weather effects caused by the Sun's variability. NASA GSFC's Space Weather Center (SWC) (http://science.gsfc.nasa.gov//674/swx services/swx services.html) has developed space weather products/capabilities/services that not only respond to NASA's needs but also address broader interests by leveraging the latest scientific research results and state-of-the-art models hosted at the Community Coordinated Modeling Center (CCMC: http://ccmc.gsfc.nasa.gov). By combining forefront space weather science and models, employing an innovative and configurable dissemination system (iSWA.gsfc.nasa.gov), taking advantage of scientific expertise both in-house and from the broader community as well as fostering and actively participating in multilateral collaborations both nationally and internationally, NASA/GSFC space weather Center, as a sibling organization to CCMC, is poised to address NASA's space weather needs (and needs of various partners) and to help enhancing space weather forecasting capabilities collaboratively. With a large number of state-of-the-art physics-based models running in real-time covering the whole space weather domain, it offers predictive capabilities and a comprehensive view of space weather events throughout the solar system. In this paper, we will provide some highlights of our service products/capabilities. In particular, we will take the 23 January and the 27 January space weather events as examples to illustrate how we can use the iSWA system to track them in the interplanetary space and forecast their impacts.

Real-time validation of receiver state information in optical space-time block code systems.

PubMed

Alamia, John; Kurzweg, Timothy

2014-06-15

Free space optical interconnect (FSOI) systems are a promising solution to interconnect bottlenecks in high-speed systems. To overcome some sources of diminished FSOI performance caused by close proximity of multiple optical channels, multiple-input multiple-output (MIMO) systems implementing encoding schemes such as space-time block coding (STBC) have been developed. These schemes utilize information pertaining to the optical channel to reconstruct transmitted data. The STBC system is dependent on accurate channel state information (CSI) for optimal system performance. As a result of dynamic changes in optical channels, a system in operation will need to have updated CSI. Therefore, validation of the CSI during operation is a necessary tool to ensure FSOI systems operate efficiently. In this Letter, we demonstrate a method of validating CSI, in real time, through the use of moving averages of the maximum likelihood decoder data, and its capacity to predict the bit error rate (BER) of the system.

Closed Loop System Identification with Genetic Algorithms

NASA Technical Reports Server (NTRS)

Whorton, Mark S.

2004-01-01

High performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.

Accelerated testing of space mechanisms

NASA Technical Reports Server (NTRS)

Murray, S. Frank; Heshmat, Hooshang

1995-01-01

This report contains a review of various existing life prediction techniques used for a wide range of space mechanisms. Life prediction techniques utilized in other non-space fields such as turbine engine design are also reviewed for applicability to many space mechanism issues. The development of new concepts on how various tribological processes are involved in the life of the complex mechanisms used for space applications are examined. A 'roadmap' for the complete implementation of a tribological prediction approach for complex mechanical systems including standard procedures for test planning, analytical models for life prediction and experimental verification of the life prediction and accelerated testing techniques are discussed. A plan is presented to demonstrate a method for predicting the life and/or performance of a selected space mechanism mechanical component.

Magnetospheric Multiscale Observation of Plasma Velocity-Space Cascade: Hermite Representation and Theory.

PubMed

Servidio, S; Chasapis, A; Matthaeus, W H; Perrone, D; Valentini, F; Parashar, T N; Veltri, P; Gershman, D; Russell, C T; Giles, B; Fuselier, S A; Phan, T D; Burch, J

2017-11-17

Plasma turbulence is investigated using unprecedented high-resolution ion velocity distribution measurements by the Magnetospheric Multiscale mission (MMS) in the Earth's magnetosheath. This novel observation of a highly structured particle distribution suggests a cascadelike process in velocity space. Complex velocity space structure is investigated using a three-dimensional Hermite transform, revealing, for the first time in observational data, a power-law distribution of moments. In analogy to hydrodynamics, a Kolmogorov approach leads directly to a range of predictions for this phase-space transport. The scaling theory is found to be in agreement with observations. The combined use of state-of-the-art MMS data sets, novel implementation of a Hermite transform method, and scaling theory of the velocity cascade opens new pathways to the understanding of plasma turbulence and the crucial velocity space features that lead to dissipation in plasmas.

Modeling volatility using state space models.

PubMed

Timmer, J; Weigend, A S

1997-08-01

In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict their time evolution adequately, we estimate state space models that explicitly include observational noise. We obtain relaxation times for shocks in the logarithm of volatility ranging from three weeks (for foreign exchange) to three to five months (for stock indices). In most cases, a two-dimensional hidden state is required to yield residuals that are consistent with white noise. We compare these results with ordinary autoregressive models (without a hidden state) and find that autoregressive models underestimate the relaxation times by about two orders of magnitude since they do not distinguish between observational and dynamic noise. This new interpretation of the dynamics of volatility in terms of relaxators in a state space model carries over to stochastic volatility models and to GARCH models, and is useful for several problems in finance, including risk management and the pricing of derivative securities. Data sets used: Olsen & Associates high frequency DEM/USD foreign exchange rates (8 years). Nikkei 225 index (40 years). Dow Jones Industrial Average (25 years).

Experimental investigations, modeling, and analyses of high-temperature devices for space applications: Part 1. Final report, June 1996--December 1998

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

Tournier, J.; El-Genk, M.S.; Huang, L.

1999-01-01

The Institute of Space and Nuclear Power Studies at the University of New Mexico has developed a computer simulation of cylindrical geometry alkali metal thermal-to-electric converter cells using a standard Fortran 77 computer code. The objective and use of this code was to compare the experimental measurements with computer simulations, upgrade the model as appropriate, and conduct investigations of various methods to improve the design and performance of the devices for improved efficiency, durability, and longer operational lifetime. The Institute of Space and Nuclear Power Studies participated in vacuum testing of PX series alkali metal thermal-to-electric converter cells and developedmore » the alkali metal thermal-to-electric converter Performance Evaluation and Analysis Model. This computer model consisted of a sodium pressure loss model, a cell electrochemical and electric model, and a radiation/conduction heat transfer model. The code closely predicted the operation and performance of a wide variety of PX series cells which led to suggestions for improvements to both lifetime and performance. The code provides valuable insight into the operation of the cell, predicts parameters of components within the cell, and is a useful tool for predicting both the transient and steady state performance of systems of cells.« less

Experimental investigations, modeling, and analyses of high-temperature devices for space applications: Part 2. Final report, June 1996--December 1998

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

Tournier, J.; El-Genk, M.S.; Huang, L.

1999-01-01

The Institute of Space and Nuclear Power Studies at the University of New Mexico has developed a computer simulation of cylindrical geometry alkali metal thermal-to-electric converter cells using a standard Fortran 77 computer code. The objective and use of this code was to compare the experimental measurements with computer simulations, upgrade the model as appropriate, and conduct investigations of various methods to improve the design and performance of the devices for improved efficiency, durability, and longer operational lifetime. The Institute of Space and Nuclear Power Studies participated in vacuum testing of PX series alkali metal thermal-to-electric converter cells and developedmore » the alkali metal thermal-to-electric converter Performance Evaluation and Analysis Model. This computer model consisted of a sodium pressure loss model, a cell electrochemical and electric model, and a radiation/conduction heat transfer model. The code closely predicted the operation and performance of a wide variety of PX series cells which led to suggestions for improvements to both lifetime and performance. The code provides valuable insight into the operation of the cell, predicts parameters of components within the cell, and is a useful tool for predicting both the transient and steady state performance of systems of cells.« less

Predicting the magnetic vectors within coronal mass ejections arriving at Earth: 2. Geomagnetic response

NASA Astrophysics Data System (ADS)

Savani, N. P.; Vourlidas, A.; Richardson, I. G.; Szabo, A.; Thompson, B. J.; Pulkkinen, A.; Mays, M. L.; Nieves-Chinchilla, T.; Bothmer, V.

2017-02-01

This is a companion to Savani et al. (2015) that discussed how a first-order prediction of the internal magnetic field of a coronal mass ejection (CME) may be made from observations of its initial state at the Sun for space weather forecasting purposes (Bothmer-Schwenn scheme (BSS) model). For eight CME events, we investigate how uncertainties in their predicted magnetic structure influence predictions of the geomagnetic activity. We use an empirical relationship between the solar wind plasma drivers and Kp index together with the inferred magnetic vectors, to make a prediction of the time variation of Kp (Kp(BSS)). We find a 2σ uncertainty range on the magnetic field magnitude (|B|) provides a practical and convenient solution for predicting the uncertainty in geomagnetic storm strength. We also find the estimated CME velocity is a major source of error in the predicted maximum Kp. The time variation of Kp(BSS) is important for predicting periods of enhanced and maximum geomagnetic activity, driven by southerly directed magnetic fields, and periods of lower activity driven by northerly directed magnetic field. We compare the skill score of our model to a number of other forecasting models, including the NOAA/Space Weather Prediction Center (SWPC) and Community Coordinated Modeling Center (CCMC)/SWRC estimates. The BSS model was the most unbiased prediction model, while the other models predominately tended to significantly overforecast. The True skill score of the BSS prediction model (TSS = 0.43 ± 0.06) exceeds the results of two baseline models and the NOAA/SWPC forecast. The BSS model prediction performed equally with CCMC/SWRC predictions while demonstrating a lower uncertainty.

Density dependence and climate effects in Rocky Mountain elk: an application of regression with instrumental variables for population time series with sampling error.

PubMed

Creel, Scott; Creel, Michael

2009-11-01

1. Sampling error in annual estimates of population size creates two widely recognized problems for the analysis of population growth. First, if sampling error is mistakenly treated as process error, one obtains inflated estimates of the variation in true population trajectories (Staples, Taper & Dennis 2004). Second, treating sampling error as process error is thought to overestimate the importance of density dependence in population growth (Viljugrein et al. 2005; Dennis et al. 2006). 2. In ecology, state-space models are used to account for sampling error when estimating the effects of density and other variables on population growth (Staples et al. 2004; Dennis et al. 2006). In econometrics, regression with instrumental variables is a well-established method that addresses the problem of correlation between regressors and the error term, but requires fewer assumptions than state-space models (Davidson & MacKinnon 1993; Cameron & Trivedi 2005). 3. We used instrumental variables to account for sampling error and fit a generalized linear model to 472 annual observations of population size for 35 Elk Management Units in Montana, from 1928 to 2004. We compared this model with state-space models fit with the likelihood function of Dennis et al. (2006). We discuss the general advantages and disadvantages of each method. Briefly, regression with instrumental variables is valid with fewer distributional assumptions, but state-space models are more efficient when their distributional assumptions are met. 4. Both methods found that population growth was negatively related to population density and winter snow accumulation. Summer rainfall and wolf (Canis lupus) presence had much weaker effects on elk (Cervus elaphus) dynamics [though limitation by wolves is strong in some elk populations with well-established wolf populations (Creel et al. 2007; Creel & Christianson 2008)]. 5. Coupled with predictions for Montana from global and regional climate models, our results predict a substantial reduction in the limiting effect of snow accumulation on Montana elk populations in the coming decades. If other limiting factors do not operate with greater force, population growth rates would increase substantially.

Assessing performance of Bayesian state-space models fit to Argos satellite telemetry locations processed with Kalman filtering.

PubMed

Silva, Mónica A; Jonsen, Ian; Russell, Deborah J F; Prieto, Rui; Thompson, Dave; Baumgartner, Mark F

2014-01-01

Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km) was nearly half that of LS estimates (11.6 ± 8.4 km). Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.

Assessing Performance of Bayesian State-Space Models Fit to Argos Satellite Telemetry Locations Processed with Kalman Filtering

PubMed Central

Silva, Mónica A.; Jonsen, Ian; Russell, Deborah J. F.; Prieto, Rui; Thompson, Dave; Baumgartner, Mark F.

2014-01-01

Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to “true” GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6±5.6 km) was nearly half that of LS estimates (11.6±8.4 km). Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales’ behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates. PMID:24651252

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

NASA Astrophysics Data System (ADS)

Xavier, Marcelo A.; Trimboli, M. Scott

2015-07-01

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models.

Switching Kalman filter for failure prognostic

NASA Astrophysics Data System (ADS)

Lim, Chi Keong Reuben; Mba, David

2015-02-01

The use of condition monitoring (CM) data to predict remaining useful life have been growing with increasing use of health and usage monitoring systems on aircraft. There are many data-driven methodologies available for the prediction and popular ones include artificial intelligence and statistical based approach. The drawback of such approaches is that they require a lot of failure data for training which can be scarce in practice. In lieu of this, methods using state-space and regression-based models that extract information from the data history itself have been explored. However, such methods have their own limitations as they utilize a single time-invariant model which does not represent changing degradation path well. This causes most degradation modeling studies to focus only on segments of their CM data that behaves close to the assumed model. In this paper, a state-space based method; the Switching Kalman Filter (SKF), is adopted for model estimation and life prediction. The SKF approach however, uses multiple models from which the most probable model is inferred from the CM data using Bayesian estimation before it is applied for prediction. At the same time, the inference of the degradation model itself can provide maintainers with more information for their planning. This SKF approach is demonstrated with a case study on gearbox bearings that were found defective from the Republic of Singapore Air Force AH64D helicopter. The use of in-service CM data allows the approach to be applied in a practical scenario and results showed that the developed SKF approach is a promising tool to support maintenance decision-making.

An analytical procedure for evaluating shuttle abort staging aerodynamic characteristics

NASA Technical Reports Server (NTRS)

Meyer, R.

1973-01-01

An engineering analysis and computer code (AERSEP) for predicting Space Shuttle Orbiter - HO Tank longitudinal aerodynamic characteristics during abort separation has been developed. Computed results are applicable at Mach numbers above 2 for angle-of-attack between plus or minus 10 degrees. No practical restrictions on orbiter-tank relative positioning are indicated for tank-under-orbiter configurations. Input data requirements and computer running times are minimal facilitating program use for parametric studies, test planning, and trajectory analysis. In a majority of cases AERSEP Orbiter-Tank interference predictions are as accurate as state-of-the-art estimates for interference-free or isolated-vehicle configurations. AERSEP isolated-orbiter predictions also show excellent correlation with data.

Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space

PubMed Central

Karnik, Rahul; Beer, Michael A.

2015-01-01

The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix) rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs. PMID:26465884

Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space.

PubMed

Karnik, Rahul; Beer, Michael A

2015-01-01

The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix) rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs.

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

Toward a holographic theory for general spacetimes

NASA Astrophysics Data System (ADS)

Nomura, Yasunori; Salzetta, Nico; Sanches, Fabio; Weinberg, Sean J.

2017-04-01

We study a holographic theory of general spacetimes that does not rely on the existence of asymptotic regions. This theory is to be formulated in a holographic space. When a semiclassical description is applicable, the holographic space is assumed to be a holographic screen: a codimension-1 surface that is capable of encoding states of the gravitational spacetime. Our analysis is guided by conjectured relationships between gravitational spacetime and quantum entanglement in the holographic description. To understand basic features of this picture, we catalog predictions for the holographic entanglement structure of cosmological spacetimes. We find that qualitative features of holographic entanglement entropies for such spacetimes differ from those in AdS/CFT but that the former reduce to the latter in the appropriate limit. The Hilbert space of the theory is analyzed, and two plausible structures are found: a direct-sum and "spacetime-equals-entanglement" structure. The former preserves a naive relationship between linear operators and observable quantities, while the latter respects a more direct connection between holographic entanglement and spacetime. We also discuss the issue of selecting a state in quantum gravity, in particular how the state of the multiverse may be selected in the landscape.

State-Space Estimation of Soil Organic Carbon Stock

NASA Astrophysics Data System (ADS)

Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.

2014-04-01

Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.

Development of Reduced-Order Models for Aeroelastic and Flutter Prediction Using the CFL3Dv6.0 Code

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Bartels, Robert E.

2002-01-01

A reduced-order model (ROM) is developed for aeroelastic analysis using the CFL3D version 6.0 computational fluid dynamics (CFD) code, recently developed at the NASA Langley Research Center. This latest version of the flow solver includes a deforming mesh capability, a modal structural definition for nonlinear aeroelastic analyses, and a parallelization capability that provides a significant increase in computational efficiency. Flutter results for the AGARD 445.6 Wing computed using CFL3D v6.0 are presented, including discussion of associated computational costs. Modal impulse responses of the unsteady aerodynamic system are then computed using the CFL3Dv6 code and transformed into state-space form. Important numerical issues associated with the computation of the impulse responses are presented. The unsteady aerodynamic state-space ROM is then combined with a state-space model of the structure to create an aeroelastic simulation using the MATLAB/SIMULINK environment. The MATLAB/SIMULINK ROM is used to rapidly compute aeroelastic transients including flutter. The ROM shows excellent agreement with the aeroelastic analyses computed using the CFL3Dv6.0 code directly.

A Novel Method for Satellite Maneuver Prediction

NASA Astrophysics Data System (ADS)

Shabarekh, C.; Kent-Bryant, J.; Keselman, G.; Mitidis, A.

2016-09-01

A space operations tradecraft consisting of detect-track-characterize-catalog is insufficient for maintaining Space Situational Awareness (SSA) as space becomes increasingly congested and contested. In this paper, we apply analytical methodology from the Geospatial-Intelligence (GEOINT) community to a key challenge in SSA: predicting where and when a satellite may maneuver in the future. We developed a machine learning approach to probabilistically characterize Patterns of Life (PoL) for geosynchronous (GEO) satellites. PoL are repeatable, predictable behaviors that an object exhibits within a context and is driven by spatio-temporal, relational, environmental and physical constraints. An example of PoL are station-keeping maneuvers in GEO which become generally predictable as the satellite re-positions itself to account for orbital perturbations. In an earlier publication, we demonstrated the ability to probabilistically predict maneuvers of the Galaxy 15 (NORAD ID: 28884) satellite with high confidence eight days in advance of the actual maneuver. Additionally, we were able to detect deviations from expected PoL within hours of the predicted maneuver [6]. This was done with a custom unsupervised machine learning algorithm, the Interval Similarity Model (ISM), which learns repeating intervals of maneuver patterns from unlabeled historical observations and then predicts future maneuvers. In this paper, we introduce a supervised machine learning algorithm that works in conjunction with the ISM to produce a probabilistic distribution of when future maneuvers will occur. The supervised approach uses a Support Vector Machine (SVM) to process the orbit state whereas the ISM processes the temporal intervals between maneuvers and the physics-based characteristics of the maneuvers. This multiple model approach capitalizes on the mathematical strengths of each respective algorithm while incorporating multiple features and inputs. Initial findings indicate that the combined approach can predict 70% of maneuver times within 3 days of a true maneuver time and 22% of maneuver times within 24 hours of a maneuver. We have also been able to detect deviations from expected maneuver patterns up to a week in advance.

Transition of planar Couette flow at infinite Reynolds numbers.

PubMed

Itano, Tomoaki; Akinaga, Takeshi; Generalis, Sotos C; Sugihara-Seki, Masako

2013-11-01

An outline of the state space of planar Couette flow at high Reynolds numbers (Re<10^{5}) is investigated via a variety of efficient numerical techniques. It is verified from nonlinear analysis that the lower branch of the hairpin vortex state (HVS) asymptotically approaches the primary (laminar) state with increasing Re. It is also predicted that the lower branch of the HVS at high Re belongs to the stability boundary that initiates a transition to turbulence, and that one of the unstable manifolds of the lower branch of HVS lies on the boundary. These facts suggest HVS may provide a criterion to estimate a minimum perturbation arising transition to turbulent states at the infinite Re limit.

Nonlinear analysis and performance evaluation of the Annular Suspension and Pointing System (ASPS)

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1978-01-01

The Annular Suspension and Pointing System (ASPS) can provide high accurate fine pointing for a variety of solar-, stellar-, and Earth-viewing scientific instruments during space shuttle orbital missions. In this report, a detailed nonlinear mathematical model is developed for the ASPS/Space Shuttle system. The equations are augmented with nonlinear models of components such as magnetic actuators and gimbal torquers. Control systems and payload attitude state estimators are designed in order to obtain satisfactory pointing performance, and statistical pointing performance is predicted in the presence of measurement noise and disturbances.

Thermal finite-element analysis of space shuttle main engine turbine blade

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Tong, Michael T.; Kaufman, Albert

1987-01-01

Finite-element, transient heat transfer analyses were performed for the first-stage blades of the space shuttle main engine (SSME) high-pressure fuel turbopump. The analyses were based on test engine data provided by Rocketdyne. Heat transfer coefficients were predicted by performing a boundary-layer analysis at steady-state conditions with the STAN5 boundary-layer code. Two different peak-temperature overshoots were evaluated for the startup transient. Cutoff transient conditions were also analyzed. A reduced gas temperature profile based on actual thermocouple data was also considered. Transient heat transfer analyses were conducted with the MARC finite-element computer code.

Work Addiction and 21st Century Information Technologies in Traditional and Virtual Work Spaces in the United States

ERIC Educational Resources Information Center

Hunka, Patricia L.

2014-01-01

This study was completed to understand whether or not work addiction or work addiction intensity could be predicted from mobile technology use. The study further investigated whether or not gender, workspace, income, or education level would moderate the relationship. The sample used was drawn from service industry employees who are not in the…

A State Space Model for Spatial Updating of Remembered Visual Targets during Eye Movements

PubMed Central

Mohsenzadeh, Yalda; Dash, Suryadeep; Crawford, J. Douglas

2016-01-01

In the oculomotor system, spatial updating is the ability to aim a saccade toward a remembered visual target position despite intervening eye movements. Although this has been the subject of extensive experimental investigation, there is still no unifying theoretical framework to explain the neural mechanism for this phenomenon, and how it influences visual signals in the brain. Here, we propose a unified state-space model (SSM) to account for the dynamics of spatial updating during two types of eye movement; saccades and smooth pursuit. Our proposed model is a non-linear SSM and implemented through a recurrent radial-basis-function neural network in a dual Extended Kalman filter (EKF) structure. The model parameters and internal states (remembered target position) are estimated sequentially using the EKF method. The proposed model replicates two fundamental experimental observations: continuous gaze-centered updating of visual memory-related activity during smooth pursuit, and predictive remapping of visual memory activity before and during saccades. Moreover, our model makes the new prediction that, when uncertainty of input signals is incorporated in the model, neural population activity and receptive fields expand just before and during saccades. These results suggest that visual remapping and motor updating are part of a common visuomotor mechanism, and that subjective perceptual constancy arises in part from training the visual system on motor tasks. PMID:27242452

The Gtr-Model a Universal Framework for Quantum-Like Measurements

NASA Astrophysics Data System (ADS)

Aerts, Diederik; Bianchi, Massimiliano Sassoli De

We present a very general geometrico-dynamical description of physical or more abstract entities, called the general tension-reduction (GTR) model, where not only states, but also measurement-interactions can be represented, and the associated outcome probabilities calculated. Underlying the model is the hypothesis that indeterminism manifests as a consequence of unavoidable uctuations in the experimental context, in accordance with the hidden-measurements interpretation of quantum mechanics. When the structure of the state space is Hilbertian, and measurements are of the universal kind, i.e., are the result of an average over all possible ways of selecting an outcome, the GTR-model provides the same predictions of the Born rule, and therefore provides a natural completed version of quantum mechanics. However, when the structure of the state space is non-Hilbertian and/or not all possible ways of selecting an outcome are available to be actualized, the predictions of the model generally differ from the quantum ones, especially when sequential measurements are considered. Some paradigmatic examples will be discussed, taken from physics and human cognition. Particular attention will be given to some known psychological effects, like question order effects and response replicability, which we show are able to generate non-Hilbertian statistics. We also suggest a realistic interpretation of the GTR-model, when applied to human cognition and decision, which we think could become the generally adopted interpretative framework in quantum cognition research.

Prediction and generation of binary Markov processes: Can a finite-state fox catch a Markov mouse?

NASA Astrophysics Data System (ADS)

Ruebeck, Joshua B.; James, Ryan G.; Mahoney, John R.; Crutchfield, James P.

2018-01-01

Understanding the generative mechanism of a natural system is a vital component of the scientific method. Here, we investigate one of the fundamental steps toward this goal by presenting the minimal generator of an arbitrary binary Markov process. This is a class of processes whose predictive model is well known. Surprisingly, the generative model requires three distinct topologies for different regions of parameter space. We show that a previously proposed generator for a particular set of binary Markov processes is, in fact, not minimal. Our results shed the first quantitative light on the relative (minimal) costs of prediction and generation. We find, for instance, that the difference between prediction and generation is maximized when the process is approximately independently, identically distributed.

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies.

PubMed

Hansen, Katja; Montavon, Grégoire; Biegler, Franziska; Fazli, Siamac; Rupp, Matthias; Scheffler, Matthias; von Lilienfeld, O Anatole; Tkatchenko, Alexandre; Müller, Klaus-Robert

2013-08-13

The accurate and reliable prediction of properties of molecules typically requires computationally intensive quantum-chemical calculations. Recently, machine learning techniques applied to ab initio calculations have been proposed as an efficient approach for describing the energies of molecules in their given ground-state structure throughout chemical compound space (Rupp et al. Phys. Rev. Lett. 2012, 108, 058301). In this paper we outline a number of established machine learning techniques and investigate the influence of the molecular representation on the methods performance. The best methods achieve prediction errors of 3 kcal/mol for the atomization energies of a wide variety of molecules. Rationales for this performance improvement are given together with pitfalls and challenges when applying machine learning approaches to the prediction of quantum-mechanical observables.

Long-term cryogenic space storage system

NASA Technical Reports Server (NTRS)

Hopkins, R. A.; Chronic, W. L.

1973-01-01

Discussion of the design, fabrication and testing of a 225-cu ft spherical cryogenic storage system for long-term subcritical applications under zero-g conditions in storing subcritical cryogens for space vehicle propulsion systems. The insulation system design, the analytical methods used, and the correlation between the performance test results and analytical predictions are described. The best available multilayer insulation materials and state-of-the-art thermal protection concepts were applied in the design, providing a boiloff rate of 0.152 lb/hr, or 0.032% per day, and an overall heat flux of 0.066 Btu/sq ft hr based on a 200 sq ft surface area. A six to eighteen month cryogenic storage is provided by this system for space applications.

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

Impacts of variability in cellulosic biomass yields on energy security.

PubMed

Mullins, Kimberley A; Matthews, H Scott; Griffin, W Michael; Anex, Robert

2014-07-01

The practice of modeling biomass yields on the basis of deterministic point values aggregated over space and time obscures important risks associated with large-scale biofuel use, particularly risks related to drought-induced yield reductions that may become increasingly frequent under a changing climate. Using switchgrass as a case study, this work quantifies the variability in expected yields over time and space through switchgrass growth modeling under historical and simulated future weather. The predicted switchgrass yields across the United States range from about 12 to 19 Mg/ha, and the 80% confidence intervals range from 20 to 60% of the mean. Average yields are predicted to decrease with increased temperatures and weather variability induced by climate change. Feedstock yield variability needs to be a central part of modeling to ensure that policy makers acknowledge risks to energy supplies and develop strategies or contingency plans that mitigate those risks.

Conformational free energy modeling of druglike molecules by metadynamics in the WHIM space.

PubMed

Spiwok, Vojtěch; Hlat-Glembová, Katarína; Tvaroška, Igor; Králová, Blanka

2012-03-26

Protein-ligand affinities can be significantly influenced not only by the interaction itself but also by conformational equilibrium of both binding partners, free ligand and free protein. Identification of important conformational families of a ligand and prediction of their thermodynamics is important for efficient ligand design. Here we report conformational free energy modeling of nine small-molecule drugs in explicitly modeled water by metadynamics with a bias potential applied in the space of weighted holistic invariant molecular (WHIM) descriptors. Application of metadynamics enhances conformational sampling compared to unbiased molecular dynamics simulation and allows to predict relative free energies of key conformations. Selected free energy minima and one example of transition state were tested by a series of unbiased molecular dynamics simulation. Comparison of free energy surfaces of free and target-bound Imatinib provides an estimate of free energy penalty of conformational change induced by its binding to the target. © 2012 American Chemical Society

A View of Hurricane Katrina with Early 2lSt Century Technology

NASA Technical Reports Server (NTRS)

Lin, Xin; Li, J.-L.; Suarez, M. J.; Tompkins, A. M.; Waliser, D. E.; Rienecker, M. M.; Bacmeister, J.; Jiang, J.; Wu, H.-T.; Tassone, C. M.

2006-01-01

Recent advances in space-borne observations and numerical weather prediction models provide new opportunities for improving hurricane forecasts. In this study, state-of-the-art satellite observations are used to document the evolution of one of the most devastating tropical cyclones ever to hit the United States: Hurricane Katrina. The ECMWF and NASA global high-resolution forecasts, the latter being run in experimental mode, are compared with satellite observations, with a focus on precipitation and cloud processes. Future directions on modeling and observations are briefly discussed.

Solid-state lighting life prediction using extended Kalman filter

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

Lall, Pradeep; Wei, Junchao; Davis, Lynn

2013-07-16

Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. The U.S. Department of Energy has made a long term commitment to advance the efficiency, understandingmore » and development of solid-state lighting (SSL) and is making a strong push for the acceptance and use of SSL products to reduce overall energy consumption attributable to lighting. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of SSL Luminaires from LM-80 test data. The TM-21 model uses an Arrhenius Equation with an Activation Energy, Pre-decay factor and Decay Rates. Several failure mechanisms may be active in a luminaire at a single time causing lumen depreciation. The underlying TM-21 Arrhenius Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, a Kalman Filter and Extended Kalman Filters have been used to develop a 70% Lumen Maintenance Life Prediction Model for a LEDs used in SSL luminaires. This model can be used to calculate acceleration factors, evaluate failure-probability and identify ALT methodologies for reducing test time. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state has been described in state space form using the measurement of the feature vector, velocity of feature vector change and the acceleration of the feature vector change. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.« less

Space Monitoring Data Center at Moscow State University

NASA Astrophysics Data System (ADS)

Kalegaev, Vladimir; Bobrovnikov, Sergey; Barinova, Vera; Myagkova, Irina; Shugay, Yulia; Barinov, Oleg; Dolenko, Sergey; Mukhametdinova, Ludmila; Shiroky, Vladimir

Space monitoring data center of Moscow State University provides operational information on radiation state of the near-Earth space. Internet portal http://swx.sinp.msu.ru/ gives access to the actual data characterizing the level of solar activity, geomagnetic and radiation conditions in the magnetosphere and heliosphere in the real time mode. Operational data coming from space missions (ACE, GOES, ELECTRO-L1, Meteor-M1) at L1, LEO and GEO and from the Earth’s surface are used to represent geomagnetic and radiation state of near-Earth environment. On-line database of measurements is also maintained to allow quick comparison between current conditions and conditions experienced in the past. The models of space environment working in autonomous mode are used to generalize the information obtained from observations on the whole magnetosphere. Interactive applications and operational forecasting services are created on the base of these models. They automatically generate alerts on particle fluxes enhancements above the threshold values, both for SEP and relativistic electrons using data from LEO orbits. Special forecasting services give short-term forecast of SEP penetration to the Earth magnetosphere at low altitudes, as well as relativistic electron fluxes at GEO. Velocities of recurrent high speed solar wind streams on the Earth orbit are predicted with advance time of 3-4 days on the basis of automatic estimation of the coronal hole areas detected on the images of the Sun received from the SDO satellite. By means of neural network approach, Dst and Kp indices online forecasting 0.5-1.5 hours ahead, depending on solar wind and the interplanetary magnetic field, measured by ACE satellite, is carried out. Visualization system allows representing experimental and modeling data in 2D and 3D.

Cost and risk assessment for spacecraft operation decisions caused by the space debris environment

NASA Astrophysics Data System (ADS)

Schaub, Hanspeter; Jasper, Lee E. Z.; Anderson, Paul V.; McKnight, Darren S.

2015-08-01

Space debris is a topic of concern among many in the space community. Most forecasting analyses look centuries into the future to attempt to predict how severe debris densities and fluxes will become in orbit regimes of interest. Conversely, space operators currently do not treat space debris as a major mission hazard. This survey paper outlines the range of cost and risk evaluations a space operator must consider when determining a debris-related response. Beyond the typical direct costs of performing an avoidance maneuver, the total cost including indirect costs, political costs and space environmental costs are discussed. The weights on these costs can vary drastically across mission types and orbit regimes flown. The operator response options during a mission are grouped into four categories: no action, perform debris dodging, follow stricter mitigation, and employ ADR. Current space operations are only considering the no action and debris dodging options, but increasing debris risk will eventually force the stricter mitigation and ADR options. Debris response equilibria where debris-related risks and costs settle on a steady-state solution are hypothesized.

Cascading Failures as Continuous Phase-Space Transitions

DOE PAGES

Yang, Yang; Motter, Adilson E.

2017-12-14

In network systems, a local perturbation can amplify as it propagates, potentially leading to a large-scale cascading failure. We derive a continuous model to advance our understanding of cascading failures in power-grid networks. The model accounts for both the failure of transmission lines and the desynchronization of power generators and incorporates the transient dynamics between successive steps of the cascade. In this framework, we show that a cascade event is a phase-space transition from an equilibrium state with high energy to an equilibrium state with lower energy, which can be suitably described in a closed form using a global Hamiltonian-likemore » function. From this function, we show that a perturbed system cannot always reach the equilibrium state predicted by quasi-steady-state cascade models, which would correspond to a reduced number of failures, and may instead undergo a larger cascade. We also show that, in the presence of two or more perturbations, the outcome depends strongly on the order and timing of the individual perturbations. These results offer new insights into the current understanding of cascading dynamics, with potential implications for control interventions.« less

Capping spheres with scarry crystals: Organizing principles of multi-dislocation, ground-state patterns

NASA Astrophysics Data System (ADS)

Azadi, Amir; Grason, Gregory M.

