Verification of Ares I Liftoff Acoustic Environments via the Ares Scale Model Acoustic Test

NASA Technical Reports Server (NTRS)

Counter, Douglas D.; Houston, Janice D.

2012-01-01

Launch environments, such as Liftoff Acoustic (LOA) and Ignition Overpressure (IOP), are important design factors for any vehicle and are dependent upon the design of both the vehicle and the ground systems. The NASA Constellation Program had several risks to the development of the Ares I vehicle linked to LOA which are used in the development of the vibro-acoustic environments. The risks included cost, schedule and technical impacts for component qualification due to high predicted vibro-acoustic environments. One solution is to mitigate the environment at the component level. However, where the environment is too severe to mitigate at the component level, reduction of the launch environments is required. The Ares I Scale Model Acoustic Test (ASMAT) program was implemented to verify the predicted Ares I launch environments and to determine the acoustic reduction for the LOA environment with an above deck water sound suppression system. The test article included a 5% scale Ares I vehicle model, tower and Mobile Launcher. Acoustic and pressure data were measured by approximately 200 instruments. The ASMAT results are compared to the Ares I LOA predictions and water suppression effectiveness results are presented.

REVIEW: Widespread access to predictive models in the motor system: a short review

NASA Astrophysics Data System (ADS)

Davidson, Paul R.; Wolpert, Daniel M.

2005-09-01

Recent behavioural and computational studies suggest that access to internal predictive models of arm and object dynamics is widespread in the sensorimotor system. Several systems, including those responsible for oculomotor and skeletomotor control, perceptual processing, postural control and mental imagery, are able to access predictions of the motion of the arm. A capacity to make and use predictions of object dynamics is similarly widespread. Here, we review recent studies looking at the predictive capacity of the central nervous system which reveal pervasive access to forward models of the environment.

Single-Event Effects Ground Testing and On-Orbit Rate Prediction Methods: The Past, Present and Future

NASA Technical Reports Server (NTRS)

Reed, Robert A.; Kinnison, Jim; Pickel, Jim; Buchner, Stephen; Marshall, Paul W.; Kniffin, Scott; LaBel, Kenneth A.

2003-01-01

Over the past 27 years, or so, increased concern over single event effects in spacecraft systems has resulted in research, development and engineering activities centered around a better understanding of the space radiation environment, single event effects predictive methods, ground test protocols, and test facility developments. This research has led to fairly well developed methods for assessing the impact of the space radiation environment on systems that contain SEE sensitive devices and the development of mitigation strategies either at the system or device level.

Vibroacoustic Payload Environment Prediction System (VAPEPS): VAPEPS management center remote access guide

NASA Technical Reports Server (NTRS)

Fernandez, J. P.; Mills, D.

1991-01-01

A Vibroacoustic Payload Environment Prediction System (VAPEPS) Management Center was established at the JPL. The center utilizes the VAPEPS software package to manage a data base of Space Shuttle and expendable launch vehicle payload flight and ground test data. Remote terminal access over telephone lines to the computer system, where the program resides, was established to provide the payload community a convenient means of querying the global VAPEPS data base. This guide describes the functions of the VAPEPS Management Center and contains instructions for utilizing the resources of the center.

Chaos and the (un)predictability of evolution in a changing environment

PubMed Central

Rego-Costa, Artur; Débarre, Florence; Chevin, Luis-Miguel

2018-01-01

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution, by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability. PMID:29235104

AST Launch Vehicle Acoustics

NASA Technical Reports Server (NTRS)

Houston, Janice; Counter, D.; Giacomoni, D.

2015-01-01

The liftoff phase induces acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are then used in the prediction of internal vibration responses of the vehicle and components which result in the qualification levels. Thus, predicting these liftoff acoustic (LOA) environments is critical to the design requirements of any launch vehicle. If there is a significant amount of uncertainty in the predictions or if acoustic mitigation options must be implemented, a subscale acoustic test is a feasible pre-launch test option to verify the LOA environments. The NASA Space Launch System (SLS) program initiated the Scale Model Acoustic Test (SMAT) to verify the predicted SLS LOA environments and to determine the acoustic reduction with an above deck water sound suppression system. The SMAT was conducted at Marshall Space Flight Center and the test article included a 5% scale SLS vehicle model, tower and Mobile Launcher. Acoustic and pressure data were measured by approximately 250 instruments. The SMAT liftoff acoustic results are presented, findings are discussed and a comparison is shown to the Ares I Scale Model Acoustic Test (ASMAT) results.

Early prediction of student goals and affect in narrative-centered learning environments

NASA Astrophysics Data System (ADS)

Lee, Sunyoung

Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.

Molecular mechanisms of system responses to novel stimuli are predictable from public data

PubMed Central

Danziger, Samuel A.; Ratushny, Alexander V.; Smith, Jennifer J.; Saleem, Ramsey A.; Wan, Yakun; Arens, Christina E.; Armstrong, Abraham M.; Sitko, Katherine; Chen, Wei-Ming; Chiang, Jung-Hsien; Reiss, David J.; Baliga, Nitin S.; Aitchison, John D.

2014-01-01

Systems scale models provide the foundation for an effective iterative cycle between hypothesis generation, experiment and model refinement. Such models also enable predictions facilitating the understanding of biological complexity and the control of biological systems. Here, we demonstrate the reconstruction of a globally predictive gene regulatory model from public data: a model that can drive rational experiment design and reveal new regulatory mechanisms underlying responses to novel environments. Specifically, using ∼1500 publically available genome-wide transcriptome data sets from Saccharomyces cerevisiae, we have reconstructed an environment and gene regulatory influence network that accurately predicts regulatory mechanisms and gene expression changes on exposure of cells to completely novel environments. Focusing on transcriptional networks that induce peroxisomes biogenesis, the model-guided experiments allow us to expand a core regulatory network to include novel transcriptional influences and linkage across signaling and transcription. Thus, the approach and model provides a multi-scalar picture of gene dynamics and are powerful resources for exploiting extant data to rationally guide experimentation. The techniques outlined here are generally applicable to any biological system, which is especially important when experimental systems are challenging and samples are difficult and expensive to obtain—a common problem in laboratory animal and human studies. PMID:24185701

ATD-2 IADS Metroplex Traffic Management Overview Brief

NASA Technical Reports Server (NTRS)

Engelland, Shawn

2016-01-01

ATD-2 will improve the predictability and the operational efficiency of the air traffic system in metroplex environments through the enhancement, development and integration of the nation's most advanced and sophisticated arrival, departure, and surface prediction, scheduling and management systems.

An assessment of the microgravity and acoustic environments in Space Station Freedom using VAPEPS

NASA Technical Reports Server (NTRS)

Bergen, Thomas F.; Scharton, Terry D.; Badilla, Gloria A.

1992-01-01

The Vibroacoustic Payload Environment Prediction System (VAPEPS) was used to predict the stationary on-orbit environments in one of the Space Station Freedom modules. The model of the module included the outer structure, equipment and payload racks, avionics, and cabin air and duct systems. Acoustic and vibratory outputs of various source classes were derived and input to the model. Initial results of analyses, performed in one-third octave frequency bands from 10 to 10,000 Hz, show that both the microgravity and acoustic environments will be exceeded in some one-third octave bands with the current SSF design. Further analyses indicate that interior acoustic level requirements will be exceeded even if the microgravity requirements are met.

A Stochastic Model of Plausibility in Live Virtual Constructive Environments

DTIC Science & Technology

2017-09-14

objective in virtual environment research and design is the maintenance of adequate consistency levels in the face of limited system resources such as...provides some commentary with regard to system design considerations and future research directions. II. SYSTEM MODEL DVEs are often designed as a...exceed the system’s requirements. Research into predictive models of virtual environment consistency is needed to provide designers the tools to

Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

2018-01-04

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment-trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. Copyright © 2018 Montesinos-Lopez et al.

Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis.

PubMed

Kim, Young Bin; Lee, Sang Hyeok; Kang, Shin Jin; Choi, Myung Jin; Lee, Jung; Kim, Chang Hun

2015-01-01

In this paper, we present a method for predicting the value of virtual currencies used in virtual gaming environments that support multiple users, such as massively multiplayer online role-playing games (MMORPGs). Predicting virtual currency values in a virtual gaming environment has rarely been explored; it is difficult to apply real-world methods for predicting fluctuating currency values or shares to the virtual gaming world on account of differences in domains between the two worlds. To address this issue, we herein predict virtual currency value fluctuations by collecting user opinion data from a virtual community and analyzing user sentiments or emotions from the opinion data. The proposed method is straightforward and applicable to predicting virtual currencies as well as to gaming environments, including MMORPGs. We test the proposed method using large-scale MMORPGs and demonstrate that virtual currencies can be effectively and efficiently predicted with it.

Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis

PubMed Central

Kim, Young Bin; Lee, Sang Hyeok; Kang, Shin Jin; Choi, Myung Jin; Lee, Jung; Kim, Chang Hun

2015-01-01

In this paper, we present a method for predicting the value of virtual currencies used in virtual gaming environments that support multiple users, such as massively multiplayer online role-playing games (MMORPGs). Predicting virtual currency values in a virtual gaming environment has rarely been explored; it is difficult to apply real-world methods for predicting fluctuating currency values or shares to the virtual gaming world on account of differences in domains between the two worlds. To address this issue, we herein predict virtual currency value fluctuations by collecting user opinion data from a virtual community and analyzing user sentiments or emotions from the opinion data. The proposed method is straightforward and applicable to predicting virtual currencies as well as to gaming environments, including MMORPGs. We test the proposed method using large-scale MMORPGs and demonstrate that virtual currencies can be effectively and efficiently predicted with it. PMID:26241496

A Multigroup Method for the Calculation of Neutron Fluence with a Source Term

NASA Technical Reports Server (NTRS)

Heinbockel, J. H.; Clowdsley, M. S.

1998-01-01

Current research on the Grant involves the development of a multigroup method for the calculation of low energy evaporation neutron fluences associated with the Boltzmann equation. This research will enable one to predict radiation exposure under a variety of circumstances. Knowledge of radiation exposure in a free-space environment is a necessity for space travel, high altitude space planes and satellite design. This is because certain radiation environments can cause damage to biological and electronic systems involving both short term and long term effects. By having apriori knowledge of the environment one can use prediction techniques to estimate radiation damage to such systems. Appropriate shielding can be designed to protect both humans and electronic systems that are exposed to a known radiation environment. This is the goal of the current research efforts involving the multi-group method and the Green's function approach.

Systems design study of the Pioneer Venus spacecraft. Appendices to volume 1, section 7 (part 2 of 3). [procedures for predicting aeroheating environment of Venus entry probes

NASA Technical Reports Server (NTRS)

1973-01-01

The procedures for predicting the aeroheating environment of Venus entry probes are outlined. After some consideration, a number of assumptions were adopted in order to make the prediction techniques tractable. Among these assumptions are thermochemical equilibrium, uncoupled radiative and convective processes, and uncoupled ablation products effects. The single strip method of integral relations, appropriately constrained, is shown to provide adequate inviscid results as a basis for heating calculations on blunt configurations. Techniques for prediction of the laminar, transitional, and turbulent convective environment are outlined and shown to agree with data. The prediction of radiative heating in C, N, and O gas mixtures is discussed and a practical scheme adopted. A comparison with LRC calculations is made.

Vibroacoustic payload environment prediction system (VAPEPS): Data base management center remote access guide

NASA Technical Reports Server (NTRS)

Thomas, V. C.

1986-01-01

A Vibroacoustic Data Base Management Center has been established at the Jet Propulsion Laboratory (JPL). The center utilizes the Vibroacoustic Payload Environment Prediction System (VAPEPS) software package to manage a data base of shuttle and expendable launch vehicle flight and ground test data. Remote terminal access over telephone lines to a dedicated VAPEPS computer system has been established to provide the payload community a convenient means of querying the global VAPEPS data base. This guide describes the functions of the JPL Data Base Management Center and contains instructions for utilizing the resources of the center.

Early Family System Types Predict Children's Emotional Attention Biases at School Age

ERIC Educational Resources Information Center

Lindblom, Jallu; Peltola, Mikko J.; Vänskä, Mervi; Hietanen, Jari K.; Laakso, Anu; Tiitinen, Aila; Tulppala, Maija; Punamäki, Raija-Leena

2017-01-01

The family environment shapes children's social information processing and emotion regulation. Yet, the long-term effects of early family systems have rarely been studied. This study investigated how family system types predict children's attentional biases toward facial expressions at the age of 10 years. The participants were 79 children from…

Predicting green: really radical (plant) predictive processing

PubMed Central

Friston, Karl

2017-01-01

In this article we account for the way plants respond to salient features of their environment under the free-energy principle for biological systems. Biological self-organization amounts to the minimization of surprise over time. We posit that any self-organizing system must embody a generative model whose predictions ensure that (expected) free energy is minimized through action. Plants respond in a fast, and yet coordinated manner, to environmental contingencies. They pro-actively sample their local environment to elicit information with an adaptive value. Our main thesis is that plant behaviour takes place by way of a process (active inference) that predicts the environmental sources of sensory stimulation. This principle, we argue, endows plants with a form of perception that underwrites purposeful, anticipatory behaviour. The aim of the article is to assess the prospects of a radical predictive processing story that would follow naturally from the free-energy principle for biological systems; an approach that may ultimately bear upon our understanding of life and cognition more broadly. PMID:28637913

Laboratory evaluation of the pointing stability of the ASPS Vernier System

NASA Technical Reports Server (NTRS)

1980-01-01

The annular suspension and pointing system (ASPS) is an end-mount experiment pointing system designed for use in the space shuttle. The results of the ASPS Vernier System (AVS) pointing stability tests conducted in a laboratory environment are documented. A simulated zero-G suspension was used to support the test payload in the laboratory. The AVS and the suspension were modelled and incorporated into a simulation of the laboratory test. Error sources were identified and pointing stability sensitivities were determined via simulation. Statistical predictions of laboratory test performance were derived and compared to actual laboratory test results. The predicted mean pointing stability during simulated shuttle disturbances was 1.22 arc seconds; the actual mean laboratory test pointing stability was 1.36 arc seconds. The successful prediction of laboratory test results provides increased confidence in the analytical understanding of the AVS magnetic bearing technology and allows confident prediction of in-flight performance. Computer simulations of ASPS, operating in the shuttle disturbance environment, predict in-flight pointing stability errors less than 0.01 arc seconds.

Chaos and the (un)predictability of evolution in a changing environment.

PubMed

Rego-Costa, Artur; Débarre, Florence; Chevin, Luis-Miguel

2018-02-01

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Predictability sieve, pointer states, and the classicality of quantum trajectories

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

Dalvit, D. A. R.; Zurek, W. H.; Dziarmaga, J.

2005-12-15

We study various measures of classicality of the states of open quantum systems subject to decoherence. Classical states are expected to be stable in spite of decoherence, and are thought to leave conspicuous imprints on the environment. Here these expected features of environment-induced superselection are quantified using four different criteria: predictability sieve (which selects states that produce least entropy), purification time (which looks for states that are the easiest to find out from the imprint they leave on the environment), efficiency threshold (which finds states that can be deduced from measurements on a smallest fraction of the environment), and puritymore » loss time (that looks for states for which it takes the longest to lose a set fraction of their initial purity). We show that when pointer states--the most predictable states of an open quantum system selected by the predictability sieve--are well defined, all four criteria agree that they are indeed the most classical states. We illustrate this with two examples: an underdamped harmonic oscillator, for which coherent states are unanimously chosen by all criteria, and a free particle undergoing quantum Brownian motion, for which most criteria select almost identical Gaussian states (although, in this case, the predictability sieve does not select well defined pointer states)« less

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

PubMed

Rajagopalan, Ramesh; Litvan, Irene; Jung, Tzyy-Ping

2017-11-01

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Spacecraft Charging and Auroral Boundary Predictions in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Minow, Joseph I.

2016-01-01

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

Predicting evolutionary rescue via evolving plasticity in stochastic environments

PubMed Central

Baskett, Marissa L.

2016-01-01

Phenotypic plasticity and its evolution may help evolutionary rescue in a novel and stressful environment, especially if environmental novelty reveals cryptic genetic variation that enables the evolution of increased plasticity. However, the environmental stochasticity ubiquitous in natural systems may alter these predictions, because high plasticity may amplify phenotype–environment mismatches. Although previous studies have highlighted this potential detrimental effect of plasticity in stochastic environments, they have not investigated how it affects extinction risk in the context of evolutionary rescue and with evolving plasticity. We investigate this question here by integrating stochastic demography with quantitative genetic theory in a model with simultaneous change in the mean and predictability (temporal autocorrelation) of the environment. We develop an approximate prediction of long-term persistence under the new pattern of environmental fluctuations, and compare it with numerical simulations for short- and long-term extinction risk. We find that reduced predictability increases extinction risk and reduces persistence because it increases stochastic load during rescue. This understanding of how stochastic demography, phenotypic plasticity, and evolution interact when evolution acts on cryptic genetic variation revealed in a novel environment can inform expectations for invasions, extinctions, or the emergence of chemical resistance in pests. PMID:27655762

DEPEND - A design environment for prediction and evaluation of system dependability

NASA Technical Reports Server (NTRS)

Goswami, Kumar K.; Iyer, Ravishankar K.

1990-01-01

The development of DEPEND, an integrated simulation environment for the design and dependability analysis of fault-tolerant systems, is described. DEPEND models both hardware and software components at a functional level, and allows automatic failure injection to assess system performance and reliability. It relieves the user of the work needed to inject failures, maintain statistics, and output reports. The automatic failure injection scheme is geared toward evaluating a system under high stress (workload) conditions. The failures that are injected can affect both hardware and software components. To illustrate the capability of the simulator, a distributed system which employs a prediction-based, dynamic load-balancing heuristic is evaluated. Experiments were conducted to determine the impact of failures on system performance and to identify the failures to which the system is especially susceptible.

Predictive Compensator Optimization for Head Tracking Lag in Virtual Environments

NASA Technical Reports Server (NTRS)

Adelstein, Barnard D.; Jung, Jae Y.; Ellis, Stephen R.

2001-01-01

We examined the perceptual impact of plant noise parameterization for Kalman Filter predictive compensation of time delays intrinsic to head tracked virtual environments (VEs). Subjects were tested in their ability to discriminate between the VE system's minimum latency and conditions in which artificially added latency was then predictively compensated back to the system minimum. Two head tracking predictors were parameterized off-line according to cost functions that minimized prediction errors in (1) rotation, and (2) rotation projected into translational displacement with emphasis on higher frequency human operator noise. These predictors were compared with a parameterization obtained from the VE literature for cost function (1). Results from 12 subjects showed that both parameterization type and amount of compensated latency affected discrimination. Analysis of the head motion used in the parameterizations and the subsequent discriminability results suggest that higher frequency predictor artifacts are contributory cues for discriminating the presence of predictive compensation.

LAMPS software

NASA Technical Reports Server (NTRS)

Perkey, D. J.; Kreitzberg, C. W.

1984-01-01

The dynamic prediction model along with its macro-processor capability and data flow system from the Drexel Limited-Area and Mesoscale Prediction System (LAMPS) were converted and recorded for the Perkin-Elmer 3220. The previous version of this model was written for Control Data Corporation 7600 and CRAY-1a computer environment which existed until recently at the National Center for Atmospheric Research. The purpose of this conversion was to prepare LAMPS for porting to computer environments other than that encountered at NCAR. The emphasis was shifted from programming tasks to model simulation and evaluation tests.

Predictive sufficiency and the use of stored internal state

NASA Technical Reports Server (NTRS)

Musliner, David J.; Durfee, Edmund H.; Shin, Kang G.

1994-01-01

In all embedded computing systems, some delay exists between sensing and acting. By choosing an action based on sensed data, a system is essentially predicting that there will be no significant changes in the world during this delay. However, the dynamic and uncertain nature of the real world can make these predictions incorrect, and thus, a system may execute inappropriate actions. Making systems more reactive by decreasing the gap between sensing and action leaves less time for predictions to err, but still provides no principled assurance that they will be correct. Using the concept of predictive sufficiency described in this paper, a system can prove that its predictions are valid, and that it will never execute inappropriate actions. In the context of our CIRCA system, we also show how predictive sufficiency allows a system to guarantee worst-case response times to changes in its environment. Using predictive sufficiency, CIRCA is able to build real-time reactive control plans which provide a sound basis for performance guarantees that are unavailable with other reactive systems.

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions

PubMed Central

Rajagopalan, Ramesh; Jung, Tzyy-Ping

2017-01-01

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems. PMID:29104256

Space vehicle engine and heat shield environment review. Volume 1: Engineering analysis

NASA Technical Reports Server (NTRS)

Mcanelly, W. B.; Young, C. T. K.

1973-01-01

Methods for predicting the base heating characteristics of a multiple rocket engine installation are discussed. The environmental data is applied to the design of adequate protection system for the engine components. The methods for predicting the base region thermal environment are categorized as: (1) scale model testing, (2) extrapolation of previous and related flight test results, and (3) semiempirical analytical techniques.

The GP problem: quantifying gene-to-phenotype relationships.

PubMed

Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L

2002-01-01

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.

Performance prediction evaluation of ceramic materials in point-focusing solar receivers

NASA Technical Reports Server (NTRS)

Ewing, J.; Zwissler, J.

1979-01-01

A performance prediction was adapted to evaluate the use of ceramic materials in solar receivers for point focusing distributed applications. System requirements were determined including the receiver operating environment and system operating parameters for various engine types. Preliminary receiver designs were evolved from these system requirements. Specific receiver designs were then evaluated to determine material functional requirements.

Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C.; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

2018-01-01

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment–trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. PMID:29097376

Modeling and control for closed environment plant production systems

NASA Technical Reports Server (NTRS)

Fleisher, David H.; Ting, K. C.; Janes, H. W. (Principal Investigator)

2002-01-01

A computer program was developed to study multiple crop production and control in controlled environment plant production systems. The program simulates crop growth and development under nominal and off-nominal environments. Time-series crop models for wheat (Triticum aestivum), soybean (Glycine max), and white potato (Solanum tuberosum) are integrated with a model-based predictive controller. The controller evaluates and compensates for effects of environmental disturbances on crop production scheduling. The crop models consist of a set of nonlinear polynomial equations, six for each crop, developed using multivariate polynomial regression (MPR). Simulated data from DSSAT crop models, previously modified for crop production in controlled environments with hydroponics under elevated atmospheric carbon dioxide concentration, were used for the MPR fitting. The model-based predictive controller adjusts light intensity, air temperature, and carbon dioxide concentration set points in response to environmental perturbations. Control signals are determined from minimization of a cost function, which is based on the weighted control effort and squared-error between the system response and desired reference signal.

Service-Oriented Architecture (SOA) Instantiation within a Hard Real-Time, Deterministic Combat System Environment

ERIC Educational Resources Information Center

Moreland, James D., Jr

2013-01-01

This research investigates the instantiation of a Service-Oriented Architecture (SOA) within a hard real-time (stringent time constraints), deterministic (maximum predictability) combat system (CS) environment. There are numerous stakeholders across the U.S. Department of the Navy who are affected by this development, and therefore the system…

Capturing the complexity: Content, type, and amount of instruction and quality of the classroom learning environment synergistically predict third graders’ vocabulary and reading comprehension outcomes

PubMed Central

Connor, Carol McDonald; Spencer, Mercedes; Day, Stephanie L.; Giuliani, Sarah; Ingebrand, Sarah W.; McLean, Leigh; Morrison, Frederick J.

2014-01-01

We examined classrooms as complex systems that affect students’ literacy learning through interacting effects of content and amount of time individual students spent in literacy instruction along with the global quality of the classroom-learning environment. We observed 27 third grade classrooms serving 315 target students using two different observation systems. The first assessed instruction at a more micro-level; specifically, the amount of time individual students spent in literacy instruction defined by the type of instruction, role of the teacher, and content. The second assessed the quality of the classroom-learning environment at a more macro level focusing on classroom organization, teacher responsiveness, and support for vocabulary and language. Results revealed that both global quality of the classroom learning environment and time individual students spent in specific types of literacy instruction covering specific content interacted to predict students’ comprehension and vocabulary gains whereas neither system alone did. These findings support a dynamic systems model of how individual children learn in the context of classroom literacy instruction and the classroom-learning environment, which can help to improve observations systems, advance research, elevate teacher evaluation and professional development, and enhance student achievement. PMID:25400293

Using a RIVPACS model to predict expected macrofaunal species richness in Puget Sound

EPA Science Inventory

As part of a project to develop regional indicators for Pacific coastal environments using soft-bottom benthic species, we are evaluating a RIVPACS predictive model (River InVertebrate Prediction and Classification System). This approach was originally developed for rivers and s...

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

2015-01-01

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacity-building applications that extend numerical weather prediction to developing countries are intended to provide near real-time applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weather-related hazards, or impacts that local weather events may have during the recovery phase.

Interaction Network Estimation: Predicting Problem-Solving Diversity in Interactive Environments

ERIC Educational Resources Information Center

Eagle, Michael; Hicks, Drew; Barnes, Tiffany

2015-01-01

Intelligent tutoring systems and computer aided learning environments aimed at developing problem solving produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled student-tutor interactions using complex networks in…

Development of a prediction model on the acceptance of electronic laboratory notebooks in academic environments.

PubMed

Kloeckner, Frederik; Farkas, Robert; Franken, Tobias; Schmitz-Rode, Thomas

2014-04-01

Documentation of research data plays a key role in the biomedical engineering innovation processes. It makes an important contribution to the protection of intellectual property, the traceability of results and fulfilling the regulatory requirement. Because of the increasing digitalization in laboratories, an electronic alternative to the commonly-used paper-bound notebooks could contribute to the production of sophisticated documentation. However, compared to in an industrial environment, the use of electronic laboratory notebooks is not widespread in academic laboratories. Little is known about the acceptance of an electronic documentation system and the underlying reasons for this. Thus, this paper aims to establish a prediction model on the potential preference and acceptance of scientists either for paper-based or electronic documentation. The underlying data for the analysis originate from an online survey of 101 scientists in industrial, academic and clinical environments. Various parameters were analyzed to identify crucial factors for the system preference using binary logistic regression. The analysis showed significant dependency between the documentation system preference and the supposed workload associated with the documentation system (p<0.006; odds ratio=58.543) and an additional personal component. Because of the dependency of system choice on specific parameters it is possible to predict the acceptance of an electronic laboratory notebook before implementation.

Predictive systems ecology

PubMed Central

Evans, Matthew R.; Bithell, Mike; Cornell, Stephen J.; Dall, Sasha R. X.; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J.; Lewis, Simon L.; Mace, Georgina M.; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K. J.; Petchey, Owen; Smith, Matthew; Travis, Justin M. J.; Benton, Tim G.

2013-01-01

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive. PMID:24089332

Predictive systems ecology.

PubMed

Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

2013-11-22

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

Environmental exposure modeling and monitoring of human pharmaceutical concentrations in the environment

USGS Publications Warehouse

Versteeg, D.J.; Alder, A. C.; Cunningham, V. L.; Kolpin, D.W.; Murray-Smith, R.; Ternes, T.

2005-01-01

Human pharmaceuticals are receiving increased attention as environmental contaminants. This is due to their biological activity and the number of monitoring programs focusing on analysis of these compounds in various environmental media and compartments. Risk assessments are needed to understand the implications of reported concentrations; a fundamental part of the risk assessment is an assessment of environmental exposures. The purpose of this chapter is to provide guidance on the use of predictive tools (e.g., models) and monitoring data in exposure assessments for pharmaceuticals in the environment. Methods to predict environmental concentrations from equations based on first principles are presented. These equations form the basis of existing GIS (geographic information systems)-based systems for understanding the spatial distribution of pharmaceuticals in the environment. The pharmaceutical assessment and transport (PhATE), georeferenced regional exposure assessment tool for European rivers (GREAT-ER), and geographical information system (GIS)-ROUT models are reviewed and recommendations are provided concerning the design and execution of monitoring studies. Model predictions and monitoring data are compared to evaluate the relative utility of each approach in environmental exposure assessments. In summary, both models and monitoring data can be used to define representative exposure concentrations of pharmaceuticals in the environment in support of environmental risk assessments.

Sea-air boundary meteorological sensor

NASA Astrophysics Data System (ADS)

Barbosa, Jose G.

2015-05-01

The atmospheric environment can significantly affect radio frequency and optical propagation. In the RF spectrum refraction and ducting can degrade or enhance communications and radar coverage. Platforms in or beneath refractive boundaries can exploit the benefits or suffer the effects of the atmospheric boundary layers. Evaporative ducts and surface-base ducts are of most concern for ocean surface platforms and evaporative ducts are almost always present along the sea-air interface. The atmospheric environment also degrades electro-optical systems resolution and visibility. The atmospheric environment has been proven not to be uniform and under heterogeneous conditions substantial propagation errors may be present for large distances from homogeneous models. An accurate and portable atmospheric sensor to profile the vertical index of refraction is needed for mission planning, post analysis, and in-situ performance assessment. The meteorological instrument used in conjunction with a radio frequency and electro-optical propagation prediction tactical decision aid tool would give military platforms, in real time, the ability to make assessments on communication systems propagation ranges, radar detection and vulnerability ranges, satellite communications vulnerability, laser range finder performance, and imaging system performance predictions. Raman lidar has been shown to be capable of measuring the required atmospheric parameters needed to profile the atmospheric environment. The atmospheric profile could then be used as input to a tactical decision aid tool to make propagation predictions.

Real-time on-line space research laboratory environment monitoring with off-line trend and prediction analysis

NASA Astrophysics Data System (ADS)

Jules, Kenol; Lin, Paul P.

2007-06-01

With the International Space Station currently operational, a significant amount of acceleration data is being down-linked, processed and analyzed daily on the ground on a continuous basis for the space station reduced gravity environment characterization, the vehicle design requirements verification and science data collection. To help understand the impact of the unique spacecraft environment on the science data, an artificial intelligence monitoring system was developed, which detects in near real time any change in the reduced gravity environment susceptible to affect the on-going experiments. Using a dynamic graphical display, the monitoring system allows science teams, at any time and any location, to see the active vibration disturbances, such as pumps, fans, compressor, crew exercise, re-boost and extra-vehicular activities that might impact the reduced gravity environment the experiments are exposed to. The monitoring system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many increments (an increment usually lasts 6 months) collected onboard the station for selected disturbances. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential systems failures. The monitoring system has two operating modes: online and offline. Both near real-time on-line vibratory disturbance detection and off-line detection and trend analysis are discussed in this paper.

The problem of ecological scaling in spatially complex, nonequilibrium ecological systems [chapter 3

Treesearch

Samuel A. Cushman; Jeremy Littell; Kevin McGarigal

2010-01-01

In the previous chapter we reviewed the challenges posed by spatial complexity and temporal disequilibrium to efforts to understand and predict the structure and dynamics of ecological systems. The central theme was that spatial variability in the environment and population processes fundamentally alters the interactions between species and their environments, largely...

An object programming based environment for protein secondary structure prediction.

PubMed

Giacomini, M; Ruggiero, C; Sacile, R

1996-01-01

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

Low frequency vibration isolation technology for microgravity space experiments

NASA Technical Reports Server (NTRS)

Grodsinsky, Carlos M.; Brown, Gerald V.

1989-01-01

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

Characterizing the Severe Turbulence Environments Associated With Commercial Aviation Accidents: A Real-Time Turbulence Model (RTTM) Designed for the Operational Prediction of Hazardous Aviation Turbulence Environments

NASA Technical Reports Server (NTRS)

Kaplan, Michael L.; Lux, Kevin M.; Cetola, Jeffrey D.; Huffman, Allan W.; Riordan, Allen J.; Slusser, Sarah W.; Lin, Yuh-Lang; Charney, Joseph J.; Waight, Kenneth T.

2004-01-01

Real-time prediction of environments predisposed to producing moderate-severe aviation turbulence is studied. We describe the numerical model and its postprocessing system designed for said prediction of environments predisposed to severe aviation turbulence as well as presenting numerous examples of its utility. The numerical model is MASS version 5.13, which is integrated over three different grid matrices in real time on a university work station in support of NASA Langley Research Center s B-757 turbulence research flight missions. The postprocessing system includes several turbulence-related products, including four turbulence forecasting indices, winds, streamlines, turbulence kinetic energy, and Richardson numbers. Additionally, there are convective products including precipitation, cloud height, cloud mass fluxes, lifted index, and K-index. Furthermore, soundings, sounding parameters, and Froude number plots are also provided. The horizontal cross-section plot products are provided from 16 000 to 46 000 ft in 2000-ft intervals. Products are available every 3 hours at the 60- and 30-km grid interval and every 1.5 hours at the 15-km grid interval. The model is initialized from the NWS ETA analyses and integrated two times a day.

Prediction of passenger ride quality in a multifactor environment

NASA Technical Reports Server (NTRS)

Dempsey, T. K.; Leatherwood, J. D.

1976-01-01

A model being developed, permits the understanding and prediction of passenger discomfort in a multifactor environment with particular emphasis upon combined noise and vibration. The model has general applicability to diverse transportation systems and provides a means of developing ride quality design criteria as well as a diagnostic tool for identifying the vibration and/or noise stimuli causing discomfort. Presented are: (1) a review of the basic theoretical and mathematical computations associated with the model, (2) a discussion of methodological and criteria investigations for both the vertical and roll axes of vibration, (3) a description of within-axis masking of discomfort responses for the vertical axis, thereby allowing prediction of the total discomfort due to any random vertical vibration, (4) a discussion of initial data on between-axis masking, and (5) discussion of a study directed towards extension of the vibration model to the more general case of predicting ride quality in the combined noise and vibration environments.

Reflector surface distortion analysis techniques (thermal distortion analysis of antennas in space)

NASA Technical Reports Server (NTRS)

Sharp, R.; Liao, M.; Giriunas, J.; Heighway, J.; Lagin, A.; Steinbach, R.

1989-01-01

A group of large computer programs are used to predict the farfield antenna pattern of reflector antennas in the thermal environment of space. Thermal Radiation Analysis Systems (TRASYS) is a thermal radiation analyzer that interfaces with Systems Improved Numerical Differencing Analyzer (SINDA), a finite difference thermal analysis program. The programs linked together for this analysis can now be used to predict antenna performance in the constantly changing space environment. They can be used for very complex spacecraft and antenna geometries. Performance degradation caused by methods of antenna reflector construction and materials selection are also taken into consideration. However, the principal advantage of using this program linkage is to account for distortions caused by the thermal environment of space and the hygroscopic effects of the dry-out of graphite/epoxy materials after the antenna is placed into orbit. The results of this type of analysis could ultimately be used to predict antenna reflector shape versus orbital position. A phased array antenna distortion compensation system could then use this data to make RF phase front corrections. That is, the phase front could be adjusted to account for the distortions in the antenna feed and reflector geometry for a particular orbital position.

The Space Shuttle Orbiter molecular environment induced by the supplemental flash evaporator system

NASA Technical Reports Server (NTRS)

Ehlers, H. K. F.

1985-01-01

The water vapor environment of the Space Shuttle Orbiter induced by the supplemental flash evaporator during the on-orbit flight phase has been analyzed based on Space II model predictions and orbital flight measurements. Model data of local density, column density, and return flux are presented. Results of return flux measurements with a mass spectrometer during STS-2 and of direct flux measurements during STS-4 are discussed and compared with model predictions.

The Properties of Convective Clouds Over the Western Pacific and Their Relationship to the Environment of Tropical Cyclones

DTIC Science & Technology

2010-09-30

oceans from radar , aircraft and satellite data; 2) Derive an accurate mesoscale environment of convective systems through the assimilation of satellite... radar , lidar and in-situ data; 3) Evaluate the quality of the global forecast system (e.g., Navy Operational Global Atmospheric Prediction System or...from Aqua and NASA Tropical Rainfall Measuring Mission (TRMM), 2) developing mesoscale data assimilation techniques to assimilate satellite, radar

eTOXlab, an open source modeling framework for implementing predictive models in production environments.

PubMed

Carrió, Pau; López, Oriol; Sanz, Ferran; Pastor, Manuel

2015-01-01

Computational models based in Quantitative-Structure Activity Relationship (QSAR) methodologies are widely used tools for predicting the biological properties of new compounds. In many instances, such models are used as a routine in the industry (e.g. food, cosmetic or pharmaceutical industry) for the early assessment of the biological properties of new compounds. However, most of the tools currently available for developing QSAR models are not well suited for supporting the whole QSAR model life cycle in production environments. We have developed eTOXlab; an open source modeling framework designed to be used at the core of a self-contained virtual machine that can be easily deployed in production environments, providing predictions as web services. eTOXlab consists on a collection of object-oriented Python modules with methods mapping common tasks of standard modeling workflows. This framework allows building and validating QSAR models as well as predicting the properties of new compounds using either a command line interface or a graphic user interface (GUI). Simple models can be easily generated by setting a few parameters, while more complex models can be implemented by overriding pieces of the original source code. eTOXlab benefits from the object-oriented capabilities of Python for providing high flexibility: any model implemented using eTOXlab inherits the features implemented in the parent model, like common tools and services or the automatic exposure of the models as prediction web services. The particular eTOXlab architecture as a self-contained, portable prediction engine allows building models with confidential information within corporate facilities, which can be safely exported and used for prediction without disclosing the structures of the training series. The software presented here provides full support to the specific needs of users that want to develop, use and maintain predictive models in corporate environments. The technologies used by eTOXlab (web services, VM, object-oriented programming) provide an elegant solution to common practical issues; the system can be installed easily in heterogeneous environments and integrates well with other software. Moreover, the system provides a simple and safe solution for building models with confidential structures that can be shared without disclosing sensitive information.

Rate dependent fractionation of sulfur isotopes in through-flowing systems

NASA Astrophysics Data System (ADS)

Giannetta, M.; Sanford, R. A.; Druhan, J. L.

2017-12-01

The fidelity of reactive transport models in quantifying microbial activity in the subsurface is often improved through the use stable isotopes. However, the accuracy of current predictions for microbially mediated isotope fractionations within open through-flowing systems typically depends on nutrient availability. This disparity arises from the common application of a single `effective' fractionation factor assigned to a given system, despite extensive evidence for variability in the fractionation factor between eutrophic environments and many naturally occurring, nutrient-limited environments. Here, we demonstrate a reactive transport model with the capacity to simulate a variable fractionation factor over a range of microbially mediated reduction rates and constrain the model with experimental data for nutrient limited conditions. Two coupled isotope-specific Monod rate laws for 32S and 34S, constructed to quantify microbial sulfate reduction and predict associated S isotope partitioning, were parameterized using a series of batch reactor experiments designed to minimize microbial growth. In the current study, we implement these parameterized isotope-specific rate laws within an open, through-flowing system to predict variable fractionation with distance as a function of sulfate reduction rate. These predictions are tested through a supporting laboratory experiment consisting of a flow-through column packed with homogenous porous media inoculated with the same species of sulfate reducing bacteria used in the previous batch reactors, Desulfovibrio vulgaris. The collective results of batch reactor and flow-through column experiments support a significant improvement for S isotope predictions in isotope-sensitive multi-component reactive transport models through treatment of rate-dependent fractionation. Such an update to the model will better equip reactive transport software for isotope informed characterization of microbial activity within energy and nutrient limited environments.

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning

PubMed Central

Jo, ByungWan

2018-01-01

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R2 and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality. PMID:29561777

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning.

PubMed

Jo, ByungWan; Khan, Rana Muhammad Asad

2018-03-21

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R ² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

Predicting the thermal/structural performance of the atmospheric trace molecules spectroscopy /ATMOS/ Fourier transform spectrometer

NASA Technical Reports Server (NTRS)

Miller, J. M.

1980-01-01

ATMOS is a Fourier transform spectrometer to measure atmospheric trace molecules over a spectral range of 2-16 microns. Assessment of the system performance of ATMOS includes evaluations of optical system errors induced by thermal and structural effects. In order to assess the optical system errors induced from thermal and structural effects, error budgets are assembled during system engineering tasks and line of sight and wavefront deformations predictions (using operational thermal and vibration environments and computer models) are subsequently compared to the error budgets. This paper discusses the thermal/structural error budgets, modelling and analysis methods used to predict thermal/structural induced errors and the comparisons that show that predictions are within the error budgets.

Reducing usage of the computational resources by event driven approach to model predictive control

NASA Astrophysics Data System (ADS)

Misik, Stefan; Bradac, Zdenek; Cela, Arben

2017-08-01

This paper deals with a real-time and optimal control of dynamic systems while also considers the constraints which these systems might be subject to. Main objective of this work is to propose a simple modification of the existing Model Predictive Control approach to better suit needs of computational resource-constrained real-time systems. An example using model of a mechanical system is presented and the performance of the proposed method is evaluated in a simulated environment.

Acoustics Research of Propulsion Systems

NASA Technical Reports Server (NTRS)

Gao, Ximing; Houston, Janice

2014-01-01

The liftoff phase induces high acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests to generate 1/3 octave band Sound Pressure Level (SPL) spectra. In an effort to update the accuracy and quality of liftoff acoustic loading predictions, non-stationary flight data from the Ares I-X were processed in PC-Signal in two flight phases: simulated hold-down and liftoff. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semi-empirical methods. This consisted of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares I-X flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Development and Life Prediction of Erosion Resistant Turbine Low Conductivity Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Miller, Robert A.; Kuczmarski, Maria A.

2010-01-01

Future rotorcraft propulsion systems are required to operate under highly-loaded conditions and in harsh sand erosion environments, thereby imposing significant material design and durability issues. The incorporation of advanced thermal barrier coatings (TBC) in high pressure turbine systems enables engine designs with higher inlet temperatures, thus improving the engine efficiency, power density and reliability. The impact and erosion resistance of turbine thermal barrier coating systems are crucial to the turbine coating technology application, because a robust turbine blade TBC system is a prerequisite for fully utilizing the potential coating technology benefit in the rotorcraft propulsion. This paper describes the turbine blade TBC development in addressing the coating impact and erosion resistance. Advanced thermal barrier coating systems with improved performance have also been validated in laboratory simulated engine erosion and/or thermal gradient environments. A preliminary life prediction modeling approach to emphasize the turbine blade coating erosion is also presented.

Measurements of Ground Acoustic Environments for Small Solid Rocket Motor Firings

NASA Technical Reports Server (NTRS)

Vu, Bruce; Plotkin, Ken

2011-01-01

Mobile launcher deck and tower are exposed to severe acoustic environments during launch. These environments, if not properly managed, can weaken ground support equipment and result in structure failure. The objectives of this study were: (1) Characterize the acoustic ground environment with and without water suppression systems. (2) Validate the ground acoustic prediction based on scaling of Saturn V data. and (3) Validate a semi-empirical acoustic analysis.

Space Environmental Effects (SEE) Testing Capability: NASA/Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

DeWittBurns, H.; Crave, Paul; Finckenor, Miria; Finchum, Charles; Nehls, Mary; Schneider, Todd; Vaughn, Jason

2012-01-01

Understanding the effects of the space environment on materials and systems is fundamental and essential for mission success. If not properly understood and designed for, the space environment can lead to materials degradation, reduction of functional lifetime, and system failure. Ground based testing is critical in predicting performance NASA/MSFC's expertise and capabilities make up the most complete SEE testing capability available.

Online EEG-Based Workload Adaptation of an Arithmetic Learning Environment.

PubMed

Walter, Carina; Rosenstiel, Wolfgang; Bogdan, Martin; Gerjets, Peter; Spüler, Martin

2017-01-01

In this paper, we demonstrate a closed-loop EEG-based learning environment, that adapts instructional learning material online, to improve learning success in students during arithmetic learning. The amount of cognitive workload during learning is crucial for successful learning and should be held in the optimal range for each learner. Based on EEG data from 10 subjects, we created a prediction model that estimates the learner's workload to obtain an unobtrusive workload measure. Furthermore, we developed an interactive learning environment that uses the prediction model to estimate the learner's workload online based on the EEG data and adapt the difficulty of the learning material to keep the learner's workload in an optimal range. The EEG-based learning environment was used by 13 subjects to learn arithmetic addition in the octal number system, leading to a significant learning effect. The results suggest that it is feasible to use EEG as an unobtrusive measure of cognitive workload to adapt the learning content. Further it demonstrates that a promptly workload prediction is possible using a generalized prediction model without the need for a user-specific calibration.

Evaluation of acoustic testing techniques for spacecraft systems

NASA Technical Reports Server (NTRS)

Cockburn, J. A.

1971-01-01

External acoustic environments, structural responses, noise reductions, and the internal acoustic environments have been predicted for a typical shroud/spacecraft system during lift-off and various critical stages of flight. Spacecraft responses caused by energy transmission from the shroud via mechanical and acoustic paths have been compared and the importance of the mechanical path has been evaluated. Theoretical predictions have been compared extensively with available laboratory and in-flight measurements. Equivalent laboratory acoustic fields for simulation of shroud response during the various phases of flight have been derived and compared in detail. Techniques for varying the time-space correlations of laboratory acoustic fields have been examined, together with methods for varying the time and spatial distribution of acoustic amplitudes. Possible acoustic testing configurations for shroud/spacecraft systems have been suggested and trade-off considerations have been reviewed. The problem of simulating the acoustic environments versus simulating the structural responses has been considered and techniques for testing without the shroud installed have been discussed.

The Properties of Convective Clouds Over the Western Pacific and Their Relationship to the Environment of Tropical Cyclones

DTIC Science & Technology

2011-09-30

assimilating satellite, radar and in-situ observations for improved numerical simulations of major Typhoons (Jiangmi, Sinlaku, Nuri and Hagupit) during T- PARC ...oceans from radar , aircraft and satellite data; 2) Derive an accurate mesoscale environment of convective systems through the assimilation of satellite... radar , lidar and in-situ data; 3) Evaluate the quality of the global forecast system (e.g., Navy Operational Global Atmospheric Prediction System or

Discriminability of Prediction Artifacts in a Time Delayed Virtual Environment

NASA Technical Reports Server (NTRS)

Adelstein, Bernard D.; Jung, Jae Y.; Ellis, Stephen R.

2001-01-01

Overall latency remains an impediment to perceived image stability and consequently to human performance in virtual environment (VE) systems. Predictive compensators have been proposed as a means to mitigate these shortcomings, but they introduce rendering errors because of induced motion overshoot and heightened noise. Discriminability of these compensator artifacts was investigated by a protocol in which head tracked image stability for 35 ms baseline VE system latency was compared against artificially added (16.7 to 100 ms) latency compensated by a previously studied Kalman Filter (K-F) predictor. A control study in which uncompensated 16.7 to 100 ms latencies were compared against the baseline was also performed. Results from 10 subjects in the main study and 8 in the control group indicate that predictive compensation artifacts are less discernible than the disruptions of uncompensated time delay for the shorter but not the longer added latencies. We propose that noise magnification and overshoot are contributory cues to the presence of predictive compensation.

Development and approach to low-frequency microgravity isolation systems

NASA Technical Reports Server (NTRS)

Grodsinsky, Carlos M.

1990-01-01

The low-gravity environment provided by space flight has afforded the science community a unique arena for the study of fundamental and technological sciences. However, the dynamic environment observed on space shuttle flights and predicted for Space Station Freedom has complicated the analysis of prior microgravity experiments and prompted concern for the viability of proposed space experiments requiring long-term, low-gravity environments. Thus, isolation systems capable of providing significant improvements to this random environment are being developed. The design constraints imposed by acceleration-sensitive, microgravity experiment payloads in the unique environment of space and a theoretical background for active isolation are discussed. A design is presented for a six-degree-of-freedom, active, inertial isolation system based on the baseline relative and inertial isolation techniques described.

Analysis of EAWAG-BBD pathway prediction system for the identification of malathion degrading microbes

PubMed Central

Sivakumar, Subramaniam; Anitha, Palanivel; Ramesh, Balsubramanian; Suresh, Gopal

2017-01-01

Insecticides are the toxic substances that are used to kill insects. The use of insecticides is believed to be one of the major factors behind the increase in agricultural productivity in the 20th century. The organophosphates are now the largest and most versatile class of insecticide used and Malathion is the predominant type utilized. The accumulation of Malathion in environment is the biggest threat to the environment because of its toxicity. Malathion is lethal to beneficial insects, snails, micro crustaceans, fish, birds, amphibians, and soil microorganisms. Chronic exposure of non-diabetic farmers to organophosphorus Malathion pesticides may induce insulin resistance, which might ultimately results in diabetes mellitus. Given the potential carcinogenic risk from the pesticides there is serious need to develop remediation processes to eliminate or minimize contamination in the environment. Biodegradation could be a reliable and cost effective technique for pesticide abatement. Since today as there were no metabolic pathway predicted for the degradation of organophosphates pesticide Malathion in KEGG database or in any of the other pathway databases. Thus in the present study, an attempt has been made to predict the microbial biodegradation pathway of Malathion using bioinformatics tools. The present study predicted the degradation pathway for Malathion. The present study also identifies, Streptomyces sp. and E.coli are capable of degrading Malathion through pathway prediction system. PMID:28584447

Analysis of EAWAG-BBD pathway prediction system for the identification of malathion degrading microbes.

PubMed

Sivakumar, Subramaniam; Anitha, Palanivel; Ramesh, Balsubramanian; Suresh, Gopal

2017-01-01

Insecticides are the toxic substances that are used to kill insects. The use of insecticides is believed to be one of the major factors behind the increase in agricultural productivity in the 20th century. The organophosphates are now the largest and most versatile class of insecticide used and Malathion is the predominant type utilized. The accumulation of Malathion in environment is the biggest threat to the environment because of its toxicity. Malathion is lethal to beneficial insects, snails, micro crustaceans, fish, birds, amphibians, and soil microorganisms. Chronic exposure of non-diabetic farmers to organophosphorus Malathion pesticides may induce insulin resistance, which might ultimately results in diabetes mellitus. Given the potential carcinogenic risk from the pesticides there is serious need to develop remediation processes to eliminate or minimize contamination in the environment. Biodegradation could be a reliable and cost effective technique for pesticide abatement. Since today as there were no metabolic pathway predicted for the degradation of organophosphates pesticide Malathion in KEGG database or in any of the other pathway databases. Thus in the present study, an attempt has been made to predict the microbial biodegradation pathway of Malathion using bioinformatics tools. The present study predicted the degradation pathway for Malathion. The present study also identifies, Streptomyces sp. and E.coli are capable of degrading Malathion through pathway prediction system.

A Morphing Radiator for High-Turndown Thermal Control of Crewed Space Exploration Vehicles

NASA Technical Reports Server (NTRS)

Cognata, Thomas J.; Hardtl, Darren; Sheth, Rubik; Dinsmore, Craig

2015-01-01

Spacecraft designed for missions beyond low earth orbit (LEO) face a difficult thermal control challenge, particularly in the case of crewed vehicles where the thermal control system (TCS) must maintain a relatively constant internal environment temperature despite a vastly varying external thermal environment and despite heat rejection needs that are contrary to the potential of the environment. A thermal control system is in other words required to reject a higher heat load to warm environments and a lower heat load to cold environments, necessitating a quite high turndown ratio. A modern thermal control system is capable of a turndown ratio of on the order of 12:1, but for crew safety and environment compatibility these are massive multi-loop fluid systems. This paper discusses the analysis of a unique radiator design which employs the behavior of shape memory alloys (SMA) to vary the turndown of, and thus enable, a single-loop vehicle thermal control system for space exploration vehicles. This design, a morphing radiator, varies its shape in response to facesheet temperature to control view of space and primary surface emissivity. Because temperature dependence is inherent to SMA behavior, the design requires no accommodation for control, instrumentation, nor power supply in order to operate. Thermal and radiation modeling of the morphing radiator predict a turndown ranging from 11.9:1 to 35:1 independent of TCS configuration. Stress and deformation analyses predict the desired morphing behavior of the concept. A system level mass analysis shows that by enabling a single loop architecture this design could reduce the TCS mass by between 139 kg and 225 kg. The concept is demonstrated in proof-of-concept benchtop tests.