2014-03-01

Predicting the ground state ordering of curved crystals remains an unsolved, century-old challenge, beginning with the classic Thomson problem to more recent studies of particle-coated droplets. We study the structural features and underlying principles of multi-dislocation ground states of a crystalline cap adhered to a spherical substrate. In the continuum limit, vanishing lattice spacing, a --> 0 , dislocations proliferate and we show that ground states approach a characteristic sequence of patterns of n-fold radial grain boundary ``scars,'' extending from the boundary and terminating in the bulk. A combination of numerical and asymptotic analysis reveals that energetic hierarchy gives rise to a structural hierarchy, whereby the number of dislocation and scars diverge as a --> 0 while the scar length and number of dislocations per scar become remarkably independent of lattice spacing. We show the that structural hierarchy remains intact when n-fold symmetry becomes unstable to polydispersed forked-scar morphologies. We expect this analysis to resolve previously open questions about the optimal symmetries of dislocation patterns in Thomson-like problems, both with and without excess 5-fold defects.

Cross-shell excitations in Si 31

DOE PAGES

Tai, P. -L.; Tabor, S. L.; Lubna, R. S.; ...

2017-07-28

The Si-31 nucleus was produced through the O-18(18O, an) fusion-evaporation reaction at E-lab = 24 MeV. Evaporated a particles from the reaction were detected and identified in the Microball detector array for channel selection. Multiple gamma-ray coincidence events were detected in Gammasphere. The energy and angle information for the alpha particles was used to determine the Si-31 recoil kinematics on an event-by-event basis for a more accurate Doppler correction. A total of 22 new states and 52 new gamma transitions were observed, including 14 from states above the neutron separation energy. The positive-parity states predicted by the shell-model calculations inmore » the sd model space agree well with experiment. The negative-parity states were compared with shell-model calculations in the psdpf model space with some variations in the N = 20 shell gap. The best agreement was found with a shell gap intermediate between that originally used for A approximate to 20 nuclei and that previously adapted for P-32,P-34. This variation suggests the need for a more universal cross-shell interaction.« less

Cascading Failures as Continuous Phase-Space Transitions

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

Yang, Yang; Motter, Adilson E.

In network systems, a local perturbation can amplify as it propagates, potentially leading to a large-scale cascading failure. We derive a continuous model to advance our understanding of cascading failures in power-grid networks. The model accounts for both the failure of transmission lines and the desynchronization of power generators and incorporates the transient dynamics between successive steps of the cascade. In this framework, we show that a cascade event is a phase-space transition from an equilibrium state with high energy to an equilibrium state with lower energy, which can be suitably described in a closed form using a global Hamiltonian-likemore » function. From this function, we show that a perturbed system cannot always reach the equilibrium state predicted by quasi-steady-state cascade models, which would correspond to a reduced number of failures, and may instead undergo a larger cascade. We also show that, in the presence of two or more perturbations, the outcome depends strongly on the order and timing of the individual perturbations. These results offer new insights into the current understanding of cascading dynamics, with potential implications for control interventions.« less

The prediction of a new high-pressure phase of hafnia using first-principles computations

NASA Astrophysics Data System (ADS)

Al-Khatatbeh, Y.; Tarawneh, K.; Hamad, B.

2018-02-01

Using density functional theory (DFT) calculations, we predicted a new high- pressure phase of hafnia (HfO2). We found the hexagonal phase (Ni2In-type structure; space group: P63 /mmc) to be the stable phase at ultrahigh pressures greater than ~386 GPa. Our findings are consistent with recent calculations performed on the similar dioxide ZrO2 [M. Durandurdu, J. Solid State Chem. 230, 233 (2015)] where this phase has been claimed to be the most stable at pressures greater than 380 GPa. The Birch-Murnaghan equation of state (BM- EOS) of the new phase shows that this phase is more compressible and less dense than Fe2P-type phase. Additionally, the hardness calculations using a scaling model confirmed that our newly predicted phase has a similar hardness compared to the other HfO2 phases, indicating that none of the HfO2 phases can be considered to be superhard.

Parse, simulation, and prediction of NOx emission across the Midwestern United States

NASA Astrophysics Data System (ADS)

Fang, H.; Michalski, G. M.; Spak, S.

2017-12-01

Accurately constraining N emissions in space and time has been a challenge for atmospheric scientists. It has been suggested that 15N isotopes may be a way of tracking N emission sources across various spatial and temporal scales. However, the complexity of multiple N sources that can quickly change in intensity has made this a difficult problem. We have used a SMOKE emission model to parse NOx emission across the Midwestern United States for a one-year simulation. An isotope mass balance methods was used to assign 15N values to road, non-road, point, and area sources. The SMOKE emissions and isotope mass balance were then combined to predict the 15N of NOx emissions (Figure 1). This ^15N of NOx emissions model was then incorporated into CMAQ to assess the role of transport and chemistry would impact the 15N value of NOx due to mixing and removal processes. The predicted 15N value of NOx was compared to those in recent measurements of NOx and atmospheric nitrate.

Empirical algorithms to predict aragonite saturation state

NASA Astrophysics Data System (ADS)

Turk, Daniela; Dowd, Michael

2017-04-01

Novel sensor packages deployed on autonomous platforms (Profiling Floats, Gliders, Moorings, SeaCycler) and biogeochemical models have a potential to increase the coverage of a key water chemistry variable, aragonite saturation state (ΩAr) in time and space, in particular in the under sampled regions of global ocean. However, these do not provide the set of inorganic carbon measurements commonly used to derive ΩAr. There is therefore a need to develop regional predictive models to determine ΩAr from measurements of commonly observed or/and non carbonate oceanic variables. Here, we investigate predictive skill of several commonly observed oceanographic variables (temperature, salinity, oxygen, nitrate, phosphate and silicate) in determining ΩAr using climatology and shipboard data. This will allow us to assess potential for autonomous sensors and biogeochemical models to monitor ΩAr regionally and globally. We apply the regression models to several time series data sets and discuss regional differences and their implications for global estimates of ΩAr.

Prediction and verification of creep behavior in metallic materials and components for the space shuttle thermal protection system

NASA Technical Reports Server (NTRS)

Davis, J. W.; Cramer, B. A.

1976-01-01

A method of analysis was developed for predicting permanent cyclic creep deflections in stiffened panel structures. This method uses creep equations based on cyclic tensile creep tests and a computer program to predict panel deflections as a function of mission cycle. Four materials were investigated - a titanium alloy (Ti-6Al-4V), a cobalt alloy (L605), and two nickel alloys (Rene'41 and TDNiCr). Steady-state and cyclic creep response data were obtained by testing tensile specimens fabricated from thin gage sheet (0.025 and 0.63 cm nominal). Steady-state and cyclic creep equations were developed which describe creep as a function of time, temperature and load. Tests were also performed on subsize (6.35 x 30.5 cm) rib and corrugation stiffened panels. These tests were used to correlate creep responses between elemental specimens and panels. The panel response was analyzed by use of a specially written computer program.

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

PubMed

Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

2011-09-01

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.

A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

NASA Astrophysics Data System (ADS)

Matouš, Karel; Geers, Marc G. D.; Kouznetsova, Varvara G.; Gillman, Andrew

2017-02-01

Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.

A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

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

Matouš, Karel, E-mail: kmatous@nd.edu; Geers, Marc G.D.; Kouznetsova, Varvara G.

2017-02-01

Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platformmore » in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.« less

Assessment of Various Flow Solvers Used to Predict the Thermal Environment inside Space Shuttle Solid Rocket Motor Joints

NASA Technical Reports Server (NTRS)

Wang, Qun-Zhen; Cash, Steve (Technical Monitor)

2002-01-01

It is very important to accurately predict the gas pressure, gas and solid temperature, as well as the amount of O-ring erosion inside the space shuttle Reusable Solid Rocket Motor (RSRM) joints in the event of a leak path. The scenarios considered are typically hot combustion gas rapid pressurization events of small volumes through narrow and restricted flow paths. The ideal method for this prediction is a transient three-dimensional computational fluid dynamics (CFD) simulation with a computational domain including both combustion gas and surrounding solid regions. However, this has not yet been demonstrated to be economical for this application due to the enormous amount of CPU time and memory resulting from the relatively long fill time as well as the large pressure and temperature rising rate. Consequently, all CFD applications in RSRM joints so far are steady-state simulations with solid regions being excluded from the computational domain by assuming either a constant wall temperature or no heat transfer between the hot combustion gas and cool solid walls.

Small Engine Technology. Task 4: Advanced Small Turboshaft Compressor (ASTC) Performance and Range Investigation

NASA Technical Reports Server (NTRS)

Hansen, Jeff L.; Delaney, Robert A.

1997-01-01

This contact had two main objectives involving both numerical and experimental investigations of a small highly loaded two-stage axial compressor designated Advanced Small Turboshaft Compressor (ASTC) winch had a design pressure ratio goal of 5:1 at a flowrate of 10.53 lbm/s. The first objective was to conduct 3-D Navier Stokes multistage analyses of the ASTC using several different flow modelling schemes. The second main objective was to complete a numerical/experimental investigation into stall range enhancement of the ASTC. This compressor was designed wider a cooperative Space Act Agreement and all testing was completed at NASA Lewis Research Center. For the multistage analyses, four different flow model schemes were used, namely: (1) steady-state ADPAC analysis, (2) unsteady ADPAC analysis, (3) steady-state APNASA analysis, and (4) steady state OCOM3D analysis. The results of all the predictions were compared to the experimental data. The steady-state ADPAC and APNASA codes predicted similar overall performance and produced good agreement with data, however the blade row performance and flowfield details were quite different. In general, it can be concluded that the APNASA average-passage code does a better job of predicting the performance and flowfield details of the highly loaded ASTC compressor.

Review of ESOC re-entry prediction results of Salyut-7/Kosmos-1686

NASA Technical Reports Server (NTRS)

Klinkrad, H.

1991-01-01

An overview of activities at ESA/ESOC during the followup of the Salyut-7/Kosmos-1686 decay, and of related cooperations with space agencies, research institutes, and national bodies within the ESA Member States, within the U.S. and within the USSR, is presented. A postflight analysis indicated areas for improvement in the forecast procedures, especially during the last day of the orbital lifetime. Corresponding revised decay predictions are presented for Salyut-7/Kosmos-1686, and the improved procedures are verified by an analysis of the reentries of Kosmos-1402A and Kosmos-1402C.

Theoretical predictions of vibration-rotation-tunneling dynamics of the weakly bound trimer (H 2O) 2HCl

NASA Astrophysics Data System (ADS)

Struniewicz, Cezary; Korona, Tatiana; Moszynski, Robert; Milet, Anne

2001-08-01

In this Letter we report a theoretical study of the vibration-rotation-tunneling (VRT) states of the (H 2O) 2HCl trimer. Five degrees of freedom are considered: two angles corresponding to the torsional (flipping) motions of the free, non-hydrogen-bonded, hydrogen atoms in the complex, and three angles describing the overall rotation of the trimer in the space. A two-dimensional potential energy surface is generated ab initio by symmetry-adapted perturbation theory (SAPT). Tunneling splittings, frequencies of the intermolecular vibrations, and vibrational line strengths of spectroscopic transitions are predicted.

A Monte Carlo Analysis of the Thrust Imbalance for the RSRMV Booster During Both the Ignition Transient and Steady State Operation

NASA Technical Reports Server (NTRS)

Foster, Winfred A., Jr.; Crowder, Winston; Steadman, Todd E.

2014-01-01

This paper presents the results of statistical analyses performed to predict the thrust imbalance between two solid rocket motor boosters to be used on the Space Launch System (SLS) vehicle. Two legacy internal ballistics codes developed for the Space Shuttle program were coupled with a Monte Carlo analysis code to determine a thrust imbalance envelope for the SLS vehicle based on the performance of 1000 motor pairs. Thirty three variables which could impact the performance of the motors during the ignition transient and thirty eight variables which could impact the performance of the motors during steady state operation of the motor were identified and treated as statistical variables for the analyses. The effects of motor to motor variation as well as variations between motors of a single pair were included in the analyses. The statistical variations of the variables were defined based on data provided by NASA's Marshall Space Flight Center for the upgraded five segment booster and from the Space Shuttle booster when appropriate. The results obtained for the statistical envelope are compared with the design specification thrust imbalance limits for the SLS launch vehicle

The Predicted Growth of the Low Earth Orbit Space Debris Environment: An Assessment of Future Risk for Spacecraft

NASA Technical Reports Server (NTRS)

Krisko, Paula H.

2007-01-01

Space debris is a worldwide-recognized issue concerning the safety of commercial, military, and exploration spacecraft. The space debris environment includes both naturally occuring meteoroids and objects in Earth orbit that are generated by human activity, termed orbital debris. Space agencies around the world are addressing the dangers of debris collisions to both crewed and robotic spacecraft. In the United States, the Orbital Debris Program Office at the NASA Johnson Space Center leads the effort to categorize debris, predict its growth, and formulate mitigation policy for the environment from low Earth orbit (LEO) through geosynchronous orbit (GEO). This paper presents recent results derived from the NASA long-term debris environment model, LEGEND. It includes the revised NASA sodium potassium droplet model, newly corrected for a factor of two over-estimation of the droplet population. The study indicates a LEO environment that is already highly collisionally active among orbital debris larger than 1 cm in size. Most of the modeled collision events are non-catastrophic (i.e., They lead to a cratering of the target, but no large scale fragmentation.). But they are potentially mission-ending, and take place between impactors smaller than 10 cm and targets larger than 10 cm. Given the small size of the impactor these events would likely be undetectable by present-day measurement means. The activity continues into the future as would be expected. Impact rates of about four per year are predicted by the current study within the next 30 years, with the majority of targets being abandoned intacts (spent upper stages and spacecraft). Still, operational spacecraft do show a small collisional activity, one that increases over time as the small fragment population increases.

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems

DOE PAGES

Ghosh, Soumen; Cramer, Christopher J.; Truhlar, Donald G.; ...

2017-01-19

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e., systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. Here, we recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functionalmore » theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet–triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet–triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.« less

Generalized-active-space pair-density functional theory: an efficient method to study large, strongly correlated, conjugated systems

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

Ghosh, Soumen; Cramer, Christopher J.; Truhlar, Donald G.

Predicting ground- and excited-state properties of open-shell organic molecules by electronic structure theory can be challenging because an accurate treatment has to correctly describe both static and dynamic electron correlation. Strongly correlated systems, i.e., systems with near-degeneracy correlation effects, are particularly troublesome. Multiconfigurational wave function methods based on an active space are adequate in principle, but it is impractical to capture most of the dynamic correlation in these methods for systems characterized by many active electrons. Here, we recently developed a new method called multiconfiguration pair-density functional theory (MC-PDFT), that combines the advantages of wave function theory and density functionalmore » theory to provide a more practical treatment of strongly correlated systems. Here we present calculations of the singlet–triplet gaps in oligoacenes ranging from naphthalene to dodecacene. Calculations were performed for unprecedently large orbitally optimized active spaces of 50 electrons in 50 orbitals, and we test a range of active spaces and active space partitions, including four kinds of frontier orbital partitions. We show that MC-PDFT can predict the singlet–triplet splittings for oligoacenes consistent with the best available and much more expensive methods, and indeed MC-PDFT may constitute the benchmark against which those other models should be compared, given the absence of experimental data.« less

Thermographic Imaging of the Space Shuttle During Re-Entry Using a Near Infrared Sensor

NASA Technical Reports Server (NTRS)

Zalameda, Joseph N.; Horvath, Thomas J.; Kerns, Robbie V.; Burke, Eric R.; Taylor, Jeff C.; Spisz, Tom; Gibson, David M.; Shea, Edward J.; Mercer, C. David; Schwartz, Richard J.;

Physiological Observations and Omics to Develop Personalized Sensormotor Adaptability Countermeasures Using Bed Rest and Space Flight Data

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Seidler, R. D.; Feiveson, A.; Oddsson, L.; Zanello, S.; Oman, C. M.; Ploutz-Snyder, L.; Peters, B.; Cohen, H. S.; Reschke, M.;

Space vehicle acoustics prediction improvement for payloads. [space shuttle

NASA Technical Reports Server (NTRS)

Dandridge, R. E.

1979-01-01

The modal analysis method was extensively modified for the prediction of space vehicle noise reduction in the shuttle payload enclosure, and this program was adapted to the IBM 360 computer. The predicted noise reduction levels for two test cases were compared with experimental results to determine the validity of the analytical model for predicting space vehicle payload noise environments in the 10 Hz one-third octave band regime. The prediction approach for the two test cases generally gave reasonable magnitudes and trends when compared with the measured noise reduction spectra. The discrepancies in the predictions could be corrected primarily by improved modeling of the vehicle structural walls and of the enclosed acoustic space to obtain a more accurate assessment of normal modes. Techniques for improving and expandng the noise prediction for a payload environment are also suggested.

An empirical evaluation of landscape energetic models: Mallard and American black duck space use during the non-breeding period

USGS Publications Warehouse

Beatty, William S.; Webb, Elisabeth B.; Kesler, Dylan C.; Naylor, Luke W.; Raedeke, Andrew H.; Humburg, Dale D.; Coluccy, John M.; Soulliere, G.

2015-01-01

Bird conservation Joint Ventures are collaborative partnerships between public agencies and private organizations that facilitate habitat management to support waterfowl and other bird populations. A subset of Joint Ventures has developed energetic carrying capacity models (ECCs) to translate regional waterfowl population goals into habitat objectives during the non-breeding period. Energetic carrying capacity models consider food biomass, metabolism, and available habitat to estimate waterfowl carrying capacity within an area. To evaluate Joint Venture ECCs in the context of waterfowl space use, we monitored 33 female mallards (Anas platyrhynchos) and 55 female American black ducks (A. rubripes) using global positioning system satellite telemetry in the central and eastern United States. To quantify space use, we measured first-passage time (FPT: time required for an individual to transit across a circle of a given radius) at biologically relevant spatial scales for mallards (3.46 km) and American black ducks (2.30 km) during the non-breeding period, which included autumn migration, winter, and spring migration. We developed a series of models to predict FPT using Joint Venture ECCs and compared them to a biological null model that quantified habitat composition and a statistical null model, which included intercept and random terms. Energetic carrying capacity models predicted mallard space use more efficiently during autumn and spring migrations, but the statistical null was the top model for winter. For American black ducks, ECCs did not improve predictions of space use; the biological null was top ranked for winter and the statistical null was top ranked for spring migration. Thus, ECCs provided limited insight into predicting waterfowl space use during the non-breeding season. Refined estimates of spatial and temporal variation in food abundance, habitat conditions, and anthropogenic disturbance will likely improve ECCs and benefit conservation planners in linking non-breeding waterfowl habitat objectives with distribution and population parameters. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Orbiting space debris: Dangers, measurement, and mitigation

NASA Astrophysics Data System (ADS)

McNutt, Ross T.

1992-01-01

Space debris is a growing environmental problem. Accumulation of objects in Earth orbit threatens space systems through the possibility of collisions and runaway debris multiplication. The amount of debris in orbit is uncertain due to the lack of information on the population of debris between 1 and 10 centimeters diameter. Collisions with debris even smaller than 1 cm can be catastrophic due to the high orbital velocities involved. Research efforts are under way at NASA, Unites States Space Command and the Air Force Phillips Laboratory to detect and catalog the debris population in near-Earth space. Current international and national laws are inadequate to control the proliferation of space debris. Space debris is a serious problem with large economic, military, technical, and diplomatic components. Actions need to be taken now for the following reasons: determine the full extent of the orbital debris problem; accurately predict the future evolution of the debris population; decide the extent of the debris mitigation procedures required; implement these policies on a global basis via an international treaty. Action must be initiated now, before the the loss of critical space systems such as the Space Shuttle or the Space Station.

A two-component rain model for the prediction of attenuation and diversity improvement

NASA Technical Reports Server (NTRS)

Crane, R. K.

1982-01-01

A new model was developed to predict attenuation statistics for a single Earth-satellite or terrestrial propagation path. The model was extended to provide predictions of the joint occurrences of specified or higher attenuation values on two closely spaced Earth-satellite paths. The joint statistics provide the information required to obtain diversity gain or diversity advantage estimates. The new model is meteorologically based. It was tested against available Earth-satellite beacon observations and terrestrial path measurements. The model employs the rain climate region descriptions of the Global rain model. The rms deviation between the predicted and observed attenuation values for the terrestrial path data was 35 percent, a result consistent with the expectations of the Global model when the rain rate distribution for the path is not used in the calculation. Within the United States the rms deviation between measurement and prediction was 36 percent but worldwide it was 79 percent.

Joint Data Assimilation and Parameter Calibration in on-line groundwater modelling using Sequential Monte Carlo techniques

NASA Astrophysics Data System (ADS)

Ramgraber, M.; Schirmer, M.

2017-12-01

As computational power grows and wireless sensor networks find their way into common practice, it becomes increasingly feasible to pursue on-line numerical groundwater modelling. The reconciliation of model predictions with sensor measurements often necessitates the application of Sequential Monte Carlo (SMC) techniques, most prominently represented by the Ensemble Kalman Filter. In the pursuit of on-line predictions it seems advantageous to transcend the scope of pure data assimilation and incorporate on-line parameter calibration as well. Unfortunately, the interplay between shifting model parameters and transient states is non-trivial. Several recent publications (e.g. Chopin et al., 2013, Kantas et al., 2015) in the field of statistics discuss potential algorithms addressing this issue. However, most of these are computationally intractable for on-line application. In this study, we investigate to what extent compromises between mathematical rigour and computational restrictions can be made within the framework of on-line numerical modelling of groundwater. Preliminary studies are conducted in a synthetic setting, with the goal of transferring the conclusions drawn into application in a real-world setting. To this end, a wireless sensor network has been established in the valley aquifer around Fehraltorf, characterized by a highly dynamic groundwater system and located about 20 km to the East of Zürich, Switzerland. By providing continuous probabilistic estimates of the state and parameter distribution, a steady base for branched-off predictive scenario modelling could be established, providing water authorities with advanced tools for assessing the impact of groundwater management practices. Chopin, N., Jacob, P.E. and Papaspiliopoulos, O. (2013): SMC2: an efficient algorithm for sequential analysis of state space models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 75 (3), p. 397-426. Kantas, N., Doucet, A., Singh, S.S., Maciejowski, J., and Chopin, N. (2015): On Particle Methods for Parameter Estimation in State-Space Models. Statistical Science, 30 (3), p. 328.-351.

Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

NASA Astrophysics Data System (ADS)

An, Zhe; Rey, Daniel; Ye, Jingxin; Abarbanel, Henry D. I.

2017-01-01

The problem of forecasting the behavior of a complex dynamical system through analysis of observational time-series data becomes difficult when the system expresses chaotic behavior and the measurements are sparse, in both space and/or time. Despite the fact that this situation is quite typical across many fields, including numerical weather prediction, the issue of whether the available observations are "sufficient" for generating successful forecasts is still not well understood. An analysis by Whartenby et al. (2013) found that in the context of the nonlinear shallow water equations on a β plane, standard nudging techniques require observing approximately 70 % of the full set of state variables. Here we examine the same system using a method introduced by Rey et al. (2014a), which generalizes standard nudging methods to utilize time delayed measurements. We show that in certain circumstances, it provides a sizable reduction in the number of observations required to construct accurate estimates and high-quality predictions. In particular, we find that this estimate of 70 % can be reduced to about 33 % using time delays, and even further if Lagrangian drifter locations are also used as measurements.

NEOPROP: A NEO Propagator for Space Situational Awareness

NASA Astrophysics Data System (ADS)

Zuccarelli, Valentino; Bancelin, David; Weikert, Sven; Thuillot, William; Hestroffer, Daniel; Yabar Valle, Celia; Koschny, Detlef

2013-09-01

The overall aim of the Space Situational Awareness (SSA) Preparatory Programme is to support the European independent utilisation of and access to space for research or services, through providing timely and quality data, information, services and knowledge regarding the environment, the threats and the sustainable exploitation of the outer space surrounding our planet Earth. The SSA system will comprise three main segments:• Space Weather (SWE) monitoring and forecast• Near-Earth Objects (NEO) survey and follow-up• Space Surveillance and Tracking (SST) of man-made space objectsCurrently, there are over 600.000 asteroids known in our Solar System, where more than 9.500 of these are NEOs. These could potentially hit our planet and depending on their size could produce considerable damage. For this reason NEOs deserve active detection and tracking efforts.The role of the SSA programme is to provide warning services against potential asteroid impact hazards, including discovery, identification, orbit prediction and civil alert capabilities. ESA is now working to develop a NEO Coordination Centre which will later evolve into a SSA-NEO Small Bodies Data Centre (SBDC), located at ESA/ESRIN, Italy. The Software prototype developed in the frame of this activity may be later implemented as a part of the SSA-NEO programme simulators aimed at assessing the trajectory of asteroids. There already exist different algorithms to predict orbits for NEOs. The objective of this activity is to come up with a different trajectory prediction algorithm, which allows an independent validation of the current algorithms within the SSA-NEO segment (e.g. NEODyS, JPL Sentry System).The key objective of this activity was to design, develop, test, verify, and validate trajectory prediction algorithm of NEOs in order to be able to computeanalytically and numerically the minimum orbital intersection distances (MOIDs).The NEOPROP software consists of two separate modules/tools:1. The Analytical Module makes use of analytical algorithms in order to rapidly assess the impact risk of a NEO. It is responsible for the preliminary analysis. Orbit Determination algorithms, as the Gauss and the Linear Least Squares (LLS) methods, will determine the initial state (from MPC observations), along with its uncertainty, and the MOID of the NEO (analytically).2. The Numerical Module makes use of numerical algorithms in order to refine and to better assess the impact probabilities. The initial state provided by the orbit determination process will be used to numerically propagate the trajectory. The numerical propagation can be run in two modes: one faster ("fast analysis"), in order to get a fast evaluation of the trajectory and one more precise ("complete analysis") taking into consideration more detailed perturbation models. Moreover, a configurable number of Virtual Asteroids (VAs) will be numerically propagated in order to determine the Earth closest approach. This new "MOID" computation differs from the analytical one since it takes into consideration the full dynamics of the problem.

Advanced Control Algorithms for Compensating the Phase Distortion Due to Transport Delay in Human-Machine Systems

NASA Technical Reports Server (NTRS)

Guo, Liwen; Cardullo, Frank M.; Kelly, Lon C.

2007-01-01

The desire to create more complex visual scenes in modern flight simulators outpaces recent increases in processor speed. As a result, simulation transport delay remains a problem. New approaches for compensating the transport delay in a flight simulator have been developed and are presented in this report. The lead/lag filter, the McFarland compensator and the Sobiski/Cardullo state space filter are three prominent compensators. The lead/lag filter provides some phase lead, while introducing significant gain distortion in the same frequency interval. The McFarland predictor can compensate for much longer delay and cause smaller gain error in low frequencies than the lead/lag filter, but the gain distortion beyond the design frequency interval is still significant, and it also causes large spikes in prediction. Though, theoretically, the Sobiski/Cardullo predictor, a state space filter, can compensate the longest delay with the least gain distortion among the three, it has remained in laboratory use due to several limitations. The first novel compensator is an adaptive predictor that makes use of the Kalman filter algorithm in a unique manner. In this manner the predictor can accurately provide the desired amount of prediction, while significantly reducing the large spikes caused by the McFarland predictor. Among several simplified online adaptive predictors, this report illustrates mathematically why the stochastic approximation algorithm achieves the best compensation results. A second novel approach employed a reference aircraft dynamics model to implement a state space predictor on a flight simulator. The practical implementation formed the filter state vector from the operator s control input and the aircraft states. The relationship between the reference model and the compensator performance was investigated in great detail, and the best performing reference model was selected for implementation in the final tests. Theoretical analyses of data from offline simulations with time delay compensation show that both novel predictors effectively suppress the large spikes caused by the McFarland compensator. The phase errors of the three predictors are not significant. The adaptive predictor yields greater gain errors than the McFarland predictor for short delays (96 and 138 ms), but shows smaller errors for long delays (186 and 282 ms). The advantage of the adaptive predictor becomes more obvious for a longer time delay. Conversely, the state space predictor results in substantially smaller gain error than the other two predictors for all four delay cases.

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

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

Xavier, MA; Trimboli, MS

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggestmore » significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.« less

Prediction of the bottomonium D-wave spectrum from full lattice QCD.

PubMed

Daldrop, J O; Davies, C T H; Dowdall, R J

2012-03-09

We calculate the full spectrum of D-wave states in the Υ system in lattice QCD for the first time, by using an improved version of nonrelativistic QCD on coarse and fine "second-generation" gluon field configurations from the MILC Collaboration that include the effect of up, down, strange, and charm quarks in the sea. By taking the 2S-1S splitting to set the lattice spacing, we determine the (3)D2-1S splitting to 2.3% and find agreement with experiment. Our prediction of the fine structure relative to the (3)D2 gives the (3)D3 at 10.181(5) GeV and the (3)D1 at 10.147(6) GeV. We also discuss the overlap of (3)D1 operators with (3)S1 states.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

PubMed

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

Real time estimation and prediction of ship motions using Kalman filtering techniques

NASA Technical Reports Server (NTRS)

Triantafyllou, M. A.; Bodson, M.; Athans, M.

1982-01-01

A landing scheme for landing V/STOL aircraft on rolling ships was sought using computerized simulations. The equations of motion as derived from hydrodynamics, their form and the physical mechanisms involved and the general form of the approximation are discussed. The modeling of the sea is discussed. The derivation of the state-space equations for the DD-963 destroyer is described. Kalman filter studies are presented and the influence of the various parameters is assessed. The effect of various modeling parameters on the rms error is assessed and simplifying conclusions are drawn. An upper bound for prediction time of about five seconds is established, with the exception of roll, which can be predicted up to ten seconds ahead.

Tethered Satellites as Enabling Platforms for an Operational Space Weather Monitoring System

NASA Technical Reports Server (NTRS)

Krause, L. Habash; Gilchrist, B. E.; Bilen, S.; Owens, J.; Voronka, N.; Furhop, K.

2013-01-01

Space weather nowcasting and forecasting models require assimilation of near-real time (NRT) space environment data to improve the precision and accuracy of operational products. Typically, these models begin with a climatological model to provide "most probable distributions" of environmental parameters as a function of time and space. The process of NRT data assimilation gently pulls the climate model closer toward the observed state (e.g. via Kalman smoothing) for nowcasting, and forecasting is achieved through a set of iterative physics-based forward-prediction calculations. The issue of required space weather observatories to meet the spatial and temporal requirements of these models is a complex one, and we do not address that with this poster. Instead, we present some examples of how tethered satellites can be used to address the shortfalls in our ability to measure critical environmental parameters necessary to drive these space weather models. Examples include very long baseline electric field measurements, magnetized ionospheric conductivity measurements, and the ability to separate temporal from spatial irregularities in environmental parameters. Tethered satellite functional requirements will be presented for each space weather parameter considered in this study.

Microdosemeter instrument (MIDN) for assessing risk in space.

PubMed

Pisacane, V L; Dolecek, Q E; Malak, H; Cucinotta, F A; Zaider, M; Rosenfeld, A B; Rusek, A; Sivertz, M; Dicello, J F

2011-02-01

Radiation in space generally produces higher dose rates than that on the Earth's surface, and contributions from primary galactic and solar events increase with altitude within the magnetosphere. Presently, no personnel monitor is available to astronauts for real-time monitoring of dose, radiation quality and regulatory risk. This group is developing a prototypic instrument for use in an unknown, time-varying radiation field. This microdosemeter-dosemeter nucleon instrument is for use in a spacesuit, spacecraft, remote rover and other applications. It provides absorbed dose, dose rate and dose equivalent in real time so that action can be taken to reduce exposure. Such a system has applications in health physics, anti-terrorism and radiation-hardening of electronics as well. The space system is described and results of ground-based studies are presented and compared with predictions of transport codes. An early prototype in 2007 was successfully launched, the only solid-state microdosemeter to have flown in space.

Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

USGS Publications Warehouse

Archfield, Stacey A.; Pugliese, Alessio; Castellarin, Attilio; Skøien, Jon O.; Kiang, Julie E.

2013-01-01

In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

Space propulsion technology overview

NASA Technical Reports Server (NTRS)

Pelouch, J. J., Jr.

1979-01-01

Chemical and electric propulsion technologies for operations beyond the shuttle's orbit with focus on future mission needs and economic effectiveness is discussed. The adequacy of the existing propulsion state-of-the-art, barriers to its utilization, benefit of technology advances, and the prognosis for advancement are the themes of the discussion. Low-thrust propulsion for large space systems is cited as a new technology with particularly high benefit. It is concluded that the shuttle's presence for at least two decades is a legitimate basis for new propulsion technology, but that this technology must be predicted on an awareness of mission requirements, economic factors, influences of other technologies, and real constraints on its utilization.

Application of the Hilbert space average method on heat conduction models.

PubMed

Michel, Mathias; Gemmer, Jochen; Mahler, Günter

2006-01-01

We analyze closed one-dimensional chains of weakly coupled many level systems, by means of the so-called Hilbert space average method (HAM). Subject to some concrete conditions on the Hamiltonian of the system, our theory predicts energy diffusion with respect to a coarse-grained description for almost all initial states. Close to the respective equilibrium, we investigate this behavior in terms of heat transport and derive the heat conduction coefficient. Thus, we are able to show that both heat (energy) diffusive behavior as well as Fourier's law follows from and is compatible with a reversible Schrödinger dynamics on the complete level of description.

Interface Configuration Experiments (ICE) Explore the Effects of Microgravity on Fluids

NASA Technical Reports Server (NTRS)

1996-01-01

The Interface Configuration Experiment (ICE) is actually a series of experiments that explore the striking behavior of liquid-vapor interfaces (i.e., fluid surfaces) in a low gravity environment under which major shifts in liquid position can arise from small changes in container shape or contact angle. Although these experiments are designed to test current mathematical theory, there are numerous practical applications that could result from these studies. When designing fluid management systems for space-based operations, it is important to be able to predict the locations and configurations that fluids will assume in containers under low-gravity conditions. The increased ability to predict, and hence control, fluid interfaces is vital to systems and/or processes where capillary forces play a significant role both in space and on the Earth. Some of these applications are in general coating processes (paints, pesticides, printing, etc.), fluid transport in porous media (ground water flows, oil recovery, etc.), liquid propellant systems in space (liquid fuel and oxygen), capillary-pumped loops and heat pipes, and space-based life-support systems. In space, almost every fluid system is affected, if not dominated, by capillarity. Knowledge of the liquid-vapor interface behavior, and in particular the interface shape from which any analysis must begin, is required as a foundation to predict how these fluids will react in microgravity and on Earth. With such knowledge, system designs can be optimized, thereby decreasing costs and complexity, while increasing performance and reliability. ICE has increased, and will continue to increase this knowledge, as it probes the specific peculiarities of current theory upon which our current understanding of these effects is based. Several versions of ICE were conducted in NASA Lewis Research Center's drop towers and on the space shuttle during the first and second United States Microgravity Laboratory missions (USML-1 and USML-2). Additional tests are planned for the space shuttle and for the Russian Mir space station. These studies will focus on interfacial problems concerning surface existence, uniqueness, configuration, stability, and flow characteristics.

Smoothing-based compressed state Kalman filter for joint state-parameter estimation: Applications in reservoir characterization and CO2 storage monitoring

NASA Astrophysics Data System (ADS)

Li, Y. J.; Kokkinaki, Amalia; Darve, Eric F.; Kitanidis, Peter K.

2017-08-01

The operation of most engineered hydrogeological systems relies on simulating physical processes using numerical models with uncertain parameters and initial conditions. Predictions by such uncertain models can be greatly improved by Kalman-filter techniques that sequentially assimilate monitoring data. Each assimilation constitutes a nonlinear optimization, which is solved by linearizing an objective function about the model prediction and applying a linear correction to this prediction. However, if model parameters and initial conditions are uncertain, the optimization problem becomes strongly nonlinear and a linear correction may yield unphysical results. In this paper, we investigate the utility of one-step ahead smoothing, a variant of the traditional filtering process, to eliminate nonphysical results and reduce estimation artifacts caused by nonlinearities. We present the smoothing-based compressed state Kalman filter (sCSKF), an algorithm that combines one step ahead smoothing, in which current observations are used to correct the state and parameters one step back in time, with a nonensemble covariance compression scheme, that reduces the computational cost by efficiently exploring the high-dimensional state and parameter space. Numerical experiments show that when model parameters are uncertain and the states exhibit hyperbolic behavior with sharp fronts, as in CO2 storage applications, one-step ahead smoothing reduces overshooting errors and, by design, gives physically consistent state and parameter estimates. We compared sCSKF with commonly used data assimilation methods and showed that for the same computational cost, combining one step ahead smoothing and nonensemble compression is advantageous for real-time characterization and monitoring of large-scale hydrogeological systems with sharp moving fronts.

A Study on Re-entry Predictions of Uncontrolled Space Objects for Space Situational Awareness

NASA Astrophysics Data System (ADS)

Choi, Eun-Jung; Cho, Sungki; Lee, Deok-Jin; Kim, Siwoo; Jo, Jung Hyun

2017-12-01

The key risk analysis technologies for the re-entry of space objects into Earth’s atmosphere are divided into four categories: cataloguing and databases of the re-entry of space objects, lifetime and re-entry trajectory predictions, break-up models after re-entry and multiple debris distribution predictions, and ground impact probability models. In this study, we focused on re- entry prediction, including orbital lifetime assessments, for space situational awareness systems. Re-entry predictions are very difficult and are affected by various sources of uncertainty. In particular, during uncontrolled re-entry, large spacecraft may break into several pieces of debris, and the surviving fragments can be a significant hazard for persons and properties on the ground. In recent years, specific methods and procedures have been developed to provide clear information for predicting and analyzing the re-entry of space objects and for ground-risk assessments. Representative tools include object reentry survival analysis tool (ORSAT) and debris assessment software (DAS) developed by National Aeronautics and Space Administration (NASA), spacecraft atmospheric re-entry and aerothermal break-up (SCARAB) and debris risk assessment and mitigation analysis (DRAMA) developed by European Space Agency (ESA), and semi-analytic tool for end of life analysis (STELA) developed by Centre National d’Etudes Spatiales (CNES). In this study, various surveys of existing re-entry space objects are reviewed, and an efficient re-entry prediction technique is suggested based on STELA, the life-cycle analysis tool for satellites, and DRAMA, a re-entry analysis tool. To verify the proposed method, the re-entry of the Tiangong-1 Space Lab, which is expected to re-enter Earth’s atmosphere shortly, was simulated. Eventually, these results will provide a basis for space situational awareness risk analyses of the re-entry of space objects.

Analysis of helicopter flight dynamics through modeling and simulation of primary flight control actuation system

NASA Astrophysics Data System (ADS)

Nelson, Hunter Barton

A simplified second-order transfer function actuator model used in most flight dynamics applications cannot easily capture the effects of different actuator parameters. The present work integrates a nonlinear actuator model into a nonlinear state space rotorcraft model to determine the effect of actuator parameters on key flight dynamics. The completed actuator model was integrated with a swashplate kinematics where step responses were generated over a range of key hydraulic parameters. The actuator-swashplate system was then introduced into a nonlinear state space rotorcraft simulation where flight dynamics quantities such as bandwidth and phase delay analyzed. Frequency sweeps were simulated for unique actuator configurations using the coupled nonlinear actuator-rotorcraft system. The software package CIFER was used for system identification and compared directly to the linearized models. As the actuator became rate saturated, the effects on bandwidth and phase delay were apparent on the predicted handling qualities specifications.

Measurement of differential cross sections for top quark pair production using the lepton + jets final state in proton-proton collisions at 13 TeV

DOE PAGES

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; ...

2017-05-01

Differential and double-differential cross sections for the production of top quark pairs in proton-proton collisions at 13 TeV are measured as a function of jet multiplicity and of kinematic variables of the top quarks and the top quark-antiquark system. This analysis is based on data collected by the CMS experiment at the LHC corresponding to an integrated luminosity of 2.3 fb –1. The measurements are performed in the lepton+jets decay channels with a single muon or electron in the final state. Furthermore, the differential cross sections are presented at particle level, within a phase space close to the experimental acceptance,more » and at parton level in the full phase space. The results are compared to several standard model predictions.« less

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

Zhao, Luning; Neuscamman, Eric

We present a modification to variational Monte Carlo’s linear method optimization scheme that addresses a critical memory bottleneck while maintaining compatibility with both the traditional ground state variational principle and our recently-introduced variational principle for excited states. For wave function ansatzes with tens of thousands of variables, our modification reduces the required memory per parallel process from tens of gigabytes to hundreds of megabytes, making the methodology a much better fit for modern supercomputer architectures in which data communication and per-process memory consumption are primary concerns. We verify the efficacy of the new optimization scheme in small molecule tests involvingmore » both the Hilbert space Jastrow antisymmetric geminal power ansatz and real space multi-Slater Jastrow expansions. Satisfied with its performance, we have added the optimizer to the QMCPACK software package, with which we demonstrate on a hydrogen ring a prototype approach for making systematically convergent, non-perturbative predictions of Mott-insulators’ optical band gaps.« less

Phase space dynamics and control of the quantum particles associated to hypergraph states

NASA Astrophysics Data System (ADS)

Berec, Vesna

2015-05-01

As today's nanotechnology focus becomes primarily oriented toward production and manipulation of materials at the subatomic level, allowing the performance and complexity of interconnects where the device density accepts more than hundreds devices on a single chip, the manipulation of semiconductor nanostructures at the subatomic level sets its prime tasks on preserving and adequate transmission of information encoded in specified (quantum) states. The presented study employs the quantum communication protocol based on the hypergraph network model where the numerical solutions of equations of motion of quantum particles are associated to vertices (assembled with device chip), which follow specific controllable paths in the phase space. We address these findings towards ultimate quest for prediction and selective control of quantum particle trajectories. In addition, presented protocols could represent valuable tool for reducing background noise and uncertainty in low-dimensional and operationally meaningful, scalable complex systems.

Scaling for hard-sphere colloidal glasses near jamming

NASA Astrophysics Data System (ADS)

Zargar, Rojman; DeGiuli, Eric; Bonn, Daniel

2016-12-01

Hard-sphere colloids are model systems in which to study the glass transition and universal properties of amorphous solids. Using covariance matrix analysis to determine the vibrational modes, we experimentally measure here the scaling behavior of the density of states, shear modulus, and mean-squared displacement (MSD) in a hard-sphere colloidal glass. Scaling the frequency with the boson-peak frequency, we find that the density of states at different volume fractions all collapse on a single master curve, which obeys a power law in terms of the scaled frequency. Below the boson peak, the exponent is consistent with theoretical results obtained by real-space and phase-space approaches to understanding amorphous solids. We find that the shear modulus and the MSD are nearly inversely proportional, and show a singular power-law dependence on the distance from random close packing. Our results are in very good agreement with the theoretical predictions.

New low-energy 0 + state and shape coexistence in Ni 70

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

Prokop, C. J.; Crider, B. P.; Liddick, S. N.

2015-12-01

In recent models, the neutron-rich Ni isotopes around N = 40 are predicted to exhibit multiple low-energy excited 0(+) states attributed to neutron and proton excitations across both the N = 40 and Z = 28 shell gaps. In Ni-68, the three observed 0(+) states have been interpreted in terms of triple shape coexistence between spherical, oblate, and prolate deformed shapes. In the present work a new (0(2)(+)) state at an energy of 1567 keV has been discovered in Ni-70 by using beta-delayed, gamma-ray spectroscopy following the decay of Co-70. The precipitous drop in the energy of the prolate-deformed 0(+)more » level between Ni-68 and Ni-70 with the addition of two neutrons compares favorably with results of Monte Carlo shell-model calculations carried out in the large fpg(9/2)d(5/2) model space, which predict a 0(2)(+) state at 1525 keV in Ni-70. The result extends the shape-coexistence picture in the region to Ni-70 and confirms the importance of the role of the tensor component of the monopole interaction in describing the structure of neutron-rich nuclei.« less

Prediction and warning system of SEP events and solar flares for risk estimation in space launch operations

NASA Astrophysics Data System (ADS)

García-Rigo, Alberto; Núñez, Marlon; Qahwaji, Rami; Ashamari, Omar; Jiggens, Piers; Pérez, Gustau; Hernández-Pajares, Manuel; Hilgers, Alain

2016-07-01

A web-based prototype system for predicting solar energetic particle (SEP) events and solar flares for use by space launch operators is presented. The system has been developed as a result of the European Space Agency (ESA) project SEPsFLAREs (Solar Events Prediction system For space LAunch Risk Estimation). The system consists of several modules covering the prediction of solar flares and early SEP Warnings (labeled Warning tool), the prediction of SEP event occurrence and onset, and the prediction of SEP event peak and duration. In addition, the system acquires data for solar flare nowcasting from Global Navigation Satellite Systems (GNSS)-based techniques (GNSS Solar Flare Detector, GSFLAD and the Sunlit Ionosphere Sudden Total Electron Content Enhancement Detector, SISTED) as additional independent products that may also prove useful for space launch operators.

Extensions and evaluations of a general quantitative theory of forest structure and dynamics

PubMed Central

Enquist, Brian J.; West, Geoffrey B.; Brown, James H.

2009-01-01

Here, we present the second part of a quantitative theory for the structure and dynamics of forests under demographic and resource steady state. The theory is based on individual-level allometric scaling relations for how trees use resources, fill space, and grow. These scale up to determine emergent properties of diverse forests, including size–frequency distributions, spacing relations, canopy configurations, mortality rates, population dynamics, successional dynamics, and resource flux rates. The theory uniquely makes quantitative predictions for both stand-level scaling exponents and normalizations. We evaluate these predictions by compiling and analyzing macroecological datasets from several tropical forests. The close match between theoretical predictions and data suggests that forests are organized by a set of very general scaling rules. Our mechanistic theory is based on allometric scaling relations, is complementary to “demographic theory,” but is fundamentally different in approach. It provides a quantitative baseline for understanding deviations from predictions due to other factors, including disturbance, variation in branching architecture, asymmetric competition, resource limitation, and other sources of mortality, which are not included in the deliberately simplified theory. The theory should apply to a wide range of forests despite large differences in abiotic environment, species diversity, and taxonomic and functional composition. PMID:19363161

RBSURFpred: Modeling protein accessible surface area in real and binary space using regularized and optimized regression.

PubMed

Tarafder, Sumit; Toukir Ahmed, Md; Iqbal, Sumaiya; Tamjidul Hoque, Md; Sohel Rahman, M

2018-03-14

Accessible surface area (ASA) of a protein residue is an effective feature for protein structure prediction, binding region identification, fold recognition problems etc. Improving the prediction of ASA by the application of effective feature variables is a challenging but explorable task to consider, specially in the field of machine learning. Among the existing predictors of ASA, REGAd 3 p is a highly accurate ASA predictor which is based on regularized exact regression with polynomial kernel of degree 3. In this work, we present a new predictor RBSURFpred, which extends REGAd 3 p on several dimensions by incorporating 58 physicochemical, evolutionary and structural properties into 9-tuple peptides via Chou's general PseAAC, which allowed us to obtain higher accuracies in predicting both real-valued and binary ASA. We have compared RBSURFpred for both real and binary space predictions with state-of-the-art predictors, such as REGAd 3 p and SPIDER2. We also have carried out a rigorous analysis of the performance of RBSURFpred in terms of different amino acids and their properties, and also with biologically relevant case-studies. The performance of RBSURFpred establishes itself as a useful tool for the community. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Ensemble Canonical Correlation Prediction of Seasonal Precipitation Over the United States: Raising the Bar for Dynamical Model Forecasts

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, Kyu-Myong; Shen, S. P.

2001-01-01

This paper presents preliminary results of an ensemble canonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into non-overlapping sectors. The canonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all the regions of the US in every season compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible to the enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduces the spring predictability barrier over all the regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and additional local observations. The enhanced ECC forecast skill provides a new benchmark for evaluating dynamical model forecasts.

Fifty Years of Space Weather Forecasting from Boulder

NASA Astrophysics Data System (ADS)

Berger, T. E.

2015-12-01

The first official space weather forecast was issued by the Space Disturbances Laboratory in Boulder, Colorado, in 1965, ushering in an era of operational prediction that continues to this day. Today, the National Oceanic and Atmospheric Administration (NOAA) charters the Space Weather Prediction Center (SWPC) as one of the nine National Centers for Environmental Prediction (NCEP) to provide the nation's official watches, warnings, and alerts of space weather phenomena. SWPC is now integral to national and international efforts to predict space weather events, from the common and mild, to the rare and extreme, that can impact critical technological infrastructure. In 2012, the Strategic National Risk Assessment included extreme space weather events as low-to-medium probability phenomena that could, unlike any other meteorogical phenomena, have an impact on the government's ability to function. Recognizing this, the White House chartered the Office of Science and Technology Policy (OSTP) to produce the first comprehensive national strategy for the prediction, mitigation, and response to an extreme space weather event. The implementation of the National Strategy is ongoing with NOAA, its partners, and stakeholders concentrating on the goal of improving our ability to observe, model, and predict the onset and severity of space weather events. In addition, work continues with the research community to improve our understanding of the physical mechanisms - on the Sun, in the heliosphere, and in the Earth's magnetic field and upper atmosphere - of space weather as well as the effects on critical infrastructure such as electrical power transmission systems. In fifty years, people will hopefully look back at the history of operational space weather prediction and credit our efforts today with solidifying the necessary developments in observational systems, full-physics models of the entire Sun-Earth system, and tools for predicting the impacts to infrastructure to protect against any and all forms of space weather.

Lifetime predictions for the Solar Maximum Mission (SMM) and San Marco spacecraft

NASA Technical Reports Server (NTRS)

Smith, E. A.; Ward, D. T.; Schmitt, M. W.; Phenneger, M. C.; Vaughn, F. J.; Lupisella, M. L.

1989-01-01

Lifetime prediction techniques developed by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) are described. These techniques were developed to predict the Solar Maximum Mission (SMM) spacecraft orbit, which is decaying due to atmospheric drag, with reentry predicted to occur before the end of 1989. Lifetime predictions were also performed for the Long Duration Exposure Facility (LDEF), which was deployed on the 1984 SMM repair mission and is scheduled for retrieval on another Space Transportation System (STS) mission later this year. Concepts used in the lifetime predictions were tested on the San Marco spacecraft, which reentered the Earth's atmosphere on December 6, 1988. Ephemerides predicting the orbit evolution of the San Marco spacecraft until reentry were generated over the final 90 days of the mission when the altitude was less than 380 kilometers. The errors in the predicted ephemerides are due to errors in the prediction of atmospheric density variations over the lifetime of the satellite. To model the time dependence of the atmospheric densities, predictions of the solar flux at the 10.7-centimeter wavelength were used in conjunction with Harris-Priester (HP) atmospheric density tables. Orbital state vectors, together with the spacecraft mass and area, are used as input to the Goddard Trajectory Determination System (GTDS). Propagations proceed in monthly segments, with the nominal atmospheric drag model scaled for each month according to the predicted monthly average value of F10.7. Calibration propagations are performed over a period of known orbital decay to obtain the effective ballistic coefficient. Progagations using plus or minus 2 sigma solar flux predictions are also generated to estimate the despersion in expected reentry dates. Definitive orbits are compared with these predictions as time expases. As updated vectors are received, these are also propagated to reentryto continually update the lifetime predictions.

Emission current from a single micropoint of explosive emission cathode

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

Wu, Ping; Science and Technology on High Power Microwave Laboratory, Northwest Institute of Nuclear Technology, Xi'an 710024; Sun, Jun

Explosive emission cathodes (EECs) are widely used due to their large current. There has been much research on the explosive electron emission mechanism demonstrating that a current density of 10{sup 8}–10{sup 9 }A/cm{sup 2} is necessary for a micropoint to explode in several nanoseconds and the micropoint size is in micron-scale according to the observation of the cathode surface. This paper, however, makes an effort to research the current density and the micropoint size in another way which considers the space charge screening effect. Our model demonstrates that the relativistic effect is insignificant for the micropoint emission due to the smallmore » size of the micropoint and uncovers that the micron-scale size is an intrinsic demand for the micropoint to reach a space charge limited current density of 10{sup 8}–10{sup 9 }A/cm{sup 2}. Meanwhile, our analysis shows that as the voltage increases, the micropoint emission will turn from a field limited state to a space charge limited state, which makes the steady-state micropoint current density independent of the cathode work function and much less dependent on the electric field and the field enhancement factor than that predicted by the Fowler-Nordheim formula.« less

Determination of Thermal State of Charge in Solar Heat Receivers

NASA Technical Reports Server (NTRS)

Glakpe, E. K.; Cannon, J. N.; Hall, C. A., III; Grimmett, I. W.

1996-01-01

The research project at Howard University seeks to develop analytical and numerical capabilities to study heat transfer and fluid flow characteristics, and the prediction of the performance of solar heat receivers for space applications. Specifically, the study seeks to elucidate the effects of internal and external thermal radiation, geometrical and applicable dimensionless parameters on the overall heat transfer in space solar heat receivers. Over the last year, a procedure for the characterization of the state-of-charge (SOC) in solar heat receivers for space applications has been developed. By identifying the various factors that affect the SOC, a dimensional analysis is performed resulting in a number of dimensionless groups of parameters. Although not accomplished during the first phase of the research, data generated from a thermal simulation program can be used to determine values of the dimensionless parameters and the state-of-charge and thereby obtain a correlation for the SOC. The simulation program selected for the purpose is HOTTube, a thermal numerical computer code based on a transient time-explicit, axisymmetric model of the total solar heat receiver. Simulation results obtained with the computer program are presented the minimum and maximum insolation orbits. In the absence of any validation of the code with experimental data, results from HOTTube appear reasonable qualitatively in representing the physical situations modeled.

Waveguide Modulator for Interference Tolerant Functional Near Infrared Spectrometer (fNIRS)

NASA Technical Reports Server (NTRS)

Walton, Joanne; Tin, Padetha; Mackey, Jeffrey

2017-01-01

Many crew-related errors in aviation and astronautics are caused by hazardous cognitive states including overstress, disengagement, high fatigue and ineffective crew coordination. Safety can be improved by monitoring and predicting these cognitive states in a non-intrusive manner and designing mitigation strategies. Measuring hemoglobin concentration changes in the brain with functional Near Infrared Spectroscopy is a promising technique for monitoring cognitive state and optimizing human performance during both space and aviation operations. A compact, wearable fNIRS system would provide an innovative early warning system during long duration missions to detect and prevent vigilance decrements in pilots and astronauts. This effort focused on developing a waveguide modulator for use in a fNIRS system.

En Route Spacing System and Method

NASA Technical Reports Server (NTRS)

Erzberger, Heinz (Inventor); Green, Steven M. (Inventor)

2002-01-01

A method of and computer software for minimizing aircraft deviations needed to comply with an en route miles-in-trail spacing requirement imposed during air traffic control operations via establishing a spacing reference geometry, predicting spatial locations of a plurality of aircraft at a predicted time of intersection of a path of a first of said plurality of aircraft with the spacing reference geometry, and determining spacing of each of the plurality of aircraft based on the predicted spatial locations.

En route spacing system and method

NASA Technical Reports Server (NTRS)

Erzberger, Heinz (Inventor); Green, Steven M. (Inventor)

2002-01-01

A method of and computer software for minimizing aircraft deviations needed to comply with an en route miles-in-trail spacing requirement imposed during air traffic control operations via establishing a spacing reference geometry, predicting spatial locations of a plurality of aircraft at a predicted time of intersection of a path of a first of said plurality of aircraft with the spacing reference geometry, and determining spacing of each of the plurality of aircraft based on the predicted spatial locations.

Deadbeat Predictive Controllers

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh

1997-01-01

Several new computational algorithms are presented to compute the deadbeat predictive control law. The first algorithm makes use of a multi-step-ahead output prediction to compute the control law without explicitly calculating the controllability matrix. The system identification must be performed first and then the predictive control law is designed. The second algorithm uses the input and output data directly to compute the feedback law. It combines the system identification and the predictive control law into one formulation. The third algorithm uses an observable-canonical form realization to design the predictive controller. The relationship between all three algorithms is established through the use of the state-space representation. All algorithms are applicable to multi-input, multi-output systems with disturbance inputs. In addition to the feedback terms, feed forward terms may also be added for disturbance inputs if they are measurable. Although the feedforward terms do not influence the stability of the closed-loop feedback law, they enhance the performance of the controlled system.

Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems

PubMed Central

Lomnitz, Jason G.; Savageau, Michael A.

2016-01-01

Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment, and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1) enumeration of the repertoire of model phenotypes, (2) prediction of values for the parameters for any model phenotype, and (3) analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3, and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between three stable states by transient stimulation through one of two input channels: a positive channel that increases the count, and a negative channel that decreases the count. This example shows the power of these new automated methods to rapidly identify behaviors of interest and efficiently predict parameter values for their realization. These tools may be applied to understand complex natural circuitry and to aid in the rational design of synthetic circuits. PMID:27462346

Entanglement dynamics in critical random quantum Ising chain with perturbations

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

Huang, Yichen, E-mail: ychuang@caltech.edu

We simulate the entanglement dynamics in a critical random quantum Ising chain with generic perturbations using the time-evolving block decimation algorithm. Starting from a product state, we observe super-logarithmic growth of entanglement entropy with time. The numerical result is consistent with the analytical prediction of Vosk and Altman using a real-space renormalization group technique. - Highlights: • We study the dynamical quantum phase transition between many-body localized phases. • We simulate the dynamics of a very long random spin chain with matrix product states. • We observe numerically super-logarithmic growth of entanglement entropy with time.

Near infrared spectroscopy based monitoring of extraction processes of raw material with the help of dynamic predictive modeling

NASA Astrophysics Data System (ADS)

Wang, Haixia; Suo, Tongchuan; Wu, Xiaolin; Zhang, Yue; Wang, Chunhua; Yu, Heshui; Li, Zheng

2018-03-01

The control of batch-to-batch quality variations remains a challenging task for pharmaceutical industries, e.g., traditional Chinese medicine (TCM) manufacturing. One difficult problem is to produce pharmaceutical products with consistent quality from raw material of large quality variations. In this paper, an integrated methodology combining the near infrared spectroscopy (NIRS) and dynamic predictive modeling is developed for the monitoring and control of the batch extraction process of licorice. With the spectra data in hand, the initial state of the process is firstly estimated with a state-space model to construct a process monitoring strategy for the early detection of variations induced by the initial process inputs such as raw materials. Secondly, the quality property of the end product is predicted at the mid-course during the extraction process with a partial least squares (PLS) model. The batch-end-time (BET) is then adjusted accordingly to minimize the quality variations. In conclusion, our study shows that with the help of the dynamic predictive modeling, NIRS can offer the past and future information of the process, which enables more accurate monitoring and control of process performance and product quality.

Instruments for Deep Space Weather Prediction and Science

NASA Astrophysics Data System (ADS)

DeForest, C. E.; Laurent, G.

2018-02-01

We discuss remote space weather monitoring system concepts that could mount on the Deep Space Gateway and provide predictive capability for space weather events including SEP events and CME crossings, and advance heliophysics of the solar wind.

Predictive Feature Selection for Genetic Policy Search

DTIC Science & Technology

2014-05-22

inverted pendulum balancing problem (Gomez and Miikkulainen, 1999), where the agent must learn a policy in a continuous state space using discrete...algorithms to automate the process of training and/or designing NNs, mitigate these drawbacks and allow NNs to be easily applied to RL domains (Sher, 2012...racing simulator and the double inverted pendulum balance environments. It also includes parameter settings for all algorithms included in the study

Replacement Capability Options for the United States Space Shuttle

DTIC Science & Technology

2013-09-01

extended periods, and to expand our knowledge of solar astronomy well beyond Earth-based observations.” During the Skylab missions, both the man...determined Skylab’s orbit was no longer stable due to higher than predicted solar activity. Therefore, Skylab had to be de-orbited earlier than...Module houses the oxygen, life support, power, communications, thermal control, and propulsions systems. The solar arrays for the Soyuz are also

Evaluation of the 29-km Eta Model for Weather Support to the United States Space Program

NASA Technical Reports Server (NTRS)

Manobianco, John; Nutter, Paul

1997-01-01

The Applied Meteorology Unit (AMU) conducted a year-long evaluation of NCEP's 29-km mesoscale Eta (meso-eta) weather prediction model in order to identify added value to forecast operations in support of the United States space program. The evaluation was stratified over warm and cool seasons and considered both objective and subjective verification methodologies. Objective verification results generally indicate that meso-eta model point forecasts at selected stations exhibit minimal error growth in terms of RMS errors and are reasonably unbiased. Conversely, results from the subjective verification demonstrate that model forecasts of developing weather events such as thunderstorms, sea breezes, and cold fronts, are not always as accurate as implied by the seasonal error statistics. Sea-breeze case studies reveal that the model generates a dynamically-consistent thermally direct circulation over the Florida peninsula, although at a larger scale than observed. Thunderstorm verification reveals that the meso-eta model is capable of predicting areas of organized convection, particularly during the late afternoon hours but is not capable of forecasting individual thunderstorms. Verification of cold fronts during the cool season reveals that the model is capable of forecasting a majority of cold frontal passages through east central Florida to within +1-h of observed frontal passage.

The transition from the open minimum to the ring minimum on the ground state and on the lowest excited state of like symmetry in ozone: A configuration interaction study

DOE PAGES

Theis, Daniel; Ivanic, Joseph; Windus, Theresa L.; ...

2016-03-10

The metastable ring structure of the ozone 1 1A 1 ground state, which theoretical calculations have shown to exist, has so far eluded experimental detection. An accurate prediction for the energy difference between this isomer and the lower open structure is therefore of interest, as is a prediction for the isomerization barrier between them, which results from interactions between the lowest two 1A 1 states. In the present work, valence correlated energies of the 1 1A 1 state and the 2 1A 1 state were calculated at the 1 1A 1 open minimum, the 1 1A 1 ring minimum, themore » transition state between these two minima, the minimum of the 2 1A 1 state, and the conical intersection between the two states. The geometries were determined at the full-valence multi-configuration self-consistent-field level. Configuration interaction (CI) expansions up to quadruple excitations were calculated with triple-zeta atomic basis sets. The CI expansions based on eight different reference configuration spaces were explored. To obtain some of the quadruple excitation energies, the method of CorrelationEnergy Extrapolation by Intrinsic Scaling was generalized to the simultaneous extrapolation for two states. This extrapolation method was shown to be very accurate. On the other hand, none of the CI expansions were found to have converged to millihartree (mh) accuracy at the quadruple excitation level. The data suggest that convergence to mh accuracy is probably attained at the sextuple excitation level. On the 11A1 state, the present calculations yield the estimates of (ring minimum—open minimum) ~45–50 mh and (transition state—open minimum) ~85–90 mh. For the (2 1A 1– 1A 1) excitation energy, the estimate of ~130–170 mh is found at the open minimum and 270–310 mh at the ring minimum. At the transition state, the difference (2 1A 1– 1A 1) is found to be between 1 and 10 mh. The geometry of the transition state on the 11A1 surface and that of the minimum on the 2 1A 1 surface nearly coincide. More accurate predictions of the energydifferences also require CI expansions to at least sextuple excitations with respect to the valence space. Furthermore, for every wave function considered, the omission of the correlations of the 2s oxygen orbitals, which is a widely used approximation, was found to cause errors of about ±10 mh with respect to the energy differences.« less

The transition from the open minimum to the ring minimum on the ground state and on the lowest excited state of like symmetry in ozone: A configuration interaction study

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

Theis, Daniel; Ivanic, Joseph; Windus, Theresa L.

The metastable ring structure of the ozone 1 1A 1 ground state, which theoretical calculations have shown to exist, has so far eluded experimental detection. An accurate prediction for the energy difference between this isomer and the lower open structure is therefore of interest, as is a prediction for the isomerization barrier between them, which results from interactions between the lowest two 1A 1 states. In the present work, valence correlated energies of the 1 1A 1 state and the 2 1A 1 state were calculated at the 1 1A 1 open minimum, the 1 1A 1 ring minimum, themore » transition state between these two minima, the minimum of the 2 1A 1 state, and the conical intersection between the two states. The geometries were determined at the full-valence multi-configuration self-consistent-field level. Configuration interaction (CI) expansions up to quadruple excitations were calculated with triple-zeta atomic basis sets. The CI expansions based on eight different reference configuration spaces were explored. To obtain some of the quadruple excitation energies, the method of CorrelationEnergy Extrapolation by Intrinsic Scaling was generalized to the simultaneous extrapolation for two states. This extrapolation method was shown to be very accurate. On the other hand, none of the CI expansions were found to have converged to millihartree (mh) accuracy at the quadruple excitation level. The data suggest that convergence to mh accuracy is probably attained at the sextuple excitation level. On the 11A1 state, the present calculations yield the estimates of (ring minimum—open minimum) ~45–50 mh and (transition state—open minimum) ~85–90 mh. For the (2 1A 1– 1A 1) excitation energy, the estimate of ~130–170 mh is found at the open minimum and 270–310 mh at the ring minimum. At the transition state, the difference (2 1A 1– 1A 1) is found to be between 1 and 10 mh. The geometry of the transition state on the 11A1 surface and that of the minimum on the 2 1A 1 surface nearly coincide. More accurate predictions of the energydifferences also require CI expansions to at least sextuple excitations with respect to the valence space. Furthermore, for every wave function considered, the omission of the correlations of the 2s oxygen orbitals, which is a widely used approximation, was found to cause errors of about ±10 mh with respect to the energy differences.« less

Real-time 3-D space numerical shake prediction for earthquake early warning

NASA Astrophysics Data System (ADS)

Wang, Tianyun; Jin, Xing; Huang, Yandan; Wei, Yongxiang

2017-12-01

In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of source parameters. For computation efficiency, wave direction is assumed to propagate on the 2-D surface of the earth in these methods. In fact, since the seismic wave propagates in the 3-D sphere of the earth, the 2-D space modeling of wave direction results in inaccurate wave estimation. In this paper, we propose a 3-D space numerical shake prediction method, which simulates the wave propagation in 3-D space using radiative transfer theory, and incorporate data assimilation technique to estimate the distribution of wave energy. 2011 Tohoku earthquake is studied as an example to show the validity of the proposed model. 2-D space model and 3-D space model are compared in this article, and the prediction results show that numerical shake prediction based on 3-D space model can estimate the real-time ground motion precisely, and overprediction is alleviated when using 3-D space model.

Models of Solar Wind Structures and Their Interaction with the Earth's Space Environment

NASA Astrophysics Data System (ADS)

Watermann, J.; Wintoft, P.; Sanahuja, B.; Saiz, E.; Poedts, S.; Palmroth, M.; Milillo, A.; Metallinou, F.-A.; Jacobs, C.; Ganushkina, N. Y.; Daglis, I. A.; Cid, C.; Cerrato, Y.; Balasis, G.; Aylward, A. D.; Aran, A.