A Morphing Radiator for High-Turndown Thermal Control of Crewed Space Exploration Vehicles

NASA Technical Reports Server (NTRS)

Cognata, Thomas J.; Hartl, Darren J.; Sheth, Rubik; Dinsmore, Craig

2014-01-01

Spacecraft designed for missions beyond low earth orbit (LEO) face a difficult thermal control challenge, particularly in the case of crewed vehicles where the thermal control system (TCS) must maintain a relatively constant internal environment temperature despite a vastly varying external thermal environment and despite heat rejection needs that are contrary to the potential of the environment. A thermal control system may be required to reject a higher heat load to warm environments and a lower heat load to cold environments, necessitating a relatively high turndown ratio. A modern thermal control system is capable of a turndown ratio of on the order of 12:1, but crew safety and environment compatibility have constrained these solutions to massive multi-loop fluid systems. This paper discusses the analysis of a unique radiator design that employs the behavior of shape memory alloys (SMAs) to vary the turndown of, and thus enable, a single-loop vehicle thermal control system for space exploration vehicles. This design, a morphing radiator, varies its shape in response to facesheet temperature to control view of space and primary surface emissivity. Because temperature dependence is inherent to SMA behavior, the design requires no accommodation for control, instrumentation, or power supply in order to operate. Thermal and radiation modeling of the morphing radiator predict a turndown ranging from 11.9:1 to 35:1 independent of TCS configuration. Coupled thermal-stress analyses predict that the desired morphing behavior of the concept is attainable. A system level mass analysis shows that by enabling a single loop architecture this design could reduce the TCS mass by between 139 kg and 225 kg. The concept has been demonstrated in proof-of-concept benchtop tests.

Continued Research into Characterizing the Preturbulence Environment for Sensor Development, New Hazard Algorithms and Experimental Flight Planning

NASA Technical Reports Server (NTRS)

Kaplan, Michael L.; Lin, Yuh-Lang

2005-01-01

The purpose of the research was to develop and test improved hazard algorithms that could result in the development of sensors that are better able to anticipate potentially severe atmospheric turbulence, which affects aircraft safety. The research focused on employing numerical simulation models to develop improved algorithms for the prediction of aviation turbulence. This involved producing both research simulations and real-time simulations of environments predisposed to moderate and severe aviation turbulence. The research resulted in the following fundamental advancements toward the aforementioned goal: 1) very high resolution simulations of turbulent environments indicated how predictive hazard indices could be improved resulting in a candidate hazard index that indicated the potential for improvement over existing operational indices, 2) a real-time turbulence hazard numerical modeling system was improved by correcting deficiencies in its simulation of moist convection and 3) the same real-time predictive system was tested by running the code twice daily and the hazard prediction indices updated and improved. Additionally, a simple validation study was undertaken to determine how well a real time hazard predictive index performed when compared to commercial pilot observations of aviation turbulence. Simple statistical analyses were performed in this validation study indicating potential skill in employing the hazard prediction index to predict regions of varying intensities of aviation turbulence. Data sets from a research numerical model where provided to NASA for use in a large eddy simulation numerical model. A NASA contractor report and several refereed journal articles where prepared and submitted for publication during the course of this research.

Maltreatment, Family Environment, and Social Risk Factors: Determinants of the Child Welfare to Juvenile Justice Transition among Maltreated Children and Adolescents

PubMed Central

Vidal, Sarah; Prince, Dana; Connell, Christian M.; Caron, Colleen M.; Kaufman, Joy S.; Tebes, Jacob K.

2017-01-01

This study prospectively examines the transition from the child welfare system into the juvenile justice system among 10,850 maltreated children and adolescents and explores how patterns of risks, including severity and chronicity of maltreatment, adverse family environment, and social risk factors, affect service systems transition. Almost three percent of maltreated children and adolescents had their first juvenile justice adjudication within an average of approximately six years of their initial child protective services investigation (CPS). Social risk factors, including a child’s age at index CPS investigation (older), gender (boys), and race/ethnicity (Black and Hispanic vs. White) significantly predicted the risk of transition into the juvenile justice system. Recurrence of maltreatment and experiencing at least one incident of neglect over the course of the study period also increased the risk of transition into the juvenile justice system. However, subtypes of maltreatment, including physical, sexual, and other types of abuse did not significantly predict the risk of juvenile justice system transition. Finally, family environment characterized by poverty also significantly increased the risk of juvenile justice system transition. These findings have important implications for developing and tailoring services for maltreated children, particularly those at-risk for transitioning into the juvenile justice system. PMID:27886518

Maltreatment, family environment, and social risk factors: Determinants of the child welfare to juvenile justice transition among maltreated children and adolescents.

PubMed

Vidal, Sarah; Prince, Dana; Connell, Christian M; Caron, Colleen M; Kaufman, Joy S; Tebes, Jacob K

2017-01-01

This study prospectively examines the transition from the child welfare system into the juvenile justice system among 10,850 maltreated children and adolescents and explores how patterns of risks, including severity and chronicity of maltreatment, adverse family environment, and social risk factors, affect service systems transition. Almost three percent of maltreated children and adolescents had their first juvenile justice adjudication within an average of approximately six years of their initial child protective services investigation (CPS). Social risk factors, including a child's age at index CPS investigation (older), gender (boys), and race/ethnicity (Black and Hispanic) significantly predicted the risk of transition into the juvenile justice system. Recurrence of maltreatment and experiencing at least one incident of neglect over the course of the study period also increased the risk of transition into the juvenile justice system. However, subtypes of maltreatment, including physical, sexual, and other types of abuse did not significantly predict the risk of juvenile justice system transition. Finally, family environment characterized by poverty also significantly increased the risk of juvenile justice system transition. These findings have important implications for developing and tailoring services for maltreated children, particularly those at-risk for transitioning into the juvenile justice system. Copyright © 2016 Elsevier Ltd. All rights reserved.

Resource Management in Constrained Dynamic Situations

NASA Astrophysics Data System (ADS)

Seok, Jinwoo

Resource management is considered in this dissertation for systems with limited resources, possibly combined with other system constraints, in unpredictably dynamic environments. Resources may represent fuel, power, capabilities, energy, and so on. Resource management is important for many practical systems; usually, resources are limited, and their use must be optimized. Furthermore, systems are often constrained, and constraints must be satisfied for safe operation. Simplistic resource management can result in poor use of resources and failure of the system. Furthermore, many real-world situations involve dynamic environments. Many traditional problems are formulated based on the assumptions of given probabilities or perfect knowledge of future events. However, in many cases, the future is completely unknown, and information on or probabilities about future events are not available. In other words, we operate in unpredictably dynamic situations. Thus, a method is needed to handle dynamic situations without knowledge of the future, but few formal methods have been developed to address them. Thus, the goal is to design resource management methods for constrained systems, with limited resources, in unpredictably dynamic environments. To this end, resource management is organized hierarchically into two levels: 1) planning, and 2) control. In the planning level, the set of tasks to be performed is scheduled based on limited resources to maximize resource usage in unpredictably dynamic environments. In the control level, the system controller is designed to follow the schedule by considering all the system constraints for safe and efficient operation. Consequently, this dissertation is mainly divided into two parts: 1) planning level design, based on finite state machines, and 2) control level methods, based on model predictive control. We define a recomposable restricted finite state machine to handle limited resource situations and unpredictably dynamic environments for the planning level. To obtain a policy, dynamic programing is applied, and to obtain a solution, limited breadth-first search is applied to the recomposable restricted finite state machine. A multi-function phased array radar resource management problem and an unmanned aerial vehicle patrolling problem are treated using recomposable restricted finite state machines. Then, we use model predictive control for the control level, because it allows constraint handling and setpoint tracking for the schedule. An aircraft power system management problem is treated that aims to develop an integrated control system for an aircraft gas turbine engine and electrical power system using rate-based model predictive control. Our results indicate that at the planning level, limited breadth-first search for recomposable restricted finite state machines generates good scheduling solutions in limited resource situations and unpredictably dynamic environments. The importance of cooperation in the planning level is also verified. At the control level, a rate-based model predictive controller allows good schedule tracking and safe operations. The importance of considering the system constraints and interactions between the subsystems is indicated. For the best resource management in constrained dynamic situations, the planning level and the control level need to be considered together.

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.

Orchestrating Bulk Data Movement in Grid Environments

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

Vazhkudai, SS

2005-01-25

Data Grids provide a convenient environment for researchers to manage and access massively distributed bulk data by addressing several system and transfer challenges inherent to these environments. This work addresses issues involved in the efficient selection and access of replicated data in Grid environments in the context of the Globus Toolkit{trademark}, building middleware that (1) selects datasets in highly replicated environments, enabling efficient scheduling of data transfer requests; (2) predicts transfer times of bulk wide-area data transfers using extensive statistical analysis; and (3) co-allocates bulk data transfer requests, enabling parallel downloads from mirrored sites. These efforts have demonstrated a decentralizedmore » data scheduling architecture, a set of forecasting tools that predict bandwidth availability within 15% error and co-allocation architecture, and heuristics that expedites data downloads by up to 2 times.« less

Microgravity Acceleration Environment of the International Space Station (panel)

NASA Technical Reports Server (NTRS)

DeLombard, Richard; Hrovat, Kenneth; Kelly, Eric; McPherson, Kevin; Foster, William M.; Schafer, Craig P.

2001-01-01

This paper examines the microgravity environment provided to the early science experiments by the International Space Station vehicle which is under construction. The microgravity environment will be compared with predicted levels for this stage of assembly. Included are initial analyses of the environment and preliminary identification of some sources of accelerations. Features of the operations of the accelerometer instruments, the data processing system, and data dissemination to users are also described.

Genetic variability of psychrotolerant Acidithiobacillus ferrivorans revealed by (meta)genomic analysis.

PubMed

González, Carolina; Yanquepe, María; Cardenas, Juan Pablo; Valdes, Jorge; Quatrini, Raquel; Holmes, David S; Dopson, Mark

2014-11-01

Acidophilic microorganisms inhabit low pH environments such as acid mine drainage that is generated when sulfide minerals are exposed to air. The genome sequence of the psychrotolerant Acidithiobacillus ferrivorans SS3 was compared to a metagenome from a low temperature acidic stream dominated by an A. ferrivorans-like strain. Stretches of genomic DNA characterized by few matches to the metagenome, termed 'metagenomic islands', encoded genes associated with metal efflux and pH homeostasis. The metagenomic islands were enriched in mobile elements such as phage proteins, transposases, integrases and in one case, predicted to be flanked by truncated tRNAs. Cus gene clusters predicted to be involved in copper efflux and further Cus-like RND systems were predicted to be located in metagenomic islands and therefore, constitute part of the flexible gene complement of the species. Phylogenetic analysis of Cus clusters showed both lineage specificity within the Acidithiobacillus genus as well as niche specificity associated with an acidic environment. The metagenomic islands also contained a predicted copper efflux P-type ATPase system and a polyphosphate kinase potentially involved in polyphosphate mediated copper resistance. This study identifies genetic variability of low temperature acidophiles that likely reflects metal resistance selective pressures in the copper rich environment. Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

The Properties of Convective Clouds Over the Western Pacific and Their Relationship to the Environment of Tropical Cyclones

DTIC Science & Technology

2009-09-30

from radar , aircraft and satellite data; 2) Derive an accurate mesoscale environment of convective systems through the assimilation of satellite... radar , lidar and in-situ data; 3) Evaluate the quality of the global forecast system (e.g., Navy Operational Global Atmospheric Prediction System or...ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 satellite, radar , lidar and in-situ data

ICPP: Approach for Understanding Complexity of Plasma

NASA Astrophysics Data System (ADS)

Sato, Tetsuya

2000-10-01

In this talk I wish to present an IT system that could promote Science of Complexity. In order to deal with a seemingly `complex' phenomenon, which means `beyond analytical manipulation', computer simulation is a viable powerful tool. However, complexity implies a concept beyond the horizon of reductionism. Therefore, rather than simply solving a complex phenomenon for a given boundary condition, one must establish an intelligent way of attacking mutual evolution of a system and its environment. NIFS-TCSC has been developing a prototype system that consists of supercomputers, virtual reality devices and high-speed network system. Let us explain this by picking up a global atmospheric circulation group, global oceanic circulation group and local weather prediction group. Local weather prediction group predicts the local change of the weather such as the creation of cloud and rain in the near future under the global conditions obtained by the global atmospheric and ocean groups. The global groups run simulations by modifying the local heat source/sink evaluated by the local weather prediction and then obtain the global conditions in the next time step. By repeating such a feedback performance one can predict the mutual evolution of the local system and its environment. Mutual information exchanges among multiple groups are carried out instantaneously by the networked common virtual reality space in which 3-D global and local images of the atmospheric and oceanic circulation and the cloud and rain maps are arbitrarily manipulated by any of the groups and commonly viewed. The present networking system has a great advantage that any simulation groups can freely and arbitrarily change their alignment, so that mutual evolution of any stratum system can become tractable by utilizing this network system.

Homogenization Theory for the Prediction of Obstructed Solute Diffusivity in Macromolecular Solutions.

PubMed

Donovan, Preston; Chehreghanianzabi, Yasaman; Rathinam, Muruhan; Zustiak, Silviya Petrova

2016-01-01

The study of diffusion in macromolecular solutions is important in many biomedical applications such as separations, drug delivery, and cell encapsulation, and key for many biological processes such as protein assembly and interstitial transport. Not surprisingly, multiple models for the a-priori prediction of diffusion in macromolecular environments have been proposed. However, most models include parameters that are not readily measurable, are specific to the polymer-solute-solvent system, or are fitted and do not have a physical meaning. Here, for the first time, we develop a homogenization theory framework for the prediction of effective solute diffusivity in macromolecular environments based on physical parameters that are easily measurable and not specific to the macromolecule-solute-solvent system. Homogenization theory is useful for situations where knowledge of fine-scale parameters is used to predict bulk system behavior. As a first approximation, we focus on a model where the solute is subjected to obstructed diffusion via stationary spherical obstacles. We find that the homogenization theory results agree well with computationally more expensive Monte Carlo simulations. Moreover, the homogenization theory agrees with effective diffusivities of a solute in dilute and semi-dilute polymer solutions measured using fluorescence correlation spectroscopy. Lastly, we provide a mathematical formula for the effective diffusivity in terms of a non-dimensional and easily measurable geometric system parameter.

Interactive Schematic Integration Within the Propellant System Modeling Environment

NASA Technical Reports Server (NTRS)

Coote, David; Ryan, Harry; Burton, Kenneth; McKinney, Lee; Woodman, Don

2012-01-01

Task requirements for rocket propulsion test preparations of the test stand facilities drive the need to model the test facility propellant systems prior to constructing physical modifications. The Propellant System Modeling Environment (PSME) is an initiative designed to enable increased efficiency and expanded capabilities to a broader base of NASA engineers in the use of modeling and simulation (M&S) technologies for rocket propulsion test and launch mission requirements. PSME will enable a wider scope of users to utilize M&S of propulsion test and launch facilities for predictive and post-analysis functionality by offering a clean, easy-to-use, high-performance application environment.

Solar-Terrestrial Predictions: Proceedings of a workshop. Volume 2: Geomagnetic and space environment papers and ionosphere papers

NASA Astrophysics Data System (ADS)

Thompson, R. J.; Cole, D. G.; Wilkinson, P. J.; Shea, M. A.; Smart, D.

1990-11-01

The following subject areas were covered: a probability forecast for geomagnetic activity; cost recovery in solar-terrestrial predictions; magnetospheric specification and forecasting models; a geomagnetic forecast and monitoring system for power system operation; some aspects of predicting magnetospheric storms; some similarities in ionospheric disturbance characteristics in equatorial, mid-latitude, and sub-auroral regions; ionospheric support for low-VHF radio transmission; a new approach to prediction of ionospheric storms; a comparison of the total electron content of the ionosphere around L=4 at low sunspot numbers with the IRI model; the French ionospheric radio propagation predictions; behavior of the F2 layer at mid-latitudes; and the design of modern ionosondes.

Recent Geoeffective Space Weather Events and Technological System Impacts

NASA Astrophysics Data System (ADS)

Redmon, R. J.; Denig, W. F.; Loto'aniu, P. T. M.; Singer, H. J.; Wilkinson, D. C.; Knipp, D. J.; Kilcommons, L. M.

2015-12-01

We review the state of the space environment for three recent intense geoeffective storms using NOAA observations and model predictions. On February 27, 2014, the US Wide Area Augmentation System (WAAS) navigation service over eastern Alaska and northeastern continental US was degraded due to a strong ionospheric storm. Similarly, on March 17, the St. Patrick's Day geomagnetic storm commenced, resulting in the most intense storm of the solar cycle to date with mid-latitude auroral sightings, intense ionospheric irregularities and WAAS degradation. On June 22, a strong (G4) geomagnetic storm commenced following the impact of 3 coronal mass ejections (CMEs). Late on June 22, solar protons entered the polar regions along open magnetic field lines producing intense radio absorption. We summarize, compare and contrast the space environmental state for each of these events from the perspective of NOAA observations and model predictions. We do so by leveraging GOES and POES/MetOp observations of the space radiation environment, DMSP observations of precipitating particles and bulk plasma parameters, OVATION Prime predictions of the auroral energy input and the US Total Electron Content (USTEC) and D-Region Absorption Prediction (DRAP) modeled response of the ionosphere. We discuss impacts to technological systems as available.

Relationships among neighborhood environment, racial discrimination, psychological distress, and preterm birth in African American women.

PubMed

Giurgescu, Carmen; Zenk, Shannon N; Dancy, Barbara L; Park, Chang G; Dieber, William; Block, Richard

2012-01-01

To (a) examine the relationships among objective and perceived indicators of neighborhood environment, racial discrimination, psychological distress, and gestational age at birth; (b) determine if neighborhood environment and racial discrimination predicted psychological distress; (c) determine if neighborhood environment, racial discrimination, and psychological distress predicted preterm birth; and (d) determine if psychological distress mediated the effects of neighborhood environment and racial discrimination on preterm birth. Descriptive correlational comparative. Postpartum unit of a medical center in Chicago. African American women (n(1)  = 33 with preterm birth; n(2)  = 39 with full-term birth). Women completed the instruments 24 to 72 hours after birth. Objective measures of the neighborhood were derived using geographic information systems (GIS). Women who reported higher levels of perceived social and physical disorder and perceived crime also reported higher levels of psychological distress. Women who reported more experiences of racial discrimination also had higher levels of psychological distress. Objective social disorder and perceived crime predicted psychological distress. Objective physical disorder and psychological distress predicted preterm birth. Psychological distress mediated the effect of objective social disorder and perceived crime on preterm birth. Women's neighborhood environments and racial discrimination were related to psychological distress, and these factors may increase the risk for preterm birth. © 2012 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses.

Predicting Student Performance in a Collaborative Learning Environment

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

2015-01-01

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Study of high altitude plume impingement

NASA Technical Reports Server (NTRS)

Wojciechowski, C. J.; Penny, M. M.; Prozan, R. J.; Seymour, D.; Greenwood, T. F.

1972-01-01

Computer program has been developed as analytical tool to predict severity of effects of exhaust of rocket engines on adjacent spacecraft surfaces. Program computes forces, moments, pressures, and heating rates on surfaces immersed in or subjected to exhaust plume environments. Predictions will be useful in design of systems where such problems are anticipated.

Evaluation of Radiation Belt Space Weather Forecasts for Internal Charging Analyses

NASA Technical Reports Server (NTRS)

Minow, Joseph I.; Coffey, Victoria N.; Jun, Insoo; Garrett, Henry B.

2007-01-01

A variety of static electron radiation belt models, space weather prediction tools, and energetic electron datasets are used by spacecraft designers and operations support personnel as internal charging code inputs to evaluate electrostatic discharge risks in space systems due to exposure to relativistic electron environments. Evaluating the environment inputs is often accomplished by comparing whether the data set or forecast tool reliability predicts measured electron flux (or fluence over a given period) for some chosen period. While this technique is useful as a model metric, it does not provide the information necessary to evaluate whether short term deviances of the predicted flux is important in the charging evaluations. In this paper, we use a 1-D internal charging model to compute electric fields generated in insulating materials as a function of time when exposed to relativistic electrons in the Earth's magnetosphere. The resulting fields are assumed to represent the "true" electric fields and are compared with electric field values computed from relativistic electron environments derived from a variety of space environment and forecast tools. Deviances in predicted fields compared to the "true" fields which depend on insulator charging time constants will be evaluated as a potential metric for determining the importance of predicted and measured relativistic electron flux deviations over a range of time scales.

Structural, Thermal, and Optical Performance (STOP) Modeling and Results for the James Webb Space Telescope Integrated Science Instrument Module

NASA Technical Reports Server (NTRS)

Gracey, Renee; Bartoszyk, Andrew; Cofie, Emmanuel; Comber, Brian; Hartig, George; Howard, Joseph; Sabatke, Derek; Wenzel, Greg; Ohl, Raymond

2016-01-01

The James Webb Space Telescope includes the Integrated Science Instrument Module (ISIM) element that contains four science instruments (SI) including a Guider. We performed extensive structural, thermal, and optical performance(STOP) modeling in support of all phases of ISIM development. In this paper, we focus on modeling and results associated with test and verification. ISIMs test program is bound by ground environments, mostly notably the 1g and test chamber thermal environments. This paper describes STOP modeling used to predict ISIM system performance in 0g and at various on-orbit temperature environments. The predictions are used to project results obtained during testing to on-orbit performance.

Analyzing System on A Chip Single Event Upset Responses using Single Event Upset Data, Classical Reliability Models, and Space Environment Data

NASA Technical Reports Server (NTRS)

Berg, Melanie; LaBel, Kenneth; Campola, Michael; Xapsos, Michael

2017-01-01

We are investigating the application of classical reliability performance metrics combined with standard single event upset (SEU) analysis data. We expect to relate SEU behavior to system performance requirements. Our proposed methodology will provide better prediction of SEU responses in harsh radiation environments with confidence metrics. single event upset (SEU), single event effect (SEE), field programmable gate array devises (FPGAs)

STS-1 mission contamination evaluation approach

NASA Technical Reports Server (NTRS)

Jacobs, S.; Ehlers, H.; Miller, E. R.

1980-01-01

The space transportation system 1 mission will be the first opportunity to assess the induced environment of the orbiter payload bay region. Two tools were developed to aid in this assessment. The shuttle payload contamination evaluation computer program was developed to provide an analytical tool for prediction of the induced molecular contamination environment of the space shuttle orbiter during its onorbit operations. An induced environment contamination monitor was constructed and tested to measure the space shuttle orbiter contamination environment inside the payload bay during ascent and descent and inside and outside the payload bay during the onorbit phase. Measurements are to be performed during the four orbital flight test series. Measurements planned for the first flight are described and predicted environmental data are discussed. The results indicate that the expected data are within the measurement range of the induced environment contamination monitor instruments evaluated, and therefore it is expected that useful contamination environmental data will be available after the first flight.

Using VAPEPS for noise control on Space Station Freedom

NASA Technical Reports Server (NTRS)

Badilla, Gloria; Bergen, Thomas; Scharton, Terry

1991-01-01

Noise environmental control is an important design consideration for Space Station Freedom (SSF), both for crew safety and productivity. Acoustic noise requirements are established to eliminate fatigue and potential hearing loss by crew members from long-term exposure and to facilitate speech communication. VAPEPS (VibroAcoustic Payload Environment Prediction System) is currently being applied to SSF for prediction of the on-orbit noise and vibration environments induced in the 50 to 10,000 Hz frequency range. Various sources such as fans, pumps, centrifuges, exercise equipment, and other mechanical devices are used in the analysis. The predictions will be used in design tradeoff studies and to provide confidence that requirements will be met. Preliminary predictions show that the required levels will be exceeded unless substantial noise control measures are incorporated in the SSF design. Predicted levels for an SSF design without acoustic control treatments exceed requirements by 25 dB in some one-third octave frequency bands.

Real-time estimation of incident delay in dynamic and stochastic networks

DOT National Transportation Integrated Search

1997-01-01

The ability to predict the link travel times is a necessary requirement for most intelligent transportation systems (ITS) applications such as route guidance systems. In an urban traffic environment, these travel times are dynamic and stochastic and ...

Fifth International Symposium on Liquid Space Propulsion

NASA Technical Reports Server (NTRS)

Garcia, R. (Compiler)

2005-01-01

Contents include the fiollowing: Theme: Life-life Combustion Devices Technology. Technical Sessions: International Perspectives. System Level Effects. Component Level Processes. Material Considerations. Design Environments -- Predictions. Injector Design Technology. Design Environments -- Measurements. Panel Discussion: Views on future research and development needs and Symposium observations. Aquarium Welcome and Southern Belle Riverboat Recognition Banquet evening events.

CORMIX1: AN EXPERT SYSTEM FOR MIXING ZONE ANALYSIS OF TOXIC AND CONVENTIONAL, SINGLE PORT AQUATIC DISCHARGES

EPA Science Inventory

An expert system, CORMIX1, was developed to predict the dilution and trajectory of a single buoyant discharge into an unstratified aquatic environment with and without crossflow. The system uses knowledge and inference rules obtained from hydrodynamic experts to classify and pred...

Envirotyping for deciphering environmental impacts on crop plants.

PubMed

Xu, Yunbi

2016-04-01

Global climate change imposes increasing impacts on our environments and crop production. To decipher environmental impacts on crop plants, the concept "envirotyping" is proposed, as a third "typing" technology, complementing with genotyping and phenotyping. Environmental factors can be collected through multiple environmental trials, geographic and soil information systems, measurement of soil and canopy properties, and evaluation of companion organisms. Envirotyping contributes to crop modeling and phenotype prediction through its functional components, including genotype-by-environment interaction (GEI), genes responsive to environmental signals, biotic and abiotic stresses, and integrative phenotyping. Envirotyping, driven by information and support systems, has a wide range of applications, including environmental characterization, GEI analysis, phenotype prediction, near-iso-environment construction, agronomic genomics, precision agriculture and breeding, and development of a four-dimensional profile of crop science involving genotype (G), phenotype (P), envirotype (E) and time (T) (developmental stage). In the future, envirotyping needs to zoom into specific experimental plots and individual plants, along with the development of high-throughput and precision envirotyping platforms, to integrate genotypic, phenotypic and envirotypic information for establishing a high-efficient precision breeding and sustainable crop production system based on deciphered environmental impacts.

Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans.

PubMed

Stevens, Jeffrey R; Marewski, Julian N; Schooler, Lael J; Gilby, Ian C

2016-08-01

In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees ( Pan troglodytes ) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition.

Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans

PubMed Central

Marewski, Julian N.; Schooler, Lael J.; Gilby, Ian C.

2016-01-01

In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees (Pan troglodytes) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition. PMID:27853606

Man-Machine Integration Design and Analysis System (MIDAS) v5: Augmentations, Motivations, and Directions for Aeronautics Applications

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2011-01-01

As automation and advanced technologies are introduced into transport systems ranging from the Next Generation Air Transportation System termed NextGen, to the advanced surface transportation systems as exemplified by the Intelligent Transportations Systems, to future systems designed for space exploration, there is an increased need to validly predict how the future systems will be vulnerable to error given the demands imposed by the assistive technologies. One formalized approach to study the impact of assistive technologies on the human operator in a safe and non-obtrusive manner is through the use of human performance models (HPMs). HPMs play an integral role when complex human-system designs are proposed, developed, and tested. One HPM tool termed the Man-machine Integration Design and Analysis System (MIDAS) is a NASA Ames Research Center HPM software tool that has been applied to predict human-system performance in various domains since 1986. MIDAS is a dynamic, integrated HPM and simulation environment that facilitates the design, visualization, and computational evaluation of complex man-machine system concepts in simulated operational environments. The paper will discuss a range of aviation specific applications including an approach used to model human error for NASA s Aviation Safety Program, and what-if analyses to evaluate flight deck technologies for NextGen operations. This chapter will culminate by raising two challenges for the field of predictive HPMs for complex human-system designs that evaluate assistive technologies: that of (1) model transparency and (2) model validation.

The single event upset environment for avionics at high latitude

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

Sims, A.J.; Dyer, C.S.; Peerless, C.L.

1994-12-01

Modern avionic systems for civil and military applications are becoming increasingly reliant upon embedded microprocessors and associated memory devices. The phenomenon of single event upset (SEU) is well known in space systems and designers have generally been careful to use SEU tolerant devices or to implement error detection and correction (EDAC) techniques where appropriate. In the past, avionics designers have had no reason to consider SEU effects but is clear that the more prevalent use of memory devices combined with increasing levels of IC integration will make SEU mitigation an important design consideration for future avionic systems. To this end,more » it is necessary to work towards producing models of the avionics SEU environment which will permit system designers to choose components and EDAC techniques which are based on predictions of SEU rates correct to much better than an order of magnitude. Measurements of the high latitude SEU environment at avionics altitude have been made on board a commercial airliner. Results are compared with models of primary and secondary cosmic rays and atmospheric neutrons. Ground based SEU tests of static RAMs are used to predict rates in flight.« less

Modeling critical habitat for Flammulated Owls (Otus flammeolus)

Treesearch

David A. Christie; Astrid M. van Woudenberg

1997-01-01

Multiple logistic regression analysis was used to produce a prediction model for Flammulated Owl (Otus flammeolus) breeding habitat within the Kamloops Forest Region in south-central British Columbia. Using the model equation, a pilot habitat prediction map was created within a Geographic Information System (GIS) environment that had a 75.7 percent...

Automation Rover for Extreme Environments

NASA Technical Reports Server (NTRS)

Sauder, Jonathan; Hilgemann, Evan; Johnson, Michael; Parness, Aaron; Hall, Jeffrey; Kawata, Jessie; Stack, Kathryn

2017-01-01

Almost 2,300 years ago the ancient Greeks built the Antikythera automaton. This purely mechanical computer accurately predicted past and future astronomical events long before electronics existed1. Automata have been credibly used for hundreds of years as computers, art pieces, and clocks. However, in the past several decades automata have become less popular as the capabilities of electronics increased, leaving them an unexplored solution for robotic spacecraft. The Automaton Rover for Extreme Environments (AREE) proposes an exciting paradigm shift from electronics to a fully mechanical system, enabling longitudinal exploration of the most extreme environments within the solar system.

Model Predictions and Observed Performance of JWST's Cryogenic Position Metrology System

NASA Technical Reports Server (NTRS)

Lunt, Sharon R.; Rhodes, David; DiAntonio, Andrew; Boland, John; Wells, Conrad; Gigliotti, Trevis; Johanning, Gary

2016-01-01

The James Webb Space Telescope cryogenic testing requires measurement systems that both obtain a very high degree of accuracy and can function in that environment. Close-range photogrammetry was identified as meeting those criteria. Testing the capability of a close-range photogrammetric system prior to its existence is a challenging problem. Computer simulation was chosen over building a scaled mock-up to allow for increased flexibility in testing various configurations. Extensive validation work was done to ensure that the actual as-built system meet accuracy and repeatability requirements. The simulated image data predicted the uncertainty in measurement to be within specification and this prediction was borne out experimentally. Uncertainty at all levels was verified experimentally to be less than 0.1 millimeters.

Research in space commercialization, technology transfer, and communications, volume 2

NASA Technical Reports Server (NTRS)

Dunn, D. A.; Agnew, C. E.

1983-01-01

Spectrum management, models for evaluating communication systems, the communications regulatory environment, expert prediction and consensus, remote sensing, and manned space operations research are discussed.

Microbial community assembly patterns under incipient conditions in a basaltic soil system

NASA Astrophysics Data System (ADS)

Sengupta, A.; Stegen, J.; Alves Meira Neto, A.; Wang, Y.; Chorover, J.; Troch, P. A. A.; Maier, R. M.

2017-12-01

In sub-surface environments, the biotic components are critically linked to the abiotic processes. However, there is limited understanding of community establishment, functional associations, and community assembly processes of such microbes in sub-surface environments. This study presents the first analysis of microbial signatures in an incipient terrestrial basalt soil system conducted under controlled conditions. A sub-meter scale sampling of a soil mesocosm revealed the contrasting distribution patterns of simple soil parameters such as bulk density and electrical conductivity. Phylogenetic analysis of 16S rRNA gene indicated the presence of a total 40 bacterial and archaeal phyla, with high relative abundance of Actinobacteria on the surface and highest abundance of Proteobacteria throughout the system. Community diversity patterns were inferred to be dependent on depth profile and average water content in the system. Predicted functional gene analysis suggested mixotrophy lifestyles with both autotrophic and heterotrophic metabolisms, likelihood of a unique salt tolerant methanogenic pathway with links to novel Euryarchea, signatures of an incomplete nitrogen cycle, and predicted enzymes of extracellular iron (II) to iron (III) conversion followed by intracellular uptake, transport and regulation. Null modeling revealed microbial community assembly was predominantly governed by variable selection, but the influence of the variable selection did not show systematic spatial structure. The presence of significant heterogeneity in predicted functions and ecologically deterministic shifts in community composition in a homogeneous incipient basalt highlights the complexity exhibited by microorganisms even in the simplest of environmental systems. This presents an opportunity to further develop our understanding of how microbial communities establish, evolve, impact, and respond in sub-surface environments.

The UKC2 regional coupled environmental prediction system

NASA Astrophysics Data System (ADS)

Lewis, Huw W.; Castillo Sanchez, Juan Manuel; Graham, Jennifer; Saulter, Andrew; Bornemann, Jorge; Arnold, Alex; Fallmann, Joachim; Harris, Chris; Pearson, David; Ramsdale, Steven; Martínez-de la Torre, Alberto; Bricheno, Lucy; Blyth, Eleanor; Bell, Victoria A.; Davies, Helen; Marthews, Toby R.; O'Neill, Clare; Rumbold, Heather; O'Dea, Enda; Brereton, Ashley; Guihou, Karen; Hines, Adrian; Butenschon, Momme; Dadson, Simon J.; Palmer, Tamzin; Holt, Jason; Reynard, Nick; Best, Martin; Edwards, John; Siddorn, John

2018-01-01

It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather mediated through various components of the environment, require a more integrated Earth System approach to forecasting. This hypothesis can be explored using regional coupled prediction systems, in which the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land can be simulated. Such systems are becoming increasingly common research tools. This paper describes the development of the UKC2 regional coupled research system, which has been delivered under the UK Environmental Prediction Prototype project. This provides the first implementation of an atmosphere-land-ocean-wave modelling system focussed on the United Kingdom and surrounding seas at km-scale resolution. The UKC2 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled, via OASIS3-MCT libraries, at unprecedentedly high resolution across the UK within a north-western European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a new research tool for UK environmental science. This paper documents the technical design and implementation of UKC2, along with the associated evaluation framework. An analysis of new results comparing the output of the coupled UKC2 system with relevant forced control simulations for six contrasting case studies of 5-day duration is presented. Results demonstrate that performance can be achieved with the UKC2 system that is at least comparable to its component control simulations. For some cases, improvements in air temperature, sea surface temperature, wind speed, significant wave height and mean wave period highlight the potential benefits of coupling between environmental model components. Results also illustrate that the coupling itself is not sufficient to address all known model issues. Priorities for future development of the UK Environmental Prediction framework and component systems are discussed.

Progress and challenges in the development of physically-based numerical models for prediction of flow and contaminant dispersion in the urban environment

NASA Astrophysics Data System (ADS)

Lien, F. S.; Yee, E.; Ji, H.; Keats, A.; Hsieh, K. J.

2006-06-01

The release of chemical, biological, radiological, or nuclear (CBRN) agents by terrorists or rogue states in a North American city (densely populated urban centre) and the subsequent exposure, deposition and contamination are emerging threats in an uncertain world. The modeling of the transport, dispersion, deposition and fate of a CBRN agent released in an urban environment is an extremely complex problem that encompasses potentially multiple space and time scales. The availability of high-fidelity, time-dependent models for the prediction of a CBRN agent's movement and fate in a complex urban environment can provide the strongest technical and scientific foundation for support of Canada's more broadly based effort at advancing counter-terrorism planning and operational capabilities.The objective of this paper is to report the progress of developing and validating an integrated, state-of-the-art, high-fidelity multi-scale, multi-physics modeling system for the accurate and efficient prediction of urban flow and dispersion of CBRN (and other toxic) materials discharged into these flows. Development of this proposed multi-scale modeling system will provide the real-time modeling and simulation tool required to predict injuries, casualties and contamination and to make relevant decisions (based on the strongest technical and scientific foundations) in order to minimize the consequences of a CBRN incident in a populated centre.

The role of future scenarios to understand deep uncertainty

EPA Science Inventory

The environment and its interaction with human systems(economic, social and political) is complex and dynamic. Key drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents a challe...

A Method for Evaluating the Safety Impacts of Air Traffic Automation

NASA Technical Reports Server (NTRS)

Kostiuk, Peter; Shapiro, Gerald; Hanson, Dave; Kolitz, Stephan; Leong, Frank; Rosch, Gene; Bonesteel, Charles

1998-01-01

This report describes a methodology for analyzing the safety and operational impacts of emerging air traffic technologies. The approach integrates traditional reliability models of the system infrastructure with models that analyze the environment within which the system operates, and models of how the system responds to different scenarios. Products of the analysis include safety measures such as predicted incident rates, predicted accident statistics, and false alarm rates; and operational availability data. The report demonstrates the methodology with an analysis of the operation of the Center-TRACON Automation System at Dallas-Fort Worth International Airport.

Homogenization Theory for the Prediction of Obstructed Solute Diffusivity in Macromolecular Solutions

PubMed Central

Donovan, Preston; Chehreghanianzabi, Yasaman; Rathinam, Muruhan; Zustiak, Silviya Petrova

2016-01-01

The study of diffusion in macromolecular solutions is important in many biomedical applications such as separations, drug delivery, and cell encapsulation, and key for many biological processes such as protein assembly and interstitial transport. Not surprisingly, multiple models for the a-priori prediction of diffusion in macromolecular environments have been proposed. However, most models include parameters that are not readily measurable, are specific to the polymer-solute-solvent system, or are fitted and do not have a physical meaning. Here, for the first time, we develop a homogenization theory framework for the prediction of effective solute diffusivity in macromolecular environments based on physical parameters that are easily measurable and not specific to the macromolecule-solute-solvent system. Homogenization theory is useful for situations where knowledge of fine-scale parameters is used to predict bulk system behavior. As a first approximation, we focus on a model where the solute is subjected to obstructed diffusion via stationary spherical obstacles. We find that the homogenization theory results agree well with computationally more expensive Monte Carlo simulations. Moreover, the homogenization theory agrees with effective diffusivities of a solute in dilute and semi-dilute polymer solutions measured using fluorescence correlation spectroscopy. Lastly, we provide a mathematical formula for the effective diffusivity in terms of a non-dimensional and easily measurable geometric system parameter. PMID:26731550

User manual of the CATSS system (version 1.0) communication analysis tool for space station

NASA Technical Reports Server (NTRS)

Tsang, C. S.; Su, Y. T.; Lindsey, W. C.

1983-01-01

The Communication Analysis Tool for the Space Station (CATSS) is a FORTRAN language software package capable of predicting the communications links performance for the Space Station (SS) communication and tracking (C & T) system. An interactive software package was currently developed to run on the DEC/VAX computers. The CATSS models and evaluates the various C & T links of the SS, which includes the modulation schemes such as Binary-Phase-Shift-Keying (BPSK), BPSK with Direct Sequence Spread Spectrum (PN/BPSK), and M-ary Frequency-Shift-Keying with Frequency Hopping (FH/MFSK). Optical Space Communication link is also included. CATSS is a C & T system engineering tool used to predict and analyze the system performance for different link environment. Identification of system weaknesses is achieved through evaluation of performance with varying system parameters. System tradeoff for different values of system parameters are made based on the performance prediction.

The effects of high energy particles on planetary missions

NASA Technical Reports Server (NTRS)

Robinson, Paul A., Jr.

1988-01-01

Researchers review the background and motivation for the detailed study of the variability and uncertainty of the particle environment from a space systems planning perspective. The engineering concern raised by each environment is emphasized rather than the underlying physics of the magnetosphere or the sun. Missions now being planned span the short term range of one to three years to periods over ten years. Thus the engineering interest is beginning to stretch over periods of several solar cycles. Coincidentally, detailed measurements of the environment are now becoming available over that period of time. Both short term and long term environmental predictions are needed for proper mission planning. Short term predictions, perhaps based on solar indices, real time observations, or short term systematics, are very useful in near term planning -- launches, EVAs (extravehicular activities), coordinated observations, and experiments which require the magnetosphere to be in a certain state. Long term predictions of both average and extreme conditions are essential to mission design. Engineering considerations are many times driven by the worst case environment. Knowledge of the average conditions and their variability allows trade-off studies to be made, implementation of designs which degrade gracefully under multi-stress environments.

On the nature of the fragment environment created by the range destruction or random failure of solid rocket motor casings

NASA Technical Reports Server (NTRS)

Eck, M.; Mukunda, M.

1988-01-01

Given here are predictions of fragment velocities and azimuths resulting from the Space Transportation System Solid Rocket Motor range destruct, or random failure occurring at any time during the 120 seconds of Solid Rocket Motor burn. Results obtained using the analytical methods described showed good agreement between predictions and observations for two specific events. It was shown that these methods have good potential for use in predicting the fragmentation process of a number of generically similar casing systems. It was concluded that coupled Eulerian-Lagrangian calculational methods of the type described here provide a powerful tool for predicting Solid Rocket Motor response.

Munitions in the Underwater Environment: State of the Science and Knowledge Gaps

DTIC Science & Technology

2010-06-01

the Munitions Items Disposition Action System ( MIDAS ). Munitions constituents (MCs) can be identified through the known munitions type. The MIDAS and...physical damage to the casing, adjacent or touching metals, and water or substrate qualities such as temperature, pH, or Redox potential. The...environments, little is known on modeling the fate of MCs in the underwater environment. One of the anticipated problems in predicting the fate and

Verification of an analytic modeler for capillary pump loop thermal control systems

NASA Technical Reports Server (NTRS)

Schweickart, R. B.; Neiswanger, L.; Ku, J.

1987-01-01

A number of computer programs have been written to model two-phase heat transfer systems for space use. These programs support the design of thermal control systems and provide a method of predicting their performance in the wide range of thermal environments of space. Predicting the performance of one such system known as the capillary pump loop (CPL) is the intent of the CPL Modeler. By modeling two developed CPL systems and comparing the results with actual test data, the CPL Modeler has proven useful in simulating CPL operation. Results of the modeling effort are discussed, together with plans for refinements to the modeler.

Launch Vehicle Debris Models and Crew Vehicle Ascent Abort Risk

NASA Technical Reports Server (NTRS)

Gee, Ken; Lawrence, Scott

2013-01-01

For manned space launch systems, a reliable abort system is required to reduce the risks associated with a launch vehicle failure during ascent. Understanding the risks associated with failure environments can be achieved through the use of physics-based models of these environments. Debris fields due to destruction of the launch vehicle is one such environment. To better analyze the risk posed by debris, a physics-based model for generating launch vehicle debris catalogs has been developed. The model predicts the mass distribution of the debris field based on formulae developed from analysis of explosions. Imparted velocity distributions are computed using a shock-physics code to model the explosions within the launch vehicle. A comparison of the debris catalog with an existing catalog for the Shuttle external tank show good comparison in the debris characteristics and the predicted debris strike probability. The model is used to analyze the effects of number of debris pieces and velocity distributions on the strike probability and risk.

Uncertainties in radiation effect predictions for the natural radiation environments of space.

PubMed

McNulty, P J; Stassinopoulos, E G

1994-10-01

Future manned missions beyond low earth orbit require accurate predictions of the risk to astronauts and to critical systems from exposure to ionizing radiation. For low-level exposures, the hazards are dominated by rare single-event phenomena where individual cosmic-ray particles or spallation reactions result in potentially catastrophic changes in critical components. Examples might be a biological lesion leading to cancer in an astronaut or a memory upset leading to an undesired rocket firing. The risks of such events appears to depend on the amount of energy deposited within critical sensitive volumes of biological cells and microelectronic components. The critical environmental information needed to estimate the risks posed by the natural space environments, including solar flares, is the number of times more than a threshold amount of energy for an event will be deposited in the critical microvolumes. These predictions are complicated by uncertainties in the natural environments, particularly the composition of flares, and by the effects of shielding. Microdosimetric data for large numbers of orbits are needed to improve the environmental models and to test the transport codes used to predict event rates.

Uncertainties in radiation effect predictions for the natural radiation environments of space

NASA Technical Reports Server (NTRS)

Mcnulty, P. J.; Stassinopoulos, E. G.

1994-01-01

Future manned missions beyond low earth orbit require accurate predictions of the risk to astronauts and to critical systems from exposure to ionizing radiation. For low-level exposures, the hazards are dominated by rare single-event phenomena where individual cosmic-ray particles or spallation reactions result in potentially catastrophic changes in critical components. Examples might be a biological lesion leading to cancer in an astronaut or a memory upset leading to an undesired rocket firing. The risks of such events appears to depend on the amount of energy deposited within critical sensitive volumes of biological cells and microelectronic components. The critical environmental information needed to estimate the risks posed by the natural space environments, including solar flares, is the number of times more than a threshold amount of energy for an event will be deposited in the critical microvolumes. These predictions are complicated by uncertainties in the natural environments, particularly the composition of flares, and by the effects of shielding. Microdosimetric data for large numbers of orbits are needed to improve the environmental models and to test the transport codes used to predict event rates.

Multimedia University: A Paperless Environment to Take the Challenges for the 21st Century

ERIC Educational Resources Information Center

Reaz, Mamun Bin Ibne; Hussain, Sazzad; Khadem, Shajib

2007-01-01

Predictability of absolute data transaction for real time information and reduction of incalculable data delivery time are the major factors to lead the global education as well as economic system towards a paperless environment. Some universities such as the University of Phoenix, Western Governors University, UK Open University, University of…

RFI Math Model programs for predicting intermodulation interference

NASA Technical Reports Server (NTRS)

Stafford, J. M.

1974-01-01

Receivers operating on a space vehicle or an aircraft having many on-board transmitters are subject to intermodulation interference from mixing in the transmitting antenna systems, the external environment, or the receiver front-ends. This paper presents the techniques utilized in RFI Math Model computer programs that were developed to aid in the prevention of interference by predicting problem areas prior to occurrence. Frequencies and amplitudes of possible intermodulation products generated in the external environment are calculated and compared to receiver sensitivities. Intermodulation products generated in receivers are evaluated to determine the adequacy of preselector ejection.

Learning about Ecological Systems by Constructing Qualitative Models with DynaLearn

ERIC Educational Resources Information Center

Leiba, Moshe; Zuzovsky, Ruth; Mioduser, David; Benayahu, Yehuda; Nachmias, Rafi

2012-01-01

A qualitative model of a system is an abstraction that captures ordinal knowledge and predicts the set of qualitatively possible behaviours of the system, given a qualitative description of its structure and initial state. This paper examines an innovative approach to science education using an interactive learning environment that supports…

The role of future scenarios to understand deep uncertainty in air quality management

EPA Science Inventory

The environment and it’s interaction with human systems (economic, social and political) is complex and dynamic. Key drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents ...

Operational specification and forecasting advances for Dst, LEO thermospheric densities, and aviation radiation dose and dose rate

NASA Astrophysics Data System (ADS)

Tobiska, W. Kent

Space weather’s effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun’s photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET’s Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. In addition, an ENLIL/Rice Dst prediction out to several days has also been developed and will be described. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the “weather” of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning.

PubMed

Chalmers, Eric; Contreras, Edgar Bermudez; Robertson, Brandon; Luczak, Artur; Gruber, Aaron

2017-04-17

The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in the future. The ability to predict actions' consequences may facilitate such knowledge transfer. We consider here domains where an RL agent has access to two kinds of information: agent-centric information with constant semantics across tasks, and environment-centric information, which is necessary to solve the task, but with semantics that differ between tasks. For example, in robot navigation, environment-centric information may include the robot's geographic location, while agent-centric information may include sensor readings of various nearby obstacles. We propose that these situations provide an opportunity for a very natural style of knowledge transfer, in which the agent learns to predict actions' environmental consequences using agent-centric information. These predictions contain important information about the affordances and dangers present in a novel environment, and can effectively transfer knowledge from agent-centric to environment-centric learning systems. Using several example problems including spatial navigation and network routing, we show that our knowledge transfer approach can allow faster and lower cost learning than existing alternatives.

Reusable Solid Rocket Motor Nozzle Joint-4 Thermal Analysis

NASA Technical Reports Server (NTRS)

Clayton, J. Louie

2001-01-01

This study provides for development and test verification of a thermal model used for prediction of joint heating environments, structural temperatures and seal erosions in the Space Shuttle Reusable Solid Rocket Motor (RSRM) Nozzle Joint-4. The heating environments are a result of rapid pressurization of the joint free volume assuming a leak path has occurred in the filler material used for assembly gap close out. Combustion gases flow along the leak path from nozzle environment to joint O-ring gland resulting in local heating to the metal housing and erosion of seal materials. Analysis of this condition was based on usage of the NASA Joint Pressurization Routine (JPR) for environment determination and the Systems Improved Numerical Differencing Analyzer (SINDA) for structural temperature prediction. Model generated temperatures, pressures and seal erosions are compared to hot fire test data for several different leak path situations. Investigated in the hot fire test program were nozzle joint-4 O-ring erosion sensitivities to leak path width in both open and confined joint geometries. Model predictions were in generally good agreement with the test data for the confined leak path cases. Worst case flight predictions are provided using the test-calibrated model. Analysis issues are discussed based on model calibration procedures.

Frontotemporal Dementia Selectively Impairs Transitive Reasoning About Familiar Spatial Environments

PubMed Central

Vartanian, Oshin; Goel, Vinod; Tierney, Michael; Huey, Edward D.; Grafman, Jordan

2010-01-01

Although patients with frontotemporal dementia (FTD) are known to exhibit a wide range of cognitive and personality difficulties, some evidence suggests that there may be a degree of selectivity in their reasoning impairments. Based on a recent review of the neuroimaging literature on reasoning, the authors hypothesized that the presence or absence of familiar content may have a selective impact on the reasoning abilities of patients with FTD. Specifically, the authors predicted that patients with frontalvariant FTD would be more impaired when reasoning about transitive arguments involving familiar spatial environments than when reasoning about identical logical arguments involving unfamiliar spatial environments. As predicted, patients with FTD were less accurate than normal controls only when the content of arguments involved familiar spatial environments. These results indicate a degree of selectivity in the cognitive deficits of this patient population and suggest that the frontal-temporal lobe system may play a necessary role in reasoning about familiar material. PMID:19702415

Theory of quantized systems: formal basis for DEVS/HLA distributed simulation environment

NASA Astrophysics Data System (ADS)

Zeigler, Bernard P.; Lee, J. S.

1998-08-01

In the context of a DARPA ASTT project, we are developing an HLA-compliant distributed simulation environment based on the DEVS formalism. This environment will provide a user- friendly, high-level tool-set for developing interoperable discrete and continuous simulation models. One application is the study of contract-based predictive filtering. This paper presents a new approach to predictive filtering based on a process called 'quantization' to reduce state update transmission. Quantization, which generates state updates only at quantum level crossings, abstracts a sender model into a DEVS representation. This affords an alternative, efficient approach to embedding continuous models within distributed discrete event simulations. Applications of quantization to message traffic reduction are discussed. The theory has been validated by DEVSJAVA simulations of test cases. It will be subject to further test in actual distributed simulations using the DEVS/HLA modeling and simulation environment.

Payload/orbiter contamination control requirement study: Spacelab configuration contamination study

NASA Technical Reports Server (NTRS)

Bareiss, L. E.; Hetrick, M. A.; Ress, E. B.; Strange, D. A.

1976-01-01

The assessment of the Spacelab carrier induced contaminant environment was continued, and the ability of Spacelab to meet established contamination control criteria for the space transportation system program was determined. The primary areas considered included: (1) updating, refining, and improving the Spacelab contamination computer model and contamination analysis methodology, (2) establishing the resulting adjusted induced environment predictions for comparison with the applicable criteria, (3) determining the Spacelab design and operational requirements necessary to meet the criteria, (4) conducting mission feasibility analyses of the combined Spacelab/Orbiter contaminant environment for specific proposed mission and payload mixes, and (5) establishing a preliminary Spacelab mission support plan as well as model interface requirements; A summary of those activities conducted to date with respect to the modelling, analysis, and predictions of the induced environment, including any modifications in approach or methodology utilized in the contamination assessment of the Spacelab carrier, was presented.