2009-11-01

The discipline of “Space Weather” is built on the scientific foundation of solar-terrestrial physics but with a strong orientation toward applied research. Models describing the solar-terrestrial environment are therefore at the heart of this discipline, for both physical understanding of the processes involved and establishing predictive capabilities of the consequences of these processes. Depending on the requirements, purely physical models, semi-empirical or empirical models are considered to be the most appropriate. This review focuses on the interaction of solar wind disturbances with geospace. We cover interplanetary space, the Earth’s magnetosphere (with the exception of radiation belt physics), the ionosphere (with the exception of radio science), the neutral atmosphere and the ground (via electromagnetic induction fields). Space weather relevant state-of-the-art physical and semi-empirical models of the various regions are reviewed. They include models for interplanetary space, its quiet state and the evolution of recurrent and transient solar perturbations (corotating interaction regions, coronal mass ejections, their interplanetary remnants, and solar energetic particle fluxes). Models of coupled large-scale solar wind-magnetosphere-ionosphere processes (global magnetohydrodynamic descriptions) and of inner magnetosphere processes (ring current dynamics) are discussed. Achievements in modeling the coupling between magnetospheric processes and the neutral and ionized upper and middle atmospheres are described. Finally we mention efforts to compile comprehensive and flexible models from selections of existing modules applicable to particular regions and conditions in interplanetary space and geospace.

Earthquakes triggered by fluid extraction

USGS Publications Warehouse

Segall, P.

1989-01-01

Seismicity is correlated in space and time with production from some oil and gas fields where pore pressures have declined by several tens of megapascals. Reverse faulting has occurred both above and below petroleum reservoirs, and normal faulting has occurred on the flanks of at least one reservoir. The theory of poroelasticity requires that fluid extraction locally alter the state of stress. Calculations with simple geometries predict stress perturbations that are consistent with observed earthquake locations and focal mechanisms. Measurements of surface displacement and strain, pore pressure, stress, and poroelastic rock properties in such areas could be used to test theoretical predictions and improve our understanding of earthquake mechanics. -Author

New Predictive Filters for Compensating the Transport Delay on a Flight Simulator

NASA Technical Reports Server (NTRS)

Guo, Liwen; Cardullo, Frank M.; Houck, Jacob A.; Kelly, Lon C.; Wolters, Thomas E.

2004-01-01

The problems of transport delay in a flight simulator, such as its sources and effects, are reviewed. Then their effects on a pilot-in-the-loop control system are investigated with simulations. Three current prominent delay compensators the lead/lag filter, McFarland filter, and the Sobiski/Cardullo filter were analyzed and compared. This paper introduces two novel delay compensation techniques an adaptive predictor using the Kalman estimator and a state space predictive filter using a reference aerodynamic model. Applications of these two new compensators on recorded data from the NASA Langley Research Center Visual Motion Simulator show that they achieve better compensation over the current ones.

Investigation of SSME alternate high pressure fuel turbopump lift-off seal fluid and structural dynamic interaction

NASA Technical Reports Server (NTRS)

Elrod, David A.

1989-01-01

The Space Shuttle main engine (SSME) alternate turbopump development program (ATD) high pressure fuel turbopump (HPFTP) design utilizes an innovative lift-off seal (LOS) design that is located in close proximity to the turbine end bearing. Cooling flow exiting the bearing passes through the lift-off seal during steady state operation. The potential for fluid excitation of lift-off seal structural resonances is investigated. No fluid excitation of LOS resonances is predicted. However, if predicted LOS natural frequencies are significantly lowered by the presence of the coolant, pressure oscillations caused by synchronous whirl of the HPFTP rotor may excite a resonance.

Quantum Foam

ScienceCinema

Lincoln, Don

2018-01-16

The laws of quantum mechanics and relativity are quite perplexing however it is when the two theories are merged that things get really confusing. This combined theory predicts that empty space isn’t empty at all – it’s a seething and bubbling cauldron of matter and antimatter particles springing into existence before disappearing back into nothingness. Scientists call this complicated state of affairs “quantum foam.” In this video, Fermilab’s Dr. Don Lincoln discusses this mind-bending idea and sketches some of the experiments that have convinced scientists that this crazy prediction is actually true.

Specification of the near-Earth space environment with SHIELDS

DOE PAGES

Jordanova, Vania Koleva; Delzanno, Gian Luca; Henderson, Michael Gerard; ...

2017-11-26

Here, predicting variations in the near-Earth space environment that can lead to spacecraft damage and failure is one example of “space weather” and a big space physics challenge. A project recently funded through the Los Alamos National Laboratory (LANL) Directed Research and Development (LDRD) program aims at developing a new capability to understand, model, and predict Space Hazards Induced near Earth by Large Dynamic Storms, the SHIELDS framework. The project goals are to understand the dynamics of the surface charging environment (SCE), the hot (keV) electrons representing the source and seed populations for the radiation belts, on both macro- andmore » micro-scale. Important physics questions related to particle injection and acceleration associated with magnetospheric storms and substorms, as well as plasma waves, are investigated. These challenging problems are addressed using a team of world-class experts in the fields of space science and computational plasma physics, and state-of-the-art models and computational facilities. A full two-way coupling of physics-based models across multiple scales, including a global MHD (BATS-R-US) embedding a particle-in-cell (iPIC3D) and an inner magnetosphere (RAM-SCB) codes, is achieved. New data assimilation techniques employing in situ satellite data are developed; these provide an order of magnitude improvement in the accuracy in the simulation of the SCE. SHIELDS also includes a post-processing tool designed to calculate the surface charging for specific spacecraft geometry using the Curvilinear Particle-In-Cell (CPIC) code that can be used for reanalysis of satellite failures or for satellite design.« less

Specification of the near-Earth space environment with SHIELDS

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

Jordanova, Vania Koleva; Delzanno, Gian Luca; Henderson, Michael Gerard

Here, predicting variations in the near-Earth space environment that can lead to spacecraft damage and failure is one example of “space weather” and a big space physics challenge. A project recently funded through the Los Alamos National Laboratory (LANL) Directed Research and Development (LDRD) program aims at developing a new capability to understand, model, and predict Space Hazards Induced near Earth by Large Dynamic Storms, the SHIELDS framework. The project goals are to understand the dynamics of the surface charging environment (SCE), the hot (keV) electrons representing the source and seed populations for the radiation belts, on both macro- andmore » micro-scale. Important physics questions related to particle injection and acceleration associated with magnetospheric storms and substorms, as well as plasma waves, are investigated. These challenging problems are addressed using a team of world-class experts in the fields of space science and computational plasma physics, and state-of-the-art models and computational facilities. A full two-way coupling of physics-based models across multiple scales, including a global MHD (BATS-R-US) embedding a particle-in-cell (iPIC3D) and an inner magnetosphere (RAM-SCB) codes, is achieved. New data assimilation techniques employing in situ satellite data are developed; these provide an order of magnitude improvement in the accuracy in the simulation of the SCE. SHIELDS also includes a post-processing tool designed to calculate the surface charging for specific spacecraft geometry using the Curvilinear Particle-In-Cell (CPIC) code that can be used for reanalysis of satellite failures or for satellite design.« less

Quantum correlations are weaved by the spinors of the Euclidean primitives

PubMed Central

2018-01-01

The exceptional Lie group E8 plays a prominent role in both mathematics and theoretical physics. It is the largest symmetry group associated with the most general possible normed division algebra, namely, that of the non-associative real octonions, which—thanks to their non-associativity—form the only possible closed set of spinors (or rotors) that can parallelize the 7-sphere. By contrast, here we show how a similar 7-sphere also arises naturally from the algebraic interplay of the graded Euclidean primitives, such as points, lines, planes and volumes, which characterize the three-dimensional conformal geometry of the ambient physical space, set within its eight-dimensional Clifford-algebraic representation. Remarkably, the resulting algebra remains associative, and allows us to understand the origins and strengths of all quantum correlations locally, in terms of the geometry of the compactified physical space, namely, that of a quaternionic 3-sphere, S3, with S7 being its algebraic representation space. Every quantum correlation can thus be understood as a correlation among a set of points of this S7, computed using manifestly local spinors within S3, thereby extending the stringent bounds of ±2 set by Bell inequalities to the bounds of ±22 on the strengths of all possible strong correlations, in the same quantitatively precise manner as that predicted within quantum mechanics. The resulting geometrical framework thus overcomes Bell’s theorem by producing a strictly deterministic and realistic framework that allows a locally causal understanding of all quantum correlations, without requiring either remote contextuality or backward causation. We demonstrate this by first proving a general theorem concerning the geometrical origins of the correlations predicted by arbitrarily entangled quantum states, and then reproducing the correlations predicted by the EPR-Bohm and the GHZ states. The raison d’être of strong correlations turns out to be the Möbius-like twists in the Hopf bundles of S3 and S7. PMID:29893385

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions

PubMed Central

Lehnert, Teresa; Timme, Sandra; Pollmächer, Johannes; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-01-01

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation. PMID:26150807

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions.

PubMed

Lehnert, Teresa; Timme, Sandra; Pollmächer, Johannes; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-01-01

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation.

Plasma physics and the 2013-2022 decadal survey in solar and space physics

NASA Astrophysics Data System (ADS)

Baker, Daniel N.

2016-11-01

The U.S. National Academies established in 2011 a steering committee to develop a comprehensive strategy for solar and space physics research. This updated and extended the first (2003) solar and space physics decadal survey. The latest decadal study implemented a 2008 Congressional directive to NASA for the fields of solar and space physics, but also addressed research in other federal agencies. The new survey broadly canvassed the fields of research to determine the current state of the discipline, identified the most important open scientific questions, and proposed the measurements and means to obtain them so as to advance the state of knowledge during the years 2013-2022. Research in this field has sought to understand: dynamical behaviour of the Sun and its heliosphere; properties of the space environments of the Earth and other solar system bodies; multiscale interaction between solar system plasmas and the interstellar medium; and energy transport throughout the solar system and its impact on the Earth and other solar system bodies. Research in solar and space plasma processes using observation, theory, laboratory studies, and numerical models has offered the prospect of understanding this interconnected system well enough to develop a predictive capability for operational support of civil and military space systems. We here describe the recommendations and strategic plans laid out in the 2013-2022 decadal survey as they relate to measurement capabilities and plasma physical research. We assess progress to date. We also identify further steps to achieve the Survey goals with an emphasis on plasma physical aspects of the program.

Stationary to nonstationary transition in crossed-field devices

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

Marini, Samuel; Rizzato, Felipe B.; Pakter, Renato

2016-03-15

The previous results based on numerical simulations showed that a cold electron beam injected in a crossed field gap does not reach a time independent stationary state in the space charge limited regime [P. J. Christenson and Y. Y. Lau, Phys. Plasmas 1, 3725 (1994)]. In this work, the effect of finite injection temperature in the transition from stationary to nonstationary states is investigated. A fully kinetic model for the electron flow is derived and used to determine the possible stationary states of the system. It is found that although there is always a stationary solution for any set ofmore » parameters, depending on the injection temperature the electron flow becomes very sensitive to fluctuations and the stationary state is never reached. By investigating the nonlinear dynamics of a characteristic electron, a theory based on a single free parameter is constructed to predict when the transition between stationary and nonstationary states occurs. In agreement with the previous numerical results, the theory indicates that for vanishing temperatures the system never reaches the time independent stationary state in the space charge limited regime. Nevertheless, as the injection temperature is raised it is found a broad range of system parameters for which the stationary state is indeed attained. By properly adjusting the free parameter in the theory, one can be able to describe, to a very good accuracy, when the transition occurs.« less

Association with humans and seasonality interact to reverse predictions for animal space use.

PubMed

Laver, Peter N; Alexander, Kathleen A

2018-01-01

Variation in animal space use reflects fitness trade-offs associated with ecological constraints. Associated theories such as the metabolic theory of ecology and the resource dispersion hypothesis generate predictions about what drives variation in animal space use. But, metabolic theory is usually tested in macro-ecological studies and is seldom invoked explicitly in within-species studies. Full evaluation of the resource dispersion hypothesis requires testing in more species. Neither have been evaluated in the context of anthropogenic landscape change. In this study, we used data for banded mongooses ( Mungos mungo ) in northeastern Botswana, along a gradient of association with humans, to test for effects of space use drivers predicted by these theories. We used Bayesian parameter estimation and inference from linear models to test for seasonal differences in space use metrics and to model seasonal effects of space use drivers. Results suggest that space use is strongly associated with variation in the level of overlap that mongoose groups have with humans. Seasonality influences this association, reversing seasonal space use predictions historically-accepted by ecologists. We found support for predictions of the metabolic theory when moderated by seasonality, by association with humans and by their interaction. Space use of mongooses living in association with humans was more concentrated in the dry season than the wet season, when historically-accepted ecological theory predicted more dispersed space use. Resource richness factors such as building density were associated with space use only during the dry season. We found negligible support for predictions of the resource dispersion hypothesis in general or for metabolic theory where seasonality and association with humans were not included. For mongooses living in association with humans, space use was not associated with patch dispersion or group size over both seasons. In our study, living in association with humans influenced space use patterns that diverged from historically-accepted predictions. There is growing need to explicitly incorporate human-animal interactions into ecological theory and research. Our results and methodology may contribute to understanding effects of anthropogenic landscape change on wildlife populations.

Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

PubMed Central

Sikosek, Tobias; Bornberg-Bauer, Erich; Chan, Hue Sun

2012-01-01

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed. PMID:23028272

Space-time measurements of oceanic sea states

NASA Astrophysics Data System (ADS)

Fedele, Francesco; Benetazzo, Alvise; Gallego, Guillermo; Shih, Ping-Chang; Yezzi, Anthony; Barbariol, Francesco; Ardhuin, Fabrice

2013-10-01

Stereo video techniques are effective for estimating the space-time wave dynamics over an area of the ocean. Indeed, a stereo camera view allows retrieval of both spatial and temporal data whose statistical content is richer than that of time series data retrieved from point wave probes. We present an application of the Wave Acquisition Stereo System (WASS) for the analysis of offshore video measurements of gravity waves in the Northern Adriatic Sea and near the southern seashore of the Crimean peninsula, in the Black Sea. We use classical epipolar techniques to reconstruct the sea surface from the stereo pairs sequentially in time, viz. a sequence of spatial snapshots. We also present a variational approach that exploits the entire data image set providing a global space-time imaging of the sea surface, viz. simultaneous reconstruction of several spatial snapshots of the surface in order to guarantee continuity of the sea surface both in space and time. Analysis of the WASS measurements show that the sea surface can be accurately estimated in space and time together, yielding associated directional spectra and wave statistics at a point in time that agrees well with probabilistic models. In particular, WASS stereo imaging is able to capture typical features of the wave surface, especially the crest-to-trough asymmetry due to second order nonlinearities, and the observed shape of large waves are fairly described by theoretical models based on the theory of quasi-determinism (Boccotti, 2000). Further, we investigate space-time extremes of the observed stationary sea states, viz. the largest surface wave heights expected over a given area during the sea state duration. The WASS analysis provides the first experimental proof that a space-time extreme is generally larger than that observed in time via point measurements, in agreement with the predictions based on stochastic theories for global maxima of Gaussian fields.

Deconstructing field-induced ketene isomerization through Lagrangian descriptors.

PubMed

Craven, Galen T; Hernandez, Rigoberto

2016-02-07

The time-dependent geometrical separatrices governing state transitions in field-induced ketene isomerization are constructed using the method of Lagrangian descriptors. We obtain the stable and unstable manifolds of time-varying transition states as dynamic phase space objects governing configurational changes when the ketene molecule is subjected to an oscillating electric field. The dynamics of the isomerization reaction are modeled through classical trajectory studies on the Gezelter-Miller potential energy surface and an approximate dipole moment model which is coupled to a time-dependent electric field. We obtain a representation of the reaction geometry, over varying field strengths and oscillation frequencies, by partitioning an initial phase space into basins labeled according to which product state is reached at a given time. The borders between these basins are in agreement with those obtained using Lagrangian descriptors, even in regimes exhibiting chaotic dynamics. Major outcomes of this work are: validation and extension of a transition state theory framework built from Lagrangian descriptors, elaboration of the applicability for this theory to periodically- and aperiodically-driven molecular systems, and prediction of regimes in which isomerization of ketene and its derivatives may be controlled using an external field.

Failing States as Epidemiologic Risk Zones: Implications for Global Health Security.

PubMed

Hirschfeld, Katherine

Failed states commonly experience health and mortality crises that include outbreaks of infectious disease, violent conflict, reductions in life expectancy, and increased infant and maternal mortality. This article draws from recent research in political science, security studies, and international relations to explore how the process of state failure generates health declines and outbreaks of infectious disease. The key innovation of this model is a revised definition of "the state" as a geographically dynamic rather than static political space. This makes it easier to understand how phases of territorial contraction, collapse, and regeneration interrupt public health programs, destabilize the natural environment, reduce human security, and increase risks of epidemic infectious disease and other humanitarian crises. Better understanding of these dynamics will help international health agencies predict and prepare for future health and mortality crises created by failing states.

Prediction of high-dimensional states subject to respiratory motion: a manifold learning approach

NASA Astrophysics Data System (ADS)

Liu, Wenyang; Sawant, Amit; Ruan, Dan

2016-07-01

The development of high-dimensional imaging systems in image-guided radiotherapy provides important pathways to the ultimate goal of real-time full volumetric motion monitoring. Effective motion management during radiation treatment usually requires prediction to account for system latency and extra signal/image processing time. It is challenging to predict high-dimensional respiratory motion due to the complexity of the motion pattern combined with the curse of dimensionality. Linear dimension reduction methods such as PCA have been used to construct a linear subspace from the high-dimensional data, followed by efficient predictions on the lower-dimensional subspace. In this study, we extend such rationale to a more general manifold and propose a framework for high-dimensional motion prediction with manifold learning, which allows one to learn more descriptive features compared to linear methods with comparable dimensions. Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where accurate and efficient prediction can be performed. A fixed-point iterative pre-image estimation method is used to recover the predicted value in the original state space. We evaluated and compared the proposed method with a PCA-based approach on level-set surfaces reconstructed from point clouds captured by a 3D photogrammetry system. The prediction accuracy was evaluated in terms of root-mean-squared-error. Our proposed method achieved consistent higher prediction accuracy (sub-millimeter) for both 200 ms and 600 ms lookahead lengths compared to the PCA-based approach, and the performance gain was statistically significant.

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 study of material damping in large space structures

NASA Technical Reports Server (NTRS)

Highsmith, A. L.; Allen, D. H.

1989-01-01

A constitutive model was developed for predicting damping as a function of damage in continuous fiber reinforced laminated composites. The damage model is a continuum formulation, and uses internal state variables to quantify damage and its subsequent effect on material response. The model is sensitive to the stacking sequence of the laminate. Given appropriate baseline data from unidirectional material, and damping as a function of damage in one crossply laminate, damage can be predicted as a function of damage in other crossply laminates. Agreement between theory and experiment was quite good. A micromechanics model was also developed for examining the influence of damage on damping. This model explicitly includes crack surfaces. The model provides reasonable predictions of bending stiffness as a function of damage. Damping predictions are not in agreement with the experiment. This is thought to be a result of dissipation mechanisms such as friction, which are not presently included in the analysis.

DUAL STATE-PARAMETER UPDATING SCHEME ON A CONCEPTUAL HYDROLOGIC MODEL USING SEQUENTIAL MONTE CARLO FILTERS

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin

Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.

Test Report: Low-Cost Access to TDRS Using TOPEX to Emulate Small Satellite Performance

NASA Technical Reports Server (NTRS)

Horan, Stephen

1997-01-01

This report lists the objectives and conclusions of a series of experimental contacts between the TOPEX and the TDRS satellites. These experiments are designed to verify the theoretical prediction that a spin-stabilized satellite with a broad-beam, zenith-pointing antenna can have regular, significant contacts with the TDRS and use those contacts for data services. This series of experiments is a joint project between the experimenters at New Mexico State University (NMSU), the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), and the Jet Propulsion Laboratory (JPL). In these experiments, we show that: (1) The satellite contacts during the experiment begin and end as predicted prior to the experiment; (2) The data contact is held for the desired contact duration; (3) The data quality through the contact is high and similar to that required by actual project needs; and (4) The receiving hardware at the White Sands Complex (WSC) is able to track the signals better than expected by analysis of the antenna pattern effects alone predict. We believe that these experiments successfully demonstrate the basic concept and its validity with actual spacecraft systems.

Analysis of solar receiver flux distributions for US/Russian solar dynamic system demonstration on the MIR Space Station

NASA Technical Reports Server (NTRS)

Kerslake, Thomas W.; Fincannon, James

1995-01-01

The United States and Russia have agreed to jointly develop a solar dynamic (SD) system for flight demonstration on the Russian MIR space station starting in late 1997. Two important components of this SD system are the solar concentrator and heat receiver provided by Russia and the U.S., respectively. This paper describes optical analysis of the concentrator and solar flux predictions on target receiver surfaces. The optical analysis is performed using the code CIRCE2. These analyses account for finite sun size with limb darkening, concentrator surface slope and position errors, concentrator petal thermal deformation, gaps between petals, and the shading effect of the receiver support struts. The receiver spatial flux distributions are then combined with concentrator shadowing predictions. Geometric shadowing patterns are traced from the concentrator to the target receiver surfaces. These patterns vary with time depending on the chosen MIR flight attitude and orbital mechanics of the MIR spacecraft. The resulting predictions provide spatial and temporal receiver flux distributions for any specified mission profile. The impact these flux distributions have on receiver design and control of the Brayton engine are discussed.

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-2014-2873

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-2014-2874

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

Numerical method for predicting flow characteristics and performance of nonaxisymmetric nozzles, theory

NASA Technical Reports Server (NTRS)

Thomas, P. D.

1979-01-01

The theoretical foundation and formulation of a numerical method for predicting the viscous flowfield in and about isolated three dimensional nozzles of geometrically complex configuration are presented. High Reynolds number turbulent flows are of primary interest for any combination of subsonic, transonic, and supersonic flow conditions inside or outside the nozzle. An alternating-direction implicit (ADI) numerical technique is employed to integrate the unsteady Navier-Stokes equations until an asymptotic steady-state solution is reached. Boundary conditions are computed with an implicit technique compatible with the ADI technique employed at interior points of the flow region. The equations are formulated and solved in a boundary-conforming curvilinear coordinate system. The curvilinear coordinate system and computational grid is generated numerically as the solution to an elliptic boundary value problem. A method is developed that automatically adjusts the elliptic system so that the interior grid spacing is controlled directly by the a priori selection of the grid spacing on the boundaries of the flow region.

The consciousness state space (CSS)—a unifying model for consciousness and self

PubMed Central

Berkovich-Ohana, Aviva; Glicksohn, Joseph

2014-01-01

Every experience, those we are aware of and those we are not, is embedded in a subjective timeline, is tinged with emotion, and inevitably evokes a certain sense of self. Here, we present a phenomenological model for consciousness and selfhood which relates time, awareness, and emotion within one framework. The consciousness state space (CSS) model is a theoretical one. It relies on a broad range of literature, hence has high explanatory and integrative strength, and helps in visualizing the relationship between different aspects of experience. Briefly, it is suggested that all phenomenological states fall into two categories of consciousness, core and extended (CC and EC, respectively). CC supports minimal selfhood that is short of temporal extension, its scope being the here and now. EC supports narrative selfhood, which involves personal identity and continuity across time, as well as memory, imagination and conceptual thought. The CSS is a phenomenological space, created by three dimensions: time, awareness and emotion. Each of the three dimensions is shown to have a dual phenomenological composition, falling within CC and EC. The neural spaces supporting each of these dimensions, as well as CC and EC, are laid out based on the neuroscientific literature. The CSS dynamics include two simultaneous trajectories, one in CC and one in EC, typically antagonistic in normal experiences. However, this characteristic behavior is altered in states in which a person experiences an altered sense of self. Two examples are laid out, flow and meditation. The CSS model creates a broad theoretical framework with explanatory and unificatory power. It constructs a detailed map of the consciousness and selfhood phenomenology, which offers constraints for the science of consciousness. We conclude by outlining several testable predictions raised by the CSS model. PMID:24808870

Exchange Coupling Interactions from the Density Matrix Renormalization Group and N-Electron Valence Perturbation Theory: Application to a Biomimetic Mixed-Valence Manganese Complex.

PubMed

Roemelt, Michael; Krewald, Vera; Pantazis, Dimitrios A

2018-01-09

The accurate description of magnetic level energetics in oligonuclear exchange-coupled transition-metal complexes remains a formidable challenge for quantum chemistry. The density matrix renormalization group (DMRG) brings such systems for the first time easily within reach of multireference wave function methods by enabling the use of unprecedentedly large active spaces. But does this guarantee systematic improvement in predictive ability and, if so, under which conditions? We identify operational parameters in the use of DMRG using as a test system an experimentally characterized mixed-valence bis-μ-oxo/μ-acetato Mn(III,IV) dimer, a model for the oxygen-evolving complex of photosystem II. A complete active space of all metal 3d and bridge 2p orbitals proved to be the smallest meaningful starting point; this is readily accessible with DMRG and greatly improves on the unrealistic metal-only configuration interaction or complete active space self-consistent field (CASSCF) values. Orbital optimization is critical for stabilizing the antiferromagnetic state, while a state-averaged approach over all spin states involved is required to avoid artificial deviations from isotropic behavior that are associated with state-specific calculations. Selective inclusion of localized orbital subspaces enables probing the relative contributions of different ligands and distinct superexchange pathways. Overall, however, full-valence DMRG-CASSCF calculations fall short of providing a quantitative description of the exchange coupling owing to insufficient recovery of dynamic correlation. Quantitatively accurate results can be achieved through a DMRG implementation of second order N-electron valence perturbation theory (NEVPT2) in conjunction with a full-valence metal and ligand active space. Perspectives for future applications of DMRG-CASSCF/NEVPT2 to exchange coupling in oligonuclear clusters are discussed.

Modeling the Earth system in the Mission to Planet Earth era

NASA Technical Reports Server (NTRS)

Unninayar, Sushel; Bergman, Kenneth H.

1993-01-01

A broad overview is made of global earth system modeling in the Mission to Planet Earth (MTPE) era for the multidisciplinary audience encompassed by the Global Change Research Program (GCRP). Time scales of global system fluctuation and change are described in Section 2. Section 3 provides a rubric for modeling the global earth system, as presently understood. The ability of models to predict the future state of the global earth system and the extent to which their predictions are reliable are covered in Sections 4 and 5. The 'engineering' use of global system models (and predictions) is covered in Section 6. Section 7 covers aspects of an increasing need for improved transform algorithms and better methods to assimilate this information into global models. Future monitoring and data requirements are detailed in Section 8. Section 9 covers the NASA-initiated concept 'Mission to Planet Earth,' which employs space and ground based measurement systems to provide the scientific basis for understanding global change. Section 10 concludes this review with general remarks concerning the state of global system modeling and observing technology and the need for future research.

Measurement of Reconstructed Charged Particle Multiplicities of Neutrino Interactions in MicroBooNE

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

Rafique, Aleena

2017-09-25

Here, we compare the observed charged particle multiplicity distributions in the MicroBooNE liquid argon time projection chamber from neutrino interactions in a restricted final state phase space to predictions of this distribution from several GENIE models. The measurement uses a data sample consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2015-2016 with the Fermilab Booster Neutrino Beam (BNB), which has an average neutrino energy of 800 MeV, using an exposure corresponding to 5e19 protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction andmore » uses a data-driven technique to determine the contribution to each multiplicity bin from neutrino interactions and cosmic-induced backgrounds. The restricted phase space employed makes the measurement most sensitive to the higher-energy charged particles expected from primary neutrino-argon collisions and less sensitive to lower energy protons expected to be produced in final state interactions of collision products with the target argon nucleus.« less

Two-Dimensional Electronic Spectroscopy of Benzene, Phenol, and Their Dimer: An Efficient First-Principles Simulation Protocol.

PubMed

Nenov, Artur; Mukamel, Shaul; Garavelli, Marco; Rivalta, Ivan

2015-08-11

First-principles simulations of two-dimensional electronic spectroscopy in the ultraviolet region (2DUV) require computationally demanding multiconfigurational approaches that can resolve doubly excited and charge transfer states, the spectroscopic fingerprints of coupled UV-active chromophores. Here, we propose an efficient approach to reduce the computational cost of accurate simulations of 2DUV spectra of benzene, phenol, and their dimer (i.e., the minimal models for studying electronic coupling of UV-chromophores in proteins). We first establish the multiconfigurational recipe with the highest accuracy by comparison with experimental data, providing reference gas-phase transition energies and dipole moments that can be used to construct exciton Hamiltonians involving high-lying excited states. We show that by reducing the active spaces and the number of configuration state functions within restricted active space schemes, the computational cost can be significantly decreased without loss of accuracy in predicting 2DUV spectra. The proposed recipe has been successfully tested on a realistic model proteic system in water. Accounting for line broadening due to thermal and solvent-induced fluctuations allows for direct comparison with experiments.

Quasiparticle interference of Fermi arc states in the type-II Weyl semimetal candidate WT e2

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Yang, Xing; Peng, Lang; Wang, Zhi-Jun; Li, Jian; Yi, Chang-Jiang; Xian, Jing-Jing; Shi, You-Guo; Fu, Ying-Shuang

2018-04-01

Weyl semimetals possess linear dispersions through pairs of Weyl nodes in three-dimensional momentum spaces, whose hallmark arclike surface states are connected to Weyl nodes with different chirality. WT e2 was recently predicted to be a new type of Weyl semimetal. Here, we study the quasiparticle interference (QPI) of its Fermi arc surface states by combined spectroscopic-imaging scanning tunneling spectroscopy and density functional theory calculations. We observed the electron scattering on two types of WT e2 surfaces unambiguously. Its scattering signal can be ascribed mainly to trivial surface states. We also address the QPI feature of nontrivial surface states from theoretical calculations. The experimental QPI patterns show some features that are likely related to the nontrivial Fermi arc states, whose existence is, however, not conclusive. Our study provides an indispensable clue for studying the Weyl semimetal phase in WT e2 .

Dynamics of sleep/wake determination--Normal and abnormal

NASA Astrophysics Data System (ADS)

Mahowald, Mark W.; Schenck, Carlos H.; O'Connor, Kevin A.

1991-10-01

Virtually all members of the animal kingdom experience a relentless and powerful cycling of states of being: wakefulness, rapid eye movement sleep, and nonrapid eye movement sleep. Each of these states is composed of a number of physiologic variables generated in a variety of neural structures. The predictable oscillations of these states are driven by presumed neural pacemakers which are entrained to the 24 h geophysical environment by the light/dark cycle. Experiments in nature have indicated that wake/sleep rhythm perturbations may occur either involving desynchronization of the basic 24 h wake/sleep cycle within the geophysical 24 h cycle (circadian rhythm disturbances) or involving the rapid oscillation or incomplete declaration of state (such as narcolepsy). The use of phase spaces to describe states of being may be of interest in the description of state determination in both illness and health. Some fascinating clinical and experimental phenomena may represent bifurcations in the sleep/wake control system.

Current gaps in understanding and predicting space weather: An operations perspective

NASA Astrophysics Data System (ADS)

Murtagh, W. J.

2016-12-01

The NOAA Space Weather Prediction Center (SWPC), one of the nine National Weather Service (NWS) National Centers for Environmental Prediction, is the Nation's official source for space weather alerts and warnings. Space weather effects the technology that forms the backbone of global economic vitality and national security, including satellite and airline operations, communications networks, and the electric power grid. Many of SWPC's over 48,000 subscribers rely on space weather forecasts for critical decision making. But extraordinary gaps still exist in our ability to meet customer needs for accurate and timely space weather forecasts and warnings. The 2015 National Space Weather Strategy recognizes that it is imperative that we improve the fundamental understanding of space weather and increase the accuracy, reliability, and timeliness of space-weather observations and forecasts in support of the growing demands. In this talk we provide a broad perspective of the key challenges that currently limit the forecaster's ability to better understand and predict space weather. We also examine the impact of these limitations on the end-user community.

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

2017-01-01

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Terrestrial Environment (Climatic) Criteria Guidelines for use in Aerospace Vehicle Development. 2008 Revision

NASA Technical Reports Server (NTRS)

Johnson, D. L. (Editor)

2008-01-01

This document provides guidelines for the terrestrial environment that are specifically applicable in the development of design requirements/specifications for NASA aerospace vehicles, payloads, and associated ground support equipment. The primary geographic areas encompassed are the John F. Kennedy Space Center, FL; Vandenberg AFB, CA; Edwards AFB, CA; Michoud Assembly Facility, New Orleans, LA; John C. Stennis Space Center, MS; Lyndon B. Johnson Space Center, Houston, TX; George C. Marshall Space Flight Center, Huntsville, AL; and the White Sands Missile Range, NM. This document presents the latest available information on the terrestrial environment applicable to the design and operations of aerospace vehicles and supersedes information presented in NASA-HDBK-1001 and TM X-64589, TM X-64757, TM-78118, TM-82473, and TM-4511. Information is included on winds, atmospheric thermodynamic models, radiation, humidity, precipitation, severe weather, sea state, lightning, atmospheric chemistry, seismic criteria, and a model to predict atmospheric dispersion of aerospace engine exhaust cloud rise and growth. In addition, a section has been included to provide information on the general distribution of natural environmental extremes in the conterminous United States, and world-wide, that may be needed to specify design criteria in the transportation of space vehicle subsystems and components. A section on atmospheric attenuation has been added since measurements by sensors on certain Earth orbital experiment missions are influenced by the Earth s atmosphere. There is also a section on mission analysis, prelaunch monitoring, and flight evaluation as related to the terrestrial environment inputs. The information in these guidelines is recommended for use in the development of aerospace vehicle and related equipment design and associated operational criteria, unless otherwise stated in contract work specifications. The terrestrial environmental data in these guidelines are primarily limited to information below 90 km altitude.

Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

DOE PAGES

An, Zhe; Rey, Daniel; Ye, Jingxin; ...

2017-01-16

The problem of forecasting the behavior of a complex dynamical system through analysis of observational time-series data becomes difficult when the system expresses chaotic behavior and the measurements are sparse, in both space and/or time. Despite the fact that this situation is quite typical across many fields, including numerical weather prediction, the issue of whether the available observations are "sufficient" for generating successful forecasts is still not well understood. An analysis by Whartenby et al. (2013) found that in the context of the nonlinear shallow water equations on a β plane, standard nudging techniques require observing approximately 70 % of themore » full set of state variables. Here we examine the same system using a method introduced by Rey et al. (2014a), which generalizes standard nudging methods to utilize time delayed measurements. Here, we show that in certain circumstances, it provides a sizable reduction in the number of observations required to construct accurate estimates and high-quality predictions. In particular, we find that this estimate of 70 % can be reduced to about 33 % using time delays, and even further if Lagrangian drifter locations are also used as measurements.« less

Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

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

An, Zhe; Rey, Daniel; Ye, Jingxin

The problem of forecasting the behavior of a complex dynamical system through analysis of observational time-series data becomes difficult when the system expresses chaotic behavior and the measurements are sparse, in both space and/or time. Despite the fact that this situation is quite typical across many fields, including numerical weather prediction, the issue of whether the available observations are "sufficient" for generating successful forecasts is still not well understood. An analysis by Whartenby et al. (2013) found that in the context of the nonlinear shallow water equations on a β plane, standard nudging techniques require observing approximately 70 % of themore » full set of state variables. Here we examine the same system using a method introduced by Rey et al. (2014a), which generalizes standard nudging methods to utilize time delayed measurements. Here, we show that in certain circumstances, it provides a sizable reduction in the number of observations required to construct accurate estimates and high-quality predictions. In particular, we find that this estimate of 70 % can be reduced to about 33 % using time delays, and even further if Lagrangian drifter locations are also used as measurements.« less

Manipulating time and space: Collision prediction in peripersonal and extrapersonal space.

PubMed

Iachini, Tina; Ruotolo, Francesco; Vinciguerra, Michela; Ruggiero, Gennaro

2017-09-01

Being able to predict potential collisions is a necessary survival prerequisite for all moving species. Temporal and spatial information is fundamental for this purpose. However, it is not clear yet if the peripersonal (i.e. near) and extrapersonal (i.e. far) distance between our body and the moving objects affects the way in which we can predict possible collisions. In order to assess this, we manipulated independently velocity and path of two balls moving one towards the other in such a way as to collide or not in peripersonal and extrapersonal space. In two experiments, participants had to judge if these balls were to collide or not. The results consistently showed a lower discrimination capacity and a more liberal tendency to predict collisions when the moving balls were in peripersonal space and their velocity was different rather than equal. This did not happen in extrapersonal space. Therefore, peripersonal space was particularly affected by temporal information. The possible link between the motor and anticipatory adaptive function of peripersonal space and collision prediction mechanisms is discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Oscillatory bistability of real-space transfer in semiconductor heterostructures

NASA Astrophysics Data System (ADS)

Do˙ttling, R.; Scho˙ll, E.

1992-01-01

Charge transport parallel to the layers of a modulation-doped GaAs/AlxGa1-xAs heterostructure is studied theoretically. The heating of electrons by the applied electric field leads to real-space transfer of electrons from the GaAs into the adjacent AlxGa1-xAs layer. For sufficiently large dc bias, spontaneous periodic 100-GHz current oscillations, and bistability and hysteretic switching transitions between oscillatory and stationary states are predicted. We present a detailed investigation of complex bifurcation scenarios as a function of the bias voltage U0 and the load resistance RL. For large RL subcritical Hopf bifurcations and global bifurcations of limit cycles are displayed.

Universal linear and nonlinear electrodynamics of a Dirac fluid

NASA Astrophysics Data System (ADS)

Sun, Zhiyuan; Basov, Dmitry N.; Fogler, Michael M.

2018-03-01

A general relation is derived between the linear and second-order nonlinear ac conductivities of an electron system in the hydrodynamic regime of frequencies below the interparticle scattering rate. The magnitude and tensorial structure of the hydrodynamic nonlinear conductivity are shown to differ from their counterparts in the more familiar kinetic regime of higher frequencies. Due to universality of the hydrodynamic equations, the obtained formulas are valid for systems with an arbitrary Dirac-like dispersion, ranging from solid-state electron gases to free-space plasmas, either massive or massless, at any temperature, chemical potential, or space dimension. Predictions for photon drag and second-harmonic generation in graphene are presented as one application of this theory.

A Battery Health Monitoring Framework for Planetary Rovers

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Kulkarni, Chetan Shrikant

2014-01-01

Batteries have seen an increased use in electric ground and air vehicles for commercial, military, and space applications as the primary energy source. An important aspect of using batteries in such contexts is battery health monitoring. Batteries must be carefully monitored such that the battery health can be determined, and end of discharge and end of usable life events may be accurately predicted. For planetary rovers, battery health estimation and prediction is critical to mission planning and decision-making. We develop a model-based approach utilizing computaitonally efficient and accurate electrochemistry models of batteries. An unscented Kalman filter yields state estimates, which are then used to predict the future behavior of the batteries and, specifically, end of discharge. The prediction algorithm accounts for possible future power demands on the rover batteries in order to provide meaningful results and an accurate representation of prediction uncertainty. The framework is demonstrated on a set of lithium-ion batteries powering a rover at NASA.

Probability-based collaborative filtering model for predicting gene-disease associations.

PubMed

Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan

2017-12-28

Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene-disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our model. Firstly, on the basis of a typical latent factorization model, we propose model I with an average heterogeneous regularization. Secondly, we develop modified model II with personal heterogeneous regularization to enhance the accuracy of aforementioned models. In this model, vector space similarity or Pearson correlation coefficient metrics and data on related species are also used. We compared the results of PCFM with the results of four state-of-arts approaches. The results show that PCFM performs better than other advanced approaches. PCFM model can be leveraged for predictions of disease genes, especially for new human genes or diseases with no known relationships.

A Framework of Covariance Projection on Constraint Manifold for Data Fusion.

PubMed

Bakr, Muhammad Abu; Lee, Sukhan

2018-05-17

A general framework of data fusion is presented based on projecting the probability distribution of true states and measurements around the predicted states and actual measurements onto the constraint manifold. The constraint manifold represents the constraints to be satisfied among true states and measurements, which is defined in the extended space with all the redundant sources of data such as state predictions and measurements considered as independent variables. By the general framework, we mean that it is able to fuse any correlated data sources while directly incorporating constraints and identifying inconsistent data without any prior information. The proposed method, referred to here as the Covariance Projection (CP) method, provides an unbiased and optimal solution in the sense of minimum mean square error (MMSE), if the projection is based on the minimum weighted distance on the constraint manifold. The proposed method not only offers a generalization of the conventional formula for handling constraints and data inconsistency, but also provides a new insight into data fusion in terms of a geometric-algebraic point of view. Simulation results are provided to show the effectiveness of the proposed method in handling constraints and data inconsistency.

Against Laplacian Reduction of Newtonian Mass to Spatiotemporal Quantities

NASA Astrophysics Data System (ADS)

Martens, Niels C. M.

2018-05-01

Laplace wondered about the minimal choice of initial variables and parameters corresponding to a well-posed initial value problem. Discussions of Laplace's problem in the literature have focused on choosing between spatiotemporal variables relative to absolute space (i.e. substantivalism) or merely relative to other material bodies (i.e. relationalism) and between absolute masses (i.e. absolutism) or merely mass ratios (i.e. comparativism). This paper extends these discussions of Laplace's problem, in the context of Newtonian Gravity, by asking whether mass needs to be included in the initial state at all, or whether a purely spatiotemporal initial state suffices. It is argued that mass indeed needs to be included; removing mass from the initial state drastically reduces the predictive and explanatory power of Newtonian Gravity.

Against Laplacian Reduction of Newtonian Mass to Spatiotemporal Quantities

NASA Astrophysics Data System (ADS)

Martens, Niels C. M.

2018-03-01

Laplace wondered about the minimal choice of initial variables and parameters corresponding to a well-posed initial value problem. Discussions of Laplace's problem in the literature have focused on choosing between spatiotemporal variables relative to absolute space (i.e. substantivalism) or merely relative to other material bodies (i.e. relationalism) and between absolute masses (i.e. absolutism) or merely mass ratios (i.e. comparativism). This paper extends these discussions of Laplace's problem, in the context of Newtonian Gravity, by asking whether mass needs to be included in the initial state at all, or whether a purely spatiotemporal initial state suffices. It is argued that mass indeed needs to be included; removing mass from the initial state drastically reduces the predictive and explanatory power of Newtonian Gravity.

The Challenge of Fulfilling a Perplexing Space Weather User Requirement

NASA Astrophysics Data System (ADS)

Kunches, J. M.; Boteler, D.; Wang, H.

2006-12-01

To fly commercial aircraft over the poles, it is necessary to ensure that air-ground and air-air communications be maintained throughout the flight. Some U. S. carriers have requested a seven hour lead-time for predictions of HF outages, the primary communication means for flying over the pole. This very difficult-to-meet specification results from the necessity to make alternative fueling arrangements, schedule additional flight crews, modify the loading of the aircraft, etc., to minimize the costs due to redirecting aircraft away from the optimal polar route. To satisfy this stringent requirement, better predictions of solar energetic particle (SEPs) events are necessary. Even soft SEPs can cause HF outages lasting for hours. This requirement challenges the international science community to significantly improve current predictive methodologies. Presently, a 1-2 hour lead-time may be the longest that can be obtained with a reasonable false alarm rate. Globally, there are a number of new programs, organized under the auspices of the International Space Environment Service (ISES), to facilitate progress in meeting the airlines' requirement. The Regional Warning Center in Canada is implementing a network of riometers at high latitudes, so to detect ionospheric conditions that result in HF outages. This chain is now being deployed. The Regional Warning Centers in Russia, China, the United States and Japan are working with the Canadians, to acquire and make available, other real-time data relevant to the problem. These data include solar, interplanetary, geomagnetic and ionospheric data. Clearly this challenge spans the realm of space science, from the solar and galactic origins of energetic particles, to the D-Region of Earth's ionosphere. The presentation will lay out a roadmap for an iterative solution to the prediction challenge, and identify some of the key areas to be addressed.

Impact of climate change on mercury concentrations and deposition in the eastern United States.

PubMed

Megaritis, Athanasios G; Murphy, Benjamin N; Racherla, Pavan N; Adams, Peter J; Pandis, Spyros N

2014-07-15

The global-regional climate-air pollution modeling system (GRE-CAPS) was applied over the eastern United States to study the impact of climate change on the concentration and deposition of atmospheric mercury. Summer and winter periods (300 days for each) were simulated, and the present-day model predictions (2000s) were compared to the future ones (2050s) assuming constant emissions. Climate change affects Hg(2+) concentrations in both periods. On average, atmospheric Hg(2+) levels are predicted to increase in the future by 3% in summer and 5% in winter respectively due to enhanced oxidation of Hg(0) under higher temperatures. The predicted concentration change of Hg(2+) was found to vary significantly in space due to regional-scale changes in precipitation, ranging from -30% to 30% during summer and -20% to 40% during winter. Particulate mercury, Hg(p) has a similar spatial response to climate change as Hg(2+), while Hg(0) levels are not predicted to change significantly. In both periods, the response of mercury deposition to climate change varies spatially with an average predicted increase of 6% during summer and 4% during winter. During summer, deposition increases are predicted mostly in the western parts of the domain while mercury deposition is predicted to decrease in the Northeast and also in many areas in the Midwest and Southeast. During winter mercury deposition is predicted to change from -30% to 50% mainly due to the changes in rainfall and the corresponding changes in wet deposition. Copyright © 2014 Elsevier B.V. All rights reserved.

Progress in space weather predictions and applications

NASA Astrophysics Data System (ADS)

Lundstedt, H.

The methods of today's predictions of space weather and effects are so much more advanced and yesterday's statistical methods are now replaced by integrated knowledge-based neuro-computing models and MHD methods. Within the ESA Space Weather Programme Study a real-time forecast service has been developed for space weather and effects. This prototype is now being implemented for specific users. Today's applications are not only so many more but also so much more advanced and user-oriented. A scientist needs real-time predictions of a global index as input for an MHD model calculating the radiation dose for EVAs. A power company system operator needs a prediction of the local value of a geomagnetically induced current. A science tourist needs to know whether or not aurora will occur. Soon we might even be able to predict the tropospheric climate changes and weather caused by the space weather.

Light-front holography and superconformal quantum mechanics: A new approach to hadron structure and color confinement

NASA Astrophysics Data System (ADS)

Brodsky, Stanley J.; Deur, Alexandre; de Téramond, Guy F.; Dosch, Hans Günter

2015-11-01

A primary question in hadron physics is how the mass scale for hadrons consisting of light quarks, such as the proton, emerges from the QCD Lagrangian even in the limit of zero quark mass. If one requires the effective action which underlies the QCD Lagrangian to remain conformally invariant and extends the formalism of de Alfaro, Fubini and Furlan to light-front Hamiltonian theory, then a unique, color-confining potential with a mass parameter κ emerges. The actual value of the parameter κ is not set by the model - only ratios of hadron masses and other hadronic mass scales are predicted. The result is a nonperturbative, relativistic light-front quantum mechanical wave equation, the Light-Front Schrödinger Equation which incorporates color confinement and other essential spectroscopic and dynamical features of hadron physics, including a massless pion for zero quark mass and linear Regge trajectories with the identical slope in the radial quantum number n and orbital angular momentum L. The same light-front equations for mesons with spin J also can be derived from the holographic mapping to QCD (3+1) at fixed light-front time from the soft-wall model modification of AdS5 space with a specific dilaton profile. Light-front holography thus provides a precise relation between the bound-state amplitudes in the fifth dimension of AdS space and the boost-invariant light-front wavefunctions describing the internal structure of hadrons in physical space-time. One can also extend the analysis to baryons using superconformal algebra - 2 × 2 supersymmetric representations of the conformal group. The resulting fermionic LF bound-state equations predict striking similarities between the meson and baryon spectra. In fact, the holographic QCD light-front Hamiltonians for the states on the meson and baryon trajectories are identical if one shifts the internal angular momenta of the meson (LM) and baryon (LB) by one unit: LM = LB + 1. We also show how the mass scale κ underlying confinement and the masses of light-quark hadrons determines the scale ΛMS¯ controlling the evolution of the perturbative QCD coupling. The relation between scales is obtained by matching the nonperturbative dynamics, as described by an effective conformal theory mapped to the light-front and its embedding in AdS space, to the perturbative QCD regime. The data for the effective coupling defined from the Bjorken sum rule αg1(Q2) are remarkably consistent with the Gaussian form predicted by LF holographic QCD. The result is an effective coupling defined at all momenta. The predicted value ΛMS¯(NF=3)=0.440mρ=0.341±0.024GeV is in agreement with the world average 0.339±0.010GeV. We thus can connect ΛMS¯ to hadron masses. The analysis applies to any renormalization scheme.

TH-CD-207A-07: Prediction of High Dimensional State Subject to Respiratory Motion: A Manifold Learning Approach

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

Liu, W; Sawant, A; Ruan, D

Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit moremore » descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction reliability in such low dimensional manifold. The fixed-point iterative approach turns out to work well practically for the pre-image recovery. Our approach is particularly suitable to facilitate managing respiratory motion in image-guide radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.« less

Large eddy simulation of turbulent premixed combustion using tabulated detailed chemistry and presumed probability density function

NASA Astrophysics Data System (ADS)

Zhang, Hongda; Han, Chao; Ye, Taohong; Ren, Zhuyin

2016-03-01

A method of chemistry tabulation combined with presumed probability density function (PDF) is applied to simulate piloted premixed jet burner flames with high Karlovitz number using large eddy simulation. Thermo-chemistry states are tabulated by the combination of auto-ignition and extended auto-ignition model. To evaluate the predictive capability of the proposed tabulation method to represent the thermo-chemistry states under the condition of different fresh gases temperature, a-priori study is conducted by performing idealised transient one-dimensional premixed flame simulations. Presumed PDF is used to involve the interaction of turbulence and flame with beta PDF to model the reaction progress variable distribution. Two presumed PDF models, Dirichlet distribution and independent beta distribution, respectively, are applied for representing the interaction between two mixture fractions that are associated with three inlet streams. Comparisons of statistical results show that two presumed PDF models for the two mixture fractions are both capable of predicting temperature and major species profiles, however, they are shown to have a significant effect on the predictions for intermediate species. An analysis of the thermo-chemical state-space representation of the sub-grid scale (SGS) combustion model is performed by comparing correlations between the carbon monoxide mass fraction and temperature. The SGS combustion model based on the proposed chemistry tabulation can reasonably capture the peak value and change trend of intermediate species. Aspects regarding model extensions to adequately predict the peak location of intermediate species are discussed.

Best of both worlds: combining pharma data and state of the art modeling technology to improve in Silico pKa prediction.

PubMed

Fraczkiewicz, Robert; Lobell, Mario; Göller, Andreas H; Krenz, Ursula; Schoenneis, Rolf; Clark, Robert D; Hillisch, Alexander

2015-02-23

In a unique collaboration between a software company and a pharmaceutical company, we were able to develop a new in silico pKa prediction tool with outstanding prediction quality. An existing pKa prediction method from Simulations Plus based on artificial neural network ensembles (ANNE), microstates analysis, and literature data was retrained with a large homogeneous data set of drug-like molecules from Bayer. The new model was thus built with curated sets of ∼14,000 literature pKa values (∼11,000 compounds, representing literature chemical space) and ∼19,500 pKa values experimentally determined at Bayer Pharma (∼16,000 compounds, representing industry chemical space). Model validation was performed with several test sets consisting of a total of ∼31,000 new pKa values measured at Bayer. For the largest and most difficult test set with >16,000 pKa values that were not used for training, the original model achieved a mean absolute error (MAE) of 0.72, root-mean-square error (RMSE) of 0.94, and squared correlation coefficient (R(2)) of 0.87. The new model achieves significantly improved prediction statistics, with MAE = 0.50, RMSE = 0.67, and R(2) = 0.93. It is commercially available as part of the Simulations Plus ADMET Predictor release 7.0. Good predictions are only of value when delivered effectively to those who can use them. The new pKa prediction model has been integrated into Pipeline Pilot and the PharmacophorInformatics (PIx) platform used by scientists at Bayer Pharma. Different output formats allow customized application by medicinal chemists, physical chemists, and computational chemists.

Large space structure model reduction and control system design based upon actuator and sensor influence functions

NASA Technical Reports Server (NTRS)

Yam, Y.; Lang, J. H.; Johnson, T. L.; Shih, S.; Staelin, D. H.

1983-01-01

A model reduction procedure based on aggregation with respect to sensor and actuator influences rather than modes is presented for large systems of coupled second-order differential equations. Perturbation expressions which can predict the effects of spillover on both the aggregated and residual states are derived. These expressions lead to the development of control system design constraints which are sufficient to guarantee, to within the validity of the perturbations, that the residual states are not destabilized by control systems designed from the reduced model. A numerical example is provided to illustrate the application of the aggregation and control system design method.

Summary of Cumulus Parameterization Workshop

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Starr, David OC.; Hou, Arthur; Newman, Paul; Sud, Yogesh

2002-01-01

A workshop on cumulus parameterization took place at the NASA Goddard Space Flight Center from December 3-5, 2001. The major objectives of this workshop were (1) to review the problem of representation of moist processes in large-scale models (mesoscale models, Numerical Weather Prediction models and Atmospheric General Circulation Models), (2) to review the state-of-the-art in cumulus parameterization schemes, and (3) to discuss the need for future research and applications. There were a total of 31 presentations and about 100 participants from the United States, Japan, the United Kingdom, France and South Korea. The specific presentations and discussions during the workshop are summarized in this paper.

Dynamical properties of dissipative XYZ Heisenberg lattices

NASA Astrophysics Data System (ADS)

Rota, R.; Minganti, F.; Biella, A.; Ciuti, C.

2018-04-01

We study dynamical properties of dissipative XYZ Heisenberg lattices where anisotropic spin-spin coupling competes with local incoherent spin flip processes. In particular, we explore a region of the parameter space where dissipative magnetic phase transitions for the steady state have been recently predicted by mean-field theories and exact numerical methods. We investigate the asymptotic decay rate towards the steady state both in 1D (up to the thermodynamical limit) and in finite-size 2D lattices, showing that critical dynamics does not occur in 1D, but it can emerge in 2D. We also analyze the behavior of individual homodyne quantum trajectories, which reveal the nature of the transition.

Historical Review of Lower Body Negative Pressure Research in Space Medicine.

PubMed

Campbell, Mark R; Charles, John B

2015-07-01

Cephalad redistribution of intravascular and extravascular fluid occurs as a result of weightlessness during spaceflight. This provokes cardiovascular, cardiopulmonary, and autonomic nervous system responses. The resulting altered functional state can result in orthostatic hypotension and intolerance upon landing and return to a gravity environment. In-flight lower body negative pressure (LBNP) transiently restores normal body fluid distribution. Early in the U.S. space program, LBNP was devised as a way to test for orthostatic intolerance. With the development of the Skylab Program and longer duration spaceflight, it was realized that it could provide a method of monitoring orthostatic intolerance in flight and predicting the post-landing orthostatic response. LBNP was also investigated not only as an in-flight cardiovascular orthostatic stress test, but also as a countermeasure to cardiovascular deconditioning on Soviet space stations, Skylab, and the Shuttle. It is still being used by the Russian program on the International Space Station as an end-of-flight countermeasure.

A Satellite View of Global Water and Energy Cycling

NASA Astrophysics Data System (ADS)

Houser, P. R.

2012-12-01

The global water cycle describes liquid, solid and vapor water dynamics as it moves through the atmosphere, oceans and land. Life exists because of water, and civilization depends on adapting to the constraints imposed by water availability. The carbon, water and energy cycles are strongly interdependent - energy is moved through evaporation and condensation, and photosynthesis is closely related to transpiration. There are significant knowledge gaps about water storage, fluxes and dynamics - we currently do not really know how much water is stored in snowpacks, groundwater or reservoirs. The view from space offers a vision for water science advancement. This vision includes observation, understanding, and prediction advancements that will improve water management and to inform water-related infrastructure that planning to provide for human needs and to protect the natural environment. The water cycle science challenge is to deploy a series of coordinated earth observation satellites, and to integrate in situ and space-borne observations to quantify the key water-cycle state variables and fluxes. The accompanying societal challenge is to integrate this information along with water cycle physics, and ecosystems and societal considerations as a basis for enlightened water resource management and to protect life and property from effects of water cycle extremes. Better regional to global scale water-cycle observations and predictions need to be readily available to reduce loss of life and property caused by water-related hazards. To this end, the NASA Energy and Water cycle Study (NEWS) has been documenting the satellite view of the water cycle with a goal of enabling improved, observationally based, predictions of water and energy cycle consequences of Earth system variability and change. NEWS has fostered broad interdisciplinary collaborations to study experimental and operational satellite observations and has developed analysis tools for characterizing air/sea fluxes, ocean circulation, atmospheric states, radiative balances, land surface states, sub-surface hydrology, snow and ice. This presentation will feature an overview of recent progress towards this challenge, and lay out the plan for coordination with complementary international efforts.

Search for excited states in 25O

NASA Astrophysics Data System (ADS)

Jones, M. D.; Fossez, K.; Baumann, T.; DeYoung, P. A.; Finck, J. E.; Frank, N.; Kuchera, A. N.; Michel, N.; Nazarewicz, W.; Rotureau, J.; Smith, J. K.; Stephenson, S. L.; Stiefel, K.; Thoennessen, M.; Zegers, R. G. T.

2017-11-01

Background: Theoretical calculations suggest the presence of low-lying excited states in 25O. Previous experimental searches by means of proton knockout on 26F produced no evidence for such excitations. Purpose: We search for excited states in 25O using the 24O(d ,p ) 25O reaction. The theoretical analysis of excited states in unbound O,2725 is based on the configuration interaction approach that accounts for couplings to the scattering continuum. Method: We use invariant-mass spectroscopy to measure neutron-unbound states in 25O. For the theoretical approach, we use the complex-energy Gamow Shell Model and Density Matrix Renormalization Group method with a finite-range two-body interaction optimized to the bound states and resonances of O-2623, assuming a core of 22O. We predict energies, decay widths, and asymptotic normalization coefficients. Results: Our calculations in a large s p d f space predict several low-lying excited states in 25O of positive and negative parity, and we obtain an experimental limit on the relative cross section of a possible Jπ=1/2 + state with respect to the ground state of 25O at σ1 /2 +/σg .s .=0 .25-0.25+1.0 . We also discuss how the observation of negative parity states in 25O could guide the search for the low-lying negative parity states in 27O. Conclusion: Previous experiments based on the proton knockout of 26F suffered from the low cross sections for the population of excited states in 25O because of low spectroscopic factors. In this respect, neutron transfer reactions carry more promise.

Estimation of critical behavior from the density of states in classical statistical models

NASA Astrophysics Data System (ADS)

Malakis, A.; Peratzakis, A.; Fytas, N. G.

2004-12-01

We present a simple and efficient approximation scheme which greatly facilitates the extension of Wang-Landau sampling (or similar techniques) in large systems for the estimation of critical behavior. The method, presented in an algorithmic approach, is based on a very simple idea, familiar in statistical mechanics from the notion of thermodynamic equivalence of ensembles and the central limit theorem. It is illustrated that we can predict with high accuracy the critical part of the energy space and by using this restricted part we can extend our simulations to larger systems and improve the accuracy of critical parameters. It is proposed that the extensions of the finite-size critical part of the energy space, determining the specific heat, satisfy a scaling law involving the thermal critical exponent. The method is applied successfully for the estimation of the scaling behavior of specific heat of both square and simple cubic Ising lattices. The proposed scaling law is verified by estimating the thermal critical exponent from the finite-size behavior of the critical part of the energy space. The density of states of the zero-field Ising model on these lattices is obtained via a multirange Wang-Landau sampling.

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

Modelling and model predictive control for a bicycle-rider system

NASA Astrophysics Data System (ADS)

Chu, T. D.; Chen, C. K.

2018-01-01

This study proposes a bicycle-rider control model based on model predictive control (MPC). First, a bicycle-rider model with leaning motion of the rider's upper body is developed. The initial simulation data of the bicycle rider are then used to identify the linear model of the system in state-space form for MPC design. Control characteristics of the proposed controller are assessed by simulating the roll-angle tracking control. In this riding task, the MPC uses steering and leaning torques as the control inputs to control the bicycle along a reference roll angle. The simulation results in different cases have demonstrated the applicability and performance of the MPC for bicycle-rider modelling.

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

Core excitations across the neutron shell gap in 207Tl

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

Wilson, E.; Podolyák, Zs.; Grawe, H.

2015-05-05

The single closed-neutron-shell, one proton–hole nucleus 207Tl was populated in deep-inelastic collisions of a 208Pb beam with a 208Pb target. The yrast and near-yrast level scheme has been established up to high excitation energy, comprising an octupole phonon state and a large number of core excited states. Based on shell-model calculations, all observed single core excitations were established to arise from the breaking of the N=126 neutron core. While the shell-model calculations correctly predict the ordering of these states, their energies are compressed at high spins. It is concluded that this compression is an intrinsic feature of shell-model calculations usingmore » two-body matrix elements developed for the description of two-body states, and that multiple core excitations need to be considered in order to accurately calculate the energy spacings of the predominantly three-quasiparticle states.« less

Valence State Driven Site Preference in the Quaternary Compound Ca5MgAgGe5: An Electron-Deficient Phase with Optimized Bonding

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

Ponou, Simeon; Lidin, Sven; Zhang, Yuemei

The quaternary phase Ca5Mg0.95Ag1.05(1)Ge5 (3) was synthesized by high-temperature solid-state techniques, and its crystal structure was determined by single-crystal diffraction methods in the orthorhombic space group Pnma – Wyckoff sequence c12 with a = 23.1481(4) Å, b = 4.4736(1) Å, c = 11.0128(2) Å, V = 1140.43(4) Å3, Z = 4. The crystal structure can be described as linear intergrowths of slabs cut from the CaGe (CrB-type) and the CaMGe (TiNiSi-type; M = Mg, Ag) structures. Hence, 3 is a hettotype of the hitherto missing n = 3 member of the structure series with the general formula R2+nT2X2+n, previously describedmore » with n = 1, 2, and 4. The member with n = 3 was predicted in the space group Cmcm – Wyckoff sequence f5c2. The experimental space group Pnma (in the nonstandard setting Pmcn) corresponds to a klassengleiche symmetry reduction of index two of the predicted space group Cmcm. This transition originates from the switching of one Ge and one Ag position in the TiNiSi-related slab, a process that triggers an uncoupling of each of the five 8f sites in Cmcm into two 4c sites in Pnma. The Mg/Ag site preference was investigated using VASP calculations and revealed a remarkable example of an intermetallic compound for which the electrostatic valency principle is a critical structure-directing force. The compound is deficient by one valence electron according to the Zintl concept, but LMTO electronic structure calculations indicate electronic stabilization and overall bonding optimization in the polyanionic network. Other stability factors beyond the Zintl concept that may account for the electronic stabilization are discussed.« less

L70 life prediction for solid state lighting using Kalman Filter and Extended Kalman Filter based models

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

Lall, Pradeep; Wei, Junchao; Davis, Lynn

2013-08-08

Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is definedmore » by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.« less

Requirements for Simulating Space Radiation With Particle Accelerators

NASA Technical Reports Server (NTRS)

Schimmerling, W.; Wilson, J. W.; Cucinotta, F.; Kim, M-H Y.

2004-01-01

Interplanetary space radiation consists of fully ionized nuclei of atomic elements with high energy for which only the few lowest energy ions can be stopped in shielding materials. The health risk from exposure to these ions and their secondary radiations generated in the materials of spacecraft and planetary surface enclosures is a major limiting factor in the management of space radiation risk. Accurate risk prediction depends on a knowledge of basic radiobiological mechanisms and how they are modified in the living tissues of a whole organism. To a large extent, this knowledge is not currently available. It is best developed at ground-based laboratories, using particle accelerator beams to simulate the components of space radiation. Different particles, in different energy regions, are required to study different biological effects, including beams of argon and iron nuclei in the energy range 600 to several thousand MeV/nucleon and carbon beams in the energy range of approximately 100 MeV/nucleon to approximately 1000 MeV/nucleon. Three facilities, one each in the United States, in Germany and in Japan, currently have the partial capability to satisfy these constraints. A facility has been proposed using the Brookhaven National Laboratory Booster Synchrotron in the United States; in conjunction with other on-site accelerators, it will be able to provide the full range of heavy ion beams and energies required. International cooperation in the use of these facilities is essential to the development of a safe international space program.

Community Coordinated Modeling Center: Addressing Needs of Operational Space Weather Forecasting

NASA Technical Reports Server (NTRS)

Kuznetsova, M.; Maddox, M.; Pulkkinen, A.; Hesse, M.; Rastaetter, L.; Macneice, P.; Taktakishvili, A.; Berrios, D.; Chulaki, A.; Zheng, Y.;

The Opportunity in Commercial Approaches for Future NASA Deep Space Exploration Elements

NASA Technical Reports Server (NTRS)

Zapata, Edgar

2017-01-01

In 2011, NASA released a report assessing the market for commercial crew and cargo services to low Earth orbit (LEO). The report stated that NASA had spent a few hundred million dollars in the Commercial Orbital Transportation Services (COTS) program on the portion related to the development of the Falcon 9 launch vehicle. Yet a NASA cost model predicted the cost would have been significantly more with a non-commercial cost-plus contracting approach. By 2016 a NASA request for information stated it must "maximize the efficiency and sustainability of the Exploration Systems development programs", as "critical to free resources for reinvestment...such as other required deep space exploration capabilities." This work joins the previous two events, showing the potential for commercial, public private partnerships, modeled on programs like COTS, to reduce the cost to NASA significantly for "...other required deep space exploration capabilities." These other capabilities include landers, stages and more. We mature the concept of "costed baseball cards", adding cost estimates to NASA's space systems "baseball cards." We show some potential costs, including analysis, the basis of estimates, data sources and caveats to address a critical question - based on initial assessment, are significant agency resources justified for more detailed analysis and due diligence to understand and invest in public private partnerships for human deep space exploration systems? The cost analysis spans commercial to cost-plus contracting approaches, for smaller elements vs. larger, with some variation for lunar or Mars. By extension, we delve briefly into the potentially much broader significance of the individual cost estimates if taken together as a NASA investment portfolio where public private partnership are stitched together for deep space exploration. How might multiple improvements in individual systems add up to NASA human deep space exploration achievements, realistically, affordably, sustainably, in a relevant timeframe?

Fixed points, stable manifolds, weather regimes, and their predictability

DOE PAGES

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

2009-10-27

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s fixed points in phase space. The model dynamics is characterized by the coexistence of multiple ''weather regimes.'' To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, ''bred vectors'' and singular vectors. These results are then verified in the framework of ensemblemore » forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.« less

Enzyme clustering accelerates processing of intermediates through metabolic channeling

PubMed Central

Castellana, Michele; Wilson, Maxwell Z.; Xu, Yifan; Joshi, Preeti; Cristea, Ileana M.; Rabinowitz, Joshua D.; Gitai, Zemer; Wingreen, Ned S.

2015-01-01

We present a quantitative model to demonstrate that coclustering multiple enzymes into compact agglomerates accelerates the processing of intermediates, yielding the same efficiency benefits as direct channeling, a well-known mechanism in which enzymes are funneled between enzyme active sites through a physical tunnel. The model predicts the separation and size of coclusters that maximize metabolic efficiency, and this prediction is in agreement with previously reported spacings between coclusters in mammalian cells. For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model prediction that enzyme agglomerates can accelerate the processing of a shared intermediate by one branch, and thus regulate steady-state flux division. Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling and its application to both efficiency improvement and metabolic regulation. PMID:25262299

Fixed points, stable manifolds, weather regimes, and their predictability.

PubMed

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

2009-12-01

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model's fixed points in phase space. The model dynamics is characterized by the coexistence of multiple "weather regimes." To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, "bred vectors" and singular vectors. These results are then verified in the framework of ensemble forecasts issued from "clouds" (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.

Measurement of the forward-backward asymmetry of top-quark and antiquark pairs using the full CDF Run II data set

NASA Astrophysics Data System (ADS)

Aaltonen, T.; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Apollinari, G.; Appel, J. A.; Arisawa, T.; Artikov, A.; Asaadi, J.; Ashmanskas, W.; Auerbach, B.; Aurisano, A.; Azfar, F.; Badgett, W.; Bae, T.; Barbaro-Galtieri, A.; Barnes, V. E.; Barnett, B. A.; Barria, P.; Bartos, P.; Bauce, M.; Bedeschi, F.; Behari, S.; Bellettini, G.; Bellinger, J.; Benjamin, D.; Beretvas, A.; Bhatti, A.; Bland, K. R.; Blumenfeld, B.; Bocci, A.; Bodek, A.; Bortoletto, D.; Boudreau, J.; Boveia, A.; Brigliadori, L.; Bromberg, C.; Brucken, E.; Budagov, J.; Budd, H. S.; Burkett, K.; Busetto, G.; Bussey, P.; Butti, P.; Buzatu, A.; Calamba, A.; Camarda, S.; Campanelli, M.; Canelli, F.; Carls, B.; Carlsmith, D.; Carosi, R.; Carrillo, S.; Casal, B.; Casarsa, M.; Castro, A.; Catastini, P.; Cauz, D.; Cavaliere, V.; Cerri, A.; Cerrito, L.; Chen, Y. C.; Chertok, M.; Chiarelli, G.; Chlachidze, G.; Cho, K.; Chokheli, D.; Clark, A.; Clarke, C.; Convery, M. E.; Conway, J.; Corbo, M.; Cordelli, M.; Cox, C. A.; Cox, D. J.; Cremonesi, M.; Cruz, D.; Cuevas, J.; Culbertson, R.; d'Ascenzo, N.; Datta, M.; de Barbaro, P.; Demortier, L.; Deninno, M.; D'Errico, M.; Devoto, F.; Di Canto, A.; Di Ruzza, B.; Dittmann, J. R.; Donati, S.; D'Onofrio, M.; Dorigo, M.; Driutti, A.; Ebina, K.; Edgar, R.; Erbacher, R.; Errede, S.; Esham, B.; Farrington, S.; Fernández Ramos, J. P.; Field, R.; Flanagan, G.; Forrest, R.; Franklin, M.; Freeman, J. C.; Frisch, H.; Funakoshi, Y.; Galloni, C.; Garfinkel, A. F.; Garosi, P.; Gerberich, H.; Gerchtein, E.; Giagu, S.; Giakoumopoulou, V.; Gibson, K.; Ginsburg, C. M.; Giokaris, N.; Giromini, P.; Glagolev, V.; Glenzinski, D.; Gold, M.; Goldin, D.; Golossanov, A.; Gomez, G.; Gomez-Ceballos, G.; Goncharov, M.; González López, O.; Gorelov, I.; Goshaw, A. T.; Goulianos, K.; Gramellini, E.; Grosso-Pilcher, C.; Guimaraes da Costa, J.; Hahn, S. R.; Han, J. Y.; Happacher, F.; Hara, K.; Hare, M.; Harr, R. F.; Harrington-Taber, T.; Hatakeyama, K.; Hays, C.; Heinrich, J.; Herndon, M.; Hocker, A.; Hong, Z.; Hopkins, W.; Hou, S.; Hughes, R. E.; Husemann, U.; Hussein, M.; Huston, J.; Introzzi, G.; Iori, M.; Ivanov, A.; James, E.; Jang, D.; Jayatilaka, B.; Jeon, E. J.; Jindariani, S.; Jones, M.; Joo, K. K.; Jun, S. Y.; Junk, T. R.; Kambeitz, M.; Kamon, T.; Karchin, P. E.; Kasmi, A.; Kato, Y.; Ketchum, W.; Keung, J.; Kilminster, B.; Kim, D. H.; Kim, H. S.; Kim, J. E.; Kim, M. J.; Kim, S. H.; Kim, S. B.; Kim, Y. J.; Kim, Y. K.; Kimura, N.; Kirby, M.; Kondo, K.; Kong, D. J.; Konigsberg, J.; Kotwal, A. V.; Kreps, M.; Kroll, J.; Kruse, M.; Kuhr, T.; Kurata, M.; Laasanen, A. T.; Lammel, S.; Lancaster, M.; Lannon, K.; Latino, G.; Lee, H. S.; Lee, J. S.; Leo, S.; Leone, S.; Lewis, J. D.; Limosani, A.; Lipeles, E.; Lister, A.; Liu, Q.; Liu, T.; Lockwitz, S.; Loginov, A.; Lucchesi, D.; Lucà, A.; Lueck, J.; Lujan, P.; Lukens, P.; Lungu, G.; Lys, J.; Lysak, R.; Madrak, R.; Maestro, P.; Malik, S.; Manca, G.; Manousakis-Katsikakis, A.; Marchese, L.; Margaroli, F.; Marino, P.; Matera, K.; Mattson, M. E.; Mazzacane, A.; Mazzanti, P.; McNulty, R.; Mehta, A.; Mehtala, P.; Mesropian, C.; Miao, T.; Mietlicki, D.; Mitra, A.; Miyake, H.; Moed, S.; Moggi, N.; Moon, C. S.; Moore, R.; Morello, M. J.; Mukherjee, A.; Muller, Th.; Murat, P.; Mussini, M.; Nachtman, J.; Nagai, Y.; Naganoma, J.; Nakano, I.; Napier, A.; Nett, J.; Nigmanov, T.; Nodulman, L.; Noh, S. Y.; Norniella, O.; Oakes, L.; Oh, S. H.; Oh, Y. D.; Okusawa, T.; Orava, R.; Ortolan, L.; Pagliarone, C.; Palencia, E.; Palni, P.; Papadimitriou, V.; Parker, W.; Pauletta, G.; Paulini, M.; Paus, C.; Phillips, T. J.; Piacentino, G.; Pianori, E.; Pilot, J.; Pitts, K.; Plager, C.; Pondrom, L.; Poprocki, S.; Potamianos, K.; Pranko, A.; Prokoshin, F.; Ptohos, F.; Punzi, G.; Redondo Fernández, I.; Renton, P.; Rescigno, M.; Rimondi, F.; Ristori, L.; Robson, A.; Rodriguez, T.; Rolli, S.; Ronzani, M.; Roser, R.; Rosner, J. L.; Ruffini, F.; Ruiz, A.; Russ, J.; Rusu, V.; Sakumoto, W. K.; Sakurai, Y.; Santi, L.; Sato, K.; Saveliev, V.; Savoy-Navarro, A.; Schlabach, P.; Schmidt, E. E.; Schwarz, T.; Scodellaro, L.; Scuri, F.; Seidel, S.; Seiya, Y.; Semenov, A.; Sforza, F.; Shalhout, S. Z.; Shears, T.; Shepard, P. F.; Shimojima, M.; Shochet, M.; Shreyber-Tecker, I.; Simonenko, A.; Sliwa, K.; Smith, J. R.; Snider, F. D.; Song, H.; Sorin, V.; St. Denis, R.; Stancari, M.; Stentz, D.; Strologas, J.; Sudo, Y.; Sukhanov, A.; Suslov, I.; Takemasa, K.; Takeuchi, Y.; Tang, J.; Tecchio, M.; Teng, P. K.; Thom, J.; Thomson, E.; Thukral, V.; Toback, D.; Tokar, S.; Tollefson, K.; Tomura, T.; Tonelli, D.; Torre, S.; Torretta, D.; Totaro, P.; Trovato, M.; Ukegawa, F.; Uozumi, S.; Vázquez, F.; Velev, G.; Vellidis, C.; Vernieri, C.; Vidal, M.; Vilar, R.; Vizán, J.; Vogel, M.; Volpi, G.; Wagner, P.; Wallny, R.; Wang, S. M.; Waters, D.; Wester, W. C.; Whiteson, D.; Wicklund, A. B.; Wilbur, S.; Williams, H. H.; Wilson, J. S.; Wilson, P.; Winer, B. L.; Wittich, P.; Wolbers, S.; Wolfe, H.; Wright, T.; Wu, X.; Wu, Z.; Yamamoto, K.; Yamato, D.; Yang, T.; Yang, U. K.; Yang, Y. C.; Yao, W.-M.; Yeh, G. P.; Yi, K.; Yoh, J.; Yorita, K.; Yoshida, T.; Yu, G. B.; Yu, I.; Zanetti, A. M.; Zeng, Y.; Zhou, C.; Zucchelli, S.; CDF Collaboration

2016-06-01

We measure the forward-backward asymmetry of the production of top-quark and antiquark pairs in proton-antiproton collisions at center-of-mass energy √{s }=1.96 TeV using the full data set collected by the Collider Detector at Fermilab (CDF) in Tevatron Run II corresponding to an integrated luminosity of 9.1 fb-1 . The asymmetry is characterized by the rapidity difference between top quarks and antiquarks (Δ y ) and measured in the final state with two charged leptons (electrons and muons). The inclusive asymmetry, corrected to the entire phase space at parton level, is measured to be AFBt t ¯=0.12 ±0.13 , consistent with the expectations from the standard model (SM) and previous CDF results in the final state with a single charged lepton. The combination of the CDF measurements of the inclusive AFBt t ¯ in both final states yields AFBt t ¯=0.160 ±0.045 , which is consistent with the SM predictions. We also measure the differential asymmetry as a function of Δ y . A linear fit to AFBt t ¯(|Δ y |), assuming zero asymmetry at Δ y =0 , yields a slope of α =0.14 ±0.15 , consistent with the SM prediction and the previous CDF determination in the final state with a single charged lepton. The combined slope of AFBt t ¯(|Δ y |) in the two final states is α =0.227 ±0.057 , which is 2.0 σ larger than the SM prediction.

Thread mapping using system-level model for shared memory multicores

NASA Astrophysics Data System (ADS)

Mitra, Reshmi

Exploring thread-to-core mapping options for a parallel application on a multicore architecture is computationally very expensive. For the same algorithm, the mapping strategy (MS) with the best response time may change with data size and thread counts. The primary challenge is to design a fast, accurate and automatic framework for exploring these MSs for large data-intensive applications. This is to ensure that the users can explore the design space within reasonable machine hours, without thorough understanding on how the code interacts with the platform. Response time is related to the cycles per instructions retired (CPI), taking into account both active and sleep states of the pipeline. This work establishes a hybrid approach, based on Markov Chain Model (MCM) and Model Tree (MT) for system-level steady state CPI prediction. It is designed for shared memory multicore processors with coarse-grained multithreading. The thread status is represented by the MCM states. The program characteristics are modeled as the transition probabilities, representing the system moving between active and suspended thread states. The MT model extrapolates these probabilities for the actual application size (AS) from the smaller AS performance. This aspect of the framework, along with, the use of mathematical expressions for the actual AS performance information, results in a tremendous reduction in the CPI prediction time. The framework is validated using an electromagnetics application. The average performance prediction error for steady state CPI results with 12 different MSs is less than 1%. The total run time of model is of the order of minutes, whereas the actual application execution time is in terms of days.

Hidden Fermi liquid; the moral: a good effective low-energy theory is worth all of Monte Carlo with Las Vegas thrown in

NASA Astrophysics Data System (ADS)

Anderson, Philip W.; Casey, Philip A.

2010-04-01

We present a formalism for dealing directly with the effects of the Gutzwiller projection implicit in the t-J model which is widely believed to underlie the phenomenology of the high-Tc cuprates. We suggest that a true Bardeen-Cooper-Schrieffer condensation from a Fermi liquid state takes place, but in the unphysical space prior to projection. At low doping, however, instead of a hidden Fermi liquid one gets a 'hidden' non-superconducting resonating valence bond state which develops hole pockets upon doping. The theory which results upon projection does not follow conventional rules of diagram theory and in fact in the normal state is a Z = 0 non-Fermi liquid. Anomalous properties of the 'strange metal' normal state are predicted and compared against experimental findings.

Optimization of nonlinear, non-Gaussian Bayesian filtering for diagnosis and prognosis of monotonic degradation processes

NASA Astrophysics Data System (ADS)

Corbetta, Matteo; Sbarufatti, Claudio; Giglio, Marco; Todd, Michael D.

2018-05-01

The present work critically analyzes the probabilistic definition of dynamic state-space models subject to Bayesian filters used for monitoring and predicting monotonic degradation processes. The study focuses on the selection of the random process, often called process noise, which is a key perturbation source in the evolution equation of particle filtering. Despite the large number of applications of particle filtering predicting structural degradation, the adequacy of the picked process noise has not been investigated. This paper reviews existing process noise models that are typically embedded in particle filters dedicated to monitoring and predicting structural damage caused by fatigue, which is monotonic in nature. The analysis emphasizes that existing formulations of the process noise can jeopardize the performance of the filter in terms of state estimation and remaining life prediction (i.e., damage prognosis). This paper subsequently proposes an optimal and unbiased process noise model and a list of requirements that the stochastic model must satisfy to guarantee high prognostic performance. These requirements are useful for future and further implementations of particle filtering for monotonic system dynamics. The validity of the new process noise formulation is assessed against experimental fatigue crack growth data from a full-scale aeronautical structure using dedicated performance metrics.

Selective Tree-ring Models: A Novel Method for Reconstructing Streamflow Using Tree Rings

NASA Astrophysics Data System (ADS)

Foard, M. B.; Nelson, A. S.; Harley, G. L.

2017-12-01

Surface water is among the most instrumental and vulnerable resources in the Northwest United States (NW). Recent observations show that overall water quantity is declining in streams across the region, while extreme flooding events occur more frequently. Historical streamflow models inform probabilities of extreme flow events (flood or drought) by describing frequency and duration of past events. There are numerous examples of tree-rings being utilized to reconstruct streamflow in the NW. These models confirm that tree-rings are highly accurate at predicting streamflow, however there are many nuances that limit their applicability through time and space. For example, most models predict streamflow from hydrologically altered rivers (e.g. dammed, channelized) which may hinder our ability to predict natural prehistoric flow. They also have a tendency to over/under-predict extreme flow events. Moreover, they often neglect to capture the changing relationships between tree-growth and streamflow over time and space. To address these limitations, we utilized national tree-ring and streamflow archives to investigate the relationships between the growth of multiple coniferous species and free-flowing streams across the NW using novel species-and site-specific streamflow models - a term we coined"selective tree-ring models." Correlation function analysis and regression modeling were used to evaluate the strengths and directions of the flow-growth relationships. Species with significant relationships in the same direction were identified as strong candidates for selective models. Temporal and spatial patterns of these relationships were examined using running correlations and inverse distance weighting interpolation, respectively. Our early results indicate that (1) species adapted to extreme climates (e.g. hot-dry, cold-wet) exhibit the most consistent relationships across space, (2) these relationships weaken in locations with mild climatic variability, and (3) some species appear to be strong candidates for predicting high flow events, while others may be better at pridicting drought. These findings indicate that selective models may outperform traditional models when reconstructing distinctive aspects of streamflow.

Outcome Prediction in Mathematical Models of Immune Response to Infection.

PubMed

Mai, Manuel; Wang, Kun; Huber, Greg; Kirby, Michael; Shattuck, Mark D; O'Hern, Corey S

2015-01-01

Clinicians need to predict patient outcomes with high accuracy as early as possible after disease inception. In this manuscript, we show that patient-to-patient variability sets a fundamental limit on outcome prediction accuracy for a general class of mathematical models for the immune response to infection. However, accuracy can be increased at the expense of delayed prognosis. We investigate several systems of ordinary differential equations (ODEs) that model the host immune response to a pathogen load. Advantages of systems of ODEs for investigating the immune response to infection include the ability to collect data on large numbers of 'virtual patients', each with a given set of model parameters, and obtain many time points during the course of the infection. We implement patient-to-patient variability v in the ODE models by randomly selecting the model parameters from distributions with coefficients of variation v that are centered on physiological values. We use logistic regression with one-versus-all classification to predict the discrete steady-state outcomes of the system. We find that the prediction algorithm achieves near 100% accuracy for v = 0, and the accuracy decreases with increasing v for all ODE models studied. The fact that multiple steady-state outcomes can be obtained for a given initial condition, i.e. the basins of attraction overlap in the space of initial conditions, limits the prediction accuracy for v > 0. Increasing the elapsed time of the variables used to train and test the classifier, increases the prediction accuracy, while adding explicit external noise to the ODE models decreases the prediction accuracy. Our results quantify the competition between early prognosis and high prediction accuracy that is frequently encountered by clinicians.

Predicting Material Performance in the Space Environment from Laboratory Test Data, Static Design Environments, and Space Weather Models

NASA Technical Reports Server (NTRS)

Minow, Josep I.; Edwards, David L.

2008-01-01

Qualifying materials for use in the space environment is typically accomplished with laboratory exposures to simulated UV/EUV, atomic oxygen, and charged particle radiation environments with in-situ or subsequent measurements of material properties of interest to the particular application. Choice of environment exposure levels are derived from static design environments intended to represent either mean or extreme conditions that are anticipated to be encountered during a mission. The real space environment however is quite variable. Predictions of the on orbit performance of a material qualified to laboratory environments can be done using information on 'space weather' variations in the real environment. This presentation will first review the variability of space environments of concern for material degradation and then demonstrate techniques for using test data to predict material performance in a variety of space environments from low Earth orbit to interplanetary space using historical measurements and space weather models.

Simulated Aging of Spacecraft External Materials on Orbit

NASA Astrophysics Data System (ADS)

Khatipov, S.

Moscow State Engineering Physics Institute (MIFI), in cooperation with Air Force Research Laboratory's Satellite Assessment Center (SatAC), the European Office of Aerospace Research and Development (EOARD), and the International Science and Technology Center (ISTC), has developed a database describing the changes in optical properties of materials used on the external surfaces of spacecraft due to space environmental factors. The database includes data acquired from tests completed under contract with the ISTC and EOARD, as well as from previous Russian materials studies conducted within the last 30 years. The space environmental factors studied are for those found in Low Earth Orbits (LEO) and Geosynchronous orbits (GEO), including electron irradiation at 50, 100, and 200 keV, proton irradiation at 50, 150, 300, and 500 keV, and ultraviolet irradiation equivalent to 1 sun-year. The material characteristics investigated were solar absorption (aS), spectral reflectance (rl), solar reflectance (rS), emissivity (e), spectral transmission coefficient (Tl), solar transmittance (TS), optical density (D), relative optical density (D/x), Bi-directional Reflectance Distribution Function (BRDF), and change of appearance and color in the visible wavelengths. The materials tested in the project were thermal control coatings (paints), multilayer insulation (films), and solar cells. The ability to predict changes in optical properties of spacecraft materials is important to increase the fidelity of space observation tools, better understand observation of space objects, and increase the longevity of spacecraft. The end goal of our project is to build semi-empirical mathematical models to predict the long-term effects of space aging as a function of time and orbit.

A Subjective Test of Modulated Blade Spacing for Helicopter Main Rotors

NASA Technical Reports Server (NTRS)

Sullivan, Brenda M.; Edwards, Bryan D.; Brentner, Kenneth S.; Booth, Earl R., Jr.

2002-01-01

Analytically, uneven (modulated) spacing of main rotor blades was found to reduce helicopter noise. A study was performed to see if these reductions transferred to improvements in subjective response. Using a predictive computer code, sounds produced by six main rotor configurations: 4 blades evenly spaced, 5 blades evenly spaced and four configurations with 5 blades with modulated spacing of varying amounts, were predicted. These predictions were converted to audible sounds corresponding to the level flyover, takeoff and approach flight conditions. Subjects who heard the simulations were asked to assess the overflight sounds in terms of noisiness on a scale of 0 to 10. In general the evenly spaced configurations were found less noisy than the modulated spacings, possibly because the uneven spacings produced a perceptible pulsating sound due to the very low fundamental frequency.

The transition from the open minimum to the ring minimum on the ground state and on the lowest excited state of like symmetry in ozone: A configuration interaction study

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

Theis, Daniel; Windus, Theresa L.; Ruedenberg, Klaus

The metastable ring structure of the ozone 1{sup 1}A{sub 1} ground state, which theoretical calculations have shown to exist, has so far eluded experimental detection. An accurate prediction for the energy difference between this isomer and the lower open structure is therefore of interest, as is a prediction for the isomerization barrier between them, which results from interactions between the lowest two {sup 1}A{sub 1} states. In the present work, valence correlated energies of the 1{sup 1}A{sub 1} state and the 2{sup 1}A{sub 1} state were calculated at the 1{sup 1}A{sub 1} open minimum, the 1{sup 1}A{sub 1} ring minimum,more » the transition state between these two minima, the minimum of the 2{sup 1}A{sub 1} state, and the conical intersection between the two states. The geometries were determined at the full-valence multi-configuration self-consistent-field level. Configuration interaction (CI) expansions up to quadruple excitations were calculated with triple-zeta atomic basis sets. The CI expansions based on eight different reference configuration spaces were explored. To obtain some of the quadruple excitation energies, the method of Correlation Energy Extrapolation by Intrinsic Scaling was generalized to the simultaneous extrapolation for two states. This extrapolation method was shown to be very accurate. On the other hand, none of the CI expansions were found to have converged to millihartree (mh) accuracy at the quadruple excitation level. The data suggest that convergence to mh accuracy is probably attained at the sextuple excitation level. On the 1{sup 1}A{sub 1} state, the present calculations yield the estimates of (ring minimum—open minimum) ∼45–50 mh and (transition state—open minimum) ∼85–90 mh. For the (2{sup 1}A{sub 1}–{sup 1}A{sub 1}) excitation energy, the estimate of ∼130–170 mh is found at the open minimum and 270–310 mh at the ring minimum. At the transition state, the difference (2{sup 1}A{sub 1}–{sup 1}A{sub 1}) is found to be between 1 and 10 mh. The geometry of the transition state on the 1{sup 1}A{sub 1} surface and that of the minimum on the 2{sup 1}A{sub 1} surface nearly coincide. More accurate predictions of the energy differences also require CI expansions to at least sextuple excitations with respect to the valence space. For every wave function considered, the omission of the correlations of the 2s oxygen orbitals, which is a widely used approximation, was found to cause errors of about ±10 mh with respect to the energy differences.« less

Thermographic imaging of the space shuttle during re-entry using a near-infrared sensor

NASA Astrophysics Data System (ADS)

Zalameda, Joseph N.; Horvath, Thomas J.; Kerns, Robbie V.; Burke, Eric R.; Taylor, Jeff C.; Spisz, Tom; Gibson, David M.; Shea, Edward J.; Mercer, C. David; Schwartz, Richard J.; Tack, Steve; Bush, Brett C.; Dantowitz, Ronald F.; Kozubal, Marek J.

2012-06-01

High resolution calibrated near infrared (NIR) imagery of the Space Shuttle Orbiter was obtained during hypervelocity atmospheric re-entry of the STS-119, STS-125, STS-128, STS-131, STS-132, STS-133, and STS-134 missions. This data has provided information on the distribution of surface temperature and the state of the airflow over the windward surface of the Orbiter during descent. The thermal imagery complemented data collected with onboard surface thermocouple instrumentation. The spatially resolved global thermal measurements made during the Orbiter's hypersonic re-entry will provide critical flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is critical for the validation of physics-based, semi-empirical boundary-layer transition prediction methods as well as stimulating the validation of laminar numerical chemistry models and the development of turbulence models supporting NASA's next-generation spacecraft. In this paper we provide details of the NIR imaging system used on both air and land-based imaging assets. The paper will discuss calibrations performed on the NIR imaging systems that permitted conversion of captured radiant intensity (counts) to temperature values. Image processing techniques are presented to analyze the NIR data for vignetting distortion, best resolution, and image sharpness.

Modeling high resolution space-time variations in energy demand/CO2 emissions of human inhabited landscapes in the United States under a changing climate

NASA Astrophysics Data System (ADS)

Godbole, A. V.; Gurney, K. R.

2010-12-01

With urban and exurban areas now accounting for more than 50% of the world's population, projected to increase 20% by 2050 (UN World Urbanization Prospects, 2009), urban-climate interactions are of renewed interest to the climate change scientific community (Karl et. al, 1988; Kalnay and Cai, 2003; Seto and Shepherd, 2009). Until recently, climate modeling efforts treated urban-human systems as independent of the earth system. With studies pointing to the disproportionately large influence of urban areas on their surrounding environment (Small et. al, 2010), modeling efforts have begun to explicitly account for urban processes in land models, like the CLM 4.0 urban layer, for example (Oleson.et. al, 2008, 2010). A significant portion of the urban energy demand comes from the space heating and cooling requirement of the residential and commercial sectors - as much as 51% (DOE, RECS 2005) and 11% (Belzer, D. 2006) respectively, in the United States. Thus, these sectors are both responsible for a significant fraction of fossil fuel CO2 emissions and will be influenced by a changing climate through changes in energy use and energy supply planning. This points to the possibility of interactive processes and feedbacks with the climate system. Space conditioning energy demand is strongly driven by external air temperature (Ruth, M. et.al, 2006) in addition to other socio-economic variables such as building characteristics (age of structure, activity cycle, weekend/weekday usage profile), occupant characteristics (age of householder, household income) and energy prices (Huang, 2006; Santin et. al, 2009; Isaac and van Vuuren, 2009). All of these variables vary both in space and time. Projections of climate change have begun to simulate changes in temperature at much higher resolution than in the past (Diffenbaugh et. al, 2005). Hence, in order to understand how climate change and variability will potentially impact energy use/emissions and energy planning, these two components of the human-climate system must be coupled in climate modeling efforts to better understand the impacts and feedbacks. To implement modeling strategies for coupling the human and climate systems, their interactions must first be examined in greater detail at high spatial and temporal resolutions. This work attempts to quantify the impact of high resolution variations in projected climate change on energy use/emissions in the United States. We develop a predictive model for the space heating component of residential and commercial energy demand by leveraging results from the high resolution fossil fuel CO2 inventory of the Vulcan Project (Gurney et al., 2009). This predictive model is driven by high resolution temperature data from the RegCM3 model obtained by implementing a downscaling algorithm (Chow and Levermore, 2007). We will present the energy use/emissions in both the space and time domain from two different predictive models highlighting strengths and weaknesses in both. Furthermore, we will explore high frequency variations in the projected temperature field and how these might place potentially large burdens on energy supply and delivery.

COI Structural Analysis Presentation

NASA Technical Reports Server (NTRS)

Cline, Todd; Stahl, H. Philip (Technical Monitor)

2001-01-01

This report discusses the structural analysis of the Next Generation Space Telescope Mirror System Demonstrator (NMSD) developed by Composite Optics Incorporated (COI) in support of the Next Generation Space Telescope (NGST) project. The mirror was submitted to Marshall Space Flight Center (MSFC) for cryogenic testing and evaluation. Once at MSFC, the mirror was lowered to approximately 40 K and the optical surface distortions were measured. Alongside this experiment, an analytical model was developed and used to compare to the test results. A NASTRAN finite element model was provided by COI and a thermal model was developed from it. Using the thermal model, steady state nodal temperatures were calculated based on the predicted environment of the large cryogenic test chamber at MSFC. This temperature distribution was applied in the structural analysis to solve for the deflections of the optical surface. Finally, these deflections were submitted for optical analysis and comparison to the interferometer test data.

A Blocked Linear Method for Optimizing Large Parameter Sets in Variational Monte Carlo

DOE PAGES

Zhao, Luning; Neuscamman, Eric

2017-05-17

We present a modification to variational Monte Carlo’s linear method optimization scheme that addresses a critical memory bottleneck while maintaining compatibility with both the traditional ground state variational principle and our recently-introduced variational principle for excited states. For wave function ansatzes with tens of thousands of variables, our modification reduces the required memory per parallel process from tens of gigabytes to hundreds of megabytes, making the methodology a much better fit for modern supercomputer architectures in which data communication and per-process memory consumption are primary concerns. We verify the efficacy of the new optimization scheme in small molecule tests involvingmore » both the Hilbert space Jastrow antisymmetric geminal power ansatz and real space multi-Slater Jastrow expansions. Satisfied with its performance, we have added the optimizer to the QMCPACK software package, with which we demonstrate on a hydrogen ring a prototype approach for making systematically convergent, non-perturbative predictions of Mott-insulators’ optical band gaps.« less

Satisfying the Einstein–Podolsky–Rosen criterion with massive particles

PubMed Central

Peise, J.; Kruse, I.; Lange, K.; Lücke, B.; Pezzè, L.; Arlt, J.; Ertmer, W.; Hammerer, K.; Santos, L.; Smerzi, A.; Klempt, C.

2015-01-01

In 1935, Einstein, Podolsky and Rosen (EPR) questioned the completeness of quantum mechanics by devising a quantum state of two massive particles with maximally correlated space and momentum coordinates. The EPR criterion qualifies such continuous-variable entangled states, where a measurement of one subsystem seemingly allows for a prediction of the second subsystem beyond the Heisenberg uncertainty relation. Up to now, continuous-variable EPR correlations have only been created with photons, while the demonstration of such strongly correlated states with massive particles is still outstanding. Here we report on the creation of an EPR-correlated two-mode squeezed state in an ultracold atomic ensemble. The state shows an EPR entanglement parameter of 0.18(3), which is 2.4 s.d. below the threshold 1/4 of the EPR criterion. We also present a full tomographic reconstruction of the underlying many-particle quantum state. The state presents a resource for tests of quantum nonlocality and a wide variety of applications in the field of continuous-variable quantum information and metrology. PMID:26612105

Satisfying the Einstein-Podolsky-Rosen criterion with massive particles.

PubMed

Peise, J; Kruse, I; Lange, K; Lücke, B; Pezzè, L; Arlt, J; Ertmer, W; Hammerer, K; Santos, L; Smerzi, A; Klempt, C

2015-11-27

In 1935, Einstein, Podolsky and Rosen (EPR) questioned the completeness of quantum mechanics by devising a quantum state of two massive particles with maximally correlated space and momentum coordinates. The EPR criterion qualifies such continuous-variable entangled states, where a measurement of one subsystem seemingly allows for a prediction of the second subsystem beyond the Heisenberg uncertainty relation. Up to now, continuous-variable EPR correlations have only been created with photons, while the demonstration of such strongly correlated states with massive particles is still outstanding. Here we report on the creation of an EPR-correlated two-mode squeezed state in an ultracold atomic ensemble. The state shows an EPR entanglement parameter of 0.18(3), which is 2.4 s.d. below the threshold 1/4 of the EPR criterion. We also present a full tomographic reconstruction of the underlying many-particle quantum state. The state presents a resource for tests of quantum nonlocality and a wide variety of applications in the field of continuous-variable quantum information and metrology.

Satisfying the Einstein-Podolsky-Rosen criterion with massive particles

NASA Astrophysics Data System (ADS)

Peise, J.; Kruse, I.; Lange, K.; Lücke, B.; Pezzè, L.; Arlt, J.; Ertmer, W.; Hammerer, K.; Santos, L.; Smerzi, A.; Klempt, C.

2015-11-01

In 1935, Einstein, Podolsky and Rosen (EPR) questioned the completeness of quantum mechanics by devising a quantum state of two massive particles with maximally correlated space and momentum coordinates. The EPR criterion qualifies such continuous-variable entangled states, where a measurement of one subsystem seemingly allows for a prediction of the second subsystem beyond the Heisenberg uncertainty relation. Up to now, continuous-variable EPR correlations have only been created with photons, while the demonstration of such strongly correlated states with massive particles is still outstanding. Here we report on the creation of an EPR-correlated two-mode squeezed state in an ultracold atomic ensemble. The state shows an EPR entanglement parameter of 0.18(3), which is 2.4 s.d. below the threshold 1/4 of the EPR criterion. We also present a full tomographic reconstruction of the underlying many-particle quantum state. The state presents a resource for tests of quantum nonlocality and a wide variety of applications in the field of continuous-variable quantum information and metrology.

Modeling AWSoM CMEs with EEGGL: A New Approach for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Jin, M.; Manchester, W.; van der Holst, B.; Sokolov, I.; Toth, G.; Vourlidas, A.; de Koning, C. A.; Gombosi, T. I.