Mathematical and computational modeling simulation of solar drying Systems

USDA-ARS?s Scientific Manuscript database

Mathematical modeling of solar drying systems has the primary aim of predicting the required drying time for a given commodity, dryer type, and environment. Both fundamental (Fickian diffusion) and semi-empirical drying models have been applied to the solar drying of a variety of agricultural commo...

APPLICATION OF A WATER QUALITY ASSESSMENT MODELING SYSTEM AT A SUPERFUND SITE

EPA Science Inventory

Water quality modeling and related exposure assessments at a Superfund site, Silver Bow Creek-Clark Fork River in Montana, demonstrate the capability to predict the fate of mining waste pollutants in the environment. inked assessment system--consisting of hydrology and erosion, r...

Role of future scenarios in understanding deep uncertainty in long-term air quality management

EPA Science Inventory

The environment and its interactions with human systems, whether economic, social or political, are complex. Relevant drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions. This kind of deep uncertainty presents a challenge to ...

Advanced Computational Modeling Approaches for Shock Response Prediction

NASA Technical Reports Server (NTRS)

Derkevorkian, Armen; Kolaini, Ali R.; Peterson, Lee

2015-01-01

Motivation: (1) The activation of pyroshock devices such as explosives, separation nuts, pin-pullers, etc. produces high frequency transient structural response, typically from few tens of Hz to several hundreds of kHz. (2) Lack of reliable analytical tools makes the prediction of appropriate design and qualification test levels a challenge. (3) In the past few decades, several attempts have been made to develop methodologies that predict the structural responses to shock environments. (4) Currently, there is no validated approach that is viable to predict shock environments overt the full frequency range (i.e., 100 Hz to 10 kHz). Scope: (1) Model, analyze, and interpret space structural systems with complex interfaces and discontinuities, subjected to shock loads. (2) Assess the viability of a suite of numerical tools to simulate transient, non-linear solid mechanics and structural dynamics problems, such as shock wave propagation.

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.

A Simulation System for Validating the Analytical Prediction of Performance of the Convolutional Encoded and Symbol Interleaved TDRSS S-band Return Link Service in a Pulsed RFI Environment

NASA Technical Reports Server (NTRS)

1981-01-01

A hardware integrated convolutional coding/symbol interleaving and integrated symbol deinterleaving/Viterbi decoding simulation system is described. Validation on the system of the performance of the TDRSS S-band return link with BPSK modulation, operating in a pulsed RFI environment is included. The system consists of three components, the Fast Linkabit Error Rate Tester (FLERT), the Transition Probability Generator (TPG), and a modified LV7017B which includes rate 1/3 capability as well as a periodic interleaver/deinterleaver. Operating and maintenance manuals for each of these units are included.

Common spaceborne multicomputer operating system and development environment

NASA Technical Reports Server (NTRS)

Craymer, L. G.; Lewis, B. F.; Hayes, P. J.; Jones, R. L.

1994-01-01

A preliminary technical specification for a multicomputer operating system is developed. The operating system is targeted for spaceborne flight missions and provides a broad range of real-time functionality, dynamic remote code-patching capability, and system fault tolerance and long-term survivability features. Dataflow concepts are used for representing application algorithms. Functional features are included to ensure real-time predictability for a class of algorithms which require data-driven execution on an iterative steady state basis. The development environment supports the development of algorithm code, design of control parameters, performance analysis, simulation of real-time dataflow applications, and compiling and downloading of the resulting application.

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Suarez, Vicente J.; Goodnight, Thomas W.; Callahan, John

2007-01-01

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical radioisotope power system (RPS) launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources were designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

Assessing the vulnerability of traditional maize seed systems in Mexico to climate change.

PubMed

Bellon, Mauricio R; Hodson, David; Hellin, Jon

2011-08-16

Climate change is predicted to have major impacts on small-scale farmers in Mexico whose livelihoods depend on rain-fed maize. We examined the capacity of traditional maize seed systems to provide these farmers with appropriate genetic material under predicted agro-ecological conditions associated with climate change. We studied the structure and spatial scope of seed systems of 20 communities in four transects across an altitudinal gradient from 10-2,980 m above sea level in five states of eastern Mexico. Results indicate that 90% of all of the seed lots are obtained within 10 km of a community and 87% within an altitudinal range of ±50 m but with variation across four agro-climate environments: wet lowland, dry lowland, wet upper midlatitude, and highlands. Climate models suggest a drying and warming trend for the entire study area during the main maize season, leading to substantial shifts in the spatial distribution patterns of agro-climate environments. For all communities except those in the highlands, predicted future maize environments already are represented within the 10-km radial zones, indicating that in the future farmers will have easy access to adapted planting material. Farmers in the highlands are the most vulnerable and probably will need to acquire seed from outside their traditional geographical ranges. This change in seed sources probably will entail important information costs and the development of new seed and associated social networks, including improved linkages between traditional and formal seed systems and more effective and efficient seed-supply chains. The study has implications for analogous areas elsewhere in Mexico and around the world.

Spatial Attention, Motor Intention, and Bayesian Cue Predictability in the Human Brain.

PubMed

Kuhns, Anna B; Dombert, Pascasie L; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2017-05-24

Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional system. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner. In these tasks, the percentage of cue validity changed unpredictably over time. Trialwise estimates of cue predictability were derived from a Bayesian observer model of behavioral responses. These estimates were included as parametric regressors for analyzing the BOLD time series. Parametric effects of cue predictability in valid and invalid trials were considered to reflect belief updating by precision-weighted prediction errors. The brain areas exhibiting predictability-dependent effects dissociated between the spatial attention and motor intention task, with the right temporoparietal cortex being involved during spatial attention and the left angular gyrus and anterior cingulate cortex during motor intention. Connectivity analyses revealed that all three areas showed predictability-dependent coupling with the right hippocampus. These results suggest that precision-weighted prediction errors of stimulus locations and motor responses are encoded in distinct brain regions, but that crosstalk with the hippocampus may be necessary to integrate new trialwise outcomes in both cognitive systems. SIGNIFICANCE STATEMENT The brain is able to infer the environments' statistical structure and responds strongly to expectancy violations. In the spatial attentional domain, it has been shown that parts of the attentional networks are sensitive to the predictability of stimuli. It remains unknown, however, whether these effects are ubiquitous or if they are specific for different cognitive systems. The present study compared the influence of model-derived cue predictability on brain activity in the spatial attentional and motor intentional system. We identified areas with distinct predictability-dependent activation for spatial attention and motor intention, but also common connectivity changes of these regions with the hippocampus. These findings provide novel insights into the generality and specificity of predictive processing signatures in the human brain. Copyright © 2017 the authors 0270-6474/17/375334-11$15.00/0.

Overview of the Ares I Scale Model Acoustic Test Program

NASA Technical Reports Server (NTRS)

Counter, Douglas D.; Houston, Janice D.

2011-01-01

Launch environments, such as lift-off acoustic (LOA) and ignition overpressure (IOP), are important design factors for any vehicle and are dependent upon the design of both the vehicle and the ground systems. LOA environments are used directly in the development of vehicle vibro-acoustic environments and IOP is used in the loads assessment. The NASA Constellation Program had several risks to the development of the Ares I vehicle linked to LOA. The risks included cost, schedule and technical impacts for component qualification due to high predicted vibro-acoustic environments. One solution is to mitigate the environment at the component level. However, where the environment is too severe for component survivability, reduction of the environment itself is required. The Ares I Scale Model Acoustic Test (ASMAT) program was implemented to verify the Ares I LOA and IOP environments for the vehicle and ground systems including the Mobile Launcher (ML) and tower. An additional objective was to determine the acoustic reduction for the LOA environment with an above deck water sound suppression system. ASMAT was a development test performed at the Marshall Space Flight Center (MSFC) East Test Area (ETA) Test Stand 116 (TS 116). The ASMAT program is described in this presentation.

More About Vector Adaptive/Predictive Coding Of Speech

NASA Technical Reports Server (NTRS)

Jedrey, Thomas C.; Gersho, Allen

1992-01-01

Report presents additional information about digital speech-encoding and -decoding system described in "Vector Adaptive/Predictive Encoding of Speech" (NPO-17230). Summarizes development of vector adaptive/predictive coding (VAPC) system and describes basic functions of algorithm. Describes refinements introduced enabling receiver to cope with errors. VAPC algorithm implemented in integrated-circuit coding/decoding processors (codecs). VAPC and other codecs tested under variety of operating conditions. Tests designed to reveal effects of various background quiet and noisy environments and of poor telephone equipment. VAPC found competitive with and, in some respects, superior to other 4.8-kb/s codecs and other codecs of similar complexity.

The Density Functional Theory of Flies: Predicting distributions of interacting active organisms

NASA Astrophysics Data System (ADS)

Kinkhabwala, Yunus; Valderrama, Juan; Cohen, Itai; Arias, Tomas

On October 2nd, 2016, 52 people were crushed in a stampede when a crowd panicked at a religious gathering in Ethiopia. The ability to predict the state of a crowd and whether it is susceptible to such transitions could help prevent such catastrophes. While current techniques such as agent based models can predict transitions in emergent behaviors of crowds, the assumptions used to describe the agents are often ad hoc and the simulations are computationally expensive making their application to real-time crowd prediction challenging. Here, we pursue an orthogonal approach and ask whether a reduced set of variables, such as the local densities, are sufficient to describe the state of a crowd. Inspired by the theoretical framework of Density Functional Theory, we have developed a system that uses only measurements of local densities to extract two independent crowd behavior functions: (1) preferences for locations and (2) interactions between individuals. With these two functions, we have accurately predicted how a model system of walking Drosophila melanogaster distributes itself in an arbitrary 2D environment. In addition, this density-based approach measures properties of the crowd from only observations of the crowd itself without any knowledge of the detailed interactions and thus it can make predictions about the resulting distributions of these flies in arbitrary environments, in real-time. This research was supported in part by ARO W911NF-16-1-0433.

Remote Sensing of Supercooled Cloud Layers in Cold Climate Using Ground Based Integrated Sensors System and Comparison with Pilot Reports and model forecasts

NASA Astrophysics Data System (ADS)

Boudala, Faisal; Wu, Di; Gultepe, Ismail; Anderson, Martha; turcotte, marie-france

2017-04-01

In-flight aircraft icing is one of the major weather hazards to aviation . It occurs when an aircraft passes through a cloud layer containing supercooled drops (SD). The SD in contact with the airframe freezes on the surface which degrades the performance of the aircraft.. Prediction of in-flight icing requires accurate prediction of SD sizes, liquid water content (LWC), and temperature. The current numerical weather predicting (NWP) models are not capable of making accurate prediction of SD sizes and associated LWC. Aircraft icing environment is normally studied by flying research aircraft, which is quite expensive. Thus, developing a ground based remote sensing system for detection of supercooled liquid clouds and characterization of their impact on severity of aircraft icing one of the important tasks for improving the NWPs based predictions and validations. In this respect, Environment and Climate Change Canada (ECCC) in cooperation with the Department of National Defense (DND) installed a number of specialized ground based remote sensing platforms and present weather sensors at Cold Lake, Alberta that includes a multi-channel microwave radiometer (MWR), K-band Micro Rain radar (MRR), Ceilometer, Parsivel distrometer and Vaisala PWD22 present weather sensor. In this study, a number of pilot reports confirming icing events and freezing precipitation that occurred at Cold Lake during the 2014-2016 winter periods and associated observation data for the same period are examined. The icing events are also examined using aircraft icing intensity estimated using ice accumulation model which is based on a cylindrical shape approximation of airfoil and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predicted LWC, median volume diameter and temperature. The results related to vertical atmospheric profiling conditions, surface observations, and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predictions are given. Preliminary results suggest that remote sensing and present weather sensors based observations of cloud SD regions can be used to describe micro and macro physical characteristics of the icing conditions. The model based icing intensity prediction reasonably agreed with the PIREPs and MWR observations.

Program Predicts Time Courses of Human/Computer Interactions

NASA Technical Reports Server (NTRS)

Vera, Alonso; Howes, Andrew

2005-01-01

CPM X is a computer program that predicts sequences of, and amounts of time taken by, routine actions performed by a skilled person performing a task. Unlike programs that simulate the interaction of the person with the task environment, CPM X predicts the time course of events as consequences of encoded constraints on human behavior. The constraints determine which cognitive and environmental processes can occur simultaneously and which have sequential dependencies. The input to CPM X comprises (1) a description of a task and strategy in a hierarchical description language and (2) a description of architectural constraints in the form of rules governing interactions of fundamental cognitive, perceptual, and motor operations. The output of CPM X is a Program Evaluation Review Technique (PERT) chart that presents a schedule of predicted cognitive, motor, and perceptual operators interacting with a task environment. The CPM X program allows direct, a priori prediction of skilled user performance on complex human-machine systems, providing a way to assess critical interfaces before they are deployed in mission contexts.

Space shuttle orbiter mechanical refrigeration system

NASA Technical Reports Server (NTRS)

Williams, J. L.

1974-01-01

A radiator/condenser was designed which is efficient in both condensation (refrigeration) and liquid phase (radiator) operating modes, including switchover from the refrigeration mode to the radiator mode and vice versa. A method for predicting the pressure drop of a condensing two-phase flow in zero-gravity was developed along with a method for predicting the flow regime which would prevail along the condensation path. The hybrid refrigeration system was assembled with the two radiator/condenser panels installed in a space environment simulator. The system was tested under both atmospheric and vacuum conditions. Results of the tests are presented.

Measurement and Characterization of Space Shuttle Solid Rocket Motor Plume Acoustics

NASA Technical Reports Server (NTRS)

Kenny, Jeremy; Hobbs, Chris; Plotkin, Ken; Pilkey, Debbie

2009-01-01

Lift-off acoustic environments generated by the future Ares I launch vehicle are assessed by the NASA Marshall Space Flight Center (MSFC) acoustics team using several prediction tools. This acoustic environment is directly caused by the Ares I First Stage booster, powered by the five-segment Reusable Solid Rocket Motor (RSRMV). The RSRMV is a larger-thrust derivative design from the currently used Space Shuttle solid rocket motor, the Reusable Solid Rocket Motor (RSRM). Lift-off acoustics is an integral part of the composite launch vibration environment affecting the Ares launch vehicle and must be assessed to help generate hardware qualification levels and ensure structural integrity of the vehicle during launch and lift-off. Available prediction tools that use free field noise source spectrums as a starting point for generation of lift-off acoustic environments are described in the monograph NASA SP-8072: "Acoustic Loads Generated by the Propulsion System." This monograph uses a reference database for free field noise source spectrums which consist of subscale rocket motor firings, oriented in horizontal static configurations. The phrase "subscale" is appropriate, since the thrust levels of rockets in the reference database are orders of magnitude lower than the current design thrust for the Ares launch family. Thus, extrapolation is needed to extend the various reference curves to match Ares-scale acoustic levels. This extrapolation process yields a subsequent amount of uncertainty added upon the acoustic environment predictions. As the Ares launch vehicle design schedule progresses, it is important to take every opportunity to lower prediction uncertainty and subsequently increase prediction accuracy. Never before in NASA s history has plume acoustics been measured for large scale solid rocket motors. Approximately twice a year, the RSRM prime vendor, ATK Launch Systems, static fires an assembled RSRM motor in a horizontal configuration at their test facility in Utah. The remaining RSRM static firings will take place on elevated terrain, with the nozzle exit plume being mostly undeflected and the landscape allowing placement of microphones within direct line of sight to the exhaust plume. These measurements will help assess the current extrapolation process by direct comparison between subscale and full scale solid rocket motor data.

Characterizing the Preturbulence Environment for Sensor Development, New Hazard Algorithms and NASA Experimental Flight Planning

NASA Technical Reports Server (NTRS)

Kaplan, Michael L.; Lin, Yuh-Lang

2004-01-01

During the grant period, several tasks were performed in support of the NASA Turbulence Prediction and Warning Systems (TPAWS) program. The primary focus of the research was on characterizing the preturbulence environment by developing predictive tools and simulating atmospheric conditions that preceded severe turbulence. The goal of the research being to provide both dynamical understanding of conditions that preceded turbulence as well as providing predictive tools in support of operational NASA B-757 turbulence research flights. The advancements in characterizing the preturbulence environment will be applied by NASA to sensor development for predicting turbulence onboard commercial aircraft. Numerical simulations with atmospheric models as well as multi-scale observational analyses provided insights into the environment organizing turbulence in a total of forty-eight specific case studies of severe accident producing turbulence on commercial aircraft. These accidents exclusively affected commercial aircraft. A paradigm was developed which diagnosed specific atmospheric circulation systems from the synoptic scale down to the meso-y scale that preceded turbulence in both clear air and in proximity to convection. The emphasis was primarily on convective turbulence as that is what the TPAWS program is most focused on in terms of developing improved sensors for turbulence warning and avoidance. However, the dynamical paradigm also has applicability to clear air and mountain turbulence. This dynamical sequence of events was then employed to formulate and test new hazard prediction indices that were first tested in research simulation studies and then ultimately were further tested in support of the NASA B-757 turbulence research flights. The new hazard characterization algorithms were utilized in a Real Time Turbulence Model (RTTM) that was operationally employed to support the NASA B-757 turbulence research flights. Improvements in the RTTM were implemented in an effort to increase the accuracy of the operational characterization of the preturbulence environment. Additionally, the initial research necessary to create a statistical evaluation scheme for the characterization indices utilized in the RTTM was undertaken. Results of all components of this research were then published in NASA contractor reports and scientific journal papers.

Research-Based Monitoring, Prediction, and Analysis Tools of the Spacecraft Charging Environment for Spacecraft Users

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Kuznetsova, Maria M.; Pulkkinen, Antti A.; Maddox, Marlo M.; Mays, Mona Leila

2015-01-01

The Space Weather Research Center (http://swrc. gsfc.nasa.gov) at NASA Goddard, part of the Community Coordinated Modeling Center (http://ccmc.gsfc.nasa.gov), is committed to providing research-based forecasts and notifications to address NASA's space weather needs, in addition to its critical role in space weather education. It provides a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, and weekly summaries and reports. In this paper, we focus on how (near) real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the integrated Space Weather Analysis system (http://iswa.gsfc.nasa.gov), enable monitoring, analyzing, and predicting the spacecraft charging environment for spacecraft users. Relevant tools and resources are discussed.

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.

REE radiation fault model: a tool for organizing and communication radiation test data and construction COTS based spacebourne computing systems

NASA Technical Reports Server (NTRS)

Ferraro, R.; Some, R.

2002-01-01

The growth in data rates of instruments on future NASA spacecraft continues to outstrip the improvement in communications bandwidth and processing capabilities of radiation-hardened computers. Sophisticated autonomous operations strategies will further increase the processing workload. Given the reductions in spacecraft size and available power, standard radiation hardened computing systems alone will not be able to address the requirements of future missions. The REE project was intended to overcome this obstacle by developing a COTS- based supercomputer suitable for use as a science and autonomy data processor in most space environments. This development required a detailed knowledge of system behavior in the presence of Single Event Effect (SEE) induced faults so that mitigation strategies could be designed to recover system level reliability while maintaining the COTS throughput advantage. The REE project has developed a suite of tools and a methodology for predicting SEU induced transient fault rates in a range of natural space environments from ground-based radiation testing of component parts. In this paper we provide an overview of this methodology and tool set with a concentration on the radiation fault model and its use in the REE system development methodology. Using test data reported elsewhere in this and other conferences, we predict upset rates for a particular COTS single board computer configuration in several space environments.

Leveraging Social Networking Technologies: An Analysis of the Knowledge Flows Facilitated by Social Media and the Potential Improvements in Situational Awareness, Readiness, and Productivity

DTIC Science & Technology

2010-09-01

articulating perception, interpretation and actionable prediction in an operational environment . BCKS’ success with digital storytelling has far...podcasts; wikis and other collaborative spaces; social networks such as Facebook and LinkedIn; other user generated content; virtual social environments ...study of Xerox’s knowledge management systems noting that 80% of its IT was focused on adapting to the social dynamics of its workplace environment

Dynamical mechanical characteristic simulation and analysis of the low voltage switch under vibration and shock conditions

NASA Astrophysics Data System (ADS)

Miao, Xiaodan; Han, Feng

2017-04-01

The low voltage switch has widely application especially in the hostile environment such as large vibration and shock conditions. In order to ensure the validity of the switch in the hostile environment, it is necessary to predict its mechanical characteristic. In traditional method, the complex and expensive testing system is build up to verify its validity. This paper presented a method based on finite element analysis to predict the dynamic mechanical characteristic of the switch by using ANSYS software. This simulation could provide the basis for the design and optimization of the switch to shorten the design process to improve the product efficiency.

A Simplified Approach for the Rapid Generation of Transient Heat-Shield Environments

NASA Technical Reports Server (NTRS)

Wurster, Kathryn E.; Zoby, E. Vincent; Mills, Janelle C.; Kamhawi, Hilmi

2007-01-01

A simplified approach has been developed whereby transient entry heating environments are reliably predicted based upon a limited set of benchmark radiative and convective solutions. Heating, pressure and shear-stress levels, non-dimensionalized by an appropriate parameter at each benchmark condition are applied throughout the entry profile. This approach was shown to be valid based on the observation that the fully catalytic, laminar distributions examined were relatively insensitive to altitude as well as velocity throughout the regime of significant heating. In order to establish a best prediction by which to judge the results that can be obtained using a very limited benchmark set, predictions based on a series of benchmark cases along a trajectory are used. Solutions which rely only on the limited benchmark set, ideally in the neighborhood of peak heating, are compared against the resultant transient heating rates and total heat loads from the best prediction. Predictions based on using two or fewer benchmark cases at or near the trajectory peak heating condition, yielded results to within 5-10 percent of the best predictions. Thus, the method provides transient heating environments over the heat-shield face with sufficient resolution and accuracy for thermal protection system design and also offers a significant capability to perform rapid trade studies such as the effect of different trajectories, atmospheres, or trim angle of attack, on convective and radiative heating rates and loads, pressure, and shear-stress levels.

Mars Science Laboratory Rover System Thermal Test

NASA Technical Reports Server (NTRS)

Novak, Keith S.; Kempenaar, Joshua E.; Liu, Yuanming; Bhandari, Pradeep; Dudik, Brenda A.

2012-01-01

On November 26, 2011, NASA launched a large (900 kg) rover as part of the Mars Science Laboratory (MSL) mission to Mars. The MSL rover is scheduled to land on Mars on August 5, 2012. Prior to launch, the Rover was successfully operated in simulated mission extreme environments during a 16-day long Rover System Thermal Test (STT). This paper describes the MSL Rover STT, test planning, test execution, test results, thermal model correlation and flight predictions. The rover was tested in the JPL 25-Foot Diameter Space Simulator Facility at the Jet Propulsion Laboratory (JPL). The Rover operated in simulated Cruise (vacuum) and Mars Surface environments (8 Torr nitrogen gas) with mission extreme hot and cold boundary conditions. A Xenon lamp solar simulator was used to impose simulated solar loads on the rover during a bounding hot case and during a simulated Mars diurnal test case. All thermal hardware was exercised and performed nominally. The Rover Heat Rejection System, a liquid-phase fluid loop used to transport heat in and out of the electronics boxes inside the rover chassis, performed better than predicted. Steady state and transient data were collected to allow correlation of analytical thermal models. These thermal models were subsequently used to predict rover thermal performance for the MSL Gale Crater landing site. Models predict that critical hardware temperatures will be maintained within allowable flight limits over the entire 669 Sol surface mission.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

Environment as a witness: Selective proliferation of information and emergence of objectivity in a quantum universe

NASA Astrophysics Data System (ADS)

Ollivier, Harold; Poulin, David; Zurek, Wojciech H.

2005-10-01

We study the role of the information deposited in the environment of an open quantum system in the course of the decoherence process. Redundant spreading of information—the fact that some observables of the system can be independently read off from many distinct fragments of the environment—is investigated as the key to effective objectivity, the essential ingredient of classical reality. This focus on the environment as a communication channel through which observers learn about physical systems underscores the importance of quantum Darwinism—selective proliferation of information about “the fittest states” chosen by the dynamics of decoherence at the expense of their superpositions—as redundancy imposes the existence of preferred observables. We demonstrate that the only observables that can leave multiple imprints in the environment are the familiar pointer observables singled out by environment-induced superselection (einselection) for their predictability. Many independent observers monitoring the environment will therefore agree on properties of the system as they can only learn about preferred observables. In this operational sense, the selective spreading of information leads to appearance of an objective classical reality from within the quantum substrate.

Study to assess the effects of magnetohydrodynamic electromagnetic pulse on electric power systems, phase 1, volume 3

NASA Astrophysics Data System (ADS)

Legro, J. R.; Abi-Samra, N. C.; Tesche, F. M.

1985-05-01

In addition to the initial transients designated as fast transient high-altitude EMP (HEMP) and intermediate time EMP, electromagnetic signals are also perceived at times from seconds to hundreds of seconds after a high-altitude nuclear burst. This signal was defined by the term magnetohydrodynamic-electromagnetic pulse (MHD-EMP). The MHD-EMP phenomena was detected in actual weapon tests and predicted from theoretical models. A preliminary research effort to investigate the nature and coupling of the MHD-EMP environments to electric power systems documented the construction of approximate system response network models, and the development of a unified methodology to assess equipment and systematic vulnerability are defined. The MHD-EMP environment is compared to a qualitatively similar natural event, the electromagnetic environment produced by geomagnetic storms.

Interfacing remote sensing and geographic information systems for global environmental change research

NASA Technical Reports Server (NTRS)

Lee, Jae K.; Randolph, J. C.; Lulla, Kamlesh P.; Helfert, Michael R.

1993-01-01

Because changes in the Earth's environment have become major global issues, continuous, longterm scientific information is required to assess global problems such as deforestation, desertification, greenhouse effects and climate variations. Global change studies require understanding of interactions of complex processes regulating the Earth system. Space-based Earth observation is an essential element in global change research for documenting changes in Earth environment. It provides synoptic data for conceptual predictive modeling of future environmental change. This paper provides a brief overview of remote sensing technology from the perspective of global change research.

Capturing the Complexity: Content, Type, and Amount of Instruction and Quality of the Classroom Learning Environment Synergistically Predict Third Graders' Vocabulary and Reading Comprehension Outcomes

ERIC Educational Resources Information Center

Connor, Carol McDonald; Spencer, Mercedes; Day, Stephanie L.; Giuliani, Sarah; Ingebrand, Sarah W.; McLean, Leigh; Morrison, Frederick J.

2014-01-01

We examined classrooms as complex systems that affect students' literacy learning through interacting effects of content and amount of time individual students spent in literacy instruction along with the global quality of the classroom learning environment. We observed 27 3rd-grade classrooms serving 315 target students using 2 different…

Complexity science and leadership in healthcare.

PubMed

Burns, J P

2001-10-01

The emerging field of complexity science offers an alternative leadership strategy for the chaotic, complex healthcare environment. A survey revealed that healthcare leaders intuitively support principles of complexity science. Leadership that uses complexity principles offers opportunities in the chaotic healthcare environment to focus less on prediction and control and more on fostering relationships and creating conditions in which complex adaptive systems can evolve to produce creative outcomes.

Going Home: The Influence of Workforce Performance Management Systems on the Decision to Engage in Remote Work Environments

ERIC Educational Resources Information Center

Jones, Kenneth E., Jr.

2011-01-01

Since 1975, the advance of home-based or remote work has been predicted and encouraged (Nilles). Remote work entails the ability of workers to function as productively from distant locations as those workers in face-to-face office environments: e.g. secondary offices, co-workplace offices, mobile workstations, and home. This study will look at the…

Systems and methods for knowledge discovery in spatial data

DOEpatents

Obradovic, Zoran; Fiez, Timothy E.; Vucetic, Slobodan; Lazarevic, Aleksandar; Pokrajac, Dragoljub; Hoskinson, Reed L.

2005-03-08

Systems and methods are provided for knowledge discovery in spatial data as well as to systems and methods for optimizing recipes used in spatial environments such as may be found in precision agriculture. A spatial data analysis and modeling module is provided which allows users to interactively and flexibly analyze and mine spatial data. The spatial data analysis and modeling module applies spatial data mining algorithms through a number of steps. The data loading and generation module obtains or generates spatial data and allows for basic partitioning. The inspection module provides basic statistical analysis. The preprocessing module smoothes and cleans the data and allows for basic manipulation of the data. The partitioning module provides for more advanced data partitioning. The prediction module applies regression and classification algorithms on the spatial data. The integration module enhances prediction methods by combining and integrating models. The recommendation module provides the user with site-specific recommendations as to how to optimize a recipe for a spatial environment such as a fertilizer recipe for an agricultural field.

USGS global change research

USGS Publications Warehouse

,

1995-01-01

The Earth's global environment--its interrelated climate, land, oceans, fresh water, atmospheric and ecological systems-has changed continually throughout Earth history. Human activities are having ever-increasing effects on these systems. Sustaining our environment as population and demands for resources increase requires a sound understanding of the causes and cycles of natural change and the effects of human activities on the Earth's environmental systems. The U.S. Global Change Research Program was authorized by Congress in 1989 to provide the scientific understanding necessary to develop national and international policies concerning global environmental issues, particularly global climate change. The program addresses questions such as: what factors determine global climate; have humans already begun to change the global climate; will the climate of the future be very different; what will be the effects of climate change; and how much confidence do we have in our predictions? Through understanding, we can improve our capability to predict change, reduce the adverse effects of human activities, and plan strategies for adapting to natural and human-induced environmental change.

An Efficient Recommendation Filter Model on Smart Home Big Data Analytics for Enhanced Living Environments.

PubMed

Chen, Hao; Xie, Xiaoyun; Shu, Wanneng; Xiong, Naixue

2016-10-15

With the rapid growth of wireless sensor applications, the user interfaces and configurations of smart homes have become so complicated and inflexible that users usually have to spend a great amount of time studying them and adapting to their expected operation. In order to improve user experience, a weighted hybrid recommender system based on a Kalman Filter model is proposed to predict what users might want to do next, especially when users are located in a smart home with an enhanced living environment. Specifically, a weight hybridization method was introduced, which combines contextual collaborative filter and the contextual content-based recommendations. This method inherits the advantages of the optimum regression and the stability features of the proposed adaptive Kalman Filter model, and it can predict and revise the weight of each system component dynamically. Experimental results show that the hybrid recommender system can optimize the distribution of weights of each component, and achieve more reasonable recall and precision rates.

An Efficient Recommendation Filter Model on Smart Home Big Data Analytics for Enhanced Living Environments

PubMed Central

Chen, Hao; Xie, Xiaoyun; Shu, Wanneng; Xiong, Naixue

2016-01-01

With the rapid growth of wireless sensor applications, the user interfaces and configurations of smart homes have become so complicated and inflexible that users usually have to spend a great amount of time studying them and adapting to their expected operation. In order to improve user experience, a weighted hybrid recommender system based on a Kalman Filter model is proposed to predict what users might want to do next, especially when users are located in a smart home with an enhanced living environment. Specifically, a weight hybridization method was introduced, which combines contextual collaborative filter and the contextual content-based recommendations. This method inherits the advantages of the optimum regression and the stability features of the proposed adaptive Kalman Filter model, and it can predict and revise the weight of each system component dynamically. Experimental results show that the hybrid recommender system can optimize the distribution of weights of each component, and achieve more reasonable recall and precision rates. PMID:27754456

Integrating Space Systems Operations at the Marine Expeditionary Force Level

DTIC Science & Technology

2015-06-01

Electromagnetic Interference ENVI Environment for Visualizing Images EW Electronic Warfare xvi FA40 Space Operations Officer FEC Fires and Effects...Information Facility SFE Space Force Enhancement SIGINT Signals Intelligence SSA Space Situational Awareness SSE Space Support Element STK Systems...April 23, 2015. 65 • GPS Interference and Navigation Tool (GIANT) for providing GPS accuracy prediction reports • Systems Toolkit ( STK ) Analysis

Laboratory Studies on the Formation of Carbon-Bearing Molecules in Extraterrestrial Environments: From the Gas Phase to the Solid State

NASA Technical Reports Server (NTRS)

Jamieson, C. S.; Guo, Y.; Gu, X.; Zhang, F.; Bennett, C. J.; Kaiser, R. I.

2006-01-01

A detailed knowledge of the formation of carbon-bearing molecules in interstellar ices and in the gas phase of the interstellar medium is of paramount interest to understand the astrochemical evolution of extraterrestrial environments (1). This research also holds strong implications to comprehend the chemical processing of Solar System environments such as icy planets and their moons together with the atmospheres of planets and their satellites (2). Since the present composition of each interstellar and Solar System environment reflects the matter from which it was formed and the processes which have changed the chemical nature since the origin (solar wind, planetary magnetospheres, cosmic ray exposure, photolysis, chemical reactions), a detailed investigation of the physicochemical mechanisms altering the pristine environment is of paramount importance to grasp the contemporary composition. Once these underlying processes have been unraveled, we can identify those molecules, which belonged to the nascent setting, distinguish molecular species synthesized in a later stage, and predict the imminent chemical evolution of, for instance, molecular clouds. Laboratory experiments under controlled physicochemical conditions (temperature, pressure, chemical composition, high energy components) present ideal tools for simulating the chemical evolution of interstellar and Solar System environments. Here, laboratory experiments can predict where and how (reaction mechanisms; chemicals necessary) in extraterrestrial environments and in the interstellar medium complex, carbon bearing molecules can be formed on interstellar grains and in the gas phase. This paper overviews the experimental setups utilized in our laboratory to mimic the chemical processing of gas phase and solid state (ices) environments. These are a crossed molecular beams machine (3) and a surface scattering setup (4). We also present typical results of each setup (formation of amino acids, aldehydes, epoxides; synthesis of hydrogen terminated carbon chains as precursors to complex PAHs and to carbonaceous dust grains in general; nitriles as precursor to amino acids).

Sustainable Systems SFA 2.0

ScienceCinema

Hubbard, Susan

2018-05-07

Berkeley Lab Earth Sciences Division Director Susan Hubbard, the Project Lead for the Sustainable Systems Scientific Focus Area (SFA) 2.0, gives an overview of the project and its mission to develop a predictive understanding of terrestrial environments, from the genome to the watershed scales, to enable a new class of solutions for environmental and energy solutions.

Sustainable Systems SFA 2.0

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

Hubbard, Susan

2015-12-19

Berkeley Lab Earth Sciences Division Director Susan Hubbard, the Project Lead for the Sustainable Systems Scientific Focus Area (SFA) 2.0, gives an overview of the project and its mission to develop a predictive understanding of terrestrial environments, from the genome to the watershed scales, to enable a new class of solutions for environmental and energy solutions.

A Comparison of Two Scoring Methods for an Automated Speech Scoring System

ERIC Educational Resources Information Center

Xi, Xiaoming; Higgins, Derrick; Zechner, Klaus; Williamson, David

2012-01-01

This paper compares two alternative scoring methods--multiple regression and classification trees--for an automated speech scoring system used in a practice environment. The two methods were evaluated on two criteria: construct representation and empirical performance in predicting human scores. The empirical performance of the two scoring models…

Enhanced pid vs model predictive control applied to bldc motor

NASA Astrophysics Data System (ADS)

Gaya, M. S.; Muhammad, Auwal; Aliyu Abdulkadir, Rabiu; Salim, S. N. S.; Madugu, I. S.; Tijjani, Aminu; Aminu Yusuf, Lukman; Dauda Umar, Ibrahim; Khairi, M. T. M.

2018-01-01

BrushLess Direct Current (BLDC) motor is a multivariable and highly complex nonlinear system. Variation of internal parameter values with environment or reference signal increases the difficulty in controlling the BLDC effectively. Advanced control strategies (like model predictive control) often have to be integrated to satisfy the control desires. Enhancing or proper tuning of a conventional algorithm results in achieving the desired performance. This paper presents a performance comparison of Enhanced PID and Model Predictive Control (MPC) applied to brushless direct current motor. The simulation results demonstrated that the PSO-PID is slightly better than the PID and MPC in tracking the trajectory of the reference signal. The proposed scheme could be useful algorithms for the system.

Advancing Continuous Predictive Analytics Monitoring: Moving from Implementation to Clinical Action in a Learning Health System.

PubMed

Keim-Malpass, Jessica; Kitzmiller, Rebecca R; Skeeles-Worley, Angela; Lindberg, Curt; Clark, Matthew T; Tai, Robert; Calland, James Forrest; Sullivan, Kevin; Randall Moorman, J; Anderson, Ruth A

2018-06-01

In the intensive care unit, clinicians monitor a diverse array of data inputs to detect early signs of impending clinical demise or improvement. Continuous predictive analytics monitoring synthesizes data from a variety of inputs into a risk estimate that clinicians can observe in a streaming environment. For this to be useful, clinicians must engage with the data in a way that makes sense for their clinical workflow in the context of a learning health system (LHS). This article describes the processes needed to evoke clinical action after initiation of continuous predictive analytics monitoring in an LHS. Copyright © 2018 Elsevier Inc. All rights reserved.

Engineering Aerothermal Analysis for X-34 Thermal Protection System Design

NASA Technical Reports Server (NTRS)

Wurster, Kathryn E.; Riley, Christopher J.; Zoby, E. Vincent

1998-01-01

Design of the thermal protection system for any hypersonic flight vehicle requires determination of both the peak temperatures over the surface and the heating-rate history along the flight profile. In this paper, the process used to generate the aerothermal environments required for the X-34 Testbed Technology Demonstrator thermal protection system design is described as it has evolved from a relatively simplistic approach based on engineering methods applied to critical areas to one of detailed analyses over the entire vehicle. A brief description of the trajectory development leading to the selection of the thermal protection system design trajectory is included. Comparisons of engineering heating predictions with wind-tunnel test data and with results obtained using a Navier-Stokes flowfield code and an inviscid/boundary layer method are shown. Good agreement is demonstrated among all these methods for both the ground-test condition and the peak heating flight condition. Finally, the detailed analysis using engineering methods to interpolate the surface-heating-rate results from the inviscid/boundary layer method to predict the required thermal environments is described and results presented.

Engineering Aerothermal Analysis for X-34 Thermal Protection System Design

NASA Technical Reports Server (NTRS)

Wurster, Kathryn E.; Riley, Christopher J.; Zoby, E. Vincent

1998-01-01

Design of the thermal protection system for any hypersonic flight vehicle requires determination of both the peak temperatures over the surface and the heating-rate history along the flight profile. In this paper, the process used to generate the aerothermal environments required for the X-34 Testbed Technology Demonstrator thermal protection system design is described as it has evolved from a relatively simplistic approach based on engineering methods applied to critical areas to one of detailed analyses over the entire vehicle. A brief description of the trajectory development leading to the selection of the thermal protection system design trajectory is included. Comparisons of engineering heating predictions with wind-tunnel test data and with results obtained using a Navier- Stokes flowfield code and an inviscid/boundary layer method are shown. Good agreement is demonstrated among all these methods for both the ground-test condition and the peak heating flight condition. Finally, the detailed analysis using engineering methods to interpolate the surface-heating-rate results from the inviscid/boundary layer method to predict the required thermal environments is described and results presented.

Rocket Engine Nozzle Side Load Transient Analysis Methodology: A Practical Approach

NASA Technical Reports Server (NTRS)

Shi, John J.

2005-01-01

During the development stage, in order to design/to size the rocket engine components and to reduce the risks, the local dynamic environments as well as dynamic interface loads must be defined. There are two kinds of dynamic environment, i.e. shock transients and steady-state random and sinusoidal vibration environments. Usually, the steady-state random and sinusoidal vibration environments are scalable, but the shock environments are not scalable. In other words, based on similarities only random vibration environments can be defined for a new engine. The methodology covered in this paper provides a way to predict the shock environments and the dynamic loads for new engine systems and new engine components in the early stage of new engine development or engine nozzle modifications.

Root Systems of Individual Plants, and the Biotic and Abiotic Factors Controlling Their Depth and Distribution: a Synthesis Using a Global Database.

NASA Astrophysics Data System (ADS)

Tumber-Davila, S. J.; Schenk, H. J.; Jackson, R. B.

2017-12-01

This synthesis examines plant rooting distributions globally, by doubling the number of entries in the Root Systems of Individual Plants database (RSIP) created by Schenk and Jackson. Root systems influence many processes, including water and nutrient uptake and soil carbon storage. Root systems also mediate vegetation responses to changing climatic and environmental conditions. Therefore, a collective understanding of the importance of rooting systems to carbon sequestration, soil characteristics, hydrology, and climate, is needed. Current global models are limited by a poor understanding of the mechanisms affecting rooting, carbon stocks, and belowground biomass. This improved database contains an extensive bank of records describing the rooting system of individual plants, as well as detailed information on the climate and environment from which the observations are made. The expanded RSIP database will: 1) increase our understanding of rooting depths, lateral root spreads and above and belowground allometry; 2) improve the representation of plant rooting systems in Earth System Models; 3) enable studies of how climate change will alter and interact with plant species and functional groups in the future. We further focus on how plant rooting behavior responds to variations in climate and the environment, and create a model that can predict rooting behavior given a set of environmental conditions. Preliminary results suggest that high potential evapotranspiration and seasonality of precipitation are indicative of deeper rooting after accounting for plant growth form. When mapping predicted deep rooting by climate, we predict deepest rooting to occur in equatorial South America, Africa, and central India.

Predicting combined sewer overflows chamber depth using artificial neural networks with rainfall radar data.

PubMed

Mounce, S R; Shepherd, W; Sailor, G; Shucksmith, J; Saul, A J

2014-01-01

Combined sewer overflows (CSOs) represent a common feature in combined urban drainage systems and are used to discharge excess water to the environment during heavy storms. To better understand the performance of CSOs, the UK water industry has installed a large number of monitoring systems that provide data for these assets. This paper presents research into the prediction of the hydraulic performance of CSOs using artificial neural networks (ANN) as an alternative to hydraulic models. Previous work has explored using an ANN model for the prediction of chamber depth using time series for depth and rain gauge data. Rainfall intensity data that can be provided by rainfall radar devices can be used to improve on this approach. Results are presented using real data from a CSO for a catchment in the North of England, UK. An ANN model trained with the pseudo-inverse rule was shown to be capable of predicting CSO depth with less than 5% error for predictions more than 1 hour ahead for unseen data. Such predictive approaches are important to the future management of combined sewer systems.

Modeling the prediction of business intelligence system effectiveness.

PubMed

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

2016-01-01

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

Forecasting Electric Power Generation of Photovoltaic Power System for Energy Network

NASA Astrophysics Data System (ADS)

Kudo, Mitsuru; Takeuchi, Akira; Nozaki, Yousuke; Endo, Hisahito; Sumita, Jiro

Recently, there has been an increase in concern about the global environment. Interest is growing in developing an energy network by which new energy systems such as photovoltaic and fuel cells generate power locally and electric power and heat are controlled with a communications network. We developed the power generation forecast method for photovoltaic power systems in an energy network. The method makes use of weather information and regression analysis. We carried out forecasting power output of the photovoltaic power system installed in Expo 2005, Aichi Japan. As a result of comparing measurements with a prediction values, the average prediction error per day was about 26% of the measured power.

Assessing the vulnerability of traditional maize seed systems in Mexico to climate change

PubMed Central

Bellon, Mauricio R.; Hodson, David; Hellin, Jon

2011-01-01

Climate change is predicted to have major impacts on small-scale farmers in Mexico whose livelihoods depend on rain-fed maize. We examined the capacity of traditional maize seed systems to provide these farmers with appropriate genetic material under predicted agro-ecological conditions associated with climate change. We studied the structure and spatial scope of seed systems of 20 communities in four transects across an altitudinal gradient from 10–2,980 m above sea level in five states of eastern Mexico. Results indicate that 90% of all of the seed lots are obtained within 10 km of a community and 87% within an altitudinal range of ±50 m but with variation across four agro-climate environments: wet lowland, dry lowland, wet upper midlatitude, and highlands. Climate models suggest a drying and warming trend for the entire study area during the main maize season, leading to substantial shifts in the spatial distribution patterns of agro-climate environments. For all communities except those in the highlands, predicted future maize environments already are represented within the 10-km radial zones, indicating that in the future farmers will have easy access to adapted planting material. Farmers in the highlands are the most vulnerable and probably will need to acquire seed from outside their traditional geographical ranges. This change in seed sources probably will entail important information costs and the development of new seed and associated social networks, including improved linkages between traditional and formal seed systems and more effective and efficient seed-supply chains. The study has implications for analogous areas elsewhere in Mexico and around the world. PMID:21825131

Simulating social-ecological systems: the Island Digital Ecosystem Avatars (IDEA) consortium.

PubMed

Davies, Neil; Field, Dawn; Gavaghan, David; Holbrook, Sally J; Planes, Serge; Troyer, Matthias; Bonsall, Michael; Claudet, Joachim; Roderick, George; Schmitt, Russell J; Zettler, Linda Amaral; Berteaux, Véronique; Bossin, Hervé C; Cabasse, Charlotte; Collin, Antoine; Deck, John; Dell, Tony; Dunne, Jennifer; Gates, Ruth; Harfoot, Mike; Hench, James L; Hopuare, Marania; Kirch, Patrick; Kotoulas, Georgios; Kosenkov, Alex; Kusenko, Alex; Leichter, James J; Lenihan, Hunter; Magoulas, Antonios; Martinez, Neo; Meyer, Chris; Stoll, Benoit; Swalla, Billie; Tartakovsky, Daniel M; Murphy, Hinano Teavai; Turyshev, Slava; Valdvinos, Fernanda; Williams, Rich; Wood, Spencer

2016-01-01

Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine-terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions.

Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

PubMed

Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

2016-05-01

In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Reverse Ecology: from systems to environments and back.

PubMed

Levy, Roie; Borenstein, Elhanan

2012-01-01

The structure of complex biological systems reflects not only their function but also the environments in which they evolved and are adapted to. Reverse Ecology-an emerging new frontier in Evolutionary Systems Biology-aims to extract this information and to obtain novel insights into an organism's ecology. The Reverse Ecology framework facilitates the translation of high-throughput genomic data into large-scale ecological data, and has the potential to transform ecology into a high-throughput field. In this chapter, we describe some of the pioneering work in Reverse Ecology, demonstrating how system-level analysis of complex biological networks can be used to predict the natural habitats of poorly characterized microbial species, their interactions with other species, and universal patterns governing the adaptation of organisms to their environments. We further present several studies that applied Reverse Ecology to elucidate various aspects of microbial ecology, and lay out exciting future directions and potential future applications in biotechnology, biomedicine, and ecological engineering.

The Scientific Committee on Antarctic Research (SCAR) in the IPY 2007-2009

NASA Astrophysics Data System (ADS)

Kennicutt, M. C.; Wilson, T. J.; Summerhayes, C.

2005-05-01

The Scientific Committee on Antarctic Research (SCAR) initiates, develops, and coordinates international scientific research in the Antarctic region. SCAR is assuming a leadership position in the IPY primarily through its five major Scientific Research Programs; ACE, SALE, EBA, AGCS, and ICESTAR; which will be briefly described.Antarctic Climate Evolution (ACE) promotes the exchange of data and ideas between research groups focusing on the evolution of Antarctica's climate system and ice sheet. The program will: (1) quantitatively assess the climate and glacial history of Antarctica; (2) identify the processes which govern Antarctic change and feed back around the globe; (3) improve our ability to model past changes in Antarctica; and (4)document past change to predict future change in Antarctica. Subglacial Antarctic Lake Environments (SALE) promotes, facilitates, and champions cooperation and collaboration in the exploration and study of subglacial environments in Antarctica. SALE intends to understand the complex interplay of biological, geological, chemical, glaciological, and physical processes within subglacial lake environments through coordinated international research teams. Evolution and Biodiversity in the Antarctic (EBA) will use a suite of modern techniques and interdisciplinary approaches, to explore the evolutionary history of selected modern Antarctic biota, examine how modern biological diversity in the Antarctic influences the way present-day ecosystems function, and thereby predict how the biota may respond to future environmental change. Antarctica and the Global Climate System (AGCS) will investigate the nature of the atmospheric and oceanic linkages between the climate of the Antarctic and the rest of the Earth system, and the mechanisms involved therein. A combination of modern instrumented records of atmospheric and oceanic conditions, and the climate signals held within ice cores will be used to understand past and future climate variability and change in the Antarctic as a result of natural and anthropogenic forcings over the last 100,000 years. Interhemispheric Conjugacy Effects in Solar-Terrestrial and Aeronomy Research (ICESTAR) will study the interactions between and collective behavior of the many component parts of the Earth system, including the interaction between the natural environment and human society. Objectives include specification and prediction of the state of the system and assimilation and integration of data from disparate sources to understand the complex geospace environment.

A New Mechanism for a Brain

ERIC Educational Resources Information Center

Andreae, John H.; Cleary, John G.

1976-01-01

The new mechanism, PUSS, enables experience of any complex environment to be accumulated in a predictive model. PURR-PUSS is a teachable robot system based on the new mechanism. Cumulative learning is demonstrated by a detailed example. (Author)

Personality, perceived environment, and behavior systems related to future smoking intentions among youths: an application of problem-behavior theory in Shanghai, China.

PubMed

Cai, Yong; Li, Rui; Zhu, Jingfen; Na, Li; He, Yaping; Redmon, Pam; Qiao, Yun; Ma, Jin

2015-01-01

Smoking among youths is a worldwide problem, particularly in China. Many endogenous and environmental factors influence smokers' intentions to smoke; therefore, a comprehensive model is needed to understand the significance and relationship of predictors. This study aimed to develop a prediction model based on problem-behavior theory (PBT) to interpret intentions to smoke among Chinese youths. We conducted a cross-sectional study of 26,675 adolescents from junior, senior, and vocational high schools in Shanghai, China. Data on smoking status, smoking knowledge, attitude toward smoking, parents' and peers' smoking, and media exposure to smoking were collected from students. A structural equation model was used to assess the developed prediction model. The experimental smoking rate and current smoking rate among the students were 11.0% and 3%, respectively. Our constructed model showed an acceptable fit to the data (comparative fit index = 0.987, root-mean-square error of approximation = 0.034). Intention to smoke was predicted by perceived environment (β = 0.455, P < 0.001) system consisting of peer smoking (β = 0.599, P < 0.001), parent smoking (β = 0.152, P < 0.001), and media exposure to smoking (β = 0.226, P < 0.001), and behavior system (β = 0.487, P < 0.001) consisting of tobacco experimentation (β = 0.663, P < 0.001) and current smoking (β = 0.755, P < 0.001). Smoking intention was irrelevant for personality system in students (β = -0.113, P>0.05) which consisted of acceptance of tobacco use (β = 0.668, P < 0.001) and academic performance (β = 0.171, P < 0.001). The PBT-based model we developed provides a good understanding of the predictors of intentions to smoke and it suggests future interventions among youths should focus on components in perceived environment and behavior systems, and take into account the moderating effects of personality system.

Damage prognosis: the future of structural health monitoring.

PubMed

Farrar, Charles R; Lieven, Nick A J

2007-02-15

This paper concludes the theme issue on structural health monitoring (SHM) by discussing the concept of damage prognosis (DP). DP attempts to forecast system performance by assessing the current damage state of the system (i.e. SHM), estimating the future loading environments for that system, and predicting through simulation and past experience the remaining useful life of the system. The successful development of a DP capability will require the further development and integration of many technology areas including both measurement/processing/telemetry hardware and a variety of deterministic and probabilistic predictive modelling capabilities, as well as the ability to quantify the uncertainty in these predictions. The multidisciplinary and challenging nature of the DP problem, its current embryonic state of development, and its tremendous potential for life-safety and economic benefits qualify DP as a 'grand challenge' problem for engineers in the twenty-first century.

Estimating the Reliability of Electronic Parts in High Radiation Fields

NASA Technical Reports Server (NTRS)

Everline, Chester; Clark, Karla; Man, Guy; Rasmussen, Robert; Johnston, Allan; Kohlhase, Charles; Paulos, Todd

2008-01-01

Radiation effects on materials and electronic parts constrain the lifetime of flight systems visiting Europa. Understanding mission lifetime limits is critical to the design and planning of such a mission. Therefore, the operational aspects of radiation dose are a mission success issue. To predict and manage mission lifetime in a high radiation environment, system engineers need capable tools to trade radiation design choices against system design and reliability, and science achievements. Conventional tools and approaches provided past missions with conservative designs without the ability to predict their lifetime beyond the baseline mission.This paper describes a more systematic approach to understanding spacecraft design margin, allowing better prediction of spacecraft lifetime. This is possible because of newly available electronic parts radiation effects statistics and an enhanced spacecraft system reliability methodology. This new approach can be used in conjunction with traditional approaches for mission design. This paper describes the fundamentals of the new methodology.

Model predictive control of non-linear systems over networks with data quantization and packet loss.

PubMed

Yu, Jimin; Nan, Liangsheng; Tang, Xiaoming; Wang, Ping

2015-11-01

This paper studies the approach of model predictive control (MPC) for the non-linear systems under networked environment where both data quantization and packet loss may occur. The non-linear controlled plant in the networked control system (NCS) is represented by a Tagaki-Sugeno (T-S) model. The sensed data and control signal are quantized in both links and described as sector bound uncertainties by applying sector bound approach. Then, the quantized data are transmitted in the communication networks and may suffer from the effect of packet losses, which are modeled as Bernoulli process. A fuzzy predictive controller which guarantees the stability of the closed-loop system is obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Welcome to NASA's Earth Science Enterprise: Educational CD-ROM Activity Supplement

NASA Technical Reports Server (NTRS)

1999-01-01

Since its inception in 1958, NASA has been studying the Earth and its changing environment by observing the atmosphere, oceans, land, ice, and snow, and their influence on weather and climate. We now understand that the key to gaining a better understanding of the global environment is exploring how the Earth's systems of air, land, water, and life interact with each other. This approach-called Earth Systems Science-blends together fields like meteorology, oceanography, geology, and biology. In 1991, NASA launched a more comprehensive program to study the Earth as an integrated environmental system. They call it NASA's Earth Science Enterprise. A major component of the Earth Science Enterprise is the Earth Observing System (EOS). EOS is series of satellites to be launched over the next two decades that will be used to intensively study the Earth, with the hopes of expanding our under- standing of how natural processes affect us, and how we might be affecting them. Such studies will yield improved weather forecasts, tools for managing agriculture and forests, information for fishermen and local planners, and, eventually, the ability to predict how the climate will change in the future. Today's program is laying the foundation for long-term environmental and climate monitoring and prediction. Potentially, this will provide the understanding needed in the future to support difficult decisions regarding the Earth's environment.

Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance

PubMed Central

Bokulich, Nicholas A; Bergsveinson, Jordyn; Ziola, Barry; Mills, David A

2015-01-01

Distinct microbial ecosystems have evolved to meet the challenges of indoor environments, shaping the microbial communities that interact most with modern human activities. Microbial transmission in food-processing facilities has an enormous impact on the qualities and healthfulness of foods, beneficially or detrimentally interacting with food products. To explore modes of microbial transmission and spoilage-gene frequency in a commercial food-production scenario, we profiled hop-resistance gene frequencies and bacterial and fungal communities in a brewery. We employed a Bayesian approach for predicting routes of contamination, revealing critical control points for microbial management. Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment. Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk. Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments. DOI: http://dx.doi.org/10.7554/eLife.04634.001 PMID:25756611

SSME lifetime prediction and verification, integrating environments, structures, materials: The challenge

NASA Technical Reports Server (NTRS)

Ryan, R. S.; Salter, L. D.; Young, G. M., III; Munafo, P. M.

1985-01-01

The planned missions for the space shuttle dictated a unique and technology-extending rocket engine. The high specific impulse requirements in conjunction with a 55-mission lifetime, plus volume and weight constraints, produced unique structural design, manufacturing, and verification requirements. Operations from Earth to orbit produce severe dynamic environments, which couple with the extreme pressure and thermal environments associated with the high performance, creating large low cycle loads and high alternating stresses above endurance limit which result in high sensitivity to alternating stresses. Combining all of these effects resulted in the requirements for exotic materials, which are more susceptible to manufacturing problems, and the use of an all-welded structure. The challenge of integrating environments, dynamics, structures, and materials into a verified SSME structure is discussed. The verification program and developmental flight results are included. The first six shuttle flights had engine performance as predicted with no failures. The engine system has met the basic design challenges.

The UKC2 regional coupled prediction system

NASA Astrophysics Data System (ADS)

Castillo, Juan; Lewis, Huw; Graham, Jennifer; Saulter, Andrew; Arnold, Alex; Fallmann, Joachim; Martinez de la Torre, Alberto; Blyth, Eleanor; Bricheno, Lucy

2017-04-01

It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather through the environment, requires a more integrated approach to forecasting. This approach also delivers research benefits through providing tools with which to explore the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land. This hypothesis is being tested in a UK regional context at km-scale through the UK Environmental Prediction Project. This presentation will provide an introduction to the UKC2 UK Environmental Prediction research system. This incorporates models of the atmosphere (Met Office Unified Model), land surface (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled (via OASIS3-MCT libraries) at unprecedentedly high resolution across the UK and the wider north-west European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a unique new research tool for UK environmental science. The presentation will highlight work undertaken to review and improve the computational cost of running these systems for efficient research application. Research will be presented highlighting case study evaluation on the sensitivity of the ocean and surface waves to the representation of feedbacks to the atmosphere, and on the sensitivity of weather systems and boundary layer cloud development to the exchange of heat and momentum at the ocean surface modified through sea surface temperature and wave-induced roughness. The presentation will discuss plans for future development through UKC3 and beyond.

Predicted persistence and response times of linear and cyclic volatile methylsiloxanes in global and local environments.

PubMed

Kim, Jaeshin; Mackay, Donald; Whelan, Michael John

2018-03-01

We investigated the response times of eight volatile methylsiloxanes (VMSs) in environmental systems at different scales from local to global, with a particular focus on overall loss rates after cessation of emissions. In part, this is driven by proposals to restrict the use of some of these compounds in certain products in Europe. The GloboPOP model estimated low absolute Arctic Contamination Potentials for all VMSs and rapid response times in all media except sediment. VMSs are predicted to be distributed predominantly in air where they react with OH radicals, leading to short response times. After cessation of emissions VMSs concentrations in the environment are expected to decrease rapidly from current levels. Response times in specific water and sediment systems were evaluated using a dynamic QWASI model. Response times were sensitive to both physico-chemical properties and environmental characteristics. Degradation was predicted to play the most important role in determining response times in water and sediment. In the case of the lowest molecular weight VMSs such as L2 and D3, response times were essentially independent of environmental characteristics due to fast hydrolysis in water and sediment. However, response times for the other VMSs are system-specific. They are relatively short in shallow water bodies but increase with depth due to the diminishing role of volatilization on concentration change as volume to surface area ratio increases. In sediment, degradation and resuspension rates also contribute most to the response times. The estimated response times for local environments are useful for planning future monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

NASA Technical Reports Server (NTRS)

Suarez, Vicente J.; Lewandowski, Edward J.; Callahan, John

2006-01-01

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical RPS launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources was designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

Predicting the Overall Spatial Quality of Automotive Audio Systems

NASA Astrophysics Data System (ADS)

Koya, Daisuke

The spatial quality of automotive audio systems is often compromised due to their unideal listening environments. Automotive audio systems need to be developed quickly due to industry demands. A suitable perceptual model could evaluate the spatial quality of automotive audio systems with similar reliability to formal listening tests but take less time. Such a model is developed in this research project by adapting an existing model of spatial quality for automotive audio use. The requirements for the adaptation were investigated in a literature review. A perceptual model called QESTRAL was reviewed, which predicts the overall spatial quality of domestic multichannel audio systems. It was determined that automotive audio systems are likely to be impaired in terms of the spatial attributes that were not considered in developing the QESTRAL model, but metrics are available that might predict these attributes. To establish whether the QESTRAL model in its current form can accurately predict the overall spatial quality of automotive audio systems, MUSHRA listening tests using headphone auralisation with head tracking were conducted to collect results to be compared against predictions by the model. Based on guideline criteria, the model in its current form could not accurately predict the overall spatial quality of automotive audio systems. To improve prediction performance, the QESTRAL model was recalibrated and modified using existing metrics of the model, those that were proposed from the literature review, and newly developed metrics. The most important metrics for predicting the overall spatial quality of automotive audio systems included those that were interaural cross-correlation (IACC) based, relate to localisation of the frontal audio scene, and account for the perceived scene width in front of the listener. Modifying the model for automotive audio systems did not invalidate its use for domestic audio systems. The resulting model predicts the overall spatial quality of 2- and 5-channel automotive audio systems with a cross-validation performance of R. 2 = 0.85 and root-mean-squareerror (RMSE) = 11.03%.

Evolution of Bacterial Suicide

NASA Astrophysics Data System (ADS)

Tchernookov, Martin; Nemenman, Ilya

2013-03-01

While active, controlled cellular suicide (autolysis) in bacteria is commonly observed, it has been hard to argue that autolysis can be beneficial to an individual who commits it. We propose a theoretical model that predicts that bacterial autolysis is evolutionarily advantageous to an individualand would fixate in physically structured environments for stationary phase colonies. We perform spatially resolved agent-based simulations of the model, which predict that lower mixing in the environment results in fixation of a higher autolysis rate from a single mutated cell, regardless of the colony's genetic diversity. We argue that quorum sensing will fixate as well, even if initially rare, if it is coupled to controlling the autolysis rate. The model does not predict a strong additional competitive advantage for cells where autolysis is controlled by quorum sensing systems that distinguish self from nonself. These predictions are broadly supported by recent experimental results in B. subtilisand S. pneumoniae. Research partially supported by the James S McDonnell Foundation grant No. 220020321 and by HFSP grant No. RGY0084/2011.

In Silico Models for Ecotoxicity of Pharmaceuticals.

PubMed

Roy, Kunal; Kar, Supratik

2016-01-01

Pharmaceuticals and their active metabolites are one of the significantly emerging environmental toxicants. The major routes of entry of pharmaceuticals into the environment are industries, hospitals, or direct disposal of unwanted or expired drugs made by the patient. The most important and distinct features of pharmaceuticals are that they are deliberately designed to have an explicit mode of action and designed to exert an effect on humans and other living systems. This distinctive feature makes pharmaceuticals and their metabolites different from other chemicals, and this necessitates the evaluation of the direct effects of pharmaceuticals in various environmental compartments as well as to living systems. In this background, the alarming situation of ecotoxicity of diverse pharmaceuticals have forced government and nongovernment regulatory authorities to recommend the application of in silico methods to provide quick information about the risk assessment and fate properties of pharmaceuticals as well as their ecological and indirect human health effects. This chapter aims to offer information regarding occurrence of pharmaceuticals in the environment, their persistence, environmental fate, and toxicity as well as application of in silico methods to provide information about the basic risk management and fate prediction of pharmaceuticals in the environment. Brief ideas about toxicity endpoints, available ecotoxicity databases, and expert systems employed for rapid toxicity predictions of ecotoxicity of pharmaceuticals are also discussed.

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.

An energy-economy-environment model for simulating the impacts of socioeconomic development on energy and environment.

PubMed

Wang, Wenyi; Zeng, Weihua; Yao, Bo

2014-01-01

Many rapidly developing regions have begun to draw the attention of the world. Meanwhile, the energy and environmental issues associated with rapid economic growth have aroused widespread critical concern. Therefore, studying energy, economic, and environmental systems is of great importance. This study establishes a system dynamic model that covers multiple aspects of those systems, such as energy, economy, population, water pollution, air pollution, solid waste, and technology. The model designed here attempts to determine the impacts of socioeconomic development on the energy and environment of Tongzhou District in three scenarios: under current, planning, and sustainable conditions. The results reveal that energy shortages and water pollutions are very serious and are the key issues constraining future social and economic development. Solid waste emissions increase with population growth. The prediction results provide valuable insights into social advancement.

Neuromechanics of crawling in D. melanogaster larvae

NASA Astrophysics Data System (ADS)

Pehlevan, Cengiz; Paoletti, Paolo; Mahadevan, L.

2015-03-01

Nervous system, body and environment interact in non-trivial ways to generate locomotion and thence behavior in an organism. Here we present a minimal integrative mathematical model to describe the simple behavior of forward crawling in Drosophila larvae. Our model couples the excitation-inhibition circuits in the nervous system to force production in the muscles and body movement in a frictional environment, which in turn leads to a proprioceptive signal that feeds back to the nervous system. Our results explain the basic observed phenomenology of crawling with or without proprioception, and elucidate the stabilizing role of proprioception in crawling with respect to external and internal perturbations. Our integrated approach allows us to make testable predictions on the effect of changing body-environment interactions on crawling, and serves as a substrate for the development of hierarchical models linking cellular processes to behavior.

Harpoon Pyrotechnic Shock Study

DTIC Science & Technology

1979-09-01

Air Systems Command, was performed from July 1973 to July 1979. In the Interest of economy and timeliness in presenting the information, the report is...Both actual test data and predicted shock levey are presented. .L{U’Shock spectra environment predictions are made for several types of explosive ...mounting structure 5 to 10 inches (127 to 254 mm) from the explosive device. Attenuation across the component mounting interface is the only loss

Revolutionize Situational Awareness in Emergencies

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

Hehlen, Markus Peter

This report describes an integrated system that provides real-time actionable information to first responders. LANL will integrate three technologies to form an advanced predictive real-time sensor network including compact chemical and wind sensor sin low cost rugged package for outdoor installation; flexible robust communication architecture linking sensors in near-real time to globally accessible servers; and the QUIC code which predicts contamination transport and dispersal in urban environments in near real time.

Determining the potential productivity of food crops in controlled environments

NASA Technical Reports Server (NTRS)

Bugbee, Bruce

1992-01-01

The quest to determine the maximum potential productivity of food crops is greatly benefitted by crop growth models. Many models have been developed to analyze and predict crop growth in the field, but it is difficult to predict biological responses to stress conditions. Crop growth models for the optimal environments of a Controlled Environment Life Support System (CELSS) can be highly predictive. This paper discusses the application of a crop growth model to CELSS; the model is used to evaluate factors limiting growth. The model separately evaluates the following four physiological processes: absorption of PPF by photosynthetic tissue, carbon fixation (photosynthesis), carbon use (respiration), and carbon partitioning (harvest index). These constituent processes determine potentially achievable productivity. An analysis of each process suggests that low harvest index is the factor most limiting to yield. PPF absorption by plant canopies and respiration efficiency are also of major importance. Research concerning productivity in a CELSS should emphasize: (1) the development of gas exchange techniques to continuously monitor plant growth rates and (2) environmental techniques to reduce plant height in communities.

A cluster expansion model for predicting activation barrier of atomic processes

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

Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit, E-mail: achatter@iitk.ac.in

2013-06-15

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEBmore » results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.« less

Predicting Fatigue and Psychophysiological Test Performance from Speech for Safety-Critical Environments.

PubMed

Baykaner, Khan Richard; Huckvale, Mark; Whiteley, Iya; Andreeva, Svetlana; Ryumin, Oleg

2015-01-01

Automatic systems for estimating operator fatigue have application in safety-critical environments. A system which could estimate level of fatigue from speech would have application in domains where operators engage in regular verbal communication as part of their duties. Previous studies on the prediction of fatigue from speech have been limited because of their reliance on subjective ratings and because they lack comparison to other methods for assessing fatigue. In this paper, we present an analysis of voice recordings and psychophysiological test scores collected from seven aerospace personnel during a training task in which they remained awake for 60 h. We show that voice features and test scores are affected by both the total time spent awake and the time position within each subject's circadian cycle. However, we show that time spent awake and time-of-day information are poor predictors of the test results, while voice features can give good predictions of the psychophysiological test scores and sleep latency. Mean absolute errors of prediction are possible within about 17.5% for sleep latency and 5-12% for test scores. We discuss the implications for the use of voice as a means to monitor the effects of fatigue on cognitive performance in practical applications.

Predicting Fatigue and Psychophysiological Test Performance from Speech for Safety-Critical Environments

PubMed Central

Baykaner, Khan Richard; Huckvale, Mark; Whiteley, Iya; Andreeva, Svetlana; Ryumin, Oleg

2015-01-01

Automatic systems for estimating operator fatigue have application in safety-critical environments. A system which could estimate level of fatigue from speech would have application in domains where operators engage in regular verbal communication as part of their duties. Previous studies on the prediction of fatigue from speech have been limited because of their reliance on subjective ratings and because they lack comparison to other methods for assessing fatigue. In this paper, we present an analysis of voice recordings and psychophysiological test scores collected from seven aerospace personnel during a training task in which they remained awake for 60 h. We show that voice features and test scores are affected by both the total time spent awake and the time position within each subject’s circadian cycle. However, we show that time spent awake and time-of-day information are poor predictors of the test results, while voice features can give good predictions of the psychophysiological test scores and sleep latency. Mean absolute errors of prediction are possible within about 17.5% for sleep latency and 5–12% for test scores. We discuss the implications for the use of voice as a means to monitor the effects of fatigue on cognitive performance in practical applications. PMID:26380259

Orbiter Boundary Layer Transition Prediction Tool Enhancements

NASA Technical Reports Server (NTRS)

Berry, Scott A.; King, Rudolph A.; Kegerise, Michael A.; Wood, William A.; McGinley, Catherine B.; Berger, Karen T.; Anderson, Brian P.

2010-01-01

Updates to an analytic tool developed for Shuttle support to predict the onset of boundary layer transition resulting from thermal protection system damage or repair are presented. The boundary layer transition tool is part of a suite of tools that analyze the local aerothermodynamic environment to enable informed disposition of damage for making recommendations to fly as is or to repair. Using mission specific trajectory information and details of each d agmea site or repair, the expected time (and thus Mach number) of transition onset is predicted to help define proper environments for use in subsequent thermal and stress analysis of the thermal protection system and structure. The boundary layer transition criteria utilized within the tool were updated based on new local boundary layer properties obtained from high fidelity computational solutions. Also, new ground-based measurements were obtained to allow for a wider parametric variation with both protuberances and cavities and then the resulting correlations were calibrated against updated flight data. The end result is to provide correlations that allow increased confidence with the resulting transition predictions. Recently, a new approach was adopted to remove conservatism in terms of sustained turbulence along the wing leading edge. Finally, some of the newer flight data are also discussed in terms of how these results reflect back on the updated correlations.

Physics-based statistical model and simulation method of RF propagation in urban environments

DOEpatents

Pao, Hsueh-Yuan; Dvorak, Steven L.

2010-09-14

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

Adverse Childhood Environment: Relationship With Sexual Risk Behaviors and Marital Status in a Large American Sample.

PubMed

Anderson, Kermyt G

2017-01-01

A substantial theoretical and empirical literature suggests that stressful events in childhood influence the timing and patterning of subsequent sexual and reproductive behaviors. Stressful childhood environments have been predicted to produce a life history strategy in which adults are oriented more toward short-term mating behaviors and less toward behaviors consistent with longevity. This article tests the hypothesis that adverse childhood environment will predict adult outcomes in two areas: risky sexual behavior (engagement in sexual risk behavior or having taken an HIV test) and marital status (currently married vs. never married, divorced, or a member of an unmarried couple). Data come from the Behavioral Risk Factor Surveillance System. The sample contains 17,530 men and 23,978 women aged 18-54 years living in 13 U.S. states plus the District of Columbia. Adverse childhood environment is assessed through 11 retrospective measures of childhood environment, including having grown up with someone who was depressed or mentally ill, who was an alcoholic, who used or abused drugs, or who served time in prison; whether one's parents divorced in childhood; and two scales measuring childhood exposure to violence and to sexual trauma. The results indicate that adverse childhood environment is associated with increased likelihood of engaging in sexual risk behaviors or taking an HIV test, and increased likelihood of being in an unmarried couple or divorced/separated, for both men and women. The predictions are supported by the data, lending further support to the hypothesis that childhood environments influence adult reproductive strategy.

Predicting ecological roles in the rhizosphere using metabolome and transportome modeling

DOE PAGES

Larsen, Peter E.; Collart, Frank R.; Dai, Yang; ...

2015-09-02

The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. New algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad’s ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter ofmore » plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism’s transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.« less

Predicting Ecological Roles in the Rhizosphere Using Metabolome and Transportome Modeling

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

Larsen, Peter E.; Collart, Frank R.; Dai, Yang

2015-09-02

The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. However, new algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad's ecological role in the rhizosphere: a biofilm, biocontrol agent, promotermore » of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism's transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.« less

Overview of Boundary Layer Transition Research in Support of Orbiter Return To Flight

NASA Technical Reports Server (NTRS)

Berry, Scott A.; Horvath, Thomas J.; Greene, Francis A.; Kinder, Gerald R.; Wang, K. C.

2006-01-01

A predictive tool for estimating the onset of boundary layer transition resulting from damage to and/or repair of the thermal protection system was developed in support of Shuttle Return to Flight. The boundary layer transition tool is part of a suite of tools that analyze the aerothermodynamic environment to the local thermal protection system to allow informed disposition of damage for making recommendations to fly as is or to repair. Using mission specific trajectory information and details of each damage site or repair, the expected time (and thus Mach number) at transition onset is predicted to help define the aerothermodynamic environment to use in the subsequent thermal and stress analysis of the local thermal protection system and structure. The boundary layer transition criteria utilized for the tool was developed from ground-based measurements to account for the effect of both protuberances and cavities and has been calibrated against select flight data. Computed local boundary layer edge conditions were used to correlate the results, specifically the momentum thickness Reynolds number over the edge Mach number and the boundary layer thickness. For the initial Return to Flight mission, STS-114, empirical curve coefficients of 27, 100, and 900 were selected to predict transition onset for protuberances based on height, and cavities based on depth and length, respectively.

Calibrating a novel multi-sensor physical activity measurement system.

PubMed

John, D; Liu, S; Sasaki, J E; Howe, C A; Staudenmayer, J; Gao, R X; Freedson, P S

2011-09-01

Advancing the field of physical activity (PA) monitoring requires the development of innovative multi-sensor measurement systems that are feasible in the free-living environment. The use of novel analytical techniques to combine and process these multiple sensor signals is equally important. This paper describes a novel multi-sensor 'integrated PA measurement system' (IMS), the lab-based methodology used to calibrate the IMS, techniques used to predict multiple variables from the sensor signals, and proposes design changes to improve the feasibility of deploying the IMS in the free-living environment. The IMS consists of hip and wrist acceleration sensors, two piezoelectric respiration sensors on the torso, and an ultraviolet radiation sensor to obtain contextual information (indoors versus outdoors) of PA. During lab-based calibration of the IMS, data were collected on participants performing a PA routine consisting of seven different ambulatory and free-living activities while wearing a portable metabolic unit (criterion measure) and the IMS. Data analyses on the first 50 adult participants are presented. These analyses were used to determine if the IMS can be used to predict the variables of interest. Finally, physical modifications for the IMS that could enhance the feasibility of free-living use are proposed and refinement of the prediction techniques is discussed.

Prediction of dry ice mass for firefighting robot actuation

NASA Astrophysics Data System (ADS)

Ajala, M. T.; Khan, Md R.; Shafie, A. A.; Salami, MJE; Mohamad Nor, M. I.

2017-11-01

The limitation in the performance of electric actuated firefighting robots in high-temperature fire environment has led to research on the alternative propulsion system for the mobility of firefighting robots in such environment. Capitalizing on the limitations of these electric actuators we suggested a gas-actuated propulsion system in our earlier study. The propulsion system is made up of a pneumatic motor as the actuator (for the robot) and carbon dioxide gas (self-generated from dry ice) as the power source. To satisfy the consumption requirement (9cfm) of the motor for efficient actuation of the robot in the fire environment, the volume of carbon dioxide gas, as well as the corresponding mass of the dry ice that will produce the required volume for powering and actuation of the robot, must be determined. This article, therefore, presents the computational analysis to predict the volumetric requirement and the dry ice mass sufficient to power a carbon dioxide gas propelled autonomous firefighting robot in a high-temperature environment. The governing equation of the sublimation of dry ice to carbon dioxide is established. An operating time of 2105.53s and operating pressure ranges from 137.9kPa to 482.65kPa were achieved following the consumption rate of the motor. Thus, 8.85m3 is computed as the volume requirement of the CAFFR while the corresponding dry ice mass for the CAFFR actuation ranges from 21.67kg to 75.83kg depending on the operating pressure.

Aeroheating Environments for a Mars Smart Lander

NASA Technical Reports Server (NTRS)

Edquist, Karl T.; Liechty, Derek S.; Hollis, Brian R.; Alter, Stephen J.; Loomis, Mark P.

2002-01-01

A proposed Mars Smart Lander is designed to reach the surface via lifting-body atmospheric entry (alpha = 16 deg) to within 10 km of the target site. CFD (computational fluid dynamics) predictions of the forebody aeroheating environments are given for a direct entry from a 2005 launch. The solutions were obtained using an 8-species gas in thermal and chemical nonequilibrium with a radiative-equilibrium wall temperature boundary condition. Select wind tunnel data are presented from tests at NASA Langley Research Center. Turbulence effects are included to account for both smooth body transition and turbulence due to heatshield penetrations. Natural transition is based on a momentum-thickness Reynolds number value of 200. The effects of heatshield penetrations on turbulence are estimated from wind tunnel tests of various cavity sizes and locations. Both natural transition and heatshield penetrations are predicted to cause turbulence prior to the nominal trajectory peak heating time. Laminar and turbulent CFD predictions along the trajectory are used to estimate heat rates and loads. The predicted peak turbulent heat rate of 63 W/sq cm on the heatshield leeward flank is 70% higher than the laminar peak. The maximum integrated heat load for a fully turbulent heat pulse is 38% higher than the laminar load on the heatshield nose. The predicted aeroheating environments with uncertainty factors will be used to design a thermal protection system.

The environment workbench: A design tool for Space Station Freedom

NASA Technical Reports Server (NTRS)

Jongeward, Gary A.; Kuharski, Robert A.; Rankin, Thomas V.; Wilcox, Katherine G.; Roche, James C.

1991-01-01

The environment workbench (EWB) is being developed for NASA by S-CUBED to provide a standard tool that can be used by the Space Station Freedom (SSF) design and user community for requirements verification. The desktop tool will predict and analyze the interactions of SSF with its natural and self-generated environments. A brief review of the EWB design and capabilities is presented. Calculations using a prototype EWB of the on-orbit floating potentials and contaminant environment of SSF are also presented. Both the positive and negative grounding configurations for the solar arrays are examined to demonstrate the capability of the EWB to provide quick estimates of environments, interactions, and system effects.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

PubMed Central

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-01-01

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348

A Low-Cost Sensor Buoy System for Monitoring Shallow Marine Environments

PubMed Central

Albaladejo, Cristina; Soto, Fulgencio; Torres, Roque; Sánchez, Pedro; López, Juan A.

2012-01-01

Monitoring of marine ecosystems is essential to identify the parameters that determine their condition. The data derived from the sensors used to monitor them are a fundamental source for the development of mathematical models with which to predict the behaviour of conditions of the water, the sea bed and the living creatures inhabiting it. This paper is intended to explain and illustrate a design and implementation for a new multisensor monitoring buoy system. The system design is based on a number of fundamental requirements that set it apart from other recent proposals: low cost of implementation, the possibility of application in coastal shallow-water marine environments, suitable dimensions for deployment and stability of the sensor system in a shifting environment like the sea bed, and total autonomy of power supply and data recording. The buoy system has successfully performed remote monitoring of temperature and marine pressure (SBE 39 sensor), temperature (MCP9700 sensor) and atmospheric pressure (YOUNG 61302L sensor). The above requirements have been satisfactorily validated by operational trials in a marine environment. The proposed buoy sensor system thus seems to offer a broad range of applications. PMID:23012562

Development of dry coal feeders

NASA Technical Reports Server (NTRS)

Bonin, J. H.; Cantey, D. E.; Daniel, A. D., Jr.; Meyer, J. W.

1977-01-01

Design and fabrication of equipment of feed coal into pressurized environments were investigated. Concepts were selected based on feeder system performance and economic projections. These systems include: two approaches using rotating components, a gas or steam driven ejector, and a modified standpipe feeder concept. Results of development testing of critical components, design procedures, and performance prediction techniques are reviewed.

Space and time in ecology: Noise or fundamental driver? [chapter 2

Treesearch

Samuel A. Cushman

2010-01-01

In this chapter I frame the central issue of the book, namely is spatial and temporal complexity in ecological systems merely noise around the predictions of non-spatial, equilibrium processes? Or, alternatively, do spatial and temporal variability in the environment and autogenic space­time processes in populations fundamentally alter system behavior such that ideal...

Analysis of Environmental Stress Factors Using an Artificial Growth System and Plant Fitness Optimization

PubMed Central

Lee, Meonghun; Yoe, Hyun

2015-01-01

The environment promotes evolution. Evolutionary processes represent environmental adaptations over long time scales; evolution of crop genomes is not inducible within the relatively short time span of a human generation. Extreme environmental conditions can accelerate evolution, but such conditions are often stress inducing and disruptive. Artificial growth systems can be used to induce and select genomic variation by changing external environmental conditions, thus, accelerating evolution. By using cloud computing and big-data analysis, we analyzed environmental stress factors for Pleurotus ostreatus by assessing, evaluating, and predicting information of the growth environment. Through the indexing of environmental stress, the growth environment can be precisely controlled and developed into a technology for improving crop quality and production. PMID:25874206

Web-Based Learning Support System

NASA Astrophysics Data System (ADS)

Fan, Lisa

Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

Radiation Effects on Emerging Technologies: Implications of Space Weather Risk Management

NASA Technical Reports Server (NTRS)

LaBel, Kenneth A.; Barth, Janet L.

2000-01-01

As NASA and its space partners endeavor to develop a network of satellites capable of supporting humankind's needs for advanced space weather prediction and understanding, one of the key challenges is to design a space system to operate in the natural space radiation environment In this paper, we present a description of the natural space radiation environment, the effects of interest to electronic or photonic systems, and a sample of emerging technologies and their specific issues. We conclude with a discussion of operations in the space radiation hazard and considerations for risk management.

Plasmonic Landau damping in active environments

NASA Astrophysics Data System (ADS)

Thakkar, Niket; Montoni, Nicholas P.; Cherqui, Charles; Masiello, David J.

2018-03-01

Optical manipulation of charge on the nanoscale is of fundamental importance to an array of proposed technologies from selective photocatalysis to nanophotonics. Open plasmonic systems where collective electron oscillations release energy and charge to their environments offer a potential means to this end as plasmons can rapidly decay into energetic electron-hole pairs; however, isolating this decay from other plasmon-environment interactions remains a challenge. Here we present an analytic theory of noble-metal nanoparticles that quantitatively models plasmon decay into electron-hole pairs, demonstrates that this decay depends significantly on the nanoparticle's dielectric environment, and disentangles this effect from competing decay pathways. Using our approach to incorporate embedding material and substrate effects on plasmon-electron interaction, we show that predictions from the model agree with four separate experiments. Finally, examination of coupled nanoparticle-emitter systems further shows that the hybridized in-phase mode more efficiently decays to photons whereas the out-of-phase mode more efficiently decays to electron-hole pairs, offering a strategy to tailor open plasmonic systems for charge manipulation.

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

Quinn, Heather; Wirthlin, Michael

A variety of fault emulation systems have been created to study the effect of single-event effects (SEEs) in static random access memory (SRAM) based field-programmable gate arrays (FPGAs). These systems are useful for augmenting radiation-hardness assurance (RHA) methodologies for verifying the effectiveness for mitigation techniques; understanding error signatures and failure modes in FPGAs; and failure rate estimation. For radiation effects researchers, it is important that these systems properly emulate how SEEs manifest in FPGAs. If the fault emulation systems does not mimic the radiation environment, the system will generate erroneous data and incorrect predictions of behavior of the FPGA inmore » a radiation environment. Validation determines whether the emulated faults are reasonable analogs to the radiation-induced faults. In this study we present methods for validating fault emulation systems and provide several examples of validated FPGA fault emulation systems.« less

Operational specification and forecasting advances for Dst, LEO thermospheric densities, and aviation radiation dose and dose rate

NASA Astrophysics Data System (ADS)

Tobiska, W.; Knipp, D. J.; Burke, W. J.; Bouwer, D.; Bailey, J. J.; Hagan, M. P.; Didkovsky, L. V.; Garrett, H. B.; Bowman, B. R.; Gannon, J. L.; Atwell, W.; Blake, J. B.; Crain, W.; Rice, D.; Schunk, R. W.; Fulgham, J.; Bell, D.; Gersey, B.; Wilkins, R.; Fuschino, R.; Flynn, C.; Cecil, K.; Mertens, C. J.; Xu, X.; Crowley, G.; Reynolds, A.; Azeem, S. I.; Wiley, S.; Holland, M.; Malone, K.

2013-12-01

Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET's Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the 'weather' of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

Imprints to the terrestrial environment at galactic arm crossings of the solar system

NASA Astrophysics Data System (ADS)

Fahr, H. J.; Fichtner, H.; Scherer, K.; Stawicki, O.

At its itinerary through our milky way galaxy the solar system moves through highly variable interstellar environments. Due to its orbital revolution around the galactic center, the solar system also crosses periodically the spiral arms of our galactic plane and thereby expe riences pronounced enviromental changes. Gas densities, magnetic fields and galactic cosmic ray intensities are substantially higher there compared to interarm conditions. Here we present theoretical calculations describing the SN-averaged galactic cosmic ray spectrum for regions inside and outside of galactic arms which then allow to predict how periodic passages of the solar system through galactic arms should be reflected by enhanced particle irradiations of the earth`s atmosphere and by correlated terrestrial Be-10 production rates.

Analytical modeling of intumescent coating thermal protection system in a JP-5 fuel fire environment

NASA Technical Reports Server (NTRS)

Clark, K. J.; Shimizu, A. B.; Suchsland, K. E.; Moyer, C. B.

1974-01-01

The thermochemical response of Coating 313 when exposed to a fuel fire environment was studied to provide a tool for predicting the reaction time. The existing Aerotherm Charring Material Thermal Response and Ablation (CMA) computer program was modified to treat swelling materials. The modified code is now designated Aerotherm Transient Response of Intumescing Materials (TRIM) code. In addition, thermophysical property data for Coating 313 were analyzed and reduced for use in the TRIM code. An input data sensitivity study was performed, and performance tests of Coating 313/steel substrate models were carried out. The end product is a reliable computational model, the TRIM code, which was thoroughly validated for Coating 313. The tasks reported include: generation of input data, development of swell model and implementation in TRIM code, sensitivity study, acquisition of experimental data, comparisons of predictions with data, and predictions with intermediate insulation.

Shuttle data book: SRM fragment velocity model. Presented to the SRB Fragment Model Review Panel

NASA Technical Reports Server (NTRS)

1989-01-01

This study was undertaken to determine the velocity of fragments generated by the range safety destruction (RSD) or random failure of a Space Transportation System (STS) Solid Rocket Motor (SRM). The specific requirement was to provide a fragment model for use in those Galileo and Ulysses RTG safety analyses concerned with possible fragment impact on the spacecraft radioisotope thermoelectric generators (RTGS). Good agreement was obtained between predictions and observations for fragment velocity, velocity distributions, azimuths, and rotation rates. Based on this agreement with the entire data base, the model was used to predict the probable fragment environments which would occur in the event of an STS-SRM RSD or randon failure at 10, 74, 84 and 110 seconds. The results of these predictions are the basis of the fragment environments presented in the Shuttle Data Book (NSTS-08116). The information presented here is in viewgraph form.

Optimal Prediction in the Retina and Natural Motion Statistics

NASA Astrophysics Data System (ADS)

Salisbury, Jared M.; Palmer, Stephanie E.

2016-03-01

Almost all behaviors involve making predictions. Whether an organism is trying to catch prey, avoid predators, or simply move through a complex environment, the organism uses the data it collects through its senses to guide its actions by extracting from these data information about the future state of the world. A key aspect of the prediction problem is that not all features of the past sensory input have predictive power, and representing all features of the external sensory world is prohibitively costly both due to space and metabolic constraints. This leads to the hypothesis that neural systems are optimized for prediction. Here we describe theoretical and computational efforts to define and quantify the efficient representation of the predictive information by the brain. Another important feature of the prediction problem is that the physics of the world is diverse enough to contain a wide range of possible statistical ensembles, yet not all inputs are probable. Thus, the brain might not be a generalized predictive machine; it might have evolved to specifically solve the prediction problems most common in the natural environment. This paper summarizes recent results on predictive coding and optimal predictive information in the retina and suggests approaches for quantifying prediction in response to natural motion. Basic statistics of natural movies reveal that general patterns of spatiotemporal correlation are present across a wide range of scenes, though individual differences in motion type may be important for optimal processing of motion in a given ecological niche.

An investigation of the performance of an electronic in-line pump system for diesel engines

NASA Astrophysics Data System (ADS)

Fan, Li-Yun; Zhu, Yuan-Xian; Long, Wu-Qiang; Ma, Xiu-Zhen; Xue, Ying-Ying

2008-12-01

WIT Electronic Fuel System Co., Ltd. has developed a new fuel injector, the Electronic In-line Pump (EIP) system, designed to meet China’s diesel engine emission and fuel economy regulations. It can be used on marine diesel engines and commercial vehicle engines through different EIP systems. A numerical model of the EIP system was built in the AMESim environment for the purpose of creating a design tool for engine application and system optimization. The model was used to predict key injection characteristics under different operating conditions, such as injection pressure, injection rate, and injection duration. To validate these predictions, experimental tests were conducted under the conditions that were modeled. The results were quite encouraging and in agreement with model predictions. Additional experiments were conducted to study the injection characteristics of the EIP system. These results show that injection pressure and injection quantity are insensitive to injection timing variations, this is due to the design of the constant velocity cam profile. Finally, injection quantity and pressure vs. pulse width at different cam speeds are presented, an important injection characteristic for EIP system calibration.

Prediction and characterization of application power use in a high-performance computing environment

DOE PAGES

Bugbee, Bruce; Phillips, Caleb; Egan, Hilary; ...

2017-02-27

Power use in data centers and high-performance computing (HPC) facilities has grown in tandem with increases in the size and number of these facilities. Substantial innovation is needed to enable meaningful reduction in energy footprints in leadership-class HPC systems. In this paper, we focus on characterizing and investigating application-level power usage. We demonstrate potential methods for predicting power usage based on a priori and in situ characteristics. Lastly, we highlight a potential use case of this method through a simulated power-aware scheduler using historical jobs from a real scientific HPC system.

Operationalization of Prediction, Hindcast, and Evaluation Systems using the Freie Univ Evaluation System Framework (Freva) incl. a Showcase in Decadal Climate Prediction

NASA Astrophysics Data System (ADS)

Kadow, Christopher; Illing, Sebastian; Schartner, Thomas; Ulbrich, Uwe; Cubasch, Ulrich

2017-04-01

Operationalization processes are important for Weather and Climate Services. Complex data and work flows need to be combined fast to fulfill the needs of service centers. Standards in data and software formats help in automatic solutions. In this study we show a software solution in between hindcasts, forecasts, and validation to be operationalized. Freva (see below) structures data and evaluation procedures and can easily be monitored. Especially in the development process of operationalized services, Freva supports scientists and project partners. The showcase of the decadal climate prediction project MiKlip (fona-miklip.de) shows such a complex development process. Different predictions, scientists input, tasks, and time evolving adjustments need to be combined to host precise climate informations in a web environment without losing track of its evolution. The Freie Univ Evaluation System Framework (Freva - freva.met.fu-berlin.de) is a software infrastructure for standardized data and tool solutions in Earth system science. Freva runs on high performance computers to handle customizable evaluation systems of research projects, institutes or universities. It combines different software technologies into one common hybrid infrastructure, including all features present in the shell and web environment. The database interface satisfies the international standards provided by the Earth System Grid Federation (ESGF). Freva indexes different data projects into one common search environment by storing the meta data information of the self-describing model, reanalysis and observational data sets in a database. This implemented meta data system with its advanced but easy-to-handle search tool supports users, developers and their plugins to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitation of the provision and usage of tools and climate data automatically increases the number of scientists working with the data sets and identifying discrepancies. The integrated webshell (shellinabox) adds a degree of freedom in the choice of the working environment and can be used as a gateto the research projects HPC. Plugins are able to integrate their e.g. post-processed results into the database ofthe user. This allows e.g. post-processing plugins to feed statistical analysis plugins, which fosters an active exchange between plugin developers of a research project. Additionally, the history and configuration sub-system stores every analysis performed with the evaluation system in a database. Configurations and results of the tools can be shared among scientists via shell or web system. Therefore, plugged-in tools benefit from transparency and reproducibility. Furthermore, if configurations match while starting an evaluation plugin, the system suggests to use results already produced by other users - saving CPU/h, I/O, disk space and time. The efficient interaction between different technologies improves the Earth system modeling science framed by Freva.

Prediction of space shuttle fluctuating pressure environments, including rocket plume effects

NASA Technical Reports Server (NTRS)

Plotkin, K. J.; Robertson, J. E.

1973-01-01

Preliminary estimates of space shuttle fluctuating pressure environments have been made based on prediction techniques developed by Wyle Laboratories. Particular emphasis has been given to the transonic speed regime during launch of a parallel-burn space shuttle configuration. A baseline configuration consisting of a lightweight orbiter and monolithic SRB, together with a typical flight trajectory, have been used as models for the predictions. Critical fluctuating pressure environments are predicted at transonic Mach numbers. Comparisons between predicted environments and wind tunnel test results, in general, showed good agreement. Predicted one-third octave band spectra for the above environments were generally one of three types: (1) attached turbulent boundary layer spectra (typically high frequencies); (2) homogeneous separated flow and shock-free interference flow spectra (typically intermediate frequencies); and (3) shock-oscillation and shock-induced interference flow spectra (typically low frequencies). Predictions of plume induced separated flow environments were made. Only the SRB plumes are important, with fluctuating levels comparable to compression-corner induced separated flow shock oscillation.

Understanding the Radioactive Ingrowth and Decay of Naturally Occurring Radioactive Materials in the Environment: An Analysis of Produced Fluids from the Marcellus Shale

PubMed Central

Nelson, Andrew W.; Eitrheim, Eric S.; Knight, Andrew W.; May, Dustin; Mehrhoff, Marinea A.; Shannon, Robert; Litman, Robert; Burnett, William C.; Forbes, Tori Z.

2015-01-01

Background The economic value of unconventional natural gas resources has stimulated rapid globalization of horizontal drilling and hydraulic fracturing. However, natural radioactivity found in the large volumes of “produced fluids” generated by these technologies is emerging as an international environmental health concern. Current assessments of the radioactivity concentration in liquid wastes focus on a single element—radium. However, the use of radium alone to predict radioactivity concentrations can greatly underestimate total levels. Objective We investigated the contribution to radioactivity concentrations from naturally occurring radioactive materials (NORM), including uranium, thorium, actinium, radium, lead, bismuth, and polonium isotopes, to the total radioactivity of hydraulic fracturing wastes. Methods For this study we used established methods and developed new methods designed to quantitate NORM of public health concern that may be enriched in complex brines from hydraulic fracturing wastes. Specifically, we examined the use of high-purity germanium gamma spectrometry and isotope dilution alpha spectrometry to quantitate NORM. Results We observed that radium decay products were initially absent from produced fluids due to differences in solubility. However, in systems closed to the release of gaseous radon, our model predicted that decay products will begin to ingrow immediately and (under these closed-system conditions) can contribute to an increase in the total radioactivity for more than 100 years. Conclusions Accurate predictions of radioactivity concentrations are critical for estimating doses to potentially exposed individuals and the surrounding environment. These predictions must include an understanding of the geochemistry, decay properties, and ingrowth kinetics of radium and its decay product radionuclides. Citation Nelson AW, Eitrheim ES, Knight AW, May D, Mehrhoff MA, Shannon R, Litman R, Burnett WC, Forbes TZ, Schultz MK. 2015. Understanding the radioactive ingrowth and decay of naturally occurring radioactive materials in the environment: an analysis of produced fluids from the Marcellus Shale. Environ Health Perspect 123:689–696; http://dx.doi.org/10.1289/ehp.1408855 PMID:25831257

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

A comparison between coherent and noncoherent mobile systems in large Doppler shift, delay spread, and C/I environment

NASA Technical Reports Server (NTRS)

Feher, Kamilo

1993-01-01

The performance and implementation complexity of coherent and of noncoherent QPSK and GMSK modulation/demodulation techniques in a complex mobile satellite systems environment, including large Doppler shift, delay spread, and low C/I, are compared. We demonstrate that for large f(sub d)T(sub b) products, where f(sub d) is the Doppler shift and T(sub b) is the bit duration, noncoherent (discriminator detector or differential demodulation) systems have a lower BER floor than their coherent counterparts. For significant delay spreads, e.g., tau(sub rms) greater than 0.4 T(sub b), and low C/I, coherent systems outperform noncoherent systems. However, the synchronization time of coherent systems is longer than that of noncoherent systems. Spectral efficiency, overall capacity, and related hardware complexity issues of these systems are also analyzed. We demonstrate that coherent systems have a simpler overall architecture (IF filter implementation-cost versus carrier recovery) and are more robust in an RF frequency drift environment. Additionally, the prediction tools, computer simulations, and analysis of coherent systems is simpler. The threshold or capture effect in low C/I interference environment is critical for noncoherent discriminator based systems. We conclude with a comparison of hardware architectures of coherent and of noncoherent systems, including recent trends in commercial VLSI technology and direct baseband to RF transmit, RF to baseband (0-IF) receiver implementation strategies.

A comparison between coherent and noncoherent mobile systems in large Doppler shift, delay spread, and C/I environment

NASA Astrophysics Data System (ADS)

Feher, Kamilo

The performance and implementation complexity of coherent and of noncoherent QPSK and GMSK modulation/demodulation techniques in a complex mobile satellite systems environment, including large Doppler shift, delay spread, and low C/I, are compared. We demonstrate that for large f(sub d)T(sub b) products, where f(sub d) is the Doppler shift and T(sub b) is the bit duration, noncoherent (discriminator detector or differential demodulation) systems have a lower BER floor than their coherent counterparts. For significant delay spreads, e.g., tau(sub rms) greater than 0.4 T(sub b), and low C/I, coherent systems outperform noncoherent systems. However, the synchronization time of coherent systems is longer than that of noncoherent systems. Spectral efficiency, overall capacity, and related hardware complexity issues of these systems are also analyzed. We demonstrate that coherent systems have a simpler overall architecture (IF filter implementation-cost versus carrier recovery) and are more robust in an RF frequency drift environment. Additionally, the prediction tools, computer simulations, and analysis of coherent systems is simpler. The threshold or capture effect in low C/I interference environment is critical for noncoherent discriminator based systems. We conclude with a comparison of hardware architectures of coherent and of noncoherent systems, including recent trends in commercial VLSI technology and direct baseband to RF transmit, RF to baseband (0-IF) receiver implementation strategies.

Retreatment Predictions in Odontology by means of CBR Systems.

PubMed

Campo, Livia; Aliaga, Ignacio J; De Paz, Juan F; García, Alvaro Enrique; Bajo, Javier; Villarubia, Gabriel; Corchado, Juan M

2016-01-01

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising.

Retreatment Predictions in Odontology by means of CBR Systems

PubMed Central

Campo, Livia; Aliaga, Ignacio J.; García, Alvaro Enrique; Villarubia, Gabriel; Corchado, Juan M.

2016-01-01

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising. PMID:26884749

Ares I-X Launch Abort System, Crew Module, and Upper Stage Simulator Vibroacoustic Flight Data Evaluation, Comparison to Predictions, and Recommendations for Adjustments to Prediction Methodology and Assumptions

NASA Technical Reports Server (NTRS)

Smith, Andrew; Harrison, Phil

2010-01-01

The National Aeronautics and Space Administration (NASA) Constellation Program (CxP) has identified a series of tests to provide insight into the design and development of the Crew Launch Vehicle (CLV) and Crew Exploration Vehicle (CEV). Ares I-X was selected as the first suborbital development flight test to help meet CxP objectives. The Ares I-X flight test vehicle (FTV) is an early operational model of CLV, with specific emphasis on CLV and ground operation characteristics necessary to meet Ares I-X flight test objectives. The in-flight part of the test includes a trajectory to simulate maximum dynamic pressure during flight and perform a stage separation of the Upper Stage Simulator (USS) from the First Stage (FS). The in-flight test also includes recovery of the FS. The random vibration response from the ARES 1-X flight will be reconstructed for a few specific locations that were instrumented with accelerometers. This recorded data will be helpful in validating and refining vibration prediction tools and methodology. Measured vibroacoustic environments associated with lift off and ascent phases of the Ares I-X mission will be compared with pre-flight vibration predictions. The measured flight data was given as time histories which will be converted into power spectral density plots for comparison with the maximum predicted environments. The maximum predicted environments are documented in the Vibroacoustics and Shock Environment Data Book, AI1-SYS-ACOv4.10 Vibration predictions made using statistical energy analysis (SEA) VAOne computer program will also be incorporated in the comparisons. Ascent and lift off measured acoustics will also be compared to predictions to assess whether any discrepancies between the predicted vibration levels and measured vibration levels are attributable to inaccurate acoustic predictions. These comparisons will also be helpful in assessing whether adjustments to prediction methodologies are needed to improve agreement between the predicted and measured flight data. Future assessment will incorporate hybrid methods in VAOne analysis (i.e., boundary element methods, BEM and finite element methods, FEM). These hybrid methods will enable the ability to import NASTRAN models providing much more detailed modeling of the underlying beams and support structure of the ARES 1-X test vehicle. Measured acoustic data will be incorporated into these analyses to improve correlation for additional post flight analysis.

Comprehensive Solar-Terrestrial Environment Model (COSTEM) for Space Weather Predictions

DTIC Science & Technology

2007-07-01

research in data assimilation methodologies applicable to the space environment, as well as "threat adaptive" grid computing technologies, where we...SWMF is tested by(SWMF) [29, 43] was designed in 2001 and has sse et xriig mlil ope been developed to integrate and couple several system tests...its components. The night on several computer/compiler platforms. main design goals of the SWMF were to minimizedocumented. mai deigngoas o th SWF

Electric Conduction in Solids: a Pedagogical Approach Supported by Laboratory Measurements and Computer Modelling Environments

NASA Astrophysics Data System (ADS)

Bonura, A.; Capizzo, M. C.; Fazio, C.; Guastella, I.

2008-05-01

In this paper we present a pedagogic approach aimed at modeling electric conduction in semiconductors, built by using NetLogo, a programmable modeling environment for building and exploring multi-agent systems. `Virtual experiments' are implemented to confront predictions of different microscopic models with real measurements of electric properties of matter, such as resistivity. The relations between these electric properties and other physical variables, like temperature, are, then, analyzed.

A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

PubMed

Zhang, Jing; Liang, Lichen; Anderson, Jon R; Gatewood, Lael; Rottenberg, David A; Strother, Stephen C

2008-01-01

As functional magnetic resonance imaging (fMRI) becomes widely used, the demands for evaluation of fMRI processing pipelines and validation of fMRI analysis results is increasing rapidly. The current NPAIRS package, an IDL-based fMRI processing pipeline evaluation framework, lacks system interoperability and the ability to evaluate general linear model (GLM)-based pipelines using prediction metrics. Thus, it can not fully evaluate fMRI analytical software modules such as FSL.FEAT and NPAIRS.GLM. In order to overcome these limitations, a Java-based fMRI processing pipeline evaluation system was developed. It integrated YALE (a machine learning environment) into Fiswidgets (a fMRI software environment) to obtain system interoperability and applied an algorithm to measure GLM prediction accuracy. The results demonstrated that the system can evaluate fMRI processing pipelines with univariate GLM and multivariate canonical variates analysis (CVA)-based models on real fMRI data based on prediction accuracy (classification accuracy) and statistical parametric image (SPI) reproducibility. In addition, a preliminary study was performed where four fMRI processing pipelines with GLM and CVA modules such as FSL.FEAT and NPAIRS.CVA were evaluated with the system. The results indicated that (1) the system can compare different fMRI processing pipelines with heterogeneous models (NPAIRS.GLM, NPAIRS.CVA and FSL.FEAT) and rank their performance by automatic performance scoring, and (2) the rank of pipeline performance is highly dependent on the preprocessing operations. These results suggest that the system will be of value for the comparison, validation, standardization and optimization of functional neuroimaging software packages and fMRI processing pipelines.

Development of a Simulation Capability for the Space Station Active Rack Isolation System

NASA Technical Reports Server (NTRS)

Johnson, Terry L.; Tolson, Robert H.