2015-12-01

The major source of destructive space weather is coronal mass ejections (CMEs). However, our understanding of CMEs and their propagation in the heliosphere is limited by the insufficient observations. Therefore, the development of first-principals numerical models plays a vital role in both theoretical investigation and providing space weather forecasts. Here, we present results of the simulation of CME propagation from the Sun to 1AU by combining the analytical Gibson & Low (GL) flux rope model with the state-of-art solar wind model AWSoM. We also provide an approach for transferring this research model to a space weather forecasting tool by demonstrating how the free parameters of the GL flux rope can be prescribed based on remote observations via the new Eruptive Event Generator by Gibson-Low (EEGGL) toolkit. This capability allows us to predict the long-term evolution of the CME in interplanetary space. We perform proof-of-concept case studies to show the capability of the model to capture physical processes that determine CME evolution while also reproducing many observed features both in the corona and at 1 AU. We discuss the potential and limitations of this model as a future space weather forecasting tool.

State of the art for ab initio vs empirical potentials for HeH+ (2e-), BeH+ (4e-), BeH (5e-), Li2 (6e-) and BH (6e-)

NASA Astrophysics Data System (ADS)

Dattani, Nike

For large internuclear distances, the potential energy between two atoms is known analytically, based on constants that are calculated from atomic ab initio rather than molecular ab initio. This analytic form can be built into models for molecular potentials that are fitted to spectroscopic data. Such empirical potentials constitute the most accurate molecular potentials known. For HeH+, and BeH+, the long-range form of the potential is based only on the polarizabilities for He and H respectively, for which we have included up to 4th order QED corrections. For BeH, the best ab initio potential matches all but one observed vibrational spacing to < 1 cm- accuracy, and for Li2 the discrepancy in the spacings is < 0.08 cm-1 for all vibrational levels. But experimental methods such as photoassociation require the absolute energies, not spacings, and these are still several in several cm-1 disagreement. So empirical potentials are still the only reliable way to predict energies for few-electron systems. We also give predictions for various unobserved ''halo nucleonic molecules'' containing the ''halo'' isotopes: 6,8He, 11Li, 11,14Be and 8 , 17 , 19B.

Electrical Performance of the International Space Station U.S. Photovoltaic Array During Bifacial Illumination

NASA Technical Reports Server (NTRS)

Delleur, Ann M.; Kerslake, Thomas W.

2002-01-01

With the first United States (U.S.) photovoltaic array (PVA) activated on International Space Station (ISS) in December 2000, on-orbit data can now be compared to analytical predictions. Due to ISS operational constraints, it is not always possible to point the front side of the arrays at the Sun. Thus, in many cases, sunlight directly illuminates the backside of the PVA as well as albedo illumination on either the front or the back. During this time, appreciable power is produced since the solar cells are mounted on a thin, solar transparent substrate. It is important to present accurate predictions for both front and backside power generation for mission planning, certification of flight readiness for a given mission, and on-orbit mission support. To provide a more detailed assessment of the ISS power production capability, the authors developed a PVA electrical performance model applicable to generalized bifacial illumination conditions. On-orbit PVA performance data were also collected and analyzed. This paper describes the ISS PVA performance model, and the methods used to reduce orbital performance data. Analyses were performed using SPACE. a NASA-GRC developed computer code for the ISS program office. Results showed a excellent comparison of on-orbit performance data and analytical results.

Free-space propagation of high-dimensional structured optical fields in an urban environment

PubMed Central

Lavery, Martin P. J.; Peuntinger, Christian; Günthner, Kevin; Banzer, Peter; Elser, Dominique; Boyd, Robert W.; Padgett, Miles J.; Marquardt, Christoph; Leuchs, Gerd

2017-01-01

Spatially structured optical fields have been used to enhance the functionality of a wide variety of systems that use light for sensing or information transfer. As higher-dimensional modes become a solution of choice in optical systems, it is important to develop channel models that suitably predict the effect of atmospheric turbulence on these modes. We investigate the propagation of a set of orthogonal spatial modes across a free-space channel between two buildings separated by 1.6 km. Given the circular geometry of a common optical lens, the orthogonal mode set we choose to implement is that described by the Laguerre-Gaussian (LG) field equations. Our study focuses on the preservation of phase purity, which is vital for spatial multiplexing and any system requiring full quantum-state tomography. We present experimental data for the modal degradation in a real urban environment and draw a comparison to recognized theoretical predictions of the link. Our findings indicate that adaptations to channel models are required to simulate the effects of atmospheric turbulence placed on high-dimensional structured modes that propagate over a long distance. Our study indicates that with mitigation of vortex splitting, potentially through precorrection techniques, one could overcome the challenges in a real point-to-point free-space channel in an urban environment. PMID:29075663

Free-space propagation of high-dimensional structured optical fields in an urban environment.

PubMed

Lavery, Martin P J; Peuntinger, Christian; Günthner, Kevin; Banzer, Peter; Elser, Dominique; Boyd, Robert W; Padgett, Miles J; Marquardt, Christoph; Leuchs, Gerd

2017-10-01

Spatially structured optical fields have been used to enhance the functionality of a wide variety of systems that use light for sensing or information transfer. As higher-dimensional modes become a solution of choice in optical systems, it is important to develop channel models that suitably predict the effect of atmospheric turbulence on these modes. We investigate the propagation of a set of orthogonal spatial modes across a free-space channel between two buildings separated by 1.6 km. Given the circular geometry of a common optical lens, the orthogonal mode set we choose to implement is that described by the Laguerre-Gaussian (LG) field equations. Our study focuses on the preservation of phase purity, which is vital for spatial multiplexing and any system requiring full quantum-state tomography. We present experimental data for the modal degradation in a real urban environment and draw a comparison to recognized theoretical predictions of the link. Our findings indicate that adaptations to channel models are required to simulate the effects of atmospheric turbulence placed on high-dimensional structured modes that propagate over a long distance. Our study indicates that with mitigation of vortex splitting, potentially through precorrection techniques, one could overcome the challenges in a real point-to-point free-space channel in an urban environment.

Understanding Epileptiform After-Discharges as Rhythmic Oscillatory Transients.

PubMed

Baier, Gerold; Taylor, Peter N; Wang, Yujiang

2017-01-01

Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients in response to stimulation. Even when using the same stimulation parameters in the same patient, wide variability in the duration of transient response has been reported. These transients have long been considered important for the mapping of the excitability levels in the epileptic brain but their dynamic mechanism is still not well understood. To investigate the occurrence of abnormal transients dynamically, we use a thalamo-cortical neural population model of epileptic spike-wave activity and study the interaction between slow and fast subsystems. In a reduced version of the thalamo-cortical model, slow wave oscillations arise from a fold of cycles (FoC) bifurcation. This marks the onset of a region of bistability between a high amplitude oscillatory rhythm and the background state. In vicinity of the bistability in parameter space, the model has excitable dynamics, showing prolonged rhythmic transients in response to suprathreshold pulse stimulation. We analyse the state space geometry of the bistable and excitable states, and find that the rhythmic transient arises when the impending FoC bifurcation deforms the state space and creates an area of locally reduced attraction to the fixed point. This area essentially allows trajectories to dwell there before escaping to the stable steady state, thus creating rhythmic transients. In the full thalamo-cortical model, we find a similar FoC bifurcation structure. Based on the analysis, we propose an explanation of why stimulation induced epileptiform activity may vary between trials, and predict how the variability could be related to ongoing oscillatory background activity. We compare our dynamic mechanism with other mechanisms (such as a slow parameter change) to generate excitable transients, and we discuss the proposed excitability mechanism in the context of stimulation responses in the epileptic cortex.

Advanced Subsonic Technology (AST) Area of Interest (AOI) 6: Develop and Validate Aeroelastic Codes for Turbomachinery

NASA Technical Reports Server (NTRS)

Gardner, Kevin D.; Liu, Jong-Shang; Murthy, Durbha V.; Kruse, Marlin J.; James, Darrell

1999-01-01

AlliedSignal Engines, in cooperation with NASA GRC (National Aeronautics and Space Administration Glenn Research Center), completed an evaluation of recently-developed aeroelastic computer codes using test cases from the AlliedSignal Engines fan blisk and turbine databases. Test data included strain gage, performance, and steady-state pressure information obtained for conditions where synchronous or flutter vibratory conditions were found to occur. Aeroelastic codes evaluated included quasi 3-D UNSFLO (MIT Developed/AE Modified, Quasi 3-D Aeroelastic Computer Code), 2-D FREPS (NASA-Developed Forced Response Prediction System Aeroelastic Computer Code), and 3-D TURBO-AE (NASA/Mississippi State University Developed 3-D Aeroelastic Computer Code). Unsteady pressure predictions for the turbine test case were used to evaluate the forced response prediction capabilities of each of the three aeroelastic codes. Additionally, one of the fan flutter cases was evaluated using TURBO-AE. The UNSFLO and FREPS evaluation predictions showed good agreement with the experimental test data trends, but quantitative improvements are needed. UNSFLO over-predicted turbine blade response reductions, while FREPS under-predicted them. The inviscid TURBO-AE turbine analysis predicted no discernible blade response reduction, indicating the necessity of including viscous effects for this test case. For the TURBO-AE fan blisk test case, significant effort was expended getting the viscous version of the code to give converged steady flow solutions for the transonic flow conditions. Once converged, the steady solutions provided an excellent match with test data and the calibrated DAWES (AlliedSignal 3-D Viscous Steady Flow CFD Solver). However, efforts expended establishing quality steady-state solutions prevented exercising the unsteady portion of the TURBO-AE code during the present program. AlliedSignal recommends that unsteady pressure measurement data be obtained for both test cases examined for use in aeroelastic code validation.

Wetting state and maximum spreading factor of microdroplets impacting on superhydrophobic textured surfaces with anisotropic arrays of pillars

NASA Astrophysics Data System (ADS)

Kwon, Dae Hee; Huh, Hyung Kyu; Lee, Sang Joon

2013-07-01

The dynamic behaviors of microdroplets that impact on textured surfaces with various patterns of microscale pillars are experimentally investigated in this study. A piezoelectric inkjet is used to generate the microdroplets that have a diameter of less than 46 μm and a controlled Weber number. The impact and spreading dynamics of an individual droplet are captured by using a high-speed imaging system. The anisotropic and directional wettability and the wetting states on the textured surfaces with anisotropically arranged pillars are revealed for the first time in this study. The impalement transition from the Cassie-Baxter state to the partially impaled state is evaluated by balancing the wetting pressure P wet and the capillary pressure P C even on the anisotropic textured surfaces. The maximum spreading factor is measured and compared with the theoretical prediction to elucidate the wettability of the textured surfaces. For a given Weber number, the maximum spreading factor decreases as the texture area fraction of the textured surface decreases. In addition, the maximum spreading factors along the direction of longer inter-pillar spacing always have smaller values than those along the direction of shorter inter-pillar spacing when a droplet impacts on the anisotropic arrays of pillars.

Gravitationally self-bound quantum states in unstable potentials

NASA Astrophysics Data System (ADS)

Jääskeläinen, Markku

2018-04-01

Quantum mechanics at present cannot be unified with the theory of gravity at the deepest level, and to guide research towards the solution of this fundamental problem, we need to look for ways to observe or refute predictions originating from attempts to combine quantum theory with gravity. The influence of the gravitational field created by the material density given by the wave function itself gives rise to nontrivial phenomena. In this study I consider the wave function for the center-of-mass coordinate of a spherical mass distribution under the influence of the self-interaction of Newtonian gravity. I solve numerically for the ground state in the presence of an unstable potential and find that the energy of the free-space bound state can be lowered despite the nontrapping character of the potential. The center-of-mass ground state becomes increasingly localized for the used unstable potentials, although only in a limited parameter regime. The feebleness of the energy shift makes the observation of these effects demanding and requires further developments in the cooling of material particles. In addition, the influence of gravitational perturbations that are present in typical laboratory settings necessitates the use of extremely quiet and controlled environments such as those provided by recently proposed space-borne experiments.

Predicting Mission Success in Small Satellite Missions

NASA Technical Reports Server (NTRS)

Saunders, Mark; Richie, Wayne; Rogers, John; Moore, Arlene

1992-01-01

In our global society with its increasing international competition and tighter financial resources, governments, commercial entities and other organizations are becoming critically aware of the need to ensure that space missions can be achieved on time and within budget. This has become particularly true for the National Aeronautics and Space Administration's (NASA) Office of Space Science (OSS) which has developed their Discovery and Explorer programs to meet this need. As technologies advance, space missions are becoming smaller and more capable than their predecessors. The ability to predict the mission success of these small satellite missions is critical to the continued achievement of NASA science mission objectives. The NASA Office of Space Science, in cooperation with the NASA Langley Research Center, has implemented a process to predict the likely success of missions proposed to its Discovery and Explorer Programs. This process is becoming the basis for predicting mission success in many other NASA programs as well. This paper describes the process, methodology, tools and synthesis techniques used to predict mission success for this class of mission.

Predicting Mission Success in Small Satellite Missions

NASA Technical Reports Server (NTRS)

Saunders, Mark; Richie, R. Wayne; Moore, Arlene; Rogers, John

1999-01-01

In our global society with its increasing international competition and tighter financial resources, governments, commercial entities and other organizations are becoming critically aware of the need to ensure that space missions can be achieved on time and within budget. This has become particularly true for the National Aeronautics and Space Administration's (NASA's) Office of Space Science (OSS) which has developed their Discovery and Explorer programs to meet this need. As technologies advance, space missions are becoming smaller and more capable than their predecessors. The ability to predict the mission success of these small satellite missions is critical to the continued achievement of NASA science mission objectives. The NASA Office of Space Science, in cooperation with the NASA Langley Research Center, has implemented a process to predict the likely success of missions proposed to its Discovery and Explorer Programs. This process is becoming the basis for predicting mission success in many other NASA programs as well. This paper describes the process, methodology, tools and synthesis techniques used to predict mission success for this class of mission.

Prediction Accuracy of Error Rates for MPTB Space Experiment

NASA Technical Reports Server (NTRS)

Buchner, S. P.; Campbell, A. B.; Davis, D.; McMorrow, D.; Petersen, E. L.; Stassinopoulos, E. G.; Ritter, J. C.

1998-01-01

This paper addresses the accuracy of radiation-induced upset-rate predictions in space using the results of ground-based measurements together with standard environmental and device models. The study is focused on two part types - 16 Mb NEC DRAM's (UPD4216) and 1 Kb SRAM's (AMD93L422) - both of which are currently in space on board the Microelectronics and Photonics Test Bed (MPTB). To date, ground-based measurements of proton-induced single event upset (SEM cross sections as a function of energy have been obtained and combined with models of the proton environment to predict proton-induced error rates in space. The role played by uncertainties in the environmental models will be determined by comparing the modeled radiation environment with the actual environment measured aboard MPTB. Heavy-ion induced upsets have also been obtained from MPTB and will be compared with the "predicted" error rate following ground testing that will be done in the near future. These results should help identify sources of uncertainty in predictions of SEU rates in space.

Space radiator simulation system analysis

NASA Technical Reports Server (NTRS)

Black, W. Z.; Wulff, W.

1972-01-01

A transient heat transfer analysis was carried out on a space radiator heat rejection system exposed to an arbitrarily prescribed combination of aerodynamic heating, solar, albedo, and planetary radiation. A rigorous analysis was carried out for the radiation panel and tubes lying in one plane and an approximate analysis was used to extend the rigorous analysis to the case of a curved panel. The analysis permits the consideration of both gaseous and liquid coolant fluids, including liquid metals, under prescribed, time dependent inlet conditions. The analysis provided a method for predicting: (1) transient and steady-state, two dimensional temperature profiles, (2) local and total heat rejection rates, (3) coolant flow pressure in the flow channel, and (4) total system weight and protection layer thickness.

System Analysis for the Huntsville Operation Support Center, Distributed Computer System

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Massey, D.

1985-01-01

HOSC as a distributed computing system, is responsible for data acquisition and analysis during Space Shuttle operations. HOSC also provides computing services for Marshall Space Flight Center's nonmission activities. As mission and nonmission activities change, so do the support functions of HOSC change, demonstrating the need for some method of simulating activity at HOSC in various configurations. The simulation developed in this work primarily models the HYPERchannel network. The model simulates the activity of a steady state network, reporting statistics such as, transmitted bits, collision statistics, frame sequences transmitted, and average message delay. These statistics are used to evaluate such performance indicators as throughout, utilization, and delay. Thus the overall performance of the network is evaluated, as well as predicting possible overload conditions.

Government/Industry Workshop on Payload Loads Technology

NASA Technical Reports Server (NTRS)

1978-01-01

A fully operational space shuttle is discussed which will offer science the opportunity to explore near earth orbit and finally interplanetary space on nearly a limitless basis. This multiplicity of payload/experiment combinations and frequency of launches places many burdens on dynamicists to predict launch and landing environments accurately and efficiently. Two major problems are apparent in the attempt to design for the diverse environments: (1) balancing the design criteria (loads, etc.) between launch and orbit operations, and (2) developing analytical techniques that are reliable, accurate, efficient, and low cost to meet the challenge of multiple launches and payloads. This paper deals with the key issues inherent in these problems, the key trades required, the basic approaches needed, and a summary of the state-of-the-art techniques.

Markov Modeling of Component Fault Growth over a Derived Domain of Feasible Output Control Effort Modifications

NASA Technical Reports Server (NTRS)

Bole, Brian; Goebel, Kai; Vachtsevanos, George

2012-01-01

This paper introduces a novel Markov process formulation of stochastic fault growth modeling, in order to facilitate the development and analysis of prognostics-based control adaptation. A metric representing the relative deviation between the nominal output of a system and the net output that is actually enacted by an implemented prognostics-based control routine, will be used to define the action space of the formulated Markov process. The state space of the Markov process will be defined in terms of an abstracted metric representing the relative health remaining in each of the system s components. The proposed formulation of component fault dynamics will conveniently relate feasible system output performance modifications to predictions of future component health deterioration.

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

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.

Differential and double-differential cross sections for the production of top quark pairs in proton-proton collisions at 13 TeV are measured as a function of jet multiplicity and of kinematic variables of the top quarks and the top quark-antiquark system. This analysis is based on data collected by the CMS experiment at the LHC corresponding to an integrated luminosity of 2.3 fb –1. The measurements are performed in the lepton+jets decay channels with a single muon or electron in the final state. Furthermore, the differential cross sections are presented at particle level, within a phase space close to the experimental acceptance,more » and at parton level in the full phase space. The results are compared to several standard model predictions.« less

Implications for the Cosmological Landscape: Can Thermal Inputs from a Prior Universe Account for Relic Graviton Production?

NASA Astrophysics Data System (ADS)

Beckwith, A. W.

2008-01-01

Sean Carroll's pre-inflation state of low temperature-low entropy provides a bridge between two models with different predictions. The Wheeler-de Witt equation provides thermal input into today's universe for graviton production. Also, brane world models by Sundrum allow low entropy conditions, as given by Carroll & Chen (2005). Moreover, this paper answers the question of how to go from a brane world model to the 10 to the 32 power Kelvin conditions stated by Weinberg in 1972 as necessary for the initiation of quantum gravity processes. This is a way of getting around the fact CMBR is cut off at a red shift of z = 1100. This paper discusses the difference in values of the upper bound of the cosmological constant between a large upper bound predicated for a temperature dependent vacuum energy predicted by Park (2002), and the much lower bound predicted by Barvinsky (2006). with the difference in values in vacuum energy contributing to relic graviton production. This paper claims that this large thermal influx, with a high initial cosmological constant and a large region of space for relic gravitons interacting with space-time up to the z = 1100 CMBR observational limit are interlinked processes delineated in the Lloyd (2002) analogy of the universe as a quantum computing system. Finally, the paper claims that linking a shrinking prior universe via a worm hole solution for a pseudo time dependent Wheeler-De Witt equation permits graviton generation as thermal input from the prior universe, transferred instantaneously to relic inflationary conditions today. The existence of a wormhole is presented as a necessary condition for relic gravitons. Proving the sufficiency of the existence of a worm hole for relic gravitons is a future project.

The Scintillation Prediction Observations Research Task (SPORT): an International Science Mission Using a Cubesat

NASA Technical Reports Server (NTRS)

Spann, James; Swenson, Charles; Durao, Otavio; Loures, Luis; Heelis, Rod; Bishop, Rebecca; Le, Guan; Abdu, Mangalathayil; Krause, Linda; Fry, Craig;

Water Flow Performance of a Superscale Model of the Fastrac Liquid Oxygen Pump

NASA Technical Reports Server (NTRS)

Skelley, Stephen; Zoladz, Thomas

2001-01-01

As part of the National Aeronautics and Space Administration's ongoing effort to lower the cost of access to space, the Marshall Space Flight Center has developed a rocket engine with 60,000 pounds of thrust for use on the Reusable Launch Vehicle technology demonstrator slated for launch in 2000. This gas generator cycle engine, known as the Fastrac engine, uses liquid oxygen and RP-1 for propellants and includes single stage liquid oxygen and RP-1 pumps and a single stage supersonic turbine on a common shaft. The turbopump design effort included the first use and application of new suction capability prediction codes and three-dimensional blade generation codes in an attempt to reduce the turbomachinery design and certification costs typically associated with rocket engine development. To verify the pump's predicted cavitation performance, a water flow test of a superscale model of the Fastrac liquid oxygen pump was conducted to experimentally evaluate the liquid oxygen pump's performance at and around the design point. The water flow test article replicated the flow path of the Fastrac liquid oxygen pump in a 1.582x scale model, including scaled seal clearances for correct leakage flow at a model operating speed of 5000 revolutions per minute. Flow entered the 3-blade axial-flow inducer, transitioned to a shrouded, 6- blade radial impeller, and discharged into a vaneless radial diffuser and collection volute. The test article included approximately 50 total and static pressure measurement locations as well as flush-mounted, high frequency pressure transducers for complete mapping of the pressure environment. The primary objectives of the water flow test were to measure the steady-state and dynamic pressure environment of the liquid oxygen pump versus flow coefficient, suction specific speed, and back face leakage flow rate. Initial results showed acceptable correlation between the predicted and experimentally measured pump head rise at low suction specific speeds. Likewise, only small circumferential variations in steady-state were observed from 80% to 120% of the design flow coefficient, matching the computational predictions and confirming that the integrated design approach has minimized any exit volute-induced distortions. The test article exhibited suction performance trends typically observed in inducer designs with virtually constant head rise with decreasing inlet pressure until complete pump head breakdown. Unfortunately, the net positive suction head at 3% head fall-off occurred far below that predicted at all tested flow coefficients, resulting in a negative net positive suction head margin at the design point in water. Additional testing to map the unsteady pressure environment was conducted and cavitation-induced flow disturbances at the inducer inlet were observed. Two distinct disturbances were identified, one rotating and one stationary relative to the fixed frame of reference, while the transition from one regime to the next produced significant effects on the steady state pump performance. The impact of the unsteady phenomena and the corresponding energy losses on the unexpectedly poor pump performance is also discussed.

An Early Prediction of Sunspot Cycle 25

NASA Astrophysics Data System (ADS)

Nandy, D.; Bhowmik, P.

2017-12-01

The Sun's magnetic activity governs our space environment, creates space weather and impacts our technologies and climate. With increasing reliance on space- and ground-based technologies that are subject to space weather, the need to be able to forecast the future activity of the Sun has assumed increasing importance. However, such long-range, decadal-scale space weather prediction has remained a great challenge as evident in the diverging forecasts for solar cycle 24. Based on recently acquired understanding of the physics of solar cycle predictability, we have devised a scheme to extend the forecasting window of solar cycles. Utilizing this we present an early forecast for sunspot cycle 25 which would be of use for space mission planning, satellite life-time estimates, and assessment of the long-term impacts of space weather on technological assets and planetary atmospheres.

Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

PubMed

Will, Sebastian; Jabbari, Hosna

2016-01-01

RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free software, available at http://www.bioinf.uni-leipzig.de/~will/Software/SparseMFEFold.

Ground Collision Avoidance System (Igcas)

NASA Technical Reports Server (NTRS)

Prosser, Kevin (Inventor); Hook, Loyd (Inventor); Skoog, Mark A (Inventor)

2017-01-01

The present invention is a system and method for aircraft ground collision avoidance (iGCAS) comprising a modular array of software, including a sense own state module configured to gather data to compute trajectory, a sense terrain module including a digital terrain map (DTM) and map manger routine to store and retrieve terrain elevations, a predict collision threat module configured to generate an elevation profile corresponding to the terrain under the trajectory computed by said sense own state module, a predict avoidance trajectory module configured to simulate avoidance maneuvers ahead of the aircraft, a determine need to avoid module configured to determine which avoidance maneuver should be used, when it should be initiated, and when it should be terminated, a notify Module configured to display each maneuver's viability to the pilot by a colored GUI, a pilot controls module configured to turn the system on and off, and an avoid module configured to define how an aircraft will perform avoidance maneuvers through 3-dimensional space.

Mass Spectra of Ds and Ωc in Lattice QCD with Nf = 2 + 1 + 1 Domain-Wall Quarks

NASA Astrophysics Data System (ADS)

Chiu, Ting-Wai

2018-03-01

We perform hybrid Monte Carlo simulation of lattice QCD with Nf = 2+1+1 optimal domain-wall quarks on the 323 × 64 lattice with lattice spacing a 0:06 fm, and generate a gauge ensemble with physical s and c quarks, and pion mass 280 MeV. Using 2-quark (meson) and 3-quark (baryon) interpolating operators, the mass spectra of the lowest-lying states containing s and c quarks (Ds and Ωc) are extracted [1], which turn out in good agreement with the high energy experimental values, together with the predictions of the charmed baryons which have not been observed in experiments. For the five new narrow c states observed by the LHCb Collaboration [2], the lowest-lying Ωc(3000) agrees with our predicted mass 3015(29)(34) MeV of the lowest-lying Ωc with JP = 1/2-. This implies that JP of Ωc(3000) is 1/2-.

Magnetic and noncentrosymmetric Weyl fermion semimetals in the R AlGe family of compounds (R =rare earth )

NASA Astrophysics Data System (ADS)

Chang, Guoqing; Singh, Bahadur; Xu, Su-Yang; Bian, Guang; Huang, Shin-Ming; Hsu, Chuang-Han; Belopolski, Ilya; Alidoust, Nasser; Sanchez, Daniel S.; Zheng, Hao; Lu, Hong; Zhang, Xiao; Bian, Yi; Chang, Tay-Rong; Jeng, Horng-Tay; Bansil, Arun; Hsu, Han; Jia, Shuang; Neupert, Titus; Lin, Hsin; Hasan, M. Zahid

2018-01-01

Weyl semimetals are novel topological conductors that host Weyl fermions as emergent quasiparticles. In this Rapid Communication, we propose a new type of Weyl semimetal state that breaks both time-reversal symmetry and inversion symmetry in the R AlGe (R =rare -earth ) family. Compared to previous predictions of magnetic Weyl semimetal candidates, the prediction of Weyl nodes in R AlGe is more robust and less dependent on the details of the magnetism because the Weyl nodes are generated already by the inversion breaking and the ferromagnetism acts as a simple Zeeman coupling that shifts the Weyl nodes in k space. Moreover, R AlGe offers remarkable tunability, which covers all varieties of Weyl semimetals including type I, type II, inversion breaking, and time-reversal breaking, depending on a suitable choice of the rare-earth elements. Furthermore, the unique noncentrosymmetric and ferromagnetic Weyl semimetal state in R AlGe enables the generation of spin currents.

Ab initio prediction of the vibration-rotation-tunneling spectrum of HCl-(H2O)2

NASA Astrophysics Data System (ADS)

Wormer, P. E. S.; Groenenboom, G. C.; van der Avoird, A.

2001-08-01

Quantum calculations of the vibration-rotation-tunneling (VRT) levels of the trimer HCl-(H2O)2 are presented. Two internal degrees of freedom are considered—the rotation angles of the two nonhydrogen-bonded (flipping) hydrogens in the complex—together with the overall rotation of the trimer in space. The kinetic energy expression of van der Avoird et al. [J. Chem. Phys. 105, 8034 (1996)] is used in a slightly modified form. The experimental microwave geometry of Kisiel et al. [J. Chem. Phys. 112, 5767 (2000)] served as input in the generation of a planar reference structure. The two-dimensional potential energy surface is generated ab initio by the iterative coupled-cluster method based on singly and doubly excited states with triply excited states included noniteratively [CCSD(T)]. Frequencies of vibrations and tunnel splittings are predicted for two isotopomers. The effect of the nonadditive three-body forces is considered and found to be important.

Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools

NASA Astrophysics Data System (ADS)

Shprits, Y.; Zhelavskaya, I. S.; Kellerman, A. C.; Spasojevic, M.; Kondrashov, D. A.; Ghil, M.; Aseev, N.; Castillo Tibocha, A. M.; Cervantes Villa, J. S.; Kletzing, C.; Kurth, W. S.

2017-12-01

Increasing volume of satellite measurements requires deployment of new tools that can utilize such vast amount of data. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the space environment. In this study we show how measurements can be combined by means of data assimilation and how machine learning can help analyze large amounts of data and can help develop global models that are trained on single point measurement. Data Assimilation: Manual analysis of the satellite measurements is a challenging task, while automated analysis is complicated by the fact that measurements are given at various locations in space, have different instrumental errors, and often vary by orders of magnitude. We show results of the long term reanalysis of radiation belt measurements along with fully operational real-time predictions using data assimilative VERB code. Machine Learning: We present application of the machine learning tools for the analysis of NASA Van Allen Probes upper-hybrid frequency measurements. Using the obtained data set we train a new global predictive neural network. The results for the Van Allen Probes based neural network are compared with historical IMAGE satellite observations. We also show examples of predictions of geomagnetic indices using neural networks. Combination of machine learning and data assimilation: We discuss how data assimilation tools and machine learning tools can be combine so that physics-based insight into the dynamics of the particular system can be combined with empirical knowledge of it's non-linear behavior.

Test of Martin's overkill hypothesis using radiocarbon dates on extinct megafauna.

PubMed

Surovell, Todd A; Pelton, Spencer R; Anderson-Sprecher, Richard; Myers, Adam D

2016-01-26

Following Martin [Martin PS (1973) Science 179:969-974], we propose the hypothesis that the timing of human arrival to the New World can be assessed by examining the ecological impacts of a small population of people on extinct Pleistocene megafauna. To that end, we compiled lists of direct radiocarbon dates on paleontological specimens of extinct genera from North and South America with the expectation that the initial decline of extinct megafauna should correspond in time with the initial evidence for human colonization and that those declines should occur first in eastern Beringia, next in the contiguous United States, and last in South America. Analyses of spacings and frequency distributions of radiocarbon dates for each region support the idea that the extinction event first commenced in Beringia, roughly 13,300-15,000 BP. For the United States and South America, extinctions commenced considerably later but were closely spaced in time. For the contiguous United States, extinction began at ca. 12,900-13,200 BP, and at ca. 12,600-13,900 BP in South America. For areas south of Beringia, these estimates correspond well with the first significant evidence for human presence and are consistent with the predictions of the overkill hypothesis.

Small-world networks exhibit pronounced intermittent synchronization

NASA Astrophysics Data System (ADS)

Choudhary, Anshul; Mitra, Chiranjit; Kohar, Vivek; Sinha, Sudeshna; Kurths, Jürgen

2017-11-01

We report the phenomenon of temporally intermittently synchronized and desynchronized dynamics in Watts-Strogatz networks of chaotic Rössler oscillators. We consider topologies for which the master stability function (MSF) predicts stable synchronized behaviour, as the rewiring probability (p) is tuned from 0 to 1. MSF essentially utilizes the largest non-zero Lyapunov exponent transversal to the synchronization manifold in making stability considerations, thereby ignoring the other Lyapunov exponents. However, for an N-node networked dynamical system, we observe that the difference in its Lyapunov spectra (corresponding to the N - 1 directions transversal to the synchronization manifold) is crucial and serves as an indicator of the presence of intermittently synchronized behaviour. In addition to the linear stability-based (MSF) analysis, we further provide global stability estimate in terms of the fraction of state-space volume shared by the intermittently synchronized state, as p is varied from 0 to 1. This fraction becomes appreciably large in the small-world regime, which is surprising, since this limit has been otherwise considered optimal for synchronized dynamics. Finally, we characterize the nature of the observed intermittency and its dominance in state-space as network rewiring probability (p) is varied.

Assessment of type II diabetes mellitus using irregularly sampled measurements with missing data.

PubMed

Barazandegan, Melissa; Ekram, Fatemeh; Kwok, Ezra; Gopaluni, Bhushan; Tulsyan, Aditya

2015-04-01

Diabetes mellitus is one of the leading diseases in the developed world. In order to better regulate blood glucose in a diabetic patient, improved modelling of insulin-glucose dynamics is a key factor in the treatment of diabetes mellitus. In the current work, the insulin-glucose dynamics in type II diabetes mellitus can be modelled by using a stochastic nonlinear state-space model. Estimating the parameters of such a model is difficult as only a few blood glucose and insulin measurements per day are available in a non-clinical setting. Therefore, developing a predictive model of the blood glucose of a person with type II diabetes mellitus is important when the glucose and insulin concentrations are only available at irregular intervals. To overcome these difficulties, we resort to online sequential Monte Carlo (SMC) estimation of states and parameters of the state-space model for type II diabetic patients under various levels of randomly missing clinical data. Our results show that this method is efficient in monitoring and estimating the dynamics of the peripheral glucose, insulin and incretins concentration when 10, 25 and 50% of the simulated clinical data were randomly removed.