1998-01-01

To realize quality microgravity science on the International Space Station, many microgravity facilities will utilize the Active Rack Isolation System (ARIS). Simulation capabilities for ARIS will be needed to predict the microgravity environment. This paper discusses the development of a simulation model for use in predicting the performance of the ARIS in attenuating disturbances with frequency content between 0.01 Hz and 10 Hz. The derivation of the model utilizes an energy-based approach. The complete simulation includes the dynamic model of the ISPR integrated with the model for the ARIS controller so that the entire closed-loop system is simulated. Preliminary performance predictions are made for the ARIS in attenuating both off-board disturbances as well as disturbances from hardware mounted onboard the microgravity facility. These predictions suggest that the ARIS does eliminate resonant behavior detrimental to microgravity experimentation. A limited comparison is made between the simulation predictions of ARIS attenuation of off-board disturbances and results from the ARIS flight test. These comparisons show promise, but further tuning of the simulation is needed.

Genomic Prediction with Pedigree and Genotype × Environment Interaction in Spring Wheat Grown in South and West Asia, North Africa, and Mexico.

PubMed

Sukumaran, Sivakumar; Crossa, Jose; Jarquin, Diego; Lopes, Marta; Reynolds, Matthew P

2017-02-09

Developing genomic selection (GS) models is an important step in applying GS to accelerate the rate of genetic gain in grain yield in plant breeding. In this study, seven genomic prediction models under two cross-validation (CV) scenarios were tested on 287 advanced elite spring wheat lines phenotyped for grain yield (GY), thousand-grain weight (GW), grain number (GN), and thermal time for flowering (TTF) in 18 international environments (year-location combinations) in major wheat-producing countries in 2010 and 2011. Prediction models with genomic and pedigree information included main effects and interaction with environments. Two random CV schemes were applied to predict a subset of lines that were not observed in any of the 18 environments (CV1), and a subset of lines that were not observed in a set of the environments, but were observed in other environments (CV2). Genomic prediction models, including genotype × environment (G×E) interaction, had the highest average prediction ability under the CV1 scenario for GY (0.31), GN (0.32), GW (0.45), and TTF (0.27). For CV2, the average prediction ability of the model including the interaction terms was generally high for GY (0.38), GN (0.43), GW (0.63), and TTF (0.53). Wheat lines in site-year combinations in Mexico and India had relatively high prediction ability for GY and GW. Results indicated that prediction ability of lines not observed in certain environments could be relatively high for genomic selection when predicting G×E interaction in multi-environment trials. Copyright © 2017 Sukumaran et al.

Space Environment and Effects System (SEES)

NASA Astrophysics Data System (ADS)

Higashio, Nana; Obara, Takahiro; Matsumoto, Haruhisa; Koga, Kiyokazu; Koshiishi, Hideki

Space environment group in JAXA has installed insturments to measure space environment on eleven satellites. In the last year, the biggest instrument called SEDA-AP (Space Environment Data Acquision equipment -Attached Paylod) was atteched to the palette of JEM (ISS). On the other hand, we have a web site, "Space Environment and Effects System(SEES)". This system consisits of four parts. First part is to provide data that were obtained from these insturments. There are 18 kinds of mesurments, for example, radiation, magnetic field and so on. In 1994, Anik E-1 and Anik E-2 were broken by solar storm and we could catch the abnormal data from our instrument. Second part is a warning system. Many Japanese satellites are working around the earth and they are always exposed to radioactivity in space. So we predict the the radiation data in two days and if the expected value is over the threshold of safety, we inform a warning massage to users who want to keep their satellites safe. And we also provide the warning massage for Japanese astronauts who stay at ISS. Third part is the tool of the space environment /satellite environment models. There are 12 kinds of environment models which are constructed from 90 space environment models, for example, radiation model, solar activity model and so on. If you register your infomation in the SEES web site, you can simulate space environment by using them. Fourth part is providing the 2D and 3D infomations of satellite's orvits. This show the satelllite's position on the world map at a paticular time. If you want to use this system, please visit our SEES page at (http://seesproxy.tksc.jaxa.jp/fw/dfw/SEES/index.html ).

NASA's Space Environments and Effects Program: Technology for the New Millennium

NASA Technical Reports Server (NTRS)

Hardage, Donna M.; Pearson, Steven D.

2000-01-01

Current trends in spacecraft development include the use of advanced technologies while maintaining the "faster, better, cheaper" philosophy. Spacecraft designers are continually designing with smaller and faster electronics as well as lighter and thinner materials providing better performance, lower weight, and ultimately lower costs. Given this technology trend, spacecraft will become increasingly susceptible to the harsh space environments, causing damaging or even disabling effects on space systems. NASA's Space Environments and Effects (SEE) Program defines the space environments and provides advanced technology development to support the design, development, and operation of spacecraft systems that will accommodate or mitigate effects due to the harsh space environments. This Program provides a comprehensive and focused approach to understanding the space environment, to define the best techniques for both flight and ground-based experimentation, to update the models which predict both the environments and the environmental effects on spacecraft, and finally to ensure that this multitudinous information is properly maintained and inserted into spacecraft design programs. A description of the SEE Program, its accomplishments, and future activities is provided.

Human-Robot Interaction in High Vulnerability Domains

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2016-01-01

Future NASA missions will require successful integration of the human with highly complex systems. Highly complex systems are likely to involve humans, automation, and some level of robotic assistance. The complex environments will require successful integration of the human with automation, with robots, and with human-automation-robot teams to accomplish mission critical goals. Many challenges exist for the human performing in these types of operational environments with these kinds of systems. Systems must be designed to optimally integrate various levels of inputs and outputs based on the roles and responsibilities of the human, the automation, and the robots; from direct manual control, shared human-robotic control, or no active human control (i.e. human supervisory control). It is assumed that the human will remain involved at some level. Technologies that vary based on contextual demands and on operator characteristics (workload, situation awareness) will be needed when the human integrates into these systems. Predictive models that estimate the impact of the technologies on the system performance and the on the human operator are also needed to meet the challenges associated with such future complex human-automation-robot systems in extreme environments.

Navy Enhanced Sierra Mechanics (NESM): Toolbox for predicting Navy shock and damage

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

Moyer, Thomas; Stergiou, Jonathan; Reese, Garth

Here, the US Navy is developing a new suite of computational mechanics tools (Navy Enhanced Sierra Mechanics) for the prediction of ship response, damage, and shock environments transmitted to vital systems during threat weapon encounters. NESM includes fully coupled Euler-Lagrange solvers tailored to ship shock/damage predictions. NESM is optimized to support high-performance computing architectures, providing the physics-based ship response/threat weapon damage predictions needed to support the design and assessment of highly survivable ships. NESM is being employed to support current Navy ship design and acquisition programs while being further developed for future Navy fleet needs.

Navy Enhanced Sierra Mechanics (NESM): Toolbox for predicting Navy shock and damage

DOE PAGES

Moyer, Thomas; Stergiou, Jonathan; Reese, Garth; ...

2016-05-25

Here, the US Navy is developing a new suite of computational mechanics tools (Navy Enhanced Sierra Mechanics) for the prediction of ship response, damage, and shock environments transmitted to vital systems during threat weapon encounters. NESM includes fully coupled Euler-Lagrange solvers tailored to ship shock/damage predictions. NESM is optimized to support high-performance computing architectures, providing the physics-based ship response/threat weapon damage predictions needed to support the design and assessment of highly survivable ships. NESM is being employed to support current Navy ship design and acquisition programs while being further developed for future Navy fleet needs.

An automatically tuning intrusion detection system.

PubMed

Yu, Zhenwei; Tsai, Jeffrey J P; Weigert, Thomas

2007-04-01

An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.

A urine volume measurement system

NASA Technical Reports Server (NTRS)

Poppendiek, H. F.; Mouritzen, G.; Sabin, C. M.

1972-01-01

An improved urine volume measurement system for use in the unusual environment of manned space flight is reported. The system utilizes a low time-constant thermal flowmeter. The time integral of the transient response of the flowmeter gives the urine volume during a void as it occurs. In addition, the two phase flows through the flowmeter present no problem. Developments of the thermal flowmeter and a verification of the predicted performance characteristics are summarized.

Stochastic Prediction and Feedback Control of Router Queue Size in a Virtual Network Environment

DTIC Science & Technology

2014-09-18

predictor equations, while the update equations for measurement can be thought of as corrector equations. 11 2.3.1.1 Predict Equations In the... Adaptive Filters and Self -Learning Systems. Springer London, 2005. [11] Zarchan, P., and Musoff, H. Fundamentals of Kalman filtering: A Practical...iv AFIT-ENG-T-14-S-10 Abstract Modern congestion and routing management algorithms work well for networks with static topologies and moderate

Space Environment Modelling with the Use of Artificial Intelligence Methods

NASA Astrophysics Data System (ADS)

Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

1996-12-01

Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore also handled with the modules in the Lund Space Weather Model. Interesting Links: Lund Space Weather and AI Center

Microgravity Vibration Isolation for the International Space Station

NASA Technical Reports Server (NTRS)

Whorton, Mark S.

2000-01-01

The International Space Station (ISS) is being envisioned as a laboratory for experiments in numerous microgravity (micrograms) science disciplines. Predictions of the ISS acceleration environment indicate that the ambient acceleration levels ill exceed levels that can be tolerated by the science experiments. Hence, microgravity vibration isolation systems are being developed to attenuate the accelerations to acceptable levels. While passive isolation systems are beneficial in certain applications, active isolation systems are required to provide attenuation at low frequencies and to mitigate directly induced payload disturbances. To date, three active isolation systems have been successfully tested in the orbital environment. A fourth system called g-LIMIT is currently being developed for the Microgravity Science Glovebox and is manifested for launch on the UF-1 mission. This paper presents an overview of microgravity vibration isolation technology and the g-LIMIT system in particular.

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

PubMed Central

Bandeira e Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-01-01

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. PMID:28455415

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

PubMed

Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-06-07

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.

Genome-to-Watershed Predictive Understanding of Terrestrial Environments

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Integrating Cache Performance Modeling and Tuning Support in Parallelization Tools

NASA Technical Reports Server (NTRS)

Waheed, Abdul; Yan, Jerry; Saini, Subhash (Technical Monitor)

1998-01-01

With the resurgence of distributed shared memory (DSM) systems based on cache-coherent Non Uniform Memory Access (ccNUMA) architectures and increasing disparity between memory and processors speeds, data locality overheads are becoming the greatest bottlenecks in the way of realizing potential high performance of these systems. While parallelization tools and compilers facilitate the users in porting their sequential applications to a DSM system, a lot of time and effort is needed to tune the memory performance of these applications to achieve reasonable speedup. In this paper, we show that integrating cache performance modeling and tuning support within a parallelization environment can alleviate this problem. The Cache Performance Modeling and Prediction Tool (CPMP), employs trace-driven simulation techniques without the overhead of generating and managing detailed address traces. CPMP predicts the cache performance impact of source code level "what-if" modifications in a program to assist a user in the tuning process. CPMP is built on top of a customized version of the Computer Aided Parallelization Tools (CAPTools) environment. Finally, we demonstrate how CPMP can be applied to tune a real Computational Fluid Dynamics (CFD) application.

Understanding the Home Math Environment and Its Role in Predicting Parent Report of Children's Math Skills.

PubMed

Hart, Sara A; Ganley, Colleen M; Purpura, David J

2016-01-01

There is a growing literature concerning the role of the home math environment in children's math development. In this study, we examined the relation between these constructs by specifically addressing three goals. The first goal was to identify the measurement structure of the home math environment through a series of confirmatory factor analyses. The second goal was to examine the role of the home math environment in predicting parent report of children's math skills. The third goal was to test a series of potential alternative explanations for the relation between the home math environment and parent report of children's skills, specifically the direct and indirect role of household income, parent math anxiety, and parent math ability as measured by their approximate number system performance. A final sample of 339 parents of children aged 3 through 8 drawn from Mechanical Turk answered a questionnaire online. The best fitting model of the home math environment was a bifactor model with a general factor representing the general home math environment, and three specific factors representing the direct numeracy environment, the indirect numeracy environment, and the spatial environment. When examining the association of the home math environment factors to parent report of child skills, the general home math environment factor and the spatial environment were the only significant predictors. Parents who reported doing more general math activities in the home reported having children with higher math skills, whereas parents who reported doing more spatial activities reported having children with lower math skills.

Understanding the Home Math Environment and Its Role in Predicting Parent Report of Children’s Math Skills

PubMed Central

Ganley, Colleen M.; Purpura, David J.

2016-01-01

There is a growing literature concerning the role of the home math environment in children’s math development. In this study, we examined the relation between these constructs by specifically addressing three goals. The first goal was to identify the measurement structure of the home math environment through a series of confirmatory factor analyses. The second goal was to examine the role of the home math environment in predicting parent report of children’s math skills. The third goal was to test a series of potential alternative explanations for the relation between the home math environment and parent report of children’s skills, specifically the direct and indirect role of household income, parent math anxiety, and parent math ability as measured by their approximate number system performance. A final sample of 339 parents of children aged 3 through 8 drawn from Mechanical Turk answered a questionnaire online. The best fitting model of the home math environment was a bifactor model with a general factor representing the general home math environment, and three specific factors representing the direct numeracy environment, the indirect numeracy environment, and the spatial environment. When examining the association of the home math environment factors to parent report of child skills, the general home math environment factor and the spatial environment were the only significant predictors. Parents who reported doing more general math activities in the home reported having children with higher math skills, whereas parents who reported doing more spatial activities reported having children with lower math skills. PMID:28005925

Understanding the operational environment: implications for advanced visualizations

NASA Astrophysics Data System (ADS)

Aleva, Denise; Fitzhugh, Elisabeth; Dixon, Sharon

2009-05-01

With the changing character of warfare, information superiority is a high priority. Given the complexity of current and future operating environments, analysts, strategists and planners need a multidimensional understanding of the battlespace. Asymmetric warfare necessitates that our strategists look beyond targets-based operations, where we simply identify and destroy enemy entities. Effects-based operations models the enemy as a system which reacts to our actions. This requires the capability to predict the adversary response to a selected action. Actions may be diplomatic, information, military or economic (DIME). Effects may be political, military, economic, social, information or infrastructure (PMESII). Timing must be explicitly considered and effects dynamically assessed. Visualizations of intelligence information are needed which will promote full understanding of all aspects of adversary strengths and weaknesses by providing the extensive data about adversary forces, organic essentials, infrastructure, leadership, population, and science and technology in an easily accessible and understandable format. This will enhance Effectsbased operations, and therefore, the capability to predict and counter adversary courses of action. This paper outlines a systems engineering approach to designing visualizations which convey the multidimensional information to decision makers. Visualization issues inherent in understanding the multidimensional operational environment will be discussed.

An Energy-Economy-Environment Model for Simulating the Impacts of Socioeconomic Development on Energy and Environment

PubMed Central

Yao, Bo

2014-01-01

Many rapidly developing regions have begun to draw the attention of the world. Meanwhile, the energy and environmental issues associated with rapid economic growth have aroused widespread critical concern. Therefore, studying energy, economic, and environmental systems is of great importance. This study establishes a system dynamic model that covers multiple aspects of those systems, such as energy, economy, population, water pollution, air pollution, solid waste, and technology. The model designed here attempts to determine the impacts of socioeconomic development on the energy and environment of Tongzhou District in three scenarios: under current, planning, and sustainable conditions. The results reveal that energy shortages and water pollutions are very serious and are the key issues constraining future social and economic development. Solid waste emissions increase with population growth. The prediction results provide valuable insights into social advancement. PMID:24683332

The Development of Environmental Barrier Coating Systems for SiC-SiC Ceramic Matrix Composites: Environment Effects on the Creep and Fatigue Resistance

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Ghosn, Louis J.

2014-01-01

Topics covered include: Environmental barrier coating system development: needs, challenges and limitations; Advanced environmental barrier coating systems (EBCs) for CMC airfoils and combustors; NASA EBC systems and material system evolutions, Current turbine and combustor EBC coating emphases, Advanced development, processing, testing and modeling, EBC and EBC bond coats: recent advances; Design tool and life prediction of coated CMC components; Advanced CMC-EBC rig demonstrations; Summary and future directions.

Six-Tube Freezable Radiator Testing and Model Correlation

NASA Technical Reports Server (NTRS)

Lillibridge, Sean; Navarro, Moses

2011-01-01

Freezable radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recovering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TradeMark) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested, namely MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Six-Tube Freezable Radiator Testing and Model Correlation

NASA Technical Reports Server (NTRS)

Lilibridge, Sean T.; Navarro, Moses

2012-01-01

Freezable Radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft?s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recov ering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TM) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested: MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Assessing the Challenges Associated with Developing an Integrated Modeling Approach for Predicting and Managing Water Quality and Quantity from the Watershed through the Drinking Water Treatment System

EPA Science Inventory

Natural and Engineered water systems interact throughout watersheds (e.g., at water intakes, wastewater outfalls and water pipe breaks of all kinds), and while there is clearly a link between watershed activities and the quality of water entering the engineered environment, surfa...

A systems-based approach to predict biological responses of aquatic organisms to complex environmental mixtures

EPA Science Inventory

Contaminants of emerging concern (CECs) such as new-generation pesticides, pharmaceuticals, household and personal care products, steroid hormones, and flame retardants enter the aquatic environment through multiple sources such as wastewater treatment plants and agricultural ope...

REDUCTIVE DEHALOGENATION OF HALOMETHANES IN NATURAL AND MODEL SYSTEMS: QSAR ANALYSIS

EPA Science Inventory

Reductive dehalogenation is a dominant reaction pathway for halogenated organics in anoxic environments. Towards the goal of developing predictive tools for this reaction process, the reduction kinetics for a series of halomethanes were measured in batch studies with both natural...

Meteorological Processes Affecting Air Quality – Research and Model Development Needs

EPA Science Inventory

Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were devel...

Balancing computation and communication power in power constrained clusters

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

Piga, Leonardo; Paul, Indrani; Huang, Wei

Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agentmore » may be configured to reassign the unused power to the active nodes to expedite workload processing.« less

A numerical tool for reproducing driver behaviour: experiments and predictive simulations.

PubMed

Casucci, M; Marchitto, M; Cacciabue, P C

2010-03-01

This paper presents the simulation tool called SDDRIVE (Simple Simulation of Driver performance), which is the numerical computerised implementation of the theoretical architecture describing Driver-Vehicle-Environment (DVE) interactions, contained in Cacciabue and Carsten [Cacciabue, P.C., Carsten, O. A simple model of driver behaviour to sustain design and safety assessment of automated systems in automotive environments, 2010]. Following a brief description of the basic algorithms that simulate the performance of drivers, the paper presents and discusses a set of experiments carried out in a Virtual Reality full scale simulator for validating the simulation. Then the predictive potentiality of the tool is shown by discussing two case studies of DVE interactions, performed in the presence of different driver attitudes in similar traffic conditions.

Ecotoxicity and environmental risk assessment of pharmaceuticals and personal care products in aquatic environments and wastewater treatment plants.

PubMed

Ortiz de García, Sheyla Andrea; Pinto Pinto, Gilberto; García-Encina, Pedro A; Irusta-Mata, Rubén

2014-10-01

A wide range of pharmaceuticals and personal care products (PPCPs) are present in the environment, and many of their adverse effects are unknown. The environmental risk assessment of 26 PPCPs of relevant consumption and occurrence in the aquatic environment in Spain was accomplished in this research. Based on the ecotoxicity values obtained by bioluminescence and respirometry assays and by predictions using the US EPA ecological structure-activity relationship (ECOSAR™), the compounds were classified following the Globally Harmonized System of Classification and Labelling of Chemicals. According to the criteria of the European Medicines Agency, the real risk of impact of these compounds in wastewater treatment plants (WWTPs) and in the aquatic environment was predicted. In at least two ecotoxicity tests, 65.4 % of the PPCPs under study showed high toxicity or were harmful to aquatic organisms. The global order of the species' sensitivity to the PPCPs considered was as follows: Vibrio fischeri (5 min) > Vibrio fischeri (15 min) > algae > crustaceans > fish > biomass of WWTP. Acetaminophen, ciprofloxacin, clarithromycin, clofibrate, ibuprofen, omeprazole, triclosan, parabens and 1,4-benzoquinone showed some type of risk for the aquatic environments and/or for the activated sludge of WWTPs. Development of acute and chronic ecotoxicity data, the determination of predicted and measured environmental concentrations of PPCPs, the inclusion of metabolites and transformation products and the evaluation of mixtures of these compounds will allow further improvements of the results of the ERAs and, finally, to efficiently identify the compounds that could affect the environment.

Childhood temperament and family environment as predictors of internalizing and externalizing trajectories from ages 5 to 17.

PubMed

Leve, Leslie D; Kim, Hyoun K; Pears, Katherine C

2005-10-01

Childhood temperament and family environment have been shown to predict internalizing and externalizing behavior; however, less is known about how temperament and family environment interact to predict changes in problem behavior. We conducted latent growth curve modeling on a sample assessed at ages 5, 7, 10, 14, and 17 (N = 337). Externalizing behavior decreased over time for both sexes, and internalizing behavior increased over time for girls only. Two childhood variables (fear/shyness and maternal depression) predicted boys' and girls' age-17 internalizing behavior, harsh discipline uniquely predicted boys' age-17 internalizing behavior, and maternal depression and lower family income uniquely predicted increases in girls' internalizing behavior. For externalizing behavior, an array of temperament, family environment, and Temperament x Family Environment variables predicted age-17 behavior for both sexes. Sex differences were present in the prediction of externalizing slopes, with maternal depression predicting increases in boys' externalizing behavior only when impulsivity was low, and harsh discipline predicting increases in girls' externalizing behavior only when impulsivity was high or when fear/shyness was low.

Evaluation of a conceptual framework for predicting navigation performance in virtual reality.

PubMed

Grübel, Jascha; Thrash, Tyler; Hölscher, Christoph; Schinazi, Victor R

2017-01-01

Previous research in spatial cognition has often relied on simple spatial tasks in static environments in order to draw inferences regarding navigation performance. These tasks are typically divided into categories (e.g., egocentric or allocentric) that reflect different two-systems theories. Unfortunately, this two-systems approach has been insufficient for reliably predicting navigation performance in virtual reality (VR). In the present experiment, participants were asked to learn and navigate towards goal locations in a virtual city and then perform eight simple spatial tasks in a separate environment. These eight tasks were organised along four orthogonal dimensions (static/dynamic, perceived/remembered, egocentric/allocentric, and distance/direction). We employed confirmatory and exploratory analyses in order to assess the relationship between navigation performance and performances on these simple tasks. We provide evidence that a dynamic task (i.e., intercepting a moving object) is capable of predicting navigation performance in a familiar virtual environment better than several categories of static tasks. These results have important implications for studies on navigation in VR that tend to over-emphasise the role of spatial memory. Given that our dynamic tasks required efficient interaction with the human interface device (HID), they were more closely aligned with the perceptuomotor processes associated with locomotion than wayfinding. In the future, researchers should consider training participants on HIDs using a dynamic task prior to conducting a navigation experiment. Performances on dynamic tasks should also be assessed in order to avoid confounding skill with an HID and spatial knowledge acquisition.

Complete genome sequence of Nitrosospira multiformis, an ammonia-oxidizing bacterium from the soil environment

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

Norton, Jeanette M.; Klotz, Martin G; Stein, Lisa Y

2008-01-01

The complete genome of the ammonia-oxidizing bacterium, Nitrosospira multiformis (ATCC 25196T), consists of a circular chromosome and three small plasmids totaling 3,234,309 bp and encoding 2827 putative proteins. Of these, 2026 proteins have predicted functions and 801 are without conserved functional domains, yet 747 of these have similarity to other predicted proteins in databases. Gene homologs from Nitrosomonas europaea and N. eutropha were the best match for 42% of the predicted genes in N. multiformis. The genome contains three nearly identical copies of amo and hao gene clusters as large repeats. Distinguishing features compared to N. europaea include: the presencemore » of gene clusters encoding urease and hydrogenase, a RuBisCO-encoding operon of distinctive structure and phylogeny, and a relatively small complement of genes related to Fe acquisition. Systems for synthesis of a pyoverdine-like siderophore and for acyl-homoserine lactone were unique to N. multiformis among the sequenced AOB genomes. Gene clusters encoding proteins associated with outer membrane and cell envelope functions including transporters, porins, exopolysaccharide synthesis, capsule formation and protein sorting/export were abundant. Numerous sensory transduction and response regulator gene systems directed towards sensing of the extracellular environment are described. Gene clusters for glycogen, polyphosphate and cyanophycin storage and utilization were identified providing mechanisms for meeting energy requirements under substrate-limited conditions. The genome of N. multiformis encodes the core pathways for chemolithoautotrophy along with adaptations for surface growth and survival in soil environments.« less

Evaluation of a conceptual framework for predicting navigation performance in virtual reality

PubMed Central

Thrash, Tyler; Hölscher, Christoph; Schinazi, Victor R.

2017-01-01

Previous research in spatial cognition has often relied on simple spatial tasks in static environments in order to draw inferences regarding navigation performance. These tasks are typically divided into categories (e.g., egocentric or allocentric) that reflect different two-systems theories. Unfortunately, this two-systems approach has been insufficient for reliably predicting navigation performance in virtual reality (VR). In the present experiment, participants were asked to learn and navigate towards goal locations in a virtual city and then perform eight simple spatial tasks in a separate environment. These eight tasks were organised along four orthogonal dimensions (static/dynamic, perceived/remembered, egocentric/allocentric, and distance/direction). We employed confirmatory and exploratory analyses in order to assess the relationship between navigation performance and performances on these simple tasks. We provide evidence that a dynamic task (i.e., intercepting a moving object) is capable of predicting navigation performance in a familiar virtual environment better than several categories of static tasks. These results have important implications for studies on navigation in VR that tend to over-emphasise the role of spatial memory. Given that our dynamic tasks required efficient interaction with the human interface device (HID), they were more closely aligned with the perceptuomotor processes associated with locomotion than wayfinding. In the future, researchers should consider training participants on HIDs using a dynamic task prior to conducting a navigation experiment. Performances on dynamic tasks should also be assessed in order to avoid confounding skill with an HID and spatial knowledge acquisition. PMID:28915266

Validation techniques for fault emulation of SRAM-based FPGAs

DOE PAGES

Quinn, Heather; Wirthlin, Michael

2015-08-07

A variety of fault emulation systems have been created to study the effect of single-event effects (SEEs) in static random access memory (SRAM) based field-programmable gate arrays (FPGAs). These systems are useful for augmenting radiation-hardness assurance (RHA) methodologies for verifying the effectiveness for mitigation techniques; understanding error signatures and failure modes in FPGAs; and failure rate estimation. For radiation effects researchers, it is important that these systems properly emulate how SEEs manifest in FPGAs. If the fault emulation systems does not mimic the radiation environment, the system will generate erroneous data and incorrect predictions of behavior of the FPGA inmore » a radiation environment. Validation determines whether the emulated faults are reasonable analogs to the radiation-induced faults. In this study we present methods for validating fault emulation systems and provide several examples of validated FPGA fault emulation systems.« less

Effects of low energy proton, electron, and simultaneously combined proton and electron environments in silicon and GaAs solar cells

NASA Technical Reports Server (NTRS)

Horne, W. E.; Day, A. C.; Russell, D. A.

1980-01-01

Degradation of silicon and GaAs solar cells due to exposures to low energy proton and electron environments and annealing data for these cells are discussed. Degradation of silicon cells in simultaneously combined electron and low energy proton environments and previous experimental work is summarized and evaluated. The deficiencies in current solar array damage prediction techniques indicated by these data and the relevance of these deficiencies to specific missions such as intermediate altitude orbits and orbital transfer vehicles using solar electric propulsion systems are considered.

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Newman, Clark P.; Slojkowski, Steven E.; Carpenter, J. Russell

2014-01-01

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

A model of neuro-musculo-skeletal system for human locomotion under position constraint condition.

PubMed

Ni, Jiangsheng; Hiramatsu, Seiji; Kato, Atsuo

2003-08-01

The human locomotion was studied on the basis of the interaction of the musculo-skeletal system, the neural system and the environment. A mathematical model of human locomotion under position constraint condition was established. Besides the neural rhythm generator, the posture controller and the sensory system, the environment feedback controller and the stability controller were taken into account in the model. The environment feedback controller was proposed for two purposes, obstacle avoidance and target position control of the swing foot. The stability controller was proposed to imitate the self-balancing ability of a human body and improve the stability of the model. In the stability controller, the ankle torque was used to control the velocity of the body gravity center. A prediction control algorithm was applied to calculate the torque magnitude of the stability controller. As an example, human stairs climbing movement was simulated and the results were given. The simulation result proved that the mathematical modeling of the task was successful.

Adaptability of non-genetic diversity in bacterial chemotaxis

PubMed Central

Frankel, Nicholas W; Pontius, William; Dufour, Yann S; Long, Junjiajia; Hernandez-Nunez, Luis; Emonet, Thierry

2014-01-01

Bacterial chemotaxis systems are as diverse as the environments that bacteria inhabit, but how much environmental variation can cells tolerate with a single system? Diversification of a single chemotaxis system could serve as an alternative, or even evolutionary stepping-stone, to switching between multiple systems. We hypothesized that mutations in gene regulation could lead to heritable control of chemotactic diversity. By simulating foraging and colonization of E. coli using a single-cell chemotaxis model, we found that different environments selected for different behaviors. The resulting trade-offs show that populations facing diverse environments would ideally diversify behaviors when time for navigation is limited. We show that advantageous diversity can arise from changes in the distribution of protein levels among individuals, which could occur through mutations in gene regulation. We propose experiments to test our prediction that chemotactic diversity in a clonal population could be a selectable trait that enables adaptation to environmental variability. DOI: http://dx.doi.org/10.7554/eLife.03526.001 PMID:25279698

Application of zonal model on indoor air sensor network design

NASA Astrophysics Data System (ADS)

Chen, Y. Lisa; Wen, Jin

2007-04-01

Growing concerns over the safety of the indoor environment have made the use of sensors ubiquitous. Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is more informed by intuition and experience rather by systematic design. To develop a sensor system design methodology, a proper indoor airflow modeling approach is needed. Various indoor airflow modeling techniques, from complicated computational fluid dynamics approaches to simplified multi-zone approaches, exist in the literature. In this study, the effects of two airflow modeling techniques, multi-zone modeling technique and zonal modeling technique, on indoor air protection sensor system design are discussed. Common building attack scenarios, using a typical CBW agent, are simulated. Both multi-zone and zonal models are used to predict airflows and contaminant dispersion. Genetic Algorithm is then applied to optimize the sensor location and quantity. Differences in the sensor system design resulting from the two airflow models are discussed for a typical office environment and a large hall environment.

Operational warning of interplanetary shock arrivals using energetic particle data from ACE: Real-time Upstream Monitoring System

NASA Astrophysics Data System (ADS)

Donegan, M.; Vandegriff, J.; Ho, G. C.; Julia, S. J.

2004-12-01

We report on an operational system which provides advance warning and predictions of arrival times at Earth of interplanetary (IP) shocks that originate at the Sun. The data stream used in our prediction algorithm is real-time and comes from the Electron, Proton, and Alpha Monitor (EPAM) instrument on NASA's Advanced Composition Explorer (ACE) spacecraft. Since locally accelerated energetic storm particle (ESP) events accompany most IP shocks, their arrival can be predicted using ESP event signatures. We have previously reported on the development and implementation of an algorithm which recognizes the upstream particle signature of approaching IP shocks and provides estimated countdown predictions. A web-based system (see (http://sd-www.jhuapl.edu/UPOS/RISP/index.html) combines this prediction capability with real-time ACE/EPAM data provided by the NOAA Space Environment Center. The most recent ACE data is continually processed and predictions of shock arrival time are updated every five minutes when an event is impending. An operational display is provided to indicate advisories and countdowns for the event. Running the algorithm on a test set of historical events, we obtain a median error of about 10 hours for predictions made 24-36 hours before actual shock arrival and about 6 hours when the shock is 6-12 hours away. This system can provide critical information to mission planners, satellite operations controllers, and scientists by providing significant lead-time for approaching events. Recently, we have made improvements to the triggering mechanism as well as re-training the neural network, and here we report prediction results from the latest system.

The Software Management Environment (SME)

NASA Technical Reports Server (NTRS)

Valett, Jon D.; Decker, William; Buell, John

1988-01-01

The Software Management Environment (SME) is a research effort designed to utilize the past experiences and results of the Software Engineering Laboratory (SEL) and to incorporate this knowledge into a tool for managing projects. SME provides the software development manager with the ability to observe, compare, predict, analyze, and control key software development parameters such as effort, reliability, and resource utilization. The major components of the SME, the architecture of the system, and examples of the functionality of the tool are discussed.

Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids.

PubMed

Acosta-Pech, Rocío; Crossa, José; de Los Campos, Gustavo; Teyssèdre, Simon; Claustres, Bruno; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino

2017-07-01

A new genomic model that incorporates genotype × environment interaction gave increased prediction accuracy of untested hybrid response for traits such as percent starch content, percent dry matter content and silage yield of maize hybrids. The prediction of hybrid performance (HP) is very important in agricultural breeding programs. In plant breeding, multi-environment trials play an important role in the selection of important traits, such as stability across environments, grain yield and pest resistance. Environmental conditions modulate gene expression causing genotype × environment interaction (G × E), such that the estimated genetic correlations of the performance of individual lines across environments summarize the joint action of genes and environmental conditions. This article proposes a genomic statistical model that incorporates G × E for general and specific combining ability for predicting the performance of hybrids in environments. The proposed model can also be applied to any other hybrid species with distinct parental pools. In this study, we evaluated the predictive ability of two HP prediction models using a cross-validation approach applied in extensive maize hybrid data, comprising 2724 hybrids derived from 507 dent lines and 24 flint lines, which were evaluated for three traits in 58 environments over 12 years; analyses were performed for each year. On average, genomic models that include the interaction of general and specific combining ability with environments have greater predictive ability than genomic models without interaction with environments (ranging from 12 to 22%, depending on the trait). We concluded that including G × E in the prediction of untested maize hybrids increases the accuracy of genomic models.

Experimental validation of finite element model analysis of a steel frame in simulated post-earthquake fire environments

NASA Astrophysics Data System (ADS)

Huang, Ying; Bevans, W. J.; Xiao, Hai; Zhou, Zhi; Chen, Genda

2012-04-01

During or after an earthquake event, building system often experiences large strains due to shaking effects as observed during recent earthquakes, causing permanent inelastic deformation. In addition to the inelastic deformation induced by the earthquake effect, the post-earthquake fires associated with short fuse of electrical systems and leakage of gas devices can further strain the already damaged structures during the earthquakes, potentially leading to a progressive collapse of buildings. Under these harsh environments, measurements on the involved building by various sensors could only provide limited structural health information. Finite element model analysis, on the other hand, if validated by predesigned experiments, can provide detail structural behavior information of the entire structures. In this paper, a temperature dependent nonlinear 3-D finite element model (FEM) of a one-story steel frame is set up by ABAQUS based on the cited material property of steel from EN 1993-1.2 and AISC manuals. The FEM is validated by testing the modeled steel frame in simulated post-earthquake environments. Comparisons between the FEM analysis and the experimental results show that the FEM predicts the structural behavior of the steel frame in post-earthquake fire conditions reasonably. With experimental validations, the FEM analysis of critical structures could be continuously predicted for structures in these harsh environments for a better assistant to fire fighters in their rescue efforts and save fire victims.

An Illumination Modeling System for Human Factors Analyses

NASA Technical Reports Server (NTRS)

Huynh, Thong; Maida, James C.; Bond, Robert L. (Technical Monitor)

2002-01-01

Seeing is critical to human performance. Lighting is critical for seeing. Therefore, lighting is critical to human performance. This is common sense, and here on earth, it is easily taken for granted. However, on orbit, because the sun will rise or set every 45 minutes on average, humans working in space must cope with extremely dynamic lighting conditions. Contrast conditions of harsh shadowing and glare is also severe. The prediction of lighting conditions for critical operations is essential. Crew training can factor lighting into the lesson plans when necessary. Mission planners can determine whether low-light video cameras are required or whether additional luminaires need to be flown. The optimization of the quantity and quality of light is needed because of the effects on crew safety, on electrical power and on equipment maintainability. To address all of these issues, an illumination modeling system has been developed by the Graphics Research and Analyses Facility (GRAF) and Lighting Environment Test Facility (LETF) in the Space Human Factors Laboratory at NASA Johnson Space Center. The system uses physically based ray tracing software (Radiance) developed at Lawrence Berkeley Laboratories, a human factors oriented geometric modeling system (PLAID) and an extensive database of humans and environments. Material reflectivity properties of major surfaces and critical surfaces are measured using a gonio-reflectometer. Luminaires (lights) are measured for beam spread distribution, color and intensity. Video camera performances are measured for color and light sensitivity. 3D geometric models of humans and the environment are combined with the material and light models to form a system capable of predicting lighting conditions and visibility conditions in space.

Mechanisms of cooperation in cancer nanomedicine: towards systems nanotechnology.

PubMed

Hauert, Sabine; Bhatia, Sangeeta N

2014-09-01

Nanoparticles are designed to deliver therapeutics and diagnostics selectively to tumors. Their size, shape, charge, material, coating, and cargo determine their individual functionalities. A systems approach could help predict the behavior of trillions of nanoparticles interacting in complex tumor environments. Engineering these nanosystems may lead to biomimetic strategies where interactions between nanoparticles and their environment give rise to cooperative behaviors typically seen in natural self-organized systems. Examples include nanoparticles that communicate the location of a tumor to amplify tumor homing or self-assemble and disassemble to optimize nanoparticle transport. The challenge is to discover which nanoparticle designs lead to a desired system behavior. To this end, novel nanomaterials, deep understanding of biology, and computational tools are emerging as the next frontier. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Czech Hydrometeorological Institute's severe storm nowcasting system

NASA Astrophysics Data System (ADS)

Novak, Petr

2007-02-01

To satisfy requirements for operational severe weather monitoring and prediction, the Czech Hydrometeorological Institute (CHMI) has developed a severe storm nowcasting system which uses weather radar data as its primary data source. Previous CHMI studies identified two methods of radar echo prediction, which were then implemented during 2003 into the Czech weather radar network operational weather processor. The applications put into operations were the Continuity Tracking Radar Echoes by Correlation (COTREC) algorithm, and an application that predicts future radar fields using the wind field derived from the geopotential at 700 hPa calculated from a local numerical weather prediction model (ALADIN). To ensure timely delivery of the prediction products to the users, the forecasts are implemented into a web-based viewer (JSMeteoView) that has been developed by the CHMI Radar Department. At present, this viewer is used by all CHMI forecast offices for versatile visualization of radar and other meteorological data (Meteosat, lightning detection, NWP LAM output, SYNOP data) in the Internet/Intranet environment, and the viewer has detailed geographical navigation capabilities.

Native Mussels Alter Nutrient Availability and Reduce Blue-Green Algae Abundance

EPA Science Inventory

Nutrient cycling is a key process that ties all organisms together. This is especially apparent in stream environments in which nutrients are taken up readily and cycled through the system in a downstream trajectory. Ecological stoichiometry predicts that biogeochemical cycles of...

The role of future scenarios to understand deep uncertainty for air quality management.

EPA Science Inventory

The environment and its interaction with human systems (economic, social and political) is complex and dynamic. Key drivers may disrupt systemdynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents a challeng...

Safety of High Speed Magnetic Levitation Transportation Systems : Thermal Effects and Related Safety Issues of Typical Maglev Steel Guideways

DOT National Transportation Integrated Search

1994-09-01

This report presents a theoretical analysis predicting the temperature distribution, thermal deflections, and thermal stresses that may occur in typical steel Maglev guideways under the proposed Orlando FL thermal environment. Transient, finite eleme...

GIS and crop simulation modelling applications in climate change research

USDA-ARS?s Scientific Manuscript database

The challenges that climate change presents humanity require an unprecedented ability to predict the responses of crops to environment and management. Geographic information systems (GIS) and crop simulation models are two powerful and highly complementary tools that are increasingly used for such p...

Toward autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fogel, L. J.; Calabrese, P. G.; Walsh, M. J.; Owens, A. J.

1982-01-01

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented.

Performance of a parallel code for the Euler equations on hypercube computers

NASA Technical Reports Server (NTRS)

Barszcz, Eric; Chan, Tony F.; Jesperson, Dennis C.; Tuminaro, Raymond S.

1990-01-01

The performance of hypercubes were evaluated on a computational fluid dynamics problem and the parallel environment issues were considered that must be addressed, such as algorithm changes, implementation choices, programming effort, and programming environment. The evaluation focuses on a widely used fluid dynamics code, FLO52, which solves the two dimensional steady Euler equations describing flow around the airfoil. The code development experience is described, including interacting with the operating system, utilizing the message-passing communication system, and code modifications necessary to increase parallel efficiency. Results from two hypercube parallel computers (a 16-node iPSC/2, and a 512-node NCUBE/ten) are discussed and compared. In addition, a mathematical model of the execution time was developed as a function of several machine and algorithm parameters. This model accurately predicts the actual run times obtained and is used to explore the performance of the code in interesting but yet physically realizable regions of the parameter space. Based on this model, predictions about future hypercubes are made.

Energy in a Planetary Context

NASA Technical Reports Server (NTRS)

Hoehler, Tori M.

2017-01-01

The potential present day habitability of solar system bodies beyond Earth is limited to subsurface environments, where the availability of energy in biologically useful form is a paramount consideration. Energy availability is commonly quantified in terms of molar Gibbs energy changes for metabolisms of interest, but this can provide an incomplete and even misleading picture. A second aspect of life's requirement for energy - the rate of delivery, or power - strongly influences habitability, biomass abundance, growth rates, and, ultimately, rates of evolution. We are developing an approach to quantify metabolic power, using a cell-scale reactive transport model in which physical and chemical environmental parameters are varied. Simultaneously, we evaluate cell-specific energy flux requirements and their dependence on environmental "extremes". Comparison of metabolic power supply and demand provides a constraint on how biomass abundance varies across a range of environmental parameters, and thereby a prediction of the relative habitability of different environments. We are evaluating the predictive capability of this approach through comparison to observed distributions of microbial abundance in a range of subsurface (predominantly serpentinizing) systems.

Functionally dissociable influences on learning rate in a dynamic environment

PubMed Central

McGuire, Joseph T.; Nassar, Matthew R.; Gold, Joshua I.; Kable, Joseph W.

2015-01-01

Summary Maintaining accurate beliefs in a changing environment requires dynamically adapting the rate at which one learns from new experiences. Beliefs should be stable in the face of noisy data, but malleable in periods of change or uncertainty. Here we used computational modeling, psychophysics and fMRI to show that adaptive learning is not a unitary phenomenon in the brain. Rather, it can be decomposed into three computationally and neuroanatomically distinct factors that were evident in human subjects performing a spatial-prediction task: (1) surprise-driven belief updating, related to BOLD activity in visual cortex; (2) uncertainty-driven belief updating, related to anterior prefrontal and parietal activity; and (3) reward-driven belief updating, a context-inappropriate behavioral tendency related to activity in ventral striatum. These distinct factors converged in a core system governing adaptive learning. This system, which included dorsomedial frontal cortex, responded to all three factors and predicted belief updating both across trials and across individuals. PMID:25459409

ISS Microgravity Environment

NASA Technical Reports Server (NTRS)

Laible, Michael R.

2011-01-01

The Microgravity performance assessment of the International Space Station (ISS) is comprised of a quasi-steady, structural dynamic and a vibro-acoustic analysis of the ISS assembly-complete vehicle configuration. The Boeing Houston (BHOU) Loads and Dynamics Team is responsible to verify compliance with the ISS System Specification (SSP 41000) and USOS Segment (SSP 41162) microgravity requirements. To verify the ISS environment, a series of accelerometers are on-board to monitor the current environment. This paper summarizes the results of the analysis that was performed for the Verification Analysis Cycle (VAC)-Assembly Complete (AC) and compares it to on-orbit acceleration values currently being reported. The analysis will include the predicted maximum and average environment on-board ISS during multiple activity scenarios

Concepts for a NASA Applied Spaceflight Environments Office

NASA Technical Reports Server (NTRS)

Edwards, David L.; Burns, Howard D.; Xapsos, Michael; Spann, Jim; Suggs, Robert

2010-01-01

The National Aeronautics and Space Administration (NASA) is launching a bold and ambitious new space initiative. A significant part of this new initiative includes exploration of new worlds, the development of more innovative technologies, and expansion our presence in the solar system. A common theme to this initiative is the exploration of space beyond Low Earth Orbit (LEO). As currently organized, NASA does not have an Agency-level office that provides coordination of space environment research and development. This has contributed to the formation of a gap between spaceflight environments knowledge and the application of this knowledge for multi-program use. This paper outlines a concept to establish a NASA-level Applied Spaceflight Environments (ASE) office that will provide coordination and funding for sustained multi-program support in three technical areas that have demonstrated these needs through customer requests. These technical areas are natural environments characterization and modeling, materials and systems analysis and test, and operational space environments modeling and prediction. This paper will establish the need for the ASE, discuss a concept for organizational structure and outline the scope in the three technical areas

Shuttle payload bay thermal environments: Summary and conclusion report for STS Flights 1-5

NASA Technical Reports Server (NTRS)

Fu, J. H.; Graves, G. R.

1987-01-01

The thermal data for the payload bay of the first five shuttle flights is summarized and the engineering evaluation of that data is presented. After a general discussion on mission profiles and vehicle configurations, the thermal design and flight instrumentation systems of the payload bay are described. The thermal flight data sources and a categorization of the data are then presented. A thermal flight data summarization section provides temperature data for the five phases of a typical mission profile. These are: prelaunch, ascent, on-orbit, entry and postlanding. The thermal flight data characterization section encompasses this flight data for flight to flight variations, payload effects, temperature ranges, and other variations. Discussion of the thermal environment prediction models in use by industry and various NASA Centers, and the results predicted by these models, is followed by an evaluation of the correlation between the actual flight data and the results predicted by the models. Finally, the available thermal data are evaluated from the viewpoint of the user concerned with establishing the thermal environment in the payload bay. The data deficiencies are discussed and recommendations for their elimination are presented.

Geographic patterns of cigarette butt waste in the urban environment.

PubMed

Marah, Maacah; Novotny, Thomas E

2011-05-01

This reports the initial phase of a study to quantify the spatial pattern of cigarette butt waste in an urban environment. Geographic Information Systems (GIS) was used to create a weighted overlay analysis model which was then applied to the locations of businesses where cigarettes are sold or are likely to be consumed and venues where higher concentrations of butts may be deposited. The model's utility was tested using a small-scale litter audit in three zip codes of San Diego, California. We found that cigarette butt waste is highly concentrated around businesses where cigarettes are sold or consumed. The mean number of butts for predicted high waste sites was 38.1 (SD 18.87), for predicted low waste sites mean 4.8 (SD 5.9), p<0.001. Cigarette butt waste is not uniformly distributed in the urban environment, its distribution is linked to locations and patterns of sales and consumption. A GIS and weighted overlay model may be a useful tool in predicting urban locations of greater and lesser amounts of cigarette butt waste. These data can in turn be used to develop economic cost studies and plan mitigation strategies in urban communities.

Geographic patterns of cigarette butt waste in the urban environment

PubMed Central

Novotny, Thomas E

2011-01-01

Background This reports the initial phase of a study to quantify the spatial pattern of cigarette butt waste in an urban environment. Methods Geographic Information Systems (GIS) was used to create a weighted overlay analysis model which was then applied to the locations of businesses where cigarettes are sold or are likely to be consumed and venues where higher concentrations of butts may be deposited. The model's utility was tested using a small-scale litter audit in three zip codes of San Diego, California. Results We found that cigarette butt waste is highly concentrated around businesses where cigarettes are sold or consumed. The mean number of butts for predicted high waste sites was 38.1 (SD 18.87), for predicted low waste sites mean 4.8 (SD 5.9), p<0.001. Conclusions Cigarette butt waste is not uniformly distributed in the urban environment, its distribution is linked to locations and patterns of sales and consumption. A GIS and weighted overlay model may be a useful tool in predicting urban locations of greater and lesser amounts of cigarette butt waste. These data can in turn be used to develop economic cost studies and plan mitigation strategies in urban communities. PMID:21504924

NOAA's National Air Quality Prediction and Development of Aerosol and Atmospheric Composition Prediction Components for NGGPS

NASA Astrophysics Data System (ADS)

Stajner, I.; McQueen, J.; Lee, P.; Stein, A. F.; Wilczak, J. M.; Upadhayay, S.; daSilva, A.; Lu, C. H.; Grell, G. A.; Pierce, R. B.

2017-12-01

NOAA's operational air quality predictions of ozone, fine particulate matter (PM2.5) and wildfire smoke over the United States and airborne dust over the contiguous 48 states are distributed at http://airquality.weather.gov. The National Air Quality Forecast Capability (NAQFC) providing these predictions was updated in June 2017. Ozone and PM2.5 predictions are now produced using the system linking the Community Multiscale Air Quality model (CMAQ) version 5.0.2 with meteorological inputs from the North American Mesoscale Forecast System (NAM) version 4. Predictions of PM2.5 include intermittent dust emissions and wildfire emissions from an updated version of BlueSky system. For the latter, the CMAQ system is initialized by rerunning it over the previous 24 hours to include wildfire emissions at the time when they were observed from the satellites. Post processing to reduce the bias in PM2.5 prediction was updated using the Kalman filter analog (KFAN) technique. Dust related aerosol species at the CMAQ domain lateral boundaries now come from the NEMS Global Aerosol Component (NGAC) v2 predictions. Further development of NAQFC includes testing of CMAQ predictions to 72 hours, Canadian fire emissions data from Environment and Climate Change Canada (ECCC) and the KFAN technique to reduce bias in ozone predictions. NOAA is developing the Next Generation Global Predictions System (NGGPS) with an aerosol and gaseous atmospheric composition component to improve and integrate aerosol and ozone predictions and evaluate their impacts on physics, data assimilation and weather prediction. Efforts are underway to improve cloud microphysics, investigate aerosol effects and include representations of atmospheric composition of varying complexity into NGGPS: from the operational ozone parameterization, GOCART aerosols, with simplified ozone chemistry, to CMAQ chemistry with aerosol modules. We will present progress on community building, planning and development of NGGPS.

Quorum Sensing in Populations of Spatially Extended Chaotic Oscillators Coupled Indirectly via a Heterogeneous Environment

NASA Astrophysics Data System (ADS)

Li, Bing-Wei; Cao, Xiao-Zhi; Fu, Chenbo

2017-12-01

Many biological and chemical systems could be modeled by a population of oscillators coupled indirectly via a dynamical environment. Essentially, the environment by which the individual element communicates with each other is heterogeneous. Nevertheless, most of previous works considered the homogeneous case only. Here we investigated the dynamical behaviors in a population of spatially distributed chaotic oscillators immersed in a heterogeneous environment. Various dynamical synchronization states (such as oscillation death, phase synchronization, and complete synchronized oscillation) as well as their transitions were explored. In particular, we uncovered a non-traditional quorum sensing transition: increasing the population density leaded to a transition from oscillation death to synchronized oscillation at first, but further increasing the density resulted in degeneration from complete synchronization to phase synchronization or even from phase synchronization to desynchronization. The underlying mechanism of this finding was attributed to the dual roles played by the population density. What's more, by treating the environment as another component of the oscillator, the full system was then effectively equivalent to a locally coupled system. This fact allowed us to utilize the master stability functions approach to predict the occurrence of complete synchronization oscillation, which agreed with that from the direct numerical integration of the system. The potential candidates for the experimental realization of our model were also discussed.

Quasispecies theory for evolution of modularity.

PubMed

Park, Jeong-Man; Niestemski, Liang Ren; Deem, Michael W

2015-01-01

Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a quasispecies theory for the dynamics of modularity in populations of these systems. We show how the steady-state fitness in a randomly changing environment can be computed. We derive a fluctuation dissipation relation for the rate of change of modularity and use it to derive a relationship between rate of environmental changes and rate of growth of modularity. We also find a principle of least action for the evolved modularity at steady state. Finally, we compare our predictions to simulations of protein evolution and find them to be consistent.

Microgravity vibration isolation technology: Development to demonstration. Ph.D. Thesis - Case Western Reserve Univ.

NASA Technical Reports Server (NTRS)

Grodsinsky, Carlos M.