Assessing the value of variational assimilation of streamflow data into distributed hydrologic models for improved streamflow monitoring and prediction at ungauged and gauged locations in the catchment

NASA Astrophysics Data System (ADS)

Lee, Hak Su; Seo, Dong-Jun; Liu, Yuqiong; McKee, Paul; Corby, Robert

2010-05-01

State updating of distributed hydrologic models via assimilation of streamflow data is subject to "overfitting" because large dimensionality of the state space of the model may render the assimilation problem seriously underdetermined. To examine the issue in the context of operational hydrology, we carried out a set of real-world experiments in which we assimilate streamflow data at interior and/or outlet locations into gridded SAC and kinematic-wave routing models of the U.S. National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM). We used for the experiments nine basins in the southern plains of the U.S. The experiments consist of selectively assimilating streamflow at different gauge locations, outlet and/or interior, and carrying out both dependent and independent validation. To assess the sensitivity of the quality of assimilation-aided streamflow simulation to the reduced dimensionality of the state space, we carried out data assimilation at spatially semi-distributed or lumped scale and by adjusting biases in precipitation and potential evaporation at a 6-hourly or larger scale. In this talk, we present the results and findings.

Simulator of Space Communication Networks

NASA Technical Reports Server (NTRS)

Clare, Loren; Jennings, Esther; Gao, Jay; Segui, John; Kwong, Winston

2005-01-01

Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) is a suite of software tools that simulates the behaviors of communication networks to be used in space exploration, and predict the performance of established and emerging space communication protocols and services. MACHETE consists of four general software systems: (1) a system for kinematic modeling of planetary and spacecraft motions; (2) a system for characterizing the engineering impact on the bandwidth and reliability of deep-space and in-situ communication links; (3) a system for generating traffic loads and modeling of protocol behaviors and state machines; and (4) a system of user-interface for performance metric visualizations. The kinematic-modeling system makes it possible to characterize space link connectivity effects, including occultations and signal losses arising from dynamic slant-range changes and antenna radiation patterns. The link-engineering system also accounts for antenna radiation patterns and other phenomena, including modulations, data rates, coding, noise, and multipath fading. The protocol system utilizes information from the kinematic-modeling and link-engineering systems to simulate operational scenarios of space missions and evaluate overall network performance. In addition, a Communications Effect Server (CES) interface for MACHETE has been developed to facilitate hybrid simulation of space communication networks with actual flight/ground software/hardware embedded in the overall system.

Space sickness predictors suggest fluid shift involvement and possible countermeasures

NASA Technical Reports Server (NTRS)

Simanonok, K. E.; Moseley, E. C.; Charles, J. B.

1992-01-01

Preflight data from 64 first time Shuttle crew members were examined retrospectively to predict space sickness severity (NONE, MILD, MODERATE, or SEVERE) by discriminant analysis. From 9 input variables relating to fluid, electrolyte, and cardiovascular status, 8 variables were chosen by discriminant analysis that correctly predicted space sickness severity with 59 pct. success by one method of cross validation on the original sample and 67 pct. by another method. The 8 variables in order of their importance for predicting space sickness severity are sitting systolic blood pressure, serum uric acid, calculated blood volume, serum phosphate, urine osmolality, environmental temperature at the launch site, red cell count, and serum chloride. These results suggest the presence of predisposing physiologic factors to space sickness that implicate a fluid shift etiology. Addition of a 10th input variable, hours spent in the Weightless Environment Training Facility (WETF), improved the prediction of space sickness severity to 66 pct. success by the first method of cross validation on the original sample and to 71 pct. by the second method. The data suggest that WETF training may reduce space sickness severity.

CAWSES Related Projects in Japan : Grant-in-Aid for Creative Scientific Research ügBasic Study of Space Weather Predictionüh and CHAIN (Continuous H Alpha Imaging Network)

NASA Astrophysics Data System (ADS)

Shibata, K.; Kurokawa, H.

The Grant-in-Aid for Creative Scientific Research of the Ministry of Education Science Sports Technology and Culture of Japan The Basic Study of Space Weather Prediction PI K Shibata Kyoto Univ has started in 2005 as 5 years projects with total budget 446Myen The purpose of this project is to develop a physical model of solar-terrestrial phenomena and space storms as a basis of space weather prediction by resolving fundamental physics of key phenomena from solar flares and coronal mass ejections to magnetospheric storms under international cooperation program CAWSES Climate and Weather of the Sun-Earth System Continuous H Alpha Imaging Network CHAIN Project led by H Kurokawa is a key project in this space weather study enabling continuous H alpha full Sun observations by connecting many solar telescopes in many countries through internet which provides the basis of the study of space weather prediction

Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data

PubMed Central

Pagán, Josué; Irene De Orbe, M.; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L.; Vivancos Mora, J.; Moya, José M.; Ayala, José L.

2015-01-01

Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives. PMID:26134103

Optimal strategy analysis based on robust predictive control for inventory system with random demand

NASA Astrophysics Data System (ADS)

Saputra, Aditya; Widowati, Sutrisno

2017-12-01

In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.

Are genetically robust regulatory networks dynamically different from random ones?

NASA Astrophysics Data System (ADS)

Sevim, Volkan; Rikvold, Per Arne

We study a genetic regulatory network model developed to demonstrate that genetic robustness can evolve through stabilizing selection for optimal phenotypes. We report preliminary results on whether such selection could result in a reorganization of the state space of the system. For the chosen parameters, the evolution moves the system slightly toward the more ordered part of the phase diagram. We also find that strong memory effects cause the Derrida annealed approximation to give erroneous predictions about the model's phase diagram.

Experimental Observation of Classical Dynamical Monodromy

NASA Astrophysics Data System (ADS)

Nerem, M. P.; Salmon, D.; Aubin, S.; Delos, J. B.

2018-03-01

A Hamiltonian system is said to have nontrivial monodromy if its fundamental action-angle loops do not return to their initial topological state at the end of a closed circuit in angular momentum-energy space. This process has been predicted to have consequences which can be seen in dynamical systems, called dynamical monodromy. Using an apparatus consisting of a spherical pendulum subject to magnetic potentials and torques, we observe nontrivial monodromy by the associated topological change in the evolution of a loop of trajectories.

Polarization changes in light beams trespassing anisotropic turbulence.

PubMed

Korotkova, Olga

2015-07-01

The polarization properties of deterministic or random light with isotropic source correlations propagating in anisotropic turbulence along horizontal paths are considered for the first time and predicted to change on the basis of the second-order coherence theory of beam-like fields and the extended Huygens-Fresnel integral. Our examples illustrate that the beams whose degree of polarization is unaffected by free-space propagation or isotropic turbulence can either decrease or increase on traversing the anisotropic turbulence, depending on the polarization state of the source.

Comparison of Unscented Kalman Filter and Unscented Schmidt Kalman Filter in Predicting Attitude and Associated Uncertainty of a Geosynchronous Satellite

DTIC Science & Technology

2014-09-01

the MLI coating, and similarly, the surface model as represented by the bidirectional reflectance distribution function ( BRDF ) will never be...surface model as represented by the bidirectional reflectance distribution function ( BRDF ) will never be identical to that found on actual space objects... BRDF model and how it compares to the Ashikhmin-Shirley BRDF [14] using similar nomenclature can be found in Ref. [15]. In this scenario, the state

Modeling dynamic acousto-elastic testing experiments: validation and perspectives.

PubMed

Gliozzi, A S; Scalerandi, M

2014-10-01

Materials possessing micro-inhomogeneities often display a nonlinear response to mechanical solicitations, which is sensitive to the confining pressure acting on the sample. Dynamic acoustoelastic testing allows measurement of the instantaneous variations in the elastic modulus due to the change of the dynamic pressure induced by a low-frequency wave. This paper shows that a Preisach-Mayergoyz space based hysteretic multi-state elastic model provides an explanation for experimental observations in consolidated granular media and predicts memory and nonlinear effects comparable to those measured in rocks.

Computationally guided discovery of thermoelectric materials

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

Gorai, Prashun; Stevanović, Vladan; Toberer, Eric S.

The potential for advances in thermoelectric materials, and thus solid-state refrigeration and power generation, is immense. Progress so far has been limited by both the breadth and diversity of the chemical space and the serial nature of experimental work. In this Review, we discuss how recent computational advances are revolutionizing our ability to predict electron and phonon transport and scattering, as well as materials dopability, and we examine efficient approaches to calculating critical transport properties across large chemical spaces. When coupled with experimental feedback, these high-throughput approaches can stimulate the discovery of new classes of thermoelectric materials. Within smaller materialsmore » subsets, computations can guide the optimal chemical and structural tailoring to enhance materials performance and provide insight into the underlying transport physics. Beyond perfect materials, computations can be used for the rational design of structural and chemical modifications (such as defects, interfaces, dopants and alloys) to provide additional control on transport properties to optimize performance. Through computational predictions for both materials searches and design, a new paradigm in thermoelectric materials discovery is emerging.« less

Cool Cosmology: ``WHISPER" better than ``BANG"

NASA Astrophysics Data System (ADS)

Carr, Paul

2007-10-01

Cosmologist Fred Hoyle coined ``big bang'' as a term of derision for Belgian priest George Lemaitre's prediction that the universe had originated from the expansion of a ``primeval atom'' in space-time. Hoyle referred to Lamaitre's hypothesis sarcastically as ``this big bang idea'' during a program broadcast on March 28, 1949 on the BBC. Hoyle's continuous creation or steady state theory can not explain the microwave background radiation or cosmic whisper discovered by Penzias and Wilson in 1964. The expansion and subsequent cooling of Lemaitre's hot ``primeval atom'' explains the whisper. ``Big bang'' makes no physical sense, as there was no matter (or space) to carry the sound that Hoyle's term implies. The ``big bang'' is a conjecture. New discoveries may be able to predict the observed ``whispering cosmos'' as well as dark matter and the nature of dark energy. The ``whispering universe'' is cooler cosmology than the big bang. Reference: Carr, Paul H. 2006. ``From the 'Music of the Spheres' to the 'Whispering Cosmos.' '' Chapter 3 of Beauty in Science and Spirit. Beech River Books. Center Ossipee, NH, http://www.MirrorOfNature.org.

Exploring the Model Design Space for Battery Health Management

NASA Technical Reports Server (NTRS)

Saha, Bhaskar; Quach, Cuong Chi; Goebel, Kai Frank

2011-01-01

Battery Health Management (BHM) is a core enabling technology for the success and widespread adoption of the emerging electric vehicles of today. Although battery chemistries have been studied in detail in literature, an accurate run-time battery life prediction algorithm has eluded us. Current reliability-based techniques are insufficient to manage the use of such batteries when they are an active power source with frequently varying loads in uncertain environments. The amount of usable charge of a battery for a given discharge profile is not only dependent on the starting state-of-charge (SOC), but also other factors like battery health and the discharge or load profile imposed. This paper presents a Particle Filter (PF) based BHM framework with plug-and-play modules for battery models and uncertainty management. The batteries are modeled at three different levels of granularity with associated uncertainty distributions, encoding the basic electrochemical processes of a Lithium-polymer battery. The effects of different choices in the model design space are explored in the context of prediction performance in an electric unmanned aerial vehicle (UAV) application with emulated flight profiles.

Computationally guided discovery of thermoelectric materials

DOE PAGES

Gorai, Prashun; Stevanović, Vladan; Toberer, Eric S.

2017-08-22

The potential for advances in thermoelectric materials, and thus solid-state refrigeration and power generation, is immense. Progress so far has been limited by both the breadth and diversity of the chemical space and the serial nature of experimental work. In this Review, we discuss how recent computational advances are revolutionizing our ability to predict electron and phonon transport and scattering, as well as materials dopability, and we examine efficient approaches to calculating critical transport properties across large chemical spaces. When coupled with experimental feedback, these high-throughput approaches can stimulate the discovery of new classes of thermoelectric materials. Within smaller materialsmore » subsets, computations can guide the optimal chemical and structural tailoring to enhance materials performance and provide insight into the underlying transport physics. Beyond perfect materials, computations can be used for the rational design of structural and chemical modifications (such as defects, interfaces, dopants and alloys) to provide additional control on transport properties to optimize performance. Through computational predictions for both materials searches and design, a new paradigm in thermoelectric materials discovery is emerging.« less

Inverse design of bulk morphologies in block copolymers using particle swarm optimization

NASA Astrophysics Data System (ADS)

Khadilkar, Mihir; Delaney, Kris; Fredrickson, Glenn

Multiblock polymers are a versatile platform for creating a large range of nanostructured materials with novel morphologies and properties. However, achieving desired structures or property combinations is difficult due to a vast design space comprised of parameters including monomer species, block sequence, block molecular weights and dispersity, copolymer architecture, and binary interaction parameters. Navigating through such vast design spaces to achieve an optimal formulation for a target structure or property set requires an efficient global optimization tool wrapped around a forward simulation technique such as self-consistent field theory (SCFT). We report on such an inverse design strategy utilizing particle swarm optimization (PSO) as the global optimizer and SCFT as the forward prediction engine. To avoid metastable states in forward prediction, we utilize pseudo-spectral variable cell SCFT initiated from a library of defect free seeds of known block copolymer morphologies. We demonstrate that our approach allows for robust identification of block copolymers and copolymer alloys that self-assemble into a targeted structure, optimizing parameters such as block fractions, blend fractions, and Flory chi parameters.

Direct evidence for a magnetic f-electron–mediated pairing mechanism of heavy-fermion superconductivity in CeCoIn5

PubMed Central

Van Dyke, John S.; Massee, Freek; Allan, Milan P.; Davis, J. C. Séamus; Petrovic, Cedomir; Morr, Dirk K.

2014-01-01

To identify the microscopic mechanism of heavy-fermion Cooper pairing is an unresolved challenge in quantum matter studies; it may also relate closely to finding the pairing mechanism of high-temperature superconductivity. Magnetically mediated Cooper pairing has long been the conjectured basis of heavy-fermion superconductivity but no direct verification of this hypothesis was achievable. Here, we use a novel approach based on precision measurements of the heavy-fermion band structure using quasiparticle interference imaging to reveal quantitatively the momentum space (k-space) structure of the f-electron magnetic interactions of CeCoIn5. Then, by solving the superconducting gap equations on the two heavy-fermion bands Ekα,β with these magnetic interactions as mediators of the Cooper pairing, we derive a series of quantitative predictions about the superconductive state. The agreement found between these diverse predictions and the measured characteristics of superconducting CeCoIn5 then provides direct evidence that the heavy-fermion Cooper pairing is indeed mediated by f-electron magnetism. PMID:25062692

Multiple states and hysteresis in a two-layer loop current type system

NASA Astrophysics Data System (ADS)

Kuehl, J.; Sheremet, V.

2017-12-01

Rotating table experiments are considered of a two-layer loop current type or gap-leaping system. Such experiments are representative of oceanic regions including the Kuroshio current crossing the Luzon Strait, the Gulf of Mexico Loop Current, the Northeast Chanel of the Gulf of Maine where Scotian shelf water leaps directly from Browns bank to Georges Bank and more. Systems such as these are known to admit two dominant states: leaping across the gap or penetrating into the gap forming a loop current. Which state the system will assume and when transitions between states will occur are open problems. We show that such systems admit multiple steady states with hysteresis when the strength of the current is varied. When the state of the system is viewed in a parameter space representing inertia and vorticity constraint, the system is found to be characterized by a cusp topology of solutions. The existence of such dynamics in two-layer quasi-geostrophic systems has significant implications for oceanographic predictability.

Bone Density Following Three Years of Recovery from Long-Duration Space Flight

NASA Technical Reports Server (NTRS)

Amin, Shreyasee; Achenbach, Sara J.; Atkinson, Elizabeth J.; Sibonga, Jean

2011-01-01

It is well recognized that bone mineral density [BMD] at load-bearing sites of the hip and spine sustain significant loss during space flight, estimated at approximately 0.5-1.0% per month. However, the long-term effects on bone health following return from long-duration space flight remain unclear. It is unknown whether BMD for men recovers beyond 1 year following return from space to what would be predicted or if deficits persist. Using our previously created prediction models, we compared the observed BMD of male US crew following 3 years since returning from longduration space flight with what would be predicted if they had not been exposed to microgravity.

An Operational Wake Vortex Sensor Using Pulsed Coherent Lidar

NASA Technical Reports Server (NTRS)

Barker, Ben C., Jr.; Koch, Grady J.; Nguyen, D. Chi

1998-01-01

NASA and FAA initiated a program in 1994 to develop methods of setting spacings for landing aircraft by incorporating information on the real-time behavior of aircraft wake vortices. The current wake separation standards were developed in the 1970's when there was relatively light airport traffic and a logical break point by which to categorize aircraft. Today's continuum of aircraft sizes and increased airport packing densities have created a need for re-evaluation of wake separation standards. The goals of this effort are to ensure that separation standards are adequate for safety and to reduce aircraft spacing for higher airport capacity. Of particular interest are the different requirements for landing under visual flight conditions and instrument flight conditions. Over the years, greater spacings have been established for instrument flight than are allowed for visual flight conditions. Preliminary studies indicate that the airline industry would save considerable money and incur fewer passenger delays if a dynamic spacing system could reduce separations at major hubs during inclement weather to the levels routinely achieved under visual flight conditions. The sensor described herein may become part of this dynamic spacing system known as the "Aircraft VOrtex Spacing System" (AVOSS) that will interface with a future air traffic control system. AVOSS will use vortex behavioral models and short-term weather prediction models in order to predict vortex behavior sufficiently into the future to allow dynamic separation standards to be generated. The wake vortex sensor will periodically provide data to validate AVOSS predictions. Feasibility of measuring wake vortices using a lidar was first demonstrated using a continuous wave (CW) system from NASA Marshall Space Flight Sensor and tested at the Volpe National Transportation Systems Center's wake vortex test site at JFK International Airport. Other applications of CW lidar for wake vortex measurement have been made more recently, including a system developed by the MIT Lincoln Laboratory. This lidar has been used for detailed measurements of wake vortex velocities in support of wake vortex model validation. The first measurements of wake vortices using a pulsed, lidar were made by Coherent Technologies, Inc. (CTI) using a 2 micron solid-state, flashlamp-pumped system operating at 5 Hz. This system was first deployed at Denver's Stapleton Airport. Pulsed lidar has been selected as the baseline technology for an operational sensor due to its longer range capability.

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.

Short-time dynamics of 2-thiouracil in the light absorbing S{sub 2}(ππ{sup ∗}) state

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

Jiang, Jie; Zhang, Teng-shuo; Xue, Jia-dan

2015-11-07

Ultrahigh quantum yields of intersystem crossing to the lowest triplet state T{sub 1} are observed for 2-thiouracils (2TU), which is in contrast to the natural uracils that predominantly exhibit ultrafast internal conversion to the ground state upon excitation to the singlet excited state. The intersystem crossing mechanism of 2TU has recently been investigated using second-order perturbation methods with a high-level complete-active space self-consistent field. Three competitive nonadiabatic pathways to the lowest triplet state T{sub 1} from the initially populated singlet excited state S{sub 2} were proposed. We investigate the initial decay dynamics of 2TU from the light absorbing excited statesmore » using resonance Raman spectroscopy, time-dependent wave-packet theory in the simple model, and complete-active space self-consistent field (CASSCF) and time dependent-Becke’s three-parameter exchange and correlation functional with the Lee-Yang-Parr correlation functional (TD-B3LYP) calculations. The obtained short-time structural dynamics in easy-to-visualize internal coordinates were compared with the CASSCF(16,11) predicted key nonadiabatic decay routes. Our results indicate that the predominant decay pathway initiated at the Franck-Condon region is toward the S{sub 2}/S{sub 1} conical intersection point and S{sub 2}T{sub 3} intersystem crossing point, but not toward the S{sub 2}T{sub 2} intersystem crossing point.« less

A summary of the OV1-19 satellite dose, depth dose, and linear energy transfer spectral measurements

NASA Technical Reports Server (NTRS)

Cervini, J. T.

1972-01-01

Measurements of the biophysical and physical parameters in the near earth space environment, specifically, the Inner Van Allen Belt are discussed. This region of space is of great interest to planners of the Skylab and the Space Station programs because of the high energy proton environment, especially during periods of increased solar activity. Many physical measurements of charged particle flux, spectra, and pitch angle distribution have been conducted and are programmed in the space radiation environment. Such predictions are not sufficient to accurately predict the effects of space radiations on critical biological and electronic systems operating in these environments. Some of the difficulties encountered in transferring from physical data to a prediction of the effects of space radiation on operational systems are discussed.

Honors

NASA Astrophysics Data System (ADS)

2012-02-01

Marshall Shepherd, professor of geography in the University of Georgia's Franklin College of Arts and Sciences, Athens, began a 1-year term as president-elect of the American Meteorological Society (AMS) on 22 January. In 2013 he will assume the presidency of the society. Also, five AGU members recently were elected as AMS councilors, with terms expiring in 2015: José Fuentes, Department of Meteorology, Pennsylvania State University, University Park; Richard Johnson, Atmospheric Science Department, Colorado State University, Fort Collins; Christa Peters-Lidard, Hydrological Sciences Branch at NASA's Goddard Space Flight Center, Greenbelt, Md.; Wassila Thiaw, Climate Prediction Center, National Oceanic and Atmospheric Administration, Camp Springs, Md.; and Chidong Zhang, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Fla.

Solid-state dewetting of magnetic binary multilayer thin films

NASA Astrophysics Data System (ADS)

Esterina, Ria; Liu, X. M.; Adeyeye, A. O.; Ross, C. A.; Choi, W. K.

2015-10-01

We examined solid-state dewetting behavior of magnetic multilayer thin film in both miscible (CoPd) and immiscible (CoAu) systems and found that CoPd and CoAu dewetting stages follow that of elemental materials. We established that CoPd alloy morphology and dewetting rate lie in between that of the elemental materials. Johnson-Mehl-Avrami analysis was utilized to extract the dewetting activation energy of CoPd. For CoAu, Au-rich particles and Co-rich particles are distinguishable and we are able to predict the interparticle spacings and particle densities for the particles that agree well with the experimental results. We also characterized the magnetic properties of CoPd and CoAu nanoparticles.

Further clarifying proximal withdrawal states and the turnover criterion space: Comment on Hom, Mitchell, Lee, and Griffeth (2012).

PubMed

Maertz, Carl P

2012-09-01

In "Reviewing Employee Turnover: Focusing on Proximal Withdrawal States and an Expanded Criterion," Hom, Mitchell, Lee, and Griffeth (2012) brought together many of the most important content and process factors in the employee turnover literature. In this paper, I attempt to clarify the true contributions of this framework for the turnover area and at the same time explain why improved prediction is not among these contributions. I then enumerate 3 theoretically problematic aspects of the proposed framework, which limit its contribution. Finally, I suggest 3 directions that researchers should pursue in order to test and extend the framework. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Coronas-F Orbit Monitoring and Re-Entry Prediction

NASA Technical Reports Server (NTRS)

Ivanov, N. M.; Kolyuka, Yu. F.; Afanasieva, T. I.; Gridchina, T. A.

2007-01-01

Russian scientific satellite CORONAS-F was launched on July, 31, 2001. The object was inserted in near-circular orbit with the inclination 82.5deg and a mean altitude approx. 520 km. Due to the upper atmosphere drag CORONAS-F was permanently descended and as a result on December, 6, 2005 it has finished the earth-orbital flight, having lifetime in space approx. 4.5 years. The satellite structural features and its flight attitude control led to the significant variations of its ballistic coefficient during the flight. It was a cause of some specific difficulties in the fulfillment of the ballistic and navigation support of this space vehicle flight. Besides the main mission objective CORONAS-F also has been selected by the Inter-Agency Space Debris Coordination Committee (IADC) as a target object for the next regular international re-entry test campaign on a program of surveillance and re-entry prediction for the hazard space objects within their de-orbiting phases. Spacecraft (S/C) CORONAS-F kept its working state right up to the end of the flight - down to the atmosphere entry. This fact enabled to realization of the additional research experiments, concerning with an estimation of the atmospheric density within the low earth orbits (LEO) of the artificial satellites, and made possible to continue track the S/C during final phase of its flight by means of Russian regular command & tracking system, used for it control. Thus there appeared a unique possibility of using for tracking S/C at its de-orbiting phase not only passive radar facilities, belonging to the space surveillance systems and traditionally used for support of the IADC re-entry test campaigns, but also more precise active trajectory radio-tracking facilities from the ground control complex (GCC) applied for this object. Under the corresponding decision of the Russian side such capability of additional high-precise tracking control of the CORONAS-F flight in this period of time has been implemented. The organizing of the CORONAS-F ballistic and navigational support (BNS) and solving its main tasks (such as S/C orbit determination (OD) and its motion prediction and connected with them) both for regular mission stage and for additional flight program were realized by the group of specialists from the Mission Control Center (MCC). MCC was also assigned as a principal organization from the Russian side for participation in the 7th IADC re-entry test campaign on CORONAS-F. The CORONAS-F flight features and space environments circumstances during its flight as well as a methodology and technology of spacecraft ballistic and navigational support are given below. The BNS results for different phases of S/C flight, including the results of its re-entry predictions, obtained during the realization of the 7th IADC test campaign are submitted. The accuracy of space vehicle re-entry prediction and its dependence on various factors are analyzed in more details.

Researches on High Accuracy Prediction Methods of Earth Orientation Parameters

NASA Astrophysics Data System (ADS)

Xu, X. Q.

2015-09-01

The Earth rotation reflects the coupling process among the solid Earth, atmosphere, oceans, mantle, and core of the Earth on multiple spatial and temporal scales. The Earth rotation can be described by the Earth's orientation parameters, which are abbreviated as EOP (mainly including two polar motion components PM_X and PM_Y, and variation in the length of day ΔLOD). The EOP is crucial in the transformation between the terrestrial and celestial reference systems, and has important applications in many areas such as the deep space exploration, satellite precise orbit determination, and astrogeodynamics. However, the EOP products obtained by the space geodetic technologies generally delay by several days to two weeks. The growing demands for modern space navigation make high-accuracy EOP prediction be a worthy topic. This thesis is composed of the following three aspects, for the purpose of improving the EOP forecast accuracy. (1) We analyze the relation between the length of the basic data series and the EOP forecast accuracy, and compare the EOP prediction accuracy for the linear autoregressive (AR) model and the nonlinear artificial neural network (ANN) method by performing the least squares (LS) extrapolations. The results show that the high precision forecast of EOP can be realized by appropriate selection of the basic data series length according to the required time span of EOP prediction: for short-term prediction, the basic data series should be shorter, while for the long-term prediction, the series should be longer. The analysis also showed that the LS+AR model is more suitable for the short-term forecasts, while the LS+ANN model shows the advantages in the medium- and long-term forecasts. (2) We develop for the first time a new method which combines the autoregressive model and Kalman filter (AR+Kalman) in short-term EOP prediction. The equations of observation and state are established using the EOP series and the autoregressive coefficients respectively, which are used to improve/re-evaluate the AR model. Comparing to the single AR model, the AR+Kalman method performs better in the prediction of UT1-UTC and ΔLOD, and the improvement in the prediction of the polar motion is significant. (3) Following the successful Earth Orientation Parameter Prediction Comparison Campaign (EOP PCC), the Earth Orientation Parameter Combination of Prediction Pilot Project (EOPC PPP) was sponsored in 2010. As one of the participants from China, we update and submit the short- and medium-term (1 to 90 days) EOP predictions every day. From the current comparative statistics, our prediction accuracy is on the medium international level. We will carry out more innovative researches to improve the EOP forecast accuracy and enhance our level in EOP forecast.

Deformed shell model calculations of half lives for β+/EC decay and 2ν β+β+/β+EC/ECEC decay in medium-heavy N~Z nuclei

NASA Astrophysics Data System (ADS)

Mishra, S.; Shukla, A.; Sahu, R.; Kota, V. K. B.

2008-08-01

The β+/EC half-lives of medium heavy N~Z nuclei with mass number A~64-80 are calculated within the deformed shell model (DSM) based on Hartree-Fock states by employing a modified Kuo interaction in (2p3/2,1f5/2,2p1/2,1g9/2) space. The DSM model has been quite successful in predicting many spectroscopic properties of N~Z medium heavy nuclei with A~64-80. The calculated β+/EC half-lives, for prolate and oblate shapes, compare well with the predictions of the calculations with Skyrme force by Sarriguren Going further, following recent searches, half-lives for 2ν β+β+/β+EC/ECEC decay for the nucleus Kr78 are calculated using DSM and the results compare well with QRPA predictions.

Nonlinear modeling of chaotic time series: Theory and applications

NASA Astrophysics Data System (ADS)

Casdagli, M.; Eubank, S.; Farmer, J. D.; Gibson, J.; Desjardins, D.; Hunter, N.; Theiler, J.

We review recent developments in the modeling and prediction of nonlinear time series. In some cases, apparent randomness in time series may be due to chaotic behavior of a nonlinear but deterministic system. In such cases, it is possible to exploit the determinism to make short term forecasts that are much more accurate than one could make from a linear stochastic model. This is done by first reconstructing a state space, and then using nonlinear function approximation methods to create a dynamical model. Nonlinear models are valuable not only as short term forecasters, but also as diagnostic tools for identifying and quantifying low-dimensional chaotic behavior. During the past few years, methods for nonlinear modeling have developed rapidly, and have already led to several applications where nonlinear models motivated by chaotic dynamics provide superior predictions to linear models. These applications include prediction of fluid flows, sunspots, mechanical vibrations, ice ages, measles epidemics, and human speech.

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

Two Phase Flow Modeling: Summary of Flow Regimes and Pressure Drop Correlations in Reduced and Partial Gravity

NASA Technical Reports Server (NTRS)

Balasubramaniam, R.; Rame, E.; Kizito, J.; Kassemi, M.

2006-01-01

The purpose of this report is to provide a summary of state-of-the-art predictions for two-phase flows relevant to Advanced Life Support. We strive to pick out the most used and accepted models for pressure drop and flow regime predictions. The main focus is to identify gaps in predictive capabilities in partial gravity for Lunar and Martian applications. Following a summary of flow regimes and pressure drop correlations for terrestrial and zero gravity, we analyze the fully developed annular gas-liquid flow in a straight cylindrical tube. This flow is amenable to analytical closed form solutions for the flow field and heat transfer. These solutions, valid for partial gravity as well, may be used as baselines and guides to compare experimental measurements. The flow regimes likely to be encountered in the water recovery equipment currently under consideration for space applications are provided in an appendix.

Atmospheric and oceanographic research review, 1979

NASA Technical Reports Server (NTRS)

1980-01-01

Papers generated by atmospheric, oceanographic, and climatological research performed during 1979 at the Goddard Laboratory for Atmospheric Sciences are presented. The GARP/global weather research is aimed at developing techniques for the utilization and analysis of the FGGE data sets. Observing system studies were aimed at developing a GLAS TIROS N sounding retrieval system and preparing for the joint NOAA/NASA AMTS simulation study. The climate research objective is to support the development and effective utilization of space acquired data systems by developing the GLAS GCM for short range climate predictions, studies of the sensitivity of climate to boundary conditions, and predictability studies. Ocean/air interaction studies concentrated on the development of models for the prediction of upper ocean currents, temperatures, sea state, mixed layer depths, and upwelling zones, and on studies of the interactions of the atmospheric and oceanic circulation systems on time scales of a month or more.

NEWS Climatology Project: The State of the Water Cycle at Continental to Global Scales

NASA Technical Reports Server (NTRS)

Rodell, Matthew; LEcuyer, Tristan; Beaudoing, Hiroko Kato; Olson, Bill

2011-01-01

NASA's Energy and Water Cycle Study (NEWS) program fosters collaborative research towards improved quantification and prediction of water and energy cycle consequences of climate change. In order to measure change, it is first necessary to describe current conditions. The goal of the NEWS Water and Energy Cycle Climatology project is to develop "state of the global water cycle" and "state of the global energy cycle" assessments based on data from modern ground and space based observing systems and data integrating models. The project is a multiinstitutional collaboration with more than 20 active contributors. This presentation will describe results of the first stage of the water budget analysis, whose goal was to characterize the current state of the water cycle on mean monthly, continental scales. We examine our success in closing the water budget within the expected uncertainty range and the effects of forcing budget closure as a method for refining individual flux estimates.

Reaction of O2(+)(X 2Pi sub g) with H2, D2, and HD - Guided ion beam studies, MO correlations, and statistical theory calculations

NASA Technical Reports Server (NTRS)

Weber, M. E.; Dalleska, N. F.; Tjelta, B. L.; Fisher, E. R.; Armentrout, P. B.

1993-01-01

Guided ion-beam mass spectrometry is used to examined the reactions of vibrationally cold ground-state O2(+)(X 2Pi sub g) with H2, D2, and HD. The energy dependence of the absolute integral cross sections from thermal energy to over 4 eV are measured in the center-of-mass frame of reference. Results are also presented for internally excited O2(+) ions reacting with D2 and HD. The results are consistent with the dominant state being the a 4Pi sub u electronic state. The experimental excitation functions are analyzed in detail and interpreted by extending the molecular orbital correlation arguments of Mahan (1971) and by comparison with results of statistical phase space theory and with a theory that predicts a tight transition state.

Fine-Tuning the Accretion Disk Clock in Hercules X-1

NASA Technical Reports Server (NTRS)

Still, M.; Boyd, P.

2004-01-01

RXTE ASM count rates from the X-ray pulsar Her X-1 began falling consistently during the late months of 2003. The source is undergoing another state transition similar to the anomalous low state of 1999. This new event has triggered observations from both space and ground-based observatories. In order to aid data interpretation and telescope scheduling, and to facilitate the phase-connection of cycles before and after the state transition, we have re-calculated the precession ephemeris using cycles over the last 3.5 years. We report that the source has displayed a different precession period since the last anomalous event. Additional archival data from CGRO suggests that each low state is accompanied by a change in precession period and that the subsequent period is correlated with accretion flux. Consequently our analysis reveals long-term accretion disk behaviour which is predicted by theoretical models of radiation-driven warping.