1993-01-01

The low gravity environment provided by space flight has afforded the science community a unique area for the study of fundamental and technological sciences. However, the dynamic environment observed on space shuttle flights and predicted for Space Station Freedom has complicated the analysis of prior 'microgravity' experiments and prompted concern for the viability of proposed space experiments requiring long term, low gravity environments. Thus, isolation systems capable of providing significant improvements to this random environment have been developed. This dissertation deals with the design constraints imposed by acceleration sensitive, microgravity experiment payloads in the unique environment of space. A theoretical background for the inertial feedback and feedforward isolation of a payload was developed giving the basis for two experimental active inertial isolation systems developed for the demonstration of these advanced active isolation techniques. A prototype six degree of freedom digital active isolation system was designed and developed for the ground based testing of an actively isolated payload in three horizontal degrees of freedom. A second functionally equivalent system was built for the multi-dimensional testing of an active inertial isolation system in a reduced gravity environment during low gravity aircraft trajectories. These multi-input multi-output control systems are discussed in detail with estimates on acceleration noise floor performance as well as the actual performance acceleration data. The attenuation performance is also given for both systems demonstrating the advantages between inertial and non-inertial control of a payload for both the ground base environment and the low gravity aircraft acceleration environment. A future goal for this area of research is to validate the technical approaches developed to the 0.01 Hz regime by demonstrating a functional active inertial feedforward/feedback isolation system during orbital flight. A NASA IN-STEP flight experiment has been proposed to accomplish this goal, and the expected selection for the IN-STEP program has been set for Jul. of 1993.

Program Aids Design Of Fluid-Circulating Systems

NASA Technical Reports Server (NTRS)

Bacskay, Allen; Dalee, Robert

1992-01-01

Computer Aided Systems Engineering and Analysis (CASE/A) program is interactive software tool for trade study and analysis, designed to increase productivity during all phases of systems engineering. Graphics-based command-driven software package provides user-friendly computing environment in which engineer analyzes performance and interface characteristics of ECLS/ATC system. Useful during all phases of spacecraft-design program, from initial conceptual design trade studies to actual flight, including pre-flight prediction and in-flight analysis of anomalies. Written in FORTRAN 77.

Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

NASA Technical Reports Server (NTRS)

Jules, Kenol; Lin, Paul P.

2006-01-01

One of the responsibilities of the NASA Glenn Principal Investigator Microgravity Services is to support NASA sponsored investigators in the area of reduced-gravity acceleration data analysis, interpretation and the monitoring of the reduced-gravity environment on-board various carriers. With the International Space Station currently operational, a significant amount of acceleration data is being down-linked and processed on ground for both the space station onboard environment characterization (and verification) and scientific experiments. Therefore, to help principal investigator teams monitor the acceleration level on-board the International Space Station to avoid undesirable impact on their experiment, when possible, the NASA Glenn Principal Investigator Microgravity Services developed an artificial intelligence monitoring system, which detects in near real time any change in the environment susceptible to affect onboard experiments. The main objective of the monitoring system is to help research teams identify the vibratory disturbances that are active at any instant of time onboard the International Space Station that might impact the environment in which their experiment is being conducted. The monitoring system allows any space research scientist, at any location and at any time, to see the current acceleration level on-board the Space Station via the World Wide Web. From the NASA Glenn s Exploration Systems Division web site, research scientists can see in near real time the active disturbances, such as pumps, fans, compressor, crew exercise, re-boost, extra-vehicular activity, etc., and decide whether or not to continue operating or stopping (or making note of such activity for later correlation with science results) their experiments based on the g-level associated with that specific event. A dynamic graphical display accessible via the World Wide Web shows the status of all the vibratory disturbance activities with their degree of confidence as well as their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Analysis of electromagnetic interference from power system processing and transmission components for Space Station Freedom

NASA Technical Reports Server (NTRS)

Barber, Peter W.; Demerdash, Nabeel A. O.; Wang, R.; Hurysz, B.; Luo, Z.

1991-01-01

The goal is to analyze the potential effects of electromagnetic interference (EMI) originating from power system processing and transmission components for Space Station Freedom.The approach consists of four steps: (1) develop analytical tools (models and computer programs); (2) conduct parameterization studies; (3) predict the global space station EMI environment; and (4) provide a basis for modification of EMI standards.

The Use of an Online Learning and Teaching System for Monitoring Computer Aided Design Student Participation and Predicting Student Success

ERIC Educational Resources Information Center

Akhtar, S.; Warburton, S.; Xu, W.

2017-01-01

In this paper we report on the use of a purpose built Computer Support Collaborative learning environment designed to support lab-based CAD teaching through the monitoring of student participation and identified predictors of success. This was carried out by analysing data from the interactive learning system and correlating student behaviour with…

Formation of Planetary Systems

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; DeVincenzi, Donald (Technical Monitor)

1999-01-01

An overview of current theories of star and planet formation is presented. These models are based upon observations of the Solar System and of young stars and their environments. They predict that rocky planets should form around most single stars, although it is possible that in some cases such planets are lost to orbital decay within the protoplanetary disk. The frequency of formation of gas giant planets is more difficult to predict theoretically. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant planets begin their growth like terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates.

The Birth of Planetary Systems

NASA Technical Reports Server (NTRS)

Lissaur, Jack L.

1997-01-01

An overview of current theories of star and planet formation is presented. These models are based upon observations of the Solar System and of young stars and their environments. They predict that rocky planets should form around most single stars, although it is possible that in some cases such planets are lost to orbital decay within the protoplanetary disk. The frequency of formation of gas giant planets is more difficult to predict theoretically. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant planets begin their growth like terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates.

Family-supportive work environments and psychological strain: a longitudinal test of two theories.

PubMed

Odle-Dusseau, Heather N; Herleman, Hailey A; Britt, Thomas W; Moore, Dewayne D; Castro, Carl A; McGurk, Dennis

2013-01-01

Based on the Job Demands-Resources (JDR) model (E. Demerouti, A. B. Bakker, F. Nachreiner, & W. B. Schaufeli, 2001, The job demands-resources model of burnout. Journal of Applied Psychology, 86, 499-512) and Conservation of Resources (COR) theory (S. E. Hobfoll, 2002, Social and psychological resources and adaptation. Review of General Psychology, 6, 307-324), we tested three competing models that predict different directions of causation for relationships over time between family-supportive work environments (FSWE) and psychological strain, with two waves of data from a military sample. Results revealed support for both the JDR and COR theories, first in the static model where FSWE at Time 1 predicted psychological strain at Time 2 and when testing the opposite direction, where psychological strain at Time 1 predicted FSWE at Time 2. For change models, FSWE predicted changes in psychological strain across time, although the reverse causation model was not supported (psychological strain at Time 1 did not predict changes in FSWE). Also, changes in FSWE across time predicted psychological strain at Time 2, whereas changes in psychological strain did not predict FSWE at Time 2. Theoretically, these results are important for the work-family interface in that they demonstrate the application of a systems approach to studying work and family interactions, as support was obtained for both the JDR model with perceptions of FSWE predicting psychological strain (in both the static and change models), and for COR theory where psychological strain predicts FSWE across time.

Source Data Impacts on Epistemic Uncertainty for Launch Vehicle Fault Tree Models

NASA Technical Reports Server (NTRS)

Al Hassan, Mohammad; Novack, Steven; Ring, Robert

2016-01-01

Launch vehicle systems are designed and developed using both heritage and new hardware. Design modifications to the heritage hardware to fit new functional system requirements can impact the applicability of heritage reliability data. Risk estimates for newly designed systems must be developed from generic data sources such as commercially available reliability databases using reliability prediction methodologies, such as those addressed in MIL-HDBK-217F. Failure estimates must be converted from the generic environment to the specific operating environment of the system in which it is used. In addition, some qualification of applicability for the data source to the current system should be made. Characterizing data applicability under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This paper will demonstrate a data-source applicability classification method for suggesting epistemic component uncertainty to a target vehicle based on the source and operating environment of the originating data. The source applicability is determined using heuristic guidelines while translation of operating environments is accomplished by applying statistical methods to MIL-HDK-217F tables. The paper will provide one example for assigning environmental factors uncertainty when translating between operating environments for the microelectronic part-type components. The heuristic guidelines will be followed by uncertainty-importance routines to assess the need for more applicable data to reduce model uncertainty.

Aerothermodynamic Environments Definition for the Mars Science Laboratory Entry Capsule

NASA Technical Reports Server (NTRS)

Edquist, Karl T.; Dyakonov, Artem A.; Wright, Michael J.; Tang, Chun Y.

2007-01-01

An overview of the aerothermodynamic environments definition status is presented for the Mars Science Laboratory entry vehicle. The environments are based on Navier-Stokes flowfield simulations on a candidate aeroshell geometry and worst-case entry heating trajectories. Uncertainties for the flowfield predictions are based primarily on available ground data since Mars flight data are scarce. The forebody aerothermodynamics analysis focuses on boundary layer transition and turbulent heating augmentation. Turbulent transition is expected prior to peak heating, a first for Mars entry, resulting in augmented heat flux and shear stress at the same heatshield location. Afterbody computations are also shown with and without interference effects of reaction control system thruster plumes. Including uncertainties, analysis predicts that the heatshield may experience peaks of 225 W/sq cm for turbulent heat flux, 0.32 atm for stagnation pressure, and 400 Pa for turbulent shear stress. The afterbody heat flux without thruster plume interference is predicted to be 7 W/sq cm on the backshell and 10 W/sq cm on the parachute cover. If the reaction control jets are fired near peak dynamic pressure, the heat flux at localized areas could reach as high as 76 W/sq cm on the backshell and 38 W/sq cm on the parachute cover, including uncertainties. The final flight environments used for hardware design will be updated for any changes in the aeroshell configuration, heating design trajectories, or uncertainties.

Predicting In-Situ X-ray Diffraction for the SrTiO3/Liquid Interface from First Principles

NASA Astrophysics Data System (ADS)

Letchworth-Weaver, Kendra; Gunceler, Deniz; Sundararaman, Ravishankar; Huang, Xin; Brock, Joel; Arias, T. A.

2013-03-01

Recent advances in experimental techniques, such as in-situ x-ray diffraction, allow researchers to probe the solid-liquid interface in electrochemical systems under operating conditions. These advances offer an unprecedented opportunity for theory to predict properties of electrode materials in aqueous environments and inform the design of energy conversion and storage devices. To compare with experiment, these theoretical studies require microscopic details of both the liquid and the electrode surface. Joint Density Functional Theory (JDFT), a computationally efficient alternative to molecular dynamics, couples a classical density-functional, which captures molecular structure of the liquid, to a quantum-mechanical functional for the electrode surface. We present a JDFT exploration of SrTiO3, which can catalyze solar-driven water splitting, in an electrochemical environment. We determine the geometry of the polar SrTiO3 surface and the equilibrium structure of the contacting liquid, as well as the influence of the liquid upon the electronic structure of the surface. We then predict the effect of the fluid environment on x-ray diffraction patterns and compare our predictions to in-situ measurements performed at the Cornell High Energy Synchrotron Source (CHESS). This material is based upon work supported by the Energy Materials Center at Cornell (EMC2), an Energy Frontier Research Center funded by the U.S. Department of Energy.

AGGREGATED FILTER-FEEDING CONSUMERS ALTER NUTRIENT LIMITATION: CONSEQUENCES FOR ECOSYSTEM AND COMMUNITY DYNAMICS

EPA Science Inventory

Nutrient cycling is a key process that ties all organisms together. This is especially apparent in stream environments in which nutrients are taken up readily and cycled through the system in a downstream trajectory. Ecological stoichiometry predicts that biogeochemical cycles of...

System, Scholar or Students? Which Most Influences Online MBA Course Effectiveness?

ERIC Educational Resources Information Center

Arbaugh, J. B.

2014-01-01

Considering the increasingly challenging resource environments in many business schools, this study examined whether course technologies, learner behaviors or instructor behaviors best predict online course outcomes so that administrators and support personnel can prioritize their efforts and investments. Based on reviewing prior online and…

Managing Knowledge to Save the Environment.

ERIC Educational Resources Information Center

Bundy, McGeorge

Discussed are the ways in which modern data analysis can increase understanding of complex interrelationships in natural and manmade systems, thus enhancing the rationality of decision-making. Examples are given of predictions made from economic and ecological models. The need for international cooperation on environmental questions is discussed…

Dynamic response tests of inertial and optical wind-tunnel model attitude measurement devices

NASA Technical Reports Server (NTRS)

Buehrle, R. D.; Young, C. P., Jr.; Burner, A. W.; Tripp, J. S.; Tcheng, P.; Finley, T. D.; Popernack, T. G., Jr.

1995-01-01

Results are presented for an experimental study of the response of inertial and optical wind-tunnel model attitude measurement systems in a wind-off simulated dynamic environment. This study is part of an ongoing activity at the NASA Langley Research Center to develop high accuracy, advanced model attitude measurement systems that can be used in a dynamic wind-tunnel environment. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration which results in a model attitude measurement bias error. Significant bias errors in model attitude measurement were found for the measurement using the inertial device during wind-off dynamic testing of a model system. The amount of bias present during wind-tunnel tests will depend on the amplitudes of the model dynamic response and the modal characteristics of the model system. Correction models are presented that predict the vibration-induced bias errors to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment. The optical system results were uncorrupted by model vibration in the laboratory setup.

Development of Advanced Environmental Barrier Coatings for SiC/SiC Composites at NASA GRC: Prime-Reliant Design and Durability Perspectives

NASA Technical Reports Server (NTRS)

Zhu, Dongming

2017-01-01

Environmental barrier coatings (EBCs) are considered technologically important because of the critical needs and their ability to effectively protect the turbine hot-section SiC/SiC ceramic matrix composite (CMC) components in harsh engine combustion environments. The development of NASA's advanced environmental barrier coatings have been aimed at significantly improved the coating system temperature capability, stability, erosion-impact, and CMAS resistance for SiC/SiC turbine airfoil and combustors component applications. The NASA environmental barrier coating developments have also emphasized thermo-mechanical creep and fatigue resistance in simulated engine heat flux and environments. Experimental results and models for advanced EBC systems will be presented to help establishing advanced EBC composition design methodologies, performance modeling and life predictions, for achieving prime-reliant, durable environmental coating systems for 2700-3000 F engine component applications. Major technical barriers in developing environmental barrier coating systems and the coating integration with next generation composites having further improved temperature capability, environmental stability, EBC-CMC fatigue-environment system durability will be discussed.

Estimation of the Driving Style Based on the Users' Activity and Environment Influence.

PubMed

Sysoev, Mikhail; Kos, Andrej; Guna, Jože; Pogačnik, Matevž

2017-10-21

New models and methods have been designed to predict the influence of the user's environment and activity information to the driving style in standard automotive environments. For these purposes, an experiment was conducted providing two types of analysis: (i) the evaluation of a self-assessment of the driving style; (ii) the prediction of aggressive driving style based on drivers' activity and environment parameters. Sixty seven h of driving data from 10 drivers were collected for analysis in this study. The new parameters used in the experiment are the car door opening and closing manner, which were applied to improve the prediction accuracy. An Android application called Sensoric was developed to collect low-level smartphone data about the users' activity. The driving style was predicted from the user's environment and activity data collected before driving. The prediction was tested against the actual driving style, calculated from objective driving data. The prediction has shown encouraging results, with precision values ranging from 0.727 up to 0.909 for aggressive driving recognition rate. The obtained results lend support to the hypothesis that user's environment and activity data could be used for the prediction of the aggressive driving style in advance, before the driving starts.

Verification of Ares I Liftoff Acoustic Environments via the Ares I Scale Model Acoustic Test

NASA Technical Reports Server (NTRS)

Counter, Douglas; Houston, Janice

2012-01-01

The Ares I Scale Model Acoustic Test (ASMAT) program was implemented to verify the predicted Ares I liftoff acoustic environments and to determine the acoustic reduction gained by using an above deck water sound suppression system. The test article included a 5% scale Ares I vehicle model and Mobile Launcher with tower. Acoustic and pressure data were measured by over 200 instruments. The ASMAT results are compared to Ares I-X flight data.

Using a neural network approach and time series data from an international monitoring station in the Yellow Sea for modeling marine ecosystems.

PubMed

Zhang, Yingying; Wang, Juncheng; Vorontsov, A M; Hou, Guangli; Nikanorova, M N; Wang, Hongliang

2014-01-01

The international marine ecological safety monitoring demonstration station in the Yellow Sea was developed as a collaborative project between China and Russia. It is a nonprofit technical workstation designed as a facility for marine scientific research for public welfare. By undertaking long-term monitoring of the marine environment and automatic data collection, this station will provide valuable information for marine ecological protection and disaster prevention and reduction. The results of some initial research by scientists at the research station into predictive modeling of marine ecological environments and early warning are described in this paper. Marine ecological processes are influenced by many factors including hydrological and meteorological conditions, biological factors, and human activities. Consequently, it is very difficult to incorporate all these influences and their interactions in a deterministic or analysis model. A prediction model integrating a time series prediction approach with neural network nonlinear modeling is proposed for marine ecological parameters. The model explores the natural fluctuations in marine ecological parameters by learning from the latest observed data automatically, and then predicting future values of the parameter. The model is updated in a "rolling" fashion with new observed data from the monitoring station. Prediction experiments results showed that the neural network prediction model based on time series data is effective for marine ecological prediction and can be used for the development of early warning systems.

Performance of a coupled lagged ensemble weather and river runoff prediction model system for the Alpine Ammer River catchment

NASA Astrophysics Data System (ADS)

Smiatek, G.; Kunstmann, H.; Werhahn, J.

2012-04-01

The Ammer River catchment located in the Bavarian Ammergau Alps and alpine forelands, Germany, represents with elevations reaching 2185 m and annual mean precipitation between1100 and 2000 mm a very demanding test ground for a river runoff prediction system. Large flooding events in 1999 and 2005 motivated the development of a physically based prediction tool in this area. Such a tool is the coupled high resolution numerical weather and river runoff forecasting system AM-POE that is being studied in several configurations in various experiments starting from the year 2005. Corner stones of the coupled system are the hydrological water balance model WaSiM-ETH run at 100 m grid resolution, the numerical weather prediction model (NWP) MM5 driven at 3.5 km grid cell resolution and the Perl Object Environment (POE) framework. POE implements the input data download from various sources, the input data provision via SOAP based WEB services as well as the runs of the hydrology model both with observed and with NWP predicted meteorology input. The one way coupled system utilizes a lagged ensemble prediction system (EPS) taking into account combination of recent and previous NWP forecasts. Results obtained in the years 2005-2011 reveal that river runoff simulations depict high correlation with observed runoff when driven with monitored observations in hindcast experiments. The ability to runoff forecasts is depending on lead times in the lagged ensemble prediction and shows still limitations resulting from errors in timing and total amount of the predicted precipitation in the complex mountainous area. The presentation describes the system implementation, and demonstrates the application of the POE framework in networking, distributed computing and in the setup of various experiments as well as long term results of the system application in the years 2005 - 2011.

A cooperative model for IS security risk management in distributed environment.

PubMed

Feng, Nan; Zheng, Chundong

2014-01-01

Given the increasing cooperation between organizations, the flexible exchange of security information across the allied organizations is critical to effectively manage information systems (IS) security in a distributed environment. In this paper, we develop a cooperative model for IS security risk management in a distributed environment. In the proposed model, the exchange of security information among the interconnected IS under distributed environment is supported by Bayesian networks (BNs). In addition, for an organization's IS, a BN is utilized to represent its security environment and dynamically predict its security risk level, by which the security manager can select an optimal action to safeguard the firm's information resources. The actual case studied illustrates the cooperative model presented in this paper and how it can be exploited to manage the distributed IS security risk effectively.

The effects of parental education and family income on mother-child relationships, father-child relationships, and family environments in the People's Republic of China.

PubMed

Zhang, Xiao

2012-12-01

Using a cross-sectional design with 407 Chinese children aged 3-5 years and their parents, this study examined the effects of socioeconomic status, specifically parents' education and family income, on the children's mother-child relationships, father-child relationships, and the social environment in their families. The results indicated that income negatively predicted conflict in father-child relationships and positively predicted family active-recreational environments. Income also positively predicted family cohesion among girls but not boys. Maternal education negatively predicted conflict in mother-child relationships and positively predicted closeness in mother-child and father-child relationships, family cohesion, and the intellectual-cultural and active-recreational environments in the family. Paternal education positively predicted family cohesion and intellectual-cultural and active-recreational environments. Income was found to partially mediate the effects of both maternal and paternal education on family active-recreational environments. Findings are discussed in the frameworks of the family stress model and the family investment model. © FPI, Inc.

Detecting Controller Malfunctions in Electromagnetic Environments. Part 1; Modeling and Estimation of Nominal System Function

NASA Technical Reports Server (NTRS)

Weinstein, Bernice

1999-01-01

A strategy for detecting control law calculation errors in critical flight control computers during laboratory validation testing is presented. This paper addresses Part I of the detection strategy which involves the use of modeling of the aircraft control laws and the design of Kalman filters to predict the correct control commands. Part II of the strategy which involves the use of the predicted control commands to detect control command errors is presented in the companion paper.

Models for the indices of thermal comfort

PubMed Central

Adrian, Streinu-Cercel; Sergiu, Costoiu; Maria, Mârza; Anca, Streinu-Cercel; Monica, Mârza

2008-01-01

The current paper propose the analysis and extension formulation required for establishing decision in the management of the medical national system from the point of view of quality and efficiency such as: conceiving models for the indices of thermal comfort, defining the predicted mean vote (on the thermal sensation scale) „PMV”, defining the metabolism „M”, heat transfer between the human body and the environment, defining the predicted percent of dissatisfied people „PPD”, defining all indices of thermal comfort. PMID:20108461

Options of system integrated environment modelling in the predicated dynamic cyberspace

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

Janková, Martina; Dvořák, Jiří

In this article there are briefly mentioned some selected options of contemporary conception of cybernetic system models in the corresponding and possible integratable environment with modern system dynamics thinking and all this in the cyberspace of possible projecting of predicted system characteristics. The key to new capabilities of system integration modelling in the considered cyberspace is mainly the ability to improve the environment and the system integration options, all this with the aim of modern control in the hierarchically arranged dynamic cyberspace, e.g. in the currently desired electronic business with information. The aim of this article is to assess generallymore » the trends in the use of modern modelling methods considering the cybernetics applications verified in practice, modern concept of project management and also the potential integration of artificial intelligence in the new projecting and project management of integratable and intelligent models, e.g. with the optimal structures and adaptable behaviour.The article results from the solution of a specific research partial task at the faculty; especially the moments proving that the new economics will be based more and more on information, knowledge system defined cyberspace of modern management, are stressed in the text.« less

Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia

PubMed Central

Eastin, Matthew D.; Delmelle, Eric; Casas, Irene; Wexler, Joshua; Self, Cameron

2014-01-01

Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors—all of which are influenced by environmental factors. Predictive models of dengue incidence rate, based on local weather and regional climate parameters, could benefit disease mitigation efforts. Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011. Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C—the optimal range for mosquito survival and viral transmission. Two environment-based, multivariate, autoregressive forecast models are developed that allow dengue outbreaks to be anticipated from 2 weeks to 6 months in advance. These models have the potential to enhance existing dengue early warning systems, ultimately supporting public health decisions on the timing and scale of vector control efforts. PMID:24957546

Assessment of Suited Reach Envelope in an Underwater Environment

NASA Technical Reports Server (NTRS)

Kim, Han; Benson, Elizabeth; Bernal, Yaritza; Jarvis, Sarah; Meginnis, Ian; Rajulu, Sudhakar

2017-01-01

Predicting the performance of a crewmember in an extravehicular activity (EVA) space suit presents unique challenges. The kinematic patterns of suited motions are difficult to reproduce in gravity. Additionally, 3-D suited kinematics have been practically and technically difficult to quantify in an underwater environment, in which crewmembers are commonly trained and assessed for performance. The goal of this study is to develop a hardware and software system to predictively evaluate the kinematic mobility of suited crewmembers, by measuring the 3-D reach envelope of the suit in an underwater environment. This work is ultimately aimed at developing quantitative metrics to compare the mobility of the existing Extravehicular Mobility Unit (EMU) to newly developed space suit, such as the Z-2. The EMU has been extensively used at NASA since 1981 for EVA outside the Space Shuttle and International Space Station. The Z-2 suit is NASA's newest prototype space suit. The suit is comprised of new upper torso and lower torso architectures, which were designed to improve test subject mobility.

Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system

NASA Astrophysics Data System (ADS)

Jašek, Roman; Dvořák, Jiří; Janková, Martina; Sedláček, Michal

2016-06-01

This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements' own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.

Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system

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

Jašek, Roman; Dvořák, Jiří; Janková, Martina

This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen heremore » as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements’ own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.« less

Source Data Applicability Impacts on Epistemic Uncertainty for Launch Vehicle Fault Tree Models

NASA Technical Reports Server (NTRS)

Al Hassan, Mohammad; Novack, Steven D.; Ring, Robert W.

2016-01-01

Launch vehicle systems are designed and developed using both heritage and new hardware. Design modifications to the heritage hardware to fit new functional system requirements can impact the applicability of heritage reliability data. Risk estimates for newly designed systems must be developed from generic data sources such as commercially available reliability databases using reliability prediction methodologies, such as those addressed in MIL-HDBK-217F. Failure estimates must be converted from the generic environment to the specific operating environment of the system where it is used. In addition, some qualification of applicability for the data source to the current system should be made. Characterizing data applicability under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This paper will demonstrate a data-source applicability classification method for assigning uncertainty to a target vehicle based on the source and operating environment of the originating data. The source applicability is determined using heuristic guidelines while translation of operating environments is accomplished by applying statistical methods to MIL-HDK-217F tables. The paper will provide a case study example by translating Ground Benign (GB) and Ground Mobile (GM) to the Airborne Uninhabited Fighter (AUF) environment for three electronic components often found in space launch vehicle control systems. The classification method will be followed by uncertainty-importance routines to assess the need to for more applicable data to reduce uncertainty.

Quantum Coherent Dynamics Enhanced by Synchronization with Nonequilibrium Environments

NASA Astrophysics Data System (ADS)

Ishikawa, Akira; Okada, Ryo; Uchiyama, Kazuharu; Hori, Hirokazu; Kobayashi, Kiyoshi

2018-05-01

We report the discovery of the anomalous enhancement of quantum coherent dynamics (CD) due to a non-Markovian mechanism originating from not thermal-equilibrium phonon baths but nonequilibrium coherent phonons. CD is an elementary process for quantum phenomena in nanosystems, such as excitation transfer (ET) in semiconductor nanostructures and light-harvesting systems. CD occurs in homogeneous nanosystems because system inhomogeneity typically destroys coherence. In real systems, however, nanosystems behave as open systems surrounded by environments such as phonon systems. Typically, CD in inhomogeneous nanosystems is enhanced by the absorption and emission of thermal-equilibrium phonons, and the enhancement is described by the conventional master equation. On the other hand, CD is also enhanced by synchronization between population dynamics in nanosystems and coherent phonons; namely, coherent phonons, which are self-consistently induced by phase matching with Rabi oscillation, are fed back to enhance CD. This anomalous enhancement of CD essentially originates from the nonequilibrium and dynamical non-Markovian nature of coherent phonon environments, and the enhancement is firstly predicted by applying time-dependent projection operators to nonequilibrium and dynamical environments. Moreover, CD is discussed by considering ET from a donor to an acceptor. It is found that the enhancement of ET by synchronization with coherent phonons depends on the competition between the output time from a system to an acceptor and the formation time of coherent phonons. These findings in this study will stimulate the design and manipulation of CD via structured environments from the viewpoint of application to nano-photoelectronic devices.

Cloud-based Predictive Modeling System and its Application to Asthma Readmission Prediction

PubMed Central

Chen, Robert; Su, Hang; Khalilia, Mohammed; Lin, Sizhe; Peng, Yue; Davis, Tod; Hirsh, Daniel A; Searles, Elizabeth; Tejedor-Sojo, Javier; Thompson, Michael; Sun, Jimeng

2015-01-01

The predictive modeling process is time consuming and requires clinical researchers to handle complex electronic health record (EHR) data in restricted computational environments. To address this problem, we implemented a cloud-based predictive modeling system via a hybrid setup combining a secure private server with the Amazon Web Services (AWS) Elastic MapReduce platform. EHR data is preprocessed on a private server and the resulting de-identified event sequences are hosted on AWS. Based on user-specified modeling configurations, an on-demand web service launches a cluster of Elastic Compute 2 (EC2) instances on AWS to perform feature selection and classification algorithms in a distributed fashion. Afterwards, the secure private server aggregates results and displays them via interactive visualization. We tested the system on a pediatric asthma readmission task on a de-identified EHR dataset of 2,967 patients. We conduct a larger scale experiment on the CMS Linkable 2008–2010 Medicare Data Entrepreneurs’ Synthetic Public Use File dataset of 2 million patients, which achieves over 25-fold speedup compared to sequential execution. PMID:26958172

Review of biased solar array - Plasma interaction studies

NASA Technical Reports Server (NTRS)

Stevens, N. J.

1981-01-01

Possible high voltage surface interactions on the Solar Electric Propulsion System (SEPS) are examined, with particular regard for potential effects on SEPS performance. The SEPS is intended for use for geosynchronous and planetary missions, and derives power from deployed solar cell arrays which are susceptible to collecting ions and electrons from the charged and thermal particle environment of space. The charge exchange plasma which provides the thrust force can also enhance the natural charged particle environment and increase interactions between the thrust system and the biased solar array surface. Tests of small arrays have shown that snapover, where current collection becomes proportional to the panel area, can be avoided by larger cell sizes. Arcing is predicted to diminish with larger array sizes, while the problems of efflux environments are noted to be as yet undefined and require further study.

An integrated approach to rotorcraft human factors research

NASA Technical Reports Server (NTRS)

Hart, Sandra G.; Hartzell, E. James; Voorhees, James W.; Bucher, Nancy M.; Shively, R. Jay

1988-01-01

As the potential of civil and military helicopters has increased, more complex and demanding missions in increasingly hostile environments have been required. Users, designers, and manufacturers have an urgent need for information about human behavior and function to create systems that take advantage of human capabilities, without overloading them. Because there is a large gap between what is known about human behavior and the information needed to predict pilot workload and performance in the complex missions projected for pilots of advanced helicopters, Army and NASA scientists are actively engaged in Human Factors Research at Ames. The research ranges from laboratory experiments to computational modeling, simulation evaluation, and inflight testing. Information obtained in highly controlled but simpler environments generates predictions which can be tested in more realistic situations. These results are used, in turn, to refine theoretical models, provide the focus for subsequent research, and ensure operational relevance, while maintaining predictive advantages. The advantages and disadvantages of each type of research are described along with examples of experimental results.

Convective Heating Predictions of Apollo IV Flight Data

NASA Technical Reports Server (NTRS)

White, Molly E.

2012-01-01

It has been more than 50 years since NASA engineers have attempted to design a manned space vehicle with the capability to return from beyond low Earth orbit. In this interval, our methodologies for designing the thermal protection system (TPS) to protect humans from the extremely high temperatures of re-entry have changed significantly. With these considerations in mind, we return to the Apollo IV (AS-501) flight data. This incredible data set allows us to assess the current tools and methodologies being used to design Orion MPCV. In particular, our ability to predict the aftbody separated region convective heating environments for MPCV is critical. The design uses reusable TPS in this area, whereas Apollo designers used ablative TPS which can withstand much more severe environments. This presentation will revisit the flight data, summarize the assumptions going into the analysis, present the results and draw conclusions regarding how accurately we can currently predict the heating in the aftbody separated region of a re-entry capsule.

[Application of predictive model to estimate concentrations of chemical substances in the work environment].

PubMed

Kupczewska-Dobecka, Małgorzata; Czerczak, Sławomir; Jakubowski, Marek; Maciaszek, Piotr; Janasik, Beata

2010-01-01

Based on the Estimation and Assessment of Substance Exposure (EASE) predictive model implemented into the European Union System for the Evaluation of Substances (EUSES 2.1.), the exposure to three chosen organic solvents: toluene, ethyl acetate and acetone was estimated and compared with the results of measurements in workplaces. Prior to validation, the EASE model was pretested using three exposure scenarios. The scenarios differed in the decision tree of pattern of use. Five substances were chosen for the test: 1,4-dioxane tert-methyl-butyl ether, diethylamine, 1,1,1-trichloroethane and bisphenol A. After testing the EASE model, the next step was the validation by estimating the exposure level and comparing it with the results of measurements in the workplace. We used the results of measurements of toluene, ethyl acetate and acetone concentrations in the work environment of a paint and lacquer factory, a shoe factory and a refinery. Three types of exposure scenarios, adaptable to the description of working conditions were chosen to estimate inhalation exposure. Comparison of calculated exposure to toluene, ethyl acetate and acetone with measurements in workplaces showed that model predictions are comparable with the measurement results. Only for low concentration ranges, the measured concentrations were higher than those predicted. EASE is a clear, consistent system, which can be successfully used as an additional component of inhalation exposure estimation. If the measurement data are available, they should be preferred to values estimated from models. In addition to inhalation exposure estimation, the EASE model makes it possible not only to assess exposure-related risk but also to predict workers' dermal exposure.

Systems level test and simulation for photonic processing systems

NASA Astrophysics Data System (ADS)

Erteza, I. A.; Stalker, K. T.

1995-08-01

Photonic technology is growing in importance throughout DOD. Programs have been underway in each of the Services to demonstrate the ability of photonics to enhance current electronic performance in several prototype systems, such as the Navy's SLQ-32 radar warning receiver, the Army's multi-role survivable radar and the phased array radar controller for the Airborne Warning and Control System (AWACS) upgrade. Little, though, is known about radiation effects; the component studies do not furnish the information needed to predict overall system performance in a radiation environment. To date, no comprehensive test and analysis program has been conducted to evaluate sensitivity of overall system performance to the radiation environment. The goal of this program is to relate component level effects to system level performance through modeling and testing of a selected optical processing system, and to help direct component testing to items which can directly and adversely affect overall system performance. This report gives a broad overview of the project, highlighting key results.

IMPORTANCE OF THE DYNAMICS OF BACTERIOPHAGE-HOST INTERACTIONS TO BACTERIAL ABUNDANCE AND GENETIC DIVERSITY IN AQUATIC ENVIRONMENTS (RESEARCH BRIEF)

EPA Science Inventory

Using Pseudomonas aeruginosa and its bacteriophages as a model system, we have clearly demonstrated a significant potential for viral-mediated gene transfer (transduction) of both plasmid and chromosomal DNA in freshwater microbial populations. These investigations have predicted...

Use of the Chemical Transformation Simulator as a Parameterization Tool for Modeling the Environmental Fate of Organic Chemicals and their Transformation Products

EPA Science Inventory

A Chemical Transformation Simulator is a web-based system for predicting transformation pathways and physicochemical properties of organic chemicals. Role in Environmental Modeling • Screening tool for identifying likely transformation products in the environment • Parameteri...

Infants' Grip Strength Predicts Mu Rhythm Attenuation during Observation of Lifting Actions with Weighted Blocks

ERIC Educational Resources Information Center

Upshaw, Michaela B.; Bernier, Raphael A.; Sommerville, Jessica A.

2016-01-01

Research has established that the body is fundamentally involved in perception: bodily experience influences activation of the shared neural system underlying action perception and production during action observation, and bodily characteristics influence perception of the spatial environment. However, whether bodily characteristics influence…

Neural network applications in telecommunications

NASA Technical Reports Server (NTRS)

Alspector, Joshua

1994-01-01

Neural network capabilities include automatic and organized handling of complex information, quick adaptation to continuously changing environments, nonlinear modeling, and parallel implementation. This viewgraph presentation presents Bellcore work on applications, learning chip computational function, learning system block diagram, neural network equalization, broadband access control, calling-card fraud detection, software reliability prediction, and conclusions.

Transformation of Installation Management: An Analysis of Organizational Change

DTIC Science & Technology

2006-03-15

New York: McGraw-Hill Publishing Company, 1985), 112-113. This text compares interaction of a biological system in a physical environment with...his thesis very accurately predicted the economic shock that faced U.S. businesses in the early 1990s. John Naisbitt, Megatrends : Ten New Directions

Assessing Readiness for Online Education--Research Models for Identifying Students at Risk

ERIC Educational Resources Information Center

Wladis, Claire; Conway, Katherine M.; Hachey, Alyse C.

2016-01-01

This study explored the interaction between student characteristics and the online environment in predicting course performance and subsequent college persistence among students in a large urban U.S. university system. Multilevel modeling, propensity score matching, and the KHB decomposition method were used. The most consistent pattern observed…

THEORETICAL DEVELOPMENT AND ANALYTICAL SOLUTIONS FOR TRANSPORT OF VOLATILE ORGANIC COMPOUNDS IN DUAL-POROSITY SOILS

EPA Science Inventory

Predicting the behavior of volatile organic compounds in soils or sediments is necessary for managing their use and designing appropriate remedial systems to eliminate potential threats to the environment, particularly the air and groundwater resources. In this effort, based on c...

Lateral habenula neurons signal errors in the prediction of reward information

PubMed Central

Bromberg-Martin, Ethan S.; Hikosaka, Okihide

2011-01-01

Humans and animals have a remarkable ability to predict future events, which they achieve by persistently searching their environment for sources of predictive information. Yet little is known about the neural systems that motivate this behavior. We hypothesized that information-seeking is assigned value by the same circuits that support reward-seeking, so that neural signals encoding conventional “reward prediction errors” include analogous “information prediction errors”. To test this we recorded from neurons in the lateral habenula, a nucleus which encodes reward prediction errors, while monkeys chose between cues that provided different amounts of information about upcoming rewards. We found that a subpopulation of lateral habenula neurons transmitted signals resembling information prediction errors, responding when reward information was unexpectedly cued, delivered, or denied. Their signals evaluated information sources reliably even when the animal’s decisions did not. These neurons could provide a common instructive signal for reward-seeking and information-seeking behavior. PMID:21857659

Using Temporal Correlations and Full Distributions to Separate Intrinsic and Extrinsic Fluctuations in Biological Systems

NASA Astrophysics Data System (ADS)

Hilfinger, Andreas; Chen, Mark; Paulsson, Johan

2012-12-01

Studies of stochastic biological dynamics typically compare observed fluctuations to theoretically predicted variances, sometimes after separating the intrinsic randomness of the system from the enslaving influence of changing environments. But variances have been shown to discriminate surprisingly poorly between alternative mechanisms, while for other system properties no approaches exist that rigorously disentangle environmental influences from intrinsic effects. Here, we apply the theory of generalized random walks in random environments to derive exact rules for decomposing time series and higher statistics, rather than just variances. We show for which properties and for which classes of systems intrinsic fluctuations can be analyzed without accounting for extrinsic stochasticity and vice versa. We derive two independent experimental methods to measure the separate noise contributions and show how to use the additional information in temporal correlations to detect multiplicative effects in dynamical systems.

Does tooth wear status predict ongoing sleep bruxism in 30-year-old Japanese subjects?

PubMed

Baba, Kazuyoshi; Haketa, Tadasu; Clark, Glenn T; Ohyama, Takashi

2004-01-01

This study investigated whether tooth wear status can predict bruxism level. Sixteen Japanese subjects (eight bruxers and eight age- and gender-matched controls; mean age 30 years) participated in this study. From dental casts of these subjects, the tooth wear was scored by Murphy's method. Bruxism level in these subjects was also recorded for 5 consecutive nights in the subject's home environment using a force-based bruxism detecting system. The relationship between the tooth wear score and bruxism data was evaluated statistically. Correlation analysis between the Murphy's scores of maxillary and mandibular dental arch and bruxism event duration score revealed no significant relationship between tooth wear and current bruxism. Tooth wear status is not predictive of ongoing bruxism level as measured by the force-based bruxism detection system in 30-year-old Japanese subjects.

Understanding the Role of Biology in the Global Environment: NASA'S Mission to Planet Earth

NASA Technical Reports Server (NTRS)

Townsend, William F.

1996-01-01

NASA has long used the unique perspective of space as a means of expanding our understanding of how the Earth's environment functions. In particular, the linkages between land, air, water, and life-the elements of the Earth system-are a focus for NASA's Mission to Planet Earth. This approach, called Earth system science, blends together fields like meteorology, biology, oceanography, and atmospheric science. Mission to Planet Earth uses observations from satellites, aircraft, balloons, and ground researchers as the basis for analysis of the elements of the Earth system, the interactions between those elements, and possible changes over the coming years and decades. This information is helping scientists improve our understanding of how natural processes affect us and how we might be affecting them. Such studies will yield improved weather forecasts, tools for managing agriculture and forests, information for fishermen and local planners, and, eventually, an enhanced ability to predict how the climate will change in the future. NASA has designed Mission to Planet Earth to focus on five primary themes: Land Cover and Land Use Change; Seasonal to Interannual Climate Prediction; Natural Hazards; Long-Term Climate Variability; and Atmosphere Ozone.

Early Detection of Lightning Caused Wildfires and Prediction of Wildfire Behavior through Energy Distribution, Atmospherics, Geophysics, the Sun's Azimuth, and Topology

NASA Astrophysics Data System (ADS)

Giesige, C.; Nava, E.

2016-12-01

In the midst of a changing climate we have seen extremes in weather events: lightning, wildfires, hurricanes, tornadoes, and earthquakes. All of these ride on an imbalance of magnetic and electrical distribution about the earth including what goes on from the atmospheric and geophysic levels. There is relevance to the important role the sun plays in developing and feeding of the extreme weather events along with the sun's role helping to create a separation of charges on earth furthering climactic extremes. Focusing attention in North America and on how the sun, atmospheric and geophysic winds come together producing lightning events, there are connections between energy distribution in the environment, lightning caused wildfires, and extreme wildfire behavior. Lightning caused wildfires and extreme fire behavior have become enhanced with the changing climate conditions. Even with strong developments in wildfire science, there remains a lack in full understanding of connections that create a lightning caused wildfire event and lack of monitoring advancements in predicting extreme fire behavior. Several connections have been made in our research allowing us to connect multiple facets of the environment in regards to electric and magnetic influences on wildfires. Among them include: irradiance, winds, pressure systems, humidity, and topology. The connections can be made to develop better detection systems of wildfires, establish with more accuracy areas of highest risk for wildfire and extreme wildfire behavior, and prediction of wildfire behavior. A platform found within the environment can also lead to further understanding and monitoring of other extreme weather events in the future.

Methodology for predicting maximum velocity and shear stress in a sinuous channel with bendway weirs using 1-D HEC-RAS modeling results

Treesearch

Paul Sclafani; Christopher I. Thornton; Amanda L. Cox; Steven R. Abt

2012-01-01

As with every natural process, river morphology incorporates a complex and nuanced set of processes that combine to produce an infinite set of possible outcomes. Natural laws that govern natural systems cause rivers to react to changes in the environment in order to maintain equilibrium. Changes in hydraulics, sediment transport, and habitat help keep natural systems...

Consideration for solar system exploration - A system to Mars. [biomedical, environmental, and psychological factors

NASA Technical Reports Server (NTRS)

Nicogossian, Arnauld E.; Garshnek, Victoria

1989-01-01

Biomedical issues related to a manned mission to Mars are reviewed. Consideration is given to cardiovascular deconditioning, hematological and immunological changes, bone and muscle changes, nutritional issues, and the development of physiological countermeasures. Environmental issues are discussed, including radiation hazards, toxic chemical exposure, and the cabin environment. Also, human factors, performance and behavior, medical screening of the crew, disease prediction, and health maintenance are examined.

Effect of transient liquid flow on retention characteristics of screen acquisition systems. [design of Space Shuttle feed system

NASA Technical Reports Server (NTRS)

Cady, E. C.

1977-01-01

A design analysis, is developed based on experimental data, to predict the effects of transient flow and pressure surges (caused either by valve or pump operation, or by boiling of liquids in warm lines) on the retention performance of screen acquisition systems. A survey of screen liquid acquisition system applications was performed to determine appropriate system environment and classification. A screen model was developed which assumed that the screen device was a uniformly distributed composite orthotropic structure, and which accounted for liquid inflow/outflow, gas ingestion quality, screen stress, and liquid spill. A series of 177 tests using 13 specimens (5 screen meshes, 4 screen device construction/backup methods, and 2 orientations) with three test fluids (isopropyl alcohol, Freon 114, and LH2) provided data which verified important features of the screen model and resulted in a design tool which could accurately predict the transient startup performance acquisition devices.

Use of a parallel artificial membrane system to evaluate passive absorption and elimination in small fish.

PubMed

Kwon, Jung-Hwan; Katz, Lynn E; Liljestrand, Howard M

2006-12-01

A parallel artificial lipid membrane system was developed to mimic passive mass transfer of hydrophobic organic chemicals in fish. In this physical model system, a membrane filter-supported lipid bilayer separates two aqueous phases that represent the external and internal aqueous environments of fish. To predict bioconcentration kinetics in small fish with this system, literature absorption and elimination rates were analyzed with an allometric diffusion model to quantify the mass transfer resistances in the aqueous and lipid phases of fish. The effect of the aqueous phase mass transfer resistance was controlled by adjusting stirring intensity to mimic bioconcentration rates in small fish. Twenty-three simple aromatic hydrocarbons were chosen as model compounds for purposes of evaluation. For most of the selected chemicals, literature absorption/elimination rates fall into the range predicted from measured membrane permeabilities and elimination rates of the selected chemicals determined by the diffusion model system.

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.

Shuttle payload bay dynamic environments: Summary and conclusion report for STS flights 1-5 and 9

NASA Technical Reports Server (NTRS)

Oconnell, M.; Garba, J.; Kern, D.

1984-01-01

The vibration, acoustic and low frequency loads data from the first 5 shuttle flights are presented. The engineering analysis of that data is also presented. Vibroacoustic data from STS-9 are also presented because they represent the only data taken on a large payload. Payload dynamic environment predictions developed by the participation of various NASA and industrial centers are presented along with a comparison of analytical loads methodology predictions with flight data, including a brief description of the methodologies employed in developing those predictions for payloads. The review of prediction methodologies illustrates how different centers have approached the problems of developing shuttle dynamic environmental predictions and criteria. Ongoing research activities related to the shuttle dynamic environments are also described. Analytical software recently developed for the prediction of payload acoustic and vibration environments are also described.

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

PubMed Central

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

2016-01-01

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

PubMed

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

2017-01-05

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

Measuring and predicting reservoir heterogeneity in complex deposystems. Annual report, September 20, 1990--September 20, 1991

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

Donaldson, A.; Shumaker, R.; Laughrey, C.

1992-08-01

The Lower Mississippian Big Injun sandstone, a major oil producer in the western half of West Virginia, consists of several sandstones that overstep each west. Examination of cores and thin sections has led to preliminary interpretations of depositional environments for the Big Injun. These include distributary-mouth bars with associated distal, bar crest and back bar environments in a marine-deltaic system; and channel, point bar and chute environments in a fluvial system. Overall, the Big Injun is a medium-grained sublitharenite in which initially high porosity has been modified by compaction and diagenesis. Chlorite grain coatings helped to preserve original porosity, whereasmore » illite promoted pressure solution during compaction, resulting in a loss of porosity. Diagenetic effects within specific environments are being evaluated to determine if environmental interpretations can be used to predict porosity preservation. Core plugs taken from cores in Granny Creek field were analyzed for porosity and horizontal and vertical permeability. Directional permeability was negligible, but permeability does correlate with depth. Changes in permeability with depth can be related to subdivisions of the Big Injun determined from density logs. Permeability also correlated with porosity, but porosity values derived from both cores and logs show no significant correlation trend at present. A layered reservoir model is being developed to evaluate the effect of these vertical heterogeneities. Initial attempts to characterize the heterogeneity of the Big Injun reservoir in Granny Creek field used a number of direct and indirect methods.« less

Measuring and predicting reservoir heterogeneity in complex deposystems

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

Donaldson, A.; Shumaker, R.; Laughrey, C.

1992-08-01

The Lower Mississippian Big Injun sandstone, a major oil producer in the western half of West Virginia, consists of several sandstones that overstep each west. Examination of cores and thin sections has led to preliminary interpretations of depositional environments for the Big Injun. These include distributary-mouth bars with associated distal, bar crest and back bar environments in a marine-deltaic system; and channel, point bar and chute environments in a fluvial system. Overall, the Big Injun is a medium-grained sublitharenite in which initially high porosity has been modified by compaction and diagenesis. Chlorite grain coatings helped to preserve original porosity, whereasmore » illite promoted pressure solution during compaction, resulting in a loss of porosity. Diagenetic effects within specific environments are being evaluated to determine if environmental interpretations can be used to predict porosity preservation. Core plugs taken from cores in Granny Creek field were analyzed for porosity and horizontal and vertical permeability. Directional permeability was negligible, but permeability does correlate with depth. Changes in permeability with depth can be related to subdivisions of the Big Injun determined from density logs. Permeability also correlated with porosity, but porosity values derived from both cores and logs show no significant correlation trend at present. A layered reservoir model is being developed to evaluate the effect of these vertical heterogeneities. Initial attempts to characterize the heterogeneity of the Big Injun reservoir in Granny Creek field used a number of direct and indirect methods.« less

Dynamic Risk Quantification and Management: Core needs and strategies for adapting water resources systems to a changing environment (Invited)

NASA Astrophysics Data System (ADS)

Lall, U.

2009-12-01

The concern with anthropogenic climate change has spurred significant interest in strategies for climate change adaptation in water resource systems planning and management. The thesis of this talk is that this is a subset of strategies that need to sustainably design and operate structural and non-structural systems for managing resources in a changing environment. Even with respect to a changing climate, the largest opportunity for immediate adaptation to a changing climate may be provided by an improved understanding and prediction capability for seasonal to interannual and decadal climate variability. I shall lay out some ideas as to how this can be done and provide an example for reservoir water allocation and management, and one for flood risk management.

Estimation of the Driving Style Based on the Users’ Activity and Environment Influence

PubMed Central

Sysoev, Mikhail; Kos, Andrej; Guna, Jože; Pogačnik, Matevž

2017-01-01

New models and methods have been designed to predict the influence of the user’s environment and activity information to the driving style in standard automotive environments. For these purposes, an experiment was conducted providing two types of analysis: (i) the evaluation of a self-assessment of the driving style; (ii) the prediction of aggressive driving style based on drivers’ activity and environment parameters. Sixty seven h of driving data from 10 drivers were collected for analysis in this study. The new parameters used in the experiment are the car door opening and closing manner, which were applied to improve the prediction accuracy. An Android application called Sensoric was developed to collect low-level smartphone data about the users’ activity. The driving style was predicted from the user’s environment and activity data collected before driving. The prediction was tested against the actual driving style, calculated from objective driving data. The prediction has shown encouraging results, with precision values ranging from 0.727 up to 0.909 for aggressive driving recognition rate. The obtained results lend support to the hypothesis that user’s environment and activity data could be used for the prediction of the aggressive driving style in advance, before the driving starts. PMID:29065476

Space Launch System Scale Model Acoustic Test Ignition Overpressure Testing

NASA Technical Reports Server (NTRS)

Nance, Donald K.; Liever, Peter A.

2015-01-01

The overpressure phenomenon is a transient fluid dynamic event occurring during rocket propulsion system ignition. This phenomenon results from fluid compression of the accelerating plume gas, subsequent rarefaction, and subsequent propagation from the exhaust trench and duct holes. The high-amplitude unsteady fluid-dynamic perturbations can adversely affect the vehicle and surrounding structure. Commonly known as ignition overpressure (IOP), this is an important design-to environment for the Space Launch System (SLS) that NASA is currently developing. Subscale testing is useful in validating and verifying the IOP environment. This was one of the objectives of the Scale Model Acoustic Test (SMAT), conducted at Marshall Space Flight Center (MSFC). The test data quantifies the effectiveness of the SLS IOP suppression system and improves the analytical models used to predict the SLS IOP environments. The reduction and analysis of the data gathered during the SMAT IOP test series requires identification and characterization of multiple dynamic events and scaling of the event waveforms to provide the most accurate comparisons to determine the effectiveness of the IOP suppression systems. The identification and characterization of the overpressure events, the waveform scaling, the computation of the IOP suppression system knockdown factors, and preliminary comparisons to the analytical models are discussed.

Space Launch System Scale Model Acoustic Test Ignition Overpressure Testing

NASA Technical Reports Server (NTRS)

Nance, Donald; Liever, Peter; Nielsen, Tanner

2015-01-01

The overpressure phenomenon is a transient fluid dynamic event occurring during rocket propulsion system ignition. This phenomenon results from fluid compression of the accelerating plume gas, subsequent rarefaction, and subsequent propagation from the exhaust trench and duct holes. The high-amplitude unsteady fluid-dynamic perturbations can adversely affect the vehicle and surrounding structure. Commonly known as ignition overpressure (IOP), this is an important design-to environment for the Space Launch System (SLS) that NASA is currently developing. Subscale testing is useful in validating and verifying the IOP environment. This was one of the objectives of the Scale Model Acoustic Test, conducted at Marshall Space Flight Center. The test data quantifies the effectiveness of the SLS IOP suppression system and improves the analytical models used to predict the SLS IOP environments. The reduction and analysis of the data gathered during the SMAT IOP test series requires identification and characterization of multiple dynamic events and scaling of the event waveforms to provide the most accurate comparisons to determine the effectiveness of the IOP suppression systems. The identification and characterization of the overpressure events, the waveform scaling, the computation of the IOP suppression system knockdown factors, and preliminary comparisons to the analytical models are discussed.

Materials selection for long life in LEO: A critical evaluation of atomic oxygen testing with thermal atom systems

NASA Technical Reports Server (NTRS)

Koontz, S. L.; Kuminecz, J.; Leger, L.; Nordine, P.

1988-01-01

The use of thermal atom test methods as a materials selection and screening technique for low-Earth orbit (LEO) spacecraft is critically evaluated. The chemistry and physics of thermal atom environments are compared with the LEO environment. The relative reactivities of a number of materials determined to be in thermal atom environments are compared to those observed in LEO and in high quality LEO simulations. Reaction efficiencies measured in a new type of thermal atom apparatus are one-hundredth to one-thousandth those observed in LEO, and many materials showing nearly identical reactivities in LEO show relative reactivities differing by as much as a factor of 8 in thermal atom systems. A simple phenomenological kinetic model for the reaction of oxygen atoms with organic materials can be used to explain the differences in reactivity in different environments. Certain specific thermal test environments can be used as reliable materials screening tools. Using thermal atom methods to predict material lifetime in LEO requires direct calibration of the method against LEO data or high quality simulation data for each material.

An agent based architecture for high-risk neonate management at neonatal intensive care unit.

PubMed

Malak, Jaleh Shoshtarian; Safdari, Reza; Zeraati, Hojjat; Nayeri, Fatemeh Sadat; Mohammadzadeh, Niloofar; Farajollah, Seide Sedighe Seied

2018-01-01

In recent years, the use of new tools and technologies has decreased the neonatal mortality rate. Despite the positive effect of using these technologies, the decisions are complex and uncertain in critical conditions when the neonate is preterm or has a low birth weight or malformations. There is a need to automate the high-risk neonate management process by creating real-time and more precise decision support tools. To create a collaborative and real-time environment to manage neonates with critical conditions at the NICU (Neonatal Intensive Care Unit) and to overcome high-risk neonate management weaknesses by applying a multi agent based analysis and design methodology as a new solution for NICU management. This study was a basic research for medical informatics method development that was carried out in 2017. The requirement analysis was done by reviewing articles on NICU Decision Support Systems. PubMed, Science Direct, and IEEE databases were searched. Only English articles published after 1990 were included; also, a needs assessment was done by reviewing the extracted features and current processes at the NICU environment where the research was conducted. We analyzed the requirements and identified the main system roles (agents) and interactions by a comparative study of existing NICU decision support systems. The Universal Multi Agent Platform (UMAP) was applied to implement a prototype of our multi agent based high-risk neonate management architecture. Local environment agents interacted inside a container and each container interacted with external resources, including other NICU systems and consultation centers. In the NICU container, the main identified agents were reception, monitoring, NICU registry, and outcome prediction, which interacted with human agents including nurses and physicians. Managing patients at the NICU units requires online data collection, real-time collaboration, and management of many components. Multi agent systems are applied as a well-known solution for management, coordination, modeling, and control of NICU processes. We are currently working on an outcome prediction module using artificial intelligence techniques for neonatal mortality risk prediction. The full implementation of the proposed architecture and evaluation is considered the future work.

The family environment predicts long-term academic achievement and classroom behavior following traumatic brain injury in early childhood.

PubMed

Durber, Chelsea M; Yeates, Keith Owen; Taylor, H Gerry; Walz, Nicolay Chertkoff; Stancin, Terry; Wade, Shari L

2017-07-01

This study examined how the family environment predicts long-term academic and behavioral functioning in school following traumatic brain injury (TBI) in early childhood. Using a concurrent cohort, prospective design, 15 children with severe TBI, 39 with moderate TBI, and 70 with orthopedic injury (OI) who were injured when they were 3-7 years of age were compared on tests of academic achievement and parent and teacher ratings of school performance and behavior on average 6.83 years postinjury. Soon after injury and at the longer term follow-up, families completed measures of parental psychological distress, family functioning, and quality of the home environment. Hierarchical linear regression analyses examined group differences in academic outcomes and their associations with measures of the early and later family environment. The severe TBI group, but not the moderate TBI group, performed worse than did the OI group on all achievement tests, parent ratings of academic performance, and teacher ratings of internalizing problems. Higher quality early and late home environments predicted stronger academic skills and better classroom behavior for children with both TBI and OI. The early family environment more consistently predicted academic achievement, whereas the later family environment more consistently predicted classroom functioning. The quality of the home environment predicted academic outcomes more strongly than did parental psychological distress or family functioning. TBI in early childhood has long-term consequences for academic achievement and school performance and behavior. Higher quality early and later home environments predict better school outcomes for both children with TBI and children with OI. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Design and implementation of space physics multi-model application integration based on web

NASA Astrophysics Data System (ADS)

Jiang, Wenping; Zou, Ziming

With the development of research on space environment and space science, how to develop network online computing environment of space weather, space environment and space physics models for Chinese scientific community is becoming more and more important in recent years. Currently, There are two software modes on space physics multi-model application integrated system (SPMAIS) such as C/S and B/S. the C/S mode which is traditional and stand-alone, demands a team or workshop from many disciplines and specialties to build their own multi-model application integrated system, that requires the client must be deployed in different physical regions when user visits the integrated system. Thus, this requirement brings two shortcomings: reducing the efficiency of researchers who use the models to compute; inconvenience of accessing the data. Therefore, it is necessary to create a shared network resource access environment which could help users to visit the computing resources of space physics models through the terminal quickly for conducting space science research and forecasting spatial environment. The SPMAIS develops high-performance, first-principles in B/S mode based on computational models of the space environment and uses these models to predict "Space Weather", to understand space mission data and to further our understanding of the solar system. the main goal of space physics multi-model application integration system (SPMAIS) is to provide an easily and convenient user-driven online models operating environment. up to now, the SPMAIS have contained dozens of space environment models , including international AP8/AE8 IGRF T96 models and solar proton prediction model geomagnetic transmission model etc. which are developed by Chinese scientists. another function of SPMAIS is to integrate space observation data sets which offers input data for models online high-speed computing. In this paper, service-oriented architecture (SOA) concept that divides system into independent modules according to different business needs is applied to solve the problem of the independence of the physical space between multiple models. The classic MVC(Model View Controller) software design pattern is concerned to build the architecture of space physics multi-model application integrated system. The JSP+servlet+javabean technology is used to integrate the web application programs of space physics multi-model. It solves the problem of multi-user requesting the same job of model computing and effectively balances each server computing tasks. In addition, we also complete follow tasks: establishing standard graphical user interface based on Java Applet application program; Designing the interface between model computing and model computing results visualization; Realizing three-dimensional network visualization without plug-ins; Using Java3D technology to achieve a three-dimensional network scene interaction; Improved ability to interact with web pages and dynamic execution capabilities, including rendering three-dimensional graphics, fonts and color control. Through the design and implementation of the SPMAIS based on Web, we provide an online computing and application runtime environment of space physics multi-model. The practical application improves that researchers could be benefit from our system in space physics research and engineering applications.

Flight Experiment Verification of Shuttle Boundary Layer Transition Prediction Tool

NASA Technical Reports Server (NTRS)

Berry, Scott A.; Berger, Karen T.; Horvath, Thomas J.; Wood, William A.

2016-01-01

Boundary layer transition at hypersonic conditions is critical to the design of future high-speed aircraft and spacecraft. Accurate methods to predict transition would directly impact the aerothermodynamic environments used to size a hypersonic vehicle's thermal protection system. A transition prediction tool, based on wind tunnel derived discrete roughness correlations, was developed and implemented for the Space Shuttle return-to-flight program. This tool was also used to design a boundary layer transition flight experiment in order to assess correlation uncertainties, particularly with regard to high Mach-number transition and tunnel-to-flight scaling. A review is provided of the results obtained from the flight experiment in order to evaluate the transition prediction tool implemented for the Shuttle program.

Making predictions in a changing world-inference, uncertainty, and learning.

PubMed

O'Reilly, Jill X

2013-01-01

To function effectively, brains need to make predictions about their environment based on past experience, i.e., they need to learn about their environment. The algorithms by which learning occurs are of interest to neuroscientists, both in their own right (because they exist in the brain) and as a tool to model participants' incomplete knowledge of task parameters and hence, to better understand their behavior. This review focusses on a particular challenge for learning algorithms-how to match the rate at which they learn to the rate of change in the environment, so that they use as much observed data as possible whilst disregarding irrelevant, old observations. To do this algorithms must evaluate whether the environment is changing. We discuss the concepts of likelihood, priors and transition functions, and how these relate to change detection. We review expected and estimation uncertainty, and how these relate to change detection and learning rate. Finally, we consider the neural correlates of uncertainty and learning. We argue that the neural correlates of uncertainty bear a resemblance to neural systems that are active when agents actively explore their environments, suggesting that the mechanisms by which the rate of learning is set may be subject to top down control (in circumstances when agents actively seek new information) as well as bottom up control (by observations that imply change in the environment).

Analytic Methods for Predicting Significant Multi-Quanta Effects in Collisional Molecular Energy Transfer

NASA Technical Reports Server (NTRS)

Bieniek, Ronald J.

1996-01-01

Collision-induced transitions can significantly affect molecular vibrational-rotational populations and energy transfer in atmospheres and gaseous systems. This, in turn. can strongly influence convective heat transfer through dissociation and recombination of diatomics. and radiative heat transfer due to strong vibrational coupling. It is necessary to know state-to-state rates to predict engine performance and aerothermodynamic behavior of hypersonic flows, to analyze diagnostic radiative data obtained from experimental test facilities, and to design heat shields and other thermal protective systems. Furthermore, transfer rates between vibrational and translational modes can strongly influence energy flow in various 'disturbed' environments, particularly where the vibrational and translational temperatures are not equilibrated.

Filter replacement lifetime prediction

DOEpatents

Hamann, Hendrik F.; Klein, Levente I.; Manzer, Dennis G.; Marianno, Fernando J.

2017-10-25

Methods and systems for predicting a filter lifetime include building a filter effectiveness history based on contaminant sensor information associated with a filter; determining a rate of filter consumption with a processor based on the filter effectiveness history; and determining a remaining filter lifetime based on the determined rate of filter consumption. Methods and systems for increasing filter economy include measuring contaminants in an internal and an external environment; determining a cost of a corrosion rate increase if unfiltered external air intake is increased for cooling; determining a cost of increased air pressure to filter external air; and if the cost of filtering external air exceeds the cost of the corrosion rate increase, increasing an intake of unfiltered external air.

Planet Formation

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Young, Richard E. (Technical Monitor)

1997-01-01

Modern theories of star and planet formation, which are based upon observations of the Solar System and of young stars and their environments, predict that most single stars should have rocky planets in orbit about them; the frequency of gas giant planets is more difficult to predict theoretically. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant planets begin their growth like terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates. Models for the formation of the giant planets found in recent radial velocity searches are discussed.

Organization of an optimal adaptive immune system

NASA Astrophysics Data System (ADS)

Walczak, Aleksandra; Mayer, Andreas; Balasubramanian, Vijay; Mora, Thierry

The repertoire of lymphocyte receptors in the adaptive immune system protects organisms from a diverse set of pathogens. A well-adapted repertoire should be tuned to the pathogenic environment to reduce the cost of infections. I will discuss a general framework for predicting the optimal repertoire that minimizes the cost of infections contracted from a given distribution of pathogens. The theory predicts that the immune system will have more receptors for rare antigens than expected from the frequency of encounters and individuals exposed to the same infections will have sparse repertoires that are largely different, but nevertheless exploit cross-reactivity to provide the same coverage of antigens. I will show that the optimal repertoires can be reached by dynamics that describes the competitive binding of antigens by receptors, and selective amplification of stimulated receptors.

Origin and Diversity of Planetary Systems

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Young, Richard E. (Technical Monitor)

1997-01-01

Modern theories of star and planet formation, which are based upon observations of the Solar System and of young stars and their environments, predict that rocky planets should form around most single stars, although it is possible that most such planets are lost to orbital decay within the protoplanetary disk. The frequency of formation of gas giant planets is more difficult to predict theoretically. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant planets begin their growth like terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates. Models for the formation of the giant planets found in recent radial velocity searches are discussed.

The Birth of Planetary Systems

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Young, Richard E. (Technical Monitor)

1997-01-01

An overview of current theories of star and planet formation is presented. These models are based upon observations of the Solar System and of young stars and their environments, and they predict that rocky planets should form around most single stars, although it is possible that in some cases such planets are lost to orbital decay within the protoplanetary disk. The frequency of formation of gas giant planets is more difficult to predict theoretically. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant planets begin their growth like terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates.

Performance evaluation of infrared imaging system in field test

NASA Astrophysics Data System (ADS)

Wang, Chensheng; Guo, Xiaodong; Ren, Tingting; Zhang, Zhi-jie

2014-11-01

Infrared imaging system has been applied widely in both military and civilian fields. Since the infrared imager has various types and different parameters, for system manufacturers and customers, there is great demand for evaluating the performance of IR imaging systems with a standard tool or platform. Since the first generation IR imager was developed, the standard method to assess the performance has been the MRTD or related improved methods which are not perfect adaptable for current linear scanning imager or 2D staring imager based on FPA detector. For this problem, this paper describes an evaluation method based on the triangular orientation discrimination metric which is considered as the effective and emerging method to evaluate the synthesis performance of EO system. To realize the evaluation in field test, an experiment instrument is developed. And considering the importance of operational environment, the field test is carried in practical atmospheric environment. The test imagers include panoramic imaging system and staring imaging systems with different optics and detectors parameters (both cooled and uncooled). After showing the instrument and experiment setup, the experiment results are shown. The target range performance is analyzed and discussed. In data analysis part, the article gives the range prediction values obtained from TOD method, MRTD method and practical experiment, and shows the analysis and results discussion. The experimental results prove the effectiveness of this evaluation tool, and it can be taken as a platform to give the uniform performance prediction reference.

Predictable enriched environment prevents development of hyper-emotionality in the VPA rat model of autism.

PubMed

Favre, Mônica R; La Mendola, Deborah; Meystre, Julie; Christodoulou, Dimitri; Cochrane, Melissa J; Markram, Henry; Markram, Kamila

2015-01-01

Understanding the effects of environmental stimulation in autism can improve therapeutic interventions against debilitating sensory overload, social withdrawal, fear and anxiety. Here, we evaluate the role of environmental predictability on behavior and protein expression, and inter-individual differences, in the valproic acid (VPA) model of autism. Male rats embryonically exposed (E11.5) either to VPA, a known autism risk factor in humans, or to saline, were housed from weaning into adulthood in a standard laboratory environment, an unpredictably enriched environment, or a predictably enriched environment. Animals were tested for sociability, nociception, stereotypy, fear conditioning and anxiety, and for tissue content of glutamate signaling proteins in the primary somatosensory cortex, hippocampus and amygdala, and of corticosterone in plasma, amygdala and hippocampus. Standard group analyses on separate measures were complemented with a composite emotionality score, using Cronbach's Alpha analysis, and with multivariate profiling of individual animals, using Hierarchical Cluster Analysis. We found that predictable environmental enrichment prevented the development of hyper-emotionality in the VPA-exposed group, while unpredictable enrichment did not. Individual variation in the severity of the autistic-like symptoms (fear, anxiety, social withdrawal and sensory abnormalities) correlated with neurochemical profiles, and predicted their responsiveness to predictability in the environment. In controls, the association between socio-affective behaviors, neurochemical profiles and environmental predictability was negligible. This study suggests that rearing in a predictable environment prevents the development of hyper-emotional features in animals exposed to an autism risk factor, and demonstrates that unpredictable environments can lead to negative outcomes, even in the presence of environmental enrichment.

Predictable enriched environment prevents development of hyper-emotionality in the VPA rat model of autism

PubMed Central

Favre, Mônica R.; La Mendola, Deborah; Meystre, Julie; Christodoulou, Dimitri; Cochrane, Melissa J.; Markram, Henry; Markram, Kamila

2015-01-01

Understanding the effects of environmental stimulation in autism can improve therapeutic interventions against debilitating sensory overload, social withdrawal, fear and anxiety. Here, we evaluate the role of environmental predictability on behavior and protein expression, and inter-individual differences, in the valproic acid (VPA) model of autism. Male rats embryonically exposed (E11.5) either to VPA, a known autism risk factor in humans, or to saline, were housed from weaning into adulthood in a standard laboratory environment, an unpredictably enriched environment, or a predictably enriched environment. Animals were tested for sociability, nociception, stereotypy, fear conditioning and anxiety, and for tissue content of glutamate signaling proteins in the primary somatosensory cortex, hippocampus and amygdala, and of corticosterone in plasma, amygdala and hippocampus. Standard group analyses on separate measures were complemented with a composite emotionality score, using Cronbach's Alpha analysis, and with multivariate profiling of individual animals, using Hierarchical Cluster Analysis. We found that predictable environmental enrichment prevented the development of hyper-emotionality in the VPA-exposed group, while unpredictable enrichment did not. Individual variation in the severity of the autistic-like symptoms (fear, anxiety, social withdrawal and sensory abnormalities) correlated with neurochemical profiles, and predicted their responsiveness to predictability in the environment. In controls, the association between socio-affective behaviors, neurochemical profiles and environmental predictability was negligible. This study suggests that rearing in a predictable environment prevents the development of hyper-emotional features in animals exposed to an autism risk factor, and demonstrates that unpredictable environments can lead to negative outcomes, even in the presence of environmental enrichment. PMID:26089770

Transforming the sensing and numerical prediction of high-impact local weather through dynamic adaptation.

PubMed

Droegemeier, Kelvin K

2009-03-13

Mesoscale weather, such as convective systems, intense local rainfall resulting in flash floods and lake effect snows, frequently is characterized by unpredictable rapid onset and evolution, heterogeneity and spatial and temporal intermittency. Ironically, most of the technologies used to observe the atmosphere, predict its evolution and compute, transmit or store information about it, operate in a static pre-scheduled framework that is fundamentally inconsistent with, and does not accommodate, the dynamic behaviour of mesoscale weather. As a result, today's weather technology is highly constrained and far from optimal when applied to any particular situation. This paper describes a new cyberinfrastructure framework, in which remote and in situ atmospheric sensors, data acquisition and storage systems, assimilation and prediction codes, data mining and visualization engines, and the information technology frameworks within which they operate, can change configuration automatically, in response to evolving weather. Such dynamic adaptation is designed to allow system components to achieve greater overall effectiveness, relative to their static counterparts, for any given situation. The associated service-oriented architecture, known as Linked Environments for Atmospheric Discovery (LEAD), makes advanced meteorological and cyber tools as easy to use as ordering a book on the web. LEAD has been applied in a variety of settings, including experimental forecasting by the US National Weather Service, and allows users to focus much more attention on the problem at hand and less on the nuances of data formats, communication protocols and job execution environments.

Sociodemographic Risk, Parenting, and Effortful Control: Relations to Salivary Alpha-amylase and Cortisol in Early Childhood

PubMed Central

Taylor, Zoe E.; Spinrad, Tracy L.; VanSchyndel, Sarah K.; Eisenberg, Nancy; Huynh, Jacqueline; Sulik, Michael J.; Granger, Douglas A.

2012-01-01

Early sociodemographic risk, parenting, and temperament were examined as predictors of the activity of children’s (N = 148; 81 boys, 67 girls) hypothalamic-pituitary-adrenal axis and autonomic nervous system. Demographic risk was assessed at 18 months (T1), intrusive-overcontrolling parenting and effortful control were assessed at 30 months (T2), and salivary cortisol and alpha-amylase were collected at 72 (T3) months of age. Demographic risk at T1 predicted lower levels of children’s effortful control and higher levels of mothers’ intrusive-overcontrolling parenting at T2. Intrusive-overcontrolling parenting at T2 predicted higher levels of children’s cortisol and alpha-amylase at T3, but effortful control did not uniquely predict children’s cortisol or alpha-amylase. Findings support the open nature of stress responsive physiological systems to influence by features of the early caregiving environment and underscore the utility of including measures of these systems in prevention trials designed to influence child outcomes by modifying parenting behavior. PMID:22949301

Advanced Earth-to-orbit propulsion technology program overview: Impact of civil space technology initiative

NASA Technical Reports Server (NTRS)

Stephenson, Frank W., Jr.

1988-01-01

The NASA Earth-to-Orbit (ETO) Propulsion Technology Program is dedicated to advancing rocket engine technologies for the development of fully reusable engine systems that will enable space transportation systems to achieve low cost, routine access to space. The program addresses technology advancements in the areas of engine life extension/prediction, performance enhancements, reduced ground operations costs, and in-flight fault tolerant engine operations. The primary objective is to acquire increased knowledge and understanding of rocket engine chemical and physical processes in order to evolve more realistic analytical simulations of engine internal environments, to derive more accurate predictions of steady and unsteady loads, and using improved structural analyses, to more accurately predict component life and performance, and finally to identify and verify more durable advanced design concepts. In addition, efforts were focused on engine diagnostic needs and advances that would allow integrated health monitoring systems to be developed for enhanced maintainability, automated servicing, inspection, and checkout, and ultimately, in-flight fault tolerant engine operations.

Metabolic gene regulation in a dynamically changing environment.

PubMed

Bennett, Matthew R; Pang, Wyming Lee; Ostroff, Natalie A; Baumgartner, Bridget L; Nayak, Sujata; Tsimring, Lev S; Hasty, Jeff

2008-08-28

Natural selection dictates that cells constantly adapt to dynamically changing environments in a context-dependent manner. Gene-regulatory networks often mediate the cellular response to perturbation, and an understanding of cellular adaptation will require experimental approaches aimed at subjecting cells to a dynamic environment that mimics their natural habitat. Here we monitor the response of Saccharomyces cerevisiae metabolic gene regulation to periodic changes in the external carbon source by using a microfluidic platform that allows precise, dynamic control over environmental conditions. We show that the metabolic system acts as a low-pass filter that reliably responds to a slowly changing environment, while effectively ignoring fast fluctuations. The sensitive low-frequency response was significantly faster than in predictions arising from our computational modelling, and this discrepancy was resolved by the discovery that two key galactose transcripts possess half-lives that depend on the carbon source. Finally, to explore how induction characteristics affect frequency response, we compare two S. cerevisiae strains and show that they have the same frequency response despite having markedly different induction properties. This suggests that although certain characteristics of the complex networks may differ when probed in a static environment, the system has been optimized for a robust response to a dynamically changing environment.

Financial time series prediction using spiking neural networks.

PubMed

Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

2014-01-01

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments.

Aquatic fate of a double-stranded RNA in a sediment---water system following an over-water application.

PubMed

Fischer, Joshua R; Zapata, Fatima; Dubelman, Samuel; Mueller, Geoffrey M; Uffman, Joshua P; Jiang, Changjian; Jensen, Peter D; Levine, Steven L

2017-03-01

Determining the rate of biodegradation of double-stranded RNA (dsRNA) in the environment is an essential element of a comprehensive risk assessment of an RNA-based agricultural product. This information is used during problem formulation to define relevant routes and durations of environmental exposure for in planta-expressed dsRNA. Although exposure to biotechnology-derived crops expressing dsRNA traits in the aquatic environment is predicted to be minimal, little is known regarding the fate of dsRNA in these environments. To assess exposure to aquatic environments, a study was conducted to measure the rate of biodegradation of DvSnf7 dsRNA in aerobic water-sediment systems. Aquatic systems containing natural water and sediments that varied in physical and chemical characteristics were treated with dsRNA by applying DvSnf7 dsRNA directly to the water column. In the present study, DvSnf7 dsRNA dissipated rapidly from the water phase and was undetectable within 7 d as measured by QuantiGene (Affymetrix) and a sensitive insect bioassay in these diverse systems. Degradation kinetics estimated a half-life (time to 50% dissipation [DT50]) of less than 3 d and a time to 90% dissipation of approximately 4 d. Further analysis indicated that DvSnf7 dsRNA had DT50 values of less than 6 d in both sediment-free systems containing natural water and systems with only sediment. Taken together, the results of the present study indicate that dsRNA-based agricultural products rapidly degrade and consequently are unlikely to persist in aquatic environments. Environ Toxicol Chem 2017;36:727-734. © 2016 SETAC. © 2016 SETAC.

The predictive adaptive response: modeling the life-history evolution of the butterfly Bicyclus anynana in seasonal environments.

PubMed

van den Heuvel, Joost; Saastamoinen, Marjo; Brakefield, Paul M; Kirkwood, Thomas B L; Zwaan, Bas J; Shanley, Daryl P

2013-02-01

A predictive adaptive response (PAR) is a type of developmental plasticity where the response to an environmental cue is not immediately advantageous but instead is later in life. The PAR is a way for organisms to maximize fitness in varying environments. Insects living in seasonal environments are valuable model systems for testing the existence and form of PAR. Previous manipulations of the larval and the adult environments of the butterfly Bicyclus anynana have shown that individuals that were food restricted during the larval stage coped better with forced flight during the adult stage compared to those with optimal conditions in the larval stage. Here, we describe a state-dependent energy allocation model, which we use to test whether such a response to food restriction could be adaptive in nature where this butterfly exhibits seasonal cycles. The results from the model confirm the responses obtained in our previous experimental work and show how such an outcome was facilitated by resource allocation patterns to the thorax during the pupal stage. We conclude that for B. anynana, early-stage cues can direct development toward a better adapted phenotype later in life and, therefore, that a PAR has evolved in this species.

Aerothermodynamic Environment Definition for the Genesis Sample Return Capsule

NASA Technical Reports Server (NTRS)

Cheatwood, F. McNeil; Merski, N. Ronald, Jr.; Riley, Christopher J.; Mitcheltree, Robert A.

2001-01-01

NASA's Genesis sample return mission will be the first to return material from beyond the Earth-Moon system. NASA Langley Research Center supported this mission with aerothermodynamic analyses of the sample return capsule. This paper provides an overview of that effort. The capsule is attached through its forebody to the spacecraft bus. When the attachment is severed prior to Earth entry, forebody cavities remain. The presence of these cavities could dramatically increase the heating environment in their vicinity and downstream. A combination of computational fluid dynamics calculations and wind tunnel phosphor thermography tests were employed to address this issue. These results quantify the heating environment in and around the cavities, and were a factor in the decision to switch forebody heat shield materials. A transition map is developed which predicts that the flow aft of the penetrations will still be laminar at the peak heating point of the trajectory. As the vehicle continues along the trajectory to the peak dynamic pressure point, fully turbulent flow aft of the penetrations could occur. The integrated heat load calculations show that a heat shield sized to the stagnation point levels will be adequate for the predicted environment aft of the penetrations.

A Cooperative Model for IS Security Risk Management in Distributed Environment

PubMed Central

Zheng, Chundong

2014-01-01

Given the increasing cooperation between organizations, the flexible exchange of security information across the allied organizations is critical to effectively manage information systems (IS) security in a distributed environment. In this paper, we develop a cooperative model for IS security risk management in a distributed environment. In the proposed model, the exchange of security information among the interconnected IS under distributed environment is supported by Bayesian networks (BNs). In addition, for an organization's IS, a BN is utilized to represent its security environment and dynamically predict its security risk level, by which the security manager can select an optimal action to safeguard the firm's information resources. The actual case studied illustrates the cooperative model presented in this paper and how it can be exploited to manage the distributed IS security risk effectively. PMID:24563626

A System For Load Isolation And Precision Pointing

NASA Astrophysics Data System (ADS)

Keckler, Claude R.; Hamilton, Brian J.

1983-11-01

A system capable of satisfying the accuracy and stability requirements dictated by Shuttle-borne payloads utilizing large optics has been under joint NASA/Sperry development. This device, denoted the Annular Suspension and Pointing System, employs a unique combination of conventional gimbals and magnetic bearing actuators, thereby providing for the "complete" isolation of the payload from its external environment, as well as for extremely accurate and stable pointing (≍0.01 arcseconds). This effort has been pursued through the fabrication and laboratory evaluation of engineering model hardware. Results from these tests have been instrumental in generating high fidelity computer simulations of this load isolation and precision pointing system, and in permitting confident predictions of the system's on-orbit performance. Applicability of this system to the Solar Optical Telescope mission has been examined using the computer simulation. The worst case pointing error predicted for this payload while subjected to vernier reaction control system thruster firings and crew motions aboard Shuttle was approximately 0.006 arcseconds.

ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

PubMed

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-08-15

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

PubMed Central

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-01-01

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

FAST TRACK COMMUNICATION Understanding adhesion at as-deposited interfaces from ab initio thermodynamics of deposition growth: thin-film alumina on titanium carbide

NASA Astrophysics Data System (ADS)

Rohrer, Jochen; Hyldgaard, Per

2010-12-01

We investigate the chemical composition and adhesion of chemical vapour deposited thin-film alumina on TiC using and extending a recently proposed nonequilibrium method of ab initio thermodynamics of deposition growth (AIT-DG) (Rohrer and Hyldgaard 2010 Phys. Rev. B 82 045415). A previous study of this system (Rohrer et al 2010 J. Phys.: Condens. Matter 22 015004) found that use of equilibrium thermodynamics leads to predictions of a non-binding TiC/alumina interface, despite its industrial use as a wear-resistant coating. This discrepancy between equilibrium theory and experiment is resolved by the AIT-DG method which predicts interfaces with strong adhesion. The AIT-DG method combines density functional theory calculations, rate-equation modelling of the pressure evolution of the deposition environment and thermochemical data. The AIT-DG method was previously used to predict prevalent terminations of growing or as-deposited surfaces of binary materials. Here we extend the method to predict surface and interface compositions of growing or as-deposited thin films on a substrate and find that inclusion of the nonequilibrium deposition environment has important implications for the nature of buried interfaces.

Parenting and Preschool Self-Regulation as Predictors of Social Emotional Competence in 1st Grade

PubMed Central

Russell, Beth S.; Lee, Jungeun Olivia; Spieker, Susan; Oxford, Monica L.

2016-01-01

The current longitudinal study used data from the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development (SECCYD) to examine a model of development that emphasizes early caregiving environments as predictors of social emotional competence (including classroom competence). This path analysis model included features of parenting, emotion regulation, preschool language skills, and attention to predict child outcomes in 1st grade. Early caregiving environments were directly predictive of peer relationship satisfaction, oppositional behavior, social skills, and classroom competence over and above significant mediated effects through preschool self regulation (language, inattention, and anger/frustration). These results suggest that the characteristics of supportive and stimulating caregiving shift in valence over time, such that qualities of the infant-child relationship that are significant in predicting early childhood outcomes are not the same as the caregiving qualities that move to the foreground in predicting primary school outcomes. Implications for school-readiness programming are discussed, including interventions in the early caregiving system to encourage sensitive and supportive parent child interactions to bolster school readiness via the development of social-emotional competence. PMID:27616805

A synoptic climatology of derecho producing mesoscale convective systems in the North-Central Plains

NASA Astrophysics Data System (ADS)

Bentley, Mace L.; Mote, Thomas L.; Byrd, Stephen F.

2000-09-01

Synoptic-scale environments favourable for producing derechos, or widespread convectively induced windstorms, in the North-Central Plains are examined with the goal of providing pattern-recognition/diagnosis techniques. Fifteen derechos were identified across the North-Central Plains region during 1986-1995. The synoptic environment at the initiation, mid-point and decay of each derecho was then evaluated using surface, upper-air and National Center for Atmospheric Research (NCAR)/National Center for Environmental Prediction (NCEP) reanalysis datasets.Results suggest that the synoptic environment is critical in maintaining derecho producing mesoscale convective systems (DMCSs). The synoptic environment in place downstream of the MCS initiation region determines the movement and potential strength of the system. Circulation around surface low pressure increased the instability gradient and maximized leading edge convergence in the initiation region of nearly all events regardless of DMCS location or movement. Other commonalities in the environments of these events include the presence of a weak thermal boundary, high convective instability and a layer of dry low-to-mid-tropospheric air. Of the two corridors sampled, northeastward moving derechos tend to initiate east of synoptic-scale troughs, while southeastward moving derechos form on the northeast periphery of a synoptic-scale ridge. Other differences between these two DMCS events are also discussed.

Hot limpets: predicting body temperature in a conductance-mediated thermal system.

PubMed

Denny, Mark W; Harley, Christopher D G

2006-07-01

Living at the interface between the marine and terrestrial environments, intertidal organisms may serve as a bellwether for environmental change and a test of our ability to predict its biological consequences. However, current models do not allow us to predict the body temperature of intertidal organisms whose heat budgets are strongly affected by conduction to and from the substratum. Here, we propose a simple heat-budget model of one such animal, the limpet Lottia gigantea, and test the model against measurements made in the field. Working solely from easily measured physical and meteorological inputs, the model predicts the daily maximal body temperatures of live limpets within a fraction of a degree, suggesting that it may be a useful tool for exploring the thermal biology of limpets and for predicting effects of climate change. The model can easily be adapted to predict the temperatures of chitons, acorn barnacles, keyhole limpets, and encrusting animals and plants.

Sensor Network Provides Environmental Data

NASA Technical Reports Server (NTRS)

2007-01-01

The National Biocomputation Center, a joint partnership between the Stanford University School of Medicine's Department of Surgery and NASA's Ames Research Center, is the test bed for much of NASA's research in telemedicine, the remote delivery of medical care. In early 2005, researchers at the National Biocomputation Center formed a spinoff company, Intelesense Technologies, to use the telemedicine sensors to provide integrated global monitoring systems. Intelesense uses the systems to better understand how environments and people are linked, monitor and protect natural resources, predict and adapt to environmental changes, provide for sustainable development, reduce the costs and impacts of natural disasters, and provide an effective and intelligent response to such disasters. Current projects range from protecting the environment to tracking emerging infectious diseases like avian influenza (bird flu) and helping people from around the world connect and interact with each other to better understand their environment and themselves.

Salinized rivers: degraded systems or new habitats for salt-tolerant faunas?

PubMed Central

Buchwalter, David; Davis, Jenny

2016-01-01

Anthropogenic salinization of rivers is an emerging issue of global concern, with significant adverse effects on biodiversity and ecosystem functioning. Impacts of freshwater salinization on biota are strongly mediated by evolutionary history, as this is a major factor determining species physiological salinity tolerance. Freshwater insects dominate most flowing waters, and the common lotic insect orders Ephemeroptera (mayflies), Plecoptera (stoneflies) and Trichoptera (caddisflies) are particularly salt-sensitive. Tolerances of existing taxa, rapid adaption, colonization by novel taxa (from naturally saline environments) and interactions between species will be key drivers of assemblages in saline lotic systems. Here we outline a conceptual framework predicting how communities may change in salinizing rivers. We envision that a relatively small number of taxa will be saline-tolerant and able to colonize salinized rivers (e.g. most naturally saline habitats are lentic; thus potential colonizers would need to adapt to lotic environments), leading to depauperate communities in these environments. PMID:26932680

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

USGS Publications Warehouse

Bastille-Rousseau, Guillaume; Gibbs, James P.; Yackulic, Charles B.; Frair, Jacqueline L.; Cabrera, Fredy; Rousseau, Louis-Philippe

2016-01-01

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 106 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.

Monitoring ethylene emissions from plants cultured for a controlled ecological life support system

NASA Technical Reports Server (NTRS)

Corey, Kenneth A.

1995-01-01

Emission of hydrocarbons and other volatile compounds by materials and organisms in closed environments will be a major concern in the design and management of advanced life support systems with a bioregenerative component. Ethylene, a simple hydrocarbon synthesized by plants, is involved in the elicitation of a wide range of physiological responses. In closed environments, ethylene may build up to levels which become physiologically active. In several growouts of 'Yecora Rojo' wheat in Kennedy Space Center's Biomass Production Chamber (BPC), it was observed that leaf flecking and rolling occurred in the sealed environment and was virtually eliminated when potassium permanganate was used to scrub the atmospheric environment. It was suggested that ethylene, which accumulated to about 60 ppb in the chamber and which was effectively absorbed by potassium permanganate, was responsible for the symptoms. The objectives of this work were to: (1) determine rates of ethylene evolution from lettuce (Lactuca sativa cultivar Waldemann's Green) and wheat (Triticum aestivum cultivar Yecora Rojo) plants during growth and development; (2) determine the effects of exposure of whole, vegetative stage plants to exogenous ethylene concentrations in the range of what would develop in closed environment growth chambers; and (3) develop predictive functions for changes in ethylene concentration that would develop under different cropping and closed environment configurations. Results will lead to the development of management strategies for ethylene in bioregenerative life support systems.

Intelligent Predictor of Energy Expenditure with the Use of Patch-Type Sensor Module

PubMed Central

Li, Meina; Kwak, Keun-Chang; Kim, Youn-Tae

2012-01-01

This paper is concerned with an intelligent predictor of energy expenditure (EE) using a developed patch-type sensor module for wireless monitoring of heart rate (HR) and movement index (MI). For this purpose, an intelligent predictor is designed by an advanced linguistic model (LM) with interval prediction based on fuzzy granulation that can be realized by context-based fuzzy c-means (CFCM) clustering. The system components consist of a sensor board, the rubber case, and the communication module with built-in analysis algorithm. This sensor is patched onto the user's chest to obtain physiological data in indoor and outdoor environments. The prediction performance was demonstrated by root mean square error (RMSE). The prediction performance was obtained as the number of contexts and clusters increased from 2 to 6, respectively. Thirty participants were recruited from Chosun University to take part in this study. The data sets were recorded during normal walking, brisk walking, slow running, and jogging in an outdoor environment and treadmill running in an indoor environment, respectively. We randomly divided the data set into training (60%) and test data set (40%) in the normalized space during 10 iterations. The training data set is used for model construction, while the test set is used for model validation. The experimental results revealed that the prediction error on treadmill running simulation was improved by about 51% and 12% in comparison to conventional LM for training and checking data set, respectively. PMID:23202166

Exploring the social dimension of sandy beaches through predictive modelling.

PubMed

Domínguez-Tejo, Elianny; Metternicht, Graciela; Johnston, Emma L; Hedge, Luke

2018-05-15

Sandy beaches are unique ecosystems increasingly exposed to human-induced pressures. Consistent with emerging frameworks promoting this holistic approach towards beach management, is the need to improve the integration of social data into management practices. This paper aims to increase understanding of links between demographics and community values and preferred beach activities, as key components of the social dimension of the beach environment. A mixed method approach was adopted to elucidate users' opinions on beach preferences and community values through a survey carried out in Manly Local Government Area in Sydney Harbour, Australia. A proposed conceptual model was used to frame demographic models (using age, education, employment, household income and residence status) as predictors of these two community responses. All possible regression-model combinations were compared using Akaike's information criterion. Best models were then used to calculate quantitative likelihoods of the responses, presented as heat maps. Findings concur with international research indicating the relevance of social and restful activities as important social links between the community and the beach environment. Participant's age was a significant variable in the four predictive models. The use of predictive models informed by demographics could potentially increase our understanding of interactions between the social and ecological systems of the beach environment, as a prelude to integrated beach management approaches. The research represents a practical demonstration of how demographic predictive models could support proactive approaches to beach management. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of the virtual research environment for analysis, evaluation and prediction of global climate change impacts on the regional environment

NASA Astrophysics Data System (ADS)

Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Fazliev, Alexander

2017-04-01

Description and the first results of the Russian Science Foundation project "Virtual computational information environment for analysis, evaluation and prediction of the impacts of global climate change on the environment and climate of a selected region" is presented. The project is aimed at development of an Internet-accessible computation and information environment providing unskilled in numerical modelling and software design specialists, decision-makers and stakeholders with reliable and easy-used tools for in-depth statistical analysis of climatic characteristics, and instruments for detailed analysis, assessment and prediction of impacts of global climate change on the environment and climate of the targeted region. In the framework of the project, approaches of "cloud" processing and analysis of large geospatial datasets will be developed on the technical platform of the Russian leading institution involved in research of climate change and its consequences. Anticipated results will create a pathway for development and deployment of thematic international virtual research laboratory focused on interdisciplinary environmental studies. VRE under development will comprise best features and functionality of earlier developed information and computing system CLIMATE (http://climate.scert.ru/), which is widely used in Northern Eurasia environment studies. The Project includes several major directions of research listed below. 1. Preparation of geo-referenced data sets, describing the dynamics of the current and possible future climate and environmental changes in detail. 2. Improvement of methods of analysis of climate change. 3. Enhancing the functionality of the VRE prototype in order to create a convenient and reliable tool for the study of regional social, economic and political consequences of climate change. 4. Using the output of the first three tasks, compilation of the VRE prototype, its validation, preparation of applicable detailed description of climate change in Western Siberia, and dissemination of the Project results. Results of the first stage of the Project implementation are presented. This work is supported by the Russian Science Foundation grant No16-19-10257.

Individual Differences in Adolescents' Sympathetic and Parasympathetic Functioning Moderate Associations between Family Environment and Psychosocial Adjustment

ERIC Educational Resources Information Center

Diamond, Lisa M.; Fagundes, Christopher P.; Cribbet, Matthew R.

2012-01-01

The present study tested whether individual differences in autonomic nervous system functioning interact with environmental risk factors to predict adolescents' psychosocial functioning. The authors assessed skin conductance and respiratory sinus arrhythmia at rest and during laboratory stressors in 110 14-year-olds. Subsequently, adolescents and…

Reengineering Aircraft Structural Life Prediction Using a Digital Twin

DTIC Science & Technology

2011-01-01

that exaflop-per-second computers will become available: “extrapolation of current hardware trends suggests that exascale systems could be available in...vol. 28, no. 5, pp. 339–350, 2002. [4] H. Simon, T. Zacharia, and R. Stevens, Modeling and Sim- ulation at the Exascale for Energy and the Environment

Family Interaction Patterns, Career Planning Attitudes, and Vocational Identity of High School Adolescents

ERIC Educational Resources Information Center

Hargrove, Byron K.; Inman, Arpana G.; Crane, Randy L.

2005-01-01

The purpose of the current study was to examine how perceptions of family interaction patterns as defined along three dimensions of family environment (quality of family relationships, family goal-orientations, and degree of organization and control within the family system) predict vocational identity and career planning attitudes among male and…

Metabolic scaling and biodiversity of forests

NASA Astrophysics Data System (ADS)

Banavar, Jayanth

Forests are biologically diverse and play a critical role in the dynamics of earth-climate systems. A forest is a tremendously complex system comprising co-existing rooted trees of many species and many sizes and utilizing resources from the environment. The trees interact with each other and with their environment and the interactions are not precisely known. Using scaling ideas, we will present a theoretical framework for understanding the role of geometry in determining the metabolic rate of a tree and of a forest. The quantification of tropical tree biodiversity and their abundances is still an open and challenging problem. Using a global-scale compilation, we will present a method that allows one to predict, from local censuses, the biodiversity and patterns of species abundance at the whole forest scale. The method allows one to quantify the minimum percentage cover of the forest that should be sampled in order to have a precise prediction of the estimates of biodiversity and species abundances. Collaborators: Amos Maritan, Tommaso Anfodillo, Sandro Azaele, Marco Favretti, Marco Formentin, Jacopo Grilli, Samir Suweis, Anna Tovo, Igor Volkov.

Trajectory planning and optimal tracking for an industrial mobile robot

NASA Astrophysics Data System (ADS)

Hu, Huosheng; Brady, J. Michael; Probert, Penelope J.

1994-02-01

This paper introduces a unified approach to trajectory planning and tracking for an industrial mobile robot subject to non-holonomic constraints. We show (1) how a smooth trajectory is generated that takes into account the constraints from the dynamic environment and the robot kinematics; and (2) how a general predictive controller works to provide optimal tracking capability for nonlinear systems. The tracking performance of the proposed guidance system is analyzed by simulation.

Literature survey for suppression of scattered light in large space telescopes

NASA Technical Reports Server (NTRS)

Tifft, W. G.; Fannin, B. B.

1973-01-01

A literature survey is presented of articles dealing with all aspects of predicting, measuring, and controlling unwanted scattered (stray) light. The survey is divided into four broad classifications: (1) existing baffle/telescope designs; (2) computer programs for the analysis/design of light suppression systems; (3) the mechanism, measurement, and control of light scattering; and (4) the advantages and problems introduced by the space environment for the operation of diffraction-limited optical systems.

Analysis of electromagnetic interference from power system processing and transmission components for Space Station Freedom

NASA Technical Reports Server (NTRS)

Barber, Peter W.; Demerdash, Nabeel A. O.; Hurysz, B.; Luo, Z.; Denny, Hugh W.; Millard, David P.; Herkert, R.; Wang, R.

1992-01-01

The goal of this research project was to analyze the potential effects of electromagnetic interference (EMI) originating from power system processing and transmission components for Space Station Freedom. The approach consists of four steps: (1) developing analytical tools (models and computer programs); (2) conducting parameterization (what if?) studies; (3) predicting the global space station EMI environment; and (4) providing a basis for modification of EMI standards.

A Systems Engineering Survey of Artificial Intelligence and Smart Sensor Networks in a Network-Centric Environment

DTIC Science & Technology

2009-09-01

problems, to better model the problem solving of computer systems. This research brought about the intertwining of AI and cognitive psychology . Much of...where symbol sequences are sequential intelligent states of the network, and must be classified as normal, abnormal , or unknown. These symbols...is associated with abnormal behavior; and abcbc is associated with unknown behavior, as it fits no known behavior. Predicted outcomes from

An Operational Computational Terminal Area PBL Prediction System

NASA Technical Reports Server (NTRS)

Lin, Yuh-Lang; Kaplan, Michael L.; Weglarz, Ronald P.; Hamilton, David W.

1997-01-01

There are two fundamental goals of this research project. The first and primary goal is to develop a prognostic system which could satisfy the operational weather prediction requirements of the meteorological subsystem within the Aircraft Vortex Spacing System (AVOSS). The secondary goal is to perform indepth diagnostic analyses of the meteorological conditions affecting the Memphis field experiment held during August 1995. These two goals are interdependent because a thorough understanding of the atmospheric dynamical processes which produced the unique meteorology during the Memphis deployment will help us design a prognostic system for the planetary boundary layer (PBL) which could be utilized to support the meteorological subsystem within AVOSS. The secondary goal occupied much of the first year of the research project. This involved extensive data acquisition and indepth analyses of a spectrum of atmospheric observational data sets. Concerning the primary goal, the first part of the four-stage prognostic system in support of AVOSS entitled: Terminal Area PBL Prediction System (TAPPS) was also formulated and tested in a research environment during 1996. We describe this system, and the three stages which are planned to follow. This first part of a software system designed to meet the primary goal of this research project is relatively inexpensive to implement and run operationally.

Real-Time Safety Monitoring and Prediction for the National Airspace System

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil

2016-01-01

As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have both an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecasts, predicted health of assets in the airspace, and so on. To this end, we have developed a Real-Time Safety Monitoring (RTSM) that first, estimates the state of the NAS using the dynamic models. Then, given the state estimate and a probability distribution of future inputs to the NAS, the framework predicts the evolution of the NAS, i.e., the future state, and analyzes these future states to predict the occurrence of unsafe events. The entire probability distribution of airspace safety metrics is computed, not just point estimates, without significant assumptions regarding the distribution type and or parameters. We demonstrate our overall approach by predicting the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress.

Fake Plate Vehicle Auditing Based on Composite Constraints in Internet of Things Environment

NASA Astrophysics Data System (ADS)

Li, Shasha; Xiangji Huang, Jimmy; Tohti, Turdi

2018-03-01

Accordance to the real application demands, this paper proposes a fake plate vehicle auditing method based on composite constrains strategy, a corresponding simulated IOT (internet of things) environment was created and uses liner matrix, Base64 encryption and grid monitoring technology and puts forward a real-time detecting algorithm for fake plate vehicles. The developed real system not only shows the superiority on its speed, detection accuracy and visualization, it also be good at realizing the vehicle’s real-time position and predicting the possible traveling trajectory.

In vitro simulation of pathological bone conditions to predict clinical outcome of bone tissue engineered materials

NASA Astrophysics Data System (ADS)

Nguyen, Duong Thuy Thi

According to the Centers for Disease Control, the geriatric population of ≥65 years of age will increase to 51.5 million in 2020; 40% of white women and 13% of white men will be at risk for fragility fractures or fractures sustained under normal stress and loading conditions due to bone disease, leading to hospitalization and surgical treatment. Fracture management strategies can be divided into pharmaceutical therapy, surgical intervention, and tissue regeneration for fracture prevention, fracture stabilization, and fracture site regeneration, respectively. However, these strategies fail to accommodate the pathological nature of fragility fractures, leading to unwanted side effects, implant failures, and non-unions. Compromised innate bone healing reactions of patients with bone diseases are exacerbated with protective bone therapy. Once these patients sustain a fracture, bone healing is a challenge, especially when fracture stabilization is unsuccessful. Traditional stabilizing screw and plate systems were designed with emphasis on bone mechanics rather than biology. Bone grafts are often used with fixation devices to provide skeletal continuity at the fracture gap. Current bone grafts include autologous bone tissue and donor bone tissue; however, the quality and quantity demanded by fragility fractures sustained by high-risk geriatric patients and patients with bone diseases are not met. Consequently, bone tissue engineering strategies are advancing towards functionalized bone substitutes to provide fracture reconstruction while effectively mediating bone healing in normal and diseased fracture environments. In order to target fragility fractures, fracture management strategies should be tailored to allow bone regeneration and fracture stabilization with bioactive bone substitutes designed for the pathological environment. The clinical outcome of these materials must be predictable within various disease environments. Initial development of a targeted treatment strategy should focus on simulating, in vitro, a physiological bone environment to predict clinical effectiveness of engineered bone and understand cellular responses due to the proposed agents and bioactive scaffolds. An in vitro test system can be the necessary catalyst to reduce implant failures and non-unions in fragility fractures.

Merging metagenomics and geochemistry reveals environmental controls on biological diversity and evolution.

PubMed

Alsop, Eric B; Boyd, Eric S; Raymond, Jason

2014-05-28

The metabolic strategies employed by microbes inhabiting natural systems are, in large part, dictated by the physical and geochemical properties of the environment. This study sheds light onto the complex relationship between biology and environmental geochemistry using forty-three metagenomes collected from geochemically diverse and globally distributed natural systems. It is widely hypothesized that many uncommonly measured geochemical parameters affect community dynamics and this study leverages the development and application of multidimensional biogeochemical metrics to study correlations between geochemistry and microbial ecology. Analysis techniques such as a Markov cluster-based measure of the evolutionary distance between whole communities and a principal component analysis (PCA) of the geochemical gradients between environments allows for the determination of correlations between microbial community dynamics and environmental geochemistry and provides insight into which geochemical parameters most strongly influence microbial biodiversity. By progressively building from samples taken along well defined geochemical gradients to samples widely dispersed in geochemical space this study reveals strong links between the extent of taxonomic and functional diversification of resident communities and environmental geochemistry and reveals temperature and pH as the primary factors that have shaped the evolution of these communities. Moreover, the inclusion of extensive geochemical data into analyses reveals new links between geochemical parameters (e.g. oxygen and trace element availability) and the distribution and taxonomic diversification of communities at the functional level. Further, an overall geochemical gradient (from multivariate analyses) between natural systems provides one of the most complete predictions of microbial taxonomic and functional composition. Clustering based on the frequency in which orthologous proteins occur among metagenomes facilitated accurate prediction of the ordering of community functional composition along geochemical gradients, despite a lack of geochemical input. The consistency in the results obtained from the application of Markov clustering and multivariate methods to distinct natural systems underscore their utility in predicting the functional potential of microbial communities within a natural system based on system geochemistry alone, allowing geochemical measurements to be used to predict purely biological metrics such as microbial community composition and metabolism.

Towards a National Hydrological Forecasting system for Canada : Lessons Learned from the Great Lakes and St. Lawrence Prediction System

NASA Astrophysics Data System (ADS)

Fortin, V.; Durnford, D.; Gaborit, E.; Davison, B.; Dimitrijevic, M.; Matte, P.

2016-12-01

Environment and Climate Change Canada has recently deployed a water cycle prediction system for the Great Lakes and St. Lawrence River. The model domain includes both the Canadian and US portions of the watershed. It provides 84-h forecasts of weather elements, lake level, lake ice cover and surface currents based on two-way coupling of the GEM numerical weather prediction (NWP) model with the NEMO ocean model. Streamflow of all the major tributaries of the Great Lakes and St. Lawrence River are estimated by the WATROUTE routing model, which routes the surface runoff forecasted by GEM's land-surface scheme and assimilates streamflow observations where available. Streamflow forecasts are updated twice daily and are disseminated through an OGC compliant web map service (WMS) and a web feature service (WFS). In this presentation, in addition to describing the system and documenting its forecast skill, we show how it is being used by clients for various environmental prediction applications. We then discuss the importance of two-way coupling, land-surface and hillslope modelling and the impact of horizontal resolution on hydrological prediction skill. In the second portion of the talk, we discuss plans for implementing a similar system at the national scale, using what we have learned in the Great Lakes and St. Lawrence watershed. Early results obtained for the headwaters of the Saskatchewan River as well as for the whole Nelson-Churchill watershed are presented.

An investigation of two phase flow pressure drops in a reduced acceleration environment

NASA Astrophysics Data System (ADS)

Wheeler, Montgomery W.; Best, Frederick R.; Reinarts, Thomas R.

1993-01-01

Thermal systems for space applications based on two phase flow have several advantages over single phase systems. Two phase thermal energy management and dynamic power conversion system advantages include the capability of achieving high specific power levels. Before two phase systems for space applications can be designed effectively, knowledge of the flow behavior in a reduced acceleration environment is necessary. To meet these needs, two phase flow experiments were conducted aboard the National Aeronautic and Space Administration's KC-135 using R12 as the working fluid. Annular flow two phase pressure drops were measured through 10.41-mm ID 1.251-m long glass tubing during periods with acceleration levels in the range ±0.05 G. The experiments were conducted with emphasis on achieving data with a high level of accuracy. The reduced acceleration annular flow pressure drops were compred with pressure drops measured in a 1-G environment for similar flow conditions. The reduced acceleration pressure drops were found to be 45% greater than the 1-G pressure drops. In addition, the reduced acceleration annular flow interfacial friction factors were compared with models for vertical up-flow in a 1-G environment. The reduced acceleration interfacial friction factor data was not predicted by the 1-G models.

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

The flow of plasma in the solar terrestrial environment

NASA Technical Reports Server (NTRS)

Schunk, R. W.

1992-01-01

The overall goal of our NASA Theory Program is to study the coupling, time delays, and feedback mechanisms between the various regions of the solar-terrestrial system in a self-consistent, quantitative manner. To accomplish this goal, it will eventually be necessary to have time-dependent macroscopic models of the different regions of the solar-terrestrial system and we are continually working toward this goal. However, our immediate emphasis is on the near-earth plasma environment, including the ionosphere, the plasmasphere, and the polar wind. In this area, we have developed unique global models that allow us to study the coupling between the different regions. Another important aspect of our NASA Theory Program concerns the effect that localized structure has on the macroscopic flow in the ionosphere, plasmasphere, thermosphere, and polar wind. The localized structure can be created by structured magnetospheric inputs (i.e., structured plasma convection, particle precipitation or Birkeland current patterns) or time variations in these inputs due to storms and substorms. Also, some of the plasma flows that we predict with our macroscopic models may be unstable, and another one of our goals is to examine the stability of our predicted flows. Because time-dependent, three-dimensional numerical models of the solar-terrestrial environment generally require extensive computer resources, they are usually based on relatively simple mathematical formulations (i.e., simple MHD or hydrodynamic formulation). Therefore, another long-range goal of our NASA Theory Program is to study the conditions under which various mathematical formulations can be applied to specific solar-terrestrial regions. This may involve a detailed comparison of kinetic, semikinetic, and hydrodynamic predictions for a given polar wind scenario or it may involve the comparison of a small-scale particle-in-cell (PIC) simulation of a plasma expansion event with a similar macroscopic expansion event. The different mathematical formulations have different strengths and weaknesses and a careful comparison of model predictions for similar geophysical situations will provide insight into when the various models can be used with confidence.

Efficient first-principles prediction of solid stability: Towards chemical accuracy

NASA Astrophysics Data System (ADS)

Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia; Chen, Tina; Dacek, Stephen T.; Sarmiento-Pérez, Rafael A.; Marques, Maguel A. L.; Peng, Haowei; Ceder, Gerbrand; Perdew, John P.; Sun, Jianwei

2018-03-01

The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. Here, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for main group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.

Predicting Operator Execution Times Using CogTool

NASA Technical Reports Server (NTRS)

Santiago-Espada, Yamira; Latorella, Kara A.

2013-01-01

Researchers and developers of NextGen systems can use predictive human performance modeling tools as an initial approach to obtain skilled user performance times analytically, before system testing with users. This paper describes the CogTool models for a two pilot crew executing two different types of a datalink clearance acceptance tasks, and on two different simulation platforms. The CogTool time estimates for accepting and executing Required Time of Arrival and Interval Management clearances were compared to empirical data observed in video tapes and registered in simulation files. Results indicate no statistically significant difference between empirical data and the CogTool predictions. A population comparison test found no significant differences between the CogTool estimates and the empirical execution times for any of the four test conditions. We discuss modeling caveats and considerations for applying CogTool to crew performance modeling in advanced cockpit environments.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Heliophysics: The New Science of the Sun-Solar System Connection. Recommended Roadmap for Science and Technology 2005-2035

NASA Technical Reports Server (NTRS)

2005-01-01

This is a Roadmap to understanding the environment of our Earth, from its life-sustaining Sun out past the frontiers of the solar system. A collection of spacecraft now patrols this space, revealing not a placid star and isolated planets, but an immense, dynamic, interconnected system within which our home planet is embedded and through which space explorers must journey. These spacecraft already form a great observatory with which the Heliophysics program can study the Sun, the heliosphere, the Earth, and other planetary environments as elements of a system--one that contains dynamic space weather and evolves in response to solar, planetary, and interstellar variability. NASA continually evolves the Heliophysics Great Observatory by adding new missions and instruments in order to answer the challenging questions confronting us now and in the future as humans explore the solar system. The three heliophysics science objectives: opening the frontier to space environment prediction; understanding the nature of our home in space, and safeguarding the journey of exploration, require sustained research programs that depend on combining new data, theory, analysis, simulation, and modeling. Our program pursues a deeper understanding of the fundamental physical processes that underlie the exotic phenomena of space.

Regulating Cortical Neurodynamics for Past, Present and Future

NASA Astrophysics Data System (ADS)

Liljenström, Hans

2002-09-01

Behaving systems, biological as well as artificial, need to respond quickly and accurately to changes in the environment. The response is dependent on stored memories, and novel situations should be learnt for the guidance of future behavior. A highly nonlinear system dynamics is required in order to cope with a complex and changing environment, and this dynamics should be regulated to match the demands of the current situation, and to predict future behavior. In many cases the dynamics should be regulated to minimize processing time. We use computer simulations of cortical structures in order to investigate how the neurodynamics of these systems can be regulated for optimal performance in an unknown and changing environment. In particular, we study how cortical oscillations can serve to amplify weak signals and sustain an input pattern for more accurate information processing, and how chaotic-like behavior could increase the sensitivity in initial, exploratory states. We mimic regulating mechanisms based on neuromodulators, intrinsic noise levels, and various synchronizing effects. We find optimal noise levels where system performance is maximized, and neuromodulatory strategies for an efficient pattern recognition, where the anticipatory state of the system plays an important role.

Engineered Barrier System: Physical and Chemical Environment

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

P. Dixon

2004-04-26

The conceptual and predictive models documented in this Engineered Barrier System: Physical and Chemical Environment Model report describe the evolution of the physical and chemical conditions within the waste emplacement drifts of the repository. The modeling approaches and model output data will be used in the total system performance assessment (TSPA-LA) to assess the performance of the engineered barrier system and the waste form. These models evaluate the range of potential water compositions within the emplacement drifts, resulting from the interaction of introduced materials and minerals in dust with water seeping into the drifts and with aqueous solutions forming bymore » deliquescence of dust (as influenced by atmospheric conditions), and from thermal-hydrological-chemical (THC) processes in the drift. These models also consider the uncertainty and variability in water chemistry inside the drift and the compositions of introduced materials within the drift. This report develops and documents a set of process- and abstraction-level models that constitute the engineered barrier system: physical and chemical environment model. Where possible, these models use information directly from other process model reports as input, which promotes integration among process models used for total system performance assessment. Specific tasks and activities of modeling the physical and chemical environment are included in the technical work plan ''Technical Work Plan for: In-Drift Geochemistry Modeling'' (BSC 2004 [DIRS 166519]). As described in the technical work plan, the development of this report is coordinated with the development of other engineered barrier system analysis model reports.« less

Overview of Aerothermodynamic Loads Definition Study

NASA Technical Reports Server (NTRS)

Povinelli, L. A.

1985-01-01

The Aerothermodynamic Loads Definition were studied to develop methods to more accurately predict the operating environment in the space shuttle main engine (SSME) components. Development of steady and time-dependent, three-dimensional viscous computer codes and experimental verification and engine diagnostic testing are considered. The steady, nonsteady, and transient operating loads are defined to accurately predict powerhead life. Improvements in the structural durability of the SSME turbine drive systems depends on the knowledge of the aerothermodynamic behavior of the flow through the preburner, turbine, turnaround duct, gas manifold, and injector post regions.

TSAFE Interface Control Document v 2.0

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Bach, Ralph E.

2013-01-01

This document specifies the data interface for TSAFE, the Tactical Separation-Assured Flight Environment. TSAFE is a research prototype of a software application program for alerting air traffic controllers to imminent conflicts in enroute airspace. It is intended for Air Route Traffic Control Centers ("Centers") in the U.S. National Airspace System. It predicts trajectories for approximately 3 minutes into the future, searches for conflicts, and sends data about predicted conflicts to the client, which uses the data to alert an air traffic controller of conflicts. TSAFE itself does not provide a graphical user interface.

Yield performance and stability of CMS-based triticale hybrids.

PubMed

Mühleisen, Jonathan; Piepho, Hans-Peter; Maurer, Hans Peter; Reif, Jochen Christoph

2015-02-01

CMS-based triticale hybrids showed only marginal midparent heterosis for grain yield and lower dynamic yield stability compared to inbred lines. Hybrids of triticale (×Triticosecale Wittmack) are expected to possess outstanding yield performance and increased dynamic yield stability. The objectives of the present study were to (1) examine the optimum choice of the biometrical model to compare yield stability of hybrids versus lines, (2) investigate whether hybrids exhibit a more pronounced grain yield performance and yield stability, and (3) study optimal strategies to predict yield stability of hybrids. Thirteen female and seven male parental lines and their 91 factorial hybrids as well as 30 commercial lines were evaluated for grain yield in up to 20 environments. Hybrids were produced using a cytoplasmic male sterility (CMS)-inducing cytoplasm that originated from Triticumtimopheevii Zhuk. We found that the choice of the biometrical model can cause contrasting results and concluded that a group-by-environment interaction term should be added to the model when estimating stability variance of hybrids and lines. midparent heterosis for grain yield was on average 3 % with a range from -15.0 to 11.5 %. No hybrid outperformed the best inbred line. Hybrids had, on average, lower dynamic yield stability compared to the inbred lines. Grain yield performance of hybrids could be predicted based on midparent values and general combining ability (GCA)-predicted values. In contrast, stability variance of hybrids could be predicted only based on GCA-predicted values. We speculated that negative effects of the used CMS cytoplasm might be the reason for the low performance and yield stability of the hybrids. For this purpose a detailed study on the reasons for the drawback of the currently existing CMS system in triticale is urgently required comprising also the search of potentially alternative hybridization systems.

A feasibility study on the predictive emission monitoring system applied to the Hsinta power plant of Taiwan Power Company.

PubMed

Chien, T W; Chu, H; Hsu, W C; Tseng, T K; Hsu, C H; Chen, K Y

2003-08-01

The continuous emission monitoring system (CEMS) can monitor flue gas emissions continuously and instantaneously. However, it has the disadvantages of enormous cost, easily producing errors in sampling periods of bad weather, lagging response in variable ambient environments, and missing data in daily zero and span tests and maintenance. The concept of a predictive emission monitoring system (PEMS) is to use the operating parameters of combustion equipment through thermodynamic or statistical methods to construct a mathematic model that can predict emissions by a computer program. The goal of this study is to set up a PEMS in a gas-fired combined cycle power generation unit at the Hsinta station of Taiwan Power Co. The emissions to be monitored include nitrogen oxides (NOx) and oxygen (O2) in flue gas. The major variables of the predictive model were determined based on the combustion theory. The data of these variables then were analyzed to establish a regression model. From the regression results, the influences of these variables are discussed and the predicted values are compared with the CEMS data for accuracy. In addition, according to the cost information, the capital and operation and maintenance costs for a PEMS can be much lower than those for a CEMS.

The Neighborhood Energy Balance Equation: Does Neighborhood Food Retail Environment + Physical Activity Environment = Obesity? The CARDIA Study

PubMed Central

Boone-Heinonen, Janne; Diez-Roux, Ana V.; Goff, David C.; Loria, Catherine M.; Kiefe, Catarina I.; Popkin, Barry M.; Gordon-Larsen, Penny

2013-01-01

Background Recent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA) environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI) throughout early adulthood. Methods and Findings We used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study [n=4,092; Year 7 (24-42 years, 1992-1993) followed over 5 exams through Year 25 (2010-2011); 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population) and neighborhood development intensity (a composite density score). We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25th to 75th percentile) predicted inter-exam reduction in BMI of 0.09 kg/m2 [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m2 in men, with variation across other neighborhood features [estimate (95% CI) range: -0.14 (-0.29, 0.01) to -0.22 (-0.37, -0.08)]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m2 in men [estimate (95% CI) range: -0.23 (-0.39, -0.06) to -0.31 (-0.47, -0.15)] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI. Conclusions Findings suggest that improvements in neighborhood food retail or PA environments may accumulate to reduce BMI, but some neighborhood changes may be less beneficial to women. PMID:24386458

Overview of SLS Aeroacoustic Environment Development

NASA Technical Reports Server (NTRS)

Steva, Thomas; Herron, Andrew

2017-01-01

The Space Launch System (SLS) ascent aeroacoustic environments provide the externally driven noise levels predicted for vehicle ascent during transonic and supersonic flight, and serve as an important input for component and secondary structure vibroacoustic design criteria. This aerodynamically induced noise is predominantly generated by unsteady flow within the local boundary layer due to free stream interaction with the outer mold line (OML). Additional sources are shear flow interactions, shocks, protuberance flows, and wake flows. This presentation provides an overview of the aeroacoustics discipline along with the SLS environment development process, including wind tunnel testing and general data reduction methods. The state of the discipline is also presented with a summary of aeroacoustic measurement and computational techniques currently on the horizon.

Coating Life Prediction

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Real-time Upstream Monitoring System: Using ACE Data to Predict the Arrival of Interplanetary Shocks

NASA Astrophysics Data System (ADS)

Donegan, M. M.; Wagstaff, K. L.; Ho, G. C.; Vandegriff, J.

2003-12-01

We have developed an algorithm to predict Earth arrival times for interplanetary (IP) shock events originating at the Sun. Our predictions are generated from real-time data collected by the Electron, Proton, and Alpha Monitor (EPAM) instrument on NASA's Advanced Composition Explorer (ACE) spacecraft. The high intensities of energetic ions that occur prior to and during an IP shock pose a radiation hazard to astronauts as well as to electronics in Earth orbit. The potential to predict such events is based on characteristic signatures in the Energetic Storm Particle (ESP) event ion intensities which are often associated with IP shocks. We have previously reported on the development and implementation of an algorithm to forecast the arrival of ESP events. Historical ion data from ACE/EPAM was used to train an artificial neural network which uses the signature of an approaching event to predict the time remaining until the shock arrives. Tests on the trained network have been encouraging, with an average error of 9.4 hours for predictions made 24 hours in advance, and an reduced average error of 4.9 hours when the shock is 12 hours away. The prediction engine has been integrated into a web-based system that uses real-time ACE/EPAM data provided by the NOAA Space Environment Center (http://sd-www.jhuapl.edu/UPOS/RISP/ index.html.) This system continually processes the latest ACE data, reports whether or not there is an impending shock, and predicts the time remaining until the shock arrival. Our predictions are updated every five minutes and provide significant lead-time, thereby supplying critical information that can be used by mission planners, satellite operations controllers, and scientists. We have continued to refine the prediction capabilities of this system; in addition to forecasting arrival times for shocks, we now provide confidence estimates for those predictions.

Acoustic environments for JPL shuttle payloads based on early flight data

NASA Technical Reports Server (NTRS)

Oconnell, M. R.; Kern, D. L.

1983-01-01

Shuttle payload acoustic environmental predictions for the Jet Propulsion Laboratory's Galileo and Wide Field/Planetary Camera projects have been developed from STS-2 and STS-3 flight data. This evaluation of actual STS flight data resulted in reduced predicted environments for the JPL shuttle payloads. Shuttle payload mean acoustic levels were enveloped. Uncertainty factors were added to the mean envelope to provide confidence in the predicted environment.

A Dynamic Navigation Model for Unmanned Aircraft Systems and an Application to Autonomous Front-On Environmental Sensing and Photography Using Low-Cost Sensor Systems.

PubMed

Cooper, Andrew James; Redman, Chelsea Anne; Stoneham, David Mark; Gonzalez, Luis Felipe; Etse, Victor Kwesi

2015-08-28

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.

A Dynamic Navigation Model for Unmanned Aircraft Systems and an Application to Autonomous Front-On Environmental Sensing and Photography Using Low-Cost Sensor Systems

PubMed Central

Cooper, Andrew James; Redman, Chelsea Anne; Stoneham, David Mark; Gonzalez, Luis Felipe; Etse, Victor Kwesi

2015-01-01

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement. PMID:26343680

Predictive monitoring and diagnosis of periodic air pollution in a subway station.

PubMed

Kim, YongSu; Kim, MinJung; Lim, JungJin; Kim, Jeong Tai; Yoo, ChangKyoo

2010-11-15

The purpose of this study was to develop a predictive monitoring and diagnosis system for the air pollutants in a subway system using a lifting technique with a multiway principal component analysis (MPCA) which monitors the periodic patterns of the air pollutants and diagnoses the sources of the contamination. The basic purpose of this lifting technique was to capture the multivariate and periodic characteristics of all of the indoor air samples collected during each day. These characteristics could then be used to improve the handling of strong periodic fluctuations in the air quality environment in subway systems and will allow important changes in the indoor air quality to be quickly detected. The predictive monitoring approach was applied to a real indoor air quality dataset collected by telemonitoring systems (TMS) that indicated some periodic variations in the air pollutants and multivariate relationships between the measured variables. Two monitoring models--global and seasonal--were developed to study climate change in Korea. The proposed predictive monitoring method using the lifted model resulted in fewer false alarms and missed faults due to non-stationary behavior than that were experienced with the conventional methods. This method could be used to identify the contributions of various pollution sources. Copyright © 2010 Elsevier B.V. All rights reserved.

A direct broadcast satellite-audio experiment

NASA Technical Reports Server (NTRS)

Vaisnys, Arvydas; Abbe, Brian; Motamedi, Masoud

1992-01-01

System studies have been carried out over the past three years at the Jet Propulsion Laboratory (JPL) on digital audio broadcasting (DAB) via satellite. The thrust of the work to date has been on designing power and bandwidth efficient systems capable of providing reliable service to fixed, mobile, and portable radios. It is very difficult to predict performance in an environment which produces random periods of signal blockage, such as encountered in mobile reception where a vehicle can quickly move from one type of terrain to another. For this reason, some signal blockage mitigation techniques were built into an experimental DAB system and a satellite experiment was conducted to obtain both qualitative and quantitative measures of performance in a range of reception environments. This paper presents results from the experiment and some conclusions on the effectiveness of these blockage mitigation techniques.

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

PubMed

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

2015-11-01

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

Fatigue life prediction of bonded primary joints

NASA Technical Reports Server (NTRS)

Knauss, J. F.

1979-01-01

The validation of a proposed fatigue life prediction methodology was sought through the use of aluminum butt and scarf joint and graphite/epoxy butt joint specimens in a constant amplitude fatigue environment. The structural properties of the HYSOL 9313 adhesive system were obtained by mechanical test of molded heat adhesive specimens. Aluminum contoured double cantilever beam specimens were used to generate crack velocity versus stress intensity factor data. The specific objectives were: (1) to ascertain the feasibility of predicting fatigue failure of an adhesive in a primary bonded composite structure by incorporating linear elastic crack growth behavior; and (2) to ascertain if acoustic emission and/or compliance measurement techniques can be used to detect flaws.

Cyberinfrastructure to support Real-time, End-to-End, High Resolution, Localized Forecasting

NASA Astrophysics Data System (ADS)

Ramamurthy, M. K.; Lindholm, D.; Baltzer, T.; Domenico, B.

2004-12-01

From natural disasters such as flooding and forest fires to man-made disasters such as toxic gas releases, the impact of weather-influenced severe events on society can be profound. Understanding, predicting, and mitigating such local, mesoscale events calls for a cyberinfrastructure to integrate multidisciplinary data, tools, and services as well as the capability to generate and use high resolution data (such as wind and precipitation) from localized models. The need for such end to end systems -- including data collection, distribution, integration, assimilation, regionalized mesoscale modeling, analysis, and visualization -- has been realized to some extent in many academic and quasi-operational environments, especially for atmospheric sciences data. However, many challenges still remain in the integration and synthesis of data from multiple sources and the development of interoperable data systems and services across those disciplines. Over the years, the Unidata Program Center has developed several tools that have either directly or indirectly facilitated these local modeling activities. For example, the community is using Unidata technologies such as the Internet Data Distribution (IDD) system, Local Data Manger (LDM), decoders, netCDF libraries, Thematic Realtime Environmental Distributed Data Services (THREDDS), and the Integrated Data Viewer (IDV) in their real-time prediction efforts. In essence, these technologies for data reception and processing, local and remote access, cataloging, and analysis and visualization coupled with technologies from others in the community are becoming the foundation of a cyberinfrastructure to support an end-to-end regional forecasting system. To build on these capabilities, the Unidata Program Center is pleased to be a significant contributor to the Linked Environments for Atmospheric Discovery (LEAD) project, a NSF-funded multi-institutional large Information Technology Research effort. The goal of LEAD is to create an integrated and scalable framework for identifying, accessing, preparing, assimilating, predicting, managing, analyzing, mining, and visualizing a broad array of meteorological data and model output, independent of format and physical location. To that end, LEAD will create a series of interconnected, heterogeneous Grid environments to provide a complete framework for mesoscale research, including a set of integrated Grid and Web Services. This talk will focus on the transition from today's end-to-end systems into the types of systems that the LEAD project envisions and the multidisciplinary research problems they will enable.

Solar-Terrestrial Predictions

NASA Astrophysics Data System (ADS)

Thompson, R. J.; Cole, D. G.; Wilkinson, P. J.; Shea, M. A.; Smart, D.

1990-11-01

Volume 1: The following subject areas are covered: the magnetosphere environment; forecasting magnetically quiet periods; radiation hazards to human in deep space (a summary with special reference to large solar particle events); solar proton events (review and status); problems of the physics of solar-terrestrial interactions; prediction of solar proton fluxes from x-ray signatures; rhythms in solar activity and the prediction of episodes of large flares; the role of persistence in the 24-hour flare forecast; on the relationship between the observed sunspot number and the number of solar flares; the latitudinal distribution of coronal holes and geomagnetic storms due to coronal holes; and the signatures of flares in the interplanetary medium at 1 AU. Volume 2: The following subject areas were covered: a probability forecast for geomagnetic activity; cost recovery in solar-terrestrial predictions; magnetospheric specification and forecasting models; a geomagnetic forecast and monitoring system for power system operation; some aspects of predicting magnetospheric storms; some similarities in ionospheric disturbance characteristics in equatorial, mid-latitude, and sub-auroral regions; ionospheric support for low-VHF radio transmission; a new approach to prediction of ionospheric storms; a comparison of the total electron content of the ionosphere around L=4 at low sunspot numbers with the IRI model; the French ionospheric radio propagation predictions; behavior of the F2 layer at mid-latitudes; and the design of modern ionosondes.

Compassion Fatigue and the Healthy Work Environment.

PubMed

Kelly, Lesly; Todd, Michael

2017-01-01

Burnout is a concern for critical care nurses in high-intensity environments. Studies have highlighted the importance of a healthy work environment in promoting optimal nurse and patient outcomes, but research examining the relationship between a healthy work environment and burnout is limited. To examine how healthy work environment components relate to compassion fatigue (eg, burnout, secondary trauma) and compassion satisfaction. Nurses (n = 105) in 3 intensive care units at an academic medical center completed a survey including the Professional Quality of Life and the American Association of Critical-Care Nurses' Healthy Work Environment standards. Regression models using each Healthy Work Environment component to predict each outcome, adjusting for background variables, showed that the 5 Healthy Work Environment components predicted burnout and that meaningful recognition and authentic leadership predicted compassion satisfaction. Findings on associations between healthy work environment standards and burnout suggest the potential importance of implementing the American Association of Critical-Care Nurses' Healthy Work Environment standards as a mechanism for decreasing burnout. ©2017 American Association of Critical-Care Nurses.

Web-Based Integrated Research Environment for Aerodynamic Analyses and Design

NASA Astrophysics Data System (ADS)

Ahn, Jae Wan; Kim, Jin-Ho; Kim, Chongam; Cho, Jung-Hyun; Hur, Cinyoung; Kim, Yoonhee; Kang, Sang-Hyun; Kim, Byungsoo; Moon, Jong Bae; Cho, Kum Won

e-AIRS[1,2], an abbreviation of ‘e-Science Aerospace Integrated Research System,' is a virtual organization designed to support aerodynamic flow analyses in aerospace engineering using the e-Science environment. As the first step toward a virtual aerospace engineering organization, e-AIRS intends to give a full support of aerodynamic research process. Currently, e-AIRS can handle both the computational and experimental aerodynamic research on the e-Science infrastructure. In detail, users can conduct a full CFD (Computational Fluid Dynamics) research process, request wind tunnel experiment, perform comparative analysis between computational prediction and experimental measurement, and finally, collaborate with other researchers using the web portal. The present paper describes those services and the internal architecture of the e-AIRS system.

Learning Activity Models for Multiple Agents in a Smart Space

NASA Astrophysics Data System (ADS)

Crandall, Aaron; Cook, Diane J.

With the introduction of more complex intelligent environment systems, the possibilities for customizing system behavior have increased dramatically. Significant headway has been made in tracking individuals through spaces using wireless devices [1, 18, 26] and in recognizing activities within the space based on video data (see chapter by Brubaker et al. and [6, 8, 23]), motion sensor data [9, 25], wearable sensors [13] or other sources of information [14, 15, 22]. However, much of the theory and most of the algorithms are designed to handle one individual in the space at a time. Resident tracking, activity recognition, event prediction, and behavior automation becomes significantly more difficult for multi-agent situations, when there are multiple residents in the environment.

Space Environments and Effects Concept: Transitioning Research to Operations and Applications

NASA Technical Reports Server (NTRS)

Edwards, David L.; Spann, James; Burns, Howard D.; Schumacher, Dan

2012-01-01

The National Aeronautics and Space Administration (NASA) is embarking on a course to expand human presence beyond Low Earth Orbit (LEO) while expanding its mission to explore the solar system. Destinations such as Near Earth Asteroids (NEA), Mars and its moons, and the outer planets are but a few of the mission targets. NASA has established numerous offices specializing in specific space environments disciplines that will serve to enable these missions. To complement these existing discipline offices, a concept focusing on the development of space environment and effects application is presented. This includes space climate, space weather, and natural and induced space environments. This space environment and effects application is composed of 4 topic areas; characterization and modeling, engineering effects, prediction and operation, and mitigation and avoidance. These topic areas are briefly described below. Characterization and modeling of space environments will primarily focus on utilization during Program mission concept, planning, and design phases. Engineering effects includes materials testing and flight experiments producing data to be used in mission planning and design phases. Prediction and operation pulls data from existing sources into decision-making tools and empirical data sets to be used during the operational phase of a mission. Mitigation and avoidance will develop techniques and strategies used in the design and operations phases of the mission. The goal of this space environment and effects application is to develop decision-making tools and engineering products to support the mission phases of mission concept through operations by focusing on transitioning research to operations. Products generated by this space environments and effects application are suitable for use in anomaly investigations. This paper will outline the four topic areas, describe the need, and discuss an organizational structure for this space environments and effects application.

Coupled lagged ensemble weather- and river runoff prediction in complex Alpine terrain

NASA Astrophysics Data System (ADS)

Smiatek, Gerhard; Kunstmann, Harald; Werhahn, Johannes

2013-04-01

It is still a challenge to predict fast reacting streamflow precipitation response in Alpine terrain. Civil protection measures require flood prediction in 24 - 48 lead time. This holds particularly true for the Ammer River region which was affected by century floods in 1999, 2003 and 2005. Since 2005 a coupled NWP/Hydrology model system is operated in simulating and predicting the Ammer River discharges. The Ammer River catchment is located in the Bavarian Ammergau Alps and alpine forelands, Germany. With elevations reaching 2185 m and annual mean precipitation between 1100 and 2000 mm it represents very demanding test ground for a river runoff prediction system. The one way coupled system utilizes a lagged ensemble prediction system (EPS) taking into account combination of recent and previous NWP forecasts. The major components of the system are the MM5 NWP model run at 3.5 km resolution and initialized twice a day, the hydrology model WaSiM-ETH run at 100 m resolution and Perl object environment (POE) implementing the networking and the system operation. Results obtained in the years 2005-2012 reveal that river runoff simulations depict already high correlation (NSC in range 0.53 and 0.95) with observed runoff in retrospective runs with monitored meteorology data, but suffer from errors in quantitative precipitation forecast (QPF) from the employed numerical weather prediction model. We evaluate the NWP model accuracy, especially the precipitation intensity, frequency and location and put a focus on the performance gain of bias adjustment procedures. We show how this enhanced QFP data help to reduce the uncertainty in the discharge prediction. In addition to the HND (Hochwassernachrichtendienst, Bayern) observations TERENO Longterm Observatory hydrometeorological observation data are available since 2011. They are used to evaluate the NWP performance and setup of a bias correction procedure based on ensemble postprocessing applying Bayesian (BMA) model averaging. We first present briefly the technical setup of the operational coupled lagged NWP/Hydrology model system and then focus on the evaluation of the NWP model, the BMA enhanced QPF and its application within the Ammer simulation system in the period 2011 - 2012

SHIELDS Final Technical Report

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

Jordanova, Vania Koleva

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 new capability was developed at Los Alamos National Laboratory (LANL) to understand, model, and predict Space Hazards Induced near Earth by Large Dynamic Storms, the SHIELDS framework. This framework simulates 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 micro-scale. In addition to using physics-based models (like RAM-SCB, BATS-R-US, and iPIC3D), new data assimilation techniques employing data frommore » LANL instruments on the Van Allen Probes and geosynchronous satellites were developed. An order of magnitude improvement in the accuracy in the simulation of the spacecraft surface charging environment was thus obtained. 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 and to evaluate anomalies' relation to SCE dynamics. Such diagnostics is critically important when performing forensic analyses of space-system failures.« less

Computational Pollutant Environment Assessment from Propulsion-System Testing

NASA Technical Reports Server (NTRS)

Wang, Ten-See; McConnaughey, Paul; Chen, Yen-Sen; Warsi, Saif

1996-01-01

An asymptotic plume growth method based on a time-accurate three-dimensional computational fluid dynamics formulation has been developed to assess the exhaust-plume pollutant environment from a simulated RD-170 engine hot-fire test on the F1 Test Stand at Marshall Space Flight Center. Researchers have long known that rocket-engine hot firing has the potential for forming thermal nitric oxides, as well as producing carbon monoxide when hydrocarbon fuels are used. Because of the complex physics involved, most attempts to predict the pollutant emissions from ground-based engine testing have used simplified methods, which may grossly underpredict and/or overpredict the pollutant formations in a test environment. The objective of this work has been to develop a computational fluid dynamics-based methodology that replicates the underlying test-stand flow physics to accurately and efficiently assess pollutant emissions from ground-based rocket-engine testing. A nominal RD-170 engine hot-fire test was computed, and pertinent test-stand flow physics was captured. The predicted total emission rates compared reasonably well with those of the existing hydrocarbon engine hot-firing test data.

Extracting More Information from Passive Optical Tracking Observations for Reliable Orbit Element Generation

NASA Astrophysics Data System (ADS)

Bennett, J.; Gehly, S.

2016-09-01

This paper presents results from a preliminary method for extracting more orbital information from low rate passive optical tracking data. An improvement in the accuracy of the observation data yields more accurate and reliable orbital elements. A comparison between the orbit propagations from the orbital element generated using the new data processing method is compared with the one generated from the raw observation data for several objects. Optical tracking data collected by EOS Space Systems, located on Mount Stromlo, Australia, is fitted to provide a new orbital element. The element accuracy is determined from a comparison between the predicted orbit and subsequent tracking data or reference orbit if available. The new method is shown to result in a better orbit prediction which has important implications in conjunction assessments and the Space Environment Research Centre space object catalogue. The focus is on obtaining reliable orbital solutions from sparse data. This work forms part of the collaborative effort of the Space Environment Management Cooperative Research Centre which is developing new technologies and strategies to preserve the space environment (www.serc.org.au).

Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

PubMed

Abbasi, Maryam; El Hanandeh, Ali

2016-10-01

Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Communication by Fire (and Smoke) Signals in the Kingdom of Judah

NASA Technical Reports Server (NTRS)

Borowski, Oded; Howell, Burgess F.; Sever, Thomas L.

1998-01-01

This paper examines the use of ancient fire and smoke signals for communication in the Kingdom of Judah. Historical and biblical references are cited that discuss this communication system. The current physical and political landscape of Israel precludes testing of hypotheses using traditional techniques. The use of a GIS is enlisted to overcome these obstacles and predict line-of-sight patterns that are conducive for a fire signal communication system. Final demonstration of this predictive model will incorporate state-of-the-art technology and in-field data acquisition to provide the sufficient accuracy that is required for proof-of-concept. This research will provide insight into the technical capability of the ancient Israelites for communication across a mountainous, desert environment.

Planet Formation

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; DeVincenzi, Donald L. (Technical Monitor)

1998-01-01

An overview of current theories of star and planet formation is presented. These models are based upon observations of the Solar System and of young stars and their environments. They predict that rocky planets should form around most single stars, although it is possible that in some cases such planets are lost to orbital decay within the protoplanetary disk. The frequency of formation of gas giant planets is more difficult to predict theoretically. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant planets begin their growth like terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates.

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

Riensche, Roderick M.; Paulson, Patrick R.; Danielson, Gary R.

We describe a methodology and architecture to support the development of games in a predictive analytics context. These games serve as part of an overall family of systems designed to gather input knowledge, calculate results of complex predictive technical and social models, and explore those results in an engaging fashion. The games provide an environment shaped and driven in part by the outputs of the models, allowing users to exert influence over a limited set of parameters, and displaying the results when those actions cause changes in the underlying model. We have crafted a prototype system in which we aremore » implementing test versions of games driven by models in such a fashion, using a flexible architecture to allow for future continuation and expansion of this work.« less

Crew Launch Vehicle Mobile Launcher Solid Rocket Motor Plume Induced Environment

NASA Technical Reports Server (NTRS)

Vu, Bruce T.; Sulyma, Peter

2008-01-01

The plume-induced environment created by the Ares 1 first stage, five-segment reusable solid rocket motor (RSRMV) will impose high heating rates and impact pressures on Launch Complex 39. The extremes of these environments pose a potential threat to weaken or even cause structural components to fail if insufficiently designed. Therefore the ability to accurately predict these environments is critical to assist in specifying structural design requirements to insure overall structural integrity and flight safety. This paper presents the predicted thermal and pressure environments induced by the launch of the Crew Launch Vehicle (CLV) from Launch Complex (LC) 39. Once the environments are predicted, a follow-on thermal analysis is required to determine the surface temperature response and the degradation rate of the materials. An example of structures responding to the plume-induced environment will be provided.

Distinctive Behaviors of Druggable Proteins in Cellular Networks

PubMed Central

Workman, Paul; Al-Lazikani, Bissan

2015-01-01

The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/. PMID:26699810

Climate change in Australian tropical rainforests: an impending environmental catastrophe.

PubMed

Williams, Stephen E; Bolitho, Elizabeth E; Fox, Samantha

2003-09-22

It is now widely accepted that global climate change is affecting many ecosystems around the globe and that its impact is increasing rapidly. Many studies predict that impacts will consist largely of shifts in latitudinal and altitudinal distributions. However, we demonstrate that the impacts of global climate change in the tropical rainforests of northeastern Australia have the potential to result in many extinctions. We develop bioclimatic models of spatial distribution for the regionally endemic rainforest vertebrates and use these models to predict the effects of climate warming on species distributions. Increasing temperature is predicted to result in significant reduction or complete loss of the core environment of all regionally endemic vertebrates. Extinction rates caused by the complete loss of core environments are likely to be severe, nonlinear, with losses increasing rapidly beyond an increase of 2 degrees C, and compounded by other climate-related impacts. Mountain ecosystems around the world, such as the Australian Wet Tropics bioregion, are very diverse, often with high levels of restricted endemism, and are therefore important areas of biodiversity. The results presented here suggest that these systems are severely threatened by climate change.

Experimental and numerical study of physiological responses in hot environments.

PubMed

Yang, Jie; Weng, Wenguo; Zhang, Baoting

2014-10-01

This paper proposed a multi-node human thermal model to predict human thermal responses in hot environments. The model was extended based on the Tanabe's work by considering the effects of high temperature on heat production, blood flow rate, and heat exchange coefficients. Five healthy men dressed in shorts were exposed in thermal neutral (29 °C) and high temperature (45 °C) environments. The rectal temperatures and skin temperatures of seven human body segments were continuously measured during the experiment. Validation of this model was conducted with experimental data. The results showed that the current model could accurately predict the skin and core temperatures in terms of the tendency and absolute values. In the human body segments expect calf and trunk, the temperature differences between the experimental data and the predicted results in high temperature environment were smaller than those in the thermally neutral environment conditions. The extended model was proved to be capable of predicting accurately human physiological responses in hot environments. Copyright © 2014 Elsevier Ltd. All rights reserved.

A review of toxicity and mechanisms of individual and mixtures of heavy metals in the environment.

PubMed

Wu, Xiangyang; Cobbina, Samuel J; Mao, Guanghua; Xu, Hai; Zhang, Zhen; Yang, Liuqing

2016-05-01

The rational for the study was to review the literature on the toxicity and corresponding mechanisms associated with lead (Pb), mercury (Hg), cadmium (Cd), and arsenic (As), individually and as mixtures, in the environment. Heavy metals are ubiquitous and generally persist in the environment, enabling them to biomagnify in the food chain. Living systems most often interact with a cocktail of heavy metals in the environment. Heavy metal exposure to biological systems may lead to oxidation stress which may induce DNA damage, protein modification, lipid peroxidation, and others. In this review, the major mechanism associated with toxicities of individual metals was the generation of reactive oxygen species (ROS). Additionally, toxicities were expressed through depletion of glutathione and bonding to sulfhydryl groups of proteins. Interestingly, a metal like Pb becomes toxic to organisms through the depletion of antioxidants while Cd indirectly generates ROS by its ability to replace iron and copper. ROS generated through exposure to arsenic were associated with many modes of action, and heavy metal mixtures were found to have varied effects on organisms. Many models based on concentration addition (CA) and independent action (IA) have been introduced to help predict toxicities and mechanisms associated with metal mixtures. An integrated model which combines CA and IA was further proposed for evaluating toxicities of non-interactive mixtures. In cases where there are molecular interactions, the toxicogenomic approach was used to predict toxicities. The high-throughput toxicogenomics combines studies in genetics, genome-scale expression, cell and tissue expression, metabolite profiling, and bioinformatics.

Examining College Students' Social Environment, Normative Beliefs, and Attitudes in Subsequent Initiation of Electronic Nicotine Delivery Systems.

PubMed

Agarwal, Deepti; Loukas, Alexandra; Perry, Cheryl L

2017-11-01

Although use of Electronic Nicotine Delivery Systems (ENDS) is increasingly prevalent among young adults, little is known about predictors of ENDS initiation among this population. We examined the roles of the social environment (i.e., peer ENDS use and household ENDS use), normative beliefs (i.e., social acceptability of ENDS use), and attitudes (i.e., inclination to date someone who uses ENDS) in prospectively predicting initiation of ENDS over a 1-year period among 18- to 29-year-old college students. Participants were 2,110 (18- to 29-year-old) students ( M = 20.27, SD = 2.17) from 24 colleges in Texas who participated in a three-wave online survey, with 6 months between each wave. All participants reported never using ENDS at baseline. A multivariable, multilevel logistic regression model, accounting for clustering of students within colleges, was used to assess if students' social environment, normative beliefs, and attitudes predicted subsequent initiation of ENDS up to 1 year later, adjusting for various sociodemographic factors and number of other tobacco products used. In all, 329 college students (16%) initiated ENDS within 1 year. Results from the logistic regression indicated that college students who were younger (18-24 years old), ever used other tobacco products, indicated a more dense peer network of ENDS users, and had a higher inclination to date someone who uses ENDS had higher odds of initiating ENDS than their peers. Preventing ENDS initiation should be included in college health promotion programs, which should highlight the roles of students' social environment and attitudes regarding ENDS use.

Autonomous Mission Operations for Sensor Webs

NASA Astrophysics Data System (ADS)

Underbrink, A.; Witt, K.; Stanley, J.; Mandl, D.

2008-12-01

We present interim results of a 2005 ROSES AIST project entitled, "Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations", or SWAMO. The goal of the SWAMO project is to shift the control of spacecraft missions from a ground-based, centrally controlled architecture to a collaborative, distributed set of intelligent agents. The network of intelligent agents intends to reduce management requirements by utilizing model-based system prediction and autonomic model/agent collaboration. SWAMO agents are distributed throughout the Sensor Web environment, which may include multiple spacecraft, aircraft, ground systems, and ocean systems, as well as manned operations centers. The agents monitor and manage sensor platforms, Earth sensing systems, and Earth sensing models and processes. The SWAMO agents form a Sensor Web of agents via peer-to-peer coordination. Some of the intelligent agents are mobile and able to traverse between on-orbit and ground-based systems. Other agents in the network are responsible for encapsulating system models to perform prediction of future behavior of the modeled subsystems and components to which they are assigned. The software agents use semantic web technologies to enable improved information sharing among the operational entities of the Sensor Web. The semantics include ontological conceptualizations of the Sensor Web environment, plus conceptualizations of the SWAMO agents themselves. By conceptualizations of the agents, we mean knowledge of their state, operational capabilities, current operational capacities, Web Service search and discovery results, agent collaboration rules, etc. The need for ontological conceptualizations over the agents is to enable autonomous and autonomic operations of the Sensor Web. The SWAMO ontology enables automated decision making and responses to the dynamic Sensor Web environment and to end user science requests. The current ontology is compatible with Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Sensor Model Language (SensorML) concepts and structures. The agents are currently deployed on the U.S. Naval Academy MidSTAR-1 satellite and are actively managing the power subsystem on-orbit without the need for human intervention.

Freezable Radiator Coupon Testing and Full Scale Radiator Design

NASA Technical Reports Server (NTRS)

Lillibridge, Sean T.; Guinn, John; Cognata, Thomas; Navarro, Moses

2009-01-01

Freezable radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the space craft s surroundings and because of different thermal loads during different mission phases. However, freezing and thawing (recovering) a radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. This paper summarizes tests on three test articles that were performed to further empirically quantify the behavior of a simple freezable radiator, and the culmination of those tests into a full scale design. Each test article explored the bounds of freezing and recovery behavior, as well as providing thermo-physical data of the working fluid, a 50-50 mixture of DowFrost HD and water. These results were then used as a tool for developing correlated thermal model in Thermal Desktop which could be used for modeling the behavior of a full scale thermal control system for a lunar mission. The final design of a thermal control system for a lunar mission is also documented in this paper.

Mars Science Laboratory Entry Capsule Aerothermodynamics and Thermal Protection System

NASA Technical Reports Server (NTRS)

Edquist, Karl T.; Hollis, Brian R.; Dyakonov, Artem A.; Laub, Bernard; Wright, Michael J.; Rivellini, Tomasso P.; Slimko, Eric M.; Willcockson, William H.

2007-01-01

The Mars Science Laboratory (MSL) spacecraft is being designed to carry a large rover (greater than 800 kg) to the surface of Mars using a blunt-body entry capsule as the primary decelerator. The spacecraft is being designed for launch in 2009 and arrival at Mars in 2010. The combination of large mass and diameter with non-zero angle-of-attack for MSL will result in unprecedented convective heating environments caused by turbulence prior to peak heating. Navier-Stokes computations predict a large turbulent heating augmentation for which there are no supporting flight data1 and little ground data for validation. Consequently, an extensive experimental program has been established specifically for MSL to understand the level of turbulent augmentation expected in flight. The experimental data support the prediction of turbulent transition and have also uncovered phenomena that cannot be replicated with available computational methods. The result is that the flight aeroheating environments predictions must include larger uncertainties than are typically used for a Mars entry capsule. Finally, the thermal protection system (TPS) being used for MSL has not been flown at the heat flux, pressure, and shear stress combinations expected in flight, so a test program has been established to obtain conditions relevant to flight. This paper summarizes the aerothermodynamic definition analysis and TPS development, focusing on the challenges that are unique to MSL.

ATK Launch Vehicle (ALV-X1) Liftoff Acoustic Environments: Prediction vs. Measurement

NASA Technical Reports Server (NTRS)

Houston, Janice; Counter, Douglas; Kenny, Jeremy; Murphy, John

2009-01-01

The ATK Launch Vehicle (ALV-X1) provided an opportunity to measure liftoff acoustic noise data. NASA Marshall Space Flight Center (MSFC) engineers were interested in the ALV-X1 launch because the First Stage motor and launch pad conditions, including a relativity short deflector ducting, provide a potential analogue to future Ares I launches. This paper presents the measured liftoff acoustics on the vehicle and tower. Those measured results are compared to predictions based upon the method described in NASA SP-8072 "Acoustic Loads Generated by the Propulsion System" and the Vehicle Acoustic Environment Prediction Program (VAEPP) which was developed by MSFC acoustics engineers. One-third octave band sound pressure levels will be presented. This data is useful for the ALV-X1 in validating the pre-launch environments and loads predictions. Additionally, the ALV-X1 liftoff data can be scaled to define liftoff environments for the NASA Constellation program Ares vehicles. Vehicle liftoff noise is caused by the supersonic jet flow interaction with surrounding atmosphere or more simply, jet noise. As the vehicle's First Stage motor is ignited, an acoustic noise field is generated by the exhaust. This noise field persists due to the supersonic jet noise and reflections from the launch pad and tower, then changes as the vehicle begins to liftoff from the launch pad. Depending on launch pad and adjacent tower configurations, the liftoff noise is generally very high near the nozzle exit and decreases rapidly away from the nozzle. The liftoff acoustic time range of interest is typically 0 to 20 seconds after ignition. The exhaust plume thermo-fluid mechanics generates sound at approx.10 Hz to 20 kHz. Liftoff acoustic noise is usually the most severe dynamic environment for a launch vehicle or payload in the mid to high frequency range (approx.50 to 2000 Hz). This noise environment can induce high-level vibrations along the external surfaces of the vehicle and surrounding launch facility structures. The acoustic pressure fluctuations will induce severe vibrations in relatively large lightweight structures. Consequently, there is the potential for failure of the structure or attached electrical components. Due to these potential failures, the liftoff acoustic noise is one of the noise source inputs used to determine the vibro-acoustic qualification environment for a launch vehicle and its components.

Human-robot interaction modeling and simulation of supervisory control and situational awareness during field experimentation with military manned and unmanned ground vehicles

NASA Astrophysics Data System (ADS)

Johnson, Tony; Metcalfe, Jason; Brewster, Benjamin; Manteuffel, Christopher; Jaswa, Matthew; Tierney, Terrance

2010-04-01

The proliferation of intelligent systems in today's military demands increased focus on the optimization of human-robot interactions. Traditional studies in this domain involve large-scale field tests that require humans to operate semiautomated systems under varying conditions within military-relevant scenarios. However, provided that adequate constraints are employed, modeling and simulation can be a cost-effective alternative and supplement. The current presentation discusses a simulation effort that was executed in parallel with a field test with Soldiers operating military vehicles in an environment that represented key elements of the true operational context. In this study, "constructive" human operators were designed to represent average Soldiers executing supervisory control over an intelligent ground system. The constructive Soldiers were simulated performing the same tasks as those performed by real Soldiers during a directly analogous field test. Exercising the models in a high-fidelity virtual environment provided predictive results that represented actual performance in certain aspects, such as situational awareness, but diverged in others. These findings largely reflected the quality of modeling assumptions used to design behaviors and the quality of information available on which to articulate principles of operation. Ultimately, predictive analyses partially supported expectations, with deficiencies explicable via Soldier surveys, experimenter observations, and previously-identified knowledge gaps.

Comparing Language and Literacy Environments in Two Types of Infant-Toddler Child Care Centers

ERIC Educational Resources Information Center

Norris, Deborah J.

2017-01-01

Language development is a significant milestone in the infant/toddler years; vocabulary by 2 years of age is predictive of later school success. It has been recognized within the bioecological systems theoretical framework that language develops as a result of an interplay between characteristics of the child, features of the setting, and…

Advancing Development of Intercultural Competence through Supporting Predictions in Narrative Video

ERIC Educational Resources Information Center

Ogan, Amy; Aleven, Vincent; Jones, Christopher

2009-01-01

Most successes in intelligent tutoring systems have come in well-defined domains like algebra or physics. We investigate how to support students in acquiring ill-defined skills of intercultural competence using an online environment that employs clips of feature films from a target culture. To test the effectiveness of a set of attention-focusing…

Space Evaporator Absorber Radiator (SEAR) for Thermal Storage on Manned Spacecraft

NASA Technical Reports Server (NTRS)

Izenson, Michael G.; Chen, Weibo; Chepko, Ariane; Bue, Grant; Quinn, Gregory

2014-01-01

Future manned exploration spacecraft will need to operate in challenging thermal environments. State-of the- art technology for active thermal control relies on sublimating water ice and venting the vapor overboard in very hot environments. This approach can lead to large loss of water and a significant mass penalty for the spacecraft. This paper describes an innovative thermal control system that uses a Space Evaporator Absorber Radiator (SEAR) to control spacecraft temperatures in highly variable environments without venting water. SEAR uses heat pumping and energy storage by LiCl/water absorption to enable effective cooling during hot periods and regeneration during cool periods. The LiCl absorber technology has the potential to absorb over 800 kJ per kg of system mass, compared to phase change heat sink systems that typically achieve approx. 50 kJ/kg. The optimal system is based on a trade-off between the mass of water saved and extra power needed to regenerate the LiCl absorber. This paper describes analysis models and the predicted performance and optimize the size of the SEAR system, estimated size and mass of key components, and power requirements for regeneration. We also present a concept design for an ISS test package to demonstrate operation of a subscale system in zero gravity.

Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction.

PubMed

Larsen, Peter; Hamada, Yuki; Gilbert, Jack

2012-07-31

Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science. Copyright © 2012 Elsevier B.V. All rights reserved.